A method and system for identifying sampling abnormalities in a protective relay

Abstract

The application discloses a kind of relaying protection device sampling exception discrimination method and system, it is related to electric power relay protection field, including the first sampling effective value and the second sampling effective value of multiple continuous sampling time stored in acquisition data buffer area;When satisfying unilateral value condition, the statistical difference of the first sampling effective value of multiple continuous sampling time and the second sampling effective value of corresponding time is calculated, if statistical difference is greater than the first preset difference threshold, it is judged as device sampling exception;When satisfying non-unilateral value condition, one sampling effective value is used as reference, and the other sampling effective value is grouped and counted;According to the statistical result, it is judged whether the CPU corresponding to the other sampling effective value exists sampling exception;When first CPU and second CPU are judged to have and only one sampling exception, it is judged as device sampling exception.The present application can capture the slight change of sampling effective value when sampling exception occurs, and can also cover the sampling exception working condition of effective value fluctuation near normal value.

Description

Technical Field

[0001] This invention relates to a method and system for identifying sampling anomalies in relay protection devices, belonging to the field of power relay protection. Background Technology

[0002] Abnormal sampling in relay protection devices often leads to maloperation or failure to operate, posing a significant hidden danger to the safe operation of power systems. Therefore, how to efficiently and accurately identify sampling anomalies, and subsequently issue timely alarms or handle them to prevent maloperation or failure to operate, is one of the key technical issues in the field of relay protection. Common methods for identifying sampling anomalies in relay protection include the dual AD sampling value comparison method, the dual CPU sampling effective value comparison method, and the anomaly point identification method based on sinusoidal wave characteristics. Currently, the three-CPU hardware architecture design with dual protection CPUs and an interface CPU is the mainstream configuration for high-voltage relay protection devices; therefore, the dual CPU sampling effective value comparison method is widely used in existing relay protection devices.

[0003] Chinese patent CN109541351A discloses a method for judging inconsistent current sampling in a relay protection device, which includes obtaining the analog current sampling value of the measured channel in the relay protection device using dual CPUs; calculating the fundamental effective value of each cycle of the dual CPU sampling value; comparing the maximum value of the two fundamental effective values ​​with a preset threshold for judging large and small values, and judging them separately for large and small values.

[0004] The core of the dual-CPU sampling RMS comparison method lies in the synchronous sampling and RMS calculation of the same set of analog inputs by two independent CPUs. The difference between the two results is used to determine whether the sampling loop is abnormal. Compared with the dual-AD sampling comparison method, this method has stronger resistance to harmonics and random noise and is more stable. Compared with the anomaly point identification method based on sinusoidal wave characteristics, it can effectively distinguish between real faults and sampling anomalies and is more reliable.

[0005] However, the existing dual-CPU sampling effective value comparison method still has the following shortcomings: First, this method only compares the real-time sampling fundamental effective value and cannot identify abnormal sampling conditions where the effective value fluctuates around the normal value. When a sampling anomaly causes the sampling effective value to change but still fluctuates around the normal value, the existing method is difficult to effectively identify. Second, if the two protection CPUs are not synchronized, and the update of the fundamental effective value of one CPU lags behind that of the other CPU, when the power system fluctuates, the current and voltage changes significantly, and the difference between the two CPUs may always exceed the threshold, thus misjudging the sampling anomaly. Third, the existing method usually directly uses the sampling difference between the two CPUs for blocking protection logic, which may lead to unnecessary termination of the protection function due to misjudgment, causing the device to fail to operate and thus damaging the primary equipment. Summary of the Invention

[0006] The purpose of this invention is to propose a method and system for detecting sampling anomalies in relay protection devices. This method detects sampling anomalies by caching the effective sampling values ​​of the dual-protection CPU at multiple time points in the interface CPU and comparing their averages or comparing the averages of high and low value groups.

[0007] To achieve the above objectives, the present invention is implemented using the following technical solution:

[0008] In a first aspect, this invention proposes a method for judging sampling anomalies in relay protection devices, applied to an interface CPU, comprising:

[0009] The first and second valid sample values ​​at multiple consecutive sampling moments stored in the data buffer are obtained. The first and second valid sample values ​​are data sampled by the first CPU and the second CPU at the same moment and pre-written into the data buffer.

[0010] When the first effective value of the multiple consecutive sampling times and the second effective value of the corresponding time satisfy the one-sided value case, calculate the statistical difference between the first effective value of the multiple consecutive sampling times and the second effective value of the corresponding time. If the statistical difference is greater than the first preset difference threshold, it is determined that the device sampling is abnormal.

