Journal of Measurements in Engineering: Table of Contents

Measurement of gravitational constan t G between 30 t steel plate and 5 kg iron ball

Hu, Qinggui — 2026-02-15T00:00:00Z

Journal of Measurements in Engineering, Vol. 14, Issue 2, 2026, p. 424-438.
Qinggui Hu, Xinlong Zhang
In 2008, we proposed the “New Experimental Scheme for Measuring the Gravitational Constant G between Large-Mass Objects”. In 2021, this scheme was implemented, yielding a new value of G: 9.09×10-9 N·m2/kg2. By contrast, the currently internationally recognized value is 6.67259×10-11 N·m2/kg2. The discrepancy between these two values is so significant that it cannot be adequately explained by traditional theories. To address this issue, a permanent experimental platform was established in early June 2023 at the new campus of Neijiang Normal University, enabling a repeat of the experiment. Based on this platform, an additional experimental measurement was conducted, resulting in a new G value of 7.3827302×10-10 N·m2/kg2. Subsequently, we analyzed the causes of the significant difference between the latest measured value and the first one. And we also performed a comparative analysis between the new experiment and the traditional Cavendish torsion balance experiment. The results demonstrated that the new experimental system features fewer error sources and higher stability. These new G values suggest that the gravitational constant may not be a true constant; instead, it could be related to factors such as the shape and density of objects etc.

Study on the effect of laser welding rate on Q235 weld quality

Liu, Pinxiao — 2026-02-18T00:00:00Z

Journal of Measurements in Engineering, Vol. 14, Issue 2, 2026, p. 354-368.
Pinxiao Liu, Deping Liu, Guangyu Cai, Jisen Yan, Zhenyang Liu, Haonan Liu, Kai Li
Q235 low-carbon steel is widely used in construction, bridges, machinery manufacturing and other fields because of its good plasticity and weldability. To explore the optimized application of laser welding technology in Q235 steel processing, this study used an EEF-LWM-1500 welding machine and systematically investigated the effect of different welding speeds on the joint quality of Q235 steel under the condition of a constant laser power of 1200 W. The weld quality was systematically evaluated through multiple characterization methods, including metallographic microscopy, scanning electron microscopy, tensile testing, microhardness measurement, electrochemical corrosion tests, and friction-wear experiments. Experimental results indicated that a welding speed of 120 mm/min caused burn-through in the steel plate, while increasing the speed to 240 mm/min achieved good joint formability. Notably, the heat-affected zone gradually decreased with higher welding speeds. The hardness and tensile strength of the laser-welded zone both exceeded those of the base material. Specifically, the average hardness of the weld zone peaked at 177.56 HV when the welding speed was 500 mm/min. Below this speed, hardness increased with rising welding speed, while it tended to decrease above 500 mm/min. Tensile strength showed a similar trend, with the highest value of 424.98 MPa and the lowest value of 421.94 MPa. Electrochemical corrosion tests revealed that the welded joint at 500 mm/min exhibited the smallest self-corrosion current density (1.41×10⁻5 A/cm2) and the largest capacitive arc radius, confirming optimal corrosion resistance. This study identifies that the optimal laser welding speed for Q235 steel is 500 mm/min, which provides important technical references for improving the welding quality and production efficiency of Q235 steel in practical production and expanding its application scope.

Deformation mechanisms of open-pit high-steep slopes controlled by a fault: An integrated remote sensing, field investigation and numerical simulation study

Jiang, Anmin — 2026-02-19T00:00:00Z

Journal of Measurements in Engineering, Vol. 14, Issue 2, 2026, p. 296-310.
Anmin Jiang, Daobing Zhang, Feifei Wang, Yanchen Dong, Huadong Yin, Huzhi Wang, Sheng Zhang, Zhicheng Duan, Shaoxiang Xie
The engineering disasters caused by fault structural zones represent a persistent challenge in geotechnical engineering. This study employs an integrated approach, combining multi-temporal remote sensing, field investigation, and numerical simulation, to investigate the deformation mechanisms and stability of an open-pit slope controlled by the F15 fault. The results demonstrate that the collapse of the northern slope results from the combined effect of the internal F15 fault structure and external unloading due to underground mining. Remote sensing imagery reveals a four-stage failure process: initial rock deformation, local landslides, local surface subsidence, and final surface subsidence. Significantly, the F15 structural zone alters the deformation trend of the upper slope, channeling displacement towards the eastern valley, with a maximum simulated displacement of 5.4 cm. The safety factor of the slope, calculated using the strength reduction method, is 1.45, and the potential sliding surface is identified as the F15 structural zone. While the slope is currently stable, the limited safety redundancy and observed local landslides highlight the need for targeted monitoring and reinforcement of the fault zone. This study provides data-supported insights for the prevention and control of geological disasters in similar fault-controlled mining slopes.

Rapid extraction of forest burned areas using Sentinel-2 satellite imagery on the PIE-engine platform

Mao, Lijun — 2026-04-16T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Lijun Mao, Tianxiang Zhou, Chenghui Nan
The increasing of forest fires highlights the importance of rapidly and accurately quantifying the burned areas, which is crucial evidence for determining the cause of fire and assigning responsibility. This study develops an operational tool based on the cloud-computing abilities of the PIE-Engine platform and Sentinel-2 satellite imagery. The burned areas are rapidly extracted by applying differential spectral indices such as dNDVI, dNBR and dNBR2 using the adaptive thresholds determined by the Otsu algorithm. Compared with field investigations, the accuracy of using a wildfire case in Liuhe Village, Hubei Province is high. The findings indicate that dNBR can achieve an area accuracy of 98.22 % and a pixel-level F1-score of 0.94, significantly higher than dNDVI. Although the accuracy of the random forest model is slightly high, the dNBR based method achieves an excellent balance between computational efficiency (about 2 s of processing time) and accuracy. In addition, we have developed a user-friendly web application that allows for custom parameter settings and visualizes results as a quantitative burned area map. This tool only requires a web browser, greatly reducing the technical barriers of remote sensing applications and providing a transparent, efficient, and accessible solution for supporting forest fire investigation and emergency response.

