Patent ID: 12212343

Referring toFIG.1, there is shown a schematic view of an energy management system100in a circuit101. The energy management system100comprises a signal recording module102, a data store104, a compression unit106, a transmitter108and a processor110. The data store104comprises a historic error signal105, a predefined gain107, a predefined threshold109and a codebook111. The codebook111comprises a number of indexes.

In use, and with reference toFIG.2, there is shown a compression method200for compressing a signal in accordance with the first aspect of the present invention.

At step202, the signal recording module102records a primary signal203. The primary signal may be a current or voltage signal corresponding to the circuit101.

At step204, the processor110samples the primary signal at the Nyquist rate, thereby creating a sampled signal205.

At step206, the processor110applies a hamming window to the sampled signal205, thereby creating a windowed signal207.

At step208, the processor110applies a Fast Fourier Transform to the windowed signal207, thereby creating a spectrum209of the windowed signal207.

At step210, the processor110extracts a fundamental signal and a first six harmonic signals from the spectrum209.

At step212, the processor110extracts a fundamental magnitude, a fundamental phase and a fundamental frequency from the fundamental signal of the spectrum209. The processor110further extracts a harmonic magnitude, a harmonic phase and a harmonic frequency from each of the six harmonic signals of the spectrum209. The fundamental magnitude, fundamental phase, harmonic magnitude and harmonic phase are stored in the data store104.

At step214, the processor110recreates a model signal215using the fundamental magnitude, the fundamental phase, the fundamental frequency, the harmonic magnitude, the harmonic phase, and the harmonic frequency.

At step216, the processor110subtracts the model signal215from the primary signal205, thereby creating an error signal217.

At step218, the processor110initiates an iterative process by multiplying the historic error signal105by the predefined gain107. The multiplication by the predefined gain107thereby creates a scaled signal219.

At step220, the processor110subtracts the scaled signal219from the error signal217. The subtractions of the scaled signal2019from the error signal217thereby creates a resulting signal221.

At step222, the processor110calculates the average value of the difference and compares the average value with the predefined threshold109.

At step224, if the average value meets the predefined threshold109, then step226does not occur and the predefined gain is output as an optimal gain225. If the average value does not meet the predefined threshold109, then step226occurs.

At step226, the predefined gain is adjusted to a new gain227using a stochastic descent algorithm and steps218to224are repeated with the predefined gain107being the new gain227.

At step228, the processor110subtracts the error signal217from the historical error signal105, thereby creating a residual signal229.

At step230, the processor110compares the residual signal229to the indexes in the codebook111in order to vector quantise the residual signal229as a number of residual indexes231.

At step232, the processor110composes a compressed signal233comprising the fundamental magnitude, the fundamental phase, the fundamental frequency, the harmonic magnitude, the harmonic phase, the harmonic frequency, the optimal gain225and the residual indexes231. It should be noted that the compressed signal233comprises the harmonic magnitude, the harmonic phase and the harmonic frequency of each of the six harmonic waveforms.

At step234, the transmitter108transmits the compressed signal233.

With reference toFIG.3, there is shown a schematic view of a decompression unit300.

The decompression unit300comprises a processor302, a receiver304and a data store306. The data store306comprises a codebook308and a historic residual signal312. The codebook308is substantially similar to the codebook111as described inFIG.1and comprises a number of indexes.

In use, and with reference toFIG.4, there is shown a schematic view of a decompression method400for decompressing the compressed signal233in accordance with the second aspect of the present invention.

At step402, receiver304receives the compressed signal233and stores the compressed signal233in the data store306. The compressed signal233comprises the fundamental magnitude, the fundamental phase, the fundamental frequency, the harmonic magnitude, the harmonic phase, the harmonic frequency, the optimal gain225and the residual indexes231.

At step404, the processor302compares the residual indexes231to the indexes in the codebook308and creates a reconstructed residual signal405based on the indexes that match the residual indexes231. The reconstructed residual signal405will be similar, but with some information lost, to the residual signal229.

At step406, the processor multiplies the historic residual signal312by the optimal gain225, thereby creating a scaled historic residual signal407.

At step408, the processor sums the reconstructed residual signal405with the scaled historic residual signal407, thereby creating a summed residual signal409.

At step410, the processor combines the fundamental magnitude, the fundamental phase, the fundamental frequency, thereby creating a fundamental sinusoidal signal411.

At step412, the processor combines the harmonic magnitude, the harmonic phase, and the harmonic frequency, thereby creating a harmonic sinusoidal signal413.

At step414, the processor sums the fundamental sinusoidal signal411with the harmonic sinusoidal signal413, thereby creating a sinusoidal signal415.

At step416, the processor sums the sinusoidal signal415with the summed residual signal409, thereby creating a decompressed signal417. The decompressed signal417is substantially similar to the primary signal203but with some information lost.

It will be appreciated that the above described embodiments are given by way of example only and that various modifications may be made to the described embodiments without departing from the scope of the invention as defined by the appended claims. For example, the primary signal may be current, voltage or any other circuit indicator. Further, there could be any number of harmonic signals extracted from the primary signal. Further, the primary signal may be sampled at any sampling rate and any windowing function may be applied to the sampled signal. Further, any suitable algorithm may be used to converge on an optimal gain value.