The application discloses an improved evidence theory multi-
modal tunnel anomaly identification method, and belongs to the technical field of underground
engineering safety monitoring; different
modal data are collected in the
robot inspection process, and the space-time synchronous registration of the
modal data is realized through unified time stamp and external parameter calibration;
laser radar three-dimensional structure features, visible light texture edge features and
infrared temperature field features are respectively extracted, and
basic probability distribution functions of the
modes are constructed; a modal confidence coefficient and an environment adjustment coefficient are introduced to double-dynamically correct the data, a conflict adaptive attenuation mechanism is used to improve D-S evidence fusion rules, and the
modal data fusion is realized; finally, the anomaly identification result and the early warning information are output based on the fusion trust function. The problems of low tunnel anomaly identification precision, weak environment anti-interference ability and high conflict
information fusion loss in the prior art are effectively solved, the precision and stability of the tunnel anomaly identification in the complex underground environment are greatly improved, and the method has a good
engineering application prospect.