The Experts below are selected from a list of 276 Experts worldwide ranked by ideXlab platform
Shin-ichi Sakai - One of the best experts on this subject based on the ideXlab platform.
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PCB decomposition and formation in thermal treatment Plant Equipment.
Chemosphere, 2006Co-Authors: Yukari Ishikawa, Yukio Noma, Takashi Yamamoto, Yoshihito Mori, Shin-ichi SakaiAbstract:In this study we investigated both the decomposition and unintentional formation of polychlorinated biphenyl congeners during combustion experiments of refuse-derived fuel (RDF) and automobile shredder residue (ASR) at several stages in thermal treatment Plant Equipment composed of a primary combustion chamber, a secondary combustion chamber, and other Equipments for flue gas treatment. In both experiments, the unintentional formation of PCB occurred in the primary combustion chamber at the same time as the decomposition of PCB in input samples. By combusting RDF, non-ortho-PCB predominantly formed, whereas ortho-PCB and symmetric chlorinated biphenyls (e.g., #52/69, #87/108, and #151) tended to be decomposed. ASR formed the higher chlorinated biphenyls more than RDF. These by-products from ASR had no structural relation with ortho-chlorine. Lower chlorinated biphenyls appeared as predominant homologues at the final exit site, while all congeners from lower to higher chlorinated PCB were unintentionally formed as by-products in the primary combustion chamber. This result showed that the flue gas treatment Equipments effectively removed higher chlorinated PCB. Input marker congeners of RDF were #11, #39, and #68, while those for ASR were #11, #101, #110/120, and #118. Otherwise, combustion marker congeners of RDF were #13/12, #35, #77, and #126, while those for ASR were #170, #194, #206, and #209. While the concentration of PCB increased significantly in the primary combustion chamber, the value of toxicity equivalency quantity for dioxin-like PCB decreased in the secondary combustion chamber and the flue gas treatment Equipments.
Kun Yang - One of the best experts on this subject based on the ideXlab platform.
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State Evaluation for Power Plant Equipment Based on Deviation of Operating Parameters
Advanced Materials Research, 2011Co-Authors: Si Yuan Zhao, Kun Liang Chen, Kun YangAbstract:In view of which the state of Equipment cannot be obtained accurately in real-time, a new method of state evaluation is proposed in this paper. Through Fault Tree Analysis (FTA) and Failure Mode Effects and Criticality Analysis (FMECA), the impact of parameters on Equipment state is researched and the deviation is defined to quantify the variation of the state of Equipment. The evaluating model based on deviation is established and illustrated with an example. The studied case is about the state evaluation for rotor blade and the application proves the method to be effective in the state evaluation for power Plant Equipment.
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Study on Maintenance Method Intelligent Decision Support System Used for Power Plant Equipment
2009 Asia-Pacific Power and Energy Engineering Conference, 2009Co-Authors: Xiao-feng Dong, Kun YangAbstract:With the development of industry, maintenance has become an important factor that influences survival and development of a corporation. It is an effective way for a power Plant to achieve management modernization and enhance market competition by making condition based maintenance. There are numerous pieces of Equipment in a power Plant, but the maintenance requirement is different for respective Equipment, so selecting appropriate maintenance method is the first step of making condition based maintenance in a power Plant. In the course of maintenance method selection, there are a lot of qualitative and quantitative analyses to do, so technical support from computer decision support system is necessary. According to the characteristic of condition based maintenance in a power Plant, a maintenance method intelligent decision support system used for power Plant Equipment is designed in this paper where the system's goal, function and architecture are particularly introduced.
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Study on multi-agent based maintenance decision support system used for power Plant Equipment
2008 IEEE International Conference on Industrial Engineering and Engineering Management, 2008Co-Authors: Yu-jiong Gu, Xiao-feng Dong, Jian Jun Wu, Kun YangAbstract:With the developing of industry, maintenance has become an important factor that influences survival and development of the business. There are numerous pieces of Equipment in a power Plant, but the maintenance requirement is different for respective Equipment, so making condition based maintenance in a power Plant is a systemic and integrative activity in maintenance management. As an interdisciplinary activity, a special maintenance decision support system is necessary to aid operating and maintenance personnel use that knowledge right and well. As a hotspot of Distributed Artificial Intelligence research, agent technology is one of the strongest tools for constituting large-scale distributed and open computer-based systems. This paper briefly introduces decision support system and agent technology, and presents an architecture of multiagent based maintenance decision support system used for power Plant Equipment, and describes its architecture, function and decision making process in detail.
