Automatic Analyzer Scattered Light Noise Correction
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Solution Overview
Problem
Automatic analyzers using scattered light face challenges in distinguishing noise components from air bubbles, foreign matters, and particle fluctuations, which interfere with measurement accuracy and signal-to-noise ratio.
Innovation Solution
The analyzer employs multiple detectors positioned at different angles to capture scattered light, using polynomial approximation to establish a virtual baseline and correct noise components, thereby improving the signal-to-noise ratio by separating the light signals from noise sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If scattered light measurement is used to improve sensitivity, then measurement sensitivity is improved, but noise components from air bubbles, foreign matters, and particle fluctuations increase
Solution Approach 1:
The scattered light measurement is divided into multiple detection channels with different detectors positioned at different angles. By segmenting the measurement into multiple components, the system can identify and separate noise signals from valid measurement signals, reducing the impact of air bubbles, foreign matters, and particle fluctuations while maintaining sensitivity.
Solution Approach 2:
The system uses multiple detectors to continuously monitor scattered light from different angles and feeds this information back to the control unit. The control unit analyzes the signals from all detectors and uses this feedback to identify noise components and correct measurements in real-time, thereby reducing noise impact while preserving measurement sensitivity.
2Measurement precision
If integration time is increased to improve S/N ratio, then S/N ratio properties are improved, but temporal changes in the object to be measured cause measurement errors
Solution Approach 1:
Instead of using a single long integration period, the measurement is segmented into multiple shorter integration periods with multiple detectors operating simultaneously. This allows the system to achieve equivalent noise reduction through spatial diversity rather than temporal integration, avoiding errors from temporal changes in the sample.
Solution Approach 2:
The system transitions from temporal integration (integrating over time) to spatial integration (using multiple detectors at different angles). By adding the spatial dimension to the measurement, the system achieves improved S/N ratio without extending the measurement time, thereby avoiding errors from temporal changes in the object being measured.
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
This approach effectively reduces the influence of noise components, enhancing the accuracy of concentration calculations and improving the signal-to-noise ratio in light reception signals.
Implementation Method 1
the quantity of transmitted light, which is obtained by the irradiation, and has a single wavelength or a plurality of wavelengths, is measured to calculate absorbance; and the amount of ingredients is estimated from the relationship between the absorbance and the concentration according to the Lambert-Beer law
Implementation Method 2
the sensitivities of devices are also improved not by measuring the quantity of transmitted light, but by measuring the quantity of scattered light
Data Source
Figure 1~3
Figure 4A~4B
Figure 5~6(i)
AI summary
Disclosed is an automatic analyzer which is capable of reducing the influence of scattered light having noise components other than an object to be measured, and is capable of improving the S/N ratio properties of a light reception signal. Data is obtained at a plurality of angles by a plurality of detectors (204 to 206). A signal obtained by one detector selected from among the detectors is selected as a reference signal by a detected data selection unit (18a). An approximation to be applied is selected by an approximation selection unit (18b1) of a first selected data processing unit (18b), and an approximation calculation unit (18b2) calculates an approximation using the selected approximation. A degree of variability of the reference signal is determined by a degree-of-variability calculation unit (18b3). A signal of the detector (205) is held by a second selected data processing unit (18c), and a data correction unit (18d) corrects the signal of the detector (205) by dividing the signal of the detector (205) by the degree of variability of the reference signal. A concentration calculation processing unit (18e) performs the concentration calculation by use of the corrected signal data, and a result output unit (18f) outputs the results on a CRT or the like.