Department of Mechanical Engineering, The Hague University, Delft, The Netherlands PhD candidate Eindhoven University of Technology
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1 Arie Taal Department of Mechanical Engineering, The Hague University, Delft, The Netherlands PhD candidate Eindhoven University of Technology Unit BPS PAGE 1
2 Demand Control Ventilation based on - Temperature - Presence - CO 2 quality Problem: CO 2 sensor Fault Detection and Diagnose (CO 2 -FDD) is missing. Unit BPS PAGE 2
3 Usually sensor values are stored in Building Management System (BMS) CO 2 FDD solution By comparing CO 2 values of different room wrong values can be estimated Unit BPS PAGE 3
4 Conventional FDD methods - Measurement values are compared with benchmark values - Benchmark values calculated by models Unit BPS PAGE 4
5 Physical model for CO 2 concentration V dc t dt = G t + C v t Q v t C(t)Q v t V = the volume of room in m 3, t is time in s, C(t) = CO 2 concentration in kg CO 2 /m 3 air, G(t) = CO 2 generation rate in kg/s, C V (t) = CO 2 concentration of supply air in kg CO 2 /m 3 air, Q V (t) = flow rate of supply air in m 3 /s. Unit BPS PAGE 5
6 Conventional FDD methods However: usually no sensors present for G(t) = CO 2 generation rate in kg/s, C V (t) = CO 2 concentration of supply air in kg CO 2 /m 3 air, Q V (t) = flow rate of supply air in m 3 /s. Proposed CO 2 FDD method - Comparing CO 2 measurements without using a benchmark model. - Automatic commissioning - Automatic self-correction of bias faults Unit BPS PAGE 6
7 Step 1 4 rules to estimate suspected CO 2 sensors - C measured < C ambient negative bias - C measured >C sp, u damper =100 % and t>n bias>0 - R(u damper > u max ) > θ min and t > n bias>0 - R(u damper < u max ) > θ min and t > n bias<0 Unit BPS PAGE 7
8 Rule 1 C measured < C ambient negative bias Unit BPS PAGE 8
9 Rule 2 C measured >C sp, u damper =100 % and t>n bias>0 Unit BPS PAGE 9
10 Rule 3: R(u damper >u max ) > θ min and t > n bias>0 Unit BPS PAGE 10
11 Rule 4: R(u damper <u max ) > θ min and t > n bias<0 Unit BPS PAGE 11
12 Step 2 Two methods to estimate sensor faults: % return air ventilation and - full outdoor air ventilation. Unit BPS PAGE 12
13 Demonstration of the 2 proposed CO 2 FDD methods: simulation for the HHS building Room 7 CO2: 720 ppm Volume: 166 m3 Room 8 CO2: 720 ppm Volume: 156 m3 Room 9 CO2: 790 ppm Volume: 234 m3 Room 6 CO2: 780 ppm Volume: 133 m3 Room 5 CO2: 740 ppm Volume: 30 m3 Room 4 CO2: 730 ppm Volume: 30 m3 Room 3 CO2: 800 ppm Volume: 78 m3 Room 2 CO2: 770 ppm Volume: 156 m3 Room 1 CO2: 710 ppm Volume: 78 m3 Unit BPS PAGE 13
14 Demonstration of the proposed CO 2 FDD methods: method % Fresh air Unit BPS PAGE 14
15 CO2 concentration (ppm) AUTOMATIC COMMISSIONING OF CO2 SENSORS IN Demonstration of the proposed CO 2 FDD methods: method 1 CO2 measurement in Room 2 Bias (+100 ppm) Actual CO2 concentration in Room 2 Time (h) Unit BPS PAGE 15
16 Demonstration of the proposed CO 2 FDD methods: method 2 Air circulation Unit BPS PAGE 16
17 CO2 concentration (ppm) AUTOMATIC COMMISSIONING OF CO2 SENSORS IN Demonstration of the proposed CO 2 FDD methods: method 2 CO2 measurement in Room 2 Bias (+100 ppm) Actual CO2 concentration in Room 2 Time (h) Unit BPS PAGE 17
18 scheme of the automatic CO 2 sensor commissioning BMS measurements Find suspected faulty CO2 sensor using a set of rules No Any suspected sensor? Fault-free Yes Mark the false alarm Schedule the automatic commissioning in the night, weekends or holidays Implement of Method 1 or Method 2 Any faulty sensor? Yes No Fault-free Estimate the fault through calculating the difference between fault sensor measurement and the others Remove the fault through adjusting the measurements of faulty CO2 sensor in BMS Report the results Unit BPS PAGE 18
19 Conclusions Simulations show that by % fresh air or % return air volume bias faults can be detected. Unit BPS PAGE 19
20 Thank you for your attention Unit BPS PAGE 20
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