Research on the design of a small-scale farmland rainfall runoff sampler

Ma, Yang — 2026-04-21T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Yang Ma, Huimei Zhang, Yuli Ouyang, Yue Zhang
This article designs a small-scale farmland rainfall runoff sampler for collecting rainwater during runoff events and performing chemical analysis. The system automatically collects up to 24 samples simultaneously using an STM32 microcontroller as its control unit. The controller adjusts the PWM signal to manage a DC motor's rotation and on/off state, and it accurately positions the sampling bottles via guide slots and position sensors. When the sampling bottle is positioned, the collection end sends a signal to start the peristaltic pump, which delivers water to the receiving end. And The flow rate is measured by a turbine flowmeter equipped with a pulse recorder. After calibration, the error of each 500 ml sample can be controlled within ±2 %, demonstrating relatively high accuracy and making the sampler suitable for actual sampling requirements. Its simple structure also enhances the durability of equipment in complex outdoor environments. Implementing unmanned rainwater collection can save manpower and material costs while avoiding the danger and uncertainty of manual sampling in rainy weather. The cap of the sampling bottle is designed with anti-volatility features to prevent the volatilization of chemicals such as pesticides and fertilizers in the rainwater, which is beneficial for improving the accuracy of soil and water monitoring.

Design and development of portable vibration and dynamic balance measurement system

Liu, Jianhua — 2026-05-08T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Jianhua Liu
To enhance the convenience of measuring unbalanced vibrations in rotating equipment and meet the on-site operation and maintenance requirements, a portable vibration and dynamic balance measurement system was designed and tested. The system, with the STM32F407VGT6 chip as its core, mainly consists of data detection module, data processing and transmission module, and terminal control and display module. The data detection module includes photoelectric sensors and vibration sensors. The data processing and transmission module incorporates optocoupler isolation, A/D conversion, and multiple communication modules. The terminal control and display module enables human-computer interaction and remote management. In terms of hardware design, circuits such as tracking band-pass filters and programmable gain amplifiers were developed to optimize signal acquisition quality. At the software level, fundamental frequency extraction algorithms including DFT were integrated to ensure accurate extraction of vibration characteristics. Experimental verification shows that the system can achieve high-precision acquisition of vibration signals and calculation of unbalance within the rotational speed range of 0-3000 rpm. The coincidence degree of fundamental frequency extraction results between the STM32 hardware terminal and the MATLAB software terminal exceeds 95 %, and data interaction and remote monitoring can be accomplished through multiple communication methods. This system meets the requirements of on-site portable operation and maintenance, providing reliable technical support for dynamic balance correction of rotating machinery.

Permeability evolution of prefabricated grouted curtain specimens with artificial defects under cyclic loading/unloading

Zhu, Fangcai — 2026-05-08T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Fangcai Zhu, Haijie Wen, Zengjie Liu, Jiang Guo, Xuebin Xie
Two types of rock specimens simulating grout curtains were prepared: one featuring solely an axial through-hole and the other featuring combined axial and transverse holes (termed combined-hole specimens). Coupled permeability-damage tests under cyclic loading-unloading were conducted to analyze the effects of peak stress level, confining pressure, seepage pressure difference, and defect geometry (curtain filling configuration) on permeability evolution and damage accumulation. The results indicate that: (1) Peak stress level is the primary factor governing damage development rate; (2) Higher confining pressure mitigates damage in the surrounding rock and decelerates permeability increase; (3) Larger seepage pressure difference (≥ 0.5 MPa) significantly enhances the stability and accuracy of permeability measurements; (4) For combined-hole configurations, increasing the transverse hole area (and thus the grout volume) provides more lateral seepage paths, effectively reducing axial permeability by up to two orders of magnitude. This study provides an experimental framework for assessing the long-term sealing performance of grouted curtains under repeated dynamic loading akin to blasting disturbances.

Experimental investigation on water retention and tensile strength of polyacrylamide (PAM) treated saline soil

Li, Wei — 2026-05-16T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Wei Li, Youcai Cao, Yuanhao Li, Quan Wang, Yali Wang, Jian Yang, Yiwei Jiao
Expansive, collapsible saline soils – widespread across northwestern China – are especially susceptible to desiccation-driven shrinkage, which progressively degrades soil fabric and triggers structural damage. Here we evaluate whether water-soluble polyacrylamide (PAM) can simultaneously enhance water retention and mechanical integrity in such soils. Using Atterberg-limit characterisation, indirect tensile testing, disintegration assays and desiccation – shrinkage experiments, we show that increasing PAM concentration consistently raises the liquid limit and plasticity index, whereas the plastic limit remains largely unchanged. Both shrinkage resistance and tensile capacity exhibit a clear optimum at 0.8 % PAM, where the shrinkage limit is maximised and tensile strength reaches its peak. In agreement with these macroscopic gains, PAM substantially delays disintegration and prolongs the time to complete dispersion, indicating improved stability upon wetting. Throughout drying – spanning rapid, falling-rate and constant-rate evaporation regimes – PAM-treated soils lose water markedly more slowly, demonstrating a robust improvement in water-holding capacity. We attribute these enhancements to hydrogen bonding between amide functionalities and water molecules, polymer-chain entanglement that promotes interparticle bridging, and a reduction in particle-surface electrokinetic (zeta) potential that stabilises the soil fabric.

