Signal Processing for Low-Energy Radiation Detection
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Solution Overview
Problem
Radiation detecting devices struggle to accurately detect low-energy radiation due to noise exceeding threshold values, leading to erroneous detection and inability to detect light elements with low-energy fluorescent X-rays.
Innovation Solution
A signal processing method utilizing a learning model, specifically a recurrent neural network, to determine the presence and wave height of pulse waves in radiation signals, allowing for the detection of low-energy radiation by normalizing and processing signal value sequences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a threshold value is set to prevent erroneous detection of noise, then false detection is reduced, but low-energy radiation with wave heights below the threshold cannot be detected
Solution Approach 1:
The patent applies preliminary action by performing wave height measurement on all detected pulses regardless of whether they exceed the threshold, and then performing element identification based on wave height ratios. This allows low-energy pulses that would normally be rejected to still contribute to detection through ratio-based analysis, resolving the contradiction between threshold-based reliability and low-energy detection precision
Solution Approach 2:
The patent changes the detection parameter from absolute wave height thresholding to relative wave height ratio analysis. By comparing wave heights of multiple pulses detected simultaneously, the system can identify elements based on characteristic energy ratios rather than requiring each pulse to individually exceed the threshold, enabling detection of low-energy radiation while maintaining reliability
2Reliability
If a high threshold value is used to filter noise, then false positive detections are prevented, but elements with low-energy fluorescent X-rays cannot be detected
Solution Approach 1:
The patent introduces wave height ratio as an intermediary parameter between raw pulse detection and element identification. Instead of directly thresholding individual pulses, the system uses ratios of wave heights from multiple pulses as a mediator to identify elements, allowing low-energy pulses to be detected through their characteristic ratio signatures rather than absolute amplitude
Solution Approach 2:
The patent applies partial action by measuring wave heights of all pulses including those below the threshold, and then selectively using ratio-based identification for low-energy cases. This partial measurement approach allows the system to capture low-energy signals that would otherwise be completely filtered out, while maintaining threshold-based noise rejection for high-energy signals
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 the detection of light elements with low-energy fluorescent X-rays by improving the accuracy of pulse wave detection and measurement, even for elements with atomic numbers smaller than oxygen, and simplifies the configuration of signal processing devices.
Implementation Method 1
A radiation detecting device that detects radiation such as X-rays includes a radiation detector and a signal processing device that processes a signal output by the radiation detector. The radiation detector is configured by using a semiconductor radiation detection element
Data Source
AI summary
A signal processing method counting step waves in response to detection of radiation or pulse waves obtained by converting the step waves by wave height, comprising: inputting signal value sequence in response to the detection of the radiation to a learning model outputting, when time-series signal value sequence is input, information related to presence or absence of the step wave or the pulse wave in a signal configured with the signal value sequence or information related to a wave height of the step wave or the pulse wave in the signal; and counting the step wave or the pulse wave by wave height according to the information output by the learning model.