{"title":"Characterization of road surfaces using three near-infrared diode lasers","authors":"Yin Cheng, Jianguo Liu, Huaqiao Gui, Jiaoshi Zhang, Xiuli Wei","doi":"10.1080/10739149.2023.2276698","DOIUrl":null,"url":null,"abstract":"AbstractRapid road network expansion has heightened the importance of surface condition information for traffic accident prevention and route optimization. This article introduces a laser diode-based sensor that identifies seven surface conditions and accurately measure ice, water, and snow film thicknesses on roads. An optical module was developed to detect weak optical signals based on the characteristic absorption spectrum of the target surface. The module used three laser diodes (1310, 1440, and 1550 nm wavelengths) as light sources. Additionally, a road classification algorithm that is adaptable to foggy weather was developed using a multi-wavelength processing protocol. The sensor was subjected to numerous calibration and performance verification experiments. During thick foggy measurements, the processed spectra displayed a maximum variation of 2.372% across a 600 to 25,000 m visibility range with a relative standard deviation of only 0.328%. This demonstrated effective weakening of the effects of visibility variations. During winter field testing, the sensor classified road conditions effectively and accurately measured ice, snow, and water film thicknesses, with a correlation coefficient of 0.97444. The accuracy of the measurements was less than 0.5 mm. The sensor’s effectiveness for long-term field-based road testing has been verified.Keywords: Diode laserinfrared spectrometrymulti-wavelength processingoptical sensorroad surface condition AcknowledgmentWe thank David MacDonald, MSc, from Liwen Bianji (Edanz) (www.liwenbianji.cn/) for editing the English text of a draft of this manuscript.Disclosure statementNo potential conflict of interest was reported by the authors.Additional informationFundingThis work was supported by the Key Research and Development Projects in Anhui Province, China under Grant 1908085MD114.","PeriodicalId":13547,"journal":{"name":"Instrumentation Science & Technology","volume":" 3","pages":"0"},"PeriodicalIF":1.3000,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Instrumentation Science & Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/10739149.2023.2276698","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
引用次数: 0
Abstract
AbstractRapid road network expansion has heightened the importance of surface condition information for traffic accident prevention and route optimization. This article introduces a laser diode-based sensor that identifies seven surface conditions and accurately measure ice, water, and snow film thicknesses on roads. An optical module was developed to detect weak optical signals based on the characteristic absorption spectrum of the target surface. The module used three laser diodes (1310, 1440, and 1550 nm wavelengths) as light sources. Additionally, a road classification algorithm that is adaptable to foggy weather was developed using a multi-wavelength processing protocol. The sensor was subjected to numerous calibration and performance verification experiments. During thick foggy measurements, the processed spectra displayed a maximum variation of 2.372% across a 600 to 25,000 m visibility range with a relative standard deviation of only 0.328%. This demonstrated effective weakening of the effects of visibility variations. During winter field testing, the sensor classified road conditions effectively and accurately measured ice, snow, and water film thicknesses, with a correlation coefficient of 0.97444. The accuracy of the measurements was less than 0.5 mm. The sensor’s effectiveness for long-term field-based road testing has been verified.Keywords: Diode laserinfrared spectrometrymulti-wavelength processingoptical sensorroad surface condition AcknowledgmentWe thank David MacDonald, MSc, from Liwen Bianji (Edanz) (www.liwenbianji.cn/) for editing the English text of a draft of this manuscript.Disclosure statementNo potential conflict of interest was reported by the authors.Additional informationFundingThis work was supported by the Key Research and Development Projects in Anhui Province, China under Grant 1908085MD114.
期刊介绍:
Instrumentation Science & Technology is an internationally acclaimed forum for fast publication of critical, peer reviewed manuscripts dealing with innovative instrument design and applications in chemistry, physics biotechnology and environmental science. Particular attention is given to state-of-the-art developments and their rapid communication to the scientific community.
Emphasis is on modern instrumental concepts, though not exclusively, including detectors, sensors, data acquisition and processing, instrument control, chromatography, electrochemistry, spectroscopy of all types, electrophoresis, radiometry, relaxation methods, thermal analysis, physical property measurements, surface physics, membrane technology, microcomputer design, chip-based processes, and more.
Readership includes everyone who uses instrumental techniques to conduct their research and development. They are chemists (organic, inorganic, physical, analytical, nuclear, quality control) biochemists, biotechnologists, engineers, and physicists in all of the instrumental disciplines mentioned above, in both the laboratory and chemical production environments. The journal is an important resource of instrument design and applications data.