Electricity meter and associated method

Abstract

A power meter for measuring one or more characteristics of electrical inputs associated with a power supply comprises a first analog-to-digital converter (ADC), a second ADC, and a processing resource. The first ADC is configured to receive an ADC input signal representing an electrical input and to generate a first ADC output data sequence from the ADC input signal representing an electrical input over a predetermined time period. The second ADC is configured to receive an ADC input signal representing an electrical input and to generate a second ADC output data sequence from the ADC input signal representing an electrical input over a time period. The processing resource is configured to determine a cross-correlated average data sequence corresponding to a time period based on the first and second ADC output data sequences and to determine one or more characteristics of the electrical input over the time period based on the cross-correlated average data sequence corresponding to the time period.

Description

Technical Field

[0001] The present disclosure relates to a power meter and an associated method for measuring one or more characteristics of an electrical input associated with a power supply, and more particularly, but without exclusion of others, to a power meter and an associated method for measuring one or more characteristics of alternating current, alternating voltage, or alternating power, such as alternating current, alternating voltage, or alternating power associated with a particular phase of a polyphase power supply.

Background Art

[0002] It is known to use a power meter to sample a voltage signal representing an alternating current and thereby generate an output data sequence over a predetermined time period, and to determine one or more characteristics of the alternating current over the time period based on the output data sequence, thereby measuring one or more characteristics of an electrical input such as an alternating current associated with a particular phase of a polyphase power supply.

Summary of the Invention

Problems to be Solved by the Invention

[0003] However, the generated output data sequence may contain noise as a result of the sampling operation, thereby resulting in a signal-to-noise ratio (SNR) that is too high in some applications, particularly when the alternating current is small. This can lead to a lack of accuracy in the measured values of one or more characteristics of the alternating current, thereby resulting in a lack of measurement reproducibility and / or a limited dynamic range.

Means for Solving the Problems

[0004] According to one aspect of the present disclosure, there is provided a power meter for measuring one or more characteristics of an electrical input associated with a power supply. The power meter is A first ADC configured to receive an ADC input signal representing an electrical input and to generate a first ADC output data sequence representing an electrical input over a predetermined time period from the ADC input signal, A second ADC is configured to receive an ADC input signal representing an electrical input and to generate a second ADC output data sequence representing an electrical input over a period of time from the ADC input signal. The system includes a processing resource configured to determine a cross-correlated average data sequence corresponding to a time period based on first and second ADC output data sequences, and to determine one or more characteristics of an electrical input over a time period based on the cross-correlated average data sequence corresponding to the time period.

[0005] Determining a cross-correlated averaged data sequence corresponding to a time period based on the first and second ADC output data sequences, and determining one or more characteristics of the electrical input over a time period based on the cross-correlated averaged data sequence corresponding to the time period, may act to cancel out or at least reduce any uncorrelated noise present with the first and second ADC output data sequences. Such uncorrelated noise may be thermal, or it may originate from the sample and persist across multiple stages of the first and second ADCs. Theoretically, using the first and second ADCs with cross-correlated averaging in this manner may result in canceling out up to half of the noise present in each of the first and second ADC output data sequences. In practice, this may improve the accuracy with which the electrical input can be measured, and / or improve the reproducibility of the measurement of the electrical input by up to a factor of 2. This may also result in an increase in the dynamic range of the power meter. Any harmonic distortion correlated with the electrical input may remain unaffected by the cross-correlated averaging.

[0006] Optionally, based on the first and second ADC output data sequences, a cross-correlated average data sequence corresponding to a time period can be determined. The method involves generating a product data sequence by temporally reversing the data order of the first ADC output data sequence and multiplying the temporally reversed first ADC output data sequence by the second ADC output data sequence, or by temporally reversing the data order of the second ADC output data sequence and multiplying the temporally reversed second ADC output data sequence by the first ADC output data sequence. This includes determining the square root of the data in the product data sequence.

[0007] Optionally, based on the first and second ADC output data sequences, a cross-correlated average data sequence corresponding to a time period can be determined. The first and second adjusted data sequences are generated by performing one or more adjustment operations on the first and second ADC output data sequences, respectively. Generate an integrated data sequence by temporally reversing the data order of the first integrated data sequence and multiplying the temporally reversed first integrated data sequence by the second integrated data sequence, or generate an integrated data sequence by temporally reversing the data order of the second integrated data sequence and multiplying the temporally reversed second integrated data sequence by the first integrated data sequence. This includes determining the square root of the data in the product data sequence.

