Water Pollution Warning by Online Spectroscopy on Cloud Platform
author: Susan
2022-01-04
Challenge
The traditional chemicals measure water quality takes long measure cycle by expert face twice environmental pollution. In resent year, UV, VIS spectroscopy has been widely applied to water quality monitor with advantages of fast, clean, accurate and traceable. How to improve the whole system accuracy and stability? How to response faster to warning on water pollution case? Many researchers store water quality parameters modeling at the local server can not be effectively work out best project solution to pollution at first time. It takes long time to response to pollution and take effective and immediate solution to water pollution case, cloud platform can be active to water pollution communication and research on solution.
Principle
Lambert-Beer Law is the basic law of aw of absorption spectroscopy. When a beam of parallel monochromatic light passes through a uniform, non-scattering light-absorbing solution vertically, its absorbance A is proportional to the concentration of the light-absorbing solution c and the thickness of the liquid layer (optical path) l. This law is also quantitative by ultraviolet spectroscopy. The theoretical basis of the analysis, the schematic diagram of the Lambert-Beer law is shown in Figure 1, which can be expressed as
Figure 3 Spectra of 8 standard sample solutions measured under three spectrometers
Test Result
After calculation, after using the normalization algorithm based on EWMA-PCA, the correlation coefficient can reach 99.57 65%, the variance can reach 0.0823%, and the peak offset can be reduced to 0.0005%. The above three indicate the algorithm The C10082CAH spectrometer and the Maya 2000Pro spectrometer, the C10082CAH spectrometer and the ATP2000P spectrometer, the Maya2000Pro spectrometer and the ATP2000P spectrometer, and the three sets of instruments and the data standardization process showed a benign development. The standardization algorithm is effective and performs well.
Related Products
ATP2000P Light source ATG1020H Optical fiber UV-VIS Cuvette Holder ATP0080
Related Articles
How to Measure the Water Quality of Tokyo Bay How to Detect COD by UV Spectroscopy NIR Spectroscopy for E.coli
The traditional chemicals measure water quality takes long measure cycle by expert face twice environmental pollution. In resent year, UV, VIS spectroscopy has been widely applied to water quality monitor with advantages of fast, clean, accurate and traceable. How to improve the whole system accuracy and stability? How to response faster to warning on water pollution case? Many researchers store water quality parameters modeling at the local server can not be effectively work out best project solution to pollution at first time. It takes long time to response to pollution and take effective and immediate solution to water pollution case, cloud platform can be active to water pollution communication and research on solution.
Principle
Lambert-Beer Law is the basic law of aw of absorption spectroscopy. When a beam of parallel monochromatic light passes through a uniform, non-scattering light-absorbing solution vertically, its absorbance A is proportional to the concentration of the light-absorbing solution c and the thickness of the liquid layer (optical path) l. This law is also quantitative by ultraviolet spectroscopy. The theoretical basis of the analysis, the schematic diagram of the Lambert-Beer law is shown in Figure 1, which can be expressed as
Figure 1 Schematic diagram of Lambert-Beer law
Solution
1. UV-VIS spectroscopy solution：
In the experiment, three typical spectrometers used in the water quality spectrum detection were used to detect samples, namely: Hamamatsu C10082CAH spectrometer, Ocean Maya2000Pro spectrometer, and Optosky ATP2000P spectrometer, among which Hamamatsu C10082CAH spectrometer from 200~800nm, measuring 2048 pixels; Ocean Insight Maya2000Pro spectrometer from 200~1100nm, measuring 2068 pixels; Optosky ATP2000P spectrometer, measuring 2048 pixels from 200 to 1,100 nm. The water quality detection system is shown in Figure 2. In order to verify the validity of the experimental comparison, the experiment is the same except for the spectrometer, the other experimental environment and test equipment are the same: the same light source ATG1020H, the same optical path ATP0080, and the optical fiber UV-VIS.
In the experiment, three typical spectrometers used in the water quality spectrum detection were used to detect samples, namely: Hamamatsu C10082CAH spectrometer, Ocean Maya2000Pro spectrometer, and Optosky ATP2000P spectrometer, among which Hamamatsu C10082CAH spectrometer from 200~800nm, measuring 2048 pixels; Ocean Insight Maya2000Pro spectrometer from 200~1100nm, measuring 2068 pixels; Optosky ATP2000P spectrometer, measuring 2048 pixels from 200 to 1,100 nm. The water quality detection system is shown in Figure 2. In order to verify the validity of the experimental comparison, the experiment is the same except for the spectrometer, the other experimental environment and test equipment are the same: the same light source ATG1020H, the same optical path ATP0080, and the optical fiber UV-VIS.
Figure 2 UV-Visible spectroscopy in water quality detection system
Test ResultFigure 3 Spectra of 8 standard sample solutions measured under three spectrometers
a)Hamamatsu C10082CAH spectrometer b) Ocean Insight Maya2000 Pro spectrometer c) Optosky ATP2000P spectrometer
2. EWMA-PCA Normalization algorithm can uniform different spectrometers response to different measure signals in order to standardize water quality modeling clarification.
First, use EWMA to filter the sample water quality spectrum data, and perform dimensionality reduction to extract the principal components; then use the direct standardization algorithm to perform matrix transformation on the two sets of data of the source and target computers, and finally perform Z-score standardization and normalization of the data deal with.Test Result
(a) Water quality spectral data of 8 groups of potassium hydrogen phthalate solution
(b) Three sets of comparison experiments to determine the normalized data of water absorption spectra of each concentration
(c) Standardized evaluation of water absorption spectra of each concentration measured by three sets of comparison experiments
ConclusionAfter calculation, after using the normalization algorithm based on EWMA-PCA, the correlation coefficient can reach 99.57 65%, the variance can reach 0.0823%, and the peak offset can be reduced to 0.0005%. The above three indicate the algorithm The C10082CAH spectrometer and the Maya 2000Pro spectrometer, the C10082CAH spectrometer and the ATP2000P spectrometer, the Maya2000Pro spectrometer and the ATP2000P spectrometer, and the three sets of instruments and the data standardization process showed a benign development. The standardization algorithm is effective and performs well.
Figure 4 Demonstration diagram of water pollution early warning system based on cloud platform
Build the EWMA-PCA algorithm on the cloud platform, classify the water pollution data of TensorFlow, use the convolutional neural network to establish a water quality discrimination model, classify different concentrations of COD and NO3-N solutions; and use it for water pollution early warning.Related Products
ATP2000P Light source ATG1020H Optical fiber UV-VIS Cuvette Holder ATP0080
Related Articles
- “Changes in U.S. Water Quality Management Policies and Regulations and Their Enlightenment”
- “Research Progress and Application of Water Quality Analysis Methods Based on Ultraviolet-Visible Spectroscopy”
- “Research progress of online monitoring and early warning models for drinking water”
How to Measure the Water Quality of Tokyo Bay How to Detect COD by UV Spectroscopy NIR Spectroscopy for E.coli
XRF Fluorescence Spectrometer for jewelry 
Treatment of Medical Waste Based on Spectroscopy 
Whole Blood Analysis Based on UV-VIS Spectroscopy 
Irradiance Spectrum Analysis Measure Solution 
spectrometer FAQ 
LED Light Measurement Solution 
How to Use NIR Spectrometer to Detect Textiles Rapidly 
Estimation of Forage Biomass and Nutritional Value by Ground Spectrometer