A multifunctional instrument device and an abnormal data partition recording method

Abstract

The present application belongs to the technical field of power grid monitoring, and particularly relates to a multifunctional instrument device and an abnormal data partition recording method, which comprises the following steps: continuously collecting voltage and current waveform data by the device; calculating voltage effective value, current effective value, frequency and harmonic content; respectively judging harmonic abnormality, low voltage abnormality, current abnormality and frequency abnormality; generating an abnormal record when any abnormal condition is established; selecting a corresponding memory area according to the abnormal type; calculating the fault change rate and the priority; sorting and storing in the corresponding memory area according to the rule of 10 records per round; entering the next round of recording stage when the current round of records reaches 10; and reading the fault records according to the abnormal type, round and priority by the master station or the local display module.

Description

Technical Field

[0001] This invention belongs to the field of power grid monitoring technology, specifically relating to a multi-functional instrument device and a method for recording abnormal data in partitions. Background Technology

[0002] With the large-scale integration of low-voltage distribution networks, distributed photovoltaic systems, electric vehicle charging equipment, and various nonlinear loads, power quality parameters such as voltage, current, frequency, and harmonics on the distribution side are fluctuating more frequently. Multifunctional instruments are typically installed in distribution boxes, grid connection points, user-side incoming lines, or equipment control cabinets to collect operational data such as AC voltage, current, frequency, power consumption, and harmonics, providing fundamental data for grid operation monitoring, equipment protection, and fault analysis.

[0003] Existing multi-functional instruments typically acquire AC voltage and current data through voltage sampling circuits, current sampling circuits, and metering chips or microprocessors, and calculate parameters such as RMS values, frequency, power, and energy. They can generally perform routine measurements of voltage, current, power, and energy, and can also issue over-limit alarms based on set thresholds. When a measured value exceeds a preset upper limit or falls below a preset lower limit, the device generates an alarm signal and writes the alarm time, alarm type, and partial measured values ​​to a unified event log area. Some instruments can also record harmonic content or total harmonic distortion (THD), but harmonic anomalies, voltage anomalies, current anomalies, and frequency anomalies usually lack independent storage partitions and record priority control based on fault change rates. In actual fault analysis, alarm status or a small number of unified event records often cannot accurately reflect the fault type, fault change process, and fault severity.

[0004] Existing multi-functional instrument devices have the following disadvantages: 1) The method of recording abnormal data is relatively simple. Different types of fault data are mixed and stored in the same event area. When multiple abnormalities occur in a short period of time, the later general abnormalities may cover the earlier important abnormalities, resulting in the loss of critical fault data. 2) The judgment conditions for harmonics, low voltage, short circuit or current abnormality, and frequency abnormality are not complete enough. In particular, the judgment of harmonic abnormality is based on a single measurement value or manual review of reports. There is a lack of clear formulas and algorithms, which is not conducive to automatic identification and automatic recording. 3) Faults are usually recorded in chronological order, which cannot compare the rate of change of faults, nor can it prioritize the storage of abnormal data with a large rate of change of faults; when storage space is limited, more serious and rapidly changing fault information may not be prioritized for retention. 4) The absence of separate memory areas for different exception types and the lack of a "fixed number of records per round" recording mechanism resulted in unclear data management. When the main station reads or queries locally, it needs to filter fault information from a large number of mixed records, which increases the difficulty of fault analysis.

[0005] The information disclosed in this background section is intended only to enhance the understanding of the overall background of the invention and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide a multifunctional instrument device and an abnormal data partitioning recording method, which simultaneously realizes harmonic detection, low voltage monitoring, short circuit or current abnormality detection, and frequency abnormality monitoring in the multifunctional instrument device, and writes the fault data into the harmonic memory area, voltage memory area, current memory area and frequency memory area respectively according to the abnormality type.

[0007] To achieve the above objectives, the present invention provides the following technical solution: A multi-functional instrument device, characterized in that it comprises: The voltage sampling module is used to continuously acquire the AC voltage waveform of the circuit under test; The current sampling module is used to continuously acquire the AC current waveform of the circuit under test; The data processing module calculates the effective value of voltage, effective value of current, frequency, harmonic content, and fault change rate based on the sampled data. The anomaly detection module determines whether harmonic anomalies, low voltage anomalies, current anomalies, or frequency anomalies have occurred based on set thresholds. The partitioned storage module includes a harmonic memory area, a voltage memory area, a current memory area, and a frequency memory area, which are used to store different types of abnormal data into the corresponding memory areas. The priority sorting module determines the storage order of abnormal records based on the magnitude of the fault change rate.

