Design and Accomplishment of AI Control Platform for Reactive Power Cloud Compensation System
طراحی و تحقق بستر کنترل هوش مصنوعی برای سیستم جبران ابر برای توان راکتیو-2020
The balance of active and reactive power in the power system is very important for the normal operation of the whole system, the correct method is to inject the corresponding reactive power where much of the reactive power is consumed to maintain the balance. it is of great positive significance to develop a device with integrated new switching technology that can realize non-impact switching of capacitor banks and be controlled by better algorithms. In this paper ???? an artificial intelligent (AI) control platform for reactive power cloud compensation system is designed and achieved, by switching capacitors on the load side, the requirements of capacitor switching conditions are analyzed, the requirements of capacitor bank and capacitor controller are put forward, and the theoretical analysis is carried out. Results of the installation operation in site show high performance of the designed system.
Keywords: control platform | reactive power | artificial intelligent | cloud compensation system
A digital twin to train deep reinforcement learning agent for smart manufacturing plants: Environment, interfaces and intelligence
یک دوقلوی دیجیتال برای آموزش عامل یادگیری تقویتی عمیق برای کارخانه های تولید هوشمند: محیط ، رابط ها و هوش-2020
Filling the gaps between virtual and physical systems will open new doors in Smart Manufacturing. This work proposes a data-driven approach to utilize digital transformation methods to automate smart manufacturing systems. This is fundamentally enabled by using a digital twin to represent manufacturing cells, simulate system behaviors, predict process faults, and adaptively control manipulated variables. First, the manufacturing cell is accommodated to environments such as computer-aided applications, industrial Product Lifecycle Management solutions, and control platforms for automation systems. Second, a network of interfaces between the environments is designed and implemented to enable communication between the digital world and physical manufacturing plant, so that near-synchronous controls can be achieved. Third, capabilities of some members in the family of Deep Reinforcement Learning (DRL) are discussed with manufacturing features within the context of Smart Manufacturing. Trained results for Deep Q Learning algorithms are finally presented in this work as a case study to incorporate DRL-based artificial intelligence to the industrial control process. As a result, developed control methodology, named Digital Engine, is expected to acquire process knowledges, schedule manufacturing tasks, identify optimal actions, and demonstrate control robustness. The authors show that integrating a smart agent into the industrial platforms further expands the usage of the system-level digital twin, where intelligent control algorithms are trained and verified upfront before deployed to the physical world for implementation. Moreover, DRL approach to automated manufacturing control problems under facile optimization environments will be a novel combination between data science and manufacturing industries.
Keywords: Smart manufacturing systems | Robotics | Artificial intelligence | Digital transformation | Virtual commissioning
Intelligent Mining Technology for an Underground Metal Mine Based on Un manned Equipment
تکنولوژی معدن هوشمند برای یک معدن زیرزمینی بر اساس تجهیزات یگان ویژه-2018
This article analyzes the current research status and development trend of intelligent technologies for underground metal mines in China, where such technologies are under development for use to develop mineral resources in a safe, efficient, and environmentally friendly manner. We analyze and summarize the research status of underground metal mining technology at home and abroad, including some specific examples of equipment, technology, and applications. We introduce the latest equipment and technologies with independent intellectual property rights for unmanned mining, including intelligent and unmanned control technologies for rock-drilling jumbos, down-the-hole (DTH) drills, underground scrapers, underground mining trucks, and underground charging vehicles. Three basic platforms are used for intelligent and unmanned mining: the positioning and navigation platform, information-acquisition and communication platform, and scheduling and control platform. Unmanned equipment was tested in the Fankou Lead-Zinc Mine in China, and industrial tests on the basic platforms of intelligent and unmanned mining were carried out in the mine. The experiment focused on the intelligent scraper, which can achieve autonomous intelligent driving by relying on a wireless communication system, location and navigation system, and data-acquisition system. These industrial experiments indicate that the technology is feasible. The results show that unmanned mining can promote mining technology in China to an intelligent level and can enhance the core competitive ability of China’s mining industry.
Keywords : Underground ، Autonomous ، Communication ، Navigation ، Intelligent