Jangho Yun

Detection and Classification of Stator Turn Faults and High Resistance Electrical Connections for Induction Machines

The goal of stator winding turn fault detection is to detect the fault at an early stage, and shut down the machine immediately to prevent catastrophic motor failure due to the large fault current. A number of turn fault detection techniques have been proposed; however, there is currently no method available for distinguishing turn faults from high-resistance(R) connections, which also result in 3 phase system asymmetry. It is important to distinguish the two faults since a high-R connection does not necessarily require immediate motor shutdown. In this paper, new sensorless on-line monitoring techniques for detecting and classifying stator turn faults and high-R electrical connections in induction machines based on the zero sequence voltage or negative sequence current measurements are proposed. An experimental study on a 10 hp induction motor performed under simulated turn faults and high-resistance circuit conditions verifies that the two faults can be reliably detected and classified. The proposed technique helps improve the reliability, efficiency, and safety of the motor system and industrial plant, and also allows maintenance to be performed in a more efficient manner since the course of action can be determined based on the type and severity of the fault.

Online Detection of High-Resistance Connections in the Incoming Electrical Circuit for Induction Motors

High-resistance(R) connections in the induction motor electrical circuit result in localized overheating and supply voltage unbalance, which leads to decreased efficiency, reliability, and increased fire hazard in the electrical distribution system and motor. Therefore, it is important to monitor and correct high-R connections for reliable, efficient, and safe operation of the industrial facility. This paper focuses on the development of a sensorless on-line technique for detecting poor connections based on monitoring the asymmetry in the electrical circuit. The development of the technique begins with the derivation of the dynamic model of an induction motor with high-R connections. Based on the analysis of the model, two approaches for detecting poor contacts using the negative sequence current and zero sequence voltage are proposed. In addition to detecting the existence of faults, the location and severity of the fault can also be determined using the proposed method. An experimental study on a 10 hp induction machine under simulated and realistic high- R conditions shows that the proposed techniques provide a simple low cost solution for reliably detecting poor contact problems at an early stage. It is also shown that the severity and location of the high-R contact fault can be assessed with high accuracy.

A New Strategy for Condition Monitoring of Adjustable Speed Induction Machine Drive Systems

A new strategy for monitoring the condition of adjustable speed induction machine drive systems is presented in this paper. The main concept of the new method is to use the inverter to perform off-line tests for quality assessment of the vulnerable components in the inverter, cable, and induction motor automatically whenever the motor is stopped. This new approach is suitable for monitoring system components that deteriorate gradually to failure, if the degradation is observable. Off-line test methods for monitoring the quality of the 1) dc-link aluminum electrolytic capacitor; 2) electrical connections; 3) cable and stator winding insulation; 4) stator core; and 5) rotor bar are presented along with a summary of the failure mechanism and existing test methods. It will be shown that the new strategy can be implemented with minimal hardware requirements, and that it has many advantages over existing off-line and on-line tests. An experimental study performed under simulated fault conditions for each component shows that the method provides a reliable and sensitive indication of drive system problems for reliable, efficient, and safe operation.

Automated Monitoring of High-Resistance Connections in the Electrical Distribution System of Industrial Facilities

High-resistance(R) connections due to poor contacts in the electrical distribution system can cause failures due to overheating, reduce efficiency, and pose safety risks in the industrial facility. The methods currently available for detection of high-R connections such as infrared thermography, resistance or voltage unbalance tests are inconvenient since they are off-line or walk-around type tests that do not provide continuous monitoring. In this paper, an automated technique for detecting high-R connections based on existing voltage and current measurements is proposed. The contact resistance, RHR, of the poor contact is estimated based on the voltage and current variation under startup and/or shutdown of the load for monitoring problems located upstream from the point of voltage measurement. For downstream problems, RHR is estimated based on the negative sequence current under steady state operation of the load. An experimental study on a 10hp induction motor load performed under simulated high-R circuit conditions verifies that poor contacts that exist upstream and downstream can be reliably detected without additional measurements. It is shown that the proposed technique can provide automated monitoring of the existence, location, and severity of high-R contacts for reliable, efficient, and safe operation of the industrial facility.

