This paper analyzed the noise distribution of three pulleys and one belt system theoretically and experimentally. Aiming at the influence of the tensioner on the transmission noise of the synchronous belt, on the premise of theoretical analysis of the influence of the tensioner on the transmission noise of the synchronous belt, the noise test of the synchronous belt transmission system with and without the tensioner was carried out under the same experimental conditions. Based on the principle of acoustic array measurement, a three-pulley and one belt noise test device was designed. The noise pressure distribution nephogram and amplitude–frequency characteristic curve were obtained by noise tests at different speeds. Through the comparison of the results of two groups of tests, the influence rule of the tensioner on the transmission noise of the synchronous belt was obtained. The results show that the tensioner can effectively avoid the resonance of the synchronous belt, and the noise amplitude of the three-pulley and one belt drive system is 3 dB higher after the tensioner is installed. It provides a basis for vibration and noise reduction of the engine timing transmission system.

Aiming at the problem that the machine tool synchronous belt failure during the transmission process will affect the machine tool transmission, a machine tool synchronous belt fault diagnosis method based on genetic algorithm (GA) optimized back propagation (BP) neural network is proposed. First, utilize wavelet decomposition to extract the energy characteristics of the synchronization belt fault; construct a BP neural network, and use genetic algorithms to optimize the BP neural network; finally, the energy characteristic of the vibration signal of the synchronous belt is used as the input of the neural network, and the fault simulation test is carried out. The results show that the genetic algorithm GA-optimized BP neural network has higher accuracy than the traditional BP neural network for fault diagnosis of machine tool synchronous belt.

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In order to solve the problem of too large computer overhead for convolutional neural network in the rescue action recognition, this paper proposes a rescue action recognition method combining spatiotemporal decomposition network and channel attention mechanism. After adding the channel attention mechanism, the model can generate a weight value for each feature channel, and then weight the normalized weight to each feature channel to improve the recognition accuracy of the model. The combined network model has better performance in both computer overhead and recognition accuracy, and the recognition accuracy has improved compared with the original model (S3D) in the case of only RGB video as input on rescue action data. In addition, the recognition accuracy on the public UCF-101 and KTH datasets has also improved. The experiment results show the proposed method can effectively improve the accuracy of action recognition in both the rescue action and public datasets.

In order to improve the service life of the V-ribbed belt and the ride comfort of the vehicle, the friction noise of V-ribbed belt was studied by simulation and experiment. A theoretical model of V-ribbed belts vibration is established, and the conditions for unstable vibration are derived. Based on the theory of mode coupling, the causes of high frequency friction noise of V-ribbed belts are analyzed, and it is considered that the coupling between the vibration of the V-ribbed belts and the natural frequency of the belts’ cross section causes the self-excited vibration of the belt, resulting in high frequency friction noise. Firstly, ANSYS Workbench is used to identify the belts’ cross sections with 3, 4, and 6 wedges, and the natural frequencies of the belts’ cross sections are obtained. Then on the belt drive friction tester, the influences of tension and relative sliding speed on the frequency of high frequency friction noise is studied using a single factor test method, and the frequency response curve of high frequency friction noise is also analyzed. The results of the experiment and simulation show that the transverse vibration of the V-ribbed belts is closely related to the phase and amplitude of the high frequency friction noise, and the changes in tension and relative sliding speed do not affect the frequency of the high frequency friction noise. The frequency of high frequency friction noise has a good consistency with the natural frequency of belts’ cross section, which shows that mode coupling causes the strong self-excited vibration of the V-ribbed belts and the high frequency friction noise. It provides a method and theoretical basis for the control of friction noise.