Electrical Signal Codec for Harmonic-Preserving Compression
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Solution Overview
Problem
Existing signal compression methods for electrical signals in energy management systems fail to retain high-order components necessary for inferring electrical load, leading to inefficient data transmission due to high data rates that exceed network constraints.
Innovation Solution
A method involving signal modeling to extract fundamental and harmonic frequency components, calculating an error signal, determining an optimal gain through iterative averaging, and vector quantizing residual signals to compress the signal, followed by decompression using a predefined codebook to reconstruct the primary signal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current compression methods minimizing mean square error are used, then the average error between original and reconstructed signal is reduced, but the high-order components necessary for load inference are removed
Solution Approach 1:
The patent segments the signal into distinct components: fundamental frequency, harmonic frequencies, and transient components. Each component is processed separately through specific compression techniques, allowing preservation of high-order harmonic components while compressing the overall signal. This segmentation enables selective retention of information critical for load inference.
Solution Approach 2:
Different compression strategies are applied to different parts of the signal based on their importance. The fundamental and harmonic components use one compression approach, while transient components use another. This local differentiation ensures that critical high-order components maintaining load information are preserved with higher fidelity than less important signal portions.
2Measurement precision
If high sampling rate is used to capture voltage and current waveforms for load inference, then the electrical load information is accurately captured, but the data rate becomes too large for network transmission
Solution Approach 1:
The patent extracts only the essential features from the high-rate signal: fundamental frequency, harmonic frequencies, and transient components. By taking out and separately encoding these key elements rather than transmitting the complete high-rate waveform, the data size is dramatically reduced while retaining sufficient information for accurate load inference.
Solution Approach 2:
The patent transforms the signal from time-domain high-rate samples to frequency-domain parameters (fundamental frequency, harmonics, transients). This parameter transformation reduces the data quantity while preserving the essential characteristics needed for load identification, enabling efficient network transmission without sacrificing inference accuracy.
Data Source
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AI summary
A method for compressing a signal, the method comprising: acquiring, via a signal recording module, a primary signal; modelling, via a processor, a model signal of the primary signal by: acquiring, via the processor, a sampled signal; acquiring, via the processor, a windowed signal; and extracting, via the processor: a fundamental frequency waveform having a fundamental magnitude and a fundamental phase; and at least one harmonic frequency waveform having a harmonic magnitude and a harmonic phase; wherein the model signal comprises the fundamental frequency waveform and the at least one harmonic frequency waveform; calculating, via the processor, an error signal between a reconstructed signal and the primary signal; determining, via the processor, an optimal gain from at least; an averaging step providing an average value, a predefined threshold, and a scaled signal, wherein the scaled signal is a historical error signal scaled by a predefined gain by iteratively: averaging a difference between the error signal and the scaled signal, wherein the optimal gain comprises the predefined gain when the average value meets the predefined threshold; determining, via the processor, an index from a residual signal by: determining the residual signal; vector quantising the residual signal; and indexing the vector quantised residual signal; composing, via the processor, a compressed signal, wherein the compressed signal comprises: the fundamental phase; the fundamental magnitude; the harmonic phase; the harmonic magnitude the optimal gain; the index. The compression method therefore preferably overcomes issues associated with current compression techniques, and provides a suitable technique for compressing a signal that may be used to infer the type of load on an electrical circuit.