Electricity meter and related method
By employing a dual ADC structure and cross-correlation averaging technology, the noise interference problem when measuring AC current with an electric meter is solved, achieving higher measurement accuracy and repeatability, and expanding the dynamic range.
Patent Information
- Application Number
- CN202480048536.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Priority Date
- 2023-07-27
- Filing Date
- 2024-07-26
- Publication Date
- 2026-02-24
AI Technical Summary
Existing electricity meters suffer from high signal-to-noise ratios due to noise interference when measuring AC current, resulting in insufficient measurement accuracy, poor repeatability, and limited dynamic range.
By employing a dual ADC structure and cross-correlation averaging technique, noise interference is eliminated or reduced through cross-correlation calculation of the output data sequences of the two ADCs, thereby improving measurement accuracy and repeatability.
Theoretically, it can eliminate half of the noise, and in practice, it doubles the measurement accuracy and repeatability, and increases the dynamic range.
Smart Images
Figure CN121569202A_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to an electricity meter and an associated method for measuring one or more characteristics of an electrical input associated with a power source, and particularly, but not exclusively, 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 phase of a multiphase power source). Background Technology
[0002] As is well known, an electric meter is used to measure one or more characteristics of an electrical input (such as alternating current) that is phase-dependent with a multiphase power source, by sampling a voltage signal representing an alternating current to generate a sequence of output data over a period of time, and by determining one or more characteristics of the alternating current over that period of time based on the output data sequence.
[0003] However, the generated output data sequence may include noise due to the sampling operation resulting in a signal-to-noise ratio (SNR) that is too high for some applications, especially when the AC current is low. This can lead to insufficient accuracy in the measurement of one or more characteristics of the AC current, resulting in poor measurement repeatability and / or limited dynamic range. Summary of the Invention
[0004] According to one aspect of this disclosure, an electricity meter is provided for measuring one or more characteristics of an electrical input associated with a power source, the electricity meter comprising:
[0005] The first ADC is configured to receive an ADC input signal representing an electrical input, and to generate a first ADC output data sequence representing the electrical input over a period of time from the ADC input signal.
[0006] The second ADC is configured to receive an ADC input signal representing an electrical input, and to generate a second ADC output data sequence representing the electrical input during that time period from the ADC input signal; and
[0007] The processing resources are configured to determine a cross-correlation average data sequence corresponding to the time period based on a first ADC output data sequence and a second ADC output data sequence, and to determine one or more characteristics of the electrical input during the time period based on the cross-correlation average data sequence corresponding to the time period.
[0008] A cross-correlation average data sequence corresponding to the time period is determined based on the first and second ADC output data sequences, and one or more characteristics of the electrical input within the time period are determined based on the cross-correlation average data sequence corresponding to the time period. This can be used to eliminate or at least reduce any uncorrelated noise contained in the first and second ADC output data sequences. This uncorrelated noise can be thermal and can originate from the sample-and-hold stages of the first and second ADCs. Theoretically, using the first and second ADCs in this way, along with cross-correlation averaging, can result in the elimination of up to half of the noise contained in each of the first and second ADC output data sequences. In practice, this can improve the accuracy of electrical input measurements and / or increase the repeatability of electrical input measurements by up to two times. This can also lead to an increase in the dynamic range of the meter. Any harmonic distortion associated with the electrical input can remain unaffected by cross-correlation averaging.
[0009] Optionally, based on the first ADC output data sequence and the second ADC output data sequence, determining the cross-correlation average data sequence corresponding to the time period includes:
[0010] Reverse the order of the data in the first ADC output data sequence in time, and multiply the time-reversed first ADC output data sequence by the second ADC output data sequence to generate a product data sequence; or reverse the order of the data in the second ADC output data sequence in time, and multiply the first ADC output data sequence by the time-reversed second ADC output data sequence to generate a product data sequence; and
[0011] Determine the square root of the data in the product data sequence.
[0012] Optionally, based on the first ADC output data sequence and the second ADC output data sequence, determining the cross-correlation average data sequence corresponding to the time period includes:
[0013] Perform one or more adjustment operations on the first ADC output data sequence and the second ADC output data sequence to generate the first adjusted data sequence and the second adjusted data sequence, respectively;
[0014] Reverse the order of data in the first adjusted data sequence in time, and multiply the time-reversed first adjusted data sequence by the second adjusted data sequence to generate a product data sequence; or reverse the order of data in the second adjusted data sequence in time, and multiply the first adjusted data sequence by the time-reversed second adjusted data sequence to generate a product data sequence; and
[0015] Determine the square root of the data in the product data sequence.
