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Total 49 records

    Fault diagnosis of a centrifugal pump by vibration analysis

    , Article Proceedings of the 7th Biennial Conference on Engineering Systems Design and Analysis - 2004, Manchester, 19 July 2004 through 22 July 2004 ; Volume 3 , 2004 , Pages 221-226 ; 0791841731 (ISBN); 9780791841730 (ISBN) Behzad, M ; Bastami, A. R ; Maassoumian, M ; Sharif University of Technology
    American Society of Mechanical Engineers  2004
    Abstract
    This paper gives the final Solution for vibration reduction in a centrifugal pump. Vibration measurement in different conditions has been carried out in order to find the main reason for excessive vibration of the pumps. In the first stage several parameters including cavitation, not working in the pump design condition and mechanical and electrical faults assumed to be the reason for the pump vibration. By vibration analysis it is found that the major reason for the pump vibration is working in off design conditions. More over dissolved air in the suction fluid can possibly cause two-phase flow leading to the pump vibration. For solving both problems considering pump performance curves it... 

    Multiple simultaneous fault diagnosis via hierarchical and single artificial neural networks

    , Article Scientia Iranica ; Volume 10, Issue 3 , 2003 , Pages 300-310 ; 10263098 (ISSN) Eslamloueyan, R ; Shahrokhi, M ; Bozorgmehri, R ; Sharif University of Technology
    Sharif University of Technology  2003
    Abstract
    Process Fault Diagnosis (PFD) involves interpreting the current status of the plant given sensor readings and process knowledge. There has been considerable work done in this area with a variety of approaches being proposed for PFD. Neural networks have been used to solve PFD problems in chemical processes, as they are well suited for recognizing multi-dimensional nonlinear patterns. In this work, the use of Hierarchical Artificial Neural Networks (HANN) in diagnosing the multi-faults of a chemical process are discussed and compared with that of Single Artificial Neural Networks (SANN). The lower efficiency of HANN, in comparison to SANN, in PFD is elaborated and analyzed. Also, the concept... 

    A new method for detection and evaluation of winding mechanical faults in transformer through transfer function measurements

    , Article Advances in Electrical and Computer Engineering ; Volume 11, Issue 2 , 2011 , Pages 23-30 ; 15827445 (ISSN) Bigdeli, M ; Vakilian, M ; Rahimpour, E ; Sharif University of Technology
    2011
    Abstract
    Transfer function (TF) is an acknowledged method for power transformer mechanical faults detection. However the past published works mostly discovered how to specify the faults levels and paid less attention to detection of the type of faults using comparison of TFs. whereas, it seems important for most of the applications to specify the type of fault without opening the unit. This paper presents a new method based on vector fitting (VF) to compare the TFs and specify the type, level and location of the fault. For development of the method, and its verification the required measurements are carried out on four model transformers; under intact condition, and under different fault conditions... 

    Impacts of fault diagnosis schemes on distribution system reliability

    , Article IEEE Transactions on Smart Grid ; Volume 3, Issue 2 , February , 2012 , Pages 720-727 ; 19493053 (ISSN) Kazemi, S ; Lehtonen, M ; Fotuhi Firuzabad, M ; Sharif University of Technology
    2012
    Abstract
    Design and development of fault diagnosis schemes (FDS) for electric power distribution systems are major steps in realizing the self-healing function of a smart distribution grid. The application of the FDS in the electric power distribution systems is mainly aimed at precise detecting and locating of the deteriorated components, thereby enhancing the quality and reliability of the electric power delivered to the customers. The impacts of two types of the FDS on distribution system reliability are compared and presented in this paper. The first type is a representative of the FDS which diagnoses the deteriorated components after their failing. However, the second type is a representative of... 

    A new fault detection method for modular multilevel converter semiconductor power switches

    , Article 41st Annual Conference of the IEEE Industrial Electronics Society, 9 November 2015 through 12 November 2015 ; 2015 , Pages 50-55 ; 9781479917624 (ISBN) Haghnazari, S ; Shahbazi, M ; Zolghadri, M. R ; IEEE Industrial Electonics Society (IES) ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc 
    Abstract
    This paper proposes a new fault detection method for the modular multilevel converter (MMC) semiconductor power switches. While in common MMCs, the modules capacitor voltages are measured directly for control purposes, in this paper voltage measurement point changes to module output terminal improving fault diagnosis ability. Based on this measurement reconfiguration, a novel fault detection algorithm is designed for MMCs semiconductor power switches. The open circuit and short circuit faultsare detected based on unconformity between modules output voltage and switching signals. Simulations results confirm accurate and fast operation of the proposed algorithm in faulty module diagnosis.... 

