A novel method of combining generalized frequency response function and convolutional neural network for complex system fault diagnosis

Chen, Lerui; Zhang, Zerui; Cao, Jun

doi:10.1371/journal.pone.0228324

Cited by 9 publications

(8 citation statements)

References 32 publications

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“…Hard Times, "Liu Hulan," and other works are of great value to our study of the social and cultural development at that time. The specific creation of these works follows the Western realistic modelling techniques and is created by integrating Chinese local cultural concepts, but there are also characteristics of single creation form and obvious stylized phenomenon [1].…”

Section: Introductionmentioning

confidence: 99%

Dimensional Defect Detection Research on the Sculpture Surface Combining the Convolutional Neural Network and Gabor

Liu

2022

Wireless Communications and Mobile Computing

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Thematic sculpture creation is an important part of sculpture creation. In particular, the current thematic sculpture creation in China has broken the shackles of serving politics and has shown a variety of aspects such as theme selection, modelling method, material language, and creative purpose. Since the new century, Chinese thematic sculptors have made in-depth analysis and research on the diversity of creative objects, the infinite possibilities of creative expression, and the diversity of creative purposes, especially through the phenomenon of different thematic sculptures to explore their existing predicaments, and give them reflection. If the time is too long, it will reduce the production efficiency of the sculpture production line and increase the operating cost of the enterprise. The Gabor wavelet transform is used to obtain the texture features of the sculpture surface, and the generated high-dimensional features are subjected to random projection dimension reduction. Finally, the binarization algorithm can be used to detect the defect location quickly and accurately. The feature map is extracted by selecting a deep network. The neural network algorithm structure for the sculpture dataset is presented, and the activation function and regularization method are improved on this basis.

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Section: Introductionmentioning

confidence: 99%

Dimensional Defect Detection Research on the Sculpture Surface Combining the Convolutional Neural Network and Gabor

Liu

2022

Wireless Communications and Mobile Computing

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“…According to Ref. 27 , the mathematical model of PMSM can be expressed as follows. where, is armature currents of stator winding on d -axis.…”

Section: Fault Mechanism Analysis Of Pmsm Based On Nofrf Spectrummentioning

confidence: 99%

Fault mechanism analysis and diagnosis for closed-loop drive system of industrial robot based on nonlinear spectrum

Chen

Wen

Wang

et al. 2022

Sci Rep

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To solve the problem of nonlinear characteristics neglecting and fault mechanism analysis lacking in fault diagnosis research, a new method of fault mechanism analysis and diagnosis based on nonlinear spectrum is proposed. Firstly, based on the Permanent Magnet Synchronous Motor (PMSM) model of robot, the first 4-order spectrums based on nonlinear output frequency response function (NOFRF) in different states are obtained by batch calculation method. Secondly, the high-frequency spectrum distribution rule of NOFRF spectrum in different states are analyzed. Finally, in the closed-loop simulation environment of robot, the identification method based on data-driven is adopted for NOFRF spectrum calculation to verify power loss fault of PMSM. Meanwhile, the fault diagnosis experiment is also carried out. The experimental results indicate that the key characteristics distribution rule of NOFRF spectrums in the real environment is consistent with the theoretical analysis results, and compared with the traditional fault feature extraction methods by output signal, the diagnosis with fault feature of NOFRF spectrum for industrial robot closed-loop drive system has the highest accuracy, which verifies the validity of NOFRF spectrum as the fault feature.

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“…In order to verify the accuracy of Volterra kernel calculated by TDANN, the first three-order Volterra time-domain kernels of the nonlinear system are calculated by TDANN, recursive algorithm in reference [32], and variable step size least mean square (VSSLMS) adaptive identification algorithm in reference [33], respectively. en, three different output results are obtained by equation (6).…”

Section: E Accuracy Comparison With Traditional Algorithmmentioning

confidence: 99%

“…Mathematical Problems in Engineering calculation of multiple Volterra kernels, which can improve the calculation speed and efficiency, while with identification algorithm, one operation can only calculate one Volterra kernel value. In order to demonstrate that TDANN can reduce the computational complexity, the recursive algorithm in reference [32] and the identification algorithm in reference [33] are adopted to randomly calculate several first three-order Volterra kernels of the system. e time consumption of three methods is shown in Table 2.…”

Section: E Accuracy Comparison With Traditional Algorithmmentioning

confidence: 99%

An Intelligent Calculation Method of Volterra Time-Domain Kernel Based on Time-Delay Artificial Neural Network

Zhong

Chen

2020

Mathematical Problems in Engineering

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To solve the problems of high complexity and low accuracy in Volterra time-domain kernel calculation of a nonlinear system, this paper proposes an intelligent calculation method of Volterra time-domain kernel by time-delay artificial neural networks (TDANNs) and also designs a root mean square error (RMSE) index to choose the neuron number of the network input layer. Firstly, a three-layer TDANN is designed according to the characteristics of the Volterra model. Secondly, the relationship between parameters of TDANN and Volterra time-domain kernel is analyzed, and then three-order expressions of Volterra time-domain kernel are derived. The calculation of Volterra time-domain kernel is completed by network training. Finally, it is verified by a nonlinear system. Simulation results indicate that compared with traditional methods, the new method has higher accuracy, and it can realize the batch calculation of Volterra kernel, which not only improves the calculation efficiency but also provides accurate data for fault diagnosis based on Volterra kernel in further research work.

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A novel method of combining generalized frequency response function and convolutional neural network for complex system fault diagnosis

Cited by 9 publications

References 32 publications

Dimensional Defect Detection Research on the Sculpture Surface Combining the Convolutional Neural Network and Gabor

Dimensional Defect Detection Research on the Sculpture Surface Combining the Convolutional Neural Network and Gabor

Fault mechanism analysis and diagnosis for closed-loop drive system of industrial robot based on nonlinear spectrum

An Intelligent Calculation Method of Volterra Time-Domain Kernel Based on Time-Delay Artificial Neural Network

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