Uncertainty Of Fault Diagnosis Research Articles

Recent advances in mechanism/data-driven fault diagnosis of complex engineering systems with uncertainties

<p>The relentless advancement of modern technology has given rise to increasingly intricate and sophisticated engineering systems, which in turn demand more reliable and intelligent fault diagnosis methods. This paper presents a comprehensive review of fault diagnosis in uncertain environments, focusing on innovative strategies for intelligent fault diagnosis. To this end, conventional fault diagnosis methods are first reviewed, including advances in mechanism-driven, data-driven, and hybrid-driven diagnostic models and their strengths, limitations, and applicability across various scenarios. Subsequently, we provide a thorough exploration of multi-source uncertainty in fault diagnosis, addressing its generation, quantification, and implications for diagnostic processes. Then, intelligent strategies for all stages of fault diagnosis starting from signal acquisition are highlighted, especially in the context of complex engineering systems. Finally, we conclude with insights and perspectives on future directions in the field, emphasizing the need for the continued evolution of intelligent diagnostic systems to meet the challenges posed by modern engineering complexities.</p>

Research on Ship Electronic Power System Fault Diagnosis Based on Expert System

Aiming at the difficulty in locating the fault point quickly and accurately after the ship electronic power system fault. In this paper, fault diagnosis expert system is used to diagnose the fault occurred to ensure stability of power supply of ship power system. The possible faults are divided into four categories on the base of analysis of ship electrical system fault characteristics. Frame structure is used to describe the connections between the various parts of the ship power system in knowledge presentation. Expert system uses production rules to describe the specific fault and combine the ideal of fuzzy inference to dealing with the uncertainty in fault diagnosis at the same time. The expert system designed in this paper can find fault points and provide solutions quickly and accurately and improves the reliability of the ship power system by test.

Interval-valued fuzzy spiking neural P systems for fault diagnosis of power transmission networks

It is a challenge problem how to deal with the uncertainty in fault diagnosis of power systems. To solve the challenge problem, this paper introduces an interval-valued fuzzy spiking neural P system (IVFSNP system), where the interval-valued fuzzy logic is integrated into spiking neural P systems to characterize the uncertainty. Based on the IVFSNP system, a fuzzy reasoning algorithm is presented, and the corresponding fault diagnosis model is developed. IVFSNP system is capable of describing the incomplete and uncertain fault signals from a supervisory control and data acquisition system equipped together with electric power systems. In order to evaluate the availability and effectiveness of the proposed fault diagnosis model, two case studies of fault diagnosis of a transmission network are discussed and analyzed, including complex and multiple fault situations with the incomplete and uncertain status signals. The results of the case studies demonstrate that IVFSNP system can be used to diagnose the faulty sections in power transmission networks accurately and effectively.

ADAMS Dynamics Simulating and Analysis of Vibration Signal for Deep-Groove Ball Bearings

This paper presents the dynamics-simulation and research of vibration characteristic on deep-groove ball bearing. It introduces an analysis of the vibration frequency in different damage of bearing and spectrum analysis of the fault signal on bearing to draw response on vibration characteristics in bearing, so as to provide a simple method on research of dynamic fault characteristic of bearing. This work shows some kind, characteristics signal and frequency of fault on bearing. The normal model and other two models which have raceway crack in inside track and out ring are set up by using ADAMS software to analyse the dynamic of them, the test program that vibration signal of three models are obtained by acceleration sensors to instead of that of real condition is simulated. In addition, the test signal of vibration is given in time domain respectively, and the vibration characteristic is identification by using spectrum analysis method, so that it can provides technical support for diagnosis of fault bearing. In the study of fault diagnosis, several experimental results provide that the uncertainty of fault diagnosis and interference of other complicated factors are avoided effectively in real environment. The result of simulated analysis is consistent with the theory calculation. This method is more effective, convenient and expansibility than a research of practical fault-diagnosis.

Power Transformer Fault Diagnosis Based on Data Fusion

As the fault information of power transformers has characteristics such as complementarities, redundancy and uncertainty, the diagnosis task can't be finished by the simple fault characteristic vector and the diagnosis method. The basic ideas of information fusion are introduced, and DGA (the Dissolved Gas Analysis) is combined tightly with other information such as the results of conventional electrical test of power transformer. The power transformer fault diagnosis model based on information fusion is built. The models can diagnose both fault property and fault spot, which can improve reliability and lower uncertainty in fault diagnosis.