Knowledge representation and decoupling analysis on failure mechanisms of remotely controlled intelligent machinery
Remotely controlled intelligent machinery has complications, including loose management of failure information, low information availability, and coupling influence among systems, which can be effectively solved by analyzing the system state and information characteristics of the equipment. Taking i...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-03-01
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| Series: | Information Processing in Agriculture |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214317320302286 |
| _version_ | 1797724691004129280 |
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| author | Liming Gou Jian Zhang Naiwen Li |
| author_facet | Liming Gou Jian Zhang Naiwen Li |
| author_sort | Liming Gou |
| collection | DOAJ |
| description | Remotely controlled intelligent machinery has complications, including loose management of failure information, low information availability, and coupling influence among systems, which can be effectively solved by analyzing the system state and information characteristics of the equipment. Taking intelligent agricultural machinery as the object, this study applies the knowledge representation method to explore equipment failure states' informational features and construct a knowledge framework model of system failure representation relations and a complex network conceptual model to visualize the failure information more intuitively and facilitate systematic management and utilization. The feedback-based decoupling analysis method uncouples the coupling between subsystems, identifying the critical state of decoupling well. It attempts to apply the knowledge representation and decoupling analysis to remotely controlled intelligent agricultural machinery equipment. Through the example, the result further illustrates the feasibility of knowledge representation and decoupling for remotely controlled intelligent agricultural machinery systems and provides essential support for better failure analysis. |
| first_indexed | 2024-03-12T10:20:46Z |
| format | Article |
| id | doaj.art-6f7050b7edd8475ba0fe79704f0a178b |
| institution | Directory Open Access Journal |
| issn | 2214-3173 |
| language | English |
| last_indexed | 2024-03-12T10:20:46Z |
| publishDate | 2022-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Information Processing in Agriculture |
| spelling | doaj.art-6f7050b7edd8475ba0fe79704f0a178b2023-09-02T10:08:16ZengElsevierInformation Processing in Agriculture2214-31732022-03-01918089Knowledge representation and decoupling analysis on failure mechanisms of remotely controlled intelligent machineryLiming Gou0Jian Zhang1Naiwen Li2School of Business Administration, Liaoning Technical University, Huludao 125105, ChinaSchool of Economics and Management, Beijing Information Science and Technology University, Beijing 100192, China; Laboratory of Big Data Decision making for Green Development, Beijing 100192, China; Corresponding author at: School of Economics and Management, Beijing Information Science and Technology University, Beijing 100192, China.School of Business Administration, Liaoning Technical University, Huludao 125105, ChinaRemotely controlled intelligent machinery has complications, including loose management of failure information, low information availability, and coupling influence among systems, which can be effectively solved by analyzing the system state and information characteristics of the equipment. Taking intelligent agricultural machinery as the object, this study applies the knowledge representation method to explore equipment failure states' informational features and construct a knowledge framework model of system failure representation relations and a complex network conceptual model to visualize the failure information more intuitively and facilitate systematic management and utilization. The feedback-based decoupling analysis method uncouples the coupling between subsystems, identifying the critical state of decoupling well. It attempts to apply the knowledge representation and decoupling analysis to remotely controlled intelligent agricultural machinery equipment. Through the example, the result further illustrates the feasibility of knowledge representation and decoupling for remotely controlled intelligent agricultural machinery systems and provides essential support for better failure analysis.http://www.sciencedirect.com/science/article/pii/S2214317320302286Remotely controlledFailure mechanismsKnowledge representationDecoupling analysis |
| spellingShingle | Liming Gou Jian Zhang Naiwen Li Knowledge representation and decoupling analysis on failure mechanisms of remotely controlled intelligent machinery Information Processing in Agriculture Remotely controlled Failure mechanisms Knowledge representation Decoupling analysis |
| title | Knowledge representation and decoupling analysis on failure mechanisms of remotely controlled intelligent machinery |
| title_full | Knowledge representation and decoupling analysis on failure mechanisms of remotely controlled intelligent machinery |
| title_fullStr | Knowledge representation and decoupling analysis on failure mechanisms of remotely controlled intelligent machinery |
| title_full_unstemmed | Knowledge representation and decoupling analysis on failure mechanisms of remotely controlled intelligent machinery |
| title_short | Knowledge representation and decoupling analysis on failure mechanisms of remotely controlled intelligent machinery |
| title_sort | knowledge representation and decoupling analysis on failure mechanisms of remotely controlled intelligent machinery |
| topic | Remotely controlled Failure mechanisms Knowledge representation Decoupling analysis |
| url | http://www.sciencedirect.com/science/article/pii/S2214317320302286 |
| work_keys_str_mv | AT liminggou knowledgerepresentationanddecouplinganalysisonfailuremechanismsofremotelycontrolledintelligentmachinery AT jianzhang knowledgerepresentationanddecouplinganalysisonfailuremechanismsofremotelycontrolledintelligentmachinery AT naiwenli knowledgerepresentationanddecouplinganalysisonfailuremechanismsofremotelycontrolledintelligentmachinery |