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Predictive Maintenance strategy employs vibration analysis, thermography analysis, ultrasound analysis, oil analysis and other techniques to improve machine reliability. The goal of the strategy is to provide the stated function of the facility, with the required reliability and availability at the lowest cost.
Consider a Viable and Cost-Effective Platform for the Industries of the Future (IOF)Benefit from improved safety, performance, and product deliveries to your customers. Achieve a higher rate of equipment availability, performance, product quality, and reliability. Integrated Reliability: Condition Monitoring and Maintenance of Equipment incorporate
Provides an extensive, up-to-date treatment of techniques used for machine condition monitoring Clear and concise throughout, this accessible book is the first to be wholly devoted to the field of condition monitoring for rotating machines using vibration signals. It covers various feature extraction, feature selection, and classification methods as well as their applications to machine vibration datasets. It also presents new methods including machine learning and compressive sampling, which help to improve safety, reliability, and performance. Condition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines starts by introducing readers to Vibration Analysis Techniques and Machine Condition Monitoring (MCM). It then offers readers sections covering: Rotating Machine Condition Monitoring using Learning Algorithms; Classification Algorithms; and New Fault Diagnosis Frameworks designed for MCM. Readers will learn signal processing in the time-frequency domain, methods for linear subspace learning, and the basic principles of the learning method Artificial Neural Network (ANN). They will also discover recent trends of deep learning in the field of machine condition monitoring, new feature learning frameworks based on compressive sampling, subspace learning techniques for machine condition monitoring, and much more. Covers the fundamental as well as the state-of-the-art approaches to machine condition monitoringguiding readers from the basics of rotating machines to the generation of knowledge using vibration signals Provides new methods, including machine learning and compressive sampling, which offer significant improvements in accuracy with reduced computational costs Features learning algorithms that can be used for fault diagnosis and prognosis Includes previously and recently developed dimensionality reduction techniques and classification algorithms Condition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines is an excellent book for research students, postgraduate students, industrial practitioners, and researchers.
Predictive Maintenance strategy employs vibration analysis, thermography analysis, ultrasound analysis, oil analysis and other techniques to improve machine reliability. The goal of the strategy is to provide the stated function of the facility, with the required reliability and availability at the lowest cost.
Hardbound. The need to reduce costs has generated a greater interest in condition monitoring in recent years. The Handbook of Condition Monitoring gives an extensive description of available products and their usage making it a source of practical guidance supported by basic theory.This handbook has been designed to assist individuals within companies in the methods and devices used to monitor the condition of machinery and products.
Machinery Vibration Analysis and Predictive Maintenance provides a detailed examination of the detection, location and diagnosis of faults in rotating and reciprocating machinery using vibration analysis. The basics and underlying physics of vibration signals are first examined. The acquisition and processing of signals is then reviewed followed by a discussion of machinery fault diagnosis using vibration analysis. Hereafter the important issue of rectifying faults that have been identified using vibration analysis is covered. The book also covers the other techniques of predictive maintenance such as oil and particle analysis, ultrasound and infrared thermography. The latest approaches and equipment used together with the latest techniques in vibration analysis emerging from current research are also highlighted. - Understand the basics of vibration measurement - Apply vibration analysis for different machinery faults - Diagnose machinery-related problems with vibration analysis techniques
The laboratory examination of a lubricant's characteristics, suspended impurities, and wear debris is known as oil analysis (OA). OA is carried out as part of regular predictive maintenance to deliver precise and useful data on lubricant and machine condition. Trends can be found by following the findings of oil analysis samples over the course of a certain machine. These trends can help avoid expensive repairs. Tribology is the study of wear in machinery. Tribologists frequently perform or interpret results from oil analyses. Oil analysis is a long-term program that, where relevant, can eventually be more predictive than any of the other technologies. It can take years for a plant's oil program to reach this level of sophistication and effectiveness. This book includes what all practitioners need to know to build an oil analysis program for their machine inspection. This book includes three real case studies and numerous industrial examples to improve machine reliability and enhance the condition monitoring program.
In today's competitive climate the economies of production have become a critical factor for all manufacturing companies. For this reason, achieving cost-effective plant maintenance is highly important. In this context monitoring plays a vital role. The purpose of this book is to inform readers about techniques currently available in the field of condition monitoring, and the methodology used in their application. With contributions from experts throughout the world, the Handbook of Condition Monitoring addresses the four major technique areas in condition monitoring in addition to the latest developments in condition monitoring research. Significantly, the Handbook of Condition Monitoring includes the following features: comprehensive coverage of the full range of techniques and methodologies accepted knowledge and new developments both technical and managerial content. This is the essential reference book for maintenance technicians, engineers, managers and researchers as well as graduate students involved in manufacturing and mechanical engineering, and condition monitoring.
Condition monitoring is the process of keeping an eye on a machine's condition parameter in order to spot any major changes that could be signs of a malfunction developing. It plays a significant role in preventive maintenance and is a major component of predictive maintenance. By combining machine sensor data that detects vibration and other characteristics (in real-time) with cutting-edge machine monitoring software, condition monitoring (CM), a maintenance strategy, anticipates machine health and safety. Predictive Maintenance strategy employs vibration analysis, thermography analysis, ultrasound analysis, oil analysis and other techniques to improve machine reliability. The goal of the strategy is to provide the stated function of the facility, with the required reliability and availability at the lowest cost.