The application belongs to the technical field of
heating system, and relates to a
heating system environment sensing and multi-point
water quality optimization dosing method, wherein real-time sensing and uploading of
water quality data are realized through
multiple sensor nodes, then deep periodic characteristics of the
water quality data are extracted by using
quantum state space mapping and
quantum Fourier transform, a
global optimal medicament
combination strategy is solved in a constructed
quantum optimization model by combining a
quantum annealing algorithm, a medicament
compatibility matrix is constructed by using
tensor decomposition technology to integrate medicament characteristics and
pipe network parameters, each dosing terminal calculates a dosing amount based on local sensing, consistency of dosing decisions is ensured through a PBFT
consensus mechanism, finally, a flow velocity
distribution characteristic of the
pipe network is combined, a lead
control algorithm is used to correct medicament injection
time lag,
dynamic prediction and accurate control are realized, and therefore, a breakthrough is realized in local adaptability, global coordination and dynamic responsiveness of the distributed dosing
control system, and efficiency and stability of water quality regulation of the
heating system are significantly improved.