The invention belongs to the technical field of
foreign matter detection and recognition, and provides a battery compartment
foreign matter recognition method and
system based on
laser scanning and AI recognition. A
laser scanning module is used for scanning and collecting three-dimensional
point cloud data in a battery cabin in a preset period,
point cloud preprocessing is carried out on the collected original
point cloud data, the collected original point
cloud data are converted into a unified cabin coordinate
system,
point cloud segmentation is carried out, a
hypersphere model of
normal state point cloud is constructed based on a support vector
data description method, and a
hypersphere model is constructed. The abnormal state is judged through a dynamic threshold value,
foreign matter position tracing is carried out according to personnel positioning data in combination with multi-period scanning data, and the multi-
source data alignment precision and trajectory
estimation stability are cooperatively improved through
dynamic time warping and space-time filtering. The method can effectively extract complex features, improve foreign matter recognition precision, recognize foreign matters in real time, judge the properties of the foreign matters, improve
data processing efficiency, automatically adapt to complex and changeable environments and ensure stable and reliable operation under various working conditions.