Papers by Author: Hong Bin Tang

Abstract: Concrete pump truck plays an important role in national economic development and infrastructure construction. The boom system is one of the most critical parts of concrete pump truck, so it is important to analysis the strength. In this paper, the research is on the concrete pump truck of 37 meters. The three-dimensional model is established in PRO/E. Then the model is imported to MSC.PATRAN / NASTRAN and the strength is analyzed. The results show that the maximum stress on the boom is far less than the yield limit of the material, the structure meet the strength requirements.

Abstract: Because neural network has the advantages of fast parallel processing, associative memory, self-organizing and self-learning, it is widely applied in the fault diagnosis of hydraulic system. Present in this paper is a fault diagnosis approch to a typical failure in hydraulic system which is leakage of hydraulic cylinder.The fault diagnosis approch is based on monitoring preesure singal,time domain feature and neural network. According to the method, the time domain feature is extracted from the pressure singal and costitutes the eigenvectors at first, then these eigenvectors are input into neural network to identify faults. The experimental results show that three modes of no leakage, slighter leakage and severe leakage are correctly identified and it can be used in the fault diagnosia of hydraulic syetem.

Abstract: Inner leakage of hydraulic cylinder is a very serious failure in the hydraulic system and it can lead to many problems.A important fault diagnosis way is to detect the pressure signal.But the pressure signal is seriously influenced by pressure fluctuation and other noises.It is difficult to extract features from pressure singal. Aiming at the difficulty in extracting feature from pressure singal in fault diagnosis for leakage of hydraulic cylinder,a fault diagnosis approch based on monitoring preesure singal and wavelet energy is proposed in this article.According to the method, the enegry of different frequency bands after wavelet decomposition costitutes the eigenvectors at first, then these eigenvectors are input into BP network to identify faults. The experimental results show that three modes of no leakage, slighter leakage and severe leakage were correctly identified.This approach can be used in the leakage fault diagnosis of hydraulic cylinder.