The invention discloses a probabilistic
thermal runaway early warning method and
system based on a multi-
modal three-dimensional thermal field, and relates to the technical field of
energy storage safety monitoring, and the early warning method comprises the specific steps: S100, multi-
modal data collection; s200, carrying out
time alignment processing; s300,
feature fusion extraction is carried out; s400, reconstructing a three-dimensional temperature field; s500, calculating a
thermal runaway probability; according to the method, multi-
modal data of RGB-D, long-wave
infrared and gas sensors are fused, space-
time synchronization is realized in combination with a soft Kalman alignment
algorithm, the limitation of single
physical quantity monitoring is broken through, cross-modal correlation features are extracted by adopting a
pyramid cross attention
adversarial network, and the multi-
modal data of the RGB-D, the long-wave
infrared and the gas sensors are subjected to hierarchical linkage response. The generated multi-scale feature
tensor can accurately describe the spatio-temporal evolution law of a
thermal runaway precursor, after lightweight neural
radiation field
voxel reconstruction,
millimeter-level dynamic updating of a three-dimensional temperature field is realized, the generation and
diffusion process of local hot spots in an
energy storage cabin can be captured in real time, and a high-fidelity thermal field portrait is provided for early
risk identification.