Petri Net Modeling Multi-channel Pressure Test System And Its Performance Analysis

In our country, although the aviation development obtained the very big development, aircraft development is still very weak in large. In the research and development of aerospace power, we need for a large number of experiments, and testing is measured in many parameters, which pressure is one of. In the pressure of engine test system, the pressure points need to be measured. And the test system is more complex, so the system of performance evaluation is more important. In response, this paper use Petri net theory, establishing generalized stochastic Petri net (GSPN) model for the multi-channel pressure test system, and testing the performance of the system for both qualitative and quantitative research, providing a theoretical basis and structure optimization for more complex test system performance evaluation. The main contents of the study include:1.This paper introduces in detail the situation of multi-channel pressure testing system at the engine at steady state and the transition state. In order to make the model simpler, the pressure test system based on the test develop the task into gas, pressure acquisition, and communication,which are the three sub blocks and it respectively established the GSPN model of the three sub blocks.2.According to the multi channel pressure testing system characteristics, in the steady state, firstly we build a module of GSPN model, and then build a chassis GSPN model, finally establish the512channel pressure test system for GSPN model. In the transition state, finally establish a data acquisition card GSPN model, and then build the whole system4acquisition card GSPN model. The method avoids the problem of state space explosion because of the complex testing system.3. Based on the GSPN model, we analysis the pressure test system performances, such as qualitative analysis (the accessibility, reversible, bounded ness, activity) and the quantitative analysis. According to the accessibility graph and Marco chain’s deducing which is the test system analyzing mathematical formulas of the GSPN model, whose performance include utilization rate each part of the system, the utilization rate of unit time excitation number, system time delay, the mutual influence between each part of the system, and gives the experimental verification. Through the analysis of the performance, we could optimize the test system.4. Using of the Visual C++and Matlab development tools, design the simulation interface.