A cross-domain fault diagnosis method for vehicle motors under variable operating conditions based on attention-guided graph convolutional networks

Lin, Changbo — 2026-06-04T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Changbo Lin, Xiaoyu Guo, Enyong Xu, Lidong Liang, Zhenzhen Jin
As a critical component of the automotive powertrain system, the performance status of electric motors directly impacts vehicle operational safety. During vehicle operation, sensor signals are frequently subject to noise interference, while motors typically operate under varying conditions, posing significant challenges for fault diagnosis. To address these issues, this paper proposes a cross-domain fault diagnosis method based on attention-guided graph convolutional networks, effectively countering interference from variable operating conditions. First, to tackle noise in extracted signal data, time-frequency domain feature fusion is employed to capture signal characteristics from both temporal and spectral perspectives, comprehensively extracting useful information. Subsequently, a wavelet kernel convolution layer is introduced, leveraging the multi-resolution properties of wavelet transforms to enhance feature extraction capabilities. Second, a graph-generation structure based on attention mechanisms is employed. This structure combines autoregressive moving average filter graph convolutions with multi-order graph convolutions based on Chebyshev polynomials to achieve further feature extraction and capture multi-scale information. Finally, the advancement of this method has been verified through a series of experimental cases, which demonstrates superior performance compared to other models across various cross-domain tasks.

Reliability evaluation of SiC MOSFET with performance degradation under multiple conditions based on nonlinear wiener process

Li, Yaoheng — 2026-06-04T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Yaoheng Li, Jinbao Zhang, Hui Wang, Jinle Zhang, Haiquan Zhang, Fuqiang Zhao
A reliability evaluation method for SiC MOSFET components based on the nonlinear Wiener process is proposed using small-sample threshold voltage degradation data under multiple operating conditions. In this method, the exponential function and power function are respectively used to characterize the influences of influencing factor parameters and time effects on the drift coefficient, thereby establishing a mathematical model capable of describing the degradation behavior of SiC MOSFET components. Based on the threshold voltage degradation data of 35 SiC MOSFET component samples, Limited-memory Broyden-Fletcher-Goldfarb-Shanno with Bound constraints (L-BFGS-B) is employed for parameter estimation. Meanwhile, the Bootstrap method is adopted to quantify the uncertainties of the initial degradation amount and influencing factor parameters under small-sample conditions. Through the Monte Carlo simulation method, the reliability evaluation of SiC MOSFET components is conducted under the designed operating conditions, and accurate reliability evaluation results, as well as their confidence intervals are obtained. The results demonstrate that the proposed nonlinear Wiener process model can effectively capture the degradation characteristics of SiC MOSFET components under different operating conditions, providing a scientific basis for further reliability evaluation and life prediction of power electronic equipment.

Bimetal structures manufacturing with wire arc additive manufacturing (WAAM): review of microstructure, interface, and mechanical properties

Korganci, Melike — 2026-07-09T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Melike Korganci, Nurefşan Kuvvet, Yahya Bozkurt, Sezgin Ersoy
Bimetallic structures are heterogeneous systems that combine the advantages of two different metallic materials, thereby providing tailored physical and mechanical properties for specific applications. In recent years, wire arc additive manufacturing has emerged as a promising technology for producing bimetallic structures, thanks to its high deposition rates and material efficiency. The use of wire arc additive manufacturing in the fabrication of bimetallic structures enables the production of different alloys within a single component, thereby paving the way for functionally graded and multi-material designs. The microstructures of bimetallic components produced using this method exhibit heterogeneities depending on the heat input, interlayer thermal stresses, intermetallic phase formation, and processing parameters. Mechanical properties, such as tensile strength, yield strength, and hardness, are directly dependent on the interfacial bonding conditions. At interfaces where brittle intermetallic phases form, a loss of ductility and an increased tendency to fracture are observed. A sufficient metallurgical bonding between two metallic materials results in acceptable mechanical performance in bimetallic structures built using wire arc additive manufacturing. Alloy compatibility, heat input control, and interface properties are critical for the successful application of bimetallic structures produced using this method. This review comprehensively evaluates the microstructural properties, mechanical behavior, and challenges of bimetal structures produced by wire arc additive manufacturing. The novelty of this review lies in its integrative analysis of interface-microstructural evolution and mechanical response, providing a unified perspective that has not been explicitly addressed in earlier studies. In addition, this study aims to provide a guiding framework for future research by presenting the relationship between the microstructure and mechanical properties of bimetallic structures fabricated using wire-arc additive manufacturing.

Reconstruction model of blast wave pressure field

Wang, Liangquan — 2026-07-25T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Liangquan Wang, Changli Wang, Binwen Qian, Xin Zhang, Zhenghao Wu, Botian Zhang
Blast wave is one of the main damage parameters generated by ammunition explosions. Clarifying the distribution pattern of blast wave pressure field in ammunition explosions is of great significance for evaluating the damage power of ammunition and guiding ammunition design. This study is based on the ground-reflection pressure and free-field pressure mapping model, considering the influence of altitude and surface material acoustic impedance on the distribution law of blast wave pressure. A reconstruction model of explosion blast wave pressure field was constructed, and experimental tests were conducted in typical scenarios to verify the accuracy of the pressure field reconstruction model. The results show that the blast wave pressure field reconstruction model proposed in this study can well reflect the pressure distribution law, with a reconstruction accuracy of better than 93.9 %, which compensates for the shortcomings of insufficient pressure distribution data in the pressure field reconstruction process. It provides theoretical and data support for accurate evaluation of ammunition explosion damage power and has significant military application value.

