A Heavy Metal Ion Water Quality Detection Model Based on Spectral Analysis: New Methods for Enhancing Detection Speed and Visible Spectral Denoising
Abstract
:1. Introduction
2. Simulation Modeling of the Water Quality Detection System
2.1. Visible Spectroscopy
2.2. Absorption Characteristics of Water Quality Indicators
2.3. Common Color Quantization Models and Denoising Methods in Image Processing
2.4. Principle of EEMD-SVD Spectral Denoising Method
2.4.1. Principle of EMD Denoising
2.4.2. Principle of EEMD Denoising
- Add a random Gaussian white noise sequence of the same length to the original signal , ensuring that the added noise maintains the variance and has a mean value of zero. This will result in a signal sequence that contains white noise, as shown below:
- Using the EMD theory to decompose , a set of Intrinsic Mode Functions (IMFs) and (the residual component) will be generated, as shown in (5).
- Repeat the previous two steps to obtain m instances of , as shown in (6).
- Divide the average of all the IMFs by the added white noise from to obtain the final results, as shown in (7) and (8).
- The original signal can be recovered by removing the added white noise, as shown in (1–10).
2.4.3. Denoising Method Based on SVD
2.4.4. Application of EEMD-SVD Denoising Scheme in Water Quality Detection
2.4.5. Processing and Analysis of Spectral Images
2.4.6. Neural Network Modeling
- (1)
- Convolutional Neural Networks (CNNs)
- (2)
- Heavy Metal Ion Water Quality Parameter Prediction Model
3. Design of the Multi-Parameter Water Quality Detection System
4. Case Study: Copper Ions in Water
4.1. Experimental Instruments and Materials
4.2. Spectral Image Analysis of Copper Solution
4.3. Effectiveness Analysis of the EEMD-SVD Spectral Denoising Method
4.3.1. Validation of the Rationality of the EEMD-SVD Spectral Denoising Method
- (1)
- Analysis of the Denoising Effect of Copper Ion Solution Spectra
- (2)
- Analysis of the Denoising Effect of Arsenic Ion Solution Spectra
- (3)
- Analysis of the Denoising Effect of Lead Ion Solution Spectra
- (4)
- Analysis of the Denoising Effect of Mercury Ion Solution Spectra
- (5)
- Analysis of the Denoising Effect of Chromium Ion Solution Spectra
4.3.2. Field Water Sampling and Detection Test Comparison Analysis
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Type/Step Length | Nuclear Shape | Number of Parameters |
---|---|---|
convolution/1 | 3 × 3 × 3 × 64 | 576 |
convolution/1 | 64 × 3 × 3 × 3 × 64 | 36,864 |
max pooling/1 | 2 × 2 | |
convolution/1 | 64 × 3 × 3 × 128 | 73,728 |
convolution/1 | 128 × 3 × 3 × 128 | 147,456 |
max pooling/2 | 2 × 2 | |
convolution/1 | 128 × 3 × 3 × 256 | 294,912 |
convolution/1 | 256 × 3 × 3 × 256 | 589,824 |
convolution/1 | 256 × 3 × 3 × 256 | 589,824 |
max pooling/2 | 2 × 2 | |
convolution/1 | 256 × 3 × 3 × 512 | 1,179,648 |
convolution/1 | 512 × 3 × 3 × 512 | 2,359,296 |
convolution/1 | 512 × 3 × 3 × 512 | 2,359,296 |
max pooling/2 | 2 × 2 | |
convolution/1 | 512 × 3 × 3 × 512 | 2,359,296 |
convolution/1 | 512 × 3 × 3 × 512 | 2,359,296 |
convolution/1 | 512 × 3 × 3 × 512 | 2,359,296 |
max pooling/2 | 2 × 2 | |
fully connected layer | 25088 × 4096 | 102,760,448 |
fully connected layer | 4096 × 4096 | 16,777,216 |
fully connected layer | 4096 × 1 | 4096 |
Total number of parameters | 134,251,072 |
Metal Solutions | Cr | Hg | Pb | As | Cu |
