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为保证洒布车的洒布性能及工作的可靠性,以半智能型沥青洒布车液压驱动系统的核心元件——轴向柱塞泵为实验对象,对其中心弹簧失效故障的振动信号进行了分析,并提出了利用主元分析Q统计中平方预报误差的变化对该故障进行检测的实验方法。该方法首先通过滤波消噪和包络解调的信号处理方法,从包络谱图中分析出故障的特征频率,再通过小波包能量法进行特征提取,得到特征向量样本,然后利用泵正常工作样本建立的主元模型进行故障检测,最后根据中心弹簧失效三种不同失效程度的故障检测实验来验证该方法的有效性。
In order to ensure the sprinkling performance and work reliability of the sprinkler, the axial piston pump, the core element of the semi-intelligent asphalt distribution truck hydraulic drive system, was used as the experimental object to test the vibration signal of failure of the center spring Analyzed and put forward the experimental method of detecting the fault by using the principal component analysis of variance of squared prediction in Q statistics. The method firstly analyzes the characteristic frequency of the fault from the envelope spectrum by the signal processing method of filtering noise reduction and envelope demodulation, and then extracts the feature by the wavelet packet energy method to obtain the sample of the feature vector, and then uses the pump to work normally The principal component model established by the sample is used to detect the fault. Finally, the validity of the method is verified by three kinds of failure detection experiments of center spring failure.