Comprehensive Fault Diagnosis Research Articles

Research on Comprehensive Fault Diagnosis Method of Air Compressor Oil Based on Intelligent Multi-objective Optimization

Research on Comprehensive Fault Diagnosis Method of Air Compressor Oil Based on Intelligent Multi-objective Optimization

The Remote Monitoring and Fault Diagnosis System of Coal Mine Main Fan

In order to ensure the safety and stability of coal mine main fan’s operation, the system uses programmable controller PLC as the control core, uses integrated transmitter, the man-machine interface touch screen and PC configuration software, achieving real-time monitoring and state control of the main fan’s performance, state parameter, electrical parameter, and uses PowerBuilder 9.0 system development software to build the fan’s fault diagnosis expert system, realizing the comprehensive fault diagnosis of the fan, providing accurate expert advice and repair scheme. It uses advanced Ethernet technology to realize the communication between PC and scene control system. The realization of the main fan’s automation management ensures the stability and reliability of the fan’s running.

An Integrated Qualitative–Quantitative Hypothesis Driven Approach for Comprehensive Fault Diagnosis

Faults lead to loss of productivity and in rare cases, loss of human lives. Therefore fault diagnosis is a critical task for increased reliability and safety. There are a variety of techniques that have been proposed in the literature for fault diagnosis. A comprehensive diagnostic problem is one which involves parametric changes in the presence of sensor failures and controller or actuator malfunction. In this paper we describe a diagnostic framework that integrates qualitative models with quantitative estimation to address the comprehensive diagnostic problem. The comprehensive diagnostic framework presented in this paper can be studied as four modules. The first module, also referred to as the diagnostic module, uses qualitative techniques to generate a hypotheses set of all possible root causes. In this paper we study a signed directed graph based qualitative model for the generation of hypotheses. The second module, called the hypothesis generator intelligently constructs and reorders the candidate hypothesis sets. The third module is the nonlinear estimation module, which estimates the relevant parameters in the candidate hypothesis. The fourth module performs statistical testing of the estimation results to either validate or invalidate the hypothesis. The efficacy of the proposed framework is demonstrated on simulation examples.

Diagnosis of dynamic systems based on explicit and implicit behavioral models: An application to gas turbines in esprit project tiger

We are interested in the monitoring and diagnosis of dynamic systems. We combine explicit temporal models of the behavior of a dynamic system with implicit behavioral models supporting model-based approaches. This work is driven by the needs of and is applied to two gas turbines of very different size and power. We describe the problems of building systems for these domains and illustrate how we have developed a system where these two approaches complement each other to provide a comprehensive fault detection and diagnosis system. We also explore the strengths and weaknesses of each approach. The work described here is currently working continuously, on-line to a gas turbine in a major chemical plant.

Fault Diagnosis for Robots

This paper presents a comprehensive fault diagnosis system for robots. The basic idea is a real time supervision of the robot simultaneously in time, frequency and parameter domain. In time domain a set of nonlinear equations is used to describe the dynamic behavior of the robot. In every joint each measured sensor signal is calculated from all other measured sensor signals. Due to this, for every measured sensor signal several independently signals of the same signal type are available for generation of residuals.

Integration of Fault Detection and Diagnosis Methods

For the fault detection of technical processes different methods can be applied based on the information extracted from direct measured signals, from signal models and process models. Examples for signal model based fault detection methods are spectral analysis or parameter estimation of ARMA models, examples for process model based methods are parameter estimation, state estimation or parity equation approaches. A comparison of these methods shows that they have different properties with regard to the detection of faults in the process, the actuators and the sensors.After a brief review of model based fault detection methods the various advantages and disadvantages of the different methods are summarized. The importance of realistic fault modeling is outlined and the suitability of model-based fault detection methods in dependence on the type of faults is discussed. By a proper integration of different fault detection methods mainly their advantages can be used and their disadvantages avoided. It will be shown which integrations of fault detection methods are appropriate to generate analytical symptoms which are then treated by methods of change detection and classification.For fault diagnosis a knowledge based procedure is required, because in addition to analytical symptoms also qualitative information in form of heuristic symptoms have to be taken into account. It will be shown how based on heuristic process knowledge as fault-symptom causalities and a unified representation of all symptoms an integrated fault diagnosis can be performed. This comprises the treatment of the symptom as uncertain facts and approximate diagnostic reasoning via if-then rules either in a probabilistic or a fuzzy-logic (possibilistic) frame.As examples for integrated fault detection and diagnosis experimental results are shown which were obtained with machine tools.In summary, the contribution shows how through proper integration of different fault detection methods and integration of fault diagnosis methods a comprehensive fault diagnosis of the components of technical processes can be performed.