[0008] Optionally, one or more adjustment operations include calibration adjustment operations and / or resampling operations.

[0009] Optionally, the calibration adjustment operation includes adjusting the first and second ADC output data sequences according to calibration data measured by a power meter for one or more known electrical inputs having corresponding known amplitudes, corresponding known frequencies, and corresponding known phases, respectively.

[0010] Optionally, the resampling operation includes one or more of the following: interpolation, image removal filtering, anti-aliasing filtering, and decimation.

[0011] Optionally, determining one or more characteristics of an electrical input over a time period includes determining one or more of the amplitude, frequency, and phase of the electrical input over a time period based on a cross-correlated average data sequence corresponding to the time period.

[0012] Optionally, determining one or more characteristics of the electrical input over a period of time is possible. By performing one or more adjustment operations on a cross-correlated mean data sequence corresponding to a time period, an adjusted cross-correlated mean data sequence is generated. This includes determining one or more characteristics of an electrical input over a time period based on a coordinated, cross-correlated, averaged data sequence corresponding to the time period.

[0013] Optionally, generating an adjusted cross-correlated averaged data sequence by performing one or more adjustment operations on the cross-correlated averaged data sequence corresponding to a time period includes using the zero crossing of the AC current as the phase reference for the cross-correlated averaged data sequence.

[0014] Optionally, using the zero crossing of the AC current as the phase reference for the cross-correlated averaged data sequence involves performing a phase-locked loop (PLL) operation followed by a fast Fourier transform (FFT) operation.

[0015] Optionally, determining one or more characteristics of an electrical input over a time period includes determining one or more of the amplitude, frequency, and phase of the electrical input over a time period based on a coordinated, cross-correlated, averaged data sequence corresponding to the time period.

[0016] Optionally, the power meter is configured to generate an ADC input signal based on an electrical input.

[0017] Optionally, the power meter includes a transformer, Generating an ADC input signal based on an electrical input includes using the transformer to convert the electrical input into a converted electrical input.

[0018] Optionally, the transformer includes a current step-down transformer. Optionally, the current step-down transformer has a turns ratio in the range of 1:100 to 1:10000, 1:1000 to 1:3000, approximately 1:2000, or 1:2000.

[0019] Optionally, the power meter includes a voltage divider.

[0020] Optionally, generating an ADC input signal based on an electrical input includes generating a voltage signal by passing the electrical input or the converted electrical input through the voltage divider, or generating a voltage signal by applying the electrical input or the converted electrical input to the voltage divider.

[0021] Optionally, the voltage divider includes a plurality of resistors connected in series.

[0022] Optionally, the ADC input signal includes a voltage signal.

[0023] Optionally, the power meter includes an anti-aliasing filter.

[0024] Optionally, generating an ADC input signal based on an electrical input includes filtering the voltage signal using the anti-aliasing filter.

[0025] Optionally, the ADC input signal includes a filtered voltage signal.

[0026] Optionally, the time period corresponds to one or more line cycles of the AC current. Shorter time periods corresponding to fewer line cycles allow the electrical input to be measured with higher resolution with respect to each line cycle, while longer time periods corresponding to more line cycles will allow for further improvement of the signal-to-noise ratio by performing further averaging.

[0027] Optionally, the electrical input includes AC electrical input.

[0028] Optionally, electrical inputs include input voltage, input current, or input power.

[0029] Optionally, the electrical input may include AC voltage, AC current, or AC power.

[0030] Optionally, the electrical input is associated with one phase of a multiphase power supply.

[0031] Optionally, the power meter is configured to measure one or more characteristics of each of the multiple electrical inputs.

[0032] Optionally, each electrical input may include voltage, such as AC voltage; current, such as AC current; or power, such as AC power.

[0033] Optionally, each electrical input can be associated with a different phase of a multiphase power supply.

