Bingzhen Chen

Application of steady-state detection method based on wavelet transform

A wavelet-based method is proposed for steady-state detection in continuous processes. In this method, process trends are extracted from the measured raw data via wavelet-based multi-scale processing. The process status is then measured using an index with value ranging from 0 to 1 according to the wavelet transform modulus of the extracted process signal. Finally, a steady state is identified if the computed index is small (close to zero). The determination of a characteristic scale for performing steady-state detection was also studied. Compared with the existing approaches for steady-state detection, this method has better precision for detecting changes in process due to the good localization property of wavelet transform, and is more suitable for on-line applications. In this paper, the method is described in detail, and has then been applied to the crude oil unit of a refinery, and to the recausticizing plant of a chemical pulp mill.

Learning HAZOP expert system by case-based reasoning and ontology

Abstract To improve the learning capability of HAZOP expert systems, a new learning HAZOP expert system called PetroHAZOP has been developed based on the integration of case-based reasoning (CBR) and ontology that can help automate “non-routine” HAZOP analysis. PetroHAZOP consists of four modules including case base module, CBR engine module, knowledge maintenance module and user graphical interface module. Within the case base, HAZOP analysis knowledge is represented as cases which are organized with a hierarchical structure. Similarity-based case retrieval algorithm is also depicted to find the closest-matching cases. In order to enhance the case retrieval, a new set of ontologies for CBR-based HAZOP analysis is created by integration of existing ontologies reported in literature. Finally the application of PetroHAZOP is demonstrated by two case studies of industrial processes.

Applications of process synthesis: Moving from conventional chemical processes towards biorefinery processes

Abstract Concerns about diminishing petroleum reserves, enhanced worldwide demand for fuels and fluctuations in the global oil market, together with climate change and national security have promoted many initiatives for exploring alternative, non-petroleum based processes. Among these initiatives, biorefinery processes for converting biomass derived carbohydrates into transportation fuels and chemicals are now gaining more and more attention from both academia and industry. Process synthesis, which has played a vital role for the development, design and operation of (petro) chemical processes, can be predicted to play a significant role in the design and commercialization of sustainable and cost-effective biorefinery processes. The main objective of this perspective paper is to elucidate the potential opportunities that biorenewables processing offers to optimal synthesis; challenges and future directions in this field are also concisely discussed. An attempt is made with this perspective to stimulate more and more efforts to optimally synthesize and design biorenewable conversion process to accelerate the commercialization of the biorefinery technology and further reduce the heavily reliance on petroleum-derive fuels.

Analysis of the stability and controllability of chemical processes

Chemical processes constitute strongly nonlinear systems and, for such systems, multiple steady-state solutions typically exist. In addition, the various steady state solutions are likely to differ in terms of stability and phase behaviors, which is an important consideration for practical applications. A chemical process is used in this paper to demonstrate how to analyze process stability and controllability. Finally, the conclusion is drawn that overall system stability and phase behaviors should be considered because the individual unit operations or subsystems differ from the total system in terms of these features. Therefore, the analysis of stability and controllability of process systems is important in terms of the design of inherently safer processes.

Layered digraph model for HAZOP analysis of chemical processes

Process modeling has remained challenging in the area of automating hazard and operability (HAZOP) analysis of complex chemical processes. Even though signed digraph(SDG) model has been proposed and widely applied in various HAZOP expert systems in the past one decade, the limitations of SDG have not been recognized and discussed in literature. The drawbacks of SDG models have caused incompleteness of HAZOP analysis results, which poses a significant limitation on wide acceptance of HAZOP expert systems in industrial practices. In this work, layered digraph (LDG) model extended from SDG is introduced to overcome the drawbacks of SDG models. Knowledge storage and management of LDG models are discussed in detail. Industrial case studies are used to illustrate the effectiveness of this new modeling methodology. Since process variables, process deviations, and interactions of deviations are explicitly decoupled in three dimensions, LDG model has shown to provide a much more flexible and comprehensive mechanism for HAZOP analysis.

A Signed Digraphs Based Method for Detecting Inherently Unsafe Factors of Chemical Process at Conceptual Design Stage

Abstract Digraph-based causal models have been widely used to model the cause and effect behavior of process systems. Signed digraphs (SDG) capture the direction of the effect. It should be mentioned that there are loops in SDG generated from chemical process. From the point of the inherent operability, the worst unsafe factor is the SDG having positive loops that means any disturbance occurring within the loop will propagate through the nodes one by one and are amplified gradually, so the system may lose control, which may lead to an accident. So finding the positive loops in a SDG and treating these unsafe factors in a proper manner can improve the inherent safety of a chemical process. This article proposed a method that can detect the above-mentioned unsafe factors in the process conceptual design stage automatically through the analysis of the SDG generated from the chemical process. A case study is illustrated to show the working of the algorithm, and then a complicated case from industry is studied to depict the effectiveness of the proposed algorithm.

An integrated quantitative index of stable steady state points in chemical process design

Abstract In order to design inherently safer chemical processes, researchers proposed many methods and strategies, many quantitative indices have been developed to describe the potential hazard and dangerous of different reaction routes and reactants. Because in emergency situation the disturbance may be so large that the system can not return back to the steady state points. For considering both situations under small and large disturbances, this paper proposed a quantitative index (QI), in which disturbance range index (RI) and convergence speed index (SI) were integrated, considering both capability of resistance to disturbances and speed to return to steady state point. Based on the integrated index, this paper proposed an approach for designing a more stable chemical process that can maintain stable within larger region to resist the disturbance and has shorter time to approach to the original stable steady state operation point when disturbance is encountered. The approach is applied to methyl methacrylate polymerization process and a multi-objective optimization problem considering both economic and stability factors were conducted and a Pareto set is obtained.