[0016] Optionally, one or more adjustment operations include calibration adjustment operations and / or resampling operations.
[0017] Optionally, the calibration adjustment operation includes adjusting the first ADC output data sequence and the second ADC output data sequence based on calibration data measured by the meter for one or more known electrical inputs, each known electrical input having a corresponding known amplitude, a corresponding known frequency, and a corresponding known phase.
[0018] Optionally, the resampling operation includes one or more of interpolation, image suppression filtering, anti-aliasing filtering, and decimation.
[0019] Optionally, determining one or more characteristics of the electrical input during the time period includes: determining one or more of the amplitude, frequency, and phase of the electrical input during the time period based on a cross-correlation average data sequence corresponding to the time period.
[0020] Optionally, determining one or more characteristics of the electrical input during this time period includes:
[0021] Perform one or more adjustment operations on the cross-correlation average data series corresponding to this time period to generate an adjusted cross-correlation average data series; and
[0022] One or more characteristics of the electrical input during that time period are determined based on the adjusted cross-correlation average data sequence corresponding to that time period.
[0023] Optionally, performing one or more adjustment operations on the cross-correlation average data sequence corresponding to the time period to generate an adjusted cross-correlation average data sequence includes referencing the phase of the cross-correlation average data sequence to the zero-crossing point of the alternating current.
[0024] Optionally, referencing the phase of the cross-correlation average data sequence to the zero-crossing point of the alternating current involves performing a phase-locked loop (PLL) operation followed by a fast Fourier transform (FFT) operation.
[0025] Optionally, determining one or more characteristics of the electrical input during the time period includes determining one or more of the amplitude, frequency, and phase of the electrical input during the time period based on a regulated cross-correlation average data sequence corresponding to the time period.
[0026] Optionally, the meter is configured to generate an ADC input signal based on the electrical input.
[0027] Optionally, the meter includes a transformer, wherein generating an ADC input signal based on an electrical input includes using the transformer to transform the electrical input into a transformed electrical input.
[0028] 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 1:10,000, 1:1000 to 1:3000, approximately 1:2000, or 1:2000.
[0029] Optionally, the meter includes a voltage divider.
[0030] Optionally, generating an ADC input signal based on an electrical input includes passing the electrical input or a transformed electrical input through a voltage divider to generate a voltage signal, or applying the electrical input or a transformed electrical input to a voltage divider to generate a voltage signal.
[0031] Optionally, the voltage divider includes multiple resistors connected in series.
[0032] Optionally, the ADC input signal may include a voltage signal.
[0033] Optionally, the meter includes an anti-aliasing filter.
[0034] Optionally, generating the ADC input signal based on the electrical input includes filtering the voltage signal using an anti-aliasing filter.
[0035] Optionally, the ADC input signal includes a filtered voltage signal.
[0036] Optionally, the time period corresponds to one or more line cycles of the alternating current. Shorter time periods corresponding to fewer line cycles will allow for higher resolution measurement of the electrical input for each line cycle, while longer time periods corresponding to more line cycles will allow for more averaging to further improve the signal-to-noise ratio.
[0037] Optionally, the electrical input includes an AC input.
[0038] Optionally, the electrical input may include input voltage, input current, or input power.
[0039] Optionally, the electrical input may include AC voltage, AC current, or AC power.
[0040] Optionally, the electrical input is associated with the phase of the multiphase power supply.
[0041] Optionally, the meter is configured to measure one or more characteristics of each of a plurality of electrical inputs.
[0042] Optionally, each electrical input includes a voltage such as an AC voltage, a current such as an AC current, or a power such as an AC current.
[0043] Optionally, each electrical input is associated with a different phase of a multiphase power supply.
[0044] According to one aspect of this disclosure, a method is provided for measuring one or more characteristics of an electrical input associated with a power source, the method comprising:
[0045] The first ADC receives an ADC input signal representing an electrical input and uses the first ADC to generate a first ADC output data sequence representing an electrical input over a time period from the ADC input signal.
