Condition Based Maintenance And Residual Life Prediction
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Condition-Based Maintenance and Residual Life Prediction
Author: Chandan Deep Singh
language: en
Publisher: John Wiley & Sons
Release Date: 2025-04-15
Condition-Based Maintenance and Residual Life Prediction is essential for those looking to effectively implement condition-based maintenance strategies and enhance fault detection through a comprehensive understanding of vibration data analysis and residual life prediction, addressing key challenges in the field. Issues related to condition-based maintenance include its high initial cost, new techniques that can be difficult to implement due to resistance, older equipment that can be difficult to retrofit with sensors and monitoring equipment, and difficult-to-access equipment during production that is difficult to spot-measure. Keeping the above issues in mind, a general handbook for condition-based maintenance and residual life prediction is required to carry out in fault detection. Condition-Based Maintenance and Residual Life Prediction aims to develop, analyze, and model condition-based maintenance and residual life prediction through vibration data. The analysis of vibration responses will aid in developing a fault detection system. The sources of vibration may be due to the presence of different types of defects, such as cracks in the shaft, a bent shaft, or misalignment of shafts. This will give designers a diagnostic tool for predicting the trends of vibration conditions, leading to early fault detection. The devised tool will be capable of quantifying the amplitude of vibration based on the severity of defects. With the features available in the devised diagnostic tool, the proposed model can be used for design, predictive maintenance, and condition-based maintenance.
Condition-Based Maintenance and Residual Life Prediction
Author: Chandan Deep Singh
language: en
Publisher: John Wiley & Sons
Release Date: 2025-03-10
Condition-Based Maintenance and Residual Life Prediction is essential for those looking to effectively implement condition-based maintenance strategies and enhance fault detection through a comprehensive understanding of vibration data analysis and residual life prediction, addressing key challenges in the field. Issues related to condition-based maintenance include its high initial cost, new techniques that can be difficult to implement due to resistance, older equipment that can be difficult to retrofit with sensors and monitoring equipment, and difficult-to-access equipment during production that is difficult to spot-measure. Keeping the above issues in mind, a general handbook for condition-based maintenance and residual life prediction is required to carry out in fault detection. Condition-Based Maintenance and Residual Life Prediction aims to develop, analyze, and model condition-based maintenance and residual life prediction through vibration data. The analysis of vibration responses will aid in developing a fault detection system. The sources of vibration may be due to the presence of different types of defects, such as cracks in the shaft, a bent shaft, or misalignment of shafts. This will give designers a diagnostic tool for predicting the trends of vibration conditions, leading to early fault detection. The devised tool will be capable of quantifying the amplitude of vibration based on the severity of defects. With the features available in the devised diagnostic tool, the proposed model can be used for design, predictive maintenance, and condition-based maintenance.
Residual Life Prediction and Optimal Maintenance Decision for a Piece of Equipment
This book addresses remaining life prediction and predictive maintenance of equipment. It systematically summarizes the key research findings made by the author and his team and focuses on how to create equipment performance degradation and residual life prediction models based on the performance monitoring data produced by currently used and historical equipment. Some of the theoretical results covered here have been used to make remaining life predictions and maintenance-related decisions for aerospace products such as gyros and platforms. Given its scope, the book offers a valuable reference guide for those pursuing theoretical or applied research in the areas of fault diagnosis and fault-tolerant control, remaining life prediction, and maintenance decision-making.