A Proposed ANN-Based Acceleration Control Scheme for Soft Starting Induction Motor

In this article, a new soft starting control scheme based on an artificial neural network (ANN) is presented for a three-phase induction motor (IM) drive system. The main task of the control scheme is to keep the accelerating torque constant at a level based on the value of reference acceleration. This is accomplished by the proper choice of the firing angles of thyristors in the soft starter. Using the ANN approach, the complexity of the online determination of the thyristors firing angles is resolved. The IM torque-speed characteristic curves are firstly used to train the ANN model. Secondly, the IM- soft starter system is modeled using MATLAB/SIMULINK. To prove the effectiveness of the proposed ANN-based acceleration control scheme, different reference accelerations and loading conditions are applied and investigated. Finally, a laboratory prototype of 3 kW soft starter is implemented. The proposed control scheme is executed in a real-time environment using a digital signal processor (Model: TMS320F28335). The simulation and real-time results significantly confirm that the proposed controller can efficiently reduce the IM starting current and torque pulsations. This in turn ensures a smooth acceleration of the IM during the starting process. Moreover, the proposed control scheme has the superiority over several soft starting control schemes since it has a simple control circuit configuration, less required sensors, and low computational burden of the control algorithm. © 2021 Institute of Electrical and Electronics Engineers Inc.. All rights reserved

Comparative analysis of PID and neural network controllers for improving starting torque of wound rotor induction motor

Unlike 3-phase squirrel cage induction motor, starting-up of 3-phase wound rotor counter part can be improved by adding an external resistance to the rotor circuit.Thus, leads to reduce starting current and increase starting torque. In this paper two controllers for 3-phase wound rotor induction motor have been proposed include conventional proportional integral derivative (PID)  controller and the other based on artificial neural network (NARMA-L2). A comparison between these controllers has been conducted. It has been shown that starting torque of the motor has been improved, when utilizing the neural network controller compared to the conventional counter  part. It should be noted that MATLAB/SIMULINK has been used to implement both controllers

Bond Graph Modeling and Control of Induction Motor used in Ladle Cranes

Initially when power is supplied, induction motor runs at its rated speed with the recommended specifications and varying applications. Control of the motorrsquo;s speed with the improvement of the induction motorrsquo;s dynamic and steady state characteristics which are non-linear in nature, has been possible due to the advancement of electronics. The popularity of this motor has resulted into lot of research including the transient behavior of the motor. A methodology based on modeling capabilities along with control and its computer simulation has been proposed in this paper and is represented by dynamic modeling of three-phase four pole induction motor. When physical modeling of systems is necessary the bond graph approach is good, again it is also a good tool for combining different energy domains. Dependencies between different components can easily be found through the method of bond graph. This study was conducted on the basis of parameters collected from different ladle cranes motors of Durgapur Steel Plant in India

A framework for modeling and control of wastewater pumping stations

In waste water pumping stations, centrifugal pumps driven by induction motors are used to transport the effluent collected from residential and commercial buildings to the treatment plants. Due to the varying nature of collected effluent rate, means of pump flow control should be applied. Recently, there is an engineering debate on either recommending frequency converters control or on-and-off control using soft starter technology. While there are obvious reward and cost of utilizing either approach, the lack of a simulation model makes the selection decision a matter of poor agreement. This is likely to happen in developing areas where abnormal running conditions such as power failure, excess flows, and lack of spare parts are frequently encountered. In this paper, a method for modeling wastewater pumping stations using the component oriented modeling language Modelica is presented. The model provides a valuable simulation tool to validate and judge on the different control schemes of these stations. This approach is applied successfully on a real pumping station located at the northern part of Gaza. The derived model facilitates tuning the control parameters and allows better understanding of the system dynamics

Advances in the Field of Electrical Machines and Drives

Electrical machines and drives dominate our everyday lives. This is due to their numerous applications in industry, power production, home appliances, and transportation systems such as electric and hybrid electric vehicles, ships, and aircrafts. Their development follows rapid advances in science, engineering, and technology. Researchers around the world are extensively investigating electrical machines and drives because of their reliability, efficiency, performance, and fault-tolerant structure. In particular, there is a focus on the importance of utilizing these new trends in technology for energy saving and reducing greenhouse gas emissions. This Special Issue will provide the platform for researchers to present their recent work on advances in the field of electrical machines and drives, including special machines and their applications; new materials, including the insulation of electrical machines; new trends in diagnostics and condition monitoring; power electronics, control schemes, and algorithms for electrical drives; new topologies; and innovative applications

Remote machine condition monitoring based on power supply measurements

The most widely used rotating machines in the industry are three phase alternative current (AC) induction machines. With the advances in variable speed drive (VSD) technology, they have become even more reliable than their direct current (DC) counterpart. However, inevitably these motors soon begin to fail with time due to mechanical, electrical or thermal stress hence the need for condition monitoring (CM). Condition monitoring systems help keep machines running productively by detecting potential equipment failures before it actually fails. Many condition monitoring methods exist on the market including vibration monitoring; acoustic emission monitoring, thermal monitoring, chemical monitoring, current monitoring but most of these methods require additional sensors and expensive data acquisition system on top of a specialise software tool. This all increases the cost of ownership and maintenance. For more efficient monitoring of induction motor drive systems, this research investigates an innovative remote monitoring system using existing data available in AC drives based on AC motor operating process. This research uses standard automation components already present in most automated control systems. A remote data communication platform is developed, allowing access to the control data remotely over a wireless network and internet using PLC and SCADA system. Remote machine condition monitoring is not a new idea but its application to machine monitoring based on power supply parameters indirectly measured by an inverter is new. To evaluate the basic performance of the platform, the monitoring of shaft misalignment, a typical fault in mechanical system is investigated using an in-house gearbox test rig. It has resulted in a model based detection method based on different speed and load settings against the motor current feedback read by the inverter. The results have demonstrated that the platform is reliable and effective. In addition the monitoring method can be employed to detect and diagnose different degrees of misalignment in real time. This dissertation has major contributions to knowledge which includes: Understanding of real life machine condition monitoring problems for this application, including use of wireless sensor, communication over Industrial Ethernet and network security. The use of standard automation components (PLC and SCADA) in machine condition monitoring. MSc Research (Engineering) Thesis x An improved gearbox test rig platform which has the capability of remote control, acquiring and transferring data for monitoring induction machine drive system. The presented work shows that any machine using automated components such as PLC and SCADA and incorporating motor drive systems and other actuators has the potential to use the automated components for control, condition monitoring and reporting but this will require more tests to be done using the proposed platform