fault diagnosis of rotating machinery based on

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Aug 01, 2018  One of the challenges in rotating machinery fault diagnosis is that more than one single-fault may appear at a time. Another challenge is the high cost of acquiring the exponentially increased simultaneous-fault signals. In this application, simultaneous-fault diagnosis of automotive engine based on three kinds of engine signals is studied.

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In actual engineering applications, inevitable noise seriously affects the accuracy of fault diagnosis for rotating machinery. To effectively identify the fault classes of rotating machinery under noise interference, an efficient fault diagnosis method without additional denoising procedures is proposed. First, a one-dimensional deep residual shrinkage network, which directly takes the raw ...

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Feb 01, 2021  A novel approach based on GRU for fault diagnosis of rotating machinery is proposed to exploit the temporal information from time-series vibration signals. (2) An improved feature extraction method is developed by constructing images from 1-D vibration signals and then utilizing a linear layer to lift the dimensions of each signal segments ...

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Vibration signal and shaft orbit are important features that reflect the operating state of rotating machinery. Fault diagnosis and feature extraction are critical to ensure the safety and reliable operation of rotating machinery. A novel method of fault diagnosis based on convolutional neural network (CNN), discrete wavelet transform (DWT), and singular value decomposition (SVD) is proposed ...

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May 22, 2007  Fault diagnosis is essentially a kind of pattern recognition, or classification. Artificial neural networks (ANN) are a valuable pattern-recognition method in theory and in application. Because of this, models based on neural networks have been applied in recent years in the detection and diagnosis of rotating machinery , , , , . Neural ...

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Feb 01, 2007  In this paper, a novel method for fault diagnosis of rotating machinery based on an improved wavelet package transform (IWPT), a distance evaluation technique and the support vector machines (SVMs) ensemble is proposed. In order to detect the fault occurrence, a biorthogonal wavelet with impact property is constructed via lifting scheme, and ...

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Fault Diagnosis for Rotating Machinery: A Method based on ...

Rotating machinery is one of the most typical types of mechanical equipment and plays a significant role in industrial applications. Condition monitoring and fault diagnosis of rotating machinery has gained wide attention for its significance in preventing catastrophic accident and

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Fault Diagnosis of Rotating Machinery Based on ...

Vibration signal and shaft orbit are important features that reflect the operating state of rotating machinery. Fault diagnosis and feature extraction are critical to ensure the safety and reliable operation of rotating machinery. A novel method of fault diagnosis based on convolutional neural network (CNN), discrete wavelet transform (DWT), and singular value decomposition (SVD) is proposed ...

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A Fault Diagnosis Method of Rotating Machinery Based on ...

Oct 25, 2020  The application of feature extraction method in bearing fault diagnosis plays an important role in industrial applications. In recent years, the bearing fault diagnosis methods had a very big development, the direction of the fault diagnosis of rotating machinery using the database aims to extract the features using multi-scale entropy. Then, KNN classification method is applied to classify ...

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Fault Diagnosis of Rotating Machinery Based on Empirical ...

Apr 30, 2017  Lei Y., Zuo M., “Fault diagnosis of rotating machinery using an improved HHT based on EEMD and sensitive IMFs,” Measurement Science

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Fault Diagnosis of Rotating Machinery Based on Multiple ...

Fault Diagnosis of Rotating Machinery Based on Multiple ANFIS Combination with Gas Article in Mechanical Systems and Signal Processing July 2007 Impact Factor: 2.26 DOI: 10.1016/j.ymssp.2006.11.003 CITATIONS 150 READS 108 4 authors, including: Yaguo Lei Xi'an Jiaotong University 52 PUBLICATIONS 1,474 CITATIONS SEE PROFILE Zhengjia He

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(PDF) Fault Diagnosis of Rotating Machinery Based on ...

[21] B.S. Yang, T. Han, W.W. Huang, Fault diagnosis of rotating machinery based on multi-class support vector machines, Journal of Mechanical Science and Technology 19 (2005) 846–859.

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Fault diagnosis of rotating machinery based on time ...

In order to raise the working reliability of rotating machinery in real applications and reduce the loss caused by unintended breakdowns, a new method based on improved ensemble empirical mode decomposition (EEMD) and envelope spectrum analysis is proposed for fault diagnosis in this paper. First, the collected vibration signals are decomposed into a series of intrinsic mode functions (IMFs ...

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DWT-LSTM-Based Fault Diagnosis of Rolling Bearings with ...

Since the vibration signal obtained from a single sensor may not contain full fault information, a CNN-based multi-sensor fusion method for the fault diagnosis of rotating machinery was proposed in . In [ 18 ], the features of multiple sensors are extracted through the deep belief network (DBN), and the softmax classifier results are combined ...

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Non-Stationary Vibratory Signature of Bearing Fault ...

Vibration signature-based analysis for detection and diagnosis is the commonly used technique in the monitoring of rotating machinery. Reliable features will...

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Identify Condition Indicators at the Command Line

You can derive condition indicators at the command line from signal analysis or model fitting. If you have rotating machinery, you can extract specialized features that incorporate characteristics of your system, such as characteristic fault frequencies, or derive gear condition metrics with sensitivities to specific fault

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Fault diagnosis of rotating machinery based on noise ...

