Research And Integration Of HAZOP Automation Methods For Petrochemical Processes

With the development of petrochemical process in scaling up, integration and automation,and the continuously increasing requirements for safe development,chemical process safety has been a hot research area.As one of the best approaches for process safety analysis,hazard and operability(HAZOP) analysis can thoroughly and systematically identify the potential hazards that exist in a chemical process.Therefore, it has been the best practice in the PHA of chemical process industry (CPI).Traditionally,HAZOP is a "brainstorming" activity that is done by an expert team consisting of 6～8 people coming from different areas such as process design,process instrumentation,maintenance and safety management.Due to its time-consuming and effort-consuming nature,the consistency and thoroughness of the analysis results are hardly guaranteed.To address the above issue,there has been an extensive motivation for automating HAZOP since the beginning of late 1980s. Among these efforts,signed directed graph(SDG) model based expert systems for HAZOP analysis are the most successful.Due to their shortcomings in knowledge representation that has hardly been recognized,however,they have not been widely deployed or accepted in the CPI.In this thesis,a new modeling methodology,the relative deduce algorithm and an integrated system framework are presented,consisting a complete resolvent of the automatic HAZOP study problem.A prototype system implementing the above framework is developed,and the correctness and completeness of the approach are checked.The research results of this study are listed below:1) Aiming at the drawback existing in the qualitative models mentioned above,a new qualitative model named as "Layered Directed Graph(LDG)" is presented in this paper.It uses digraph to express the professional knowledge.Based on the standard digraph,a new dimension named as "layer" is introduced to the model,which extends the model's capability of knowledge expression.The LDG model's structure,essential elements are presented in this paper,while the model construction methods are discussed in detail.A mechanisim named as "conditional cause-effect" is presented to express the complicated causality existing in chemical process.A strategy of building LDG model library is also presented.The knowledge within the model library is inheritable and reusable,which makes the construction of new model more easy and effective.2) Based on the LDG model methodology,a LDG model reasoning machine is developed,which can utilize the LDG models,perform cross-model casual reasoning and generate whole HAZOP report automatically.The LDG reasoning algorithms are detailed in the paper, including the introductions of the algorithm candidates,the comparison among algorithms,the modification of the original algorithms,the algorithm of cross-model reasoning using multi-model and the algorithm of sorting reasoning results.The reasoning machine is modularized, consisting of one core reasoning algorithm module and 4 appendix algorithm modules,which are all discussed in the paper.The framework of the reasoning machine can cope with various reasoning demands,such as the complicated conditional reasoning,the interaction with abnormal chemicals,the utilization of quantitative information about the process, the influences of control loops and safety equipments with in the process and so on.The reasoning machine's performance is tested,and the results show that the reasoning machine is practicable in most scenario.The advantages of LDG model methodology is proved by comparison of the reasoning results deduced by LDG model,SDG model and human experts.3) To improve the data preparation's efficiency,this paper presented a framework of integrating LDG model system with external CAD/CAM systems.The framework has a modularized structure,consist of 5 modules.The different CAD/CAM systems are packaged in a uniformed interface,so that LDG model system can access the data without considering the original data form.A CAD system--Intergraph SmartPlant P&ID is integrated with LDG model system in ths paper,as the implementation of the framework.Each modules of the framework are detailed and the relative data manipulating algorithms,such as data getting,data sorting,data fitting,are also discussed.The performance of data processing is tested.The whole workflow of performing automatic HAZOP analysis,from Piping and Instrument Diagram(P&ID) to HAZOP report,performed by the integrated LDG expert system is presented at the end of paper.