Sharif Digital Repository

Along with improvement of technology and need for access to energy resources, existence of pipelines such as gas, oil and water pipes is vital for our lives. These pipes will be eroded and damaged over time. With the prediction of the defects and tracking of pipeline paths, the probability of sudden damages is greatly reduced. In this research, at first various non-destructive methods of monitoring the pipelines are investigated and it is shown that the laser method is the most comprehensive and non-destructive inspection method and then the background of the chosen method is examined. Also, the hardware aspect of the system and the proper layout of the laser sensors are determined on the... 

Fatigue life prediction of a mechanical part is one of issues which a group of engineers are engaged with it and always they try to design the parts with the maximum of lifetime. Although many researches have been done in this field but yet we can see that predicted life are different from that happens in the reality because there are some uncertainties in the phenomena. Our effort in this project is creating an algorithm design so that the parts are designed by it, have the maximum fatigue life and the minimum uncertainty in prediction. In this project we have considered geometrical, material and random loading uncertainties as error resources. Older methods those are presented in this... 

Noise pollution is one of the major issues in automative industry. Many of these noises are caused by the internal combustion engine. Using reactive mufflers in the car's exhaust path can effectively reduce this annoying noises. Imposed pressure drop caused by installation this mufflers must be within an acceptable range for the car engine. Resonators, despite having a much lower pressure drop than other components of the exhaust system, can be used to cover the weaknesses of the muffler in the acoustic performance of the noise reduction set. One of the most common methods for designing a resonator is to use perforated plates. In this study the effect of various geometric parameters of a... 

Throughout recent decades, one of the most important and challenging problems in robotics has been robot's path planning. Path planning means a robot must find its way from start to the goal point and track it without any collision to the obstacles. For this aim during the recent decades a wide variety of algorithms such as A*, Dijkstra and … have been proposed that some of which generate an optimal path as their output while others tend to create only a path regardless of its optimality. One of the most practical path planning methods is RRT algorithm which is executable in real-world applications, and by generating some nodes randomly then creating a tree-based graph, thereby outputting a... 

Nowadays, the assembly process is planned by an expert and requires knowledge and it is time-consuming. The flexibility and optimality of the assembly plan depend on the knowledge and creativity of the expert, and therefore expertise is an important parameter in developing the assembly plan. Therefore, the use of intelligent methods to plan the assembly process has been considered by many researchers. . The reinforcing learning approach has the potential to solve complex problems due to the use of experience gained from interacting with the environment and Has been successfully implemented in controlling many robotic tasks. However, due to the inherent complexity of the assembly, as well as... 

Improving the performance of compressors plays a key role in saving energy in industries. The presence of aleatory and epistemic uncertainties, such as dimensional, geometrical and environmental uncertainties, causes the tolerances that are within the allowed ranges in normal assembly conditions to violate the assembly requirements in operational conditions and cause a drop in compressor efficiency. In order to reach the dimensional and geometrical tolerances of the components of a compressor, especially in the design of the rotor and stator blades, that guarantees the optimal and stable performance while not increasi the production costs, there is a need for an optimal and robust tolerance... 

Additive manufacturing (AM)has gained extensive industrial and research attention in recent years. Reducing manufacturing waste, lead-time and costs and the ability to build surfaces and parts with complex shapes, assemblies all at once or parts with internal features are some benefits of AM. However, complex error generation mechanisms underlying AM digital physical chains are likely to result in geometrical inaccuracies of the final product, thus posing significant challenges to design and tolerancing for AM. Therefore, predictive modeling of shape deviations is critical for AM. With increasing volumes and varieties of data, machine learning has gained extraordinary popularity due to its... 

Automated dimensional inspection is commonly expensive because of the requirement for high-precision measurement devices. To perform a precision measurement, the technician must be highly skilled and fully understands the operation of the equipment. Moreover, automation of the mentioned process to reduce dimensional measurement time is a complicated task due to restrictions of precise equipment such as CMM. With the expansion of the use of cameras in the industry, the measurement method with the help of machine vision systems is one of the cost-effective methods that can be achieved with the development of a suitable image processing algorithm to achieve acceptable accuracy compared to... 

The unique ability of additive manufacturing in manufacturing industrial parts with complex geometries has led to the development of topology optimization methods and their use for the optimal design of parts in various industries. However, considering the limitations of additive manufacturing methods in the optimal design of parts is usually a difficult process, and when making decisions, facing multiple conflicting design goals is often difficult and usually involves high computational cost. The main goal of this research is to provide a topology optimization method for generative design for additive manufacturing based on the concept of constructive solid geometry and using machine... 

In recent years, Additive Manufacturing has been extensively used by various industries. These manufacturing processes produce components in a layer-by-layer manner; therefore, they do not impose any geometric constrains to engineers and provide designers with the freedom to design components. Nowadays, one of the primary goals of all industries is to utilize as few raw materials as possible; this way they can deal with the shortage of raw materials and improve their efficiency. Consequently, they implement topology optimization algorithms to design and produce their components. However, topology optimization algorithms result in complicated geometries that can only be fabricated by AM.... 

