List of Articles Fault Detection

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  1 - Developing A Fault Diagnosis Approach Based On Artificial Neural Network And Self Organization Map For Occurred ADSL Faults
  Vahid Golmah Mina Tashakori
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  2 - An approach to fault detection and correction in design of systems using of Turbo ‎codes‎
  H. Hamidi
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  3 - Identify the drawbacks of an electric motor using fast Fourier transform analysis
  Mohsen Ghiasabadi Farahani
  Developments and major changes in the industrial units in different dimensions come into being discourages many new methods and systems to allocate valuable place in the meantime, And efforts in the areas of deployment of such systems will move to improve efficiency and More

  Developments and major changes in the industrial units in different dimensions come into being discourages many new methods and systems to allocate valuable place in the meantime, And efforts in the areas of deployment of such systems will move to improve efficiency and productivity has increased as a result. This research is based on methods such as, Fast Fourier analysis, curve waveform, the bearing rollers and phase angle in frequency space were analyzed, followed by imperfections and their possible origin have been nominated. After surveying data and survey results, the disadvantage caused by the unbalance of electric monetary and non-monetary alignment in transmission was measured.The vibration amplitude and phase angle errors associated with the use of changes and fixes have been identified. Manuscript profile
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  4 - Damage detection in gas transmission lines based on natural frequency changes via artificial neural networks
  Ali Asghar Binaieyan Ehsan Jamshidi Alireza Arghavan
  The purpose of this paper is to introduce a new approach for troubleshooting of gas pipelines using mechanical waveforms. In this paper, an attempt has been made to determine the defects by using natural frequency characteristics and changes. Due to the relationship bet More

  The purpose of this paper is to introduce a new approach for troubleshooting of gas pipelines using mechanical waveforms. In this paper, an attempt has been made to determine the defects by using natural frequency characteristics and changes. Due to the relationship between mass and stiffness in determining the natural frequency, a mass increase has been used instead of the reduction of stiffness. The proposed method involves modeling a 2-inch pipe with a length of 2 m in the Abaqus software and examining the natural frequencies of the pipe in a state of intact and defective (cracking). Then, an equivalent mass value was applied to model the defects. Subsequently, the pipe was subjected to experimental modal analysis and various conditions were tested by creating artificial defects (adding mass). Then, the obtained information was used in the study of the perceptron neural network in MATLAB software, and the program output is the defect location and its severity (mass value). Manuscript profile
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  5 - Fault Detection of Cylinder- head automotive Using Mechanical Waves and Intelligent Techniques
  Mojtaba Doustmohammadi Morteza Mohammadzaheri Ehsan Jamshidi
  Safety of machinery parts, it is important for users and defects as one of the most important parts of threats to the health of the pieces have always been considered. In this paper, a new method based on the use of artificial neural networkDetection Pridecylinder head More

  Safety of machinery parts, it is important for users and defects as one of the most important parts of threats to the health of the pieces have always been considered. In this paper, a new method based on the use of artificial neural networkDetection Pridecylinder head into mechanical waves is presented. Then, for verification and validation of the finite element model , modal test piece , and after confirming the fault simulation is performed on a finite element model. Force simulation model (FEM) acceleration signal - the healthy and faulty models calculated for each fault. And with the signing of mechanical defects ( acceleration difference between healthy and faulty models ) and to train a multilayer perceptron neural network (MLP) , the difference between the acceleration signal to the associated fault location. Detectionautomotive cylinder head (estimated fault location) has been. The results of the neural network capabilities designed to estimate the fault location on a good show.  Manuscript profile
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  6 - Fault Detection Based on Type 2 Fuzzy system for Single-Rod Electrohydraulic Actuator
  Hamid Ghadiri
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  7 - Identification and Robust Fault Detection of Industrial Gas Turbine Prototype Using LLNF Model
  Leila Shahmohamadi Mahdi AliyariShoorehdeli Sharareh Talaie
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  8 - A Review on Fault Detection and Diagnosis Methods in Distribution Power Networks
  Milad Samady Shadlu
  Fault detection and diagnosis algorithms are the methods whose function is determining the fault point in a system according to pre-faulting and post-faulting conditions, and fault detector is a part of system which performs this function. Accordingly, the aspects like More

