Automatic sensor evaluation in BMS commissioning of building refrigeration systems

A strategy and software is developed to automatically diagnose and evaluate the Building Management Systems (BMS) sensors of building refrigeration systems during commissioning or periodical check (recommissioning). The strategy is based on the first law of thermodynamics (i.e., heat and mass balance of water networks). The strategy evaluates soft sensor faults (biases) by examining and minimizing the weighted sum of the squares of the concerned mass and/or steady state energy balance residuals represented by the corrected measurements over a period, on the basis of the measurements downloaded from BMS. A Genetic Algorithm is employed to determine the global minimal solution to the multimodal objective function, which can be difficult to achieve by traditional gradient-directed search methods. The sensor bias estimates, the confidence intervals of bias estimates and the comparisons of the balance residuals before and after the correction are generated by the software to provide a convenient and reliable means for the engineers to check and diagnose the measurement devices of BMS. The strategy, the software configuration and examples of application are presented in this paper.