基于希尔伯特变换的信号优先级排序法在车内异响源识别中的应用

在一个多输入-单输出系统中,若输入信号之间非独立,相互存在因果关系或线性影响,可能导致故障原因判断不明。利用基于希尔伯特变换的优先级排序法对相关输入信号进行考察,检验因果关系,确定优先级最高、对输出影响最大的输入。以空调压缩机壳体、压缩机吸气口、膨胀阀低压端、发电机四个主要测点振动信号作为非独立输入,以驾驶员右耳处声信号作为输出,将开空调时车内产生异响频率作为考察目标,利用该方法确定优先级最高信号为压缩机吸气口振动。该方法比传统方法更快捷、高效,易于为企业所采纳。

Application of Signal Priority Ranking Method Based on Hilbert Transform in Identification of Interior Abnormal Sound Sources

In a multiple-input single-output (MISO) system, the cause of a problem might not be correctly detected if inputs are related to each other, or causality and linear effects exist among them. In this case, a method based on Hilbert Transform was used for causality checking and priority ranking between correlated input signals. In this paper, vibration signals on air-conditioning compressor, thermostatic expansion valve (TXV) and alternator were measured as correlated inputs. Noise signal at driver’s right ear was measured as output. Focusing on the frequency of interior abnormal sound when air-conditioning (AC) system is operating, this method was applied to investigate into the priorities of four correlated inputs. Results show that vibration signal at the compressor in-let has priority over other inputs. Compared with traditional approaches, this method is more efficient, easier to apply, and easier to be accepted by car manufacturing companies.