[0046] The system receives an ADC input signal representing the electrical input at the second ADC, and uses the second ADC to generate a second ADC output data sequence representing the electrical input during that time period from the ADC input signal; and
[0047] The cross-correlation average data sequence corresponding to the time period is determined based on the first ADC output data sequence and the second ADC output data sequence; and
[0048] One or more characteristics of the electrical input during that time period are determined based on the cross-correlation average data sequence corresponding to that time period.
[0049] Optionally, based on the first ADC output data sequence and the second ADC output data sequence, determining the cross-correlation average data sequence corresponding to the time period includes:
[0050] Reverse the order of the data in the first ADC output data sequence in time, and multiply the time-reversed first ADC output data sequence by the second ADC output data sequence to generate a product data sequence; or reverse the order of the data in the second ADC output data sequence in time, and multiply the first ADC output data sequence by the time-reversed second ADC output data sequence to generate a product data sequence; and
[0051] Determine the square root of the data in the product data sequence.
[0052] Optionally, determining the cross-correlation average data sequence corresponding to the time period based on the first ADC output data sequence and the second ADC output data sequence includes:
[0053] Perform one or more adjustment operations on the first ADC output data sequence and the second ADC output data sequence to generate the first adjusted data sequence and the second adjusted data sequence, respectively;
[0054] Reverse the order of data in the first adjusted data sequence in time, and multiply the time-reversed first adjusted data sequence by the second adjusted data sequence to generate a product data sequence; or reverse the order of data in the second adjusted data sequence in time, and multiply the first adjusted data sequence by the time-reversed second adjusted data sequence to generate a product data sequence; and
[0055] Determine the square root of the data in the product data sequence.
[0056] Optionally, one or more adjustment operations include calibration adjustment operations and / or resampling operations.
[0057] Optionally, the first ADC output data sequence and the second ADC output data sequence are adjusted based on calibration data measured by the meter for one or more known electrical inputs, each known electrical input having a corresponding known amplitude, a corresponding known frequency, and a corresponding known phase.
[0058] Optionally, the resampling operation includes one or more of interpolation, image suppression filtering, anti-aliasing filtering, and decimation.
[0059] Optionally, determining one or more characteristics of the electrical input during that time period based on the cross-correlated average data sequence corresponding to that time period includes:
[0060] Perform one or more adjustment operations on the cross-correlation average data series corresponding to this time period to generate an adjusted cross-correlation average data series; and
[0061] One or more characteristics of the electrical input during a given time period are determined based on the adjusted cross-correlation average data sequence corresponding to that time period.
[0062] Optionally, performing one or more adjustment operations on the cross-correlation average data sequence corresponding to the time period to generate an adjusted cross-correlation average data sequence includes referencing the phase of the cross-correlation average data sequence to the zero-crossing point of the electrical input.
[0063] Optionally, referencing the phase of the cross-correlation averaged data sequence to the zero-crossing of the electrical input involves performing a phase-locked loop (PLL) operation followed by a fast Fourier transform (FFT) operation.
[0064] Optionally, determining one or more characteristics of the electrical input during the time period includes determining one or more of the amplitude, frequency, and phase of the electrical input during the time period based on a regulated cross-correlation average data sequence corresponding to the time period.
[0065] Optionally, the electrical input includes an AC input.
[0066] Optionally, the electrical input may include input voltage, input current, or input power.
[0067] Optionally, the electrical input may include AC voltage, AC current, or AC power.
[0068] Optionally, the electrical input is associated with the phase of the multiphase power supply.
[0069] Optionally, the meter is configured to measure one or more characteristics of each of a plurality of electrical inputs.
[0070] Optionally, each electrical input includes a voltage such as an AC voltage, a current such as an AC current, or a power such as an AC current.
[0071] Optionally, each electrical input is associated with a different phase of a multiphase power supply.
