Abstract
Faults of hydraulic motor are characterized by nonlinearity, complexity and multi-noise. Based on these characteristics, this paper proposes a machine learning method which combines T-S fuzzy inference model with neural network for fault diagnosis of hydraulic motor. The reasoning process of T-S fuzzy reasoning mathematical model and the working principle of neural net
work model are elaborated in detail. The simulation results show that the method is effective for the fault diagnosis of hydraulic motor.
work model are elaborated in detail. The simulation results show that the method is effective for the fault diagnosis of hydraulic motor.
| Translated title of the contribution | Research on Fault Diagnosis Method of Hydraulic Motor Based on T-S Fuzzy Neural Network |
|---|---|
| Original language | Chinese (Simplified) |
| Pages (from-to) | 3027-3030 |
| Journal | 计算机与数字工程 |
| Volume | 48 |
| Issue number | 12 (总第 374) |
| Publication status | Published - 20 Dec 2020 |
Bibliographical note
Full text of this publication does not contain sufficient affiliation information. The Research Unit(s) information for this record is based on the then academic department affiliation of the author(s).Research Keywords
- 液压马达
- 故障诊断
- T-S 模糊数学模型
- 神经网络
- hydraulic motor
- fault diagnosis
- T-S fuzzy mathematical model
- neural network