CN110927655A - Diagnosis method for electric energy meter flying away and high-speed power line carrier module - Google Patents
Diagnosis method for electric energy meter flying away and high-speed power line carrier module Download PDFInfo
- Publication number
- CN110927655A CN110927655A CN201911145510.7A CN201911145510A CN110927655A CN 110927655 A CN110927655 A CN 110927655A CN 201911145510 A CN201911145510 A CN 201911145510A CN 110927655 A CN110927655 A CN 110927655A
- Authority
- CN
- China
- Prior art keywords
- electric energy
- energy meter
- metering
- suspected
- relative deviation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R35/00—Testing or calibrating of apparatus covered by the other groups of this subclass
- G01R35/04—Testing or calibrating of apparatus covered by the other groups of this subclass of instruments for measuring time integral of power or current
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R22/00—Arrangements for measuring time integral of electric power or current, e.g. electricity meters
- G01R22/06—Arrangements for measuring time integral of electric power or current, e.g. electricity meters by electronic methods
- G01R22/061—Details of electronic electricity meters
- G01R22/063—Details of electronic electricity meters related to remote communication
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R22/00—Arrangements for measuring time integral of electric power or current, e.g. electricity meters
- G01R22/06—Arrangements for measuring time integral of electric power or current, e.g. electricity meters by electronic methods
- G01R22/061—Details of electronic electricity meters
- G01R22/068—Arrangements for indicating or signaling faults
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Remote Monitoring And Control Of Power-Distribution Networks (AREA)
Abstract
The invention relates to a diagnosis method for electric energy meter flying away and a high-speed power line carrier module, wherein the method comprises the following steps: acquiring electric energy metering values of the electric energy meter which are respectively metered at the same time for a plurality of continuous days; calculating the distance between each metering value and two adjacent metering values as the central distance of the metering values; calculating the relative deviation degree of the center distance; if the relative deviation degree exceeds a set threshold value, judging that the corresponding electric energy meter measures suspected faults, and marking corresponding time information; and judging the fault type, and adopting different processing methods aiming at different types of faults. The invention adopts the distributed HPLC module to directly diagnose at the front end, thereby avoiding network congestion and time delay caused by the traditional method of summarizing data acquisition to the master station diagnosis. Judging the abnormal type according to the measurement deviation degree, being beneficial to operation and maintenance maintainers to distinguish the emergency degree of maintenance work and reasonably arrange the operation and maintenance work; different suspected fault types are judged, so that maintenance personnel can be assisted to quickly locate the fault, and the maintenance efficiency is improved.
Description
Technical Field
The invention relates to the field of power systems, in particular to a diagnosis method based on electric energy meter flying and a high-speed power line carrier (HPLC) module.
Background
Along with the vigorous construction of a strong smart grid, the coverage rate of the smart electric meter is continuously improved, and the original mechanical electric energy meter is basically replaced. According to statistics, the nationwide automatic meter reading system based on the power line carrier covers more than 5 hundred million intelligent electric meters, and the voltage, current, power, electric energy and other data information of the electric energy meters can be easily obtained through the automatic meter reading system.
The electric energy meter is a legal measuring tool for electric power commodities, and the collected electric energy information is a main basis for electric power transaction settlement between an electric power company and users, power generation enterprises and other comprehensive energy service companies. Therefore, the metering accuracy of the electric energy meter receives high attention of all parties, and is also a main supervision object of the metering administrative department in China. The electronic intelligent electric meter has the advantages of high precision, wide frequency band, strong overload capacity and low energy consumption, has more advantages than an induction electric meter, not only has the function of electricity metering, but also has the functions of data storage, charge control, remote switching on and off, data communication and self-diagnosis expansion. However, since there are many components inside the smart meter, it is very sensitive to external interference, and when the field environment is complex, disturbance factors such as external temperature, humidity or thermal shock, rated sinusoidal vibration, electromagnetic interference may cause the electric energy meter to malfunction or even fail. Stopping, flying and reversing the electric energy meter are typical representatives of metering abnormality of the intelligent electric meter, and are happened generally, but metering misalignment caused by the abnormality often causes customer doubt, influences customer service quality, and causes a power company to suffer from serious trust crisis and economic loss. How to monitor the running intelligent electric meter in real time and accurately find and eliminate faults in time is a problem which is urgently needed to be solved by power companies.