    Detection of single and dual incipient process faults using an improved artificial neural network

    , Article Iranian Journal of Chemistry and Chemical Engineering ; Volume 24, Issue 3 , 2005 , Pages 59-66 ; 10219986 (ISSN) Pishvaie, M. R ; Shahrokhi, M ; Sharif University of Technology
    2005
    Abstract
    Changes in the physicochemical conditions of process unit, even under control, may lead to what are generically referred to as faults. The cognition of causes is very important, because the system can be diagnosed and fault tolerated. In this article, we discuss and propose an artificial neural network that can detect the incipient and gradual faults either individually or mutually. The main feature of the proposed network is including the fault patterns in the input space. The scheme is examined through a sample unit with five probable occurring faults. The simulation results indicate that the proposed algorithm can detect both single and two simultaneous faults properly  

    Development of a Framework to Control and Model Based Fault Diagnosis of a Gas Transmission Network

    , M.Sc. Thesis Sharif University of Technology Kheradmandi, Masoud (Author) ; Bozorgmehry, Ramin (Supervisor)
    Abstract
    In this project a framework for Model Based Fault Diagnosis (MBFD) in a Gas Transmission Network (GTN) was developed. A black-box linear state-space model was used to capture dynamic behavior of an industrial benchmark for GTN. A full fledge commercial network simulator were used to obtain the required data for process identification. In order to check the robustness of the model zero mean white noise was imposed on various output obtained by the commercial simulator. Kalman filter was used to estimate the states of the GTN. These estimated states along with the measured output (all obtained from the commercial simulator) are almost similar to their corresponding estimated signal. This shows... 

    Experimental investigation on the fault diagnosis of permanent magnet DC electromotors

    , Article Insight: Non-Destructive Testing and Condition Monitoring ; Volume 55, Issue 8 , August , 2013 , Pages 422-427 ; ISSN: 13542575 Behzad, M ; Ebrahimi, A ; Heydari, M ; Asadi, M ; Alasti, A ; Sharif University of Technology
    Abstract
    In this paper, an algorithm for fault diagnosis of permanent magnet DC electromotors.has been investigated, based on vibration and electrical current monitoring. Several permanent magnet DC electromotors.with previously determined faults have been prepared and the vibration, current and speed data have been measured. The relationship between certain related measured data and faults has been determined. A fault diagnosis algorithm has been developed in this research based on these relationships. This algorithm can be used in mass production lines for quality control  

    Fault diagnosis in multivariate control charts using artificial neural networks

    , Article Quality and Reliability Engineering International ; Volume 21, Issue 8 , 2005 , Pages 825-840 ; 07488017 (ISSN) Akhavan Niaki, S. T ; Abbasi, B ; Sharif University of Technology
    2005
    Abstract
    Most multivariate quality control procedures evaluate the in-control or out-of-control condition based upon an overall statistic, like Hotelling's T2. Although T2 is optimal for finding a general shift in mean vectors, it is not optimal for shifts that occur for some subset of variables. This introduces a persistent problem in multivariate control charts, namely the interpretation of a signal that often discourages practitioners in applying them. In this paper, we propose an artificial neural network based model to diagnose faults in out-of-control conditions and to help identify aberrant variables when Shewhart-type multivariate control charts based on Hotelling's T2 are used. The results... 

    Development of a Fault Detection Algorithm for a PFI Engine Based on ECU Output Signals

    , M.Sc. Thesis Sharif University of Technology Falsafi, Pedram (Author) ; Hosseini, Vahid (Supervisor) ; Saidi, Mohammad Hassan (Supervisor)
    Abstract
    Electronic engine control unit (ECU) operates the different actuators using information signals received from the different sensors. Also in the case of any fault in the sensors and actuators operation ECU is responsible to detect and alert the accruing faults. Most of the common faults in the engine such as leakage in intake system and ignition system are not detectable by ECU, on the other hand ECU fault codes some times are hard to interpret or misleading. So fault diagnosis is usually based on experience of repair staff, and might be time consuming and inaccurate. In this study, using the knowledge of premixed fuel injection SI engines and emission generation and statistical data,... 

