复杂系统多传感器数据智能融合方法研究

doi:10.3901/JME.2025.04.067

摘要/Abstract

摘要： 如何将复杂系统中各种传感器测量信息进行有效融合，从而形成系统智能控制的依据，是当前智能化领域研究的热点。传统的多传感器数据融合结构一旦确定便无法改变，既缺少足够的弹性计算能力保障，限制其他传感器的加入，也阻碍系统多传感器网络的构建。为了能够形成传感器网络以汇聚全面的系统数据，提出数据智能融合方法。首先借鉴云计算中的数据池思想，在架构上设计基于数据池的数据流动结构，传感器测量信息被汇聚在数据池中，相关算法被视同为服务，解决了数据处理的弹性计算能力问题；其次，经服务处理后的数据池数据，按需求被推送到控制系统，保证了数据处理与控制分离，形成以数据池为中心的星状传感器网络；最后，设计基于检测信号的通用非模型数据融合算法框架，通过信号分解后的系数进行拟合，再利用重构信号进行状态修正，完全摆脱了对系统模型的依赖，将数据融合计算形成了服务，大大降低了后期由于传感器引入对系统控制的影响。通过从设计思想、结构演进过程和特性分析对数据智能融合方法的分析表明，其具备较高的可行性和有效性。该方法的提出可以为我国复杂系统智能控制领域研究提供一条新的思路。

关键词: 数据池, 智能控制, 非模型, 多传感器, 数据融合

Abstract: How to effectively integrate various sensor measurement information in complex systems to form the basis for intelligent control of the system is currently a hot research topic in the field of intelligence. Once the traditional multi-sensor data fusion structure is determined, it cannot be changed which lacks sufficient elastic computing power to ensure the addition of other sensors, and also hinders the construction of the system’s multi-sensor network. In order to form a sensor network to gather comprehensive system data, firstly, a data flow structure based on a data pool is designed on the architecture. So the sensor measurement information is aggregated in the data pool, and related algorithms are treated as services, solving the problem of elastic computing power in data processing; Secondly, the data processed by the service is pushed to the control system according to demand, separating data processing from control, forming a star shaped sensor network centered on the data pool; Finally, an universal non-model data fusion algorithm framework based on detection signals was designed. Which the coefficients after signal decomposition were fitted, and the reconstructed signals were used for state correction, completely eliminating the dependence on the system model and greatly reducing the impact of sensor entering control system. At last, summarized the feasibility and effectiveness of the method from the perspective of design philosophy, structural evolution process, and characteristic analysis. The proposal of this method can provide a new approach for the research of intelligent control of complex systems.

Key words: data pool, intelligent control, non-model, multi-sensor, data fusion

中图分类号:

V464

黄莹. 复杂系统多传感器数据智能融合方法研究[J]. 机械工程学报, 2025, 61(4): 67-73.

HUANG Ying. Research on Intelligent Fusion Method for Multi Sensor Data in Complex Systems[J]. Journal of Mechanical Engineering, 2025, 61(4): 67-73.

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