دانلود مقاله ISI انگلیسی شماره 1432
عنوان فارسی مقاله

یکپارچه سازی نظریه سیستم خاکستری و رگرسیون لجستیک با استدلال مبتنی بر مورد برای ارزیابی ایمنی نیروگاه های حرارتی

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
1432 2012 14 صفحه PDF سفارش دهید 10850 کلمه
خرید مقاله
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عنوان انگلیسی
Integrating gray system theory and logistic regression into case-based reasoning for safety assessment of thermal power plants
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Expert Systems with Applications, Volume 39, Issue 5, April 2012, Pages 5154–5167

کلمات کلیدی
نیروگاه های حرارتی - ارزیابی مدیریت ایمنی - استدلال مبتنی بر مورد - سیستم پشتیبانی تصمیم هوشمند - تئوری سیستم خاکستری - رگرسیون لجستیک -
پیش نمایش مقاله
پیش نمایش مقاله یکپارچه سازی نظریه سیستم خاکستری و رگرسیون لجستیک با استدلال مبتنی بر مورد برای ارزیابی ایمنی نیروگاه های حرارتی

چکیده انگلیسی

Safety assessment of thermal power plants (TPPs) is one of the important means to guarantee the safety of production in thermal power production enterprises. Due to various technical limitations, existing assessment approaches, such as analytic hierarchy process (AHP), Monte Carlo methods, artificial neural network (ANN), etc., are unable to meet the requirements of the complex security assessment of TPPs. Currently, most of the security assessments of TPP are completed by the means of experts’ evaluations. Accordingly, the assessment conclusions are greatly affected by the subjectivity of the experts. Essentially, the evaluation of power plant systems relies to a large extent on the knowledge and length of experience of the experts. Therefore in this domain case-based reasoning (CBR) is introduced for the security assessment of TPPs since this methodology models expertise through experience management. Taking the management system of TPPs as breakthrough point, this paper presents a case-based approach for the Safety assessment decision support of TPPs (SATPP). First, this paper reviews commonly used approaches for TPPs security assessment and the current general evaluation process of TPPs security assessment. Then a framework for the Management System Safety Assessment of Thermal Power Plants (MSSATPP) is constructed and an intelligent decision support system for MSSATPP (IDSS-MSSATPP) is functionally designed. IDSS-MSSATPP involves several key technologies and methods such as knowledge representation and case matching. A novel case matching method named Improved Gray CBR (IGCBR) has been developed in which a statistical approach (logistic regression) and Gray System theory are integrated. Instead of applying Gray System theory directly, it has been improved to integrate it better into CBR. In addition this paper describes an experimental prototype system of IDSS-MSSATPP (CBRsys-TPP) in which IGCBR is integrated. The experimental results based on a MSSATPP data set show that CBRsys-TPP has high accuracy and systematically good performance. Further comparative studies with several other common classification approaches also show its competitive power in terms of accuracy and the synergistic effects of the integrated components.

