fault diagnosis machine
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fault diagnosis machine

Applications of machine learning to machine fault ...

2020-4-1  Intelligent fault diagnosis (IFD) refers to applications of machine learning theories to machine fault diagnosis. This is a promising way to release the contribution from human labor and automatically recognize the health states of machines, thus it has attracted much attention in the last two or three decades.

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Fault Diagnosis of Machines Biswajit Sahoo

2019-3-24  Fault diagnosis is a broad term that addresses mainly three questions. First, find out whether fault is there in the machine or not. If fault is present, next question is to find the location of the fault. Once location of the fault is found, finally, find out the type of fault and its severity.

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Fault Diagnosis Methods Based on Machine Learning and

2021-10-29  With the increase in the installed capacity of wind power systems, the fault diagnosis and condition monitoring of wind turbines (WT) has attracted increasing attention. In recent years, machine learning (ML) has played a crucial role as an emerging technology for fault diagnosis in wind power systems has played a crucial role. Even though ML methods have shown great

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Intelligent Fault Diagnosis of Machines with Small ...

Fig. 1.The process of machine fault diagnosis (MFD) and three strategies for SI-IFD. 在接下来的内容中,第 2 节介绍了研究方法和初始的数据分析。第 3、4、5 节分别从数据增强、特征学习和分类器设计的角度回顾了现有的研究成果。

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Highly Accurate Machine Fault Diagnosis Using Deep ...

2018-8-10  We develop a novel deep learning framework to achieve highly accurate machine fault diagnosis using transfer learning to enable and accelerate the training of deep neural network. Compared with existing methods, the proposed method is faster to train and more accurate. First, original sensor data are converted to images by conducting a Wavelet

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Logical fault diagnosis method of electrical machine

In fault diagnosis, it is primary to determine the diagnosis parameters and the measuring methods. Through the simulating experiments the faults of

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Intelligent fault diagnosis 智能故障诊断 最新方向及成果 ...

2020-4-21  Expert guidance on theory and practice in condition-based intelligent machine fault diagnosis and failure prognosis Intelligent Fault Diagnosis and Prognosis for Engineering Systems gives a complete presentation of basic essentials of fault diagnosis and failure prognosis, and takes a look at the cutting-edge discipline of intelligent fault diagnosis and failure prognosis

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Data Mining for Fault Diagnosis and Machine Learning for ...

2014-4-8  Fault diagnosis is based on pattern identification and classification. The first step in steam turbine fault diagnostics is pattern identification from the measured data. The next step is to interpret what the patterns indicate about the machine, but proper interpretation requires some knowledge about the machine.

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A review on fault detection and diagnosis techniques ...

2020-11-10  For fault diagnosis in an oil-filled transformer, a majority voting based extreme learning machine (ELM) is developed which employs multiple independent ELMs (Zhang and Zhai 2018). Another hybrid voting approach is presented in Zhou et al. ( 2018 ) which combines static weighted voting and cloud similarity measurement algorithm and it is ...

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旋转机械故障诊断公开数据集整理_hustcxl的博客-CSDN博客 ...

2019-4-19  旋转机械故障诊断公开数据集整理众所周知,当下做机械故障诊断研究最基础的就是数据,再先进的方法也离不开数据的检验。笔者通过文献资料收集到如下几个比较常用的数据集并进行整理。鉴于目前尚未见比较全面的数据集整理介绍。数据来自原始研究方,笔者只整理数据获取

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Fault Diagnosis of Machines Biswajit Sahoo

2019-3-24  Fault diagnosis is a broad term that addresses mainly three questions. First, find out whether fault is there in the machine or not. If fault is present, next question is to find the location of the fault. Once location of the fault is found, finally, find out the type of fault and its severity.

Read More
Highly Accurate Machine Fault Diagnosis Using Deep ...

2018-8-10  We develop a novel deep learning framework to achieve highly accurate machine fault diagnosis using transfer learning to enable and accelerate the training of deep neural network. Compared with existing methods, the proposed method is faster to train and more accurate. First, original sensor data are converted to images by conducting a Wavelet transformation to obtain time-frequency ...

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Machinery Fault Diagnosis Guide - Plant Services

2013-9-8  ©2011 PRÜFTECHNIK Condition Monitoring – Machinery Fault Diagnosis. Distributed in the US by LUDECA, Inc. • ludeca . Static Unbalance . S U → m. Static unbalance is caused by an unbalance mass out of the gravity centerline. The static unbalance is seen when the machine is not in operation, the rotor will turn so the unbalance ...

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The Fault Diagnosis of Machine Based on Modal Analysis

Download Citation The Fault Diagnosis of Machine Based on Modal Analysis In the latest two decades, modal analysis has been used in many engineering disciplines and technology fields to solve ...

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Fault diagnosis of rotating machines based on EEMD-MPE

2021-11-9  The EEMD method has recently been widely used in fault diagnosis of rotating machines. Lei et al. utilized the EEMD method to enable the rub-impact fault diagnosis of a power generator and performed the early rub-impact fault diagnosis of a heavy oil catalytic cracking machine set. Finally, the superiority of the proposed method based on EEMD ...

