V. Fabrication and Measurement Results
5.2 Measurement results
5.2.2 Gas ROIC chip performance
73
74
IDAC. In high resistance, the current source small IDAC has relatively high noise, and thus the SNR is greatly reduced. Current mode is measured from 9nA to 13.6mA and shows SNR performance of up to 94dB and minimum of 42dB. The current mode measurement also showed a tendency that the SNR is small in the low range and the SNR increased as the current range increased. The current source used in the low range current measurement has a high noise and thus this mode has a relatively low SNR.
The SNR continues to increase up to the middle current range, and then the SNR decreases in the high current mode. This is because the high current mode is measured through small RDAC. high current mode.
This is because the high current mode is measured through small RDAC.
Fig. 77 shows the measured output power spectral density (PSD) of the dual mode IADC. A sinusoidal signal corresponding to -0.4 dBFS with 349 Hz was used for measurement, and SNR and SNDR were confirmed through hann windowing. Measured SNR, signal-to-distortion-ratio (SNDR)
Fig. 152 The signal to noise ratio (SNR) of proposed ROIC for resistance and current mode.
75
and spurious free dynamic ratio (SFDR) for the bandwidth of 2-kHz are 103.5 dB, 101.4 dB and 105.6 dB, respectively. The power of the DC level is -72.4 dB, which corresponds to a 420 μV offset.
Fig. 78 represents the measured PSD of the third order incremental ADC. The input signal appears at the DC frequency, and noise is pushed into the high frequency band greater than the inband frequency 200 Hz, which means that noise-shaping is well done. The 3rd order delta sigma incremental ADC has a 107.2 dB SNR based on a DC input of 1.2V.
Fig. 154 Measured output spectrum density of 3rd order incremental ADC.
Fig. 153 Measured output spectrum density of dual mode IADC.
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Fig. 79 shows Heater voltage versus time by operating with same frequency and heater voltage versus time by operating with different frequency. Verification was conducted from 1.5 V voltage to 3 V voltage, the proposed heater controller freely controls the heater voltage and temperature using MCU.
The voltage of the heater rises constantly, which prevents damage to the heater due to sudden power supply. By adjusting the operating frequency of the heater controller, the desired heater temperature and voltage increase rate are obtained.
ADC [53] [54] [55] [56] This work
Architecture IADC2
+IADC1 IADC1
+Multi Slope IADC2 IADC2 SAR+IADC1
+EC CMOS
Process (μm) 65 160 180 160 180
Conversion
rate(S/s) 500 2000 20 1500 4000
Dynamic
range (dB) 99.8 99.7 - - 109.1
Power (W) 10.7 μ 34.6 μ 0.24 μ 20 μ 176
SNRMAX (dB) - 98.4 93.4 81.9 103.9
FoM (dB) 173.5 174.6 169.6 157.1 179.7
Table ⅩVII shows performance comparison of gas sensor ROIC and system. The proposed dual mode incremental ADC has a high figure of merit due to high sampling rate and SNR performance.
Fig. 155 (a) heater voltage versus time by operating with same frequency and heater voltage versus time by operating with different frequency.
Table ⅩVII
Performance comparison of incremental ADC.
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Gas ROIC [57] [58] [59] [60] This work
Architecture CTIA PWM CDS A-SDM CDS+SDM
CMOS Process (μm) 0.35 0.13 0.13 0.18 0.18
Dynamic range (dB) 101.1 127.2 117 100~160
Resistance:
128.8 Current:123.8
Resistance Range (Ω) - 5~11.5M 23 k ~ 4.6 M - 90~64M
Current Range (A) 8f-100p - - 100f~10u 8n~22m
Power (W) - 0.06 m 11.3 μ 0.295 m 1.28 m
Table ⅩVIII shows performance comparison of gas sensor ROIC and system. The measured gas ROIC has a wide dynamic range compared to other works and accommodates current type gas sensors as well as resistance type gas sensors. Gas ROIC shows 128.8 dB of dynamic range of resistance mode and 123.8 dB of dynamic range of current mode.
Table ⅩVIII
Performance comparison of the gas ROIC.
78
Chapter Ⅵ
Conclusion
This doctoral thesis describes an indirect self-calibration gas sensor system with automatic gas sensor response and offset correction. The proposed gas sensor system can obtain the indirectly changed gas sensor response by using the Ro slope instead of the calibration gas, which is the input required for the inspection and calibration of the gas sensor. Since the gas sensor system does not require continuous inspection and calibration, it is possible to significantly reduce human resource and cost for the operation. The proposed intelligent gas sensor system reduces server overload through a pattern recognition algorithm based on edge computing. In addition, an optimized gas ROIC is designed to efficiently drive this gas sensor system and have versatility.
The gas sensor system is unreliable due to the gas sensor having different responsiveness depending on time and frequency of use. Addressing these fundamental limitations entails high costs such as gas and equipment required for calibration. This doctoral thesis defines the concept of a variable Ro slope that is correlated with the response of the gas sensor, and theoretically proves it. In addition, to prove this experimentally, several gas sensor samples were aged and verified, and it was shown that gas sensor calibration is possible indirectly.
Indirect self-calibration gas sensor systems are operated in the absence of gas. To determine the presence or absence of gas, a gas recognition algorithm has been proposed. The gas recognition algorithm was designed based on the gas sensor response data according to the gas leak, and it uses a gas pattern recognition algorithm and a moving average. A gas pattern recognition algorithm is used to improve gas selectivity, and in most cases, it is performed in server using wireless communication.
However, this method causes an overload on the server as the number of gas sensor modules increases.
