Automatic sensor evaluation in BMS commissioning of building refrigeration systems

Shengwei Wang, Jin Bo Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

17 Citations (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)59-73
Number of pages15
JournalAutomation in Construction
Volume11
Issue number1
DOIs
Publication statusPublished - 1 Jan 2002

Keywords

  • Building management system
  • Commissioning
  • Refrigeration system
  • Sensor fault
  • Sensor validation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Building and Construction

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