This study develops the forward-backward processing method to deal with a huge number of data collected from a long test duration at a low sampling rate. Applications of this method, in addition to the proper choice of the ratio of the frequencies of the reciprocating motion and the sampling rate and the choice of the optimum subdivision number in a cycle, are able to obtain a smooth reborn profile with a high degree of accuracy from the huge number of sampling data. This reborn profile is obtained by averaging the data mapped into every subdivision of this cycle. In order to identify the qualified cycles in the reciprocating motions, which are able to map all the sampling data in these cycles into a cycle, the starting-point criterion is also developed. This present method has been proven to be really effective when applied to the experimental results of friction coefficient and electrical contact resistance collected in a dry wear test.

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