暖通空调小流量风机机械振动信号自适应采集研究

Research on Adaptive Collection of Mechanical Vibration Signals for Small Flow Fans in HVAC Systems

当暖通空调小流量风机运行时,频繁产生的脉冲噪声增加了信号采集的复杂性并引入了干扰,使得采集到的振动信号含有大量不必要的噪声成分,降低了采集精度和准确性。为此,提出暖通空调小流量风机机械振动信号自适应采集方法。使用经验模态分解方法对振动信号进行处理,获得信号在时域和频域上的特征信息。根据振动信号的频率特征,设计自适应变采样算法在不同的时间段内动态地调整采样率,采集风机振动信号。使用数学形态滤波器调整信号的形状,去除脉冲干扰以提高采集信号的精度,并进一步优化信号的质量。实验结果表明,所提方法的振动信号自适应采集精度高,且采集时间短。

When the small flow fan of HVAC operates,the frequent generation of pulse noise increases the complexity of signal acquisition and introduces interference,resulting in a large amount of unnecessary noise components in the collected vibration signal,reducing the accuracy and accuracy of acquisition.Therefore,an adaptive collection method for mechanical vibration signals of small flow fans in HVAC is proposed.Use empirical mode decomposition method to process vibration signals and obtain feature information of the signals in both time and frequency domains.Based on the frequency characteristics of the vibration signal,an adaptive variable sampling algorithm is used to dynamically adjust the sampling rate at different time periods and collect the fan vibration signal.Use mathematical morphological filters to adjust the shape of the signal,remove pulse interference,improve the accuracy of signal acquisition,and further optimize the quality of the signal.The experimental results show that the proposed method has high adaptive acquisition accuracy and short acquisition time for vibration signals.