[0072] It should be understood that any one or more of the optional features of any of the foregoing aspects of this disclosure may be combined with any one or more of the other foregoing aspects of this disclosure or any one or more of the optional features of the other foregoing aspects of this disclosure. Attached Figure Description
[0073] A meter and associated method for measuring one or more characteristics of an electrical input associated with a power source will now be described by way of non-limiting example only, with reference to the accompanying drawings, wherein:
[0074] Figure 1 This is a schematic diagram of the first electricity meter; and
[0075] Figure 2 This is a schematic diagram of the second electricity meter. Detailed Implementation
[0076] First refer to Figure 1 The diagram illustrates a first meter, generally designated 2, used to measure one or more characteristics 4 of an electrical input associated with a power source in the form of alternating current 6. Meter 2 includes a voltage divider in the form of multiple series load resistors 8, a first ADC 10a in the form of a first delta-sigma analog-to-digital converter (ADC) and a second ADC 10b in the form of a second delta-sigma ADC, and a processing resource in the form of a microprocessor 12. The alternating current 6 may be an N-phase load current, and one or more characteristics 4 of the alternating current 6 may be one or more energy measures used for metering.
[0077] The first ADC 10a and the second ADC 10b are each configured to receive an ADC input signal in the form of a voltage signal 18, which represents the current 6 flowing through the load resistor 8. The first ADC 10a and the second ADC 10b are configured to generate a first ADC output data sequence 20a and a second ADC output data sequence 20b, respectively, representing the current 6 flowing through the load resistor 8 during a time period such as one or more line cycles of the alternating current 6. The microprocessor 12 is configured to perform a cross-correlation averaging operation 30 of the first ADC output data sequence 20a and the second ADC output data sequence 20b to determine a cross-correlation average data sequence 40 corresponding to that time period. Those skilled in the art will understand that the cross-correlation average data sequence 40 corresponding to that time period can be considered to constitute an N-phase current vector output 40 corresponding to the N-phase load current 6 within that time period. The microprocessor 12 is configured to determine one or more characteristics 4 of the phase N load current 40 during that time period based on the phase N current vector output 40. 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 during that time period.
[0078] In use, an alternating current 6 passes through a load resistor 8 to generate a voltage signal 18 representing the current 6. A first ADC 10a receives the voltage signal 18 and generates a first ADC output data sequence 20a representing the current 6 during that time period. A second ADC 10b also receives the voltage signal 18 and generates a second ADC output data sequence 20b representing the current 6 during that time period. A microprocessor 12 determines one or more characteristics of the current 4 during that time period based on the first ADC output data sequence 20a and the second ADC output data sequence 20b. Specifically, the microprocessor 12 determines the phase N current vector output 40 corresponding to the time period by performing a cross-correlation averaging operation 30 on the first ADC output data sequence 20a and the second ADC output data sequence 20b to generate a cross-correlation average data sequence 40 corresponding to the time period, and then determines one or more characteristics of the cross-correlation average data sequence 40 to generate one or more energy measurements for measuring 4. The microprocessor 12 determines the cross-correlation average data sequence 40 corresponding to the time period based on the first ADC output data sequence 20a and the second ADC output data sequence 20b (by reversing the data order of the first ADC output data sequence 20a in time, multiplying the time-reversed first ADC output data sequence with the second ADC output data sequence 20b to generate a product data sequence, and determining the cross-correlation average data sequence 40 by determining the square root of the data in the product data sequence).
[0079] The phase N current vector output 40 corresponding to the time period is determined by determining a cross-correlation average data sequence corresponding to the time period based on the first ADC output data sequence 20a and the second ADC output data sequence 20b. Then, one or more characteristics of the phase N current vector output 40 are determined to generate one or more energy metrics for metering 4. This method is used to eliminate or at least reduce any uncorrelated noise contained in the first ADC output data sequence 20a and the second ADC output data sequence 20b. This uncorrelated noise is typically thermal and originates from the sample-and-hold stages of the first and second Delta-Sigma ADCs 10a and 10b. Those skilled in the art will understand that the cross-correlation averaging operation 30 is similar to a matched filter operation, which rejects uncorrelated noise present in the first ADC output data sequence 20a and the second ADC output data sequence 20b. Theoretically, using the first ADC 10a and the second ADC 10b, along with the cross-correlation averaging operation 30, can result in the elimination of up to half of the noise contained in the first ADC output data sequence 20a and the second ADC output data sequence 20b. In practice, this can lead to improved measurement accuracy of the N-phase current vector output 40 and up to a twofold increase in measurement repeatability. It also results in an increase in the dynamic range of meter 2. Any harmonic distortion associated with the 50 or 60 Hz phase N load current 6 remains unaffected by the cross-correlation averaging operation 30.
