An Improved Dust-Concentration Measurement Algorithm Based on Multifeature Fusion of <i>β</i>-Ray Intensity Fluctuations

Zhao, Zheng; Li, Dewen; Liu, Guoqing; Wu, Fangming; Sui, Jinjun

doi:10.1109/tim.2020.2972552

Cited by 7 publications

(1 citation statement)

References 18 publications

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“…Various methods are available for measuring dust concentration. Existing representative dust measurement methods for PM2.5 include the gravimetric method and the beta-ray absorption method [ 25 ]. The gravimetric method manually measures the weight of the collected dust, while the beta-ray absorption method automatically measures the concentration using the amount of beta-rays absorbed by the dust.…”

Section: Dust Sensing Systemmentioning

confidence: 99%

Optimized Replication of ADC-Based Particle Counting Algorithm with Reconfigurable Multi-Variables in Pseudo-Supervised Digital Twining of Reference Dust Sensor Systems

Lee

Kwon

Park

2023

Sensors

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As the application fields for digital twins have expanded, various studies have been conducted with the objective of optimizing the costs. Among these studies, research on low-power and low-performance embedded devices has been implemented at a low cost by replicating the performance of existing devices. In this study, we attempt to obtain similar particle count results in a single-sensing device replicated from the particle count results in a multi-sensing device without knowledge of the particle count acquisition algorithm of the multi-sensing device. Through filtering, we suppressed the noise and baseline movements of the raw data of the device. In addition, in the process of determining the multi-threshold for obtaining the particle counts, the existing complex particle count determination algorithm was simplified to make it possible to utilize the look-up table. The proposed simplified particle count calculation algorithm reduced the optimal multi-threshold search time by 87% on average and the root mean square error by 58.5% compared to existing method. In addition, it was confirmed that the distribution of particle count from optimal multi-thresholds has a similar shape to that from multi-sensing devices.

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Section: Dust Sensing Systemmentioning

confidence: 99%