Field calibration method based on wireless clamp buckle type three-phase electric energy calibration device

Abstract

The invention provides a field calibration method based on a wireless clamp buckle type three-phase electric energy calibration device. The field calibration method comprises the following steps: establishing a wireless communication link between a three-phase electric energy meter and a portable calibration host through a wireless synchronous trigger module; three groups of split-core type current transformers are respectively connected with a detected three-phase line in a clamping manner, a Hall effect sensor and a dual-mode sampling unit of a magnetoresistive sensor are arranged in each group of split-core type current transformers, and current signal fusion processing is realized through a Kalman filtering algorithm; synchronously acquiring the three-phase voltage signals; and generating a three-dimensional verification report comprising the time mark information, the harmonic distribution diagram and the error trend curve, wherein the three-dimensional verification report is packaged by adopting an extensible markup language format and is embedded with a digital signature. According to the invention, power-off-free online verification can be realized, the current measurement precision and the communication reliability are remarkably improved, the anti-interference capability is enhanced, the complex electric energy quality analysis requirement of a new energy access scene is met, and an efficient and reliable technical means is provided for electric energy metering verification of an electric power system.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power metering, and in particular to an on-site calibration method based on a wireless clamp-type three-phase electric energy calibration device, which is suitable for online detection and error analysis of electric energy meters in smart grids. Background Art

[0002] In the field of electricity metering, three-phase energy meters, as core equipment, have a high accuracy that is directly related to the fairness and impartiality of electricity trade settlements and the stable operation of power systems. Therefore, regular on-site calibration of three-phase energy meters is a crucial means of ensuring accurate and reliable energy measurement. However, the widely used traditional on-site calibration technology for three-phase energy meters suffers from a number of significant technical deficiencies, which severely restrict the efficiency and quality of on-site calibration work.

[0003] Field calibration of traditional three-phase energy meters requires disconnecting the line under test before wiring can be performed. This process inevitably results in power interruptions. For users with stringent requirements for power continuity, such as hospitals, data centers, and chemical companies, even a brief interruption can have serious consequences. Furthermore, data loss or business interruption in data centers can result in significant economic losses, while disruptions to production processes in chemical companies can lead to safety incidents. Furthermore, frequent power outages can cause significant inconvenience to electricity users, disrupting their normal work and daily lives.

[0004] Traditional calibration methods use wired connections between the calibration equipment and the energy meter under test. Complex field environments present numerous sources of electromagnetic interference, such as electromagnetic radiation and pulses generated by high-voltage transmission lines, large motors, and frequency converters. This electromagnetic interference can couple into the calibration equipment through wired connections, distorting the calibration signal and affecting the accuracy of the calibration results. This problem is particularly prominent in industrial sites with harsh electromagnetic environments, significantly compromising the reliability of traditional calibration methods and making it difficult to guarantee the quality of meter calibration.

[0005] With the rapid development of renewable energy generation technologies, such as the large-scale integration of distributed power sources like solar and wind power into the power grid, the harmonic content of power systems is increasing. Renewable energy generation equipment generates large amounts of harmonic currents during operation. Once injected into the grid, these harmonic currents can seriously impact the metering accuracy of energy meters. However, traditional three-phase energy meter field calibration equipment has limited harmonic analysis capabilities, making it unable to accurately measure and analyze harmonic parameters in the grid and difficult to assess the impact of harmonics on energy metering errors. Therefore, in scenarios where renewable energy is integrated, traditional calibration methods cannot meet the requirements for accurate energy metering and cannot provide reliable technical support for the safe and stable operation of the power system.

[0006] Traditional calibration equipment suffers from significant data processing lags. The vast amounts of data collected during the calibration process must be transmitted to backend computers for further analysis and processing, a time-consuming process that also prevents real-time error warnings. By the time a significant error is discovered in an energy meter, significant time may have passed, causing substandard meters to continue operating and posing potential risks to electricity trade settlements. Furthermore, data processing lags hinder the timely detection of potential meter issues, preventing effective preventive measures and increasing risks to power system operations.

[0007] In summary, the traditional three-phase electric energy meter field verification technology has been unable to adapt to the development needs of the modern power system. Especially in the context of large-scale access to new energy, a new three-phase electric energy meter field verification technology is urgently needed to overcome the defects of the existing technology, improve the efficiency and accuracy of field verification, and ensure the safe and stable operation of the power system and the fairness and justice of power trade settlement. Summary of the Invention

[0008] In order to solve the problems existing in the prior art, the present invention provides an on-site verification method based on a wireless clamp-type three-phase power verification device. The method can realize online verification without power outage, improve current measurement accuracy, maintain communication reliability, and improve anti-interference ability. It can meet the complex power quality analysis requirements under new energy access scenarios and provide a more advanced, efficient and reliable technical means for the power metering and verification work of the power system.

[0009] The present invention achieves the above-mentioned purpose through the following technical solutions:

[0010] An on-site calibration method based on a wireless clamp-type three-phase power calibration device, comprising:

[0011] A wireless communication link is established between the three-phase electric energy meter and the portable calibration host through a wireless synchronization trigger module. The wireless communication link adopts adaptive frequency hopping spread spectrum technology, the operating frequency band is 2.4GHz ISM band and dynamically avoids on-site interference frequencies;

[0012] Three independent clamp-on current transformers are used to clamp the A / B / C phases of the three-phase line under test. Each clamp-on current transformer has a built-in dual-mode sampling unit consisting of a Hall effect sensor and a magnetoresistive sensor, and the current signal is fused and processed using the Kalman filter algorithm.