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FSKD (3) - Fuzzy Comprehensive Evaluation Method Based on Analytic Hierarchy Process for Falt Risk Analysis of Power Plant Equipment
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery, 2008Co-Authors: Kun Liang Chen, Kun YangAbstract:Aiming at the difficulty in evaluating the falt risk of the power Plant Equipment with quantitative method, fuzzy comprehensive evaluation method based on analytic hierarchy process (AHP) is proposed with the help of the theory of fuzzy mathematics. With this method the mathematical model is constructed, and the weight coefficient of each factor is suggested as well as the calculation process. The fuzziness and hierarchy within the model are both considered in this method, what is more, the subjective factors are quantified with the grade of membership and the quantitative risk value. So makes the evaluation more objective. The calculating result of applying the proposed method to the example demonstrates that the method is so valid and feasible that it is capable of evaluating the risk degree objectively and in further supplying some reasoning for condition decision.
Hiroaki Date - One of the best experts on this subject based on the ideXlab platform.
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as built modeling of piping system from terrestrial laser scanned point clouds using normal based region growing
Journal of Computational Design and Engineering, 2014Co-Authors: Kazuaki Kawashima, Satoshi Kanai, Hiroaki DateAbstract:Abstract Recently, renovations of Plant Equipment have been more frequent because of the shortened lifespans of the products, and as-built models from large-scale laser-scamied data is expected to streamline rebuilding processes. However, the laser-scanned data of an existing Plant has an enormous amount ofpoints, captures inmcate objects, and includes a high noise level, so the manual reconstmction of a 3D model is very time-consuming and costly. Among Plant Equipment, piping systems account for the greatest proportion. Therefore, the purpose of this research was to propose an algorithm which could automatically recognize a piping system from the terrestrial laser- scanned data Plant Equipment. The straight pomon pipes, connecting parts, and connection relationship ofthe piping system can be recognized in this algorithm. Normal-based region growing and cylinder surface fitting can extract all possible locations ofpipes, including straight pipes, elbows, and junctions. Tracing the axes of a piping system enables the recognition of the positions of these elements and their connection relationship. Using only point clouds, the recognition algorithm can be performed in a fUlly automatic way. The algorithm was applied to large-scale scamied data of an oil rig and a chemical Plant. Recognition rates of about 86%, 88%, and 71% were achieved straight pipes, elbows, andjunctions, respectively.
