Frequency Measurement Device Multi-Stage Moving Average Filter Downsampling
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Solution Overview
Problem
Existing frequency measurement devices face challenges in reducing power consumption and noise generation due to the complexity of their low-pass filter structures, particularly in high-speed operations, which limits their sampling frequency and increases circuit size and power consumption.
Innovation Solution
A frequency measurement device with a simplified low-pass filter section using multiple-stage moving average filters, where the sampling frequencies decrease at each stage, and downsampling is performed to reduce aliasing noise without additional low-pass filters, allowing for a smaller circuit scale and lower power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a digital filter (moving average filter) is used in the low-pass filter section to achieve accurate real-time measurement, then measurement precision is improved, but device complexity and power consumption increase due to multiple-bit addition and subtraction operations requiring large-scale circuits
Solution Approach 1:
The filter section is divided into multiple stages, with each stage performing simplified filtering operations. The first stage uses a moving average filter with a smaller number of taps, and subsequent stages progressively reduce the sampling frequency and filtering complexity, thereby reducing the overall computational burden and circuit scale while maintaining measurement precision.
Solution Approach 2:
The filter section operates with periodic downsampling, where the sampling frequency is reduced at each stage. This periodic reduction in sampling rate allows the system to maintain accurate frequency measurement while significantly reducing the processing power required at later stages, thus lowering device complexity and power consumption.
2Productivity
If the sampling frequency is increased to achieve high-speed operation and improved time resolving power, then productivity is improved, but power consumption increases due to the processing power requirements of the filter section
Solution Approach 1:
The system employs periodic downsampling in the filter section, where the sampling frequency is maintained at high values in early stages for accurate time-resolved measurement, then progressively reduced in subsequent stages. This allows high-speed operation when needed while reducing power consumption during sustained operation, resolving the contradiction between productivity and energy use.
Solution Approach 2:
The filtering process is segmented into multiple stages with decreasing sampling frequencies. Early stages handle high-frequency components with higher sampling rates, while later stages process downsampled data at lower rates, thereby achieving high-speed measurement capability without sustaining high power consumption throughout the entire processing chain.
3Measurement precision
If additional low-pass filters are added to reduce aliasing noise during downsampling, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The moving average filter in the first stage performs preliminary filtering that inherently suppresses aliasing components before downsampling occurs in subsequent stages. This preliminary action eliminates the need for additional dedicated anti-aliasing filters, reducing device complexity while maintaining measurement precision through the progressive filtering and downsampling approach.
Data Source
AI summary
A frequency measurement device includes: a counter section that counts a supplied pulse stream signal to be measured at a predetermined time interval and outputs a stream of count values corresponding to the frequency of the signal to be measured; and a low-pass filter section that performs a filtering process on the stream of count values, the low-pass filter section including moving average filters in multiple stages, and an output of at least one moving average filter among the moving average filters in multiple stages is downsampled.