[0011] When the first valid value of the sampling at the multiple consecutive sampling times and the second valid value of the sampling at the corresponding time satisfy the non-unilateral value condition, the other valid value is grouped and statistically analyzed based on one of the valid values ​​of the sampling; according to the statistical results, it is determined whether the CPU corresponding to the other valid value of the sampling is abnormal; when only one of the first CPU and the second CPU is judged to be abnormal, the first valid value of the sampling and the second valid value of the sampling at the corresponding time change asynchronously, and it is determined to be a device sampling abnormality.

[0012] Furthermore, the single-sided value case includes situations where the first sampled valid values ​​at multiple consecutive sampling times are all greater than or equal to, or all less than or equal to, the second sampled valid values ​​at the corresponding times.

[0013] Furthermore, the statistical difference includes the difference between the average of the first valid sample values ​​at the multiple consecutive sampling times and the average of the second valid sample values ​​at the corresponding times.

[0014] Furthermore, the first preset difference threshold is 5% of the larger of the average of the first sampled valid values ​​and the average of the second sampled valid values ​​at the corresponding time. If 5% of the larger value is less than 2% of the nominal value, the first preset difference threshold is set to 2% of the nominal value.

[0015] Further, the step of grouping and statistically analyzing the other valid sampled values ​​based on one valid sampled value, and determining whether the CPU corresponding to the other valid sampled value has a sampling anomaly based on the statistical results, includes:

[0016] Using the first valid value of the multiple consecutive sampling times as the benchmark, the second valid value of the corresponding time is compared sequentially: if the second valid value of the sampling is higher than the benchmark, it is included in the high value group; otherwise, it is included in the low value group; the average value of the high value group and the low value group are calculated respectively. If the difference between the two average values ​​is greater than the second preset difference threshold, the second CPU sampling is determined to be abnormal.

[0017] Using the second valid value of the multiple consecutive sampling times as the benchmark, the first valid value of the corresponding time is compared sequentially: if the first valid value of the sampling is higher than the benchmark, it is included in the high value group; otherwise, it is included in the low value group. The average value of the high value group and the low value group are calculated respectively. If the difference between the two average values ​​is greater than the second preset difference threshold, the first CPU sampling is determined to be abnormal.

[0018] Furthermore, the second preset difference threshold is 5% of the average value of the high value group. If this value is less than 2% of the rated value, the second preset difference threshold is set to 2% of the rated value.

[0019] Furthermore, the method also includes:

[0020] The interface CPU outputs the judgment result of the device sampling anomaly only as an alarm prompt message. The alarm prompt message is displayed locally through the device's built-in LCD panel and simultaneously uploaded to the background monitoring system via the communication protocol. The judgment result of the device sampling anomaly does not participate in the interlocking logic control of the protection output.

[0021] Furthermore, the interface CPU and the two protection CPUs within the device are independent processing units; when adding the sampling anomaly detection method, only the program of the interface CPU is upgraded, and the programs of the two protection CPUs and the device hardware are not modified.

[0022] Secondly, this invention proposes a sampling anomaly detection system for relay protection devices, comprising:

[0023] The data acquisition module is used to acquire the first and second valid sample values ​​of multiple consecutive sampling times stored in the data buffer. The first and second valid sample values ​​are data sampled by the first CPU and the second CPU at the same time and pre-written into the data buffer.

[0024] The sampling anomaly detection module under the one-sided value condition is used to calculate the statistical difference between the first sample effective value at the multiple consecutive sampling times and the second sample effective value at the corresponding time when the first sample effective value at the multiple consecutive sampling times and the second sample effective value at the corresponding time satisfy the one-sided value condition. If the statistical difference is greater than a first preset difference threshold, it is determined that the device sampling is abnormal.

[0025] The sampling anomaly detection module under non-one-sided value conditions is used to determine whether the first effective value of the sampling at the multiple consecutive sampling times and the second effective value of the sampling at the corresponding time meet the non-one-sided value condition. Based on one of the effective values ​​of the sampling, the other effective value is grouped and statistically analyzed. According to the statistical results, it is determined whether the CPU corresponding to the other effective value of the sampling has a sampling anomaly. When only one of the first CPU and the second CPU is identified as a sampling anomaly, the first effective value of the sampling changes asynchronously with the second effective value of the sampling at the corresponding time, and it is determined to be a device sampling anomaly.

