Yanchang Wang
Yanchang Wang has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Haitao Wang
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
1 shared publication - Jiahuan Zheng
College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211816, China
1 shared publication - Lijuan Li
College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, China
1 shared publication Pingping Sun
713th Research Institution of China State Shipbuilding Corporation Limited
1 shared publication- Qing Zhang
College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, China
1 shared publication - Shengping Wu
Jiangsu Special Equipment Safety Supervision and Inspection Institute, Nanjing 210036, China
1 shared publication
Latest Publications
- Open Access
- 1 May 2026
- Published by IOP Publishing in Journal of Physics: Conference Series
- Vol. 3226 (1)
Research on long-term performance evaluation and prediction of function generators
Based on the annual calibration data of a function generator from 2018 to 2025, this article systematically analyzes the error evolution rules of its output frequency and output amplitude. Through time series charts, single value-moving range control charts, and trend prediction models, we comprehensively evaluate the accuracy, precision, and long-term stability of the equipment, and predict the performance in the next two years. The analysis results show that the calibration error of the equipment during the entire observation period is far better than the technical index requirements, the process is under statistical control, the frequency error shows a slowly rising trend, the amplitude error fluctuates slightly, and there is no obvious drift. This study shows that the equipment has stable performance and controlled status, is suitable for high-precision testing scenarios, and provides data support for calibration cycle optimization and preventive maintenance of similar equipment.
- 1 May 2026
- Published by IOP Publishing in Journal of Physics: Conference Series
- Vol. 3226 (1)
Open AccessResearch on long-term performance evaluation and prediction of function generators
Based on the annual calibration data of a function generator from 2018 to 2025, this article systematically analyzes the error evolution rules of its output frequency and output amplitude. Through time series charts, single value-moving range control charts, and trend prediction models, we comprehensively evaluate the accuracy, precision, and long-term stability of the equipment, and predict the performance in the next two years. The analysis results show that the calibration error of the equipment during the entire observation period is far better than the technical index requirements, the process is under statistical control, the frequency error shows a slowly rising trend, the amplitude error fluctuates slightly, and there is no obvious drift. This study shows that the equipment has stable performance and controlled status, is suitable for high-precision testing scenarios, and provides data support for calibration cycle optimization and preventive maintenance of similar equipment.
- Open Access
Research on Eddy Current Probes for Sensitivity Improvement in Fatigue Crack Detection of Aluminum Materials
Aluminum alloys under long-term service or repetitive stress are prone to small fatigue cracks (FCs) with arbitrary orientations, necessitating eddy current probes with focused magnetic fields and directional selectivity for reliable detection. This study presents a flexible printed circuit board (FPCB) probe with a double-layer planar excitation coil and a double-layer differential receiving coil. The excitation coil employs a reverse-wound design to enhance magnetic field directionality and focusing, while the differential receiving coil improves sensitivity and suppresses common-mode noise. The probe is optimized by adjusting the excitation coil overlap and the excitation–receiving coil angles to maximize eddy current concentration and detection signals. Finite element simulations and experiments confirm the system’s effectiveness in detecting surface cracks of varying sizes and orientations. To further characterize these defects, two time-domain features are extracted: the peak-to-peak value (P), reflecting amplitude variations associated with defect size and orientation, and the signal width (W), primarily correlated with defect angle. However, substantial overlap in their value ranges for defects with different parameters means that these features alone cannot identify which specific parameter has changed, making prior defect classification using a Transformer-based approach necessary for accurate quantitative analysis. The proposed method demonstrates reliable performance and clear interpretability for defect evaluation in aluminum components.Open AccessResearch on Eddy Current Probes for Sensitivity Improvement in Fatigue Crack Detection of Aluminum Materials
Aluminum alloys under long-term service or repetitive stress are prone to small fatigue cracks (FCs) with arbitrary orientations, necessitating eddy current probes with focused magnetic fields and directional selectivity for reliable detection. This study presents a flexible printed circuit board (FPCB) probe with a double-layer planar excitation coil and a double-layer differential receiving coil. The excitation coil employs a reverse-wound design to enhance magnetic field directionality and focusing, while the differential receiving coil improves sensitivity and suppresses common-mode noise. The probe is optimized by adjusting the excitation coil overlap and the excitation–receiving coil angles to maximize eddy current concentration and detection signals. Finite element simulations and experiments confirm the system’s effectiveness in detecting surface cracks of varying sizes and orientations. To further characterize these defects, two time-domain features are extracted: the peak-to-peak value (P), reflecting amplitude variations associated with defect size and orientation, and the signal width (W), primarily correlated with defect angle. However, substantial overlap in their value ranges for defects with different parameters means that these features alone cannot identify which specific parameter has changed, making prior defect classification using a Transformer-based approach necessary for accurate quantitative analysis. The proposed method demonstrates reliable performance and clear interpretability for defect evaluation in aluminum components.