[0080] Now for reference Figure 2 A second meter, generally designated 102, is shown for measuring one or more characteristics 104 of an alternating current 106. Meter 102 includes a current-stepping transformer 107, a voltage divider in the form of multiple load resistors 108 connected in series, an anti-aliasing filter 109, a first ADC 10a in the form of a first delta-sigma analog-to-digital converter (ADC) and a second ADC 10b in the form of a second delta-sigma ADC, respectively, and processing resources in the form of a microprocessor 12. The alternating current 106 may be a phase N load current, and one or more characteristics 104 of the alternating current 106 may be one or more energy measurements for metering. The current-stepping transformer 107 may have a turns ratio of 1:2000.
[0081] The first ADC 110a and the second ADC 110b are each configured to receive an ADC input signal in the form of a voltage signal 119 at the output of the anti-aliasing filter 109. The voltage signal 119 represents the current 106. The first ADC 110a and the second ADC 110b are configured to generate a first ADC output data sequence 120a and a second ADC output data sequence 120b, respectively, which represent the current 106 during a time period such as one or more line cycles of the alternating current 106.
[0082] Microprocessor 112 is configured to perform one or more adjustment operations on a first ADC output data sequence 120a and a second ADC output data sequence 120b to generate a first adjusted data sequence 126a and a second adjusted data sequence 126b, respectively. Specifically, microprocessor 112 is configured to perform a calibration adjustment operation 122 followed by a resampling operation 124 to generate the first adjusted data sequence 126a and the second adjusted data sequence 126b from the first ADC output data sequence 120a and the second ADC output data sequence 120b, respectively. Calibration adjustment operation 122 may include adjusting the first ADC output data sequence 120a and the second ADC output data sequence 120b according to calibration data measured by meter 102 for one or more known AC currents, each known AC current having a corresponding known amplitude, a corresponding known frequency, and a corresponding known phase. Resampling operation 124 may include using one or more of interpolation, image suppression filters, anti-aliasing filters, and decimation.
[0083] The microprocessor 112 is also configured to perform a cross-correlation averaging operation 130 of the first adjusted data sequence 126a and the second adjusted data sequence 126b to generate a cross-correlation average data sequence 132 corresponding to the time period.
[0084] The microprocessor 112 is also configured to perform one or more adjustment operations on the cross-correlation average data sequence 132 corresponding to the time period to generate an adjusted cross-correlation average data sequence 140. Specifically, the microprocessor 112 is configured to reference the phase of the cross-correlation average data sequence 132 to the zero-crossing point of the alternating current 106 by performing a phase-locked loop (PLL) operation 134 and then a fast Fourier transform (FFT) operation 136 to generate the adjusted cross-correlation average data sequence 140.
[0085] Those skilled in the art will understand that the adjusted cross-correlation average data sequence 140 corresponding to this time period can be considered to constitute the N-phase current vector output 140 corresponding to the N-phase load current 106 within this time period. The microprocessor 112 is configured to determine one or more characteristics 104 of the N-phase load current 140 within this time period based on the N-phase 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 N-phase current vector output 140 during this time period.
[0086] In operation, the alternating current 106 constitutes the primary alternating current of the current transformer 107. The current transformer 107 transforms the alternating current 106 into a secondary alternating current, which passes through the load resistor 108 to generate 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.
[0087] A first ADC 110a receives a voltage signal 119 and generates a first ADC output data sequence 120a representing the current 106 during that time period. A second ADC 110b also receives the voltage signal 119 and generates a second ADC output data sequence 120b representing the current 106 during that time period. A microprocessor 112 determines one or more characteristics of the current 104 during that time period based on the first ADC output data sequence 120a and the second ADC output data sequence 120b. Specifically, the microprocessor 112 performs a calibration adjustment operation 122 on the first ADC output data sequence 120a and the second ADC output data sequence 120b, followed by a resampling operation 124 to generate a first adjusted data sequence 126a and a second adjusted data sequence 126b, respectively.
[0088] Then, the microprocessor 112 performs a cross-correlation averaging operation 130 on the first adjusted data sequence 126a and the second adjusted data sequence 126b, respectively, to generate a cross-correlation average data sequence 132. More specifically, the microprocessor 112 determines the cross-correlation average data sequence 132 corresponding to the time period based on the first adjusted data sequence 126a and the second adjusted data sequence 126b (by reversing the data order of 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 cross-correlation average data sequence 132 by determining the square root of the data in the product data sequence).
