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Parameter interval based fault isolation method has fast isolation speed and fits many kinds of nonlinear dynamic systems. In this paper, this method is extended to sensor fault isolation problem for nonlinear dynamic systems. The example shows good performance of this method for sensor fault isolation.
To solve the problem of equipment fault diagnosis, the paper proposes a fault diagnosis model based on Support Vector Machines (SVM) and studies the parameters that influence model accuracy. On the basis of analyzing model parameters influence, A new kind of evaluation function about algorithm accuracy and the Genetic algorithm of the global optimization parameters selection are presented. According...
A reliable control scheme is developed in this paper for a class of linear based on sensor mixed faults. A more practical mixed faults model of sensor than outage and continuous fault model is considered. The mixed faults model combine outage with continuous fault. Using linear matrix inequality, A sufficient condition is given to guaranteed asymptotic stability and H performance when all control...
This study presents a novel method based on the empirical mode decomposition (EMD) and the envelope analysis for the fault detection of rolling bearings. The main purpose is to overcome the traditional envelope method in the choosing of the resonant frequency band. First, the EMD method is adaptively to decompose the vibration signals into a series of the intrinsic mode function (IMF). Then, the decision...
This paper presents a new method which combines empirical mode decomposition (EMD) and power spectral density (PSD) together for bearing fault diagnosis in low speed-high load rotary machine. EMD is a novel self-adaptive method which is based on partial characters of the signal. Vibration signal measured from a defective rolling bearing is decomposed into a number of intrinsic mode functions (IMFs),...
The principal component related variable residual (PVR) statistic is introduced to industry process monitoring and fault diagnosis in pb-zn smelting process instead of the traditional square prediction error SPE statistic, which confines to Imperial Smelting Process(ISP) as the research background. The PVR statistical is not only able to provide more particular information about the process conditions,...
As the impact of underwater vehicle dynamics modeling error on fault diagnosis system, a method using improved Elman neural network to modify underwater vehicle dynamics model in the current is proposed. The neural network parameter adjustment law under the Lyapunov stability is given. Sliding mode observer is constructed for state estimation based on the modified dynamics model. The change of state...
Process monitoring is critical for efficient operations of industrial processes. When a fault occurs, relevant measured data are affected by the fault, which leads to poor quality of products consequently. This paper proposes a new output-relevant index for detecting faults that affect the output or quality, and studies the fault detectability based on total projection to latent structures (T-PLS)...
With the study and analysis on intelligent fault diagnosis for inverting circuit, an improved diagnosis method combined BP neuron network and D-S evidence theory was proposed. Each measuring point was extracted by BP neural network to obtain the local diagnosis, which is adopted to design the belief function of D-S evidence theory. Multiple monitoring points' information is fused to receive the comprehensive...
The impact fault of the hybrid machine tool were considered as the analysis object in this paper. The kinematics control principle of the hybrid machine tool was given as well as the causes of the impact based on the hybrid structure. The impact suppression method was given, which based on the preview-control algorithm. It was confirmed by experiment that the impact was reduced which was account for...
In this paper, the fault diagnosis problem is studied for progressing cavity pump well base on wavelet package and Elman neural network. The signals of active power can fully reflect the status of progressing cavity pump wells. A new fault diagnosis method for cavity pump wells is presented. This method uses wavelet time-frequency analysis technology for de-noising and filtering of active power signals,...
To online monitor process, a combined approach of fault detection and diagnosis based on Lifting Wavelets and Moving Window PCA (LW-MWPCA) was presented. Firstly the data were pre-processed to remove noise and spikes through lifting scheme wavelets, and then MWPCA was used to diagnose faults. To validate the performance and effectiveness of the proposed scheme, LW-MWPCA was applied to diagnose the...
Forging forming defects and machine failures are often caused by changes of forging force in the forging forming process. Tonnage signals contains significant amount of real-time forming information, by which the forging forming on-line monitoring system is developed. Tonnage signals produced by forging force are collected based on the principle of piezoelectric effect. The charge amplifier circuit...
A disturbance regulation feedback loop is added to state space controller in order to adapt the wind disturbances for wind turbine control systems, and a robust wind turbine speed controller is designed. The dynamic performance of wind turbine speed regulation is improved and mechanical loads are alleviated by proper design of the state-space feedback and DAC feedback parameters. The simulation results...
For a class of large- scale systems with time delays in subsystem interconnection, Optimal design of reliable guaranteed cost stabilization with continual gain sensor faults is presented. Based on the analysis of sensor faults of continue gain faults, sufficient conditions for the existence of the decentralized dynamic output feedback of reliable guaranteed cost are given. The design can guarantee...
In order to improve radar fault diagnosis system, a new architecture of fault diagnosis system based on mobile agents is proposed. The architecture is based on an embedded network built-in radar system. It utilizes all kinds of mobile fault diagnostic agents in embedded network to detect shortcomings of distributed subsystems in radar. In the architecture, all MFDAs can migrate in embedded network,...
Data process of large rotating machinery is in line with basic features of information fusion. A frame of fault diagnosis and prediction based on sensor information fusion is built. An improved extracting method of features is used to deal with the information fusion of single sensor, which raises the calculation efficiency and precision. The local fault prediction process is presented, and the fault...
This paper develops a remote distributed control system (DCS) for central air conditioner based on the Ethernet. The system architecture and function are described in detail in this paper. The DCS control system presents a control-platform that can realize the configuration of the controlled objects in different regions at the same time. In any place with access to the internet, we can perform the...
This paper presents an algorithm of Artificial Neural Network (ANN) pattern recognition method which is applied to the operations of wind turbine control system (WTCS). This paper presents two kinds of improved algorithms of Neural Network (NN) based on the basic principles to improve the convergence speed of the network. To avoid the network falling into the local minimum the genetic algorithm for...
By analyzing the complexity of fault diagnosis grid, we researched the bi-particle projection mode of fault diagnosis grid composed by project nodes and service resource nodes. As the effacter in grid, every project node and service resource node would adopt different strategies, such as selection, decision-making and competition, which will result in self-evolvement and evolvement of whole grid....
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