Study on stability assessment of buckling failure and rainfall-induced instability mechanism for steeply inclined rock slope

Chen, Peng — 2026-07-30T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Peng Chen, Haipeng Jia, Jiadong Li, Yuxia Zhao, Jipeng Zhu, Haihua Zheng, Guo Guo, Zilong Yu, Yunfei Liang, Haihua Kang
To address challenges associated with the stability assessment and engineering control of buckling failure in steeply inclined rock slopes, this study takes the southern slope of the Longyu Open-Pit Mine as a case study and adopts an integrated approach combining theoretical modeling, field monitoring, and numerical simulation. First, under the assumptions of coordinated deformation and small strain, a differential equation governing the behavior of the surface rock layer is derived. This leads to the formulation of a safety factor defined as the ratio of the critical to the actual slope length. The analysis indicates that the slope remains stable when the thickness of the rock layer exceeds 10 m and the elastic modulus is greater than 32 GPa, thereby establishing a robust mechanical model for buckling failure. Second, based on field monitoring data of displacement and strain, orthogonal testing and factor sensitivity analyses are conducted. The results reveal the following ranking of influential factors: rock layer thickness (R= 0.38+39.8 %) is an exceptionally sensitive positive factor; cohesion (R= 0.25) is a highly sensitive positive factor; unit weight and groundwater level are significantly sensitive negative factors; whereas the influence of elastic modulus is negligible (R= 0.03). These insights provide a clear priority hierarchy for monitoring and stability control measures. Finally, by incorporating real-time rainfall intensity data, FLAC3D simulations demonstrate a strong negative correlation between rainfall intensity and slope stability. Heavy rainfall is identified as a critical threshold triggering stability failure. Under such conditions, the maximum slope displacement increases by 175 %, reaching 5.5 m, and the shear strain increment develops into an arc-shaped sliding surface. The slope interval between 1360-1390 m is identified as the core risk zone, while the interval from 1290-1310 m acts as a key shear outlet. This clarifies the evolutionary pathway and key focus areas for preventing rainfall-induced instability. The findings of this study offer a solid theoretical foundation and practical technical support for the monitoring, risk warning, and engineering management of similar steeply inclined slopes.

A bearing fault diagnosis method based on MCDCGAN and DPTAN under data imbalance

Zhang, Sen — 2026-08-03T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Sen Zhang, Le Yan, Zhaodong Liu, Hao Ren, Heng Lu
Bearings are critical components of rotating machinery, yet reliable fault diagnosis remains challenging under complex conditions due to signal non-stationarity and data scarcity. To address these issues, this paper proposes a diagnostic framework that combines generative-adversarial data augmentation with dual-branch time–frequency representation learning to improve feature quality and fault classification. Firstly, the bearing vibration signals are transformed into two-dimensional time-frequency representations by utilizing the continuous wavelet transform. Subsequently, a multi-attention conditional deep convolutional generative adversarial network (MCDCGAN) is employed for conditional augmentation under class imbalance, integrating attention mechanisms and stabilization strategies to generate more reliable samples for minority fault classes. Finally, a dual-branch parallel time-frequency attention network (DPTAN) is designed to jointly learn temporal and spectral feature representations and then fuse them for fault classification. Experimental results on the CWRU and HIT datasets demonstrate that the proposed method achieves better performance than baseline models and maintains robustness under data imbalance and noisy conditions.

Determination and numerical Validation of HJC constitutive model parameters for C30 concrete based on laboratory tests

Wu, Yu — 2026-08-03T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Yu Wu, Tong Ye, Xiaoyang Wu, Jie Zhou
The Holmquist-Johnson-Cook constitutive model is widely adopted to analyze the dynamic response of concrete-like materials under impact and blast loading. In this study, a modified set of HJC constitutive parameters for C30 concrete was calibrated through a series of tests. Uniaxial compression tests were used to determine the uniaxial compressive strength and elastic parameters; conventional triaxial compression tests were performed to obtain the yield-surface parameters A, B, and N; uniaxial cyclic loading-unloading tests were conducted to determine the damage parameters D1 and D2; and split Hopkinson pressure bar (SHPB) tests were carried out to identify the strain-rate parameter C. Numerical validation was conducted using a finite element model of the SHPB test. The results demonstrate that the proposed HJC model parameters can effectively represent the dynamic mechanical behavior of C30 concrete under impact loading at low-to-medium strain rates. Both the stress-strain curves and failure modes derived from numerical simulations agree well with the experimental observations. These findings can provide reference for the impact- and blast-resistant design of concrete structures.

Microstructural evolution and corrosion resistance of CoCuNiTiX0.6 (X = Mn, Al) HEA coatings on the 45-steel substrate

Ma, Mingxing — 2026-08-04T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Mingxing Ma, Yanan Li, Chengjun Zhu, Zhixin Wang, Yanjun Xi, Bozhen Wang
Laser cladding technology was employed to prepare dual-phase CoCuNiTiX0.6 (X = Mn, Al) HEA coatings on the 45-steel substrate. The phase structure, microstructural evolution, composition analysis, and corrosion resistance of CoCuNiTiX0.6 (X = Mn, Al) HEA coatings were studied using an X-ray diffractometer, OM, SEM, EDS, and ECW. The results demonstrate that CoCuNiTiMn0.6 alloy consists of an FCC primary phase and a BCC phase. After replacing Mn with Al, CoCuNiTiAl0.6 alloy transforms into a structure dominated by the BCC phase, with a minor amount of the FCC phase. The lattice constants and cell volumes of BCC and FCC in Al-containing alloy are relatively large, but their densities are low. Both alloys have dendritic structures. The high viscosity and poor fluidity of Mn-containing alloy melt increase atomic diffusion resistance and a relatively slow occurrence of “composition undercooling” during solidification, resulting in coarse columnar crystals and pore defects. Ti and Cu exhibit the highest concentrations in the primary phase and interdendrite regions, respectively. The composition differences of Ni, Mn, and Al in different regions are relatively small. Both alloys show obvious passivation zones in 3.5wt% NaCl solution, and their Nyquist plots present a flattened semi-circular arc. The capacitive arc radius, maximum phase angle, and m value of CoCuNiTiAl0.6 HEAC are relatively large, indicating that its corrosion resistance is relatively superior, mainly due to its dense passivation film, fewer defects, and relatively uniform composition distribution.