[0034] According to one aspect of this disclosure, a method is provided for measuring one or more characteristics of electrical inputs associated with a power supply. This method is In the first ADC, an ADC input signal representing an electrical input is received, and the first ADC is used to generate a first ADC output data sequence representing an electrical input over a predetermined time period from the ADC input signal. In the second ADC, an ADC input signal representing the electrical input is received, and the second ADC is used to generate a second ADC output data sequence representing the electrical input over a time period from the ADC input signal. Based on the first and second ADC output data sequences, a cross-correlated average data sequence corresponding to a time period is determined, This includes determining one or more characteristics of an electrical input over a time period based on a cross-correlated average data sequence corresponding to the time period.

[0035] Optionally, based on the first and second ADC output data sequences, a cross-correlated average data sequence corresponding to a time period can be determined. The method involves generating a product data sequence by temporally reversing the data order of the first ADC output data sequence and multiplying the temporally reversed first ADC output data sequence by the second ADC output data sequence, or by temporally reversing the data order of the second ADC output data sequence and multiplying the temporally reversed second ADC output data sequence by the first ADC output data sequence. This includes determining the square root of the data in the product data sequence.

[0036] Optionally, based on the first and second ADC output data sequences, a cross-correlated average data sequence corresponding to a time period can be determined. The first and second adjusted data sequences are generated by performing one or more adjustment operations on the first and second ADC output data sequences, respectively. Generate an integrated data sequence by temporally reversing the data order of the first integrated data sequence and multiplying the temporally reversed first integrated data sequence by the second integrated data sequence, or generate an integrated data sequence by temporally reversing the data order of the second integrated data sequence and multiplying the temporally reversed second integrated data sequence by the first integrated data sequence. This includes determining the square root of the data in the product data sequence.

[0037] Optionally, one or more adjustment operations include calibration adjustment operations and / or resampling operations.

[0038] Optionally, the first and second ADC output data sequences are adjusted according to calibration data measured by a power meter for one or more known electrical inputs having corresponding known amplitudes, corresponding known frequencies, and corresponding known phases, respectively.

[0039] Optionally, the resampling operation includes one or more of the following: interpolation, image removal filtering, anti-aliasing filtering, and decimation.

[0040] Optionally, determining one or more characteristics of an electrical input over a time period based on a cross-correlated average data sequence corresponding to the time period is possible. By performing one or more adjustment operations on a cross-correlated mean data sequence corresponding to a time period, an adjusted cross-correlated mean data sequence is generated. This includes determining one or more characteristics of an electrical input over a time period based on a coordinated, cross-correlated, averaged data sequence corresponding to the time period.

[0041] Optionally, generating an adjusted cross-correlated averaged data sequence by performing one or more adjustment operations on the cross-correlated averaged data sequence corresponding to a time period includes using the zero crossing of the electrical input as the phase reference for the cross-correlated averaged data sequence.

[0042] Optionally, using the zero crossing of the electrical input as the phase reference for the cross-correlated mean data sequence involves performing a phase-locked loop (PLL) operation followed by a fast Fourier transform (FFT) operation.

[0043] Optionally, determining one or more characteristics of an electrical input over a time period includes determining one or more of the amplitude, frequency, and phase of the electrical input over a time period based on a coordinated, cross-correlated, averaged data sequence corresponding to the time period.

[0044] Optionally, the electrical input includes AC electrical input.

[0045] Optionally, electrical inputs include input voltage, input current, or input power.

[0046] Optionally, the electrical input may include AC voltage, AC current, or AC power.

[0047] Optionally, the electrical input is associated with one phase of a multiphase power supply.

[0048] Optionally, the power meter is configured to measure one or more characteristics of each of the multiple electrical inputs.

[0049] Optionally, each electrical input may include voltage, such as AC voltage; current, such as AC current; or power, such as AC power.

[0050] Optionally, each electrical input can be associated with a different phase of a multiphase power supply.

[0051] It should be understood that one or more of the optional features relating to any one of the prior aspects of this disclosure may be combined with one or more of the other prior aspects of this disclosure, or with one or more of the optional features relating to any one or more of the other prior aspects of this disclosure. [Brief explanation of the drawing]

[0052] [Figure 1] This is a schematic diagram of the first power meter. [Figure 2] This is a schematic diagram of the second electricity meter. [Modes for carrying out the invention]

[0053] Here, a power meter and associated method for measuring one or more characteristics of electrical inputs associated with a power supply are described only as non-limiting embodiments with reference to the drawings.