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as built modeling of piping system from terrestrial laser scanned point clouds using normal based region growing
한국CAD CAM학회 국제학술발표 논문집, 2013Co-Authors: Kazuaki Kawashima, Satoshi Kanai, Hiroaki DateAbstract:Recently, renovations of Plant Equipment have been more frequent because of the shorten lifetimes of the products, and as-built models from large-scale laser scanned data is expected to streamline their rebuilding processes. However, the laser scanned data of the existing Plant has enormous number of points, captures intricate objects and includes high level of noises, so that the manual reconstruction of a 3D model is very time-consuming and costs a lot. Among Plant Equipment, piping systems especially account for the greatest proportion of Plant Equipment. Therefore, the purpose of this research was to propose an algorithm which can automatically recognize a piping system from terrestrial laser scanned data of the Plant Equipment. The straight portion of pipes, connecting parts and connection relationship of the piping system can be recognized in this algorithm. Normal-based region-growing and cylinder surface fitting can extract all candidates of points of pipes including straight pipes, elbows and junctions. Tracing axes of piping system allows to recognize the positions of these elements and their connection relationship. Using only point clouds, the recognition algorithm can be performed in a fully automatic way. The algorithm was applied to large-scale scanned data of an oil rig. The results of the recognition rate of straight pipes, elbows, junctions were achieved at 93%, 92% and 91% respectively
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Automatic Recognition of a Piping System from Laser Scanned Points by Eigenvalue Analysis
Key Engineering Materials, 2012Co-Authors: Kazuaki Kawashima, Satoshi Kanai, Hiroaki DateAbstract:In recent years, changes in Plant Equipment have been becoming more frequent because of the short lifetime of the products, and constructing 3D shape models of existing Plants (as-built models) from large-scale laser scanned data is expected to make their rebuilding processes more efficient. However, the laser scanned data of the existing Plant has massive points, captures tangled objects and includes a large amount of noises, so that the manual reconstruction of a 3D model is very time-consuming and costs a lot. Piping systems especially, account for the greatest proportion of Plant Equipment. Therefore, the purpose of this research was to propose an algorithm which can automatically recognize a piping system from terrestrial laser scan data of the Plant Equipment. Point clouds of a piping system can be extracted based eigenvalue analysis and using region-growing from the laser scanned points. Eigenvalue analysis of the point clouds then allows for recognition of straight portion of pipes. Connecting parts can be recognized from connection relationship between pipes and neighboring points.
Kazuaki Kawashima - One of the best experts on this subject based on the ideXlab platform.
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as built modeling of piping system from terrestrial laser scanned point clouds using normal based region growing
Journal of Computational Design and Engineering, 2014Co-Authors: Kazuaki Kawashima, Satoshi Kanai, Hiroaki DateAbstract:Abstract Recently, renovations of Plant Equipment have been more frequent because of the shortened lifespans of the products, and as-built models from large-scale laser-scamied data is expected to streamline rebuilding processes. However, the laser-scanned data of an existing Plant has an enormous amount ofpoints, captures inmcate objects, and includes a high noise level, so the manual reconstmction of a 3D model is very time-consuming and costly. Among Plant Equipment, piping systems account for the greatest proportion. Therefore, the purpose of this research was to propose an algorithm which could automatically recognize a piping system from the terrestrial laser- scanned data Plant Equipment. The straight pomon pipes, connecting parts, and connection relationship ofthe piping system can be recognized in this algorithm. Normal-based region growing and cylinder surface fitting can extract all possible locations ofpipes, including straight pipes, elbows, and junctions. Tracing the axes of a piping system enables the recognition of the positions of these elements and their connection relationship. Using only point clouds, the recognition algorithm can be performed in a fUlly automatic way. The algorithm was applied to large-scale scamied data of an oil rig and a chemical Plant. Recognition rates of about 86%, 88%, and 71% were achieved straight pipes, elbows, andjunctions, respectively.
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as built modeling of piping system from terrestrial laser scanned point clouds using normal based region growing
한국CAD CAM학회 국제학술발표 논문집, 2013Co-Authors: Kazuaki Kawashima, Satoshi Kanai, Hiroaki DateAbstract:Recently, renovations of Plant Equipment have been more frequent because of the shorten lifetimes of the products, and as-built models from large-scale laser scanned data is expected to streamline their rebuilding processes. However, the laser scanned data of the existing Plant has enormous number of points, captures intricate objects and includes high level of noises, so that the manual reconstruction of a 3D model is very time-consuming and costs a lot. Among Plant Equipment, piping systems especially account for the greatest proportion of Plant Equipment. Therefore, the purpose of this research was to propose an algorithm which can automatically recognize a piping system from terrestrial laser scanned data of the Plant Equipment. The straight portion of pipes, connecting parts and connection relationship of the piping system can be recognized in this algorithm. Normal-based region-growing and cylinder surface fitting can extract all candidates of points of pipes including straight pipes, elbows and junctions. Tracing axes of piping system allows to recognize the positions of these elements and their connection relationship. Using only point clouds, the recognition algorithm can be performed in a fully automatic way. The algorithm was applied to large-scale scanned data of an oil rig. The results of the recognition rate of straight pipes, elbows, junctions were achieved at 93%, 92% and 91% respectively
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Automatic Recognition of a Piping System from Laser Scanned Points by Eigenvalue Analysis
Key Engineering Materials, 2012Co-Authors: Kazuaki Kawashima, Satoshi Kanai, Hiroaki DateAbstract:In recent years, changes in Plant Equipment have been becoming more frequent because of the short lifetime of the products, and constructing 3D shape models of existing Plants (as-built models) from large-scale laser scanned data is expected to make their rebuilding processes more efficient. However, the laser scanned data of the existing Plant has massive points, captures tangled objects and includes a large amount of noises, so that the manual reconstruction of a 3D model is very time-consuming and costs a lot. Piping systems especially, account for the greatest proportion of Plant Equipment. Therefore, the purpose of this research was to propose an algorithm which can automatically recognize a piping system from terrestrial laser scan data of the Plant Equipment. Point clouds of a piping system can be extracted based eigenvalue analysis and using region-growing from the laser scanned points. Eigenvalue analysis of the point clouds then allows for recognition of straight portion of pipes. Connecting parts can be recognized from connection relationship between pipes and neighboring points.