[0089] Then, microprocessor 112 performs a PLL operation 134 on the cross-correlation average data sequence 132 corresponding to the time period, and then performs an FFT operation 136 to generate an N-phase current vector output 140 corresponding to the N-phase load current 106 within the time period. Microprocessor 112 determines one or more characteristics of the N-phase current vector output 140 to generate one or more energy measurements for metering 104.
[0090] The N-phase current vector output 140 corresponding to the time period is determined by determining a cross-correlation average data sequence 132 corresponding to the time period based on the first ADC output data sequence 120a and the second ADC output data sequence 120b. Then, one or more characteristics of the N-phase current vector output 140 are determined to generate one or more energy measurements for metering 104. In this way, any uncorrelated noise contained in the first ADC output data sequence 120a and the second ADC output data sequence 120b can be eliminated or at least reduced. This uncorrelated noise is typically thermal and originates from the sample-and-hold stages of the first and second Delta-Sigma ADCs 110a and 110b. Those skilled in the art will understand that the cross-correlation averaging operation 130 is similar to a matched filter operation, which rejects uncorrelated noise present in the first and second ADC output data sequences 120a and 120b. Theoretically, using the first ADC 110a and the second ADC 110b, along with the cross-correlation averaging operation 130, can result in the elimination of up to half of the noise contained in the first and second ADC output data sequences 120a and 120b. In practice, this can lead to improved measurement accuracy of the N-phase current vector output 140 and up to a twofold increase in measurement repeatability. It also results in an increase in the dynamic range of the meter 102. Any harmonic distortion associated with the 50 or 60 Hz phase N load current 106 remains unaffected by the cross-correlation averaging operation 130.
[0091] Those skilled in the art will also understand that various modifications can be made to any of the above-described meters 2 and 102. For example, as an alternative to determining the cross-correlation average data sequence 40 corresponding to a time period based on the first ADC output data sequence 20a and the second ADC output data sequence 20b (by reversing the order of the data in the first ADC output data sequence 20a in time and multiplying the time-reversed first ADC output data sequence 20a by the second ADC output data sequence 20b to generate a product data sequence, and determining the cross-correlation average data sequence 40 by determining the square root of the data in the product data sequence), the cross-correlation average data sequence 40 corresponding to that time period can be determined by reversing the order of the data in the second ADC output data sequence 120b in time and multiplying the first ADC output data sequence 120a by the time-reversed second adjustment data sequence to generate a product data sequence, and determining the cross-correlation average data sequence 40 by determining the square root of the data in the product data sequence.
[0092] Similarly, as an alternative to determining the cross-correlation average data sequence 132 corresponding to a time period based on the first adjusted data sequence 126a and the second adjusted data sequence 126b (by reversing the order of the data in the first adjusted data sequence 126a in time and multiplying the time-reversed first adjusted data sequence by the second adjusted data sequence 126b to generate a product data sequence and determining the cross-correlation average data sequence 132 by determining the square root of the data in the product data sequence), the cross-correlation average data sequence 132 corresponding to a time period can be determined by reversing the order of the data in the second adjusted data sequence 126b in time and multiplying the first adjusted data sequence 126a by the time-reversed second adjusted data sequence to generate a product data sequence, and determining the cross-correlation average data sequence 132 corresponding to a time period by determining the square root of the data in the product data sequence.
[0093] Although the first ADC 10a, 110a and the second ADC 10b, 110b are described as Delta-Sigma ADCs, in other embodiments, the first ADC 10a, 110a and the second ADC 10b, 110b can be any type of ADC, such as a Wilkinson ADC, a direct conversion or flash memory ADC, a successive approximation ADC, a ramp comparison ADC, an integral ADC, a Delta-encoded or counter ramp ADC or a pipelined ADC, a time-interleaved ADC, etc.
[0094] Alternating currents of 6 and 106 can form one phase of a multiphase power supply.
[0095] Alternating currents of 6 and 106 can form phase A of a multiphase power supply.
[0096] Meters 2 and 102 can be configured to measure one or more characteristics of each of a plurality of alternating currents (such as multiple phases of a multiphase power supply) according to any of the methods described above.
[0097] Alternatively, the current step-down transformer may have a turns ratio in the range of 1:100 to 1:10,000, 1:1000 to 1:3000, approximately 1:2000, or 1:2000.
