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Multi-channel optical sensing system with a BP-ANN for heavy metal detection.
Opt Express ; 30(6): 9413-9427, 2022 Mar 14.
Article en En | MEDLINE | ID: mdl-35299369
A multi-channel optical sensing system for heavy metal concentration detection is presented in this paper. The system utilizes a multi-channel optical path combined with a unique circuit design and BP neural network (BP-ANN) to perform the online analysis of multi-wavelength signals, achieving accurate concentration detection of a heavy metal solution. An array photodiode is used to detect the transmission light intensities at multiple wavelengths through the optical path of the system, which enables the collection of useful spectral information of the solution. The system uses a unique signal acquisition method to effectively improve the efficiency of both signal acquisition and operation. BP-ANN is applied to the online analysis of multi-channel information, which overcomes the influential issue of nonlinear effect on data detection, optimizes the anti-interference ability, and lowers the detection limit of the system. This system eliminates the necessary employment of the expensive and large spectrometers and therefore greatly reduces the instrument cost and occupying space. Additionally, the detection limit of the system is extended lower than that of the conventional spectrophotometer. Compared with the detection limits of heavy metal solution obtained by using a single characteristic light wavelength, the detection limits of Cd2+, Cu2+ and Cr6+ achieved through using multi-channel detection system can be reduced by 42.64%, 38.12%, and 20.62%, respectively, and these detection limits are found as 0.0041mg/L, 0.0091mg/L, and 0.0112mg/L, respectively.

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: Opt Express Asunto de la revista: OFTALMOLOGIA Año: 2022 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: Opt Express Asunto de la revista: OFTALMOLOGIA Año: 2022 Tipo del documento: Article