[0013] Synchronous acquisition of three-phase voltage signals, including:

[0014] Sending voltage phase calibration pulses to the electric energy meter under test via a wireless communication link;

[0015] Receive the phase synchronization signal fed back by the measured electric energy meter and trigger the high-precision ADC converter for synchronous sampling. The sampling window width is set to 200μs and the sampling frequency is ≥10kHz, meeting the IEC 61000-4-7 harmonic analysis requirements.

[0016] Based on the improved S-transform algorithm, the collected voltage and current signals are analyzed in time and frequency, and a composite error model including the fundamental wave and the 2nd to 50th harmonics is constructed.

[0017] Error calculation is performed locally through the edge computing unit, and only when the error exceeds the preset threshold does the encrypted data get uploaded to the cloud analysis platform through the 5G communication module;

[0018] A three-dimensional verification report including time scale information, harmonic distribution diagram, and error trend curve is generated. The three-dimensional verification report is encapsulated in an extensible markup language format and embedded with a digital signature.

[0019] According to the present invention, a field verification method based on a wireless clamp-type three-phase power verification device is provided. The clamp-type current transformer includes a main magnetic core and an auxiliary magnetic core. The main magnetic core is made of a nanocrystalline alloy material with a relative magnetic permeability of ≥100,000; the auxiliary magnetic core is made of Permalloy to compensate for high-frequency signal distortion; wherein, a laser-welded copper short-circuit ring is provided at the gap between the magnetic cores to suppress the residual magnetism effect.

[0020] According to an on-site calibration method based on a wireless clamp-type three-phase power calibration device provided by the present invention, the wireless synchronization trigger module includes:

[0021] Rubidium atomic clock reference source, used to provide clock accuracy of ±0.01ppm;

[0022] Bidirectional timestamp exchange unit for achieving nanosecond-level time synchronization between master and slave devices;

[0023] The dynamic spectrum sensing unit monitors weak signal interference below -80dBm in real time through an energy detection algorithm.

[0024] According to an on-site calibration method based on a wireless clamp-type three-phase power calibration device provided by the present invention, the specific implementation method of the wireless synchronization trigger module establishing a wireless communication link includes:

[0025] The rubidium atomic clock reference source provides a clock synchronization signal through the following formula

[0026]

[0027] Where A is the carrier amplitude, f0 = 10 MHz is the nominal frequency, φ0 is the initial phase, K = 1.8 × 10-10 Hz -1 ×V -1is the voltage control coefficient, E((t) is the control voltage signal, and the frequency is locked by the digital phase-locked loop DPLL;

[0028] The two-way timestamp exchange unit uses the two-way time-of-flight method for ranging synchronization. The time synchronization error between the master and slave devices satisfies the following formula:

[0029]

[0030] Among them, T request The time when the master device sends the request frame, T reply is the time when the response frame is returned from the device, c = 2.9979 × 108 m / s is the speed of light, v master 、v slave They are the clock frequency offsets of the master and slave devices, respectively, and sub-nanosecond timestamps are achieved by deploying a time-to-digital converter (TDC) in the FPGA;

[0031] The dynamic spectrum sensing unit realizes spectrum hole recognition based on energy detection algorithm, and its detection probability P d Satisfies the following formula:

[0032]

[0033] Where λ is the detection threshold, N is the noise power estimate, σ 2 w is the channel noise variance, and Q() is the standard normal complementary cumulative distribution function.

[0034] According to an on-site calibration method based on a wireless clamp-type three-phase power calibration device provided by the present invention, when a weak signal below -80dBm is detected, the following frequency switching is triggered, which is expressed as the following formula:

[0035]

[0036] Among them, h i ∈{0,1} is the frequency hopping pattern generated based on the Costas sequence, Δf i is the frequency deviation step, the value range is 1-3MHz, f max =2.4835GHz is the upper limit of the ISM band.

[0037] According to the present invention, an on-site calibration method based on a wireless clamp-type three-phase power calibration device is provided. The wireless communication link is maintained using an improved CSMA / CA protocol, which adds the following to the IEEE 802.15.4 standard:

[0038] Dynamic backoff index Where SNR(t) is the real-time signal-to-noise ratio;

[0039] Priority queue scheduling mechanism, the verification data packet has higher priority than the control instruction packet;

[0040] Forward error correction coding uses a shortened RS (255,223) code with an error correction capability of t = 16 bytes.

[0041] According to an on-site calibration method based on a wireless clamp-type three-phase power calibration device provided by the present invention, the dual-mode sampling unit is composed of a Hall effect sensor and a magnetoresistive sensor to form a complementary measurement channel, wherein:

[0042] The Hall effect sensor measures the dynamic current i H (t), its output voltage satisfies the following formula:

[0043] V H =K H ·i H (t)·[1+α H (T-T0)]+υ n (t)

[0044] Among them, K H =2.5mV / kA is the Hall sensitivity coefficient, α H =0.03% / ℃ is the temperature drift coefficient, T0=25℃ is the reference temperature, v n (t) is white noise, power spectrum density Sn = 10-9V2 / Hz

[0045] The magnetoresistive sensor measures the static current i M (t), the output resistance change rate satisfies the following formula:

[0046]

[0047] Among them, K M =0.12% / A is the magnetoresistance coefficient, f c =10kHz is the cut-off frequency, R0=1kΩ is the reference resistance;

[0048] A dual-mode sensor fusion model is established, and the state variable x(t) = [i(t), φ(t)]T is defined, where i(t) is the effective value of the measured current and φ(t) is the phase angle. The system state equation is:

[0049]

[0050] Where Δt = 50 μs is the sampling interval, ω0 = 2π*50 rad / s is the power frequency angular frequency, w((k-1)) is the process noise, and the covariance matrix Q = diag(10-6, 10-4);

[0051] Then the observation equation is:

[0052]

[0053] Among them, I m is the current amplitude, v(k) is the observation noise, and the covariance matrix R=diag(SnΔt,10-5).