[0008] The present invention also provides an abnormal data partitioning and recording method for the above-mentioned multifunctional instrument device, characterized by comprising the following steps: S1. The device continuously collects voltage and current waveform data; S2. Calculate the effective value of voltage, the effective value of current, frequency, and harmonic content; S3. Perform harmonic anomaly, low voltage anomaly, current anomaly, and frequency anomaly judgments respectively; generate an anomaly record when any anomaly condition is met. S4. Select the corresponding memory area according to the exception type, and record each memory area in rounds. S5. Calculate the failure change rate and priority; S6. Sorting and storing fault records in the corresponding memory area using a fixed number of records per round; when the number of records in the current round exceeds the fixed number, proceed to the next round of recording. S7. The main station or local display module reads fault records according to the fault type, round, and priority.

[0009] Preferably, each anomaly record includes at least the anomaly occurrence time, anomaly type, anomaly judgment value, fault change rate, priority value, current round number, and sampled data or valid value data.

[0010] Preferably, the device acquires instantaneous voltage and current values, and RMS voltage values ​​at a fixed sampling frequency or a configurable sampling frequency. and the effective value of current The calculation formula is as follows: ; ; in, The number of sampling points contained within a single calculation window; This is the instantaneous voltage value. This is the instantaneous value of the current; Number of the current calculation window. This refers to the sampling point number within the window.

[0011] Preferably, the Discrete Fourier Transform (DFT) algorithm or the Fast Fourier Transform (FFT) algorithm is used for harmonic detection, and the total harmonic distortion (THD) of the voltage is calculated. and total harmonic distortion of current The formula is as follows: ; ; in, For the fundamental component, For the first The effective component of the second voltage harmonic; For the fundamental component, For the first Effective components of secondary current harmonics; when Greater than the voltage harmonic threshold, or If the content of a harmonic exceeds the current harmonic threshold, or if the content of any specified harmonic exceeds the corresponding set threshold, it is judged as a harmonic anomaly; the harmonic anomaly data is written to the harmonic memory area.

[0012] As a preferred method, low voltage is monitored by comparing the effective voltage value with the rated voltage; low voltage anomaly data is written to the voltage memory area. when At that time, it was determined to be a low voltage abnormality; among them, The rated voltage is denoted by , and the low voltage threshold coefficient is denoted by .

[0013] As a preferred method, short circuits or current anomalies are detected by comparing the effective value of the current with the rated current and a set current threshold; the current anomaly data is written into the current memory area. when When this occurs, it is determined to be a short circuit or overcurrent abnormality; when When this occurs, it is determined to be a low current abnormality; in, Rated current, This is the short-circuit or overcurrent threshold coefficient. The current threshold is low.

[0014] Preferably, the zero-crossing period method, phase-locked loop method, or fundamental phase change method are used for frequency monitoring to calculate the current frequency. Abnormal frequency data is written to the frequency memory area. when When the frequency is abnormal, it is determined to be abnormal; among them, This is the frequency deviation threshold.

[0015] Preferably, the device calculates the fault change rate and establishes a fault priority based on the change rate of each anomaly type; the formula for calculating the fault change rate is as follows: ; in, For characteristic quantity, To compare the number of computation windows corresponding to the interval, Take the rated value, set the threshold, or the measured value from the previous comparison window; The formula for calculating fault priority is as follows: ; in, This represents the fault priority value. , , , These represent the changes in harmonics, voltage, current, and frequency, respectively. These are the weighting coefficients. Add weights to exception types.

[0016] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention can simultaneously realize the automatic detection of harmonics, low voltage, short circuit or current abnormality, and frequency abnormality in a multi-functional instrument device, solving the problem that traditional instruments only perform simple over-limit alarms and the abnormality type identification is incomplete.

[0017] (2) By setting up a harmonic memory area, a voltage memory area, a current memory area and a frequency memory area, the present invention enables data of different fault types to be stored separately, which facilitates the main station or field personnel to quickly query data according to the fault type and improves the efficiency of fault analysis.

