Electrical Signal Codec Preserving Harmonics for Load Inference
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Solution Overview
Problem
Current signal compression methods, such as those minimizing mean square error, remove high-order components of electrical signals, which are essential for inferring electrical loads, making them unsuitable for energy management systems that require high data integrity.
Innovation Solution
A method that compresses electrical signals by extracting fundamental and harmonic frequency waveforms, calculating an error signal, determining an optimal gain through iterative averaging, and vector quantizing the residual signal, allowing for efficient transmission while preserving information necessary for load inference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If current compression methods minimizing mean square error are used, then data size is reduced, but high-order components essential for load inference are removed
Solution Approach 1:
The patent segments the signal into distinct frequency components (fundamental and harmonic frequencies) using Fourier transform. This segmentation allows selective preservation of high-order harmonic components that contain load inference information while compressing the overall data representation.
Solution Approach 2:
The patent changes the representation parameters from time-domain sampling to frequency-domain coefficients. By transforming the signal into frequency components and selecting only the most significant ones for transmission, the patent achieves compression while preserving the essential high-order information needed for load inference.
2Measurement precision
If high sampling rate is used to capture electrical load information, then load inference accuracy is improved, but data rate becomes too large for constrained networks
Solution Approach 1:
The patent extracts only the essential frequency components (fundamental and selected harmonics) from the full signal spectrum. This extraction process removes redundant information while retaining the critical high-order components necessary for accurate load inference, enabling transmission at lower data rates.
Solution Approach 2:
Instead of transmitting the complete high-rate sampled signal, the patent transmits a partial representation containing only the most significant frequency components. This partial action approach provides sufficient information for load inference while dramatically reducing the data rate for network transmission.
Data Source
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.