[0054] According to an on-site calibration method based on a wireless clamp-type three-phase power calibration device provided by the present invention, voltage phase calibration pulse generation and transmission include:

[0055] Generate a calibration pulse sequence with a frequency of fp = 500 Hz and a pulse width of tp = 10 μs through the DDS chip;

[0056] Manchester coding is used to modulate the pulse sequence to a 2.4 GHz carrier. The coding formula is:

[0057]

[0058] Among them, a n ∈{+1,-1} is the bipolar coded data, T = 2ms is the pulse period, τ = 20μs is the pulse width, fc = 2.4GHz is the carrier frequency, and φn is the frequency hopping phase generated according to the PN sequence;

[0059] The receiving end of the energy meter under test uses I / Q demodulation to recover the baseband signal and extracts the clock information through the digital phase-locked loop (DPLL).

[0060] According to an on-site verification method based on a wireless clamp-type three-phase power verification device provided by the present invention, the improved S-transformation algorithm implementation includes:

[0061] Define the discrete S transform, which is expressed as the following formula:

[0062]

[0063] Where X[] is the discrete Fourier transform result, n is the frequency index, corresponding to the actual frequency f = n / (NT);

[0064] The Blackman-Harris window function is introduced to suppress spectrum leakage, where the window function coefficient is expressed as the following formula:

[0065]

[0066] Set the harmonic detection threshold, expressed as the following formula:

[0067]

[0068] Among them, h is the harmonic order. When the amplitude of the harmonic component exceeds the γ of the fundamental wave, hSignificant harmonics are marked.

[0069] According to an on-site verification method based on a wireless clamp-type three-phase power verification device provided by the present invention, the generation of the three-dimensional verification report includes:

[0070] Automatically embed and verify the environmental parameters of the site, including:

[0071] Temperature: -40℃~85℃, resolution 0.1℃;

[0072] Humidity: 0~100%RH, resolution 0.1%RH;

[0073] Electromagnetic interference intensity: field strength data of 10kHz~3GHz frequency band;

[0074] Blockchain technology is used to store key verification data and generate tamper-proof verification certificates.

[0075] It can be seen that compared with the prior art, the present invention has the following beneficial effects:

[0076] The adaptive frequency hopping spread spectrum technology of the present invention can monitor the frequency band interference in real time and automatically switch to the frequency with less interference, ensuring that the wireless communication link always remains stable, greatly improving the reliability of verification data transmission, and reducing verification failures or data errors caused by communication problems.

[0077] The wireless communication method of this invention breaks free from the constraints of traditional wired connections. Verifiers no longer need to perform tedious wiring operations, avoiding problems caused by incorrect wiring or poor contact. This not only saves verification time but also reduces operational difficulty, enabling verifiers to perform their work more quickly and conveniently. The advantages of wireless communication are particularly evident in situations where space is limited or wiring is inconvenient, significantly improving verification efficiency and shortening verification cycles.

[0078] The present invention utilizes three independent clamp-on current transformers, each clamped to the A, B, and C phases of the three-phase circuit being measured. Each clamp-on transformer incorporates a dual-mode sampling unit consisting of a Hall-effect sensor and a magnetoresistive sensor. The Hall-effect and magnetoresistive sensors have different operating principles and characteristics, enabling them to sample current signals from different angles. Furthermore, the dual-mode sampling unit combines the advantages of both to more comprehensively and accurately capture the characteristics of the current signal, including current magnitude and phase, providing a more reliable data foundation for subsequent current signal processing and analysis.

[0079] The present invention sends a voltage phase calibration pulse to the electric energy meter under test via a wireless communication link, and receives a phase synchronization signal fed back by the electric energy meter under test, triggering a high-precision ADC converter for synchronous sampling, thereby ensuring that the voltage signal acquisition and the internal signal processing of the electric energy meter are highly synchronized, thereby avoiding measurement errors caused by phase deviation. In electric energy metering, the phase relationship between voltage and current is crucial for power measurement and error analysis, and accurate phase synchronization can improve the accuracy of the verification results. In addition, the high sampling parameter setting of the present invention can meet the needs of harmonic analysis, and provide accurate voltage data for constructing a composite error model containing the fundamental wave and 2-50 harmonics, thereby more comprehensively evaluating the metering performance of the electric energy meter.

[0080] The present invention uses an edge computing unit to perform error calculations locally, and only uploads encrypted data to a cloud analysis platform via a 5G communication module when the error exceeds a preset threshold. The edge computing unit can quickly process and analyze the collected data locally, calculating the error results in a timely manner. This avoids uploading large amounts of raw data directly to the cloud, reducing the amount of data transmitted and the processing pressure on the cloud server, while also improving the real-time nature of data processing. Verification results with errors within the normal range do not need to be uploaded to the cloud, further optimizing the data processing process.

[0081] The present invention generates a three-dimensional verification report including time-stamp information, harmonic distribution diagram, and error trend curve, which intuitively displays multiple key aspects of the verification results. Among them, the time-stamp information records the time point of the verification, which facilitates the tracing and analysis of the verification results in the time dimension; the harmonic distribution diagram clearly presents the content and distribution of each harmonic in the voltage and current signals, which helps to evaluate the impact of harmonics on the measurement error of the electricity meter; the error trend curve reflects the change of the electricity meter error over time, which can timely discover potential problems of the electricity meter. Therefore, the present invention enables verification personnel to have a more comprehensive and in-depth understanding of the metering performance of the electricity meter, providing strong support for subsequent decision-making.

[0082] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 The present invention is a flowchart of an on-site calibration method embodiment based on a wireless clamp-type three-phase power calibration device.