---|---|---|---|---|---|
Accuracy (%) | 90.707 | 96.676 | 96.113 | 90.909 | 99.394 |
Name | Model | Specification |
---|---|---|
Diaphragm | SK12 | Φ1.0–12 mm |
Plano-convex lens | General analytical optical quartz plain convex lens | Φ30 mm, f39.2 mm |
Diffraction grating (Holographic) | GS012 Round Ball Technology | 1200-line/mm, 20 mm × 20 mm × 2 mm |
Lens carrier | Hengyang Optical MLNR-1.2 | Φ30 mm |
Optical bench | Kopu 25009 | 55 mm × 42 mm × 55 mm |
Indicator | R | G | B | H | S | V | Grayscale Value |
---|---|---|---|---|---|---|---|
Intercept | 0.18496 | 0.02133 | −0.01037 | −0.0431 | −0.04644 | −0.00164 | 0.03605 |
Slope | 0.68115 | 0.53183 | 0.26334 | 0.32752 | 0.35757 | 0.28092 | 0.46806 |
Correlation coefficient | 0.77405 | 0.91826 | 0.93965 | 0.76279 | 0.78905 | 0.93833 | 0.94095 |
Test Object | Sample Number | Spectral Method (mg/L) | National Standard Method (mg/L) | Relative Error (%) | Repeatability (%) | Spectral Method Mean (mg/L) | National Standard Method Mean (mg/L) |
---|---|---|---|---|---|---|---|
1 | 1 | 0.082 | 0.084 | −2.38% | 1.84% | 0.08 | 0.08 |
2 | 0.079 | 0.082 | −3.66% | ||||
3 | 0.079 | 0.082 | −3.66% | ||||
4 | 0.08 | 0.083 | −3.61% | ||||
5 | 0.081 | 0.083 | −2.41% | ||||
6 | 0.078 | 0.08 | −2.50% | ||||
2 | 1 | 0.21 | 0.22 | −4.55% | 4.06% | 0.22 | 0.23 |
2 | 0.22 | 0.24 | −8.33% | ||||
3 | 0.22 | 0.23 | −4.35% | ||||
4 | 0.23 | 0.24 | −4.17% | ||||
5 | 0.21 | 0.23 | −8.70% | ||||
6 | 0.23 | 0.23 | 0.00% | ||||
3 | 1 | 0.42 | 0.41 | 2.44% | 2.28% | 0.43 | 0.42 |
2 | 0.44 | 0.43 | 2.33% | ||||
3 | 0.42 | 0.41 | 2.44% | ||||
4 | 0.44 | 0.43 | 2.33% | ||||
5 | 0.44 | 0.41 | 7.32% | ||||
6 | 0.43 | 0.41 | 4.88% | ||||
4 | 1 | 0.55 | 0.52 | 5.77% | 1.50% | 0.54 | 0.53 |
2 | 0.55 | 0.53 | 3.77% | ||||
3 | 0.54 | 0.52 | 3.85% | ||||
4 | 0.54 | 0.53 | 1.89% | ||||
5 | 0.55 | 0.52 | 5.77% | ||||
6 | 0.53 | 0.53 | 0.00% | ||||
5 | 1 | 0.74 | 0.75 | −1.33% | 1.03% | 0.73 | 0.75 |
2 | 0.72 | 0.74 | −2.70% | ||||
3 | 0.73 | 0.73 | 0.00% | ||||
4 | 0.73 | 0.76 | −3.95% | ||||
5 | 0.73 | 0.75 | −2.67% | ||||
6 | 0.72 | 0.75 | −4.00% | ||||
6 | 1 | 0.93 | 0.93 | 0.00% | 1.46% | 0.95 | 0.92 |
2 | 0.93 | 0.93 | 0.00% | ||||
3 | 0.94 | 0.91 | 3.30% | ||||
4 | 0.95 | 0.92 | 3.26% | ||||
5 | 0.96 | 0.93 | 3.23% | ||||
6 | 0.96 | 0.92 | 4.35% |
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Sun, B.; Yang, S.; Cheng, X. A Heavy Metal Ion Water Quality Detection Model Based on Spectral Analysis: New Methods for Enhancing Detection Speed and Visible Spectral Denoising. Sensors 2025, 25, 2318. https://doi.org/10.3390/s25072318
Sun B, Yang S, Cheng X. A Heavy Metal Ion Water Quality Detection Model Based on Spectral Analysis: New Methods for Enhancing Detection Speed and Visible Spectral Denoising. Sensors. 2025; 25(7):2318. https://doi.org/10.3390/s25072318
Chicago/Turabian StyleSun, Bingyang, Shunsheng Yang, and Xu Cheng. 2025. "A Heavy Metal Ion Water Quality Detection Model Based on Spectral Analysis: New Methods for Enhancing Detection Speed and Visible Spectral Denoising" Sensors 25, no. 7: 2318. https://doi.org/10.3390/s25072318
APA StyleSun, B., Yang, S., & Cheng, X. (2025). A Heavy Metal Ion Water Quality Detection Model Based on Spectral Analysis: New Methods for Enhancing Detection Speed and Visible Spectral Denoising. Sensors, 25(7), 2318. https://doi.org/10.3390/s25072318