Research on Internal Short Circuit Fault Identification of Low-Voltage Distribution Cabinet Based on Infrared Images
Due to the complex internal structure and electrical components of low-voltage distribution cabinets,the signal characteristics of short-circuit faults may be affected by various factors,resulting in significant identification deviation values.For this purpose,infrared image-based short circuit fault identification inside low-voltage distribution cabinets is investigated.Firstly,preprocess the infrared images inside the low-voltage distribution cabinet,to improve image quality and contrast.Secondly,using preprocessed infrared images and image segmentation and feature extraction techniques,locate the interval where short circuit faults occur and narrow down the fault search range.On this basis,construct node fault feature data and extract key fault feature quantities to quantitatively describe the characteristics of faults.Finally,by comparing the difference in characteristic quantities between normal and fault states,accurate identification of internal short circuit faults in low-voltage distribution cabinets can be achieved.The results show that at any point in the AB section of the interval,compared with the methods based on current analysis and electrical signal waveform analysis,the deviation value of the internal short circuit fault identification method based on infrared images in low-voltage distribution cabinets is the smallest.The fault identification results are consistent with the interval where the actual fault is located,and the practical application effect is better.
infrared imagelow-voltage distribution cabinetshort circuit fault identificationinternal short circuit
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