[0084] Figure 2 This is a schematic diagram of a three-phase power verification device in an embodiment of an on-site verification method based on a wireless clamp-type three-phase power verification device of the present invention.

[0085] Figure 3This is a flow chart of synchronously collecting three-phase voltage signals in an embodiment of an on-site verification method based on a wireless clamp-type three-phase power verification device of the present invention.

[0086] Figure 4 It is a principle diagram of a wireless synchronous trigger module in an embodiment of an on-site verification method based on a wireless clamp-type three-phase power verification device of the present invention.

[0087] Figure 5 This is a flowchart of an implementation of a wireless synchronization trigger module establishing a wireless communication link in an embodiment of an on-site verification method based on a wireless clamp-type three-phase power verification device of the present invention.

[0088] Figure 6 This is an application flow chart of a dual-mode sampling unit in an embodiment of an on-site calibration method based on a wireless clamp-type three-phase power calibration device of the present invention.

[0089] Figure 7 This is a flow chart on the generation and transmission of voltage phase calibration pulses in an embodiment of an on-site calibration method based on a wireless clamp-type three-phase power calibration device of the present invention.

[0090] Figure 8 This is a flow chart of an improved S-transformation algorithm in an embodiment of an on-site verification method based on a wireless clamp-type three-phase power verification device of the present invention. DETAILED DESCRIPTION

[0091] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0092] References to "embodiments" herein mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0093] See also Figure 1 and Figure 2 This embodiment provides an on-site calibration method based on a wireless clamp-type three-phase power calibration device, including:

[0094] Step S1: establishing a wireless communication link between the three-phase energy meter and the portable calibration host through a wireless synchronization trigger module. The wireless communication link uses adaptive frequency hopping spread spectrum technology, operates in the 2.4 GHz ISM band, and dynamically avoids on-site interference frequencies.

[0095] Step S2: Using three independent clamp-on current transformers to clamp the A / B / C phases of the three-phase line under test, respectively. Each clamp-on current transformer has a built-in dual-mode sampling unit consisting of a Hall effect sensor and a magnetoresistive sensor, and uses a Kalman filter algorithm to achieve current signal fusion processing.

[0096] Step S3, synchronously collect the three-phase voltage signals, such as Figure 3 As shown, specifically including:

[0097] Step S31, sending a voltage phase calibration pulse to the electric energy meter under test via a wireless communication link;

[0098] Step S32: receiving a phase synchronization signal fed back by the measured electric energy meter, triggering a high-precision ADC converter to perform synchronous sampling; wherein the sampling window width is set to 200 μs, and the sampling frequency is ≥10 kHz, meeting the IEC 61000-4-7 harmonic analysis requirements;

[0099] Step S33, performing a time-frequency joint analysis on the collected voltage and current signals based on an improved S-transform algorithm, and constructing a composite error model including the fundamental wave and 2nd to 50th harmonics;

[0100] Step S34: Error calculation is performed locally by the edge computing unit, and only when the error exceeds a preset threshold is the encrypted data uploaded to the cloud analysis platform via the 5G communication module;

[0101] Step S4: Generate a three-dimensional verification report including time scale information, harmonic distribution diagram, and error trend curve. The three-dimensional verification report is encapsulated in an extensible markup language format and embedded with a digital signature.

[0102] In this embodiment, the clamp-on current transformer includes a main magnetic core and an auxiliary magnetic core. The main magnetic core is made of a nanocrystalline alloy material with a relative magnetic permeability of ≥100,000; the auxiliary magnetic core is made of Permalloy to compensate for high-frequency signal distortion. Laser-welded copper short-circuit rings are provided at the gaps between the magnetic cores to suppress the residual magnetism effect.

[0103] Among them, the clamp-on current transformer adopts a clamp-shaped design, which can be easily clamped on the current loop of the electric energy meter under test. It has a built-in high-precision dual-mode sampling unit to ensure measurement accuracy, and an integrated wireless transmission module to convert the collected measurement data and send it to the host.

[0104] In this embodiment, if Figure 2As shown, the portable calibration unit utilizes a high-performance microprocessor as its core control unit for data processing and error calculation. It is equipped with a high-definition display for real-time display of measurement data and calculation results. An integrated wireless transmission module enables long-distance data transmission with multiple wireless current clamp meters. The wireless communication module utilizes a low-power design, ensuring long-term instrument operation. The insulated housing is constructed of high-strength, insulating materials for safe use. Its snap-on design allows the unit to be securely fastened to the junction box without damaging the meter. Three Type-C ports are available for connecting to dedicated wired current clamp meters to collect meter current. The unit simultaneously collects three-phase voltage signals, enabling meter voltage and pulse acquisition and meter data reading. A built-in GPS module receives GPS signals, calibrates the device's time upon reception, and also calibrates the meter's time. A built-in WiFi / Bluetooth integrated module enables communication and data transmission with a handheld device, displaying measured energy parameters on the app interface. Software-defined data processing algorithms are implemented for filtering, calibration, and error analysis of the measured data.

[0105] Fix the portable calibration host on the electric energy meter by using the knob. Press the probe at the bottom of the host to contact the various signal contacts of the electric energy meter. When the host starts measuring, it can obtain electrical parameters, read the electric energy meter pulse and other data, and display the obtained parameters on the display screen. Clamp the three wireless current clamp meters on the current loops of the three phases A / B / C of the electric energy meter to be measured. After the clamp meter starts measuring, the wireless module sends the collected and converted current signal to the host. The host receives the data and calculates the electric energy error of the electric energy meter to be measured. The current parameters can also be obtained by directly connecting the host to the wired clamp meter. The host screen displays the final measurement results and can store data. The host calculates the phase difference of the three-phase voltage and current, compares it with the pulse output of the electric energy meter, and generates an error report. The host has an embedded GPS / Beidou dual-mode timing module to realize meter clock calibration.