[0026] Thirdly, the present invention proposes a computer-readable storage medium storing a computer program / instruction thereon, which, when executed by a processor, implements the steps of the relay protection device sampling anomaly discrimination method.

[0027] Fourthly, the present invention provides a computer device comprising:

[0028] Memory, used to store computer programs / instructions;

[0029] A processor is used to execute the computer program / instructions to implement the steps of the relay protection device sampling anomaly detection method.

[0030] Compared with the prior art, the beneficial effects achieved by the embodiments of the present invention include:

[0031] 1. This invention introduces a dual-CPU mutual benchmark mechanism and a high-low value grouping comparison strategy, which can not only capture the small changes in the effective value of the sample when the sampling is abnormal, but also cover the abnormal sampling conditions where the effective value of the sample fluctuates around the normal value. This overcomes the shortcomings of existing methods that only compare real-time values ​​and cannot identify abnormal fluctuations.

[0032] 2. This invention introduces a one-sided value discrimination mechanism and a mean comparison strategy, which can effectively distinguish between the difference changes caused by the asynchronous sampling of the two CPUs and the real sampling anomalies. When the system fluctuates, it will not falsely report sampling anomalies due to the asynchronous update of the effective values ​​of the two CPUs.

[0033] 3. The preset difference threshold of the present invention adopts the principle of considering the relative deviation when the value is large and the absolute deviation when the value is small, which can ensure high sensitivity and reliability in different measurement ranges.

[0034] 4. This invention is implemented in the device's interface CPU, serving only as an alarm notification and not participating in the interlocking logic. Adding this function to the device only requires upgrading the interface program; there is no need to modify the CPU protection program or hardware, making engineering implementation convenient, especially suitable for software upgrades of existing projects. Attached Figure Description

[0035] Figure 1 This is an overall flowchart of the relay protection device sampling anomaly discrimination method proposed in the embodiments of the present invention;

[0036] Figure 2 This is a flowchart of the sampling anomaly detection process in the case of one-sided values ​​proposed in an embodiment of the present invention;

[0037] Figure 3 This is a flowchart of the sampling anomaly detection process in the case of non-single-sided value proposed in an embodiment of the present invention. Detailed Implementation

[0038] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use.

[0039] Example 1:

[0040] This embodiment proposes a method for identifying sampling anomalies in relay protection devices, such as... Figure 1 As shown, this method is based on a generator-transformer protection device. The device adopts a three-CPU hardware architecture, including two protection CPUs (CPUA and CPUB) and one interface CPU (CPUC). The two protection CPUs perform synchronous sampling and fundamental effective value calculation on the analog input of the device, respectively. The interface CPU interacts with the two protection CPUs through an internal communication bus and caches the sampled effective values.

[0041] For ease of explanation, this embodiment uses the effective value of a certain phase current as an example, with a rated current of 5A. The difference threshold setting rules are as follows:

[0042] In the case of a single-sided value, the difference threshold is 5% of the larger of the average value of CPUA cache and the average value of CPUB cache. If this value is less than 2% of the rated value (i.e., 5A × 2% = 0.1A), the threshold is reset to 0.1A. In the case of a non-single-sided value, the difference threshold is 5% of the average of the high-value group. If this value is less than 2% of the rated value (i.e., 0.1A), the threshold is reset to 0.1A. This embodiment includes the following steps:

[0043] S1: The sampled valid value of the CPU with dual cache protection.

[0044] The CPUC internally caches the valid sampled values ​​of CPUA and CPUB N times. The cache depth is N (N≥2), meaning it caches the valid sampled values ​​of CPUA and CPUB from the most recent N moments. The cached data is arranged in chronological order, with the valid sampled values ​​of CPUA and CPUB at the same moment forming a corresponding set.

[0045] S2: Determine whether it is a one-sided value.

[0046] The valid sample values ​​of CPUA and CPUB in the cache are compared sequentially. If the valid sample values ​​of CPUA are all greater than or equal to, or all less than or equal to, the valid sample values ​​of CPUB at the corresponding time, proceed to S3; otherwise, proceed to S4.

[0047] S3: Sampling anomaly detection in the case of one-sided values.

[0048] like Figure 2 As shown, calculate the average of the valid cache samples for CPUA and CPUB respectively;

[0049] Calculate the difference between the average effective values ​​of the samples from CPUA and CPUB;

[0050] The larger of the average effective values ​​of CPUA and CPUB is used as the difference threshold. If this value is less than 2% of the rated value, the difference threshold is set to 2% of the rated value, i.e., 5A × 2% = 0.1A. Therefore, the threshold is adjusted to 0.1A.