Research on asymmetric jet sounding and control technology

Li, Zhipeng — 2026-08-05T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Zhipeng Li, Jianan Zhang, Zeqian Wang, Liang Zhao, Hejuan Chen
To reveal the response characteristics and rectification mechanism of the nozzle geometry of the airflow acoustic piezoelectric generator (AAPG) to unstable and asymmetric airflow, this paper establishes a control model for modulating the airflow acoustic sounding by studying the structural design scheme for the combination of the fused airflow acoustic piezoelectric generator (AAPG) nozzle-resonant cavity-piezoelectric. Then, the sound pressure curve with sinusoidal vibration is numerically simulated at the bottom of the resonance cavity. Finally, the error between the sound pressure frequency and the theoretical control frequency is less than 7.5 % through experiments, and the portion of the sound pressure frequency and the output voltage frequency are consistent with an error of less than 4 %, verifying that the jet acoustic control model can effectively achieve acoustic control of the asymmetric jet.

Spatiotemporal feature extraction of regional building energy consumption combining residual network and convolutional attention mechanism

Gao, Qiongmin — 2026-08-06T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Qiongmin Gao, Jian Yin
When dealing with complex spatiotemporal patterns affected by multi-factor coupling, there are significant limitations in the cross-layer feature fusion ability of the model, making it difficult to effectively handle the high-dimensional spatiotemporal correlations and redundant information in building energy consumption data, resulting in insufficient capture of the multi-scale dynamic changes in the spatiotemporal features of regional building energy consumption. Therefore, a method for extracting spatiotemporal features of regional building energy consumption combining Residual Network (ResNet) and convolutional attention mechanism is proposed. First, the multi-layer structure of the residual network is used to extract the temporal and spatial features of building energy consumption respectively, and skip connections and downsampling modules are used to enhance the cross-layer feature fusion ability of the model. Then, a graph attention module and a channel attention mechanism are introduced. Taking the building monitoring area as nodes and the energy consumption correlation as edges, the weight distribution of key spatiotemporal features is dynamically learned, so as to suppress redundant information and strengthen the feature expression ability. Finally, the advancement of the proposed method is verified through experiments. The experimental results show that this method can accurately capture the hourly fluctuation law and spatial heterogeneity of building energy consumption, with a prediction deviation as low as 2.41 % and an average energy saving rate of 33.20 %, significantly superior to the traditional U-Net encoder and histogram analysis method, and has good application effects.

Study on the influence of identify orientation on acoustic-based fault diagnosis for circuit breakers in switchgear

Gu, Guangmin — 2026-08-24T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Guangmin Gu, Wei Zhang, Like Zhao, Hao Liu
As key equipment in the power system, the operating state of switchgear circuit breakers directly affects power grid reliability. Traditional fault diagnosis methods suffer from complex installation and high susceptibility to interference, while voiceprint diagnosis has become a research hotspot due to its non-contact, high sensitivity and easy deployment. However, the acquisition orientation (angle and distance) of sensors can significantly change voiceprint signal characteristics and reduce diagnostic accuracy. Therefore, this paper takes 10 kV switchgear circuit breakers as the research object, collects opening and closing voiceprint signals at different angles and distances through experiments, and studies the influence of sensor orientation on voiceprint characteristics. Time-frequency analysis shows that the energy of the closing signal is about twice that of the opening signal. Within the range of ±45°, the angle change has little effect on the energy (difference < 8 %), and the 0° orientation has the best signal-to-noise ratio. The angle has no significant effect on the frequency-domain characteristics, but the closing signal has richer high-frequency components. Distance experiments show that the signal energy follows the 1/r2 attenuation law, and the high-frequency components attenuate faster. Accordingly, this paper proposes a signal compensation method based on energy normalization, which can eliminate the spectrum distortion caused by distance and keep the signal characteristics consistent at different distances. The results provide a theoretical basis for the optimal layout of sensors in circuit breaker voiceprint diagnosis. The proposed compensation method can effectively improve the accuracy of fault diagnosis models and has important engineering application value for power equipment condition monitoring.

Experimental research on hollowing detection in concrete walls based on acoustic signal feature analysis

Wang, Jiaqi — 2026-08-28T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Jiaqi Wang, Shibin Teng, Shushu Ge, Wenlong Zhang, Fang Zhao
Concrete wall hollowing is a common defect affecting structural safety and durability, and its accurate identification is of great significance for ensuring the quality of construction projects. To achieve efficient and non-destructive detection of hollowing defects, this paper proposes a method for identifying the state of concrete wall hollowing using the characteristics of knock sound signals based on the principle of acoustic response. The study first collects acoustic signal data from hollowing and non-hollowing areas through standardized knocking experiments, and conducts systematic time-domain and frequency-domain feature analysis. By comparing signal waveform and spectral characteristics, the study explores the differences in acoustic response between hollowing and non-hollowing areas. The research results provide a reliable parameter basis for acoustic detection of concrete structures and verify the feasibility and effectiveness of the hollowing identification approach based on acoustic signal characteristics. This research method has the advantages of simplicity, low cost, and strong applicability, and can provide new technical support and application references for non-destructive testing and intelligent health monitoring of building structures. The results show that under the experimental conditions of this study, the dominant frequencies of hollow areas are mainly distributed in the range of 1650-1750 Hz, while those of non-hollow areas are concentrated within 1300-1500 Hz. The absolute values of peak amplitudes of hollow areas generally fall between 40-50 mV, whereas those of intact regions range from 10-20 mV, which provides quantitative reference criteria for hollow defect detection in practical engineering.