[0018] (3) The present invention calculates the priority of abnormal data by fault change rate, so that fault data that changes rapidly and has a great impact is saved first, avoiding general fluctuation data from covering key fault data, and improving the utilization efficiency of limited storage space.

[0019] (4) The present invention adopts a round-by-round storage mechanism of 10 fault records per round, which can maintain the record order and round relationship when anomalies occur frequently, which is convenient for local query, communication upload and subsequent data traceability. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the method flow according to an embodiment of the present invention. Detailed Implementation

[0021] The technical solution of this invention patent will be clearly and completely described below. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this invention.

[0022] In the description of this invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship are based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention.

[0023] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to a connection within two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0024] The multifunctional instrument device of this invention includes a voltage sampling module, a current sampling module, a data processing module, an anomaly detection module, a partitioned storage module, and a priority sorting module. The voltage and current sampling modules continuously collect AC voltage and current waveforms of the circuit under test; the data processing module calculates the effective voltage value, effective current value, frequency, harmonic content, and fault change rate based on the sampled data; the anomaly detection module determines whether harmonic anomalies, low voltage anomalies, current anomalies, or frequency anomalies have occurred based on set thresholds; the partitioned storage module stores different types of anomaly data into corresponding memory areas; and the priority sorting module determines the storage order of anomaly records based on the magnitude of the fault change rate.

[0025] See attached document Figure 1 The present invention provides a method for partitioning and recording abnormal data for a multi-functional instrument device, which specifically includes the following steps: the device continuously collects voltage and current waveform data; calculates the effective value of voltage, effective value of current, frequency, and harmonic content; performs harmonic anomaly, low voltage anomaly, current anomaly, and frequency anomaly judgment respectively; generates an anomaly record when any anomaly condition is met; selects the corresponding memory area according to the anomaly type; calculates the fault change rate and priority; sorts and stores the records in the corresponding memory area according to the rule of 10 records per round; when the current round of records is full (10 records), it enters the next round of recording stage; the main station or local display module can read the fault records according to the anomaly type, round, and priority.

[0026] The device acquires instantaneous voltage and current values ​​at a fixed or configurable sampling frequency. Assume a calculation window contains... Each sampling point has an instantaneous voltage value. The instantaneous value of the current is ,in Number of the current calculation window. This represents the sampling point number within the window. The formulas for calculating the RMS voltage and RMS current values ​​are as follows:

[0027]

[0028] In the formula, This represents the effective voltage value for the current calculation window. This represents the effective current value for the current calculation window.

[0029] Harmonic detection employs either the Discrete Fourier Transform (DFT) algorithm or the Fast Fourier Transform (FFT) algorithm. Taking voltage harmonics as an example, the first... The effective components of the second harmonic can be calculated using the following formula:

[0030] According to the fundamental component and the 2nd to the 1st Calculate the total harmonic distortion of the voltage using the second harmonic component:

[0031] Taking current harmonics as an example, the first The effective components of the second harmonic can be calculated using the following formula:

[0032] According to the fundamental component and the 2nd to the 1st Calculate the total harmonic distortion (THD) of the current using the second harmonic component:

[0033] when Greater than the voltage harmonic threshold ,or Greater than the current harmonic threshold If the content of any specified harmonic exceeds the corresponding set threshold, it is judged as a harmonic anomaly, and the abnormal data is written to the harmonic memory area.

[0034] Low voltage monitoring uses a comparison between the effective voltage value and the rated voltage. At that time, it was determined to be a low voltage abnormality, among which Rated voltage, The low voltage threshold coefficient can be set according to the application scenario of the device, for example, taking... to Low-voltage abnormal data is written to the voltage memory area.

[0035] Short circuit or current anomaly detection uses a comparison between the effective current value and the rated current or a set current threshold. When When this occurs, it is determined to be a short circuit or overcurrent abnormality, among which Rated current, This is the short-circuit or overcurrent threshold coefficient; when the application scenario requires detecting current loss, open circuit, or low current anomalies, a low current threshold can also be set. ,when When this occurs, it is determined to be a low current anomaly. The aforementioned current anomaly data is written to the current memory area.

[0036] Frequency monitoring can be performed using the zero-crossing cycle method, phase-locked loop method, or fundamental phase change method to calculate the current frequency. .when At that time, it was determined to be a frequency anomaly, among which For example, the frequency deviation threshold can be taken as... It can also be configured according to the power grid operation requirements. Frequency anomaly data is written to the frequency memory area.

