On-Site Sensor Sensitivity Adjustment Technique for a Maintenance-Free Heat Flow Monitoring in Building Systems
Abstract
:1. Introduction
2. Materials and Methods
2.1. Theoretical Background
2.2. Design of the Adaptive Self-Adjustment Procedure
- Heat transfer coefficient α of the computational model is optimized by fitting the simulated surface temperature, Ts,sim(t), to that determined experimentally, Ts,exp (t);
- Heat flux from the interior to the wall surface, qIN(t), is calculated from the experimental data using Equation (2) and the optimized heat transfer coefficient α from the previous step;
- Heat flux from the wall surface element to the wall, qOUT(t), is calculated from the computational data using Equation (3) and compared with qIN(t) from the previous step to validate the setup and accuracy of the computational model;
- qIN(t) and qOUT(t) are averaged to form a new variable, qREF(t), having a sufficient robustness as it combines both experimental and computational outputs;
- Sensitivity of heat flux sensors (thermopiles) is adjusted using raw U(t) (voltage) data and q(t) from the previous step and custom sensitivity function S is identified for each thermopile;
- Raw data provided by the heat flux sensors in the period are adopted and transformed into heat flux using S function from the previous step;
- The heat flux obtained in the previous step is compared with experimentally and computationally derived data to verify the adjusted sensitivity;
- The verified heat flux obtained in the previous step is validated against the reference heat flux obtained from an independent sensor.
2.3. Self-Adjustment Procedure in Real Conditions
2.4. Validation of the Proposed Self-Adjustment Approach
3. Results
3.1. Phase 1—Initialization
3.2. Phase 2—Sensor Sensitivity Adjustment
3.3. Phase 3—Sensor Performance Verification
3.4. Validation of the Self-Adjustment Technique
4. Discussion
5. Conclusions
- Factory calibration of heat flux sensors is not always sufficient as the real experimental conditions may differ from those effective during the calibration. Also, some errors may arise from the type of installation of the heat flux sensors which can subsequently affect the sensitivity of the sensor.
- Continuous monitoring of heat flow sensor performance and silent checking of their accuracy allows the proposed technique to be applied instantaneously during the ongoing experiment without interfering with experimental apparatus or taking technological breaks required for sensor manipulation or replacement.
- The proposed approach is suitable for both short-term and long-term heat flux measurements while bringing an entirely new potential for maintenance-free applications. However, a qualified decision on sensor sensitivity re-adjustment or re-initialization of the computational model running in the background is crucial to ensure high accuracy of the method.
- The principles of the adaptive re-adjustments of heat flux sensor performance allow for their integration into automatic systems and smart HVAC technologies to efficiently control the indoor environment and thermal comfort of residential buildings based on real-time performance data.
- Although the validation was performed with sufficient accuracy, the additional testing would be beneficial to include various conditions, surface materials, or different kinds of probes. Such a complex validation should be considered an essential precondition.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Parameter | AAC | Ext. Plaster | |
---|---|---|---|
Simulation | ρv (kg·m−3) | 500 | 1244 |
ρ (kg·m−3) | 2206 | 2415 | |
ψ (–) | 0.31 | 0.34 | |
λ (W·m−1·K−1) | 0.12 | 0.28 | |
c (J·kg−1·K−1) | 1050 | 1054 | |
Boundary conditions | Determined experimentally | ||
Experiment | Wall orientation | North | |
Wall thickness | 500 mm | ||
Exterior plaster thickness | 10 mm |
Description | Period | |
---|---|---|
Phase 1 | Initialization 1 | 11 August 2020–24 August 2020 |
Initialization 2 | 1 February 2021–7 February 2021 | |
Phase 2 | Sensor adjustment 1 | 28 September 2020–4 October 2020 |
Sensor adjustment 2 | 31 November 2020–6 December 2020 | |
Sensor adjustment 3 | 1 February 2021–7 February 2021 | |
Sensor adjustment 4 | 29 March 2021–4 April 2021 | |
Phase 3 | Performance verification 1 | 5 October 2020–12 October 2020 |
Performance verification 2 | 7 December 2020–14 December 2020 | |
Performance verification 3 | 8 February 2021–15 February 2021 | |
Performance verification 4 | 5 April 2021–12 April 2021 | |
Phase 4 | Validation | 1 March 2022–17 March 2022 |
Period | A (W·V−1·m−2) | B (W·m−2) | RMSE |
---|---|---|---|
28 September 2020–4 October 2020 | 0.4880 | 0.8915 | 1.078 |
30 November 2020–6 December 2020 | 0.3412 | 0.2712 | 0.888 |
1 February 2021–7 February 2021 | 0.4570 | 0.3482 | 0.889 |
29 March 2021–4 April 2021 | 0.6468 | −0.0156 | 1.270 |
USC (mV) | Ucurrent (mV) | Rcurrent (Ω) | Rheater (Ω) | Aheater (m2) | SSC (V·m2·W−1) | |
---|---|---|---|---|---|---|
1 | 3.012 | 0.596 | 10 | 99.2 ± 1.0 | (3885 ± 136) × 10−6 | (60.34 ± 2.41) × 10−6 |
2 | 2.958 | 0.594 | 10 | 99.2 ± 1.0 | (3885 ± 136) × 10−6 | (65.69 ± 2.63) × 10−6 |
3 | 2.925 | 0.592 | 10 | 99.2 ± 1.0 | (3885 ± 136) × 10−6 | (65.42 ± 2.62) × 10−6 |
4 | 2.938 | 0.593 | 10 | 99.2 ± 1.0 | (3885 ± 136) × 10−6 | (65.46 ± 2.62) × 10−6 |
5 | 2.859 | 0.588 | 10 | 99.2 ± 1.0 | (3885 ± 136) × 10−6 | (64.66 ± 2.59) × 10−6 |
SSC = (64.31 ± 2.57) × 10−6 V·m2·W−1 |
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Kočí, J.; Maděra, J.; Černý, R. On-Site Sensor Sensitivity Adjustment Technique for a Maintenance-Free Heat Flow Monitoring in Building Systems. Appl. Sci. 2024, 14, 7323. https://doi.org/10.3390/app14167323
Kočí J, Maděra J, Černý R. On-Site Sensor Sensitivity Adjustment Technique for a Maintenance-Free Heat Flow Monitoring in Building Systems. Applied Sciences. 2024; 14(16):7323. https://doi.org/10.3390/app14167323
Chicago/Turabian StyleKočí, Jan, Jiří Maděra, and Robert Černý. 2024. "On-Site Sensor Sensitivity Adjustment Technique for a Maintenance-Free Heat Flow Monitoring in Building Systems" Applied Sciences 14, no. 16: 7323. https://doi.org/10.3390/app14167323