Sweep frequency response analysis of three-phase induction motors using high frequency circuit model

• Innovative Approach: Introduces a novel method for Sweep Frequency Response Analysis (SFRA) using a high-frequency circuit model to assess the condition of induction motor windings. • Parameter Estimation: Proposes an efficient method to estimate parameter values of the motor's high frequency circuit based on SFRA test data. • Adjustment of parameter: Demonstrates the adjustment of parameter values to align simulated SFRA curves with experimental results, enhancing diagnostic accuracy. • Simulation and Experimental Validation: Combines simulation with experimental methods to validate the SFRA measurements, enhancing the reliability of the diagnostic technique. • Accuracy and Validation: Utilizes statistical indicators such as the correlation coefficient and the absolute sum of logarithmic error to verify the accuracy of the SFRA signatures. • Practical Applications: Demonstrates the practical application of the method on two induction motors with varying horsepower, showcasing its versatility across different motor specifications. Three-phase induction motor (TPIM) is one of the most important and expensive component in many industries. If a failure happens in service, the impact can be far reaching. Resulting in prolonged downtimes and expensive repairs. Sweep frequency response analysis (SFRA) is a new method that is being proposed to assess the condition of windings in motors. This paper proposes an approach for measuring the SFRA of the TPIMs using its high frequency (HF) circuit model. It also introduces an easy and efficient way to estimate the parameter values of the HF model based on the data from the SFRA test. The method first simulates the HF model and then aligns the simulated SFRA curve with the experimental one by adjusting the parameter values. This adjustment is based on individual parameter effects on the SFRA signature. The aim of this paper is to understand the SFRA signatures of TPIMs by using both experimental and simulation methods. SFRA measurements are carried out on two TPIMs (1 HP and 3 HP) under the same phases (U 1 U 2 , V 1 V 2 , W 1 W 2 ) and different phase connections (U 1 V 1 , U 1 W 1 , V 1 W 1 ). This paper utilizes two statistical indicators, Absolute Sum of Logarithmic Error (ASLE) and Correlation Coefficient (CC), for interpreting SFRA signatures. The CC values, ranging from 0.98 to 0.99, and the ASLE values, between 0.4 and 1.5 dB, indicate a good agreement between the measured and simulated SFRA signatures. This validates that the proposed HF model is accurate and can be applied to SFRA measurements for any rating of TPIM. This accuracy is verified in this paper using two different rating TPIMs.