[0051] Determine the difference between the average value of the valid samples of CPUA and CPUB and the difference threshold. If the average value difference exceeds the difference threshold, determine that the device sampling is abnormal and issue an alarm.

[0052] S4: Sampling anomaly detection in non-single-sided value cases.

[0053] like Figure 3 As shown, firstly, based on the effective value of CPUA sampling, the effective value of CPUB sampling is grouped into high and low value groups, and the average value of the high and low value groups is calculated respectively.

[0054] Calculate the difference between the average values ​​of the high and low groups of the CPUB sampled effective values;

[0055] The difference threshold is set to 5% of the average of the high-value group of the effective values ​​sampled by CPUB. If this value is less than 2% of the rated value, the difference threshold is set to 2% of the rated value, i.e., 5A × 2% = 0.1A. Therefore, the threshold is adjusted to 0.1A.

[0056] Determine the difference between the average value of the high and low value groups of the CPUB sample and the difference threshold. If the difference exceeds the difference threshold, the CPUB sample is considered abnormal.

[0057] Similarly, based on the effective value of CPUB sampling, the effective values ​​of CPUA sampling are grouped into high and low value groups, and the average value of the high and low value groups is calculated respectively.

[0058] Calculate the difference between the average values ​​of the high and low groups of the CPUA sampled effective values;

[0059] The difference threshold is set to 5% of the average of the high-value group of the CPUA sample valid values. If this value is less than 2% of the rated value, the difference threshold is set to 2% of the rated value, i.e., 5A × 2% = 0.1A. Therefore, the threshold is adjusted to 0.1A.

[0060] Determine the difference between the average value of the high and low value groups of the CPUA sample and the difference threshold. If the difference exceeds the difference threshold, the CPUA sample is determined to be abnormal.

[0061] S5: Comprehensive judgment in the case of non-one-sided value.

[0062] When only one of the dual-protection CPUs is identified as having a sampling abnormality, it is considered that the valid values ​​of CPUA and CPUB are changing asynchronously, and the device is judged to have a sampling abnormality.

[0063] After the current analog channel is judged, it is determined whether the current analog channel is the last analog channel. If not, steps S1 to S5 above are repeated until the sampling anomaly judgment of all analog channels is completed, thus achieving periodic and full-coverage sampling anomaly monitoring. The above method is implemented in the device's CPUC, and the judgment result is only used as an alarm prompt and does not participate in the interlocking logic.

[0064] Example 2:

[0065] This embodiment, based on Embodiment 1, sets up normal operating conditions: the effective current values ​​of both CPUA and CPUB fluctuate slightly around the rated value of 5A, and the effective current value of CPUA is always slightly greater than that of CPUB. This unilateral characteristic ensures that the current difference is always positive.

[0066] S1: The sampled valid value of the CPU with dual cache protection.

[0067] A cache is allocated in CPUC to cache the valid sampled values ​​of CPUA and CPUB for the most recent 6 time intervals (i.e., 6 cycles). The cached data is shown in Table 1.

[0068] Table 1. Effective values ​​of CPU sampling under normal operating conditions with dual protection

[0069]

[0070] S2: Determine whether it is a one-sided value.

[0071] Compare the effective values ​​of CPUA and CPUB at each time step:

[0072] At time T1, 5.05 > 4.95; at time T2, 5.10 > 4.90; at time T3, 5.02 > 4.98; at time T4, 5.08 > 4.92; at time T5, 5.12 > 4.88; at time T6, 5.06 > 4.94.

[0073] The effective values ​​sampled by CPUA are all greater than the effective values ​​sampled by CPUB at the corresponding time, which is a one-sided value, so proceed to S3.

[0074] S3: Sampling anomaly detection in the case of one-sided values.

[0075] Calculate the difference between the average effective values ​​of the samples from CPUA and CPUB:

[0076] Average CPUA = (5.05 + 5.10 + 5.02 + 5.08 + 5.12 + 5.06) / 6 = 5.072A;

[0077] CPUB average value = (4.95 + 4.90 + 4.98 + 4.92 + 4.88 + 4.94) / 6 = 4.928A;

[0078] The difference is 5.072 - 4.928 = 0.144A;

[0079] The larger of the average values ​​is 5.072A. The difference threshold is 5.072 × 5% = 0.2536A. Since 0.2536A > 0.1A, the difference threshold is 0.2536A.