A new strategy for condition monitoring of adjustable speed induction machine drive systems

A new strategy for monitoring the condition of adjustable speed induction machine drive systems is presented in this paper. The main concept of the new method is to use the inverter to perform off-line tests for quality assessment of the vulnerable components in the inverter, cable, and induction motor automatically whenever the motor is stopped. This new approach is suitable for monitoring system components that deteriorate gradually to failure, if the degradation is observable. Off-line test methods for monitoring the quality of the 1) dc-link aluminum electrolytic capacitor; 2) electrical connections; 3) cable and stator winding insulation; 4) stator core; and 5) rotor bar are presented along with a summary of the failure mechanism and existing test methods. It will be shown that the new strategy can be implemented with minimal hardware requirements, and that it has many advantages over existing off-line and on-line tests. An experimental study performed under simulated fault conditions for each component shows that the method provides a reliable and sensitive indication of drive system problems for reliable, efficient, and safe operation.

Influence of Die-Cast Rotor Fill Factor on the Starting Performance of Induction Machines

One of the most important requirements for low-voltage induction motor designers is to meet the customer-specified starting characteristics and international regulations on efficiency. Although porosity in die-cast rotors degrade motor performance, the fill factor (FF) of the rotor bar and end ring are usually assumed to be 100 in the design stage. If the influence of FF is not properly taken into account in the design, it results in an inaccurate prediction of the starting performance. In this paper, the influence of die-cast rotor FF on the starting torque is investigated based on the FF and porosity distributions measured from actual aluminum die-cast rotors. A simplified 3-D finite-element analysis model that accounts for the porosity distribution in bars and end rings for different FFs is presented for predicting the starting characteristics. The effectiveness of the proposed method is verified on a 440 V, 15 kW induction motor prototype with rotors with FF of 93% and 67%. The results show that porosity has a significant influence on the starting torque, and must be taken into account for reliable prediction of motor performance for design optimization.

Off-line flux injection test probe for screening defective rotors in squirrel cage induction machines

The recent trend in squirrel cage induction motor manufacturing is to replace fabricated copper rotors with aluminum die-cast rotors to reduce manufacturing cost to stay competitive in the global market. Porosity in aluminum die-cast squirrel cage rotors is inevitably introduced during the die cast process. Porosity can cause degradation in motor performance and can lead to a forced outage causing irreversible damage if it is extreme. Many off-line and on-line quality assurance test methods have been developed and applied for assessment of rotor quality. However, years of experience with the existing test methods revealed that they are not suitable for quality testing or capable of providing a quantitative assessment of rotor condition with sufficient sensitivity. In this paper, a new off-line test method capable of providing sensitive assessment of rotor porosity is proposed. It is shown that rotors with minor and distributed porosity that are difficult to detect with other tests can be screened out during manufacturing. The proposed method is verified through a 3 dimensional finite element analysis and experimental testing on closed and semi-open slot aluminum die cast rotors of 5.5 kW induction motors with porosity.

A simplified approach for predicting the starting performance of induction machines based on rotor design modification

The starting characteristics of induction motors, largely determined by the rotor design, is a critical design factor from an end-users’ perspective. The equivalent circuit model or finite element analysis (FEA) is most commonly used by motor manufacturers for the design to meet the specified starting performance, but is inaccurate or time-consuming. In this paper, a simplified approach for predicting the starting characteristics based on the equivalent circuit model and single-slot pitch 2-D and 3-D FEA is proposed. The influence of the radial cooling ducts, end bar extension, deep bar/skin effects, and magnetic saturation are taken into account for the accurate prediction of starting performance. The results of the proposed method are compared with conventional methods and verified through experimental testing on 6.6 kV and 522 kW induction motors. The results show that the proposed method is capable of providing fast prediction of the starting characteristics for the given rotor design without sacrificing accuracy.