Rainfall-induced seepage damage coupling mechanism and stability evaluation of high and steep slopes in deep open-pit mines

Wang, Peng — 2026-08-29T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Peng Wang, Haipeng Jia, Yuxia Zhao, Xingyu Liu, Shengnan Xu, Lei Song, Wenlong Wu, Jiangle Li
Steep, highly fractured rock slopes, characterized by lithological heterogeneity, intense fracturing, and sensitivity to rainfall-induced hydraulic perturbations, pose challenges that are not covered by classical sliding-surface models. This study integrates multiphysics monitoring, laboratory experiments, and probabilistic inversion to investigate a representative slope at the Luanchuan Longyu open-pit mine. A positive feedback loop was found between seepage and fracture development: elevated pore pressure induced by rainfall or increased groundwater levels drives fracture propagation, enhances permeability and seepage velocity, reduces effective stress, and initiates a self-accelerating “seepage → fracture → rock weakening” chain, even in the absence of a continuous slip surface. Lithological analysis reveals that marble and gneissic granite exhibit high strength (UCS ≈ 57-58 MPa, c≈ 6.2-6.8 MPa, ϕ ≈ 39°-43°), whereas quartz-mica schist is a highly weathering-sensitive weak layer (saturated UCS = 9.78 MPa, with 35 % strength loss and SDI = 58.96 % after 11 wetting-drying cycles). Parameter back-analysis (with 80 % confidence intervals) reveals schist (c = 24.5 kPa, ϕ = 34.4°) as the dominant weak stratum and faults (c = 8.9 kPa) as potential slip surfaces, clarifying the lithology-structure controls on failure patterns. Rainfall infiltration triggers a nonlinear hydraulic response and preferential toe flow, causing pore pressure to propagate downward and shifting slope degradation from surficial to whole-slope failure-a dynamic "surface-to-depth" progression modeled in this study. These findings provide a quantitative mechanistic framework for assessing steep, heterogeneous slopes and support intelligent hazard mitigation through rainfall thresholds and real-time monitoring.

Effect of defocus amount on microstructure and properties of laser welded joints of Q235/304 dissimilar steels

Yuehan, Chen — 2026-09-04T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Chen Yuehan, Zhang Zhengyi, Wang Minghui, Yan Jisen, Liu Qingshan, Zhou Yang
To optimize the welding process for dissimilar metals, this study explores the influence of defocus amount on the microstructure and properties of laser-welded joints between Q235 and 304 stainless steel. Welding experiments were performed using an EFE-LWM-1500 laser welding machine at a fixed laser power of 1200 W with five defocus amounts: –10 mm, –5 mm, 0 mm, +5 mm, and +10 mm. The welded joints were characterized by optical microscopy, X-ray diffraction (XRD), universal tensile testing, scanning electron microscopy (SEM), and electrochemical workstation to analyze the microstructure, phase composition, tensile strength, fracture morphology, and corrosion resistance. Metallographic analysis shows that the 304 stainless steel side is dominated by austenite, the weld center exhibits lath martensite, and the heat-affected zone of Q235 carbon steel contains Widmanstatten structure, pearlite, and acicular ferrite. The weld grains are most uniform and fine at 0 mm defocus. XRD confirms the presence of Fe-Ni solid solution in the joint. Mechanical tests reveal that the average microhardness of the weld reaches a peak of 373.05 HV and the tensile strength reaches a maximum of 309.46 MPa at 0 mm defocus. Electrochemical tests show that the self-corrosion current density is as low as 2.24×10-5 A/cm2 and the capacitive arc radius is the largest under this condition, indicating the best corrosion resistance. SEM analysis of the fracture surface shows typical necking and dimpled structures, confirming ductile fracture. The defocus amount significantly regulates the properties of Q235/304 dissimilar steel laser-welded joints. A defocus amount of 0 mm achieves the optimal microstructure and comprehensive properties, providing an important reference for optimizing laser welding parameters of dissimilar metals.

Fault identification method of transmission corridor based on 3D R-tree integrated point cloud data segmentation

Tong, Hongju — 2026-09-09T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Hongju Tong, Zengliang Chang, Dong Li, Xingguo Gao, Qingzhong Wang, Dazhong Ni
This paper addresses the inefficient and error-prone identification of tree hazards near transmission corridors by proposing a recognition method that uses 3D R-tree-integrated point cloud segmentation. LiDAR-equipped UAVs capture the original point cloud data of the corridor. The data are denoised and enhanced using principal component analysis (PCA). A 3D R-tree-integrated octree indexing structure is constructed to rapidly locate potential tree hazards by querying regions within the minimum safe distance. A Euclidean clustering algorithm with cylinder k-point constraints is applied to extract these hazardous point clouds. The spatial location of the transmission corridor is determined by fitting its point cloud via RANSAC-based least squares. Finally, distances between tree crowns and the corridor are calculated to identify hazards. Experiments demonstrate that the proposed method is efficient, accurate, and sensitive, offering an intelligent solution for automated corridor monitoring.