In this project an optimized and robust orientation estimation method using IMU and magnetic sensors is presented. Magnetic distortion effects in orientation estimation is also one of the main purposes. Proposed sensor fusion algorithm is based on a complementary filter which provides a quaternion estimation as the algebraic solution of a system from inertial/magnetic observations. To develop the basic sensor fusion algorithm some procedures including a simple calculation to deal better with non-gravitational accelerations, decrease the effect of magnetometer in the presence of distortions and online gyroscope bias estimation is added. Also, a method for classification the different types of... 

Tolerance allocation in the recent mechanical assembly is significant because it straightly affects product performance and cost. Loose tolerances may cause the quality defect while tight tolerances can increase the cost. Thermal effects and the temperature gradients are one of the factors that caused changes in the size and geometry of the components during the performance of mechanical assemblies. This thesis proposes a new approach for tolerance design considering the thermal effects, to achieve lower manufacturing cost and good product quality. Finite element analysis is used to determine the deformation of components in an assembly. The neural network is trained using experimental... 

A mechanical system inherently affected by the conditions, factors and parameters of uncertainty. Without including the uncertainty effects in the optimal design procedure, the mechanical system will not be reliable. To include uncertainty effects in an optimum design, there are two different approaches; the robust design optimization and the reliability based design optimization. In robust design optimization process, the main aim is to enhance the system performance by minimizing the variations. In reliability based design optimization process, the target is that the optimal design variables to be in appropriate reliably levels. In this paper, a new model for the reliability based robust... 

Because of increasing demands for using of rotating systems in high accuracy and high speed applications, in addition of specific condition of rotating systems, it is necessary to analysis these rotating systems characteristics. In addition to the dimensional and geometrical errors of mechanical system parts and assembly errors, manufacturing quality directly depends on Non Repetitive Run-Out (NRRO) errors; so the results of NRRO errors as an ultra-precision characteristic should be studied in required outputs. In this paper by analyzing dimensional and geometrical tolerances as tolerance zone, the variations of system outputs because of tolerances is calculated in both static and dynamic... 

Gears are a major component of many transmission systems. nowadays, improving the operating conditions and reducing the weight of the gears is one of the most needed issues in the industry. This dissertation aims to find the optimal structure of gear under different load cases and reduce its weight optimally. In this regard, topology optimization is used to develop the gear structure.In this research, two areas of bio-inspired design and additive manufacturing are used to achieve goals. These two areas can make good use of each other's potentials and achieve results that were not previously possible with traditional methods of design and manufacturing. First, an introduction and history of... 

The field of learning from demonstration is the field in which researchers seek to create methods by which a robot can learn and reproduce a skill simply by using the demonstration of the skill. One of the main drawbacks of learning from demonstration methods is their inability to improve the learned skills. To answer this question, the reinforcement learning method can be used. The reinforcement learning approach has the potential to improve the initial skill due to the use of the experience of interacting with the environment. In this project, the dynamic movement primitives algorithm is considered as the learning from demonstration method. The research approach is that first, the dynamic... 

Nowadays, with the remarkable development of the robotics industry, there is an increasing demand for mobile robots. Mobile robots can be deployed individually or in groups for various tasks such as autonomous warehouses, search and rescue operations, firefighting operations, and maintenance and repairs. It is evident that performing certain tasks, such as moving large and long objects or firefighting operations, is more efficient when robots are deployed cooperatively, and in some cases, these tasks cannot be accomplished by a single robot alone. Therefore, in recent years, the issue of path planning for cooperative robots has received significant attention. By cooperation, we mean that... 

Today, the additive manufacturing process is one of the most important manufacturing processes. In the additive manufacturing process, the mass of the parts is directly related to the printing duration, in addition to the costs of consumables. On the other hand, the use of lighter parts in industries, such as the aviation, is one of the important requirements of those industries, and topology optimization is needed to reduce the consumables and the mass of the parts. Also, since in the optimal design of engineering parts, more than one design objective is usually considered, the multi-objective optimization of topology is of great importance. The Moving Morphable Components is one of the new... 

In the present era, with the remarkable advancements in the robotics industry and the extensive development they have achieved in human societies, the role of robots is very fundamental and vital. Autonomous robots, as an essential part of this industry, are increasingly advancing and improving. One of the most crucial aspects of the efficiency of autonomous robots is their intelligent path planning and navigation. Although previous works have addressed the issue of path planning and navigation based on deep reinforcement learning, many challenges remain, especially in scenarios where the robot's knowledge of the environment is limited and minimal. In this research, by defining a deep... 

Additive manufacturing (AM), also known as Rapid prototyping or D printing, is a new technology for the manufacturing of the physical parts through an additive manner. In the AM process, the orientation pattern of the part is one of the most important factors that significantly affects the product properties such as the build time, the surface roughness, the mechanical strength, the wrinkling, and the amount of support material. The build time and the surface roughness are the more imperative criteria than others that can be considered to find the optimum orientation of parts. In this research, Two method is used to optimize part build orientation (PBO). In the first method a new combined...