[0098] Although the above description describes meters 2, 102 as configured to measure one or more characteristics of electrical inputs in the form of alternating current associated with a power source, in alternative embodiments, the meters may be configured to measure one or more characteristics of different types of electrical inputs associated with a power source. For example, the meters may be configured to measure one or more characteristics of different kinds of alternating current inputs associated with a power source.
[0099] An electricity meter can be configured to measure one or more characteristics of an electrical input, including input voltage, input current, or input power.
[0100] An electricity meter can be configured to measure one or more characteristics of an electrical input, including AC voltage, AC current, or AC power.
[0101] An electricity meter can be configured to measure one or more characteristics of an electrical input associated with the phase of a multiphase power supply.
[0102] An electricity meter can be configured to measure one or more characteristics of each of a plurality of electrical inputs, such as voltage (e.g., AC voltage), current (e.g., AC current), or power (e.g., AC power) and / or each electrical input is associated with a different phase of a multiphase power source.
[0103] Although meters 2 and 102 have been described with reference to the preferred embodiments described above, it should be understood that these embodiments are illustrative only, and the claims are not limited to these embodiments. Those skilled in the art will be able to modify and substitute the described embodiments based on this disclosure, and such modifications and substitutions are considered to fall within the scope of the appended claims. Each feature disclosed or shown in this specification may be incorporated into any embodiment, either alone or in any suitable combination with any other feature disclosed or shown herein. Specifically, those skilled in the art will understand that one or more features of the embodiments of this disclosure described above with reference to the accompanying drawings may have an effect or provide an advantage when used alone with one or more other features of the embodiments of this disclosure, and different combinations of features are also possible beyond the specific combinations of features of the embodiments of this disclosure described above.
[0104] Those skilled in the art will understand that in the foregoing description and appended claims, positional terms such as “above,” “along,” and “side” are used with reference to conceptual diagrams (e.g., those shown in the accompanying drawings). These terms are used for ease of reference but are not intended to be restrictive. Therefore, these terms should be understood to refer to objects when they are in the orientation shown in the accompanying drawings.
[0105] When used in connection with features of embodiments of the present disclosure, the use of the term "comprising" does not exclude other features or steps. When used in connection with features of embodiments of the present disclosure, the use of the terms "a" or "an" does not exclude the possibility that the embodiment may include multiple such features.
Claims
1. An electricity meter for measuring one or more characteristics of an electrical input associated with a power source, the electricity meter comprising: A first ADC is configured to receive an ADC input signal representing the electrical input and to generate a first ADC output data sequence representing the electrical input over a time period from the ADC input signal. The second ADC is configured to receive the ADC input signal representing the electrical input, and to generate a second ADC output data sequence representing the electrical input during the time period from the ADC input signal; as well as The processing resources are configured to determine a cross-correlation average data sequence corresponding to the time period based on the first ADC output data sequence and the second ADC output data sequence, and to determine one or more characteristics of the electrical input during the time period based on the cross-correlation average data sequence corresponding to the time period.
2. The electricity meter according to claim 1, wherein, Determining the cross-correlation average data sequence corresponding to the time period based on the first ADC output data sequence and the second ADC output data sequence includes: Reverse the order of the data in the first ADC output data sequence in time, and multiply the time-reversed first ADC output data sequence by the second ADC output data sequence to generate a product data sequence; or reverse the order of the data in the second ADC output data sequence in time, and multiply the first ADC output data sequence by the time-reversed second ADC output data sequence to generate a product data sequence; and Determine the square root of the data in the product data sequence.
3. The electricity meter according to claim 1, wherein, Determining the cross-correlation average data sequence corresponding to the time period based on the first ADC output data sequence and the second ADC output data sequence includes: Perform one or more adjustment operations on the first ADC output data sequence and the second ADC output data sequence to generate a first adjusted data sequence and a second adjusted data sequence, respectively; Reverse the order of the data in the first adjusted data sequence in time, and multiply the time-reversed first adjusted data sequence by the second adjusted data sequence to generate a product data sequence; or reverse the order of the data in the second adjusted data sequence in time, and multiply the first adjusted data sequence by the time-reversed second adjusted data sequence to generate a product data sequence; and Determine the square root of the data in the product data sequence.