[0037] To determine the priority of recording abnormal data, the device calculates the rate of change of faults. This applies to characteristic quantities such as voltage, current, harmonics, and frequency. Its rate of change can be calculated using the following formula:

[0038] In the formula, To compare the number of computation windows corresponding to the interval, The value can be set to the rated value, a threshold value, or the measured value from the previous comparison window. For frequency anomalies, the following can also be used: or As a measure of frequency change.

[0039] The device prioritizes faults based on the rate of change of each anomaly type. Priorities can be calculated using the following methods:

[0040] In the formula, This represents the fault priority value. , , , These represent the changes in harmonics, voltage, current, and frequency, respectively. These are the weighting coefficients. Weights are assigned to anomaly types. Alternatively, the maximum value among the various changes can be directly used as the fault priority. The higher the fault change rate, the lower the priority. The larger the value, the higher the storage priority for abnormal data.

[0041] The partitioned storage module includes a harmonic memory area, a voltage memory area, a current memory area, and a frequency memory area. Each anomaly record includes at least the anomaly occurrence time, anomaly type, anomaly judgment value, fault change rate, priority value, current round number, and sampled data or valid value data. Harmonic anomalies are written to the harmonic memory area, low voltage anomalies are written to the voltage memory area, short circuit, overcurrent, low current, or open circuit anomalies are written to the current memory area, and frequency anomalies are written to the frequency memory area.

[0042] Each memory area uses a round-robin recording method. Each round records a maximum of 10 fault records, arranged from highest to lowest fault priority within the same round. Records with higher fault change rates are stored earlier, and those with lower change rates are stored later. A fixed number of fault records are set for each round, for example, 10 records per round. Once a round reaches 10 records, subsequent faults proceed to the next round. Alternatively, before the current round ends, fault data with a priority higher than the lowest-priority record in the round can be inserted, and lower-priority records can be carried over to subsequent rounds.

[0043] In this embodiment, the multi-functional instrument device comprehensively detects harmonics, low voltage, short circuits or current anomalies, and frequency anomalies, and each anomaly type has a clear judgment formula or threshold judgment condition; the abnormal data is recorded in partitioned memory areas for harmonics, voltage, current, and frequency to avoid mixed storage of data of different fault types; the priority of abnormal data is calculated according to the fault change rate, so that abnormal data with a high fault change rate is stored first, and abnormal data with a low fault change rate is stored later; a fault recording mechanism with a fixed number of records per round is adopted, for example, 10 records per round, and after more than 10 records, the next round of recording begins, realizing round-based management of abnormal data.

[0044] Furthermore, harmonic detection algorithms can employ discrete Fourier transform, fast Fourier transform, digital filtering, wavelet analysis, or harmonic calculation algorithms built into the metering chip. As long as the fundamental component, each harmonic component, or total harmonic distortion rate can be obtained, harmonic anomaly detection can be achieved. The thresholds for judging low voltage, short circuit, current anomalies, and frequency anomalies can be fixed thresholds or adaptive thresholds automatically adjusted based on rated voltage, rated current, historical operating data, or operating mode. Partitioned storage can use physically independent storage areas or logical partitions within the same memory. The number of records per round can be set to 10, or other fixed numbers depending on the storage capacity. Fault priority can be determined using weighted summation, maximum rate of change, anomaly type classification, and combinations of duration and rate of change. Any method that prioritizes storing anomaly data with a larger rate of change will achieve the purpose of this invention.

[0045] The foregoing description of specific exemplary embodiments of the invention is for illustrative and explanatory purposes. These descriptions are not intended to limit the invention to the precise forms disclosed, and it will be apparent that many changes and variations can be made in accordance with the foregoing teachings. The exemplary embodiments were chosen and described in order to explain the specific principles of the invention and its practical application, thereby enabling those skilled in the art to implement and utilize various different exemplary embodiments of the invention, as well as various different choices and variations. The scope of the invention is intended to be defined by the claims and their equivalents.