[0080] The actual difference is 0.144A < 0.2536A, which does not exceed the threshold.

[0081] The result indicates that the sampling was normal and there were no alarms.

[0082] Example 3:

[0083] Based on Example 1, this embodiment sets an abnormal sampling condition for CPUB: the effective value of CPUA current sampling fluctuates slightly near the rated value, while the effective value of CPUB sampling fluctuates significantly, and is higher than CPUA at some times and lower than CPUA at others, exhibiting non-unilateral characteristics.

[0084] S1: The sampled valid value of the CPU with dual cache protection.

[0085] A cache is allocated in CPUC to cache the valid sampled values ​​of CPUA and CPUB from the most recent 6 time points. The cached data is shown in Table 2.

[0086] Table 2. Effective values ​​of CPU sampling under abnormal operating conditions with dual protection.

[0087]

[0088] S2: Determine whether it is a unipolar value.

[0089] Sequentially compare the sampled effective values of CPUA and CPUB at each moment:

[0090] At moments T1, T3 and T5, CPUA>CPUB, and at moments T2, T4 and T6, CPUA<CPUB, which is not a unipolar value, proceed to S4.

[0091] S4: Sampling anomaly determination in the case of non-unipolar values.

[0092] First, taking the sampled effective value of CPUA as the reference, calculate the difference between the mean values of the high and low value groups of CPUB:

[0093] The moments when the sampled effective value of CPUB is higher than that of CPUA are T2 (5.30>5.05), T4 (5.40>5.01), T6 (5.20>4.97), and the mean value of the high value group = (5.30+5.40+5.20) / 3 = 5.30A;

[0094] The moments when CPUB is lower than CPUA are T1 (4.80<5.02), T3 (4.70<4.98), T5 (4.90<5.03), and the mean value of the low value group = (4.80+4.70+4.90) / 3 = 4.80A;

[0095] Difference between the mean values of the high and low value groups = 5.30 - 4.80 = 0.50A.

[0096] 5% of the high value group mean 5.30A is 0.265A, 0.265A > 0.1A, so the difference threshold is 0.265A;

[0097] The difference 0.50A between the mean values of the high and low value groups is greater than the difference threshold 0.265A, exceeding the threshold, and it is determined that CPUB sampling is abnormal.

[0098] Taking the sampled effective value of CPUB as the reference, calculate the difference between the mean values of the high and low value groups of CPUA:

[0099] The moments when the sampled effective value of CPUA is higher than that of CPUB are T1 (5.02>4.80), T3 (4.98>4.70), T5 (5.03>4.90), and the mean value of the high value group = (5.02+4.98+5.03) / 3 = 5.01A;

[0100] The moments when CPUA is lower than CPUB are T2 (5.05<5.30), T4 (5.01<5.40), T6 (4.97<5.20), and the average value of the low-value group = (5.05+5.01+4.97) / 3 = 5.01A;

[0101] The difference between the average values of the high-value group and the low-value group is 0A.

[0102] 5% of the average value 5.01A of the high-value group is 0.2505A, 0.2505A > 0.1A, so the difference threshold is 0.2505A;

[0103] The difference 0A between the average values of the high-value group and the low-value group is less than the difference threshold 0.2505A, which does not exceed the threshold, and it is determined that the sampling of CPUA is normal.

[0104] S5: Comprehensive determination under the non-unilateral value condition.

[0105] If there is exactly one CPUB determined as sampling abnormality among the dual protection CPUs, it is comprehensively determined that the device sampling is abnormal.

[0106] The determination result is that the sampling of CPUB is abnormal, and an alarm prompt is issued.

[0107] Fourth Embodiment:

[0108] Based on the first embodiment, this embodiment sets a shutdown working condition: the unit is in a shutdown state, the primary current is 0, there is a tiny zero drift in the sampling loop, the current effective values of CPUA and CPUB both fluctuate around 0.1A, with each being higher or lower than the other, showing a non-unilateral characteristic.

[0109] S1: Cache the sampled effective values of the dual protection CPUs.

[0110] A buffer area is opened up in CPUC to cache the sampled effective values of CPUA and CPUB at the latest 6 moments. The cached data is shown in Table 3.

[0111] Table 3 Sampled effective values of dual protection CPUs under shutdown working condition

[0112]

[0113] S2: Determine whether it is a unilateral value.

