A step-by-step fuzzy diagnostic method based on frequency-domain symptom extraction and trivalent logic fuzzy diagnosis theory (TLFD), which is established by combining the trivalent logic inference theory with the possibility and fuzzy theories, is proposed herein. The features for diagnosing a number of abnormal states are extracted sequentially from the measured signals using statistical tests in the frequency domain. The symptom parameters (SPs) that can sensitively reflect symptoms of abnormal states are then selected to provide effective information for the discrimination of each state. The membership function of each state is then generated based on the possibility theory using the probability functions of the SPs. The step-by-step fuzzy diagnoses are performed based on the TLFD. This method can be used extensively to diagnose anomalies in various equipment. In this study, the diagnosis of structure faults of a rotating machine is cited as an example to demonstrate the effectiveness and universality of this method.

中文翻译：

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基于症状提取和三价逻辑模糊诊断理论的设备逐步模糊诊断方法


提出一种基于频域症状提取和三价逻辑模糊诊断理论（TLFD）的逐步模糊诊断方法，该方法将三价逻辑推理理论与可能性理论和模糊理论相结合建立。使用频域中的统计测试从测量信号中顺序提取用于诊断多个异常状态的特征。然后选择能够敏感地反映异常状态症状的症状参数（SP），为每种状态的判别提供有效信息。然后使用 SP 的概率函数根据可能性理论生成每个状态的隶属函数。基于TLFD进行逐步模糊诊断。该方法可广泛用于诊断各种设备的异常情况。本研究以旋转机械结构故障诊断为例，论证了该方法的有效性和普适性。