[0054] Referring first to Figure 1, a first power meter, generally represented as 2, is shown for measuring one or more characteristics 4 of an electrical input associated with a power source, having the form of an alternating current 6. The power meter 2 comprises a voltage divider having the form of a plurality of series-connected load resistors 8, first and second analog-to-digital converters (ADCs) having the form of first and second delta-sigma ADCs 10a, 10b, respectively, and a processing resource having the form of a microprocessor 12. The alternating current 6 may be a phase N load current, and one or more characteristics 4 of the alternating current 6 may be one or more energy meters for measurement.

[0055] The first and second ADCs 10a and 10b are each configured to receive an ADC input signal having the form of a voltage signal 18 that represents the current 6 flowing through the load resistor 8. The first and second ADCs 10a and 10b are each configured to generate first and second ADC output data sequences 20a and 20b, respectively, that represent the current 6 flowing through the load resistor 8 over a predetermined time period, such as one or more line cycles of the alternating current 6. The microprocessor 12 is configured to determine a cross-correlated averaged data sequence 40 corresponding to the time period by performing a cross-correlated averaging operation 30 of the first and second ADC output data sequences 20a and 20b. Those skilled in the art will understand that the cross-correlated averaged data sequence 40 corresponding to the time period can be considered to constitute a phase N current vector output 40 corresponding to the phase N load current 6 over the time period. Based on the phase N current vector output 40, the microprocessor 12 is configured to determine one or more characteristics 4 of the phase N load current 40 over the time period. For example, the microprocessor 12 may be configured to determine one or more of the amplitude, frequency, and phase of the phase N current vector output 40 over a period of time.

[0056] During use, the alternating current 6 passes through the load resistor 8, generating a voltage signal 18 representing the current 6. The first ADC 10a receives the voltage signal 18 and generates a first ADC output data sequence 20a representing the current 6 over a period of time. The second ADC 10b also receives the voltage signal 18 and generates a second ADC output data sequence 20b representing the current 6 over a period of time. The microprocessor 12 determines one or more characteristics of the current 4 over a period of time based on the first and second ADC output data sequences 20a and 20b. Specifically, the microprocessor 12 determines the phase N current vector output 40 corresponding to the period of time by performing a cross-correlated averaging operation 30 on the first and second ADC output data sequences 20a and 20b to generate a cross-correlated averaged data sequence 40 corresponding to the period of time, and then by determining one or more characteristics of the cross-correlated averaged data sequence 40 to generate one or more energy meters 4 for measurement. The microprocessor 12 determines the cross-correlated average data sequence 40 corresponding to a time period based on the first and second ADC output data sequences 20a and 20b by: reversing the order of the data in the first ADC output data sequence 20a in time; multiplying the reversed first ADC output data sequence by the second ADC output data sequence 20b to generate a product data sequence; and determining the square root of the data in the product data sequence to determine the cross-correlated average data sequence 40.

[0057] Thus, determining the phase N current vector output 40 corresponding to a time period by determining a cross-correlated averaged data sequence corresponding to a time period based on the first and second ADC output data sequences 20a, 20b, and then determining one or more characteristics of the phase N current vector output 40 to generate one or more energy meters 4 for measurement, acts to cancel out or at least reduce any uncorrelated noise contained in the first and second ADC output data sequences 20a, 20b. Such uncorrelated noise is generally thermal and originates from the sample-and-hold stages of the first and second delta-sigma ADCs 10a, 10b. Those skilled in the art will understand that the cross-correlated averaging operation 30 is analogous to a matched filter operation that removes uncorrelated noise present in the first and second ADC output data sequences 20a, 20b. Theoretically, using the cross-correlated averaging operation 30 with the first and second ADCs 10a, 10b can result in canceling out up to half of the noise contained in the first and second ADC output data sequences 20a, 20b. In fact, this can result in improved measurement accuracy of the phase N current vector output 40 and improved measurement repeatability of the phase N current vector output 40 by up to a factor of 2. This also results in an increased dynamic range of the power meter 2. Any harmonic distortion correlated with the phase N load current 6 at 50 or 60 Hz remains unaffected by the cross-correlated averaging operation 30.

