List of Articles عیب یابی

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  1 - Intelligent Identification of Centrifugal Pump Damage by Combining Methods Independent Component Analysis and Particle Swarm Optimization
  Mohammad sadegh Aalaei Mehdi Shekarzadeh
  Due to the progress of technical and engineering sciences and the more complex equipment and machinery in recent years, the maintenance and repair technology based on condition monitoring and defect estimation, under different titles such as performance-based logistic ( More

  Due to the progress of technical and engineering sciences and the more complex equipment and machinery in recent years, the maintenance and repair technology based on condition monitoring and defect estimation, under different titles such as performance-based logistic (PBL) and condition-based maintenance (CBM) is considered. These methods are used to prevent human and financial losses and to increase the production rate. This thesis presents an intelligent troubleshooting system to diagnose centrifugal pump-bearing faults. As a result, to design this intelligent troubleshooting system, a test set including shaft, bearings and real support conditions was designed and implemented in the laboratory. In this setup, three bearings with Normal wear and fault conditions (defect on the outer race) were examined, and vibration data were obtained. Then, the vibration data in extraction time and statistical features were calculated. After that, these features were used as classifier input data for intelligent troubleshooting. To identify the defect, the independent component analysis method was used. Also, the accuracy of fault detection was improved by using the particle batch optimization method. Finally, it was found that the statistical feature of Percentile can detect bearing defects by combining independent component analysis and particle swarm optimization methods. Manuscript profile
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  2 - Damage detection in rotating shafts possessing transverse crack through vibration analysis of breathing crack model
  Abbas Azemati Mehdi Salehi Sattar Mohammadi-Esferjani
  This paper deals with transverse crack identification in rotating shafts. In this research, after presenting the equations governing the problem, different depths and positions of crack in a rotating axis of an industrial compressor unit is investigated using a breathin More

  This paper deals with transverse crack identification in rotating shafts. In this research, after presenting the equations governing the problem, different depths and positions of crack in a rotating axis of an industrial compressor unit is investigated using a breathing crack model. Crack is modeled based on the principles of fracture mechanics and the system's motion equations are extracted. Stress intensity coefficients are implemented to model the actual crack behavior in gradual opening and closeing situations. The results showed that in the points where the cracks are closed, the stiffness has its maximum value. Also, with increasing crack depth, the total stiffness of the shaft decreases. The first harmonic in the frequency corresponds to imnbalance and the second harmonic associated with the crack effect. By changing the position of the crack from the ends to the center of the shaft, the frequency of the second harmonic decreases while its amplitude decreases. Inverse analysis can be carried out based on the second frequency along with its amplitude in order to crack identification. Manuscript profile
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  3 - Experimental Condition Monitoring of Unbalanced Rotary Shaft Based on ANFIS by Using Piezoelectric Sensor
  Mojtaba Hasanlu
  Todays, there are using hybrid methods in order to reach high level degree of accuracy and reliability for engineering systems. According to more reality modelling of system, it was mixed three strategies such as fuzzy, artificial neural networks and adaptive method. Th More

  Todays, there are using hybrid methods in order to reach high level degree of accuracy and reliability for engineering systems. According to more reality modelling of system, it was mixed three strategies such as fuzzy, artificial neural networks and adaptive method. This mixed methods is presenting and analyzing each of engineering problem. Adaptive-Neural-Fuzzy (ANF) can be showed in which a robustness and reliable model by designer who assess that in order to make decision as well. In this paper, main aim is experimental condition and health monitoring of rotary system is including shaft, bearings, electromotor which are main components of system and using piezoelectric as sensor by ANF method. Firstly, by using LabVIEW software, experimental data of flexural vibration was recorded with piezoelectric sensor where were fixed on top of bearings, and secondly we used MATLAB software for analyzing experimentation for presentation of ANF model in order to curve fitting of data. Manuscript profile
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  4 - مدلسازی لوله های انتقال گاز با شبکه های عصبی مصنوعی به منظور تشخیص عیوب آنها
  علی جودکی مرتضی محمدظاهری احسان جمشیدی
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  5 - 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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  6 - 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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  7 - تشخیص انواع عیوب چرخ دنده با استفاده از سیگنالهای آکوستیک امیشن توسط درخت مدلی لجستیک
  کاترین خلیفه زاده محسن سریانی
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  8 - بررسی حساسیت روش های عیب یابی بر پایه شکل مود به شدت آسیب
  علی حسن زاده جعفر اسکندری جم سعید شکرالهی
  اهمیت داشتن توانایی برای نظارت بر سلامت سازه و شناسایی آسیب در سریعترین زمان ممکن، یکی از مهمترین دغدغه­های مهندسان به‌ویژه در رشته­های مکانیک و هوافضاست. این اهمیت ناشی از آن است که آسیب و تخریب یک سازه در حین خدمت می‌تواند خسارات مالی و جانی بسیار شدید و بعضاً More

  اهمیت داشتن توانایی برای نظارت بر سلامت سازه و شناسایی آسیب در سریعترین زمان ممکن، یکی از مهمترین دغدغه­های مهندسان به‌ویژه در رشته­های مکانیک و هوافضاست. این اهمیت ناشی از آن است که آسیب و تخریب یک سازه در حین خدمت می‌تواند خسارات مالی و جانی بسیار شدید و بعضاً جبران‌ناپذیری را به دنبال داشته باشد. یکی از روش­های مورد توجه در این عرصه، روش عیب­یابی با استفاده از تغییرات در خصوصیات ارتعاشی سازه است. هدف از تحقیق حاضر عیب­یابی پوسته استوانه­ای کامپوزیتی از طریق انجام آنالیز مودال تجربی و به کمک روش­های عیب­یابی بر پایه شکل مود و بررسی حساسیت آن­ها در برابر شدت­های مختلف آسیب است. نتایج حاصل بیانگر آن است که تکنیک­های عیب­یابی بر پایه شکل مود از آنجا که مستقیماً از داده‌های خام تست مودال استفاده نمی­کنند، قابلیت اطمینان کمتری نسبت به تکنیک عیب­یابی دیگر دارند و کارامدی روش­های ذکر شده شدیداً به دقت تست و داده­های مودال استخراج شده وابسته است. به‌طور کلی اکثر روش­های مورد استفاده به جز در مرحله اول آسیب یعنی حفره­ای با ضخامت 4 میلی‌متر، در دیگر مراحل قادر به تشخیص موقعیت آسیب هستند. Manuscript profile