[0106] Integrated Bluetooth / Wi-Fi dual-mode communication enables real-time data transmission between the calibrator and handheld device.

[0107] In this embodiment, if Figure 4 As shown, the wireless synchronization trigger module includes:

[0108] Rubidium atomic clock reference source, used to provide clock accuracy of ±0.01ppm;

[0109] Bidirectional timestamp exchange unit for achieving nanosecond-level time synchronization between master and slave devices;

[0110] The dynamic spectrum sensing unit monitors weak signal interference below -80dBm in real time through an energy detection algorithm.

[0111] Specifically, such as Figure 5As shown, the implementation method of the wireless synchronization trigger module in this embodiment to establish a wireless communication link includes:

[0112] The rubidium atomic clock reference source provides a clock synchronization signal through the following formula

[0113]

[0114] Where A is the carrier amplitude, f0 = 10 MHz is the nominal frequency, φ0 is the initial phase, K = 1.8 × 10-10 Hz -1 ×V -1 is the voltage control coefficient, E((t) is the control voltage signal, and the frequency is locked by the digital phase-locked loop DPLL;

[0115] The two-way timestamp exchange unit uses the two-way time-of-flight method for ranging synchronization. The time synchronization error between the master and slave devices satisfies the following formula:

[0116]

[0117] Among them, T request The time when the master device sends the request frame, T reply is the time when the response frame is returned from the device, c = 2.9979 × 108 m / s is the speed of light, v master 、v slave They are the clock frequency offsets of the master and slave devices, respectively, and sub-nanosecond timestamps are achieved by deploying a time-to-digital converter (TDC) in the FPGA;

[0118] The dynamic spectrum sensing unit realizes spectrum hole recognition based on energy detection algorithm, and its detection probability P d Satisfies the following formula:

[0119]

[0120] Where λ is the detection threshold, N is the noise power estimate, σ 2 w is the channel noise variance, and Q() is the standard normal complementary cumulative distribution function.

[0121] When a weak signal below -80dBm is detected, the following frequency switching is triggered, which is expressed as the following formula:

[0122]

[0123] Among them, h i ∈{0,1} is the frequency hopping pattern generated based on the Costas sequence, Δf i is the frequency deviation step, the value range is 1-3MHz, f max =2.4835GHz is the upper limit of the ISM band.

[0124] In this embodiment, the wireless communication link is maintained using an improved CSMA / CA protocol, which adds the following to the IEEE 802.15.4 standard:

[0125] Dynamic backoff index Where SNR(t) is the real-time signal-to-noise ratio;

[0126] Priority queue scheduling mechanism, the verification data packet has higher priority than the control instruction packet;

[0127] Forward error correction coding uses a shortened RS (255,223) code with an error correction capability of t = 16 bytes.

[0128] In summary, this embodiment combines a rubidium atomic clock with a digital phase-locked loop to improve clock accuracy to ±0.01ppm, which is two orders of magnitude higher than the traditional crystal oscillator solution, providing a basic guarantee for the synchronous acquisition of three-phase parameters. The FPGA's built-in TDC is used to achieve time measurement with a resolution of 65ps, ensuring that the phase synchronization error between the master and slave devices is ≤500ps, meeting the IEC61850 standard's requirements for sample value synchronization. By combining an energy detection algorithm with a Costas frequency hopping pattern, frequency switching is achieved 200 times per second within the 2.4GHz frequency band, allowing the communication link to maintain a transmission success rate of ≥95% in complex electromagnetic environments (such as in the presence of Wi-Fi and Bluetooth interference). The improved CSMA / CA protocol dynamically adjusts the backoff window based on channel quality, increasing network throughput by 40% when the SNR is 15dB. At the same time, RS coding reduces the bit error rate from 10-3 to 10-6.

[0129] In this embodiment, if Figure 6 As shown in FIG, the dual-mode sampling unit is composed of a Hall effect sensor and a magnetoresistive sensor to form a complementary measurement channel, where:

[0130] The Hall effect sensor measures the dynamic current i H (t), its output voltage satisfies the following formula:

[0131] V H =K H ·i H (t)·[1+α H (T-T0)]+υ n (t)

[0132] Among them, K H =2.5mV / kA is the Hall sensitivity coefficient, α H =0.03% / ℃ is the temperature drift coefficient, T0=25℃ is the reference temperature, v n (t) is white noise, with power spectrum density Sn=10-9V2 / Hz.

[0133] The magnetoresistive sensor measures the static current i M (t), the output resistance change rate satisfies the following formula:

[0134]

[0135] Among them, K M =0.12% / A is the magnetoresistance coefficient, f c =10kHz is the cut-off frequency, R0=1kΩ is the reference resistance;

[0136] A dual-mode sensor fusion model is established, and the state variable x(t) = [i(t), φ(t)]T is defined, where i(t) is the effective value of the measured current and φ(t) is the phase angle. The system state equation is:

[0137]

[0138] Where Δt = 50 μs is the sampling interval, ω0 = 2π*50 rad / s is the power frequency angular frequency, w(k-1) is the process noise, and the covariance matrix Q = diag(10-6, 10-4);

[0139] Then the observation equation is:

[0140]

[0141] Among them, I m is the current amplitude, v(k) is the observation noise, and the covariance matrix R=diag(SnΔt,10-5).

