Dynamic temperature compensation model based on nonuniform temperature field change

Qian, Shengsheng; Dai, Shaosheng; Nie, Hewen; Yi, Weinan

doi:10.1016/j.infrared.2019.05.021

Cited by 8 publications

(4 citation statements)

References 2 publications

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“…Therefore, the factors affecting the accuracy of infrared temperature measurement can be determined by analyzing the factors affecting the radiation emissivity. The radiation received by the infrared sensor is mainly divided into three parts: radiation from the target, reflected radiation from the environment, and radiation from the atmosphere [20]. In other words, the temperature measured by the infrared temperature sensor includes the interference of various kinds of radiation in the measurement environment.…”

Section: Influence Factors Of Temperature Measurement Errormentioning

confidence: 99%

A Smart Helmet-Based PLS-BPNN Error Compensation Model for Infrared Body Temperature Measurement of Construction Workers during COVID-19

Cheng

et al. 2021

Mathematics

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In the context of the long-term coexistence between COVID-19 and human society, the implementation of personnel health monitoring in construction sites has become one of the urgent needs of current construction management. The installation of infrared temperature sensors on the helmets required to be worn by construction personnel to track and monitor their body temperature has become a relatively inexpensive and reliable means of epidemic prevention and control, but the accuracy of measuring body temperature has always been a problem. This study developed a smart helmet equipped with an infrared temperature sensor and conducted a simulated construction experiment to collect data of temperature and its influencing factors in indoor and outdoor construction operation environments. Then, a Partial Least Square–Back Propagation Neural Network (PLS-BPNN) temperature error compensation model was established to correct the temperature measurement results of the smart helmet. The temperature compensation effects of different models were also compared, including PLS-BPNN with Least Square Regression (LSR), Partial Least Square Regression (PLSR), and single Back Propagation Neural Network (BPNN) models. The results showed that the PLS-BPNN model had higher accuracy and reliability, and the determination coefficient of the model was 0.99377. After using PLS-BPNN model for compensation, the relative average error of infrared body temperature was reduced by 2.745 °C and RMSE was reduced by 0.9849. The relative error range of infrared body temperature detection was only 0.005~0.143 °C.

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Section: Influence Factors Of Temperature Measurement Errormentioning

confidence: 99%

A Smart Helmet-Based PLS-BPNN Error Compensation Model for Infrared Body Temperature Measurement of Construction Workers during COVID-19

Cheng

et al. 2021

Mathematics

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“…The autoignition temperature or kindling point is the lowest temperature where a material or a substance starts to ignite on its own in a normal environment with no external source of ignition presents like a flame or a spark [12]. While the heating value or heat of combustion of a substance is the amount of heat released when the material is burning [13,14].…”

Section: Temperaturementioning

confidence: 99%

Development of a portable electronic device for the detection and indication of fireworks and firecrackers for security personnel

Africa

Tan

2020

IJEECS

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The use of fireworks and firecrackers to celebrate festivities is a very common activity in the Philippines. But due to the lack of strict control and regulation, there are unwanted risks of accidents from occurring due to the poor handling and storage conditions of these devices. Proper monitoring is important to reduce any unnecessary risks imposed on human life and property. While existing storage monitoring devices exist, the developed prototype is designed to contain sensors that are more suited in monitoring the ideal conditions of where the fireworks are stored. Monitoring the climate conditions on these devices may seem trivial at first, but such climate change can involve a rapid rise in temperature that can accidentally ignite the fireworks and deal with catastrophic damage. Another concern is the rise of humidity that may alter that chemical characteristics of the gunpowder stored in the fireworks. Such changes may not have any noticeable effects until it arrives in the consumer, that may experience an unwanted and unintended change in the performance of the fireworks leading to accidents. Therefore, it is important for this device to properly monitor the surrounding area then indicate various forms of alarms as a method of redundancy.

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“…At present, the direct measurement method is mainly used to measure the emissivity of the target and needs to be carried out without atmosphere, environmental factors and under conditions of constant temperature of the object itself, which is only suitable for laboratory measurement, but the emissivity measurement of target in the outdoor field is meaningless. Nevertheless, infrared temperature measurement technology is an irreplaceable role in all walks of life [8][9][10]. It is very meaningful to determinate the emissivity and accurate temperature of the object in outdoor heterogeneous environments.…”

Section: Introductionmentioning

confidence: 99%

Study of the Test Methods of Emission Rates in Different Ambient Temperature Fields

Zhao

Jia

Pei

et al. 2022

J. Phys.: Conf. Ser.

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With the wide application and rapid development of infrared temperature measurement, which has attracted wide spread interest in the field of non-contact temperature measurement due to its unique advantages. Measurement of the real temperature of the measured object is an important task in many disciplines, especially critical and difficult for the non-contact measurement. However, the accuracy of the infrared thermography technique is difficult to reach a satisfactory level, and cannot meet the requirements of high accuracy, due to the emissivity cannot be determined in outdoor environments. It is very meaningful to determinate the emissivity and accurate temperature of the object in outdoor heterogeneous environments. The influence of external environmental factors on the object surface emissivity are analyzed in this study, which is very important to improve the measurement accuracy of the infrared thermal imaging instrument. This study reveals that the increased temperature will lead in the increase of the emissivity of nonmetallic materials first and then decreases slowly. In addition, as the ambient temperature higher, the emission rate of non-metallic object becomes smaller.

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Dynamic temperature compensation model based on nonuniform temperature field change

Cited by 8 publications

References 2 publications

A Smart Helmet-Based PLS-BPNN Error Compensation Model for Infrared Body Temperature Measurement of Construction Workers during COVID-19

A Smart Helmet-Based PLS-BPNN Error Compensation Model for Infrared Body Temperature Measurement of Construction Workers during COVID-19

Development of a portable electronic device for the detection and indication of fireworks and firecrackers for security personnel

Study of the Test Methods of Emission Rates in Different Ambient Temperature Fields

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