Rotor Crack Fault Diagnosis based on Base and Multi-sensor Adaptive Weighted Information Fusion
نویسندگان
چکیده
The faults of rotating machinery monitored by fixing the sensors on rotor directly brings some problems such as difficulty in fixing the sensors, poor universality and so on, while it brings some advantages such as rapidness, convenience and good universality and so on by fixing the sensors on the base. Since the base is far away from the fault source, the collected vibration signals are relatively weak. Multi-sensor information fusion method can describe the diagnostic object completely because it extends spatial and temporal limits, and obtains more information of the diagnostic object. A rotor crack fault diagnosis method based on base and multi-sensor adaptive weighted information fusion is proposed in this paper. The arrangement of the sensors on rotating machinery base was designed by taking advantage of the vibration transitivity of rotor-bearing-base and was verified by experiments. The adaptive weighted information fusion method is investigated, and the fault characteristic value is detected with multi-layer decomposition of wavelet analysis, and the fault of the cracked rotor is diagnosed effectively by combining with the Bode diagram in the process of speeding up. The research will provide a new method for the fault diagnosis of rotating machinery.
منابع مشابه
Model-based Approach for Multi-sensor Fault Identification in Power Plant Gas Turbines
In this paper, the multi-sensor fault diagnosis in the exhaust temperature sensors of a V94.2 heavy duty gas turbine is presented. A Laguerre network-based fuzzy modeling approach is presented to predict the output temperature of the gas turbine for sensor fault diagnosis. Due to the nonlinear dynamics of the gas turbine, in these models the Laguerre filter parts are related to the linear d...
متن کاملRotor Crack Detection by Using Multi-vibration Signal from The Basement
Rotor crack detection method by using multi-vibration signals gathered at the basements is presented in this paper. The finite element software ANSYS is applied for analyzing the vibration response characteristics of the basement to determine sensor configuration. Feature fusion for time-domain statistics of multiple sensors is performed by using the support vector machine to diagnose the depth...
متن کاملA New Fault Tolerant Nonlinear Model Predictive Controller Incorporating an UKF-Based Centralized Measurement Fusion Scheme
A new Fault Tolerant Controller (FTC) has been presented in this research by integrating a Fault Detection and Diagnosis (FDD) mechanism in a nonlinear model predictive controller framework. The proposed FDD utilizes a Multi-Sensor Data Fusion (MSDF) methodology to enhance its reliability and estimation accuracy. An augmented state-vector model is developed to incorporate the occurred senso...
متن کاملA Weighted Belief Entropy-Based Uncertainty Measure for Multi-Sensor Data Fusion
In real applications, how to measure the uncertain degree of sensor reports before applying sensor data fusion is a big challenge. In this paper, in the frame of Dempster-Shafer evidence theory, a weighted belief entropy based on Deng entropy is proposed to quantify the uncertainty of uncertain information. The weight of the proposed belief entropy is based on the relative scale of a propositio...
متن کاملMulti-information Fusion and Filter Study of Multi-sensor Velocity Measurement on High-speed Train
-For the rapid development high-speed railway system, improvement approach of the velocity measurement accuracy has been studied based on multiple speed sensors on high-speed train. In this method, the velocity measurement data from multi-channel speed sensors were dealt through data fusion of arithmetic mean filter, weighted arithmetic mean filter, Federated Kalman filter and adaptive Federate...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- JSW
دوره 7 شماره
صفحات -
تاریخ انتشار 2012