[0142] The extended Kalman filter is used to realize the state estimation of nonlinear system. The specific steps include:

[0143] Time update, expressed as the following formula:

[0144]

[0145] P(k)=F(k-1)P + (k-1)F T (k-1)+Q(k-1)

[0146] Where F(k-1) is the Jacobian matrix of the state transfer matrix

[0147] The measurement update is expressed as follows:

[0148] K(k)=P - (k)H T (k)[H(k)P - (k)H T (k)+R(k)] -1

[0149]

[0150] P + (k)=[IK(k)H(k)]P - (k)

[0151] Where H(k) is the Jacobian matrix of the observation equation and I is the identity matrix.

[0152] Optimize the filtering parameters through the adaptive adjustment mechanism: when |Δ I ∣=∣i H -i M When >0.5%In, I n is the rated current, triggering covariance matching, expressed as the following formula:

[0153]

[0154] Among them, λ = 0.95 is the forgetting factor, N = 10 is the sliding window length

[0155] When a DC component is detected (f(k) < 5 Hz), the filter switches to the unscented Kalman filter mode.

[0156] In summary, this embodiment leverages the complementary advantages of Hall sensors and magnetoresistive sensors to expand the dynamic range of current measurement to 0.1A to 10kA, a three-order-of-magnitude increase compared to a single-sensor solution. It also reduces the impact of temperature drift from 0.3% / °C to 0.02% / °C. By establishing an accurate sensor model that incorporates temperature effects and frequency characteristics, the current amplitude measurement error is reduced from 0.2% in traditional solutions to 0.02%, and the phase error is reduced from 0.1° to 0.01°. Through covariance matching and filter mode switching, optimal estimation performance is maintained in both dynamic load (such as motor startup) and steady-state load scenarios, ensuring a total harmonic distortion (THD) measurement error of ≤0.1%. The segmented magnetic core, combined with a copper shorting ring, reduces core loss from 0.5W / kg in traditional structures to 0.1W / kg, while increasing the high-frequency response cutoff frequency from 5kHz to 50kHz, meeting the harmonic analysis requirements of IEC 61000-4-7.

[0157] In the above step S31, Figure 7 As shown, the voltage phase calibration pulse generation and transmission includes:

[0158] A calibration pulse sequence with a frequency fp = 500 Hz and a pulse width tp = 10 μs is generated by a DDS (direct digital frequency synthesis) chip;

[0159] Manchester coding is used to modulate the pulse sequence to a 2.4 GHz carrier. The coding formula is:

[0160]

[0161] Among them, a n ∈{+1,-1} is the bipolar coded data, T = 2ms is the pulse period, τ = 20μs is the pulse width, fc = 2.4GHz is the carrier frequency, and φn is the frequency hopping phase generated according to the PN sequence;

[0162] The receiving end of the energy meter under test uses I / Q demodulation to recover the baseband signal and extracts the clock information through the digital phase-locked loop (DPLL).

[0163] The phase difference between the master and slave devices is calculated using the following formula:

[0164]

[0165] V master (k), V slave (k) are the sampling voltage sequences of the master and slave devices, respectively. N=200 is the length of the correlation operation window. When |Δφ|>0.1°, ADC synchronization adjustment is triggered.

[0166] In the above step S32, the high-precision ADC synchronous sampling control includes:

[0167] Use a dual-channel Σ-Δ ADC (AD7134) with the following configuration parameters:

[0168] Sampling rate fs = 12.8kHz

[0169] Oversampling rate OSR = 256

[0170] Signal-to-noise ratio (SNR) = 112dB

[0171] The sampling trigger delay chain is realized by FPGA, with the minimum adjustment step Δt adj =50ps, satisfying: t actual =t ideal ±n*Δt adj (n=0,1,…,19)

[0172] In the above step S33, the local error calculation adopts the following composite error model:

[0173]

[0174] Among them, E amp =|I^-I| / I rated is the amplitude error, E phase =|Δφ| is the phase error; is the total harmonic distortion, and the weight coefficients w1 = 0.5, w2 = 0.3, and w3 = 0.2 are set according to the electric energy measurement standard.

[0175] In the above step S34, 5G data upload adopts segmented encrypted transmission, uses AES-256-GCM algorithm to encrypt and verify the data packet, is encapsulated through UDP protocol, and the destination port number = 55555. The upload trigger condition is: Etotal>0.2% or ETHD>5% for three consecutive cycles.

[0176] Among them, Figure 8 As shown, the improved S transform algorithm is specifically implemented as follows:

[0177] The original signal is processed in segments, with the length of each segment being an integer power of 2;

[0178] Use fast Fourier transform (FFT) to accelerate convolution calculation;

[0179] The Hanning window function is introduced to suppress spectrum leakage;

[0180] Construct a three-dimensional time-frequency matrix, where the X-axis is time, the Y-axis is frequency, and the Z-axis is amplitude / phase information.

[0181] Furthermore, the discrete S transform is defined and expressed as the following formula:

[0182]

[0183] Where X[] is the discrete Fourier transform result, n is the frequency index, corresponding to the actual frequency f = n / (NT);

[0184] Furthermore, the Blackman-Harris window function is introduced to suppress spectrum leakage, where the window function coefficient is expressed as the following formula:

[0185]

[0186] Furthermore, the harmonic detection threshold is set, which is expressed as the following formula:

[0187]

[0188] Among them, h is the harmonic order. When the amplitude of the harmonic component exceeds the γ of the fundamental wave, h Significant harmonics are marked.

[0189] In summary, this embodiment controls the master-slave sampling phase synchronization error within ±500ps by generating calibration pulses using DDS combined with FPGA delay chain adjustment, meeting the 0.02-level electricity meter calibration requirements. The Blackman-Harris window function is combined with the improved S-transform to reduce the harmonic amplitude measurement error from 2% of the traditional FFT to 0.05%, and the phase measurement error from 0.5° to 0.01°. The composite error model comprehensively considers amplitude, phase, and harmonic indicators, and through dynamic weight allocation, it increases the detection sensitivity of key error terms by three times. At the same time, 5G segmented encrypted transmission improves data transmission security to the FIPS 140-2 Level 3 standard. The hierarchical threshold setting ensures the accuracy of low-order harmonic detection while reducing the false alarm rate of high-order harmonics (25-50th) from 20% to 2%, adapting to the complex power quality monitoring needs in new energy access scenarios.

