Impedance data and PNN-based non-destructive testing technology for electric meters

As the digital transformation of distribution networks progresses and smart meters are widely adopted, determining the status of returned meters for secondary use becomes crucial. Electric meter faults are diverse and complex, and the current mainstream method of manual inspection is time-consuming and inefficient. This paper introduces an innovative non-destructive testing method using impedance analysis at the meter ports, leveraging emerging artificial intelligence technologies. This method characterizes fault types through impedance features, enabling rapid and automated non-destructive testing of electric meters. Verified by examples, the proposed method significantly improves detection efficiency and accuracy compared to traditional manual methods, offering a novel technological approach for meter status assessment and reutilization.