Download or read book In belt Vibration Monitoring of Conveyor Idlers and Using Wavelet Package Decomposition and Artificial Intelligence for Early Fault Detection written by Willem Abraham Roos and published by . This book was released on 2017 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Conveyor systems make use of idlers that support the belt and its payload as it is circulated. These idlers have bearings to ensure lower friction between the idlers and the belt. These bearings do become contaminated with dust and dirt and bearings tend to fail or even seize, adding unwanted strain and stress on the belt. These idlers are monitored and replaced when needed to minimize the damage to the belt. There are several methods used to monitor the condition of the idlers. Thermal cameras are used to identify failing bearings that tend to run hotter than healthy bearings. Acoustic equipment exist that can capture the sound produced by the idler and processes it to indicate whether an idler is still working properly or when it is failing. These methods require an operator to travel the length of the belt, monitoring the idlers along the way. Vibrations have been used, with great success, to monitor idlers. An accelerometer is attached to the structure of the conveyor and the vibration signals are processed and from this a possible failing idler can be identified, either by an operator or an automated artificial intelligence system. However, the sensor can only monitor a few idlers close by and the cost of installing accelerometers along the entire length of a conveyor does make such a system infeasible. A method of using an accelerometer attached to the moving belt that travels over the idlers is investigated in this study. The vibration signals of the idler are captured as the accelerometer passes it and are then analyzed and used in a decision making system to identify and classify the idler bearing conditions. The accelerometer is attached at different positions across the width of the belt to investigate the possibility of only using one or two sensors to monitor all the bearings of the idlers across the width of the conveyor. Healthy bearings are tested against bearings with inner raceway, outer raceway and rolling element defects. Contaminated bearings are tested as well. Wavelet package decomposition is used to extract the bearing features and presents it to the intelligent decision making system. Neural networks and support vector machines are used with great success to identify and classify faulty bearings. The support vector machine monitoring system has a 100% accuracy in identifying and classifying faulty bearings, regardless of the sensor position and even when a localized payload is added. The system could not only identify a faulty bearing, but also classify the fault with 100% accuracy. These accuracies were obtained in a controlled experimental environment with a simplified test setup. The self-developed data acquisitioning system costs as much as one meter of steel reinforced rubber belt. There are some improvements needed before it could be implemented into a working conveyor, adding to the cost. A working in-belt idler monitoring system is not only plausible, but will be affordable as well.

Download or read book In belt Vibration Monitoring of Conveyor Idler Bearings by Using Wavelet Package Decomposition and Artificial Intelligence written by W. A. Roos and published by . This book was released on with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Condition Monitoring with Vibration Signals written by Hosameldin Ahmed and published by John Wiley & Sons. This book was released on 2020-01-07 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Early Fault Detection and Optimal Maintenance Control for Partially Observable Systems Subject to Vibration Monitoring written by Chen Lin and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Fault Detection of Spur Gears Using Vibration Monitoring written by Anand Parey and published by LAP Lambert Academic Publishing. This book was released on 2010-11 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gears are one of the most common and important machine components in many rotating machines. Gears my fail in many different ways and can be broadly classified as localized (e.g. pitting, spalls and crack etc.) and distribute defects (e.g. profile errors, surface roughness etc.). An early detection of incipient gear failure is required to achieve high reliability and to prevent breakdown. Gear failure can be predicted by measuring the changes in vibration level. Dynamic modeling of the gear vibration is a useful tool to study the vibration response of a geared system under various gear parameters and operating conditions. Defects can be simulated in the dynamic model to see its effects on vibration response. The vibration signal stemming from a gear pair is complex in nature. Therefore, a suitable signal processing technique is necessary to extract defect information covered under noise.

Download or read book Bulk Material Belt Conveyor Troughing and Return Idlers written by Conveyor Equipment Manufacturers Association. Engineering Conference. The Idler Committee and published by . This book was released on 2001 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dimensional standards and selection guidelines for 20-degree, 35-degree, and 45-degree troughing idlers and return rollers as well as 10-degree and 15-degree vee returns.

