{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T14:55:29Z","timestamp":1781103329038,"version":"3.54.1"},"reference-count":39,"publisher":"IGI Global Scientific Publishing","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,10]]},"abstract":"<jats:p>Due to high temperature, high pressure, high corrosion, and many other factors, the hazardous chemical device is facing more severe security challenges than other industries. Now, the monitoring methods have been very mature, which play a basic monitoring role, not a predictive fault diagnosis. In this article, the hazardous chemical device's status data will be collected from the existing industrial monitoring network, the real-time data will be preprocessed and then stored in a database, and the data will be imported to the real-time data into the ontology cognitive model; the data will be performed by big data processing and automatic reasoning so that real-time status of hazardous chemical device and the warning of security risks predict are easily obtained at any time. The model is proposed to solve the problem of knowledge representation and reasoning of the hazardous chemical device based on ontology. The model is analyzed and implemented in Prot\u00e9g\u00e9 software.<\/jats:p>","DOI":"10.4018\/ijcini.2018100106","type":"journal-article","created":{"date-parts":[[2018,12,21]],"date-time":"2018-12-21T09:25:39Z","timestamp":1545384339000},"page":"101-114","source":"Crossref","is-referenced-by-count":1,"title":["An Ontology-Based Cognitive Model for Faults Diagnosis of Hazardous Chemical Storage Devices"],"prefix":"10.4018","volume":"12","author":[{"given":"Lixiao","family":"Feng","sequence":"first","affiliation":[{"name":"School of Electrical and Information Engineering, Chongqing University of Science and Technology, Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guorong","family":"Chen","sequence":"additional","affiliation":[{"name":"Chongqing University of Science and Technology, Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Peng","sequence":"additional","affiliation":[{"name":"Chongqing University of Science and Technology, Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJCINI.2018100106-0","doi-asserted-by":"publisher","DOI":"10.1109\/INDIN.2014.6945600"},{"key":"IJCINI.2018100106-1","doi-asserted-by":"crossref","unstructured":"Alshura, Zabadi, & Abughazaleh. (2018). Big Data in Marketing Arena. Big Opportunity, Big Challenge, and Research Trends: An Integrated View. Research Gate.","DOI":"10.24818\/mer\/2018.06-06"},{"key":"IJCINI.2018100106-2","doi-asserted-by":"crossref","unstructured":"Bessedik & Taghezout. (2018). Towards a new supporting platform for collaboration in industrial diagnosis within an agent-based WEB DSS. International Journal of Computer Aided Engineering and Technology, 10(4), 457.","DOI":"10.1504\/IJCAET.2018.092865"},{"key":"IJCINI.2018100106-3","unstructured":"Chen G. (2012). Empirical analysis on blast furnace fault diagnosis method based on ontology. Journal of Chongqing University (Natural Science Edition), 5, 35-39."},{"key":"IJCINI.2018100106-4","doi-asserted-by":"crossref","unstructured":"Dargazany, Stegagno, & Mankodiya. (2018). WearableDL: Wearable Internet-of-Things and Deep Learning for Big Data Analytics\u2014Concept, Literature, and Future. Mobile Information Systems, 2018(2), 1-20.","DOI":"10.1155\/2018\/8125126"},{"key":"IJCINI.2018100106-5","doi-asserted-by":"crossref","unstructured":"Dibowski & Holub. (2017). Ontology-based fault propagation in building automation systems. International Journal of Simulation: Systems, Science & Technology, 18(3), 1.1-1.14.","DOI":"10.5013\/IJSSST.a.18.03.01"},{"key":"IJCINI.2018100106-6","doi-asserted-by":"publisher","DOI":"10.1109\/SIMS.2016.22"},{"key":"IJCINI.2018100106-7","unstructured":"Duan & Zhang. (2016). Fault diagnosis method of flight control system based on ontology and FMECA. Journal of Civil Aviation University of China, (4), 21-26."