[0190] In the above step S4, the generation of the three-dimensional verification report includes:

[0191] Automatically embed and verify the environmental parameters of the site, including:

[0192] Temperature: -40℃~85℃, resolution 0.1℃;

[0193] Humidity: 0~100%RH, resolution 0.1%RH;

[0194] Electromagnetic interference intensity: field strength data of 10kHz~3GHz frequency band;

[0195] Blockchain technology is used to store key verification data and generate tamper-proof verification certificates.

[0196] In summary, the method provided by this embodiment breaks free from the constraints of traditional wired connections. Verifiers no longer need to perform tedious wiring operations, avoiding problems caused by incorrect wiring or poor contact. This not only saves verification time but also reduces operational difficulty, enabling verifiers to perform their work more quickly and conveniently. Wireless communication offers significant advantages, particularly in situations where space is limited or wiring is difficult, significantly improving verification efficiency and shortening verification cycles.

[0197] Furthermore, the adaptive frequency hopping spread spectrum technology of this embodiment can monitor the frequency band interference in real time and automatically switch to the frequency with less interference, ensuring that the wireless communication link always remains stable, greatly improving the reliability of verification data transmission, and reducing verification failures or data errors caused by communication problems.

[0198] Furthermore, this embodiment utilizes three independent clamp-on current transformers, each clamped to the A / B / C phases of the three-phase line being measured. Each clamp-on transformer incorporates a dual-mode sampling unit consisting of a Hall-effect sensor and a magnetoresistive sensor. The Hall-effect and magnetoresistive sensors have different operating principles and characteristics, enabling them to sample current signals from different angles. Furthermore, the dual-mode sampling unit combines the advantages of both to more comprehensively and accurately capture the characteristics of the current signal, including current magnitude and phase information, providing a more reliable data foundation for subsequent current signal processing and analysis.

[0199] Furthermore, this embodiment sends a voltage phase calibration pulse to the electric energy meter under test via a wireless communication link, and receives a phase synchronization signal fed back by the electric energy meter under test, triggering a high-precision ADC converter for synchronous sampling, thereby ensuring that the voltage signal acquisition and the internal signal processing of the electric energy meter are highly synchronized, thereby avoiding measurement errors caused by phase deviation. In electric energy metering, the phase relationship between voltage and current is crucial for power measurement and error analysis, and accurate phase synchronization can improve the accuracy of the verification results. In addition, the high sampling parameter setting of the present invention can meet the requirements of harmonic analysis, and provide accurate voltage data for constructing a composite error model containing the fundamental wave and 2-50 harmonics, thereby more comprehensively evaluating the metering performance of the electric energy meter.

[0200] Furthermore, this embodiment performs error calculations locally through the edge computing unit, and only uploads encrypted data to the cloud analysis platform via the 5G communication module when the error exceeds a preset threshold. The edge computing unit can quickly process and analyze the collected data locally and calculate the error results in a timely manner. This can avoid uploading large amounts of raw data directly to the cloud, reducing the amount of data transmitted and the processing pressure on the cloud server, while also improving the real-time performance of data processing. For some verification results with errors within the normal range, there is no need to upload them to the cloud, further optimizing the data processing process.

[0201] Furthermore, this embodiment generates a three-dimensional verification report including time stamp information, harmonic distribution diagram, and error trend curve, which intuitively displays multiple key aspects of the verification results. Among them, the time stamp information records the time point of the verification, which facilitates the tracing and analysis of the verification results in the time dimension; the harmonic distribution diagram clearly presents the content and distribution of each harmonic in the voltage and current signals, which helps to evaluate the impact of harmonics on the metering error of the electricity meter; the error trend curve reflects the change of the electricity meter error over time, which can timely discover potential problems of the electricity meter. Therefore, the present invention enables verification personnel to have a more comprehensive and in-depth understanding of the metering performance of the electricity meter, providing strong support for subsequent decision-making.

[0202] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0203] The above embodiments are only preferred embodiments of the present invention and cannot be used to limit the scope of protection of the present invention. Any non-substantial changes and replacements made by technicians in this field on the basis of the present invention fall within the scope of protection required by the present invention.

Claims

1. An on-site calibration method based on a wireless clamp-type three-phase power calibration device, characterized in that: include: A wireless communication link is established between the three-phase energy meter and the portable calibration host through a wireless synchronization trigger module. The wireless communication link adopts adaptive frequency hopping spread spectrum technology, operates in the 2.4GHz ISM band and dynamically avoids on-site interference frequencies. Three independent clamp-on current transformers are used to clamp the A / B / C phases of the three-phase line under test. Each clamp-on current transformer has a built-in dual-mode sampling unit consisting of a Hall effect sensor and a magnetoresistive sensor, and the current signal is fused and processed using the Kalman filter algorithm. Synchronous acquisition of three-phase voltage signals, including: Sending voltage phase calibration pulses to the electric energy meter under test via a wireless communication link; Receive the phase synchronization signal fed back by the measured electric energy meter and trigger the high-precision ADC converter for synchronous sampling. The sampling window width is set to 200μs and the sampling frequency is ≥10kHz, meeting the IEC 61000-4-7 harmonic analysis requirements. Based on the improved S-transform algorithm, the collected voltage and current signals are analyzed in time and frequency, and a composite error model including the fundamental wave and the 2nd to 50th harmonics is constructed. Error calculation is performed locally through the edge computing unit, and only when the error exceeds the preset threshold does the encrypted data get uploaded to the cloud analysis platform through the 5G communication module; A three-dimensional verification report including time scale information, harmonic distribution diagram, and error trend curve is generated. The three-dimensional verification report is encapsulated in an extensible markup language format and embedded with a digital signature.

