Sharif Digital Repository

Fault detection and identification is one of the major issues and challenges in the field of engineering and currently is considered as an active field of research. As the replacement of human in dangerous or inaccessible environments, robotic mechanical systems can be used which exposes to a variety of stresses and actions that causes faults in the actuators or sensors. Accordingly, detection of fault at the earliest possible time after the fault accurence and its identification such that real flaw waveform is being extracted, can prevent more damage to the system without any need to human immediate interference. Model based approach in recent decades has shown their ability to detection... 

Fault detection in swarm robots is one of the most important issues that has drawn a lot of scientists’ attention. Previous studies have shown a lot of problems regarding this issue, such as dependency of data-based methods to mission and high complexity of model-based methods on the condition that nonlinear models are used. Extended information filter is an applicable method for fault detection because it could turn the inverse of a big matrix to a simple summation of information that is so desired in terms of calculations. The goal of this study is to identify the agents with fault in swarm robots online by modifying the extended information filter. In this study, it has been attempted to... 

Fatigue crack growth can have harmful effects on the reliability rotary machine. While an early warning to crack, can be used to extend the life of these expensive machines and increase reliability.Structural Vibration Condition Monitoring as a primary fault detection method, achieved to a lot amazing result and for this reason studies vibration behavior of cracked rotational shaft is a big issue for engineers of dynamic machine.In this research, first check the fault detection methods based on structural vibration condition monitoring, mode shape methods were extracted. Then by modeling rotational shaft in computer and creation of crack on it, fault detection quality of these methods have... 

One of the most critical equipments in power grids are power transformers, which are vulnerable to damage due to the possibility of faults in its various components. A very common category of such faults is turn-to-turn fault in its winding. This fault initiates by the aging of the winding insulation with a short circuit of several adjacent loops to each other and if it is not detected quickly by the transformer protection, it will spread rapidly and can lead to irreparable failure in the transformer. Traditionally, turn-to-turn fault should be detected by mechanical pressure relays, however, due to the poor performance of these relays in the rapid detection of this type of fault, in the... 

Today, data analysis has become a valuable tool in various fields in order to discover the forms or abnormal behavior of the system. For example, detecting credit card fraud, network intrusion, or detecting defects in sensors. In this thesis, a method for fault analysis is presented, which can be used as a monitoring tool to monitor the data that is received in a time series from an Internet of Things system and understand the behavior of the system. This method is designed in such a way that by matching the components with the input data, in general, it is applicable for our desired time series. The presented algorithm is implemented in an unsupervised environment using a statistical... 

Oscillation in control loops is a common problem in industrial processes. To ensure proper system performance, oscillation in control loops must first be properly detected and then eliminated. Various non-machine learning methods have been used in oscillation detection for years, with the development of machine learning algorithms, hardware improvements and easy access to diverse data, these methods have also been used for oscillation detection in recent years. In the research conducted the field of oscillation detection with machine learning, the focus has been on the advantages of machine learning methods compared to other methods. In this thesis, the aim is to examine and compare... 

This thesis focuses on the detection and estimation of faults occurring in one of the reaction wheel axes of a three-axis stabilized satellite. The wheel axes are aligned with the satellite's body axes, and the emphasis is on the attitude (rather than position) of the satellite. The primary goal of the subsystem is to determine and control the satellite's attitude, transitioning from its initial state to a desired Earth-pointing state. It is assumed that environmental disturbances, including gravitational disturbances and Drag related disturbances, are considered. Based on this, a PID controller is designed after modeling the nonlinear kinematics and dynamics of the satellite using Euler...