Rotate Vector (RV) Reducer Fault Detection and Diagnosis System: Towards Component Level Prognostics and Health Management (PHM)

Rohan, Ali; Raouf, Izaz; Kim, Heung-Soo

doi:10.3390/s20236845

Cited by 32 publications

(20 citation statements)

References 78 publications

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“…Wavelet transform is a transform analysis method which is widely used in the fields of fault detection, image processing, and signal analysis [ 15 , 16 , 17 , 18 , 19 ]. Since the WIM signal is a discrete signal, this paper uses discrete wavelet transform to process the WIM signal.…”

Section: Pre-processing Of the Wim Signalmentioning

confidence: 99%

Research on Weigh-in-Motion Algorithm of Vehicles Based on BSO-BP

Chen

et al. 2022

Sensors

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Weigh-in-motion (WIM) systems are used to measure the weight of moving vehicles. Aiming at the problem of low accuracy of the WIM system, this paper proposes a WIM model based on the beetle swarm optimization (BSO) algorithm and the error back propagation (BP) neural network. Firstly, the structure and principle of the WIM system used in this paper are analyzed. Secondly, the WIM signal is denoised and reconstructed by wavelet transform. Then, a BP neural network model optimized by BSO algorithm is established to process the WIM signal. Finally, the predictive ability of BP neural network models optimized by different algorithms are compared and conclusions are drawn. The experimental results show that the BSO-BP WIM model has fast convergence speed, high accuracy, the relative error of the maximum gross weight is 1.41%, and the relative error of the maximum axle weight is 6.69%.

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Section: Pre-processing Of the Wim Signalmentioning

confidence: 99%

Research on Weigh-in-Motion Algorithm of Vehicles Based on BSO-BP

Chen

et al. 2022

Sensors

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“…Therefore, according to the hierarchical fusion -style architecture, this paper divides the PHM system of space application fluid loop into system-level PHM, regional-level PHM and member-level PHM, and builds the architecture model of space application fluid loop PHM system on this basis, as shown in Fig. 3 [14][15][16] .…”

Section: Architecture Of Phm System For Fluid Loop In Space Applicationmentioning

confidence: 99%

Study on Prognostics and Health Management of Fluid Loop System for Space Application

Cao

Zhang

et al. 2022

J. Phys.: Conf. Ser.

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Prognostics and Health Management (PHM) is an important technical means to realize condition-based maintenance of complex systems. As a complex space application engineering, the space application fluid loop system has the requirements of high safety, high reliability and long life. Therefore, this paper adopts PHM technology to comprehensively study the space application fluid loop system from two aspects of architecture and key technology respectively. Firstly, this paper introduces the current status of health management of fluid loop system for space application and the problems to be solved urgently. Secondly, the PHM system architecture and key technologies such as condition monitoring, health assessment, fault diagnosis, fault prediction and health management are described, and the PHM system research scheme of fluid loop for space application is established. Finally, a case study is carried out by taking the fluid loop main engine of the core power equipment as an example. The analysis results show that the PHM technology can effectively reduce the system failure rate, improve the system safety and reliability, and provide a strong guarantee for the long-term on-orbit operation of the system.

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“…23 In the online prediction phase, two main steps are performed: (1) Monitoring data from industrial robots is collected and stored in the cloud. (2) The deep measurement learning model was obtained through offline training to construct the health indicator and assisted with the health assessment.…”

Section: Deep Metric Learning-based Health Indicator Constructionmentioning

confidence: 99%

“…With the advancement and development of industry 4.0, engineering systems within the industrial field become increasingly complex 1 . Nowadays, intelligent industrial robots are programmed to perform tasks automatically to reduce human intervention 2 . These robots serve as the basic components of the automatic industrial system.…”

Section: Introductionmentioning

confidence: 99%

Metric learning‐based whole health indicator model for industrial robots

Xiao

Zeng

et al. 2022

Int J of Intelligent Sys

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Aiming at the problems of complex structure, high components coupling, and difficultly monitoring of the whole health status with the industrial robot, a metric learning-based whole health indicator model is proposed.First, according to the more obvious degradation characteristics of industrial robots during accelerated operation, the accelerated signal is segmented and then the time-domain features are extracted. Second, the longterm and short-term memory (LSTM) network combined with the multihead attention is used to construct the network model, and the metric learning method is adopted to learn the similarity measurement method of the industrial robot monitoring data. Finally, the similarity measure method got from metric learning is used to construct the whole health indicator, which describes the whole degradation trend of the industrial robot.The experiments are based on the real accelerated aging data set from industrial robots. The results show that the proposed model can effectively construct the whole health indicator for industrial robots. The average trend of the proposed model reaches 0.9769. The average monotonicity reaches 0.5666, which is 0.1748, 0.1577, and 0.1492 higher than the similarity measurement method based on Euclidean distance, Markov distance, and LSTM.

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Rotate Vector (RV) Reducer Fault Detection and Diagnosis System: Towards Component Level Prognostics and Health Management (PHM)

Cited by 32 publications

References 78 publications

Research on Weigh-in-Motion Algorithm of Vehicles Based on BSO-BP

Research on Weigh-in-Motion Algorithm of Vehicles Based on BSO-BP

Study on Prognostics and Health Management of Fluid Loop System for Space Application

Metric learning‐based whole health indicator model for industrial robots

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