Real-time semi-physical simulation system and data acquisition method thereof

Abstract

The invention relates to the technical field of simulation, in particular to a real-time semi-physical simulation system and a data acquisition method thereof. The invention adopts the technical scheme that the simulation system also comprises a DAQ device which acquires data of a hardware real object and is connected with the hardware real object; and after acquiring the data of the hardware real object, the DAQ device transmits the data to a host of a simulation platform. The data of the hardware real object are acquired by the DAQ device and then transmitted to the host of the simulation platform to carry out on-line adjustment. The method effectively solves the real-time problem of the complex simulation system, and can be widely applied to the semi-physical simulation system.

Description

technical field [0001] The invention relates to the field of simulation technology, in particular to a real-time semi-physical simulation system and a data collection method thereof. Background technique [0002] A typical hardware-in-the-loop simulation system is composed of host 1, target system 2 and hardware object 3; the structural block diagram is shown in the attached figure 1 shown. Host 1 creates various prototypes, and generates and downloads code to run on the target system. The target system 2 can be another PC or an embedded system; it is used to run real-time algorithms. The hardware object 3 is an object in the real world, controlled by the target system 2, and the goal of the simulation is to verify the correctness of the algorithm on the hardware object 3. [0003] Although the above-mentioned system can measure data through the IO port of the target system, when the amount of measured data is large, it will often occupy a large amount of system resources...

AI Technical Summary

Problems solved by technology

[0003] Although the above-mentioned system can measure data through the IO port of the target system, when the amount of measured data is large, it will often occupy a large amount of system resources, which will affect the real-time performance of the simulation system.

For users, the quality of the adjustment effect can only be reflected in subjective observation results, lacking objective measurement data; therefore, it is only suitable for less complex applications or teaching demonstration occasions; for real-time signal processing and other large data volume, Systems with complex algorithms, such as aerospace, radar simulation and other applications; real-time simulation cannot be achieved

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