Research on fault diagnosis for ship course control system

Liu, Sheng; Weng, Zhenping; Gao-yun, LI

doi:10.1109/icma.2009.5245034

Cited by 5 publications

(5 citation statements)

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“…(5) Because P(F 1 | S)is greater than P(F 2 | S), diagnosis system will retrieve the fault tree F 1 of head stock hydraulic system fault tree on first and then the fault tree of motor run without load. (6) To browse the next level events of top event of fault tree F 1 and F 2 , select the judgment conditions and back to the job site. According to the amount of the state that has been collected, get the status value of judgment conditions.…”

Section: Intelligent Diagnosis Mechanism Based On Fta and Bayesian Fo...mentioning

confidence: 99%

“…Bian calculated the fuzzy probability of the top event which is AUV can't work normally and analysis the results by using operational rule [5]. Liu S analyzed the fault information of ship's course control system, and establishes a fault diagnosis model based on fuzzy nerve network algorithms [6]. Zhou ZB studied a new method based on dynamic Bayesian networks according to the deficiency of traditional Markov chain method in dynamic fault tree analysis [7].…”

Section: Introductionmentioning

confidence: 99%

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Fault Diagnosis Mechanism Based on FTA and Bayesian for Large-Scale CNC Equipments

Liu

Chen

2012

AMM

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In view of the disadvantage of current FAT-based fault diagnosis method in large-scale complicated system, fault diagnosis method of heavy NC machine based on FTA and Bayesian is discussed. Firstly, building fault trees with the help of reachability matrix, and to set the determinate conditions at every node of fault tree combining FTA with rule reasoning, the minimum cut set of fault reasons are determined as a result of step by step screening fault tree from top-down; Secondly, Bayesian method is integrated into the fault tree diagnostic method to calculate the posterior probability triggered by each fault tree in order to locate the fault tree where the fault had occurred and ensure high efficiency of fault diagnosis; Finally, B/S based intelligent fault diagnosis system for large-scale CNC equipments is developed, and the feasibility and efficiency of this method are proved in an example of fault diagnosis of Φ 160 NC boring and milling machine.

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Section: Intelligent Diagnosis Mechanism Based On Fta and Bayesian Fo...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis Mechanism Based on FTA and Bayesian for Large-Scale CNC Equipments

Liu

Chen

2012

AMM

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“…. β is the identification accuracy of LSSVMI(Least Squares Support Vector Machine Identifier).We can consider the β as the robust factor [9] .The value of robust factor changes with the precision of LSSVMI, in form as: , m E is the squares of difference between actual system output and LSSVMI output .We can get the range of robust factor:…”

Section: Applied Mechanics and Mechanical Engineering IImentioning

confidence: 99%

Supercavitating Vehicle LSSVM Multiple Intelligent Control

2011

AMM

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According to the conditions of supercavitating vehicle stable control problems, the massive uncertain factors caused by reactions between the vehicle and cavity, and the control system real-time request, the paper presents a supercavitating vehicle stable navigation least squares support vector multiple intelligent control scheme. The scheme makes full use of the nonlinear mapping ability, self-learning adaptability and parallel information processing of the least squares support vector machine. Combining with fuzzy control method, complementary advantages, the closed-loop control has been formed. The simulation shows that the control system has good adaptive ability and robustness. The supercavitating movement stability and precise control realizes even in the situation that difficult to obtain an accurate model.

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“…A survey of robust fault-tolerant control for nonlinear system is earlier launched in [2]. A robust fault-tolerant controller has designed based on linear matrix inequalities to improve the reliability of a ship course/roll control system and ameliorate the effectiveness of uncertain disturbance [3] . The authors of [4] have devised anti-windup and active fault-tolerant control methods for autonomous underwater vehicles and their simulation experimentations have validated the effectiveness to treat sensors failure.…”

Section: Introductionmentioning

confidence: 99%

A Fault-Tolerant and Anti-Disturbance Control Based on Sliding Mode Iterative Learning Law for Attitude of Satellite

Wang

2013

AMM

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To cope with the problem of the degradation of actuation effectiveness caused by actuator deflection or fault in the attitude and orbit control system (AOCS) of spacecraft on-orbit, an attitude fault-tolerant and anti-disturbance control scheme is proposed based on a sliding mode iterative learning law, in which the pseudo control input is applied to design the sliding mode controller to ensure the AOCS tracks a reference trajectory precisely after some fault occurred; By analyzing the Lyapunov stability, a novel adaptive iterative learning law is developed, which in term of the tracking error, determine some parameters in controller on-line to address the actuator failure and external disturbance. Numerical simulation experiments show that the fault-tolerant and anti-disturbance controller can ameliorate actuation malfunction and compensate the influence of external disturbance effectively.

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Research on fault diagnosis for ship course control system

Cited by 5 publications

References 0 publications

Fault Diagnosis Mechanism Based on FTA and Bayesian for Large-Scale CNC Equipments

Fault Diagnosis Mechanism Based on FTA and Bayesian for Large-Scale CNC Equipments

Supercavitating Vehicle LSSVM Multiple Intelligent Control

A Fault-Tolerant and Anti-Disturbance Control Based on Sliding Mode Iterative Learning Law for Attitude of Satellite

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