[0114] Compare the sampled effective values of CPUA and CPUB at each moment in sequence:

[0115] At moments T1, T3, T5, CPUA > CPUB, and at moments T2, T4, T6, CPUA < CPUB, which is a non-unilateral value, proceed to S4.

[0116] S4: Sampling abnormality determination under the non-unilateral value condition.

[0117] First, using the valid sampled value of CPUA as a benchmark, calculate the difference in mean values ​​between the high and low value groups of CPUB:

[0118] The times when the effective value of CPUB sample is higher than that of CPUA are T2 (0.13>0.08), T4 (0.14>0.10), and T6 (0.11>0.09). The average value of the high value group is (0.13+0.14+0.11) / 3 = 0.127A.

[0119] The times when CPUB is lower than CPUA are T1 (0.09 < 0.12), T3 (0.08 < 0.15), and T5 (0.10 < 0.13). The average value of the low value group is (0.09 + 0.08 + 0.10) / 3 = 0.090A.

[0120] The difference between the average values ​​of the high and low value groups is 0.127 - 0.090 = 0.037A.

[0121] 5% of the high-value group's average value of 0.127A is 0.00635A. Since 0.00635A < 0.1A, the difference threshold is 0.1A.

[0122] The difference between the average values ​​of the high and low value groups is 0.037A, which is less than the difference threshold of 0.1A. Since the threshold is not exceeded, CPUB sampling is considered normal.

[0123] Based on the effective value of CPUB sampling, calculate the difference in mean values ​​between high and low values ​​in CPUA:

[0124] The times when the effective value of CPUA is higher than that of CPUB are T1 (0.12>0.09), T3 (0.15>0.08), and T5 (0.13>0.10). The average value of the high value group is (0.12+0.15+0.13) / 3 = 0.133A.

[0125] The times when CPUA is lower than CPUB are T2 (0.08 < 0.13), T4 (0.10 < 0.14), and T6 (0.09 < 0.11). The average value of the low value group is (0.08 + 0.10 + 0.09) / 3 = 0.090A.

[0126] The difference between the average values ​​of the high and low value groups is 0.133 - 0.090 = 0.043A.

[0127] 5% of the high-value group's average value of 0.133A is 0.00665A. Since 0.00665A < 0.1A, the difference threshold is 0.1A.

[0128] The difference between the average values ​​of the high and low value groups is 0.043A, which is less than the difference threshold of 0.1A. Since the threshold is not exceeded, CPUA sampling is considered normal.

[0129] S5: Comprehensive determination in the case of non-unilateral values.

[0130] Neither of the dual protection CPUs is determined to be abnormal, and the comprehensive determination is that sampling is normal.

[0131] The determination result is that the zero drift is within the allowable range, the sampling is normal, and no alarm is generated.

[0132] Fifth Embodiment:

[0133] On the basis of the first embodiment, this embodiment sets a system fluctuation working condition: the current first rises synchronously and then falls synchronously, the sampling values of the two protection CPUs can accurately track the current change, although they are higher or lower than each other, the deviation amplitude is very small, and the sampling should not be determined as abnormal.

[0134] S1: Cache the sampled effective values of the dual protection CPUs.

[0135] A buffer area is opened in CPUC to cache the sampled effective values of CPUA and CPUB at the latest 6 moments. The cached data is shown in Table 4.

[0136] Table 4 Sampled effective values of dual protection CPUs under system fluctuation working condition

[0137]

[0138] S2: Determine whether it is a unilateral value.

[0139] Compare the sampled effective values of CPUA and CPUB at each moment in sequence:

[0140] CPUA > CPUB at moments T1, T3 and T5, and CPUA < CPUB at moments T2, T4 and T6, which is a non-unilateral value, and the process proceeds to S4.

[0141] S4: Sampling abnormality determination in the case of non-unilateral values.

[0142] First, taking the sampled effective value of CPUA as the reference, calculate the difference between the mean values of the high and low value groups of CPUB:

[0143] The moments when the sampled effective value of CPUB is higher than that of CPUA are T2 (6.10>6.05), T4 (8.05>7.98), and T6 (5.06>5.01), and the average value of the high value group = (6.10+8.05+5.06) / 3 = 6.403A;

[0144] The moments when CPUB is lower than CPUA are T1 (4.98<5.02), T3 (7.95<8.00), and T5 (5.98<6.02), and the average value of the low value group = (4.98+7.95+5.98) / 3 = 6.303A;

[0145] The difference between the average values ​​of the high and low value groups = 6.403 - 6.303 = 0.100A.