Discriminating surface deformation types and assessing LOS interpretation applicability using ascending and descending Sentinel-1 InSAR in the permafrost zone of the Qinghai-Tibet Engineering Corridor

Du, Qingsong — 2026-09-10T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Qingsong Du, Anhua Xu, Guoyu Li, Fei Wang, Huimin Luo, Shunshun Qi
Warming and wetting on the Qinghai-Tibet Plateau (QTP), together with increasing engineering disturbance, have accelerated permafrost degradation along the Qinghai-Tibet Engineering Corridor (QTEC), inducing surface deformation that threatens infrastructure stability and environmental safety. Interferometric synthetic aperture radar (InSAR) has become an effective tool for large-scale deformation monitoring; however, conventional single-orbit ascending or descending observations measure only one-dimensional line-of-sight (LOS) displacement. Because LOS deformation represents a projection of actual ground motion, it cannot always be directly interpreted as vertical uplift or subsidence, especially where horizontal displacement is significant. In this study, ascending and descending Sentinel-1 InSAR observations from 25 February 2017 to 31 March 2022 were integrated to decompose two-dimensional deformation components, namely east-west and vertical displacement, in the permafrost zone of the QTEC. Based on the decomposed results, surface-deformation types were discriminated, and the interpretation applicability of conventional single-orbit LOS observations was quantitatively evaluated using vertical deformation as a reference. The results show that single-orbit LOS deformation can reasonably represent vertical deformation in 52.84 % of the study area, whereas the remaining 47.16 % is dominated by horizontal displacement and is therefore unsuitable for direct interpretation as uplift or subsidence. These findings highlight the necessity of distinguishing deformation types before interpreting LOS deformation and provide practical guidance for improving the reliability of InSAR-based deformation monitoring and engineering-risk assessment in permafrost corridors.

Reliability-adaptive probabilistic imaging and severity assessment of axial cracks in steel pipelines

Zhang, Xinyu — 2026-09-27T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Xinyu Zhang, Changzhi He, Zhen Li
Axial crack detection in steel pipelines remains challenging because the crack-reflected guided-wave response is usually weak, frequency-dependent, and susceptible to dispersion, modal interference, sensor-coupling variation, and environmental noise. To address this issue, a reliability-adaptive probabilistic imaging and semi-quantitative severity-assessment framework is proposed using multi-frequency ultrasonic guided-wave signals. A T(0,1)-dominated torsional guided-wave packet is selected as the target response, and dispersion analysis is used to support mode selection and reflection-window prediction. Time-domain, frequency-domain, and time-frequency-domain features are extracted from the crack-reflection window to characterize the defect response from complementary perspectives. For each excitation frequency, a single-frequency probability image is constructed by combining reflected-response strength and travel-time consistency. A reliability-adaptive fusion strategy is then developed to integrate the probability images obtained at different frequencies, where the contribution of each frequency is determined by echo quality, inter-sensor consistency, and modal purity. Equal-weight fusion and SNR-weighted fusion are introduced as baseline methods to evaluate the contribution of the proposed reliability-adaptive weighting strategy. A confidence-enhancement step is further applied to suppress uncertain secondary hotspots and improve noise-interference stability under the tested controlled condition. Experiments were conducted on a Q235 steel pipe specimen containing three axial surface crack depths. The results show that amplitude- and energy-related features increase progressively with crack depth, indicating their sensitivity to severity variation under the present configuration. Compared with equal-weight and SNR-weighted fusion, the proposed method produces more compact probability distributions, lower background interference, and improved localization concentration around the actual crack region. The posterior-distribution-based severity index provides effective semi-quantitative grading of mild, moderate, and severe crack cases. The present study should be interpreted as controlled-condition verification of the proposed framework, while broader validation with different crack geometries, crack locations, sensor-coupling states, and environmental conditions is required in future work.

AI real-time detection of cable corrosion in power inspection videos based on a YOLOv10-transformer hybrid network

Sun, Shiquan — 2026-09-27T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Shiquan Sun, Meng Xie, Yi Feng, Jiatian Shangguan, Guangjiu Chen
The operation and maintenance of current power infrastructure face critical challenges, such as inefficient cable corrosion detection, strong subjectivity in assessments, and insufficient early-warning capabilities. Traditional manual inspection methods not only demand substantial human resources but are also susceptible to environmental factors and inspector experience, which compromises detection accuracy. Therefore, this study proposes a deep learning model that integrates a multi-scale feature extraction module with an adaptive attention mechanism (MSFEM-AAM). The model employs parallel feature extraction pathways to simultaneously capture global morphological characteristics and localized corrosion details on cable surfaces. A dynamic weight fusion mechanism is incorporated to adaptively integrate multi-scale features, thereby enhancing the model’s discriminative capability for corrosion patterns. Experimental results show that MSFEM-AAM achieves 96.8 % accuracy in corrosion grade classification (Task 2) and 94.7 % mAP in corrosion region detection (Task 1). The single-frame inference time reaches 9 ms with GPU acceleration. These quantitative metrics demonstrate the advanced performance and practical applicability of MSFEM-AAM, contributing to improved automation of corrosion detection and enhanced early-warning capabilities, thus supporting the secure and stable operation of power grids.

