Intelligent Fault Diagnosis of Gears Based on Deep Learning Feature Extraction and Particle Swarm Support Vector Machine State Recognition

Al-Masri, Ahmed N.; Mokayed, Hamam

doi:10.54216/jisiot.040102

Cited by 9 publications

(3 citation statements)

References 18 publications

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“…e PSO algorithm has the characteristics of simple implementation, high precision, and fast convergence speed. It has good applicability in the solution process, so it has attracted the attention of many researchers [11][12][13].…”

Section: Principle Of Particle Swarm Algorithmmentioning

confidence: 99%

[Retracted] Influence of Sports Biomechanics on Martial Arts Sports and Comprehensive Neuromuscular Control under the Background of Artificial Intelligence

Zhang

et al. 2022

Contrast Media & Molecular Imaging

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Neuromuscular control refers to the reflexes of nerves that affect muscle balance and function. In addition, there are interactions between joint structure, muscle function, and the central nervous system. In the integration with other intelligent control methods and optimization algorithms, such as fuzzy control/expert verification and genetic algorithm, it provides nonparametric object models, optimization parameters, reasoning models, and fault diagnosis. The central nervous system is the main research object of neuromuscular control. Martial arts often cause injuries or affect the progress of martial arts because of some irregular movements. Chinese traditional martial arts is another name for “martial arts” in the late Qing Dynasty in China. It is mainly reflected in the individual’s application and attainments in martial arts traditional teaching methods and personal cultivation. Therefore, this paper proposes an analysis of the influence of sports biomechanics on martial arts sports and comprehensive neuromuscular control in the context of artificial intelligence. In this paper, the specific research of Wushu sports is carried out mainly in two aspects: sports biomechanics and neuromuscular control. It uses a variety of algorithms, successively using particle swarm algorithm, neural network structure, fitness function, and so on. This paper compares and analyzes their accuracy and then selects the optimal algorithm. It then conducts experimental research on the martial arts movements of professional martial arts Sanda players. The final experimental conclusion shows that, regarding lower limb selective response time and the middle left lower limb prereaction time (L-PMT) of the elite athlete group and the ordinary athlete group, the average movement value of the elite group of 2.336 is significantly greater than that of the ordinary group of 1.938. This shows that, within a certain range, the larger the knee angle and the smaller the hip angle, the stronger the ability to buffer the impact of the ground, without causing greater damage to the muscles and joints.

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Section: Principle Of Particle Swarm Algorithmmentioning

confidence: 99%

[Retracted] Influence of Sports Biomechanics on Martial Arts Sports and Comprehensive Neuromuscular Control under the Background of Artificial Intelligence

Zhang

et al. 2022

Contrast Media & Molecular Imaging

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“…As the largest part of power loss, gear meshing power loss is mainly composed of sliding friction power loss and rolling friction power loss [14][15][16]. e normal load of the tooth surface and the relative sliding speed of the tooth surface are the decisive factors of the meshing power loss.…”

Section: Mathematical Model Of Transmission Efficiencymentioning

confidence: 99%

Optimized Design for Reliability of Pointer Irrigation Machine Components for Intelligent Computing

Liu

Zhang

2022

International Transactions on Electrical Energy Systems

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The application of intelligent technology has realized the transformation of people’s production and lifestyle, and also promoted the development and transformation of the agricultural field. At present, the application of agricultural intelligence is getting stronger and stronger; using its intelligent advanced methods and technologies, this paper aimed to achieve the optimization of sprinkler irrigation machine parts in the intelligent network environment to promote the rapid development of agriculture, and proposed the use of the NSGA-II algorithm in intelligent computing to guide the integration of artificial intelligence and pointer sprinkler parts, which helps to analyze and solve the objective problem of machine failure and parts damage in agriculture. In the study of the sprinkler gear system, from the perspective of gear efficiency, since it is optimized according to the minimum efficiency point of the fourth gear of the gear reducer, compared with the gear efficiency of 49.05% before this point, the efficiency of this point after optimization is 59.45%, and the minimum efficiency point will be increased by 21.2%. And because the energy loss unrelated to the power loss load will be greatly reduced, these energy losses have a greater relationship with the structure of the gearbox. In terms of each gear, compared with the previous period, the efficiency of the first gear was increased by 8.5% to 15.9%; the efficiency of the second gear increased by 8.7% to 17.4%; the efficiency of the third gear increased by 9.4% to 18.7%; and the efficiency of the fourth gear increased by 10.1% to 21.2%. Therefore, it is currently necessary to optimize the components of the sprinkler irrigation machine.

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“…Figure 2 is a flow chart of analyzing the gear pump using Fluent software. In order for the experiment to make the simulation analysis accurate and smooth, it is necessary to clarify the idea of simulation calculation, carry out a large number of practical calculations, record, analyze, and compare the condition settings and calculation results of each calculation [11][12][13]. e simulation calculation of the pressure field is carried out first, and after a certain number of steps are relatively stable, the energy model is opened, and the simulation calculation of the temperature field is carried out.…”

Section: Simulation Model Of Internal Flow Field Of Gear Pumpmentioning

confidence: 99%

Simulation of Flow-Induced Vibration and Dynamic Performance of Circular-Arc Helical Gear Pump under Background of Machine Learning

Wei

Feng

Han

et al. 2022

International Transactions on Electrical Energy Systems

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At present, with the continuous development and great improvement of mechanical manufacturing, processing, and assembly technology, mechanical flow-induced vibration (FIV) with a relatively concentrated frequency domain can be controlled by active and passive noise reduction methods. However, whether it is active noise reduction or passive noise reduction, they all focus on how to suppress the transmission of sound waves and cannot solve the problems of flow leakage, obvious temperature rise, and noise excitation from the root cause. Therefore, it is necessary to determine the location of the primary and secondary excitation sound sources of FIV, the identification of true and false sounds, and the characteristic relationship between flow and noise. This provides a theoretical basis and engineering application direction for the mechanism of noise reduction of FIV. The numerical calculation part of the acoustics in this paper is solved by the hybrid method, and the flow field is discretely calculated by the large eddy simulation (LES) module in the Fluent software. When the calculated flow field is stable, the velocity field of one impeller rotation period is selected to be output as the iterative value of the sound field and imported into ACTRAN for Fourier transform. Then, the sound field calculation is carried out, and the result of the spatial and temporal variation of the sound field is finally obtained. Through experiments, it was found that when the load of the gear pump is 8 MPa, the volumetric efficiency of the optimized circular-arc helical gear pump of the sliding bearing was improved by about 4%. When the rotation speed is 2100°r/min, the arc helical gear pump reduced the surface temperature rise by 2.5°C. This verified that the optimized performance of the sliding bearing in the arc helical gear pump is significantly improved. Through the theoretical model of the temperature rise of the sliding bearing, the phenomenon that the surface temperature of the prototype gear pump was not significantly increased with the loading in the low pressure region is explained.

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Intelligent Fault Diagnosis of Gears Based on Deep Learning Feature Extraction and Particle Swarm Support Vector Machine State Recognition

Cited by 9 publications

References 18 publications

[Retracted] Influence of Sports Biomechanics on Martial Arts Sports and Comprehensive Neuromuscular Control under the Background of Artificial Intelligence

[Retracted] Influence of Sports Biomechanics on Martial Arts Sports and Comprehensive Neuromuscular Control under the Background of Artificial Intelligence

Optimized Design for Reliability of Pointer Irrigation Machine Components for Intelligent Computing

Simulation of Flow-Induced Vibration and Dynamic Performance of Circular-Arc Helical Gear Pump under Background of Machine Learning

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