Oscilloscope Decimation Unit RMS Calculation
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Solution Overview
Problem
Existing digital oscilloscopes face challenges in precisely displaying the effective value of periodic signals due to limitations in memory and processing capabilities, especially when dealing with large ranges of time bases and high sampling rates, leading to inefficient decimation methods that fail to accurately represent the signal.
Innovation Solution
A measuring device and method that utilize a decimation unit to calculate a reduced data stream based on the root-mean-square value of sampled values, allowing for precise display of the effective value of periodic signals by selectively processing and storing only the necessary data, which includes an optional consideration of offset values and parallel processing across multiple channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the full sampling rate of the analog-to-digital converter is used for recording, then the measurement precision and signal integrity are improved, but the memory requirements and processing complexity increase disproportionately
Solution Approach 1:
The patent applies segmentation by dividing the data stream processing into multiple stages: initial decimation to reduce data volume, followed by selective RMS calculation for specific time segments. This allows the system to process high-rate signals by breaking them into manageable chunks, maintaining measurement precision while reducing overall memory and processing requirements
Solution Approach 2:
The patent extracts only the essential information needed for effective value calculation by performing RMS computation on decimated data segments rather than processing all raw samples. This extraction approach removes unnecessary data while preserving the critical signal characteristics needed for accurate measurement
2Device complexity
If data decimation is applied to reduce memory requirements, then the device complexity is reduced, but the ability to accurately calculate effective values deteriorates
Solution Approach 1:
The patent performs preliminary decimation of the data stream before RMS calculation to reduce memory requirements. By pre-processing the data to retain only essential sampling points, the system prepares the data in a form that enables accurate effective value calculation with reduced storage needs
Solution Approach 2:
The patent changes the parameter representation by calculating RMS values from decimated samples rather than storing all raw samples. This parameter transformation allows the system to maintain effective value accuracy while significantly reducing memory requirements through mathematical consolidation of multiple samples into single RMS values
3Adaptability or versatility
If the time base is extended to cover larger time ranges, then the versatility of the oscilloscope is improved, but the amount of data to be processed increases
Solution Approach 1:
The patent implements dynamic data processing by adjusting the decimation factor and RMS calculation parameters based on the selected time base range. When larger time ranges are selected, the system automatically increases decimation to maintain processing efficiency, while for shorter time bases it uses lower decimation to preserve detail, thus adapting to different measurement scenarios
Solution Approach 2:
The patent changes processing parameters dynamically based on time base settings. The decimation factor and block size for RMS calculation are adjusted according to the selected time range, allowing the system to maintain optimal processing efficiency across the full versatility of time base options from 20 ps/div to 50 s/div
Data Source
AI summary
A measuring apparatus (1) for an oscilloscope has a decimation unit (2). The decimation unit (2) has at least one input which receives from at least one data source (4) a data stream (5) having a multiplicity of samples. The decimation unit (2) likewise has at least one output at which a reduced data stream (11) is output. The reduced data stream (11) is formed from a root mean square comprising at least two samples in each case which is calculated by the decimation unit (2).