Temperature Compensation Algorithm of Air Quality Monitoring Equipment Based on TDLAS

Wang, Yue; Wang, X.Q

doi:10.3390/math11122656

Cited by 2 publications

(2 citation statements)

References 15 publications

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“…The distribution of data types after the outlier removal of the training set data by the IIForest algorithm is shown in Table 2. Due to the complex mechanisms by which the gas is to be measured, and the various components in the laser methane sensor are affected by temperature, it is not easy to ensure stable CH 4 concentration output accuracy by a single polynomial fitting model [26][27][28]. The sensor temperature compensation algorithm based on a neural network model has good generalization and learning ability, and better compensation results can be obtained from a large number of training datasets [29].…”

Section: Data Preprocessing With Improved Isolation Forest Outlier De...mentioning

confidence: 99%

Temperature Compensation of Laser Methane Sensor Based on a Large-Scale Dataset and the ISSA-BP Neural Network

Yin,

Zou,

Cheng

et al. 2024

Sensors

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We aimed to improve the detection accuracy of laser methane sensors in expansive temperature application environments. In this paper, a large-scale dataset of the measured concentration of the sensor at different temperatures is established, and a temperature compensation model based on the ISSA-BP neural network is proposed. On the data side, a large-scale dataset of 15,810 sets of laser methane sensors with different temperatures and concentrations was established, and an Improved Isolation Forest algorithm was used to clean the large-scale data and remove the outliers in the dataset. On the modeling framework, a temperature compensation model based on the ISSA-BP neural network is proposed. The quasi-reflective learning, chameleon swarm algorithm, Lévy flight, and artificial rabbits optimization are utilized to improve the initialization of the sparrow population, explorer position, anti-predator position, and position of individual sparrows in each generation, respectively, to improve the global optimization seeking ability of the standard sparrow search algorithm. The ISSA-BP temperature compensation model far outperforms the four models, SVM, RF, BP, and PSO-BP, in model evaluation metrics such as MAE, MAPE, RMSE, and R-square for both the training and test sets. The results show that the algorithm in this paper can significantly improve the detection accuracy of the laser methane sensor under the wide temperature application environment.

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Section: Data Preprocessing With Improved Isolation Forest Outlier De...mentioning

confidence: 99%

Temperature Compensation of Laser Methane Sensor Based on a Large-Scale Dataset and the ISSA-BP Neural Network

Yin,

Zou,

Cheng

et al. 2024

Sensors

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“…Algorithms to minimize disturbances have been developed [45][46][47]. TDLAS has been applied in atmospheric monitoring [48][49][50][51][52], industrial monitoring [53], combustion exhaust [54][55][56][57][58][59] for various gases, and also for NH 3 [60,61]. Other lasers commonly used in instruments are interband cascade lasers (ICLs) and quantum cascade lasers (QCLs) [62].…”

Section: Instrumentation Backgroundmentioning

confidence: 99%

Measurement of Light-Duty Vehicle Exhaust Emissions with Light Absorption Spectrometers

Giechaskiel,

Melas,

Franzetti

et al. 2024

Technologies

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Light-duty vehicle emission regulations worldwide set limits for the following gaseous pollutants: carbon monoxide (CO), nitric oxides (NOX), hydrocarbons (HCs), and/or non-methane hydrocarbons (NMHCs). Carbon dioxide (CO2) is indirectly limited by fleet CO2 or fuel consumption targets. Measurements are carried out at the dilution tunnel with “standard” laboratory-grade instruments following well-defined principles of operation: non-dispersive infrared (NDIR) analyzers for CO and CO2, flame ionization detectors (FIDs) for hydrocarbons, and chemiluminescence analyzers (CLAs) or non-dispersive ultraviolet detectors (NDUVs) for NOX. In the United States in 2012 and in China in 2020, with Stage 6, nitrous oxide (N2O) was also included. Brazil is phasing in NH3 in its regulation. Alternative instruments that can measure some or all these pollutants include Fourier transform infrared (FTIR)- and laser absorption spectroscopy (LAS)-based instruments. In the second category, quantum cascade laser (QCL) spectroscopy in the mid-infrared area or laser diode spectroscopy (LDS) in the near-infrared area, such as tunable diode laser absorption spectroscopy (TDLAS), are included. According to current regulations and technical specifications, NH3 is the only component that has to be measured at the tailpipe to avoid ammonia losses due to its hydrophilic properties and adsorption on the transfer lines. There are not many studies that have evaluated such instruments, in particular those for “non-regulated” worldwide pollutants. For this reason, we compared laboratory-grade “standard” analyzers with FTIR- and TDLAS-based instruments measuring NH3. One diesel and two gasoline vehicles at different ambient temperatures and with different test cycles produced emissions in a wide range. In general, the agreement among the instruments was very good (in most cases, within ±10%), confirming their suitability for the measurement of pollutants.

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Temperature Compensation Algorithm of Air Quality Monitoring Equipment Based on TDLAS

Cited by 2 publications

References 15 publications

Temperature Compensation of Laser Methane Sensor Based on a Large-Scale Dataset and the ISSA-BP Neural Network

Temperature Compensation of Laser Methane Sensor Based on a Large-Scale Dataset and the ISSA-BP Neural Network

Measurement of Light-Duty Vehicle Exhaust Emissions with Light Absorption Spectrometers

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