Multi-Wavelength Water Quality Sensor with Spectral Calibration
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Solution Overview
Problem
Current methods for monitoring water quality in facilities, such as swimming pools, face challenges in consistently and accurately measuring turbidity and pollutant concentrations due to factors like algae growth and airborne pollutants, which can impact public health.
Innovation Solution
A system utilizing a combination of light sources, spectral detectors, and optical sensors to continuously measure turbidity and pollutant concentrations through fluorescence and scattering analysis, with an adjustable analysis model for real-time data processing and calibration, and acoustic transducers for water hardness testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional water quality monitoring methods are used, then the system is simple and easy to operate, but the measurement precision of turbidity and pollutant concentration is insufficient
Solution Approach 1:
The system segments the measurement process into multiple independent optical measurement channels, each dedicated to measuring specific water quality parameters (turbidity, algae concentration, chemical pollutants). Each channel uses specific wavelength light sources and corresponding detectors, allowing simultaneous multi-parameter measurement with high precision while maintaining modular system architecture that manages complexity.
Solution Approach 2:
The system transitions from single-parameter measurement to multi-dimensional spectral analysis by incorporating multiple light sources emitting at different wavelengths and using a spectrometer to analyze the spectral characteristics of transmitted and scattered light. This dimensional expansion in the spectral domain enables simultaneous detection of multiple pollutants and water quality parameters with high precision.
2Reliability
If traditional water quality monitoring methods are used, then the device is simple, but the reliability of continuous monitoring is insufficient
Solution Approach 1:
The system implements continuous monitoring by maintaining constant illumination of the water sample through multiple light sources and continuously detecting transmitted and scattered light. The automated data acquisition and processing system operates continuously, providing real-time water quality data without interruption, thereby ensuring reliable continuous monitoring capability.
Solution Approach 2:
The system incorporates feedback mechanisms where the detected optical signals (transmitted light intensity, scattered light spectrum) are continuously processed to determine water quality parameters. The system can detect system impairments and calibration drifts through the use of multiple light sources and reference measurements, providing feedback for automatic correction or alerting, thereby enhancing monitoring reliability.
3Measurement precision
If multiple light sources and spectral detectors are used, then the measurement precision and pollutant differentiation capability are improved, but the use of energy increases
Solution Approach 1:
The system uses multiple light sources emitting at different wavelengths, where each wavelength is optimized for detecting specific types of pollutants (e.g., UV for chemical pollutants, visible light for algae and turbidity). This multi-functional approach allows a single measurement system to detect multiple different pollutants simultaneously, improving detection precision while managing energy consumption by selecting appropriate wavelengths for each measurement task.
4Productivity
If automated data processing and analysis model adjustment are implemented, then the productivity of water quality assessment is improved, but the device complexity increases
Solution Approach 1:
The system implements automated data processing where the collected optical data is automatically processed through algorithms that calculate water quality parameters (turbidity, algae concentration, pollutant levels). The system can automatically adjust calibration parameters and detect system impairments without manual intervention, enabling rapid water quality assessment while managing complexity through automation of routine tasks.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables continuous, accurate monitoring of water quality by distinguishing between biological and chemical pollutants, improving detection precision and enabling timely interventions for maintaining public health safety.
Implementation Method 1
measuring water-quality related characteristics of water sampled from a water facility... using at least one spectral detector... directing light towards a sampled portion of the water to be tested/monitored... measuring light that is passed through the sampled water
Implementation Method 2
measuring light that is passed through the sampled water, where opacifying polluting particles/biomass, such as algae, may cause the sampled water to irradiate and/or scatter light of distinctive detectable optical characteristics (e.g. by causing water fluorescence)
Data Source
AI summary
Systems and Methods for monitoring characteristics of a water sample taken from a water facility (WF), by using a first light source emitting light at a first wavelength, and an additional light source, emitting light at an additional wavelength which is distinctly different from the first wavelength; for each light source, performing a measurement of the water sample, using an optical sensor outputting updated sensor data and a spectral detector, outputting updated detector data; and determining adjustment properties for adjustment of an analysis model, used for ongoing determination of water characteristics such as the water turbidity level, based on comparison between the measurements for each of the light sources.