Dual-wavelength optical sensor for measuring the surface area concentration and the volume concentration of aerosols

Deng, Tian; Wang, Shu; Zhu, Ming

doi:10.1016/j.snb.2016.06.031

Cited by 25 publications

(10 citation statements)

References 5 publications

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“…24,25 Generally, the particle size measured by these two instruments is equal to the optical particle size since the structure of the measurement aerosol is regular spherical. 5,20 The integrative structure of the prototype sensor consisted of the measurement module that has been mentioned in the section on theory and design principles, a sheath gas flow module that is discussed in detail in the section on the design of the sheath flow structure, and an electrical module. The ■ RESULTS AND DISCUSSION Establishment of the Transformation Model.…”

Section: Design Of the Sheath Flow Structurementioning

confidence: 99%

“…The measurement range of SMPS is lower than 1000 nm, and the measurement period is 300 s. APS cannot measure particle sizes smaller than 532 nm, and the measurement period is 10 s. The working procedure of the whole experiment process is described in detail in the section on the experiment process in the Supporting Information. The electromobility-based instrument of SMPS and the aerodynamics-based instrument of APS are combined with each other to measure the particle size of aerosols from submicron to micron. , Generally, the particle size measured by these two instruments is equal to the optical particle size since the structure of the measurement aerosol is regular spherical. , …”

Section: Theory and Modelsmentioning

confidence: 99%

“…4 In addition, PSD is an effective parameter to distinguish the fire smoke from the nonfire aerosols for improving indoor fire detection accuracy. 5 Therefore, it is of great importance to measure the PSD of aerosols accurately for understanding and mitigating its effects.…”

mentioning

confidence: 99%

“…It is also a critical parameter for exposure hazard assessment, where smaller aerosols would penetrate into the deeper locations of the respiratory tract, lungs, and even brain tissue . In addition, PSD is an effective parameter to distinguish the fire smoke from the nonfire aerosols for improving indoor fire detection accuracy . Therefore, it is of great importance to measure the PSD of aerosols accurately for understanding and mitigating its effects.…”

mentioning

confidence: 99%

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Light Scattering Method for Aerosol Sizing Based on Machine Learning

Zeng,

Xia

2024

ACS Sens.

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Optical scattering has been widely used for aerosol sizing due to its noninvasive and real-time measurement. However, it is crucial to retrieve the particle size distribution (PSD) of aerosols without prior knowledge of the refractive index. Now, it has been a great challenge to measure the refractive index in situ. In this study, a novel PSD sensing method utilizing the light scattering angular spectrum (LSAS) and machine learning techniques is proposed to address this challenge. The complex nonlinear relationship between LSAS and PSD can be constructed while accounting for the refractive index of aerosols. A miniaturized prototype sensor is designed and tested on different sizes of aerosol samples. The experiment results showed that the maximum Kullback−Leibler divergence (D KL ) of PSD is 0.07, which indicates that the sensing method can provide the ability for highly accurate aerosol PSD measurement without requiring prior knowledge of the refractive index. The compacted prototype sensor shows great potential for aerosol analysis in conventional field measurements outside the laboratory.

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Section: Design Of the Sheath Flow Structurementioning

confidence: 99%

Section: Theory and Modelsmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Light Scattering Method for Aerosol Sizing Based on Machine Learning

Zeng,

Xia

2024

ACS Sens.

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“…First, we need to evaluate the parameters of different black and white smoke such as particle size range, particle size distribution, and refractive indices. The particle size distribution of both white and black smoke can be described by lognormal distribution [28][29][30]:…”

Section: The Potential Optical Parameters For Simulationmentioning

confidence: 99%

An optical fire detector with enhanced response sensitivities for black smoke based on the polarized light scattering

Deng¹,

Zeng²,

Wang³

et al. 2019

Meas. Sci. Technol.

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Optical fire smoke detectors trigger the fire alarms when the scattering light intensity exceeds a preset threshold. Current optical detectors usually takes a long time or even fail to trigger a fire alarm for black smoke due to the strong absorption and weak scattering efficiency. A fire smoke sensor with dual polarized channels is proposed to adjust the response sensitivities to both white and black smoke. The white and black smoke can be discriminated by the polarization degree, and thus the response sensitivity can be adjusted by a correction factor. A prototype sensor is set up and tested by monodisperse aerosols with a maximum error of 10.1%. According to the experimental results, the prototype sensor could correctly differentiate white smoke and black smoke based on polarization degree, and the fire alarm for black smoke can be triggered as fast as for white smoke.

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Discrimination Between Fire Smokes and Nuisance Aerosols Using Asymmetry Ratio and Two Wavelengths

Zheng

Zhang

et al. 2019

Fire Technol

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Dual-wavelength optical sensor for measuring the surface area concentration and the volume concentration of aerosols

Cited by 25 publications

References 5 publications

Light Scattering Method for Aerosol Sizing Based on Machine Learning

Light Scattering Method for Aerosol Sizing Based on Machine Learning

An optical fire detector with enhanced response sensitivities for black smoke based on the polarized light scattering

Discrimination Between Fire Smokes and Nuisance Aerosols Using Asymmetry Ratio and Two Wavelengths

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