[0058] Referring here to Figure 2, a second power meter, generally represented as 102, is shown for measuring one or more characteristics 104 of an AC current 106, the power meter 102 comprising a current step-down transformer 107, a voltage divider having in the form of a plurality of series-connected load resistors 108, an anti-aliasing filter 109, first and second analog-to-digital converters (ADCs) having in the form of first and second delta-sigma ADCs 110a, 110b, respectively, and a processing resource having in the form of a microprocessor 112. The AC current 106 may be a phase N load current, and one or more characteristics 104 of the AC current 106 may be one or more energy meters for measurement. The current step-down transformer 107 may have a turns ratio of 1:2000.

[0059] The first and second ADCs 110a and 110b are each configured to receive an ADC input signal having the form of a voltage signal 119 at the output of the anti-aliasing filter 109. The voltage signal 119 represents a current 106. The first and second ADCs 110a and 110b are each configured to generate first and second ADC output data sequences 120a and 120b, respectively, representing the current 106 over a predetermined time period, such as one or more line cycles of the AC current 106.

[0060] The microprocessor 112 is configured to generate the first and second adjusted data sequences 126a and 126b, respectively, by performing one or more adjustment operations on the first and second ADC output data sequences 120a and 120b. Specifically, the microprocessor 112 is configured to generate the first and second adjusted data sequences 126a and 126b, respectively, from the first and second ADC output data sequences 120a and 120b by performing a calibration adjustment operation 122 and then a resampling operation 124. The calibration adjustment operation 122 may include adjusting the first and second ADC output data sequences 120a and 120b according to calibration data measured by the power meter 102 with respect to one or more known AC currents having corresponding known amplitudes, corresponding known frequencies, and corresponding known phases, respectively. The resampling operation 124 may include the use of one or more of interpolation, image removal filters, anti-aliasing filters, and decimation.

[0061] The microprocessor 112 is further configured to generate a cross-correlated averaged data sequence 132 corresponding to a time period by performing a cross-correlated averaging operation 130 of the first and second coordinated data sequences 126a, 126b.

[0062] The microprocessor 112 is further configured to generate a tuned cross-correlated averaged data sequence 140 by performing one or more tuning operations on the cross-correlated averaged data sequence 132 corresponding to a time period. Specifically, the microprocessor 112 is configured to generate the tuned cross-correlated averaged data sequence 140 by performing a phase-locked loop (PLL) operation 134 and then a fast Fourier transform (FFT) operation 136, thereby using the zero crossing of the alternating current 106 as the phase reference for the cross-correlated averaged data sequence 132.

[0063] Those skilled in the art will understand that a coordinated, cross-correlated averaged data sequence 140 corresponding to a time period can be considered to constitute a phase-N current vector output 140 corresponding to a phase-N load current 106 over the time period. The microprocessor 112 is configured to determine one or more characteristics 104 of the phase-N load current 140 over the time period from the phase-N current vector output 140. For example, the microprocessor 112 may be configured to determine one or more of the amplitude, frequency, and phase of the phase-N current vector output 140 over the time period.

[0064] During use, the alternating current 106 constitutes the primary alternating current of the current transformer 107. The current transformer 107 converts the alternating current 106 into a secondary alternating current, which, by passing through the load resistor 108, generates an initial voltage signal 118. The initial voltage signal 118 is applied to the input of the anti-aliasing filter 109 to generate a voltage signal 119 representing the current 106.

[0065] The first ADC 110a receives a voltage signal 119 and generates a first ADC output data sequence 120a representing a current 106 over a time period. The second ADC 110b also receives a voltage signal 119 and generates a second ADC output data sequence 120b representing a current 106 over a time period. The microprocessor 112 determines one or more characteristics of the current 104 over a time period based on the first and second ADC output data sequences 120a and 120b. Specifically, the microprocessor 112 performs a calibration adjustment operation 122 on the first and second ADC output data sequences 120a and 120b, and then performs a resampling operation 124 to generate the first and second adjusted data sequences 126a and 126b, respectively.

[0066] The microprocessor 112 then generates a cross-correlated averaged data sequence 132 by performing a cross-correlated averaging operation 130 on the first and second adjusted data sequences 126a and 126b, respectively. More specifically, the microprocessor 112 determines the cross-correlated averaged data sequence 132 corresponding to a time period based on the first and second adjusted data sequences 126a and 126b by reversing the order of the data in the first adjusted data sequence 126a in time, multiplying the time-reversed first adjusted data sequence by the second adjusted data sequence 126b to generate a product data sequence, and determining the square root of the data in the product data sequence to determine the cross-correlated averaged data sequence 132.