    Optimal Sensor Locations for Monitoring of Fluid Transmission Networks Using Evolutionary Algorithms

    , M.Sc. Thesis Sharif University of Technology Dehghan Manshadi, Mehdi (Author) ; Bozorgmehry, Ramin (Supervisor)
    Abstract
    Monitoring of the water transmission networks is an essential factor to regard efficient, safe and economical strategic considerations. Several parameters (fluid pressure, fluid flow and fluid temperature in some cases) are measured to monitor the water transmission networks. The number and location of these measurements in deferent positions affect the cost and quality of the network states monitoring. It is obvious that measuring the all parameters and states of the network is not cost-effective even when it is possible. The conventional sensor-location methods have been developed based on the pressure variation stemmed from a leakage in the network. This study proposes a new procedure to... 

    Condition Monitoring and Fault Diagnosis of Anti-Lock Brake System (ABS)

    , M.Sc. Thesis Sharif University of Technology Eskandarian, Mehdi (Author) ; Behzad , Mehdi (Supervisor) ; Hoviattalab, Maryam (Supervisor)
    Abstract
    The purpose of this project is fault diagnosis of anti-lock brake system with mechatronic approach. To do this, first an appropriate model of the system has been developed. After validating the model, the effects of change in some parameters that indicates the occurrence of a fault in the system are used to examine the behavior of the system in a model-based manner. With this method, it can be analyzed that how a specific fault will impact other system parameters. in fact; the effect of various defects in the system can be detected.
    To do this, four common faults such as fault occurrence in hydraulic pump and solenoid valves, air presence and oil leakage in the system are implemented... 

    Rolling Element Bearing Fault Diagnosis and Prognosis

    , Ph.D. Dissertation Sharif University of Technology Rohani Bastami, Abbas (Author) ; Behzad, Mehdi (Supervisor)
    Abstract
    Diagnostic and prognostic of spall defect in the rolling element bearings is investigated in this thesis. A new numerical model is proposed which considers defect size, defect clearance and defect roughness. The results of this model based on surface roughness show superior similarity to experimental data than classic model. To improve diagnostic ability in the rolling element bearings, four new methods are proposed in this thesis. These methods are short-time statistical features, local curve roughness, level crossing and wavelet packet decomposition. These methods are applied in outer ring, inner ring and ball defects and it is showed that these methods have better detection ability... 

    Impacts of fault diagnosis schemes on distribution system reliability

    , Article IEEE Transactions on Smart Grid ; Vol. 3, issue. 2 , 2012 , p. 720-727 ; ISSN: 19493053 Kazemi, S ; Lehtonen, M ; Fotuhi-Firuzabad, M ; Sharif University of Technology
    Abstract
    Design and development of fault diagnosis schemes (FDS) for electric power distribution systems are major steps in realizing the self-healing function of a smart distribution grid. The application of the FDS in the electric power distribution systems is mainly aimed at precise detecting and locating of the deteriorated components, thereby enhancing the quality and reliability of the electric power delivered to the customers. The impacts of two types of the FDS on distribution system reliability are compared and presented in this paper. The first type is a representative of the FDS which diagnoses the deteriorated components after their failing. However, the second type is a representative of... 

    Circuit-breaker automated failure tracking based on coil current signature

    , Article IEEE Transactions on Power Delivery ; Vol. 29, issue. 1 , February , 2014 , pp. 283-290 ; ISSN: 08858977 Razi-Kazemi, A. A ; Vakilian, M ; Niayesh, K ; Lehtonen, M ; Sharif University of Technology
    Abstract
    The online condition assessment of circuit breakers (CBs) has been increasingly requested by power utilities in recent years. Trip and close coil current (CC) signature is an effective and noninvasive parameter in CB online condition monitoring. This paper gives an insight into the impacts of the various failures on the coil current waveform, as well as on the CB operation time. The failures and their causes are categorized based on the outcome of these investigations. Finally, a new algorithm using trip/close CC is proposed to detect the mode and cause of CB incipient failures. In this study, the CC patterns are acquired by measurements carried out on (healthy and faulty) CBs of 72.5-kV and... 

