Modeling and Simulation of Signal Acquisition System Based on Inhibitor Arcs Hierarchical Coloured Petri Nets: Taking Dust Signal Acquisition System as an Example

The development of existing signal acquisition systems has long-term and high-cost problems. To deal with such situation, this paper takes the dust signal acquisition system as an example, and proposes a modeling method combining Information Flow Hierarchical Dynamic (IFHD) with Inhibitor arcs Hierarchical Coloured Petri Nets (IHCPN). The method first establishes a Unified Modeling Language (UML) model based on the functional block diagram of the system. To simplify the reference model, improved the transformation rules between the UML model and Petri Nets (PN) model. To ensure the validity, safety, and rationality of the reference model, the dynamic analysis of the constructed PN model is carried out by using the analysis method of the reachable marking graph. The simulation results of CPN Tools show that the model satisfies boundedness, reachability, liveness, and fairness, conforms to the performance indicators of system operation. Compared with the modeling method of Hierarchical Coloured Petri Nets (HCPN), IHCPN can greatly reduce the number of model nodes and connecting arcs, reduce the complexity of the system model, and provide a reliable reference model while effectively save system development time and cost.

[1]  Ricardo J. Rodríguez,et al.  Profiling the publish/subscribe paradigm for automated analysis using colored Petri nets , 2019, Software & Systems Modeling.

[2]  Syahriah Bachok,et al.  An introduction to petri-net , 2011 .

[3]  Mohamed Ariff Ameedeen,et al.  Model interoperability via Model Driven Development , 2011, J. Comput. Syst. Sci..

[4]  K. Jensen,et al.  Colored Petri nets , 2015, Commun. ACM.

[5]  Jiming Li,et al.  A Novel Intuitionistic Fuzzy Inhibitor Arc Petri Net With Error Back Propagation Algorithm and Application in Fault Diagnosis , 2019, IEEE Access.

[6]  João Pascoal Faria,et al.  A toolset for conformance testing against UML sequence diagrams based on event-driven colored Petri nets , 2014, International Journal on Software Tools for Technology Transfer.

[7]  Xiaolin Zhu,et al.  Sensor Fault Diagnosis Based on Fuzzy Neural Petri Net , 2018, Complex..

[8]  Manuel Silva,et al.  Half a century after Carl Adam Petri's Ph.D. thesis: A perspective on the field , 2013, Annu. Rev. Control..

[9]  Li,et al.  Investigation of Induced Charge Mechanism on a Rod Electrode , 2019, Electronics.

[10]  Essam Shehab,et al.  A design to cost system for innovative product development , 2002 .

[11]  Rolf K. Eckhoff,et al.  Dust explosion causation, prevention and mitigation: An overview , 2010 .

[12]  Angelo Perkusich,et al.  Formal modeling of biomedical signal acquisition systems: source of evidence for certification , 2017, Software & Systems Modeling.

[13]  Zhiliang Wang,et al.  A Smart Home Context-aware Model Based on UML and Colored Petri Net , 2016 .

[14]  Kurt Jensen Coloured Petri Nets , 1992, EATCS Monographs in Theoretical Computer Science.

[15]  Manuel Silva Suárez,et al.  Petri nets and Automatic Control: A historical perspective , 2018, Annu. Rev. Control..