[0067] The microprocessor 112 performs a PLL operation 134 on a cross-correlated averaged data sequence 132 corresponding to a time period, and then performs an FFT operation 136 to generate a phase N current vector output corresponding to the phase N load current 106 over the time period. The microprocessor 112 generates one or more energy meters 104 for measurement by determining one or more characteristics of the phase N current vector output 140.

[0068] Thus, determining the phase N current vector output 140 corresponding to a time period by determining the cross-correlated averaged data sequence corresponding to a time period based on the first and second ADC output data sequences 120a, 120b, and then determining one or more characteristics of the phase N current vector output 140 to generate one or more energy meters 104 for measurement, acts to cancel out or at least reduce any uncorrelated noise contained in the first and second ADC output data sequences 120a, 120b. Such uncorrelated noise is generally thermal and originates from the sample-and-hold stages of the first and second delta-sigma ADCs 110a, 110b. Those skilled in the art will understand that the cross-correlated averaging operation 130 is analogous to a matched filter operation that removes uncorrelated noise present in the first and second ADC output data sequences 120a, 120b. Theoretically, using the cross-correlated averaging operation 130 with the first and second ADCs 110a, 110b can result in canceling out up to half of the noise contained in the first and second ADC output data sequences 120a, 120b. In fact, this can result in improved measurement accuracy of the phase-N current vector output 140 and improved measurement repeatability of the phase-N current vector output 140 by up to a factor of 2. This also results in an increased dynamic range of the power meter 102. Any harmonic distortion correlated with the 50 or 60 Hz phase-N load current 106 remains unaffected by the cross-correlated averaging operation 130.

[0069] Those skilled in the art will also understand that various modifications are possible to any of the aforementioned power meters 2,102. For example, instead of determining the cross-correlated average data sequence 40 corresponding to a time period based on the first and second ADC output data sequences 20a and 20b by reversing the order of the data in the first ADC output data sequence 20a in time, multiplying the time-reversed first ADC output data sequence by the second ADC output data sequence 20b to generate a product data sequence, and determining the square root of the data in the product data sequence to determine the cross-correlated average data sequence 40, The cross-correlated average data sequence 40 corresponding to a time period may be determined by generating a product data sequence by temporally reversing the order of the data in the second ADC output data sequence 120b and multiplying it with the second adjusted data sequence which has been temporally reversed with respect to the first ADC output data sequence 120a, and then determining the cross-correlated average data sequence 40 by determining the square root of the data in the product data sequence.

[0070] Similarly, instead of determining the cross-correlated average data sequence 132 corresponding to a time period based on the first and second adjusted data sequences 126a and 126b by reversing the order of the data in the first adjusted data sequence 126a in time, multiplying the time-reversed first adjusted data sequence by the second adjusted data sequence 126b to generate a product data sequence, and determining the square root of the data in the product data sequence to determine the cross-correlated average data sequence 132, The cross-correlated average data sequence 132 corresponding to a time period may be determined by generating a product data sequence by temporally reversing the order of the data in the second adjusted data sequence 126b and multiplying the first adjusted data sequence 126a by the temporally reversed second adjusted data sequence, and then determining the cross-correlated average data sequence 132 by determining the square root of the data in the product data sequence.

[0071] The first and second ADCs 10a, 110a and 10b, 110b are described as delta-sigma ADCs, respectively, but in other embodiments, the first and second ADCs 10a, 110a and 10b, 110b may each be any type of ADC, for example, the first and second ADCs 10a, 110a and 10b, 110b may each be a Wilkinson ADC, a direct conversion or flash ADC, a successive approximation ADC, a ramp comparison ADC, an integral ADC, a delta coding or counter-ramp ADC or pipeline ADC, a time interleaved ADC, etc.

[0072] The alternating current 6,106 may constitute one phase of a multiphase power supply.

[0073] The alternating current 6,106 may constitute phase A of a multiphase power supply.

[0074] The power meter 2,102 may be configured to measure one or more characteristics of each of the AC currents among a plurality of AC currents, such as the plurality of phases of a polyphase power supply according to any of the methods described above.

[0075] Optionally, the current step-down transformer may have turns ratios ranging from 1:100 to 1:10000, 1:1000 to 1:3000, approximately 1:2000, or 1:2000.