4. The electricity meter according to claim 3, wherein, The one or more adjustment operations include calibration adjustment operations and / or resampling operations.
5. The electricity meter according to claim 4, wherein, The calibration adjustment operation includes: adjusting the first ADC output data sequence and the second ADC output data sequence according to calibration data measured by the meter for one or more known electrical inputs, each known electrical input having a corresponding known amplitude, a corresponding known frequency and a corresponding known phase.
6. The electricity meter according to claim 4 or 5, wherein, The resampling operation includes one or more of interpolation, image suppression filtering, anti-aliasing filtering, and decimation.
7. The electricity meter according to any one of the preceding claims, wherein, Determining the electrical input during the time period includes: determining one or more of the amplitude, frequency, and phase of the electrical input during the time period based on the cross-correlation average data sequence corresponding to the time period.
8. The electricity meter according to any one of claims 1 to 6, wherein, Determining one or more characteristics of the electrical input during the time period based on the cross-correlation average data sequence corresponding to the time period includes: Perform one or more adjustment operations on the cross-correlation average data sequence corresponding to the said time period to generate an adjusted cross-correlation average data sequence; and One or more characteristics of the electrical input during the time period are determined based on the adjusted cross-correlation average data sequence corresponding to the time period.
9. The electricity meter according to claim 8, wherein, Performing one or more adjustment operations on the cross-correlation average data sequence corresponding to the time period to generate the adjusted cross-correlation average data sequence includes: referencing the phase of the cross-correlation average data sequence to the zero-crossing point of the electrical input.
10. The electricity meter according to claim 9, wherein, The phase reference of the cross-correlation average data sequence to the zero-crossing point of the electrical input includes performing a phase-locked loop (PLL) operation followed by a fast Fourier transform (FFT) operation.
11. The electricity meter according to any one of claims 8 to 10, wherein, Determining the one or more characteristics of the electrical input during the time period includes: determining one or more of the amplitude, frequency, and phase of the electrical input during the time period based on the adjusted cross-correlation average data sequence corresponding to the time period.
12. The electricity meter according to any one of the preceding claims, wherein, The meter is configured to generate the ADC input signal based on the electrical input.
13. The meter according to any one of the preceding claims, comprising a transformer, wherein generating the ADC input signal based on the electrical input includes using the transformer to transform the electrical input into a transformed electrical input.
14. The meter according to claim 12 or 13, comprising a voltage divider, wherein, Generating the ADC input signal based on the electrical input includes: passing the electrical input or the transformed electrical input through the voltage divider to generate a voltage signal, or applying the electrical input or the transformed electrical input to the voltage divider to generate a voltage signal.
15. The electricity meter according to claim 14, wherein, The voltage divider includes multiple resistors connected in series.
16. The electricity meter according to claim 14 or 15, wherein, The ADC input signal includes the voltage signal.
17. The meter of claim 14 or 15, comprising an anti-aliasing filter, wherein generating the ADC input signal based on the electrical input includes filtering the voltage signal using the anti-aliasing filter, and wherein the ADC input signal comprises the filtered voltage signal.
18. The electricity meter according to any one of the preceding claims, wherein, At least one of the following: The electrical input includes an alternating current input; The electrical input includes input voltage, input current, or input power; The electrical input includes AC voltage, AC current, or AC power; or The electrical input is associated with the phase of the multiphase power supply.
19. The electricity meter according to any one of the preceding claims, wherein, The meter is configured to measure one or more characteristics of each of a plurality of electrical inputs, such that each electrical input includes a voltage such as an AC voltage, a current such as an AC current, or a power such as an AC power, and / or that each electrical input is associated with a different phase of a multiphase power supply.
20. A method for measuring one or more characteristics of an electrical input associated with a power source, the method comprising: An ADC input signal representing the electrical input is received at a first ADC, and a first ADC output data sequence representing the electrical input over a time period is generated from the ADC input signal using the first ADC. The ADC input signal representing the electrical input is received at the second ADC, and a second ADC output data sequence representing the electrical input during the time period is generated from the ADC input signal using the second ADC; A cross-correlation average data sequence corresponding to the time period is determined based on the first ADC output data sequence and the second ADC output data sequence; as well as The electrical input is determined based on the cross-correlation average data sequence corresponding to the time period, which is used to determine one or more characteristics of the electrical input during the time period.