مقدمه انگلیسی

Thermal power plants (TPPs) equip numerous industrial departments and their productive process is very complicated. In TPPs, the frequency of accidents with serious consequences is extremely high. When operating TPPs, the safety of people’s lives and work conditions is a major concern. There are numerous TPPs all over the world. Taking China as an example, there are over 1200 coal-fired thermal plants. According to statistics about the national power industry of China, in 2006, the total power generated reached 2834.4 terawatt per hour (TW h) and the total installed capacity reached 622 gigawatt (GW) (Yang, Guo, & Wang, 2010). As one of the strongest nations in electric power generation, due to various limitations and causes, China produces its electric power mainly from coal (Williams, 2001). In Turkey as well, 80% of the total electricity is generated from thermal power plants (Oktay, 2009). For the purpose of reducing major and extraordinarily large accidents in TPPs and ensuring the security of electric power production, an increasing number of thermal power enterprises in China pay more attention to the security assessment issue. Security assessment of TPPs mainly concerns three aspects: Production Equipment Systems (PES), Working Circumstance Systems (WCS), and Production Management Systems. The latter is also referred to as the Management System (MS) in current research. By the analysis and evaluation of these three subsystems, the TPPs establish the necessary corrective, remedial, and preventive measure, and finally realize the aim of controlling the accidents in advance. As one of modern management ladders, safety assessment is a powerful tool for automatically diagnosing safety issues. However, numerous evaluations for production safety are irregular, unscientific, and capricious, as well as lacking powerful knowledge support. Accordingly, there is a sizable margin of error. Along with the increasing perfection of security assessment rules and the development of information technologies, new techniques are being applied to almost all aspects of power systems to improve efficiency (Zhao, Wang, Nielsen, Li, & Hao, 2010). It is of both major significance and profound social consequences for TPPs to make their security assessment process progress toward the quantification, scientization, and automatization. MS security represents an important part of the security issue in the production of TPPs. Numerous facts show that a large part of safety accidents in TPPs occurred due to the managerial inadequateness and not for the equipment malfunctions. From the perspective of management systems Security Assessment of TPPs (SATPP), this paper investigates the whole range of security assessment in TPP production, and applies the case-based reasoning (CBR) technique to the evaluation process of SATPP. It presents a case-based decision support method named Improved Gray CBR(IGCBR) for SATPP and a framework of intelligent decision support system for SATPP (IDSS-MSSATPP). The purpose of this study is to investigate the potential of historical knowledge based on cases to complement the deficiency of experts’ personal experience and of knowledge for TPP safety evaluation. It specifically investigates a framework of intelligent decision support system for TPP security assessment and a novel case retrieval method named IGCBR combining logistic regression and Gray System theory for knowledge acquisition from a case base. The framework includes the knowledge support process in TPP safety evaluation, evaluation indexes, and the functional structure of an intelligent decision support system for SATPP. After experimenting with the system, results suggest that the case-based knowledge system is able to provide powerful decision support for the team members during the SATPP. Also, results show that the proposed retrieval method yields high accuracy and synergetic effects for knowledge acquisition in case-based SATPP. Subsequent comparative experiments further verify its predominance. In the next section we introduce the study background including the SATPP evaluation process and the motivations of the study. The third section reviews common approaches used for security assessment in previous literature, as well as the technical features and the applications of case-based reasoning, especially the applications of CBR in the area of evaluation. In the fourth section, we develop a framework of case-based IDSS-MSSATPP: a case-based technical assessment process, evaluation indexes, and the functional design of IDSS-MSSATPP. The fifth section presents our research methodologies, including case knowledge representation, a novel retrieval algorithm based on Gray System theory, a weight determination method from the perspective of statistics, the experimental design, the data set, and our implemented experimental tools. In the sixth section, the key results of our research are presented. In the seventh section we present discussions and add our interpretation to the current work. The eighth section sets forth the conclusion and the implications. Finally, in the last section, the limitations are discussed and future work is suggested.

نتیجه گیری انگلیسی

In this research we developed a framework of intelligent knowledge-based system for the decision support of SATPP and integrated the case-based knowledge acquisition approach into it. Our proposed method integrates gray system theory and logistic regression into CBR methodologies to provide intelligent decision support for SATPP. By a series of experiments, the conclusion is that CBR methodologies are suitable and applicable to the security assessment process of thermal power plants. With high retrieval accuracy and comprehensive performance, the CBR system integrating Gray System Theory and statistics can provide powerful decision making support for the decision makers during the evaluation process of security assessment of thermal power plants. With the help of IDSS-MSSATPP based on CBR, the evaluation cycles of experts will be reduced with an improved efficiency. IGCBR provides a novel and effective way for the security assessment of thermal power plants. This paper also presents a new perspective on the use of prototypes through case aggregation which is one of the popular trends of CBR systems in recent years (Nilsson & Sollenborn, 2004). In case-based evaluation, the characteristic information is able to be extracted to form safety assessment cases from original security safety assessment reports. Also, previous cases can be collected and organized into a knowledge base (i.e. case base). By learning from existing evaluation cases and reusing the experiential knowledge, the quality of decision making for SATPP will be hopefully improved to a great extent. In fact, on the basis of years of experience, it is also widely acknowledged that historical safety assessment cases, especially those that are classical and testified effectively in practice, can play an important role during MSSATPP decision making process. For real security evaluation requirements, it is urgent now to build an expert knowledge-based system for the thermal power enterprises. In our current research, we aim at proposing a comprehensive evaluation and decision support method for SATPP based on CBR and to present an intelligent decision support system for SATPP based on historical expert knowledge. Our research is meaningful both in theory and in practice. First, IDSS-MSSATPP is helpful for the TPP to conduct the self evaluations. In IDSS-MSSATPP, the knowledge acquisition method based on CBR and gray system theory is integrated and it is easier for TPP to obtain expert knowledge and historical information support. This can remedy the weakness of the shortage of evaluation talents of the TPP and makes the self evaluations within the TPP possible. Every thermal power plant can organize technical personnel and managerial personnel to score according to the evaluation index and then acquire the most similar historical case knowledge support from IDSS-MSSATPP. In terms of electric power corporations, IDSS-MSSATPP is a powerful support tool during the expert panel discussions. In the period of conducting the decision making process, the experts’ work can be guided by the most similar historical cases which are important for reference and even may finally affect the conclusion of their evaluation work. Finally, our case-based evaluation approach is favorable for finishing the evaluation work with less manpower, material, and financial resources but stronger quality. Meanwhile, knowledge reuse can be realized during the process of case utilization.

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