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Applications of machine learning to machine fault

2020-4-1  In the past, traditional machine learning theories began to weak the contribution of human labor and brought the era of artificial intelligence to machine fault diagnosis. Over the recent years, the advent of deep learning theories has reformed IFD in further releasing the artificial assistance since the 2010s, which encourages to construct an end-to-end diagnosis procedure.

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Logical fault diagnosis method of electrical machine

In fault diagnosis, it is primary to determine the diagnosis parameters and the measuring methods. Through the simulating experiments the faults of electric machine are studied, such as: the ...

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GitHub - xujiachang1024/Fault-Diagnosis-with-ML: Fault ...

2019-8-30  About. Fault Diagnosis with Machine Learning Methods, the dissertation project of my MSc Data Science degree at King's College London Resources

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Fuzzy Logic Based Broken Bar Fault Diagnosis and

2020-5-20  The diagnosis of the machine state is only possible if knowing the vibratory symptoms associated with each fault. Also, consider the faults reasons in electrical machines: their origin in the design, the installation, the operating environment, the nature of the load and the maintenance program where the faults are classified according to their ...

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深度学习理论及其在电机故障诊断中的研究现状与展望-Deep ...

引用本文: 丁石川,厉雪衣,杭俊,王尹江,王群京.深度学习理论及其在电机故障诊断中的研究现状与展望[J].电力系统保护与控制,2020,48(8):172-187. [点击复制]DING Shichuan,LI Xueyi,HANG Jun,WANG Yinjiang,WANG Qunjing.Deep learning theory and its application to fault diagnosis of an electric machine[J].Power System Protection and Control,2020,48(8):172 ...

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Highly Accurate Machine Fault Diagnosis Using Deep ...

2018-8-10  We develop a novel deep learning framework to achieve highly accurate machine fault diagnosis using transfer learning to enable and accelerate the training of deep neural network. Compared with existing methods, the proposed method is faster to train and more accurate. First, original sensor data are converted to images by conducting a Wavelet

Read More
Fault diagnosis of rotating machines based on EEMD-MPE

2021-11-9  The EEMD method has recently been widely used in fault diagnosis of rotating machines. Lei et al. utilized the EEMD method to enable the rub-impact fault diagnosis of a power generator and performed the early rub-impact fault diagnosis of a heavy oil catalytic cracking machine set. Finally, the superiority of the proposed method based on EEMD ...

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Fault diagnosis strategy of CNC machine tools based on ...

2017-12-13  To ensure the safe operation of CNC machines, a fault diagnosis strategy based on cascading failure is proposed. According to fault mechanism analysis, a directed graph model of fault propagation between components in machine tool systems is established. In this study, the interpretative structural model method is used to realize the hierarchical structure of fault

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A review on fault detection and diagnosis techniques ...

2020-11-10  For fault diagnosis in an oil-filled transformer, a majority voting based extreme learning machine (ELM) is developed which employs multiple independent ELMs (Zhang and Zhai 2018). Another hybrid voting approach is presented in Zhou et al. ( 2018 ) which combines static weighted voting and cloud similarity measurement algorithm and it is ...

Read More
Fuzzy Logic Based Broken Bar Fault Diagnosis and

2020-5-20  The diagnosis of the machine state is only possible if knowing the vibratory symptoms associated with each fault. Also, consider the faults reasons in electrical machines: their origin in the design, the installation, the operating environment, the nature of the load and the maintenance program where the faults are classified according to their ...

Read More
Rotating Machinery Fault Diagnosis for Imbalanced Data ...

To diagnose rotating machinery fault for imbalanced data, a method based on fast clustering algorithm (FCA) and support vector machine (SVM) was proposed. Combined with variational mode decomposition (VMD) and principal component analysis (PCA), sensitive features of the rotating machinery fault were obtained and constituted the imbalanced fault sample set.

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Machine hearing for industrial fault diagnosis ...

2021-11-1  Project detail. This project aims to develop an automatic acoustic fault diagnosis system that can mimic the industrial engineers’ “listening and diagnostic” capability. As demonstrated from literature, human auditory system possesses exceptional capability to extract and simplify characteristic information of audio signals.

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A distributed sensor-fault detection and diagnosis ...

More importantly, the detection of faults is time-sensitive, whereas the diagnosis does not necessarily need to be fast. We propose a distributed sensor-fault detection and diagnosis system based on machine learning algorithms where the fault detection block is implemented in the sensor in order to achieve output immediately after data collection.

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The Fault Diagnosis of Machine Based on Modal Analysis

Download Citation The Fault Diagnosis of Machine Based on Modal Analysis In the latest two decades, modal analysis has been used in many engineering disciplines

Read More
Logical fault diagnosis method of electrical machine

In fault diagnosis, it is primary to determine the diagnosis parameters and the measuring methods. Through the simulating experiments the faults of

Read More
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