[0076] Although the power meter 2,102 has been described as being configured to measure one or more characteristics of electrical inputs associated with a power source having alternating current, in an alternative embodiment, the power meter may be configured to measure one or more characteristics of different types of electrical inputs associated with a power source. For example, the power meter may be configured to measure one or more characteristics of different types of alternating current electrical inputs associated with a power source.

[0077] A power meter may be configured to measure one or more characteristics of an electrical input, including input voltage, input current, or input power.

[0078] A power meter may be configured to measure one or more characteristics of an electrical input, including AC voltage, AC current, or AC power.

[0079] A power meter may be configured to measure one or more characteristics of electrical inputs associated with one phase of a multiphase power supply.

[0080] A power meter may be configured to measure one or more characteristics of each of several electrical inputs, for example, each electrical input may include voltage such as AC voltage, current such as AC current, or power such as AC power, and / or each electrical input may be associated with a different phase of a polyphase power supply.

[0081] While the power meter 2,102 has been described in relation to the preferred embodiments described above, it should be understood that these embodiments are illustrative only and the claims are not limited to those embodiments. Those skilled in the art can modify and change the embodiments described in light of this disclosure, and it is intended that such modifications and changes will be included within the scope of the appended claims. Each feature disclosed or illustrated herein may be incorporated into any embodiment, either alone or in any suitable combination with any other feature disclosed or illustrated herein. In particular, those skilled in the art will understand, with reference to the drawings, that one or more features of the embodiments of this disclosure described above may also have effects or advantages when used separately from one or more other features of the embodiments of this disclosure, and that other combinations of features other than the specific combinations of features of the embodiments of this disclosure described above are also possible.

[0082] Those skilled in the art will understand that in the preceding description and the attached claims, positional terms such as “above,” “alongside,” and “beside” are referred to with reference to conceptual diagrams such as those shown in the attached drawings. These terms are used for convenience of reference and are not intended to limit the nature of the object. Accordingly, these terms should be understood to refer to an object in the orientation shown in the attached drawings.

[0083] The use of the phrase "comprising" when used in relation to features according to embodiments of this disclosure does not exclude other features or steps. The use of the phrase "a" or "an" when used in relation to features according to embodiments of this disclosure does not exclude the possibility that an embodiment may include multiple such features.

Claims

1. A power meter for measuring one or more characteristics of electrical inputs associated with a power source, wherein the power meter is A first ADC is configured to receive an ADC input signal representing the above electrical input and to generate a first ADC output data sequence representing the above electrical input over a predetermined time period from the ADC input signal, A second ADC is configured to receive the above-mentioned ADC input signal representing the above-mentioned electrical input and to generate a second ADC output data sequence representing the above-mentioned electrical input over the above-mentioned time period from the above-mentioned ADC input signal, The system includes a processing resource configured to determine a cross-correlated average data sequence corresponding to the time period based on the first and second ADC output data sequences described above, and to determine one or more characteristics of the electrical input over the time period based on the cross-correlated average data sequence corresponding to the time period, Electricity meter.

2. Based on the first and second ADC output data sequences described above, determining the cross-correlated average data sequence corresponding to the above time period is: The first method involves reversing the order of data in the first ADC output data sequence in time, and multiplying the reversed first ADC output data sequence by the second ADC output data sequence to generate an integrated data sequence, or reversing the order of data in the second ADC output data sequence in time, and multiplying the first ADC output data sequence by the reversed second ADC output data sequence to generate an integrated data sequence. This includes determining the square root of the data in the above product data sequence. The power meter according to claim 1.

3. Based on the first and second ADC output data sequences described above, determining the cross-correlated average data sequence corresponding to the above time period is: By performing one or more adjustment operations on the first and second ADC output data sequences described above, the first and second adjusted data sequences are generated, respectively. The first method involves reversing the order of data in the first adjusted data sequence in time and multiplying the reversed first adjusted data sequence by the second adjusted data sequence to generate an integrated data sequence, or reversing the order of data in the second adjusted data sequence in time and multiplying the first adjusted data sequence by the reversed second adjusted data sequence to generate an integrated data sequence. This includes determining the square root of the data in the above product data sequence. The power meter according to claim 1.

4. The one or more adjustment operations described above include calibration adjustment operations and / or resampling operations. The power meter according to claim 3.

