Condition monitoring

About: Condition monitoring is a research topic. Over the lifetime, 13911 publications have been published within this topic receiving 201649 citations.

Vibration feature extraction techniques for fault diagnosis of rotating machinery : a literature survey

Abstract: The safety, reliability, efficiency and performance of rotating machinery are major concerns in industry. The task of condition monitoring and fault diagnosis of rotating machinery faults is significant but is often cumbersome and labour intensive. Effective and efficient feature extraction techniques are critical for reliably diagnosing rotating machinery faults. Various vibration feature extraction methods have been proposed for different types of rotating machinery during the past few decades. However, limited research has been conducted on synthesizing and analysing these techniques, resulting in apprehension when technicians need to choose a technique suitable for application. This paper presents an updated review of a variety of vibration feature extraction techniques that have demonstrated success when applied to rotating machinery. The literature is categorised into the following groups: time domain, frequency domain, time frequency analysis. The paper will comment on future directions for research on vibration feature extraction for fault diagnosis of rotating machinery.

A Symbolic Representation Approach for the Diagnosis of Broken Rotor Bars in Induction Motors

Abstract: One of the most common deficiencies of currently existing induction motor fault diagnosis techniques is their lack of automatization. Many of them rely on the qualitative interpretation of the results, a fact that requires significant user expertise, and that makes their implementation in portable condition monitoring devices difficult. In this paper, we present an automated method for the detection of the number of broken bars of an induction motor. The method is based on the transient analysis of the start-up current using wavelet approximation signal that isolates a characteristic component that emerges once a rotor bar is broken. After the isolation of this component, a number of stages are applied that transform the continuous-valued signal into a discrete one. Subsequently, an intelligent icon-like approach is applied for condensing the relative information into a representation that can be easily manipulated by a nearest neighbor classifier. The approach is tested using simulation as well as experimental data, achieving high-classification accuracy.

A fault detection method for railway point systems

Abstract: Failures of railway point systems (RPSs) often lead to service delays or hazardous situations. A condition monitoring system can be used by railway infrastructure operators to detect the early signs of the deteriorated condition of RPSs and thereby prevent failures. This paper presents a methodology for early detection of the changes in the measurement of the current drawn by the motor of the point operating equipment (POE) of an RPS, which can be used to warn about a possible failure in the system. The proposed methodology uses the one-class support vector machine classification method with the similarity measure of edit distance with real penalties. The technique has been developed taking into account specific features of the data of infield RPSs and therefore is able to detect the changes in the measurements of the current of the POE with greater accuracy compared with the commonly used threshold-based technique. The data from infield RPSs, which relate to incipient failures of RPSs, were used after the deficiencies in the data labelling were removed using expert knowledge. In addition, possible improvements in the proposed methodology were identified in order for it to be used as an automatic online condition monitoring system.

A Comprehensive Review of Condition Based Prognostic Maintenance (CBPM) for Induction Motor

Abstract: This paper presents condition monitoring aspects of induction motor, its present status with possible mitigation schemes and future maintenance challenges. The induction motors constitute the major portion of motors in domestic and industrial applications. These motors experience different types of failures and faults associated with insulation, bearing, stator, rotor, and eccentricity. As a matter of fact, these faults may subsequently enhance the probability of failures unless proper introspection is not accomplished. In order to reduce the failure time and operating cost, early detection is indispensable which necessitates condition-based approach on contrary to scheduled maintenance. The condition monitoring is a strong candidate to address the diagnosis of machinery failure problems and unreliability. In this context, a comprehensive analysis is reported in the literature with a focus on different methodologies being addressed for such objective. Utmost efforts are made to comprehensively analyze in the reported literature in a sequential manner citing the advantage and limitations in this paper. The authors hopefully described and illustrated the associated problems with possible mitigation in the context of condition monitoring which would be immensely helpful for future researchers working in these aspects and the future roadmap would be clearly reflected.