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In the present paper a degradation assessment and life prediction method has been proposed for electro-hydraulic shift valve applied to control wet shift clutch in Power-shift steering transmission (PSST). Unlike traditional analysis of contaminant sensitivity, our work is motivated by the failure mechanisms of abrasive wear with a mathematic model. Plowing process included in abrasion will consecutively increase the roughness of mating surfaces and thereby enlarge the clearance space for leaking more fluid. It is an overwhelming wear mechanism in the degradation of shift valve within serious-contaminated fluid. Herein a mathematic model for assessment and prediction is proposed by considering particle morphology and abrasion theory. Such model has been verified for its applicability and accuracy through comparison between theoretical and experimental results. Assuming the proposed model to be general, valve wearing behavior in any hydraulic system can be simulated.

The low cycle fatigue experiment is extensively used to test the reliability and durability of turbocharger. Low cycle fatigue test is mainly the switching between high and low speed. As the result of the experiment, the fatigue life is shorter as the difference between high and low speed becomes greater. In the traditional low cycle fatigue test, a large air compressor is needed to drive the turbocharger under different operating conditions, which consume large amounts of electric power. This paper presents a new experiment device which has double chambers and double turbochargers. This device can be self-circulating, without the large air compressor, to realize high and low speed switching on the premise of not exceeding the limitation of turbine entry temperature. First, a detailed model is established in GT-Power and self-circulation test data has been used to validate the model.

This paper first discusses the principles of how to identify whether a time series has chaotic characteristics, and explores a method of finding out the embedding dimension of a time series. Then Grassberger-Procaccia (G-P) algorithm is adopted to calculate correlative dimension. After the validity of G-P algorithm is confirmed using several traditional strange attractors, it is applied to calculate the fractal dimension of some vibration signals of an automotive transmission. This article presents how to apply chaos and fractal theories to diagnose the wearing of ball bearings in automotive transmissions based on the analysis of the transmission acceleration vibration signals. The results show that the vibration signals of automotive transmissions have fractal nature. There are certain correlations between a bearing's condition and the fractal dimension of its vibration signal.