  Fault detection and diagnosis algorithms are the methods whose function is determining the fault point in a system according to pre-faulting and post-faulting conditions, and fault detector is a part of system which performs this function. Accordingly, the aspects like fault detection and diagnosis and faulted point isolation have been introduced. Until now many researches have focused on fault detection methods in different parts of power system such as transformers, converters, overhead lines, underground cables, feeders, breakers, protection relays, generators, turbines, etc. , which every one of them has proposed a new and effective method in supplementing of previous works. In this paper, a comprehensive study is done on fault detection and diagnosis in distribution power systems. Also, categorizing and also methodology of previous works in literature is addressed. Fault detection and diagnosis algorithms are divided based on two viewpoints and characteristics and features of each one are described completely. Manuscript profile
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  9 - Improving Performance of Total Harmonic Distortion Based Fault Detection Scheme for Inverter Interfaced Islanded Microgrids
  Iman Sadeghkhani
  Global warming and environmental concerns have led to increasing penetration of converter interfaced renewable energy resources. One of the main challenges of inverter interfaced islanded microgrids is the fault detection. This paper investigates the performance of tota More

  Global warming and environmental concerns have led to increasing penetration of converter interfaced renewable energy resources. One of the main challenges of inverter interfaced islanded microgrids is the fault detection. This paper investigates the performance of total harmonic distortion (THD) based fault detection scheme when various inverter topologies, main current limiting strategies, and different reference frame are employed. Then, based on this analysis, the performance of THD based fault detection scheme is improved using the instantaneous saturation limit and independent control capability in the natural reference frame. The proposed scheme does not mal-operate in the presence of non-linear loads and can distinguish fault condition from load change. Also, using the auxiliary control system, the proposed fault detection scheme is capable of detecting single line to ground fault in three wire system when synchronous/stationary reference frame is employed. Various time-domain simulations verify the effectiveness of the proposed scheme in the case of symmetrical and unsymmetrical faults. Manuscript profile
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  10 - Detection of Stator Winding Fault in Induction Motor Using Fuzzy Logic with Optimal Rules
  Hamid Fekri Azgomi Javad Poshtan
  Induction motors are critical components in many industrial processes. Therefore, swift, precise and reliable monitoring and fault detection systems are required to prevent any further damages. The online monitoring of induction motors has been becoming increasingly imp More

  Induction motors are critical components in many industrial processes. Therefore, swift, precise and reliable monitoring and fault detection systems are required to prevent any further damages. The online monitoring of induction motors has been becoming increasingly important. The main difficulty in this task is the lack of an accurate analytical model to describe a faulty motor. A fuzzy logic approach may help to diagnose traction motor faults. This paper presents a simple method for the detection of stator winding faults (which make up 38% of induction motor failures) based on monitoring the line/terminal current amplitudes. In this method, fuzzy logic is used to make decisions about the stator motor condition. In fact, fuzzy logic is reminiscent of human thinking processes and natural language enabling decisions to be made based on vague information. The motor condition is described using linguistic variables. Fuzzy subsets and the corresponding membership functions describe stator current amplitudes. A knowledge base, comprising rule and data bases, is built to support the fuzzy inference. Simulation results are presented to verify the accuracy of motor’s fault detection and knowledge extraction feasibility. The preliminary results show that the proposed fuzzy approach can be used for accurate stator fault diagnosis. Manuscript profile
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  11 - Inter-Turn Fault Detection of PMSM Based on Fuzzy Logic and Discrete Wavelet Transform Using Unsupervised Clustering
  Vahid Khodashenas Limouni S.Asghar Gholamian Mehran Taghipour Gorjikolaie
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