[0146] 5% of the high-value group's average value of 6.403A is 0.320A. Since 0.320A > 0.1A, the difference threshold is 0.320A.

[0147] The difference between the average values ​​of the high and low value groups is 0.100A, which is less than the difference threshold of 0.320A. Since the threshold is not exceeded, CPUB sampling is considered normal.

[0148] Based on the effective value of CPUB sampling, calculate the difference in mean values ​​between high and low values ​​in CPUA:

[0149] The times when the effective value of CPUA is higher than that of CPUB are T1 (5.02>4.98), T3 (8.00>7.95), and T5 (6.02>5.98). The average value of the high value group is (5.02+8.00+6.02) / 3 = 6.347A.

[0150] The times when CPUA is lower than CPUB are T2 (6.05 < 6.10), T4 (7.98 < 8.05), and T6 (5.01 < 5.06). The average value of the low value group is (6.05 + 7.98 + 5.01) / 3 = 6.347A.

[0151] The difference between the average values ​​of the high and low value groups is 0A.

[0152] 5% of the high-value group's average of 6.347A is 0.317A. Since 0.317A > 0.1A, the difference threshold is 0.317A.

[0153] The difference between the average values ​​of the high and low value groups is 0A, which is less than the difference threshold of 0.317A. Since the threshold is not exceeded, CPUA sampling is considered normal.

[0154] S5: Comprehensive judgment in the case of non-one-sided value.

[0155] Neither of the dual-protection CPUs was detected as abnormal, and the overall assessment was that the sampling was normal.

[0156] The results showed that the system current dynamically changed, the dual CPUs tracked it consistently, the sampling was normal, and there were no alarms.

[0157] Example 6:

[0158] This embodiment, based on Embodiment 1, provides a relay protection device sampling anomaly detection system, including:

[0159] The data acquisition module is used to acquire the first and second valid sample values ​​of multiple consecutive sampling times stored in the data buffer. The first and second valid sample values ​​are data sampled by the first CPU and the second CPU at the same time and pre-written into the data buffer.

[0160] The sampling anomaly detection module under the one-sided value condition is used to calculate the statistical difference between the first sampled effective value and the second sampled effective value at the corresponding time when the first sampled effective value at multiple consecutive sampling times and the corresponding time satisfy the one-sided value condition. If the statistical difference is greater than the first preset difference threshold, it is determined that the device sampling is abnormal.

[0161] The sampling anomaly detection module under non-one-sided value conditions is used to determine whether the first effective value of multiple consecutive sampling times and the second effective value of the corresponding time satisfy the non-one-sided value condition. Based on one of the effective values ​​of sampling, the other effective value is grouped and statistically analyzed. According to the statistical results, it is determined whether the CPU corresponding to the other effective value of sampling has a sampling anomaly. When only one of the first CPU and the second CPU is identified as a sampling anomaly, the first effective value of sampling changes asynchronously with the second effective value of sampling at the corresponding time, which is determined to be a device sampling anomaly.

[0162] Example 7:

[0163] This embodiment proposes a computer-readable storage medium based on Embodiment 1, on which a computer program / instruction is stored. When the computer program / instruction is executed by a processor, it implements the steps of the relay protection device sampling anomaly discrimination method.

[0164] Example 8:

[0165] This embodiment proposes a computer device based on Embodiment 1, including:

[0166] Memory, used to store computer programs / instructions;

[0167] A processor is used to execute the computer program / instructions to implement the steps of the relay protection device sampling anomaly detection method.

[0168] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0169] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0170] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0171] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0172] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A method for identifying sampling anomalies in a relay protection device, characterized in that, Applied to interface CPUs, including: The first and second valid sample values ​​at multiple consecutive sampling moments stored in the data buffer are obtained. The first and second valid sample values ​​are data sampled by the first CPU and the second CPU at the same moment and pre-written into the data buffer. When the first effective value of the multiple consecutive sampling times and the second effective value of the corresponding time satisfy the one-sided value case, calculate the statistical difference between the first effective value of the multiple consecutive sampling times and the second effective value of the corresponding time. If the statistical difference is greater than the first preset difference threshold, it is determined that the device sampling is abnormal. When the first valid value of the sampling at the multiple consecutive sampling times and the second valid value of the sampling at the corresponding time satisfy the non-unilateral value condition, the other valid value is grouped and statistically analyzed based on one of the valid values ​​of the sampling; according to the statistical results, it is determined whether the CPU corresponding to the other valid value of the sampling is abnormal; when only one of the first CPU and the second CPU is judged to be abnormal, the first valid value of the sampling and the second valid value of the sampling at the corresponding time change asynchronously, and it is determined to be a device sampling abnormality.