To this end, a great many of effective fault diagnosis methods have been proposed for fault diagnosis of rotating machinery, and most of them are based on vibration signal analysis [1-3]. Feature extraction using a signal processing tool is an important stage of an effective fault diagnosis method.

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A Fault Diagnosis Method of Rotating Machinery Based on ...

Oct 25, 2020  The application of feature extraction method in bearing fault diagnosis plays an important role in industrial applications. In recent years, the bearing fault diagnosis methods had a very big development, the direction of the fault diagnosis of rotating machinery using the database aims to extract the features using multi-scale entropy. Then, KNN classification method is applied to classify ...

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Fault diagnosis of rotating machinery based on time ...

In order to raise the working reliability of rotating machinery in real applications and reduce the loss caused by unintended breakdowns, a new method based on improved ensemble empirical mode decomposition (EEMD) and envelope spectrum analysis is proposed for fault diagnosis in this paper. First, the collected vibration signals are decomposed into a series of intrinsic mode functions (IMFs ...

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Fault Diagnosis of Rotating Machinery Based on Multisensor ...

Multisensor information fusion, when applied to fault diagnosis, the time-space scope, and the quantity of information are expanded compared to what could be acquired by a single sensor, so the diagnostic object can be described more comprehensively. This paper presents a methodology of fault diagnosis in rotating machinery using multisensor information fusion that all the features are ...

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Fault diagnosis of rotating machinery based on kernel ...

Jan 22, 2015  Based on kernel density estimation (KDE) and Kullback-Leibler divergence (KLID), a new data-driven fault diagnosis method is proposed from a statistical perspective. The ensemble empirical mode decomposition (EEMD) together with the Hilbert transform is employed to extract 95 time- and frequency-domain features from raw and processed signals. The distance-based evaluation approach

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Fault Diagnosis of Rotating Machinery Based on Multiple ...

Fault Diagnosis of Rotating Machinery Based on Multiple ANFIS Combination with Gas Article in Mechanical Systems and Signal Processing July 2007 Impact Factor: 2.26 DOI: 10.1016/j.ymssp.2006.11.003 CITATIONS 150 READS 108 4 authors, including: Yaguo Lei Xi'an Jiaotong University 52 PUBLICATIONS 1,474 CITATIONS SEE PROFILE Zhengjia He

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A Rotating Machinery Fault Diagnosis Method Based on ...

Jan 17, 2019  The rotating machinery plays a vital role in industrial systems, in which unexpected mechanical faults during operation can lead to severe consequences. For fault prevention, many fault diagnostic methods based on vibration signals are available in the literature. However, the vibration signals are obtained by using different types of sensors, which can cause sensor installation issues

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Diagnosis of Rotating Machines Faults Using Artificial ...

rotating machinery faults based on vibration signature analysis, temperature monitoring, noise signature analysis, lubricant signature analysis, Artificial Intelligence (AI) techniques. many AI methods are in use for bearing defects diagnosis. For instance,

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Fault diagnosis of rotating machinery using knowledge ...

Fault diagnosis on rotating machinery based on fuzzy C-means clustering and rough set theory[J]. Information and Control, 2004, 24(1): 4–5 (in Chinese). Google Scholar [11] Mitra S, Mitra P, Pal S K. Evolutionary modular design of rough knowledge-based network using fuzzy attributes [J]. Neurocomputing ...

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(PDF) Fault detection and diagnosis of rotating machinery ...

CONCLUSIONSThis paper has presented model-based techniques for the detection and diagnosis of rotating machinery faults. A nonlinear filtering approach was developed for a rub-impact model of a rotating machine where unbalance, changes in the stiffness, and damping of the rotor and bearing system, etc., can lead to a complex nonlinear vibration ...

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Based Fault Diagnosis of Rotating Machinery

Based Fault Diagnosis of Rotating Machinery Shangjun Ma 1,*, Wei Cai 1, Wenkai Liu 2, Zhaowei Shang 2 and Geng Liu 1 1 Shaanxi Engineering Laboratory for

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Research on multitask fault diagnosis and weight ...

Oct 28, 2020  Recently, deep learning methods such as convolutional neural networks (CNN) have been widely used in fault diagnosis of rotating machinery. However, most methods are not designed to consider the influence of the working conditions and limited to classifying several fault types. In this paper, we propose two CNN-based multitask models, i.e., sigmoid multitask fault diagnosis model

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A Method for Imbalanced Fault Diagnosis Based on Self ...

Download Citation A Method for Imbalanced Fault Diagnosis Based on Self-attention Generative Adversarial Network In the real industrial scenario, the rotating machinery generally works in a ...

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A Novel Deep Learning Method for Intelligent Fault ...

Intelligent fault diagnosis methods based on deep learning becomes a research hotspot in the fault diagnosis field. Automatically and accurately identifying the incipient micro-fault of rotating machinery, especially for fault orientations and severity degree, is still a major challenge in the field of intelligent fault diagnosis.

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