The collected data of the electric energy meter for stopping, flying and reversing judgment is mainly the indication value of frozen active electric energy. The electric energy meter freezing data is typical time sequence data, and the data are collected in time sequence and describe the change of daily electricity quantity along with time. There are many types of abnormal points in the time series, and the abnormal points can be generally classified into 2 types according to the influence generated by the abnormal points, namely additive abnormal points and innovation abnormal points. An additive anomaly is generally an isolated anomaly that does not propagate to subsequent observations. The innovation exception point usually relates to the related structure in the time sequence, so that the innovation exception point often appears in pieces, and when a fault point appears, the follow-up point of the fault point also shows a certain exception due to the relevance.
An additive anomaly is an isolated anomaly, as shown in fig. 1, in which data collected during a certain period of time undergoes a large pulse change and then returns to normal quickly. The abnormal data do not reach subsequent observed values, but affect data such as freezing of the smart meter.
The type I innovation anomaly point shows that the data generates a large step at a certain moment and then starts to work stably, and all the subsequent points of the data show anomalies due to the correlation, as shown in fig. 2. Such anomalies have a large influence on the metering of the electric energy meter, and even cause billing disputes.
Type II innovation anomaly is another form of innovation anomaly, as shown in fig. 3. It is shown that the data trend produces a sudden change at a certain time and stabilizes the work. Such an abnormality is difficult to judge, errors accumulate on a time sequence, and the influence on subsequent electric energy meter measurement is the largest.
Disclosure of Invention
The invention mainly aims at the problem of abnormal metering of an electric energy meter, and provides a diagnosis method based on electric energy meter flying and a high-speed power line carrier module.
In order to achieve the above object, the present invention provides a diagnosis method based on electric energy meter flying, comprising:
acquiring electric energy metering values of the electric energy meter which are respectively metered at the same time for a plurality of continuous days;
calculating the central distance from each metering value to two adjacent metering values;
calculating the relative deviation degree of the center distance;
and if the relative deviation degree exceeds a set threshold value, judging that the corresponding electric energy meter measures suspected faults, and marking corresponding time information.
Further, acquiring electric energy metering values of the electric energy meter which are respectively metered at the same time for a plurality of continuous days every day, calculating relative deviation degree once, and reporting suspected faults of electric energy meter metering if k times of judgment that the relative deviation degree of the electric energy meter in a certain day exceeds a set threshold value, wherein k is an integer and is more than or equal to 3.
Further, the jth center distance is:
wherein xjRepresents the measurement of j day, n is more than or equal to j and more than or equal to 2;
the jth relative deviation degree is:
further, reporting the suspected fault of the electric energy meter further comprises: if the average value of the k times of deviation degrees is more than 100, only reporting the suspected fault; and if the average value of the k relative deviation degrees is not more than 10, additionally informing the operation and maintenance staff of carrying out troubleshooting on the electric energy meter.
Further, the reporting of the suspected faults of the electric energy meter includes: the method comprises the steps that data messages are added to an HPLC protocol and sent to a concentrator, suspected metering fault information of all electric energy meters in a distribution area is collected by the concentrator, the suspected metering fault information is reported to a master station at fixed time every day, and the master station processes the suspected metering fault information.