Claims

1. A multi-functional instrument device, characterized in that, include: The voltage sampling module is used to continuously acquire the AC voltage waveform of the circuit under test; The current sampling module is used to continuously acquire the AC current waveform of the circuit under test; The data processing module calculates the effective value of voltage, effective value of current, frequency, harmonic content, and fault change rate based on the sampled data. The anomaly detection module determines whether harmonic anomalies, low voltage anomalies, current anomalies, or frequency anomalies have occurred based on set thresholds. The partitioned storage module includes a harmonic memory area, a voltage memory area, a current memory area, and a frequency memory area, which are used to store different types of abnormal data into the corresponding memory areas. The priority sorting module determines the storage order of abnormal records based on the magnitude of the fault change rate.

2. A method for recording abnormal data partitioning, used in the multifunctional instrument device of claim 1, characterized in that, Includes the following steps: S1. The device continuously collects voltage and current waveform data; S2. Calculate the effective value of voltage, the effective value of current, frequency, and harmonic content; S3. Perform harmonic anomaly, low voltage anomaly, current anomaly, and frequency anomaly judgments respectively; generate an anomaly record when any anomaly condition is met. S4. Select the corresponding memory area according to the exception type, and record each memory area in rounds. S5. Calculate the failure change rate and priority; S6. Sorting and storing fault records in the corresponding memory area using a fixed number of records per round; when the number of records in the current round exceeds the fixed number, proceed to the next round of recording. S7. The main station or local display module reads fault records according to the fault type, round, and priority.

3. The abnormal data partitioning and recording method according to claim 2, characterized in that, Each anomaly record should include at least the anomaly occurrence time, anomaly type, anomaly judgment value, fault change rate, priority value, current round number, and sampled data or valid value data.

4. The abnormal data partitioning and recording method according to claim 2, characterized in that, The device acquires instantaneous voltage and current values, and RMS voltage values ​​at a fixed sampling frequency or a configurable sampling frequency. and the effective value of current The calculation formula is as follows: ； ； in, The number of sampling points contained within a single calculation window; This is the instantaneous voltage value. This is the instantaneous value of the current; Number the current calculation window. This refers to the sampling point number within the window.

5. The abnormal data partitioning and recording method according to claim 4, characterized in that, Harmonic detection is performed using either the Discrete Fourier Transform (DFT) or Fast Fourier Transform (FFT) algorithm, and the total harmonic distortion (THD) of the voltage is calculated. and total harmonic distortion of current The formula is as follows: ； ； in, For the fundamental component, For the first The effective component of the second voltage harmonic; is the fundamental component. For the first Effective components of secondary current harmonics; when Greater than the voltage harmonic threshold, or If the content of a harmonic exceeds the current harmonic threshold, or if the content of any specified harmonic exceeds the corresponding set threshold, it is judged as a harmonic anomaly; the harmonic anomaly data is written to the harmonic memory area.

6. The abnormal data partitioning and recording method according to claim 4, characterized in that, Low voltage is monitored by comparing the effective voltage value with the rated voltage; low voltage anomaly data is written to the voltage memory area. when At that time, it was determined to be a low voltage abnormality; among them, Rated voltage, This is the low voltage threshold coefficient.

7. The abnormal data partitioning and recording method according to claim 4, characterized in that, Short circuits or current anomalies are detected by comparing the effective value of the current with the rated current and a set current threshold; abnormal current data is written to the current memory area. when When this occurs, it is determined to be a short circuit or overcurrent abnormality; when When this occurs, it is determined to be a low current abnormality; in, Rated current, This is the short-circuit or overcurrent threshold coefficient. The current threshold is low.

8. The abnormal data partitioning and recording method according to claim 4, characterized in that, Frequency monitoring is performed using the zero-crossing period method, phase-locked loop method, or fundamental phase change method to calculate the current frequency. Abnormal frequency data is written to the frequency memory area. At the time, it was determined to be a frequency anomaly; among them, This is the frequency deviation threshold.

9. The abnormal data partitioning and recording method according to claim 4, characterized in that, The device calculates the failure rate of change and prioritizes failures based on the rate of change for each type of anomaly. The formula for calculating the failure rate of change is as follows: ； in, For characteristic quantity, To compare the number of computation windows corresponding to the interval, Take the rated value, set the threshold, or the measured value from the previous comparison window; The formula for calculating fault priority is as follows: ； in, This represents the fault priority value. , , , These represent the changes in harmonics, voltage, current, and frequency, respectively. These are the weighting coefficients. Add weights to exception types.

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