Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives (Hardcover)

Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives

An insightful treatment of present and emerging technologies in fault diagnosis and failure prognosis

In Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives, a team of distinguished researchers delivers a comprehensive exploration of current and emerging approaches to fault diagnosis and failure prognosis of electrical machines and drives. The authors begin with foundational background, describing the physics of failure, the motor and drive designs and components that affect failure and signals, signal processing, and analysis.

The book then moves on to describe the features of these signals and the methods commonly used to extract these features to diagnose the health of a motor or drive, as well as the methods used to identify the state of health and differentiate between possible faults or their severity.

Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives discusses the tools used to recognize trends towards failure and the estimation of remaining useful life. It addresses the relationships between fault diagnosis, failure prognosis, and fault mitigation.

The book also provides:

• A thorough introduction to the modes of failure, how early failure precursors manifest themselves in signals, and how features extracted from these signals are processed
• A comprehensive exploration of the fault diagnosis, the results of characterization, and how they used to predict the time of failure and the confidence interval associated with it
• A focus on medium-sized drives, including induction, permanent magnet AC, reluctance, and new machine and drive types

Perfect for researchers and students who wish to study or practice in the rea of electrical machines and drives, Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives is also an indispensable resource for researchers with a background in signal processing or statistics.

《電機與驅動器的故障診斷、預測和可靠性》

《電機與驅動器的故障診斷、預測和可靠性》是一本關於電機與驅動器故障診斷和故障預測的現有和新興技術的深入探討。一群傑出的研究人員提供了對電機與驅動器故障診斷和故障預測的當前和新興方法的全面探索。作者們首先介紹了基礎背景，描述了故障的物理原理、影響故障和信號的馬達和驅動器設計和組件、信號處理和分析。

接下來，本書描述了這些信號的特徵以及常用的提取這些特徵來診斷馬達或驅動器健康狀況的方法，以及用於識別健康狀態並區分可能的故障或其嚴重程度的方法。

《電機與驅動器的故障診斷、預測和可靠性》討論了識別故障趨勢和估計剩餘可用壽命的工具。它還探討了故障診斷、故障預測和故障緩解之間的關係。

本書還提供了以下內容：

- 對故障模式的全面介紹，以及早期故障前兆在信號中的表現方式以及從這些信號中提取的特徵的處理方法。
- 對故障診斷的全面探索，包括特徵的表徵結果以及如何用於預測故障時間和相關的置信區間。
- 對中型驅動器的重點介紹，包括感應、永磁交流、磁阻和新型機器和驅動器類型。

這本書非常適合希望在電機與驅動器領域進行研究或實踐的研究人員和學生，對於具有信號處理或統計學背景的研究人員來說，它也是一個不可或缺的資源。

Elias G. Strangas, PhD, is a Professor at Michigan State University, where he heads the Electrical Machines and Drives Laboratory.

Guy Clerc is a Professor at the Université de Lyon, Ampère, in Villeurbanne, France.

Hubert Razik is a Professor at the Université de Lyon, Ampère, in Villeurbanne, France.

Abdenour Soualhi is an Assistant Professor at the LASPI Laboratory in Jean Monnet University Roanne.

Elias G. Strangas, PhD，是密歇根州立大學的教授，他負責電機機器和驅動實驗室。

Guy Clerc是法國里昂安培爾大學的教授。

Hubert Razik是法國里昂安培爾大學的教授。

Abdenour Soualhi是尚蒙內大學LASPI實驗室的助理教授。