A new method for three-phase induction motor fault diagnosis using impedance analysis and advanced signal processing techniques

• Grant number: 21/09685-2
• Support type: Scholarships in Brazil - Doctorate
• Effective date (Start): April 01, 2022
• Effective date (End): February 28, 2025
• Field of knowledge: Engineering - Electrical Engineering
• Principal researcher: André Luiz Andreoli
• Grantee: Guilherme Beraldi Lucas
• Home Institution: Faculdade de Engenharia (FE). Universidade Estadual Paulista (UNESP). Campus de Bauru. Bauru , SP, Brazil

Abstract

Three-phase induction motors (TIM) are equipment used to drive a significant portion of industrial loads, such as conveyors, fans, compressors, and many others. Therefore, an eventual interruption in the operation of an MIT in a production line will result in a high operational and financial cost. However, these machines are often exposed to mechanical and electrical faults that can lead from minor damage to total failure. This obstacle has resulted in scientific interest in the development of solutions for diagnosing these failures. The most usual methods in this area analyze the variables related to TIMS, such as vibration, acoustic emission, current, and electromagnetic flux. Although, in the presence of some types of abnormalities, the impedance value of the TIM coils is modified. Thus, this project presents a new method for detecting and classifying faults in TIMS by measuring the impedance of the motor windings. The measurement will be performed by a circuit that injects variable frequency signals into the machine's electrical supply and acquires voltage signals. The application of this method does not depend on the attachment of sensors to the motor, avoiding installation failures and mechanical wearing problems. In addition, the components of the measurement circuit are simple and low cost (resistors, capacitors, and amplifiers). Furthermore, this method can be applied while the machine is in full operation, resulting in a new non-invasive technique (NIT) for fault monitoring. Finally, the application of this method, unprecedented in previously published papers, will represent a solid contribution to the field and a breakthrough for failure diagnosis techniques in TIMS.