Download or read book Intelligent Belt Conveyor Monitoring and Control written by Yusong Pang and published by . This book was released on 2010 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Application of Signal Processing and Artificial Intelligence Techniques in the Condition Monitoring of Rotating Machinery written by Nicolaas Theodor Van der Merwe and published by . This book was released on 2003 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Early Fault Detection for Gear Shaft and Planetary Gear Based on Wavelet and Hidden Markov Modeling written by Jing Yu and published by . This book was released on 2011 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fault detection and diagnosis of gear transmission systems have attracted considerable attention in recent years, due to the need to decrease the downtime on production machinery and to reduce the extent of the secondary damage caused by failures. However, little research has been done to develop gear shaft and planetary gear crack detection methods based on vibration signal analysis. In this thesis, an approach to gear shaft and planetary gear fault detection based on the application of the wavelet transform to both the time synchronously averaged (TSA) signal and residual signal is presented. Wavelet approaches themselves are sometimes inefficient for picking up the fault signal characteristic under the presence of strong noise. In this thesis, the autocovariance of maximal energy wavelet coefficients is first proposed to evaluate the gear shaft and planetary gear fault advancement quantitatively. For a comparison, the advantages and disadvantages of some approaches such as using variance, kurtosis, the application of the Kolmogorov-Smirnov test (K-S test), root mean square (RMS) , and crest factor as fault indicators with continuous wavelet transform (CWT) and discrete wavelet transform (DWT) for residual signal, are discussed. It is demonstrated using real vibration data that the early faults in gear shafts and planetary gear can be detected and identified successfully using wavelet transforms combined with the approaches mentioned above.In the second part of the thesis, the planetary gear deterioration process from the new condition to failure is modeled as a continuous time homogeneous Markov process with three states: good, warning, and breakdown. The observation process is represented by two characteristics: variance and RMS based on the analysis of autocovariance of DWT applied to the TSA signal obtained from planetary gear vibration data. The hidden Markov model parameters are estimated by maximizing the pseudo likelihood function using the EM iterative algorithm. Then, a multivariate Bayesian control chart is applied for fault detection. It can be seen from the numerical results that the Bayesian chart performs better than the traditional Chi-square chart.

Download or read book Examination of Wavelet Transforms for Early Detection of Failure in Gears by Vibration Analysis written by Zhi-Yan Xie and published by . This book was released on 1996 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Development of an Intelligent System for Vibration based Predictive Maintenance written by Mohammed Abdul Qawi Zaid and published by . This book was released on 2014 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: A machine in the best of operating condition will have some vibration because of small, minor defects. The use of the human sense of touch and feel for observation is somewhat limited, and there are many common problems that are generally out of the range of human senses. Vibration monitoring is a widely used and cost effective monitoring technique. It detects, locates, and distinguishes faults in rotating machineries. It is an established process used in predictive maintenance as it is necessary to diagnose faults in machine at early stages to prevent failure during operation. In this research an intelligent method to detect faults in rotating machineries by analyzing vibration signals was developed. The faults that can be detected are some of the most common faults in rotating machineries. An experimental set-up was designed and fabricated to observe the signals generated when it is in normal working condition and when it is in faulty condition. The components whose vibration signatures were observed are rotor disk and motor. The faulty rotor disk, mechanical looseness, and fault motor vibration signatures were studied. Four features from vibration signals for various faults were extracted in the time domain. They are Root Mean Square (RMS), crest factor, kurtosis, and skewness. These features are mapped against the respective faults using a multilayer feed forward artificial neural network. The network was trained using Levenberg-Marquardt algorithm. The simulated faults condition signal were analyzed and compared to normal condition signals. The analysis of the fault signature shows that fault conditions in the system are detected for the various components. In this research, the developed artificial neural network is able to detect the faulty conditions. The trained neural network can classify different condition with 92.5% accuracy and the precision is 0.9. For further research, it is suggested that the artificial neural network be trained to detect more inherent faults in the system components.

Download or read book Incipient Failure Detection Using Wavelets written by and published by . This book was released on 1992 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt: This project demonstrated the feasibility of incipient fault detection for vibrating systems not only for bench test conditions (helicopter gearbox) but also for mild operating conditions (condensate and fire pumps). We employed only one of the several available data channels from the multiple accelerometers mounted on the case of each equipment type. We used a continuous wavelet transform (CWT), based on the Kiang wavelet, to select features for an artificial neural network (ANN) classifier. The CWT provided enough visibility into the fault signals to allow us to reduce the size of the feature set to 10 - 15 features. We used a low-dimensional, conventional ANN classifier with rejection of ambiguous classifications. We achieved 0.000 probability of false alarm, 0.000 probability of missed detection, and