To improve this, I designed gas pattern recognition based on edge computing using tensor flow and STM 32 AI. Through edge computing, gas pattern recognition is performed in the gas sensor module to reduce server overload and enable gas recognition algorithms.
To efficiently operated the proposed indirect self-calibration gas sensor system, a gas ROIC was designed. A gas sensor requires a system having a wide sensing range because materials used for manufacturing vary depending on the type of gas to be sensed. In addition, since gas sensors are usually divided into resistance and current types, there is a disadvantage that a gas sensor module suitable for this is required. The proposed gas ROIC has a wide dynamic range gas detection front-end to
79 accommodate a wide range and various gas sensors.
Since the gas sensor system must continuously detect gas, it needs to be operated efficiently depending on the situation. In normal cases, the power required for gas detection is reduced, and when gas is detected, gas sensing proceeds with high-resolution measurement. To satisfy this demand, a dual- mode ADC that provides low-power and high-resolution modes is designed. In addition, the use of one integrator and the optimal feedback reference technique are proposed to reduce the ADC circuit power.
To obtain the Ro slope in the gas self-calibration system, it is essential to control the heater temperature. To minimize heater damage while easily controlling the heater temperature, a feedback- based heater controller was designed. The heater voltage used to control the heater temperature can be freely adjusted through the MCU. In addition, the heater controller freely applies the heater voltage speed through feedback structure and clock frequency control.
The proposed indirect self-calibration gas sensor system will be helpful for frame construction and research of systems targeting automatic unmanned systems. In addition, power optimization techniques for efficient system operation can be applied in most fields and are worth continuing research. This work did not just design the system, but also added a communication and monitoring system to build an effective gas sensor platform.
80
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ACKNOWLEDGEMENTS
First of all, I would like to thank Professor Jae Joon Kim for my research guidance. Professor Jae Joon Kim informed me about the right direction of research and the attitude of a researcher during my doctoral course. I think he deserves respect both personally and academically, and I hope that many researchers go the way of him. Also, I would like to thank Prof. Yunsik Lee, Prof . Myunghee Lee, Prof.
Heungjoo Shin, and Prof. Jeong-Min Baik, who gave a lot of advice and feedback to my doctoral thesis defense. The professors' sharp criticisms and professional knowledges from various perspectives lead my doctoral thesis to further develop.
I would like to thank Hee-Young Chae, Kyunghwan Park, and Su-Bin Choi for their research and help on the gas sensor system. In addition, I would like to thank Kwang-Muk Lee, who discussed and advised me on the direction of my research with me. I would also like to thank Myeong-Woo Kim, Chan-Sam Park, Jun-Young Yeom, Jeonghoon Jo, Hyun-Joong Kim, and Minseok Park, who belong to the same lab. I would like to thank Sung-Woo Kim, Jong-Gyu Jang, and Seung-Mok Kim, who graduated.
In particular, I would like to thank parents, older sister, and Ju-Eun Lee for supporting me to complete my Ph.D.
86
CURRICULUM VITAE
EDUCATION
PhD., Electrical Engineering, Ulsan National Institute of Science and Technology, June 2021 Advisor: Jae Joon Kim
M.S., Electrical Engineering, Kyungpook National University, February 2015 Advisor: Jae Hoon Shim
B.S., Electrical Engineering, Kyungpook National University, February 2013
PUBLICATION
1. B. Oh, K. Park, J. J. Kim, "A Triple-Mode Performance-Optimized Reconfigurable Incremental ADC for Smart Sensor Applications," IEEE Access, Vol. 7, pp. 19013-19023;
doi:10.1109/access.2019.2896756, January 31th, 2019.
2. B. Oh, J. J. Kim, "A Four-Step Incremental ADC Based on High-Coefficient Integrator and Binary Extended Counting with Capacitive DAC," IEEE Transactions on Circuits and Systems II, doi:10.1109/TCSII.2019.2943171.
3. S. Choi, C. S. Park, H. Y. Chae, B. Oh, J. Lee, Y. M. Kwon, J. M. Baik, H. Shin, J. J. Kim, "A Wide Dynamic Range Multi-Sensor ROIC for Portable Environmental Monitoring Systems with Two-Step Self-Optimization Schemes," IEEE Transactions on Circuits and Systems I, doi:10.1109/
TCSI.2021.3065503.
4. S. Choi, K. Park, S. Lee, Y. Lim, B. Oh, H. Y. Chae, C. S. Park, H. Shin, J. J. Kim, “A Three-Step Resolution-Reconfigurable Hazardous Multi-Gas Sensor Interface for Wireless Air-Quality Monitoring Applications,” Sensors, 18(3), 761; doi:10.3390/s18030761, March, 2018.
5. C. S. Park, J. Jeon, B. Oh, H. Y. Chae, K. Park, H. Son, J. J. Kim "A Portable Phase-Domain Magnetic Induction Tomography Transceiver with Phase-Band Auto-Tracking and Frequency-Sweep Capabilities," Sensors, 18(11), 3816; doi:10.3390/s18113816, November, 2018.
CONFERENCE
1. B. Oh, S. Choi, H. Y. Chae, J. J. Kim, "Multimode-based dual type gas sensor readout IC," 2020 IEIE Summer Conference, Aug. 19-21, 2020. (Poster)
2. B. Oh, K. Park, S. Choi, C. Park, J. J. Kim, "A triple-mode reconfigurable incremental sigma-delta ADC," 18th RF/Analog Circuit Workshop, Jeju, Sept. 13-14, 2018. (Poster)