Research on Hydraulic Cylinder Fault Diagnosis System Based on ARM

2012 ◽  
Vol 619 ◽  
pp. 489-493
Author(s):  
Xiu Xu Zhao ◽  
Zhe Min Hu ◽  
Yan Chen Shang
Keyword(s):  
Fault Diagnosis ◽  
Fault Detection ◽  
Hydraulic System ◽  
Hydraulic Cylinder ◽  
Diagnosis System ◽  
Fault Diagnosis System ◽  
Fault Mode ◽  
Detection Instrument

Hydraulic cylinder is an important actuator in hydraulic system, affecting the system running correctly and effectively. It’s closed and difficult to observe the failure symptoms, and result the difficulties of fault diagnosis and elimination for hydraulic cylinder. In this paper, a fault detection instrument and system for hydraulic cylinder are developed to diagnose the fault mode through position and pressure signals and infer decision based on FMEA base.

Design of Fault Diagnosis System for the Parameter-Depended Control System

2011 ◽  
Vol 320 ◽  
pp. 636-641
Author(s):  
Jing Zhou
Keyword(s):  
Control System ◽  
Fault Diagnosis ◽  
Fault Detection ◽  
Fault Isolation ◽  
Linear Matrix ◽  
Diagnosis System ◽  
Loop Control ◽  
Closed Loop Control System ◽  
Loop Control System ◽  
Fault Diagnosis System

A robust parameter-depended reduced order(RPRO) fault detection filter(FDF) is designed. Contrary to the parameter-depended uncertainty system, the order of the linear matrix inequalities is reduced, then the RPRO fault detection and fault isolated filters are constructed. Then a RPRO fault isolation filter is designed for occurrence of both actuator fault and sensor fault in the aerocraft’s closed-loop control system, and fault diagnosis system is structured based on the fault isolation filters. Through the output of the fault diagnosis system, we can alarm the fault timely and the advantages of this approach are highlighted.

Research on Fault Diagnosis System for Aircraft Hydraulic Power Carts Based on Fuzzy Diagnosis Theory

2012 ◽  
Vol 220-223 ◽  
pp. 607-610
Author(s):  
Wei Qiang Zhao ◽  
Yong Xian Liu ◽  
Mo Wu Lu
Keyword(s):  
Fault Diagnosis ◽  
High Reliability ◽  
Complex Structure ◽  
Hydraulic Power ◽  
Diagnosis System ◽  
Diagnosis Method ◽  
New Type ◽  
Fault Diagnosis System ◽  
Fault Mode ◽  
Fuzzy Diagnosis

Aircraft hydraulic power carts are important aviation support equipment. Because of their complex structure they have high failure rate. Therefore fault diagnosis system for hydraulic power carts is necessary to ensure high reliability and maintainability for hydraulic power carts. This paper presents a diagnosis method based on fuzzy diagnosis theory in the developing process of a new type of hydraulic power carts. The fault Symptom, critical value and fault causes are established based on the research of fault mode for hydraulic power carts. And also the mathematical model of fault diagnosis for hydraulic power carts is established based on fuzzy diagnosis theory. The practical test results and fault diagnosis instances show that with this fault diagnosis system fast fault diagnosis for hydraulic power carts was carried out successfully.

Study on the Fault Diagnosis of Gear Pump Based on PNN Neural Network

2014 ◽  
Vol 1044-1045 ◽  
pp. 873-876 ◽  
Author(s):  
Gui Lan Zuo ◽  
Shang Ding Lai ◽  
Yue Cheng
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Sample Size ◽  
Control Model ◽  
Gear Pump ◽  
Hydraulic Pump ◽  
Diagnosis System ◽  
Structure Feature ◽  
Fault Diagnosis System ◽  
Fault Mode

The principle of neural network’s PNN algorithm was introduced, Combining with the structure feature and work principle of the hydraulic pump, a fault diagnosis system based on PNN neural network was established. The feasibility of the system was proved through the identification, emulation and experimentation of hydraulic system’s fault patterns. The PNN control model was simulated using Matlab/Simulink toolbox. This model analyzed and studied the PNN network predictive diagnostic rate. Under different sample size and SPREAD, the simulation’s results show that this method has favorable identified capability of fault mode and favorable applicability to the hydraulic pump.

The Monitoring and Fault Diagnosis System for Controllable Pitch Propeller Based on LabVIEW

2014 ◽  
Vol 635-637 ◽  
pp. 851-855
Author(s):  
Bing Kuan Yin ◽  
Hai Gang Hu ◽  
Xin Zhou ◽  
Lin Wei Zhang
Keyword(s):  
Fault Diagnosis ◽  
Computer Technology ◽  
Hydraulic System ◽  
Shaft Speed ◽  
Diagnosis System ◽  
Shaft System ◽  
Testing Technology ◽  
System Vibration ◽  
Fault Diagnosis System ◽  
Tank Pressure

The monitoring and fault diagnosis system for controllable pitch propeller is based on modern testing technology, fieldbus technology, monitoring and diagnosis technology, computer technology. The equipment consists of various types of sensors, CANopen bus devices, LabVIEW and computer, which can monitor the CPP’s operating parameters, including shaft system vibration, shaft speed, pitch angle, liquid level of gravity tank, pressure and temperature of hydraulic system, and the system can also alarm if three typical fault of shafting occurs.

A Hybrid EKF-Fuzzy Approach to Fault Detection and Isolation of Industrial Gas Turbines

2011 ◽  
Author(s):  
Amin Salar ◽  
Ali Khaki Sedigh ◽  
SeyedMehrdad Hosseini ◽  
Hiwa Khaledi
Keyword(s):  
Fault Diagnosis ◽  
Fault Detection ◽  
Fuzzy Inference System ◽  
Gas Turbines ◽  
Fuzzy Inference ◽  
Fault Detection And Isolation ◽  
Inference System ◽  
Diagnosis System ◽  
Fault Diagnosis System ◽  
Health Parameters

Based on the Gas Path Analysis (GPA) method, nonlinear estimation and fuzzy classification theories, a comprehensive fault diagnosis system has been developed for an industrial Gas Turbine (GT). The hybrid method consists of two parts, in the first part noisy sensor output changes are translated to changes in the health parameters using an Extended Kalman Filter (EKF). In the second part the outputs of the EKF are used as the inputs of a fuzzy system. This system can isolate and evaluate the physical faults based on the predetermined rules obtained mostly from experimental data and aerothermodynamical simulations. The ratios of changes in different health parameters due to different faults and also the areas in the compressor most affected by these faults are the key factors for developing the rules. The Fuzzy Inference System (FIS) gives the fault locations in the compressor or turbine. Also, operator-friendly suggestions for the time of the compressor washing or components repair are provided. This leads to a hybrid fault detection and isolation solution for the GT, and with pre-filtering the data before use as input of fuzzy inference system, the accuracy of the fault diagnosis system is improved. Nonlinear simulation, estimation and classification results are provided to show the effectiveness of the proposed methodology.

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