Download or read book Machinery Prognostics and Prognosis Oriented Maintenance Management written by Jihong Yan and published by John Wiley & Sons. This book was released on 2015-02-02 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a complete presentatin of the basic essentials of machinery prognostics and prognosis oriented maintenance management, and takes a look at the cutting-edge discipline of intelligent failure prognosis technologies for condition-based maintenance. Presents an introduction to advanced maintenance systems, and discusses the key technologies for advanced maintenance by providing readers with up-to-date technologies Offers practical case studies on performance evaluation and fault diagnosis technology, fault prognosis and remaining useful life prediction and maintenance scheduling, enhancing the understanding of these technologies Pulls togeter recent developments and varying methods into one volume, complemented by practical examples to provide a complete reference

Download or read book Materials Design and Manufacturing for Sustainable Environment written by Santhakumar Mohan and published by Springer Nature. This book was released on 2021-02-06 with total page 909 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprises the select proceedings of the International Conference on Materials, Design and Manufacturing for Sustainable Environment (ICMDMSE 2020). The primary focus is on emerging materials and cutting-edge manufacturing technologies for sustainable environment. The book covers a wide range of topics such as advanced materials, vibration, tribology, finite element method (FEM), heat transfer, fluid mechanics, energy engineering, additive manufacturing, robotics and automation, automobile engineering, industry 4.0, MEMS and nanotechnology, optimization techniques, condition monitoring, and new paradigms in technology management. Contents of this book will be useful to students, researchers, and practitioners alike.

Download or read book Symmetry in Mechanical Engineering written by Adam Glowacz and published by MDPI. This book was released on 2020-06-03 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advancements in mechanical engineering are an essential topic for discussion. The topics relating to mechanical engineering include the following: measurements of signals of shafts, springs, belts, bearings, gears, rotors, machine elements, vibration analysis, acoustic analysis, fault diagnosis, construction, analysis of machine operation, analysis of smart-material systems, integrated systems, stresses, analysis of deformations, analysis of mechanical properties, signal processing of mechanical systems, and rotor dynamics. Mechanical engineering deals with solid and fluid mechanics, rotation, movements, materials, and thermodynamics. This book, with 15 published articles, presents the topic “Symmetry in Mechanical Engineering”. The presented topic is interesting. It is categorized into eight different sections: Deformation; Stresses; Mechanical properties; Tribology; Thermodynamic; Measurement; Fault diagnosis; Machine. The development of techniques and methods related to mechanical engineering is growing every month. The described articles have made a contribution to mechanical engineering. The proposed research can find applications in factories, oil refineries, and mines. It is essential to develop new improved methods, techniques, and devices related to mechanical engineering.

Download or read book Proceedings of the 5th International Conference on Industrial Engineering ICIE 2019 written by Andrey A. Radionov and published by Springer Nature. This book was released on 2019-11-14 with total page 1449 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights recent findings in industrial, manufacturing and mechanical engineering, and provides an overview of the state of the art in these fields, mainly in Russia and Eastern Europe. A broad range of topics and issues in modern engineering are discussed, including the dynamics of machines and working processes, friction, wear and lubrication in machines, surface transport and technological machines, manufacturing engineering of industrial facilities, materials engineering, metallurgy, control systems and their industrial applications, industrial mechatronics, automation and robotics. The book gathers selected papers presented at the 5th International Conference on Industrial Engineering (ICIE), held in Sochi, Russia in March 2019. The authors are experts in various fields of engineering, and all papers have been carefully reviewed. Given its scope, the book will be of interest to a wide readership, including mechanical and production engineers, lecturers in engineering disciplines, and engineering graduates.

Download or read book Machine Vision for the Inspection of Natural Products written by Mark Graves and published by Springer Science & Business Media. This book was released on 2003-11-20 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine vision technology has revolutionised the process of automated inspection in manufacturing. The specialist techniques required for inspection of natural products, such as food, leather, textiles and stone is still a challenging area of research. Topological variations make image processing algorithm development, system integration and mechanical handling issues much more complex. The practical issues of making machine vision systems operate robustly in often hostile environments together with the latest technological advancements are reviewed in this volume. Features: - Case studies based on real-world problems to demonstrate the practical application of machine vision systems. - In-depth description of system components including image processing, illumination, real-time hardware, mechanical handling, sensing and on-line testing. - Systems-level integration of constituent technologies for bespoke applications across a variety of industries. - A diverse range of example applications that a system may be required to handle from live fish to ceramic tiles. Machine Vision for the Inspection of Natural Products will be a valuable resource for researchers developing innovative machine vision systems in collaboration with food technology, textile and agriculture sectors. It will also appeal to practising engineers and managers in industries where the application of machine vision can enhance product safety and process efficiency.