Magnetic Resonance Apparatus Adaptive Sampling ADC
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Solution Overview
Problem
Magnetic resonance measurement apparatuses face challenges in selecting an appropriate sampling scheme, as existing technologies cannot switch between over-sampling and under-sampling based on the signal frequency, leading to inefficient signal processing and limited resolution.
Innovation Solution
A magnetic resonance measurement apparatus with an analog-to-digital converter circuit that adapts its sampling scheme based on the signal frequency, using a frequency converter circuit to convert RF signals to intermediate frequency signals when necessary, allowing for over-sampling or under-sampling depending on the observation nucleus frequency, and a signal processor to handle the target or aliased signal components accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If over-sampling is used to maintain high resolution, then measurement precision is improved, but device cost and complexity increase due to requiring expensive high-frequency ADCs
Solution Approach 1:
The patent changes the sampling frequency parameter dynamically based on the signal frequency. When the signal frequency is low enough to satisfy the under-sampling condition (fs > 2*|f_signal - k*fs|), a lower sampling frequency is used. When the signal frequency is high, over-sampling is employed. This parameter adaptation allows using less expensive ADCs while maintaining measurement precision through appropriate signal processing.
Solution Approach 2:
The system dynamically switches between over-sampling and under-sampling modes based on the relationship between signal frequency and sampling frequency. The control unit determines which sampling mode to use and adjusts the sampling frequency accordingly, making the ADC operation flexible and adaptable to different signal conditions rather than requiring a fixed high sampling rate.
2Measurement precision
If a fixed high sampling frequency is used, then measurement precision is maintained, but productivity decreases due to increased data processing load
Solution Approach 1:
The sampling frequency parameter is changed based on signal characteristics. By using under-sampling when applicable (lower fs), the data rate is reduced, decreasing the processing load on subsequent stages while maintaining sufficient precision through the aliased signal processing methodology described in the patent.
3Device complexity
If under-sampling is used to reduce ADC requirements, then device cost decreases, but measurement precision deteriorates due to aliasing effects
Solution Approach 1:
The patent converts the harmful aliasing effect into a beneficial measurement technique. Instead of treating aliasing as noise to be eliminated, the system deliberately uses under-sampling to create controlled aliasing, then processes the aliased signal components through specific signal processing steps (including phase correction and frequency shifting) to recover the original signal information accurately.
Solution Approach 2:
The system incorporates feedback mechanisms where the control unit monitors the sampling conditions and adjusts the sampling frequency and signal processing parameters accordingly. The measured signal characteristics are used to determine the appropriate sampling mode, and the processing parameters are adjusted based on the observed aliasing patterns to maintain precision.
4Productivity
If the sampling frequency is reduced, then productivity improves due to lower data rates, but measurement precision worsens when the Nyquist criterion is violated
Solution Approach 1:
The patent changes the sampling frequency parameter to optimize the balance between productivity and precision. By using under-sampling with deliberately chosen frequencies that satisfy specific conditions (fs > 2*|f_signal - k*fs|), the system reduces data rates while maintaining measurement capability through advanced signal processing of the aliased components.
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 flexible and efficient sampling by selecting the appropriate scheme without changing the sampling clock, improving signal processing precision and reducing costs by using less expensive ADCs, while maintaining high resolution.
Implementation Method 1
a frequency converter circuit is provided upstream of the analog-to-digital converter circuit, the frequency converter circuit being arranged to convert the RF reception signal into an intermediate frequency signal when a frequency determined according to an observation nucleus falls within a high frequency band
Implementation Method 2
an analog-to-digital converter circuit to which an analog reception signal including a target signal component having a first frequency can be input, arranged to sample the analog reception signal at a sampling frequency which is a second frequency
Data Source
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AI summary
In a magnetic resonance measurement apparatus such as an NMR measurement apparatus, when a frequency of an observation nucleus falls within a high frequency band, an RF reception signal is converted into an intermediate frequency signal, and is input to an analog-to-digital converter. In this case, under-sampling is executed for the intermediate frequency signal in the analog-to-digital converter, and a second-order aliased signal component generated from a target signal component is observed. On the other hand, when the frequency of the observation nucleus falls within a low frequency band, the RF reception signal is input to the analog-to-digital converter without being processed, over-sampling for the RF reception signal is executed, and the target signal component itself is observed.