Research on frequency parameter detection of frequency shifted track circuit based on nonlinear algorithm

Xie, Huaqing; Wang, Yatao; Gao, Zhiliang; Ganthia, Bibhu Prasad; Truong, Chinh V

doi:10.1515/nleng-2021-0050

Cited by 79 publications

(67 citation statements)

References 23 publications

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“…It can be seen that when the concentration of carbon tubes is small, the absorbance increases gradually with the increase of pressure, and the relationship is linear. However, the absorbance did not increase much when the carbon tube concentration reached the “saturated” concentration, which was due to the uniformity of some poorly dispersed carbon tubes [ 18 ]. Furthermore, it was found that under the same conditions, the stability of carbon nanotube composites was better than that of acidified carbon nanotubes, which may be due to the fact that the exposed T321 molecular groups of carbon tubes were mixed with surfactants to improve dispersion.…”

Section: Results Analysismentioning

confidence: 99%

Influence of Nano-Cutting Fluid in New Cutting and Forming Processes on Heat Transfer Performance of Mechanical Engineering

Liu

2022

International Journal of Analytical Chemistry

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In order to strengthen the thermal conductivity of green cutting fluid and the influence of nano-cutting fluid from new cutting and forming processes on heat transfer performance of mechanical engineering, a research method was proposed based on the influence of nano-cutting fluid from new cutting and forming processes on heat transfer performance of mechanical engineering. The dispersion stability, thermal conductivity, and viscosity characteristics of the nanofluid were studied, and the effects of acidification treatment time, type and concentration of carbon tube particles, surfactants, and testing conditions on the above properties were analyzed. It was found that the filling rate of T321 was about 25% when CNTs were filled, and the optimal compounding ratio of the two surfactants, sodium dodecyl benzenesulfonic acid (SDBS) and Tween-80 (TW-80), for the preparation of stable dispersed nanofluids was 3 ∶ 7. The optimum ratio of compound active agent to carbon tube is 5 ∶ 1. When CNTs were acidified for about 9 h and dispersed in sufficient and stable condition, the thermal conductivity of the base liquid was increased by 110% by the composite, and the shape factor of CNTs had the most significant effect on the thermal conductivity. It was found that the composite nanofluids had higher thermal conductivity and lower viscosity than the nanofluids prepared by ordinary CNTs. This was due to the fact that surfaces of CNTs were chemically modified during the opening and internal filling process, so that the composite had better dispersion stability in the base fluid.

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Section: Results Analysismentioning

confidence: 99%

Influence of Nano-Cutting Fluid in New Cutting and Forming Processes on Heat Transfer Performance of Mechanical Engineering

Liu

2022

International Journal of Analytical Chemistry

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“…Delineate the area for further processing. Using ROI to delineate the area where the target to be detected is located can reduce the processing time and increase the accuracy [18]. Then, locate the target to be detected in the ROI area and segment it from the image; that is, accurately locate the target on the basis of the ROI area.…”

Section: Bearing Inner Ring Surface Defect Detection Algorithmmentioning

confidence: 99%

Application of Image Processing Sensor and Pattern Recognition in Detection of Bearing Surface Defects

Zhu

2022

Journal of Sensors

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In order to solve the problem that the traditional detection technology can not meet the requirements of online detection, a visual detection device for bearing inner ring defects based on image processing and pattern recognition is proposed in this paper. The device systematically designs an image acquisition device of bearing inner ring based on CCD. In the hardware scheme, the appropriate lens, camera, light source, and other related hardware are selected according to the actual needs, a complete image acquisition platform of bearing inner ring is built, and the software function design is completed. The simulation results show that the qualified rate of machine detection is 98.6%, the missed detection rate is 0, and the false detection rate is 1.4%, which are better than manual detection. Conclusion. The test results show that the bearing inner ring defect detection system can detect the surface defects of bearing inner ring quickly, stably, and reliably, and the detection efficiency and accuracy are higher than the original manual detection method, so it has a good application prospect.

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“…, f t+Δt−1 ] can be determined within Δt time windows. is data set consists of the input frame window F (t−Δt+1):t and output frame window F (t+1):(t+Δt) of each time step t ∈ [Δt, (T − Δt − 1)], where T is the sampling time length [11].…”

Section: Data Processing and Presentationmentioning

confidence: 99%

Research on Human Pose Capture Based on the Deep Learning Algorithm

Xie

et al. 2022

Journal of Control Science and Engineering

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A method based on the deep learning algorithm is proposed to accurately capture the posture of the human body. It is one of the important means to improve athletes’ competitive level in modern sports to accurately analyze the posture of sports training by technical means. Aiming at the application demand of using artificial intelligence technology to accurately analyze and predict the motion training posture, a motion posture analysis and prediction system based on deep learning is designed in this paper. Based on the Arduino embedded development board and equipped with multiple IMU sensors, the scheme established a system to collect accurate human movement data such as speed and acceleration by using stepper motors and obtained accurate human movement data. The experimental results show that these models have been trained with H3.6 m data sets. The sampling frequency was reduced to 25 Hz, and the joint angles were converted into exponential graphs. When the time window covers approximately 1 660 ms, the loop network will be initialized to 40 frames, equivalent to 1 600 ms. For each action, a separate pretrained recursive model is used. It is proved that the method based on deep learning can reduce the prediction error of fine-tuning specific movements and effectively classify and predict the movements not included in the original training data.

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Research on frequency parameter detection of frequency shifted track circuit based on nonlinear algorithm

Cited by 79 publications

References 23 publications

Influence of Nano-Cutting Fluid in New Cutting and Forming Processes on Heat Transfer Performance of Mechanical Engineering

Influence of Nano-Cutting Fluid in New Cutting and Forming Processes on Heat Transfer Performance of Mechanical Engineering

Application of Image Processing Sensor and Pattern Recognition in Detection of Bearing Surface Defects

Research on Human Pose Capture Based on the Deep Learning Algorithm

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