2. The method for judging sampling anomalies in relay protection devices according to claim 1, characterized in that, The single-sided value case includes situations where the first sampled valid value at multiple consecutive sampling times is greater than or equal to, or less than or equal to, the second sampled valid value at the corresponding time.

3. The method for judging sampling anomalies in relay protection devices according to claim 1, characterized in that, The statistical difference includes the difference between the average of the first sampled valid values ​​at the multiple consecutive sampling times and the average of the second sampled valid values ​​at the corresponding times.

4. The method for judging sampling anomalies in relay protection devices according to claim 3, characterized in that, The first preset difference threshold is 5% of the larger of the average of the first sampled valid values ​​and the average of the second sampled valid values ​​at the corresponding time. If 5% of the larger value is less than 2% of the rated value, the first preset difference threshold is set to 2% of the rated value.

5. The method for judging sampling anomalies in relay protection devices according to claim 1, characterized in that, The process involves using one valid sample value as a benchmark, grouping and statistically analyzing the other valid sample values, and determining whether the CPU corresponding to the other valid sample value has a sampling anomaly based on the statistical results. This includes: Using the first valid value of the multiple consecutive sampling times as the benchmark, the second valid value of the corresponding time is compared sequentially: if the second valid value of the sampling is higher than the benchmark, it is included in the high value group; otherwise, it is included in the low value group. The average value of the high value group and the low value group are calculated respectively. If the difference between the two average values ​​is greater than the second preset difference threshold, the second CPU sampling is determined to be abnormal. Using the second valid value of the multiple consecutive sampling times as the benchmark, the first valid value of the corresponding time is compared sequentially: if the first valid value of the sampling is higher than the benchmark, it is included in the high value group; otherwise, it is included in the low value group. The average value of the high value group and the low value group are calculated respectively. If the difference between the two average values ​​is greater than the second preset difference threshold, the first CPU sampling is determined to be abnormal.

6. The method for judging sampling anomalies in relay protection devices according to claim 5, characterized in that, The second preset difference threshold is 5% of the average value of the high value group. If this value is less than 2% of the rated value, the second preset difference threshold is set to 2% of the rated value.

7. The method for judging sampling anomalies in relay protection devices according to claim 1, characterized in that, The method also includes alarm information output: The interface CPU outputs the judgment result of the device sampling anomaly as an alarm prompt message only. The alarm prompt message is displayed locally through the device's built-in LCD panel and simultaneously uploaded to the background monitoring system.

8. A sampling anomaly detection system for a relay protection device, characterized in that, include: The data acquisition module is used to acquire the first and second valid sample values ​​of multiple consecutive sampling times stored in the data buffer. The first and second valid sample values ​​are data sampled by the first CPU and the second CPU at the same time and pre-written into the data buffer. The sampling anomaly detection module under the one-sided value condition is used to calculate the statistical difference between the first sampled effective value at the multiple consecutive sampling times and the second sampled effective value at the corresponding time when the first sampled effective value at the multiple consecutive sampling times and the second sampled effective value at the corresponding time satisfy the one-sided value condition. If the statistical difference is greater than a first preset difference threshold, it is determined that the device sampling is abnormal. The sampling anomaly detection module under non-one-sided value conditions is used to determine whether the first effective value of the sampling at the multiple consecutive sampling times and the second effective value of the sampling at the corresponding time meet the non-one-sided value condition. Based on one of the effective values ​​of the sampling, the other effective value is grouped and statistically analyzed. According to the statistical results, it is determined whether the CPU corresponding to the other effective value of the sampling has a sampling anomaly. When only one of the first CPU and the second CPU is identified as a sampling anomaly, the first effective value of the sampling changes asynchronously with the second effective value of the sampling at the corresponding time, and it is determined to be a device sampling anomaly.

9. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instruction is executed by the processor, it implements the steps of the relay protection device sampling anomaly discrimination method according to any one of claims 1 to 7.

10. A computer device, characterized in that, include: Memory, used to store computer programs / instructions; A processor is configured to execute the computer program / instructions to implement the steps of the relay protection device sampling anomaly discrimination method according to any one of claims 1 to 7.

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