2. The method according to claim 1, wherein: The clamp-on current transformer includes a main magnetic core and an auxiliary magnetic core. The main magnetic core is made of nanocrystalline alloy material with a relative magnetic permeability of ≥100,000; the auxiliary magnetic core is made of Permalloy to compensate for high-frequency signal distortion; and a laser-welded copper short-circuit ring is provided at the gap between the magnetic cores to suppress the residual magnetism effect.

3. The method according to claim 1, wherein: The wireless synchronization trigger module includes: Rubidium atomic clock reference source, used to provide clock accuracy of ±0.01ppm; Bidirectional timestamp exchange unit for achieving nanosecond-level time synchronization between master and slave devices; The dynamic spectrum sensing unit monitors weak signal interference below -80dBm in real time through an energy detection algorithm.

4. The method according to claim 3, wherein: The specific implementation method of the wireless synchronization trigger module establishing a wireless communication link includes: The rubidium atomic clock reference source provides a clock synchronization signal through the following formula Where A is the carrier amplitude, f0 is the nominal frequency, φ0 is the initial phase, K is the voltage control coefficient, E(t) is the control voltage signal, and the frequency is locked by the digital phase-locked loop DPLL; The two-way timestamp exchange unit uses the two-way time-of-flight method for ranging synchronization. The time synchronization error between the master and slave devices satisfies the following formula: Among them, T request The time when the master device sends the request frame, T reply is the time when the response frame is returned from the device, c is the speed of light, v master 、v slave They are the clock frequency offsets of the master and slave devices, respectively, and sub-nanosecond timestamps are achieved by deploying a time-to-digital converter (TDC) in the FPGA; The dynamic spectrum sensing unit realizes spectrum hole recognition based on energy detection algorithm, and its detection probability P d Satisfies the following formula: Where λ is the detection threshold, N is the noise power estimate, σ 2 w is the channel noise variance, and Q() is the standard normal complementary cumulative distribution function.

5. The method according to claim 4, characterized in that: When a weak signal below -80dBm is detected, the following frequency switching is triggered, which is expressed as the following formula: Among them, h i is the frequency hopping pattern generated based on the Costas sequence, Δf i is the frequency deviation step, f max It is the upper limit of the ISM band.

6. The method according to claim 1, wherein: The wireless communication link is maintained using an improved CSMA / CA protocol, which adds the following to the IEEE 802.15.4 standard: Dynamic backoff index Where SNR((t) is the real-time signal-to-noise ratio; Priority queue scheduling mechanism, the verification data packet has higher priority than the control instruction packet; Forward error correction coding uses a shortened RS (255,223) code with an error correction capability of t = 16 bytes.

7. The method according to claim 1, wherein: The dual-mode sampling unit comprises a Hall effect sensor and a magnetoresistive sensor forming a complementary measurement channel, wherein: The Hall effect sensor measures the dynamic current i H (t), its output voltage satisfies the following formula: V H =K H ·i H (t)·[1+α H (T-T0)]+v n (t) Among them, K H is the Hall sensitivity coefficient, α H is the temperature drift coefficient, T0 is the reference temperature, v n ((t) is white noise; The magnetoresistive sensor measures the static current i M (t), the output resistance change rate satisfies the following formula: Among them, K M is the magnetoresistance coefficient, f c is the cut-off frequency, R0 is the reference resistance; A dual-mode sensor fusion model is established, and the state variable x(t) = [i(t), φ(t)]T is defined, where i(t) is the effective value of the measured current and φ(t) is the phase angle. The system state equation is: Where Δt is the sampling interval, ω0 is the power frequency angular frequency, and w(k-1) is the process noise; Then the observation equation is: Among them, I m is the current amplitude, and v(k) is the observation noise.

8. The method according to claim 1, characterized in that Voltage phase alignment pulse generation and transmission includes: Generate a calibration pulse sequence with a frequency of fp = 500 Hz and a pulse width of tp = 10 μs through the DDS chip; Manchester coding is used to modulate the pulse sequence to a 2.4 GHz carrier. The coding formula is: Among them, a n is bipolar coded data, T is the pulse period, τ is the pulse width, fc is the carrier frequency, φ n is the frequency hopping phase generated according to the PN sequence; The receiving end of the energy meter under test uses I / Q demodulation to recover the baseband signal and extracts the clock information through the digital phase-locked loop (DPLL).

9. The method according to claim 1, wherein: The improved S-transform algorithm implementation includes: Define the discrete S transform, which is expressed as the following formula: Where X[] is the discrete Fourier transform result, n is the frequency index, corresponding to the actual frequency f = n / (NT); The Blackman-Harris window function is introduced to suppress spectrum leakage, where the window function coefficient is expressed as the following formula: Set the harmonic detection threshold, expressed as the following formula: Among them, h is the harmonic order. When the amplitude of the harmonic component exceeds the γ of the fundamental wave, h Significant harmonics are marked.

10. The method according to claim 1, wherein: The generation of the three-dimensional verification report includes: Automatically embed and verify the environmental parameters of the site, including: Temperature: -40℃~85℃, resolution 0.1℃; Humidity: 0~100%RH, resolution 0.1%RH; Electromagnetic interference intensity: field strength data of 10kHz~3GHz frequency band; Blockchain technology is used to store key verification data and generate tamper-proof verification certificates.

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