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automatic recognition of a piping system from large scale terrestrial laser scan data
2011Co-Authors: Kazuaki Kawashima, Satoshi KanaiAbstract:Recently, changes in Plant Equipment have been becoming more frequent because of the short lifetime of the products, and constructing 3D shape models of existing Plants (as-built models) from large-scale laser scanned data is expected to make their rebuilding processes more efficient. However, the laser scanned data of the existing Plant has massive points, captures tangled objects and includes a large amount of noises, so that the manual reconstruction of a 3D model is very time-consuming and costs a lot. Piping systems especially, account for the greatest proportion of Plant Equipment. Therefore, the purpose of this research was to propose an algorithm which can automatically recognize a piping system from terrestrial laser scan data of the Plant Equipment. The straight portion of pipes, connecting parts and connection relationship of the piping system can be recognized in this algorithm. Eigenvalue analysis of the point clouds and of the normal vectors allows for the recognition. Using only point clouds, the recognition algorithm can be applied to registered point clouds and can be performed in a fully automatic way. The preliminary results of the recognition for large-scale scanned data from an oil rig Plant have shown the effectiveness of the algorithm.
Yukari Ishikawa - One of the best experts on this subject based on the ideXlab platform.
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PCB decomposition and formation in thermal treatment Plant Equipment.
Chemosphere, 2006Co-Authors: Yukari Ishikawa, Yukio Noma, Takashi Yamamoto, Yoshihito Mori, Shin-ichi SakaiAbstract:In this study we investigated both the decomposition and unintentional formation of polychlorinated biphenyl congeners during combustion experiments of refuse-derived fuel (RDF) and automobile shredder residue (ASR) at several stages in thermal treatment Plant Equipment composed of a primary combustion chamber, a secondary combustion chamber, and other Equipments for flue gas treatment. In both experiments, the unintentional formation of PCB occurred in the primary combustion chamber at the same time as the decomposition of PCB in input samples. By combusting RDF, non-ortho-PCB predominantly formed, whereas ortho-PCB and symmetric chlorinated biphenyls (e.g., #52/69, #87/108, and #151) tended to be decomposed. ASR formed the higher chlorinated biphenyls more than RDF. These by-products from ASR had no structural relation with ortho-chlorine. Lower chlorinated biphenyls appeared as predominant homologues at the final exit site, while all congeners from lower to higher chlorinated PCB were unintentionally formed as by-products in the primary combustion chamber. This result showed that the flue gas treatment Equipments effectively removed higher chlorinated PCB. Input marker congeners of RDF were #11, #39, and #68, while those for ASR were #11, #101, #110/120, and #118. Otherwise, combustion marker congeners of RDF were #13/12, #35, #77, and #126, while those for ASR were #170, #194, #206, and #209. While the concentration of PCB increased significantly in the primary combustion chamber, the value of toxicity equivalency quantity for dioxin-like PCB decreased in the secondary combustion chamber and the flue gas treatment Equipments.