    IGBT open-circuit fault diagnosis in a Quasi-Z-source inverter

    , Article IEEE Transactions on Industrial Electronics ; Volume 66, Issue 4 , 2019 , Pages 2847-2856 ; 02780046 (ISSN) Yaghoubi, M ; Shokrollahi Moghani, J ; Noroozi, N ; Zolghadri, M. R ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2018
    Abstract
    In this paper, a fast and practical method is proposed for open-circuit (OC) fault diagnosis (FD) in a three-phase quasi-Z-source inverter (q-ZSI). Compared to the existing fast OC FD techniques in three-phase voltage-source inverters (VSIs), this method is more cost-effective since no ultra-fast processor or high-speed measurement is required. Additionally, the method is independent of the load condition. The proposed method is only applicable to Z-source family inverters and is based on observing the effect of shoot-through (SH) intervals on the system variables during switching periods. The proposed algorithm includes two consecutive stages: OC detection and fault location identification.... 

    IGBT Open-circuit fault diagnosis in a quasi-z-source inverter

    , Article IEEE Transactions on Industrial Electronics ; Volume 66, Issue 4 , 2019 , Pages 2847-2856 ; 02780046 (ISSN) Yaghoubi, M ; Moghani, J. S ; Noroozi, N ; Zolghadri, M. R ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    Abstract
    In this paper, a fast and practical method is proposed for open-circuit (OC) fault diagnosis (FD) in a three-phase quasi-Z-source inverter (q-ZSI). Compared with the existing fast OC FD techniques in three-phase voltage source inverters, this method is more cost-effective since no ultrafast processor or high-speed measurement is required. Additionally, the method is independent of the load condition. The proposed method is only applicable to Z-source family inverters and is based on observing the effect of shoot-through intervals on the system variables during switching periods. The proposed algorithm includes two consecutive stages: OC detection and fault location identification. When both... 

    Analysis, Diagnosis and Improvement of Supply Chain (Case Study: SAIPA Automobile Manufacturer)

    , M.Sc. Thesis Sharif University of Technology Ebrahimzadeh Pilerood, Amir (Author) ; Akbari Jokar, Mohammad Reza (Supervisor)
    Abstract
    Supply chain consists of many important processes that are critical to be analyzed in order to enhance effectiveness and efficiency of the whole organization. This survey presents a state-of-the-art approach for evaluating the health of supply chain processes by conducting a structure based diagnostic methodology. The proposed method is conducted in an Iranian automotive manufacturer and results are validated based on internal documents. The results of assessment can be used to improve supply chain performance by suggesting various projects. Finally different analysis like theme analysis is performed on extracted diagnosis and on suggested projects  

    Torsional Vibration Modeling and Measurement in Single Rotor Machinery for Fault Diagnosis

    , M.Sc. Thesis Sharif University of Technology Hosseini, Alireza (Author) ; Behzad, Mahdi (Supervisor) ; Mahdigholi, Hamid (Supervisor)
    Abstract
    Experimental investigation of drillstring dynamics is essential to complete the theoretical studies and to alleviate complexity of such dynamic models. Vibration is one of the most effective parameter affecting drilling operation. Most of the experimental setups are looking for drilling mud tests, operational characteristics of bit under several bad condition and bit mud stone interaction in drilling operation and there are few setups to study vibration of the drilling setups. In this project a test rig has been introduce which is a scale of a real industrial drilling rig by the factor of 10300. Then based on the field studies of drilling failures in Iranian oil drilling rig , a crack has... 

    Performance Improvement of Cascaded H-bridge Multilevel Inverter under Faulty Conditions

    , Ph.D. Dissertation Sharif University of Technology Ouni, Saeed (Author) ; Zolghadri, Mohammad Reza (Supervisor) ; Oraee Mirzamani, Hashem (Supervisor) ; Rodriguez, Jose (Co-Advisor)
    Abstract
    Fault-tolerant ability is more subjected in Cascaded H-Bridge Multilevel Inverter due to its high-power medium-voltage applications and large number of semiconductors switches used in its structure. In this thesis, the goal is performance improvement of Cascaded H-bridge Multilevel Inverter under faulty conditions. Since to achieve the post-fault ability two steps; fault detection and post-fault control are required, both steps are considered in the improving process. In this dissertation, first operation of Cascaded H-Bridge Multilevel Inverter in normal and faulty condition is surveyed. Then, the conventional fault detection methods are mentioned and post-fault control methods are...