},{"key":"IJCINI.2018100106-8","author":"Feng"},{"key":"IJCINI.2018100106-9","doi-asserted-by":"publisher","DOI":"10.1109\/KCIC.2017.8228590"},{"key":"IJCINI.2018100106-10","doi-asserted-by":"publisher","DOI":"10.4018\/IJCINI.2018070103"},{"key":"IJCINI.2018100106-11","unstructured":"Jun, X. (2011). Concern on the hidden dangers of fire in hazardous chemical warehouse. Fire Technique and Products Information, 4, 53-57."},{"key":"IJCINI.2018100106-12","unstructured":"Li, Hu, & Zhang. (2015). A fault diagnosis method for CNC machine based on the fusion of multi-method. China Sciencepaper, (10), 1213-1219."},{"key":"IJCINI.2018100106-13","doi-asserted-by":"publisher","DOI":"10.1109\/APPEEC.2014.7066069"},{"key":"IJCINI.2018100106-14","doi-asserted-by":"crossref","unstructured":"Long, Tai, & Xu. (2016). Fault Tree Analysis of Pantograph Type Current Collector Based on Ontology Modeling. Key Engineering Materials, 693, 1371-1376.","DOI":"10.4028\/www.scientific.net\/KEM.693.1371"},{"key":"IJCINI.2018100106-15","unstructured":"Mallak, A., Weber, C., & Holland, A. (n.d.). Active Diagnosis Automotive Ontology for Distributed Embedded Systems, Digital Innovation for advanced Manufacturing managing Technological and Entrepreneuarial Challenges. IEEE."},{"key":"IJCINI.2018100106-16","doi-asserted-by":"crossref","unstructured":"Pardo, Espes, & Le-Parc. (2016). A Framework for Anomaly Diagnosis in Smart Homes Based on Ontology. Procedia Computer Science, 83, 545-552.","DOI":"10.1016\/j.procs.2016.04.255"},{"key":"IJCINI.2018100106-17","first-page":"189","article-title":"Song Renwang.","volume":"15","author":"R.Peng","year":"2016","journal-title":"Fault Diagnosis Method for Hydraulic of Concrete Pump Trucks Based on Ontology."},{"key":"IJCINI.2018100106-18","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-014-0806-3"},{"key":"IJCINI.2018100106-19","doi-asserted-by":"publisher","DOI":"10.1109\/ICISC.2017.8068581"},{"key":"IJCINI.2018100106-20","doi-asserted-by":"crossref","unstructured":"Safa & Hill. (2018, November). Necessity of big data analysis in construction management. Strategic Direction.","DOI":"10.1108\/SD-09-2018-0181"},{"key":"IJCINI.2018100106-21","doi-asserted-by":"crossref","unstructured":"Samirmi & Tang. (2015). Fuzzy Ontology Reasoning for Power Transformer Fault Diagnosis. Advances in Electrical and Computer Engineering, 15(4), 107-114.","DOI":"10.4316\/AECE.2015.04015"},{"key":"IJCINI.2018100106-22","doi-asserted-by":"publisher","DOI":"10.4316\/AECE.2015.04015"},{"key":"IJCINI.2018100106-23","unstructured":"Schneider, G. F., Kalantari, Y., & Kontes, G. (2016). An Ontology-Based Tool for Automated Configuration and Deployment of Technical Building Management Services. BauSIM\/Central European Symposium on Building Physics (CESBP), Dresden, Germany."},{"key":"IJCINI.2018100106-24","unstructured":"Wang & Wang. (2015). Deflagration accident risk analysis of Tianjin harbor hazardous materials consolidation and distribution transportation. Journal of Waterway and Harbor, 2, 167-171."