Jittered Under-Sampling for High-Frequency Signal Estimation
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Solution Overview
Problem
Modern electronic circuit breakers and digital metering devices face challenges in achieving high sampling rates for accurate detection of high-frequency signals, due to constraints on CPU utilization and power consumption, which can lead to increased complexity and cost.
Innovation Solution
The implementation of randomly jittered under-sampling techniques allows for a reduced nominal sampling rate while still enabling accurate estimation of high-frequency signal amplitudes, thereby reducing the complexity and cost of digital signal processing systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a periodic sampling rate of 10 times higher than the highest frequency component is used to ensure accurate signal representation, then measurement precision is improved, but device complexity and power consumption increase significantly
Solution Approach 1:
The patent changes the sampling rate parameter from a fixed periodic rate (10×fc) to a reduced rate (fc/4) combined with random phase shifts. This parameter change allows accurate RMS and frequency estimation without requiring the traditionally high sampling rate, thereby reducing controller complexity and power consumption while maintaining measurement precision.
Solution Approach 2:
The patent introduces dynamic random phase shifts to the sampling process. Instead of using a static periodic sampling pattern, the sampling phase varies randomly according to a specified probability distribution. This dynamic approach enables accurate signal characterization at lower sampling rates by distributing sampling points across different phases over time, reducing the need for high-speed periodic sampling hardware.
2Measurement precision
If a periodic sampling rate of 500 kHz is implemented to meet high-frequency ground fault detection requirements, then measurement precision is improved, but power consumption increases
Solution Approach 1:
The patent reduces the sampling rate parameter from 500 kHz to 125 kHz (fc/4 where fc=50 kHz) and combines it with random phase shifts. This parameter change maintains the ability to detect high-frequency ground faults up to 50 kHz while reducing the power consumption associated with running the microcontroller at the higher sampling rate.
Solution Approach 2:
The patent employs dynamic random phase modulation in the sampling process. The random phase shifts ensure that over time, samples are distributed across all phases of the signal waveform, enabling accurate detection of high-frequency components even though the instantaneous sampling rate is lower. This dynamic approach reduces the continuous high-speed processing requirements that drive power consumption.
3Measurement precision
If a periodic sampling rate of 500 kHz is used to ensure accurate signal representation, then measurement precision is improved, but the nominal sampling rate and associated costs increase
Solution Approach 1:
The patent changes the sampling parameters from a high fixed rate (500 kHz) to a lower rate (125 kHz) with random phase variations. This parameter change reduces the nominal sampling rate requirement while maintaining measurement precision through the statistical distribution of samples across signal phases, thereby simplifying the overall sampling system.
Solution Approach 2:
The patent introduces dynamic random phase shifts to compensate for the reduced sampling rate. By varying the sampling phase randomly according to a specified probability distribution, the system achieves accurate signal characterization at lower nominal rates, reducing the complexity of the sampling hardware and associated components.
Data Source
AI summary
Methods/systems employ randomly jittered under-sampling to reduce a sampling rate required to estimate the amplitude of high-frequency signals in circuit breakers, power meters, and other digital signal processing applications. The methods/systems can greatly reduce the nominal sampling rate for applications where RMS, peak and mean estimates of the signal are desired for both the entire band-limited signal and separate estimates for each frequency component. This can in turn result in large cost savings, as less complex and thus less expensive controllers and related components may be used to perform the sampling. As well, the methods/systems herein can provide reasonably accurate waveform estimates that allow additional cost savings in bill of materials (BOM) and printed circuit board assembly (PCBA) footprint and real-estate by eliminating the need for certain analog components, such as signal conditioning components.