Real-time recognition model of 3D workpiece for transmission tower based on uniseg3d and vision-inertia fusion

Li, Zeyu — 2026-09-27T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Zeyu Li, Yalong Zhao, Xiaowei Sun, Nan Jiang, Te Li, Dalue Xue
To tackle the challenges existing in point cloud segmentation for transmission tower components-specifically, weak small-target perception, blurred boundaries, poor cross-scene adaptability, and insufficient real-time performance-this study develops a real-time recognition model by integrating LiDAR-IMU with UniSeg3D. The core contribution lies in formulating a systematic solution architecture. First, to address the issues of small targets and boundary ambiguity, a multi-scale boundary-aware module is designed. By jointly optimizing classification and boundary losses, it substantially strengthens feature extraction for small components (e.g., insulators) and enhances localization accuracy along boundary regions. Second, to mitigate the reliability degradation of single-sensor systems under complex conditions (such as vegetation occlusion or illumination variation), a vision-inertial bimodal fusion strategy is introduced. High-frequency motion data from the IMU are employed to dynamically compensate for the spatial sparsity of LiDAR point clouds, thereby improving the model’s robustness across diverse scenes. Third, to meet the real-time demands of engineering applications, a feature contribution screening mechanism is incorporated. This enables structured pruning and model lightweighting-reducing processing time per single tower to within 3 seconds-while maintaining accuracy. Experimental results demonstrate that, through the synergistic integration of these techniques, the proposed model achieves an average F-score of 0.853 across six core component categories, with particularly notable advantages in small-target recognition and complex-scene adaptability compared to existing approaches. This model has realized high-precision real-time identification of components in complex scenarios, which provides a technical scheme for intelligent inspection of transmission lines, and promotes the upgrade of the inspection mode from manual to automatic. At last, the stable operation of power systems is guaranteed.

Path deviation control for multi-UAV cooperative task execution based on laser vision guidance and trajectory prediction

Liao, Jingjing — 2026-09-27T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Jingjing Liao
This paper proposes a path deviation control method that integrates laser vision guidance and trajectory prediction to address deviations caused by limited environmental perception in multi-drone cooperative tasks. First, a local 3D point cloud map is constructed using Light Detection and Ranging (LiDAR). Global environment modeling is achieved through Oriented FAST and Rotated BRIEF Simultaneous Localization and Mapping 3 (ORB-SLAM3) and a multi-agent cooperative mapping mechanism. Second, multidimensional constraints, including turning radius, velocity, and safety distance of the unmanned aerial vehicles (UAVs), are incorporated into an improved A* algorithm to enhance the accuracy and feasibility of trajectory prediction. Finally, real-time path correction is realized using a fuzzy proportional-integral-derivative (PID) controller, forming a closed “perception-planning-control” loop. Experimental results show that the proposed method achieves a path deviation of only 1.0 m, reduces task time to 10 min, and maintains a collision rate as low as 2 %. It remains stable under complex conditions such as Global Positioning System (GPS) denial and strong winds. The method significantly improves path accuracy, stability, and obstacle avoidance capability in multi-drone cooperative tasks and can be widely applied in fields such as logistics distribution, disaster monitoring, and cooperative inspection.

Short-term electricity load interval estimation algorithm based on OS-ELM feature enhancement for SVR

Wei, Yaxing — 2026-09-27T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Yaxing Wei, Jiamao Han, Bin Zhao, Yujia Chen, Wei Ao, Mingzuo Ma, Lai Man
Short-term power load forecasting is crucial for power system dispatch and market transactions. However, the dynamic, nonlinear, and uncertain nature of loads poses challenges for accurate interval estimation. This paper proposes a short-term load interval estimation algorithm based on online sequence extreme learning machine (OS-ELM) feature enhancement and support vector regression (SVR). Rather than a simple model stacking approach, it constructs a dynamically collaborative two-stage prediction architecture: OS-ELM serves as a real-time feature generator, adaptively capturing concept drift in data streams to produce dynamically enhanced features; these features are then fed into an SVR model for high-precision point prediction. Finally, dynamic confidence intervals are constructed based on the empirically updated prediction error distribution. Experiments validate the approach using actual summer data (26,304 samples) from a provincial power grid in China. Results demonstrate outstanding point prediction performance with an RMSE of 236.7 MW and MAPE of 1.80 %, outperforming benchmark models including SARIMA, LightGBM, LSTM, and Transformer. For interval forecasting, at a 95 % confidence level, it achieves 94.5 % interval coverage with an average interval width of 148.7 MW, striking a good balance between coverage and precision while maintaining high interval calibration quality. Furthermore, the scheduling scheme based on this algorithm strictly controls system voltage fluctuations within ±0.4 p.u., significantly enhancing system operational stability. This algorithm provides a solution for short-term load forecasting that combines high accuracy, strong adaptability, efficient computation, and reliable uncertainty quantification capabilities.

Method for integrity verification of power measurement data based on the data middle platform and variable-block-size hash tree

Liu, Chao — 2026-09-27T00:00:00Z

Journal of Measurements in Engineering, (in Press).
Chao Liu, Jing Chen, Chao Lin, Zengwei Zhang, Zhuang Cui
Smart grids generate large volumes of highly dynamic power measurement data, but existing integrity verification methods suffer from poor scalability and low efficiency. To address these challenges, this paper proposes a verification method based on a data middle platform and variable-block-size hash trees (VB-HTree). The data middle platform enables unified ingestion of multi-source heterogeneous data, anomaly correction, and distributed Kalman filter fusion, thereby enhancing data quality. Using VB-HTree, the method dynamically partitions hot and cold zones according to data access locality and varies block sizes to optimize hash tree depth and I/O overhead. Experiments on an IEEE 14-node system show that the proposed method achieves a data correction accuracy of 96.1 % and a data integrity verification success rate exceeding 99.5 %. The average verification time is approximately 46 % shorter than that of a fixed-block Merkle tree, offering an efficient and scalable solution for ensuring data integrity in power systems.