},{"key":"IJCINI.2018100106-25","author":"X.Wang","year":"2018","journal-title":"Improved Multi-order Distributed HOSVD with its Incremental Computing for Smart City Services"},{"key":"IJCINI.2018100106-26","doi-asserted-by":"publisher","DOI":"10.4018\/IJCINI.2018010101"},{"key":"IJCINI.2018100106-27","doi-asserted-by":"publisher","DOI":"10.4018\/IJCINI.2017070103"},{"key":"IJCINI.2018100106-28","doi-asserted-by":"publisher","DOI":"10.4018\/IJCINI.2014070103"},{"key":"IJCINI.2018100106-29","author":"L. T.Yang","year":"2018","journal-title":"A Tensor-Based Optimization Model for Secure Sustainable Cyber-Physical-Social Big Data Computations"},{"key":"IJCINI.2018100106-30","unstructured":"Yang, Y., & Lin, J. (2011). Real-time condition monitoring system of transportation equipments for hazardous chemical based on DSP technology.China Measurement & Testing Technology, 1, 60-62."},{"key":"IJCINI.2018100106-31","first-page":"1358","article-title":"Aero-engine gradual changing fault diagnosis based on canonical time warping algorithm.","volume":"9","author":"Z.Yuan","year":"2017","journal-title":"Journal of Electronic Measurement and Instrumentation[C]"},{"key":"IJCINI.2018100106-32","unstructured":"Zhang, Duan, & Zhou. (2010). Development of Real-time Condition Monitoring System of Transportation Equipment for Hazardous Chemical. Computer and Communications, 7, 106-108."},{"key":"IJCINI.2018100106-33","unstructured":"Zhang, G., & Dai, Y. (2015). Design and Implementation of Hazardous Chemical Monitoring and Management System Based on Bluetooth Locating Technology.Development & Innovation of Machinery & Electrical Products, 1, 35-37."},{"key":"IJCINI.2018100106-34","unstructured":"Xu & Zhang. (2013). Semantic SOA framework orient to aviation rep. Computer Engineering and Applications, (2), 34-38."},{"key":"IJCINI.2018100106-35","doi-asserted-by":"crossref","unstructured":"Zhao, Ke, & Hu. (2015). Research on Fault Diagnosis Knowledge Representation Method of Hydraulic System Based on Ontology-Production Rule. The Chinese Society of Mechanical Engineers, 36(2), 175-181.","DOI":"10.3901\/JME.2015.14.175"},{"key":"IJCINI.2018100106-36","unstructured":"Zhao, Ke, Hu, & Zhao. (2015). Research on Fault Diagnosis Knowledge Representation Method of Hydraulic System Based on Ontology-Production Rule. Journal of the Chinese Society of Mechanical Engineers, Transactions of the Chinese Institute of Engineers - Series C, 36(2), 175-181."},{"key":"IJCINI.2018100106-37","doi-asserted-by":"crossref","unstructured":"Zhou, Dejie, & Zhang. (2014). A research on intelligent fault diagnosis of wind turbines based on ontology and FMECA. Advanced Engineering Informatics, 29(1).","DOI":"10.1016\/j.aei.2014.10.001"},{"key":"IJCINI.2018100106-38","doi-asserted-by":"crossref","unstructured":"Zhou, J., H\u00e4nninen, K., Lundqvist, K., & Provenzano, L. (2017). An ontological approach to identify the causes of hazards for safety-critical systems. 2017 2nd International Conference on System Reliability and Safety (ICSRS), 405-413.","DOI":"10.1109\/ICSRS.2017.8272856"}],"container-title":["International Journal of Cognitive Informatics and Natural Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/www.igi-global.com\/viewtitle.aspx?TitleId=220413","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,5]],"date-time":"2022-05-05T15:58:50Z","timestamp":1651766330000},"score":1,"resource":{"primary":{"URL":"https:\/\/2.zoppoz.workers.dev:443\/http\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/IJCINI.2018100106"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2018,10]]},"references-count":39,"journal-issue":{"issue":"4"},"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.4018\/ijcini.2018100106","relation":{},"ISSN":["1557-3958","1557-3966"],"issn-type":[{"value":"1557-3958","type":"print"},{"value":"1557-3966","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,10]]}}}