The research on compensation algorithm of infrared temperature measurement based on intelligent sensors

Wei, Shaoliang; Qin, Wenbo; Han, Liguo; Fang, Cheng

doi:10.1007/s10586-018-1828-5

Cited by 10 publications

(4 citation statements)

References 8 publications

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“…In Fig. 3, it is possible to observe the reflected energy (R) caused by the ambient temperature, which has some effect on the precision of the body temperature measurements [9].…”

Section: Influence Of Environment Factors On the Operation Of Infrarementioning

confidence: 99%

IoT Non-contact Body Temperature Measurement System Implementing Access Control for COVID-19

Costanzo

Flores

2021

Advances in Intelligent Systems and Computing

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The need to have total control over body temperature within COVID-19 crisis has made infrared sensors a valid alternative to traditional thermometers, so to avoid direct contact and thus virus spreading. In this work, an IoT system is presented which performs access control to popular places through the integration of body temperature, humidity, ambient temperature and servomotor sensors. Data captured by the sensors network is transmitted via Bluetooth Low Energy to a server programmed into a raspberry, which in turn is devoted to send data to a web platform for real time monitoring. Experimental results are discussed, by revealing a 0.42% average relative error as compared to standard contact thermometer. The proposed compact and low-cost IoT platform is able to provide thermographic detection in a fast and accurate way, thus avoiding contagion risk.

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“…In Fig. 3, it is possible to observe the reflected energy (R) caused by the ambient temperature, which has some effect on the precision of the body temperature measurements [9].…”

Section: Influence Of Environment Factors On the Operation Of Infrarementioning

confidence: 99%

IoT Non-contact Body Temperature Measurement System Implementing Access Control for COVID-19

Costanzo

Flores

2021

Advances in Intelligent Systems and Computing

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“…There are already many studies on the fusion of visible and thermal images [105][106][107][108][109][110][111][112][113][114][115][116][117][118] and such fusion has been integrated with face recognition [119][120][121]. Thermal images have some problems such as low contrast [122,123], blurred edge [124,125], temperature-sensitive [126][127][128], glass rejection [129][130][131][132], and little texture details [133,134]. The fusion of visible and thermal faces images will blur or hide some valuable information and therefore, can be employed to generate a challenging dataset for face recognition.…”

Section: Introductionmentioning

confidence: 99%

Broad Learning System for Tackling Emerging Challenges in Face Recognition

Zhang¹,

Wang²

2023

Computer Modeling in Engineering &Amp; Sciences

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Face recognition has been rapidly developed and widely used. However, there is still considerable uncertainty in the computational intelligence based on human-centric visual understanding. Emerging challenges for face recognition are resulted from information loss. This study aims to tackle these challenges with a broad learning system (BLS). We integrated two models, IR 3 C with BLS and IR 3 C with a triplet loss, to control the learning process. In our experiments, we used different strategies to generate more challenging datasets and analyzed the competitiveness, sensitivity, and practicability of the proposed two models. In the model of IR 3 C with BLS, the recognition rates for the four challenging strategies are all 100%. In the model of IR 3 C with a triplet loss, the recognition rates are 94.61%, 94.61%, 96.95%, 96.23%, respectively. The experiment results indicate that the proposed two models can achieve a good performance in tackling the considered information loss challenges from face recognition.

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“…Regarding how to achieve precise temperature control, our research group [6] established a multivariate linear error compensation model for measuring distance and angle, verified the specific effects of various factors on infrared temperature measurement, and designed a point infrared measurement compensation verification system to conduct online temperature detection experiments for composite material laser consolidation forming heating points, achieving precise measurement and real-time control of heating point temperature during composite material forming process; Hijazi A et al [7] developed a new method based on the Planck radiation equation, which improved the accuracy of prediction using dual wavelength infrared temperature measurement technology and introduced non gray compensation coefficients, greatly reducing experimental errors and achieving precise temperature control; Davies et al [8] developed an infrared microscope system for measuring the temperature field during processing and introduced a thorough calibration method that infers temperature based on the measured radiation field; Wei S et al [9] used an incident angle compensation algorithm based on temperature measurement and summarized the influence of incident angle on infrared temperature measurement through experimental research and data analysis. In terms of forming process, ZHAO Yachao et al [10] designed a laser planar placement forming system using a combination of laser assisted heating and hydraulic roller pressing technology to meet the requirements of carbon fiber reinforced thermoplastic composite plate forming process.…”

Section: Introductionmentioning

confidence: 99%

Research on temperature control technology for laser molding of thermoplastic composite materials

Weng,

Wang,

Zhang

et al. 2023

3rd International Conference on Laser, Optics, and Optoelectronic Technology (LOPET 2023)

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Continuous carbon fiber reinforced thermoplastic composites have problems such as long temperature self setting time, high overshoot, and low control accuracy during laser in situ molding, resulting in poor component forming quality. This article designs a temperature closed-loop control system based on an intelligent fuzzy proportional-integral-differential (PID) controller. By introducing a fuzzy self-tuning PID algorithm, the goal of quickly adjusting to the working temperature when turned on is achieved. The temperature overshoot is significantly reduced, and the temperature control accuracy is improved. According to the requirements of laser in situ forming of carbon fiber reinforced polyether ether ketone composite materials, a laser in situ forming experimental device was built. Through simulation testing and comparison of forming temperature, the results showed that compared with traditional PID controllers, when using an intelligent fuzzy PID controller to control temperature, the temperature control accuracy was maintained at ± 10 ℃, the overshoot percentage was about 2.29%, and the adjustment time was about 9.7 seconds. All indicators met the actual engineering requirements, The temperature setting effect is good and the fitting degree is high. Therefore, the overall performance of the intelligent fuzzy PID controller is far superior to traditional PID controllers, meeting the temperature control requirements in the laser in situ molding process of thermoplastic composite materials.

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The research on compensation algorithm of infrared temperature measurement based on intelligent sensors

Cited by 10 publications

References 8 publications

IoT Non-contact Body Temperature Measurement System Implementing Access Control for COVID-19

IoT Non-contact Body Temperature Measurement System Implementing Access Control for COVID-19

Broad Learning System for Tackling Emerging Challenges in Face Recognition

Research on temperature control technology for laser molding of thermoplastic composite materials

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