5. The above calibration adjustment operation includes adjusting the first and second ADC output data sequences according to calibration data measured by the power meter with respect to one or more known electrical inputs having corresponding known amplitudes, corresponding known frequencies, and corresponding known phases, respectively. The power meter according to claim 4.

6. The above resampling operation includes one or more of interpolation, image removal filtering, anti-aliasing filtering, and decimation. The power meter according to claim 4 or 5.

7. Determining one or more characteristics of the electrical input over the above time period includes determining one or more of the amplitude, frequency, and phase of the electrical input over the above time period based on the cross-correlated average data sequence corresponding to the above time period. A power meter according to any one of claims 1 to 6.

8. Determining one or more characteristics of the electrical input over the above time period based on the above cross-correlated average data sequence corresponding to the above time period is: By performing one or more adjustment operations on the above-mentioned cross-correlated average data sequence corresponding to the above-mentioned time period, an adjusted cross-correlated average data sequence is generated. This includes determining one or more characteristics of the electrical input over the above time period based on the adjusted cross-correlated average data sequence corresponding to the above time period, A power meter according to any one of claims 1 to 6.

9. Generating the adjusted cross-correlated average data sequence by performing one or more adjustment operations on the cross-correlated average data sequence corresponding to the above time period includes using the zero crossing of the electrical input as the phase reference for the cross-correlated average data sequence. The power meter according to claim 8.

10. Using the zero crossing of the above electrical input as the phase reference for the above cross-correlated averaged data sequence includes performing a phase-locked loop (PLL) operation, followed by a fast Fourier transform (FFT) operation. The power meter according to claim 9.

11. Determining one or more characteristics of the electrical input over the above time period includes determining one or more of the amplitude, frequency, and phase of the electrical input over the above time period based on the adjusted cross-correlated average data sequence corresponding to the above time period. A power meter according to any one of claims 8 to 10.

12. The above-mentioned power meter is configured to generate the above-mentioned ADC input signal based on the above-mentioned electrical input. A power meter according to any one of claims 1 to 11.

13. The above electricity meter is equipped with a transformer, Generating the ADC input signal based on the above electrical input includes using the above transformer to convert the above electrical input to a converted electrical input. A power meter according to any one of claims 1 to 12.

14. The above power meter is equipped with a voltage divider. Generating the ADC input signal based on the above electrical input includes generating a voltage signal by passing the above electrical input or the converted electrical input through the above voltage divider, or generating a voltage signal by applying the above electrical input or the converted electrical input to the above voltage divider. The power meter according to claim 12 or 13.

15. The above voltage divider comprises multiple resistors connected in series. The power meter according to claim 14.

16. The above ADC input signal includes a voltage signal. The power meter according to claim 14 or 15.

17. The above power meter is equipped with an anti-aliasing filter. Generating the ADC input signal based on the above electrical input includes filtering the voltage signal using the above anti-aliasing filter, The above ADC input signal includes the filtered voltage signal, The power meter according to claim 14 or 15.

18. The above electrical input includes AC electrical input. The above electrical input includes input voltage, input current, or input power. The above electrical input includes AC voltage, AC current, or AC power, or The above electrical input is associated with one phase of a multiphase power supply. Characterized by at least one of the following: A power meter according to any one of claims 1 to 17.

19. The above power meter is configured to measure the characteristics of one or more of the electrical inputs among a plurality of electrical inputs. for example, Each electrical input includes a voltage such as an AC voltage, a current such as an AC current, or power such as an AC power, and / or Each electrical input is associated with a different phase of a multiphase power supply. A power meter according to any one of claims 1 to 18.

20. A method for measuring one or more characteristics of electrical inputs associated with a power supply, wherein the method is In the first ADC, an ADC input signal representing the electrical input is received, and the first ADC is used to generate a first ADC output data sequence representing the electrical input over a predetermined time period from the ADC input signal. In the second ADC, the ADC input signal representing the electrical input is received, and the second ADC is used to generate a second ADC output data sequence representing the electrical input over the specified time period from the ADC input signal. Based on the first and second ADC output data sequences described above, a cross-correlated average data sequence corresponding to the above time period is determined. This includes determining one or more characteristics of the electrical input over the above time period based on the above-mentioned cross-correlated average data sequence corresponding to the above-mentioned time period, method.

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