Engineering measurement error dynamic correction method based on multi-sensor data fusion

Abstract

The application discloses an engineering measurement error dynamic correction method based on multi-sensor data fusion and relates to the technical field of engineering measurement. By defining three error sources of sensor physical characteristics, environmental interference and human operation as estimable state variables, different characteristics of errors are processed differently: a dynamic model is established to embed the sensor and environmental errors into the state space, real-time compensation based on the model is realized, a gross error identification mechanism based on data-driven statistical characteristics is established to realize real-time diagnosis and processing of human errors, a recursive estimation algorithm is used to perform joint optimal estimation on the unified state vector, and the estimation values of the corrected physical quantity and error states are output synchronously, the scheme significantly improves the measurement accuracy and reliability through dynamic error compensation and optimal fusion, and the stability of the system in a non-ideal environment and online self-diagnosis and health monitoring of the measurement system are enhanced through robust processing of the gross error.

Images