The invention provides a high-speed power line carrier module based on diagnosis of electric energy meter flying away, which comprises an acquisition module and a main control module;
the acquisition module acquires the metering values of the electric energy meter frozen every day for a plurality of continuous days and sends the metering values to the main control module;
the main control module comprises a center distance calculation unit, a deviation calculation unit and a comparison unit; the central distance calculating unit reads the metering values of a plurality of continuous days and calculates the central distance from each metering value to two adjacent metering values; the deviation calculating unit calculates a relative deviation degree of the center distance; and the comparison unit compares the relative deviation degree with a set threshold, outputs a suspected fault signal of the corresponding electric energy meter if the relative deviation degree exceeds the set threshold, and marks corresponding time information.
Further, the master control module further comprises an output unit, suspected fault signals of the electric energy meters output by the comparison unit are accumulated, if the suspected fault signals of one electric energy meter exceed k, the suspected faults, the corresponding electric energy meter numbers and the time information are sent to the concentrator in a data message mode and are reported to the master station after being collected in a centralized mode, k is an integer and is more than or equal to 3.
Further, the main control module also comprises a fault judgment unit, and if the average value of the k relative deviation degrees is more than 100, only suspected faults are reported; if the average value of the k relative deviation degrees is (10, 100), adding information for immediately maintaining or replacing the corresponding electric energy meter in the data message, and if the average value of the k relative deviation degrees is not more than 10, adding troubleshooting information of an operation and maintenance maintainer to the electric energy meter in the data message.
The technical scheme of the invention has the following beneficial technical effects:
(1) the invention converts the abnormal measurement detection of the electric energy meter into data mining on a time sequence; the lightweight center distance detection algorithm can quickly diagnose suspected metering abnormal points, can judge abnormal types according to the metering deviation degree, is favorable for operation and maintenance maintainers to distinguish the emergency degree of maintenance work, and reasonably arranges the operation and maintenance work.
(2) The light-weight center distance detection algorithm based on HPLC resources and computing power diagnoses the metering abnormal points, has small resource consumption and obvious processing effect, and is suitable for an HPLC module embedded hardware platform. The algorithm adopts distributed arrangement, and the front end directly diagnoses, thereby avoiding network congestion and time delay caused by the traditional mode of summarizing data acquisition to the main station diagnosis.
(3) The method judges the type of the suspected fault through the deviation degree, and adopts different processing modes for different types of suspected faults, so that the cost loss caused by error metering is reduced on one hand, and the cost of operation and maintenance is reduced on the other hand.
(4) The method and the device can judge different suspected fault types, can assist maintenance personnel to quickly locate the fault, and provide maintenance efficiency.
Drawings
FIG. 1 is a schematic view of an additive anomaly;
FIG. 2 is a schematic diagram of a type I innovation anomaly;
FIG. 3 is a schematic diagram of the type II innovation outliers;
FIG. 4 is a schematic view of a flow chart of the HPLC module for diagnosing metering abnormality of the electric energy meter;
FIG. 5 is a schematic diagram of a detection simulation result of additive anomaly fly-away data;
FIG. 6 is a schematic diagram of a detection simulation result of type I innovation outlier fly-away data;
FIG. 7 is a schematic diagram of a detection simulation result of type II innovation outlier fly-away data;
fig. 8 is a schematic structural diagram of a high-speed power line carrier module based on the diagnosis of electric energy meter flying away.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings in conjunction with the following detailed description. It should be understood that the description is intended to be exemplary only, and is not intended to limit the scope of the present invention. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present invention.
The power consumption of each household is basically in a relatively stable state, the fluctuation is small, the suspected fault power consumption is diagnosed based on the condition and reported to the master station, and the fault monitoring of the electric energy meter is realized. The invention adopts an abnormal point detection method based on distance, considers the field of a given radius, and if the abnormal point is the abnormal point, the other points are not enough in the field. Compared with other abnormal point monitoring algorithms, the method does not need the user to have domain knowledge, and is more intuitive in concept.
The invention provides a method for diagnosing flying away of an electric energy meter in a first aspect, which comprises the following steps:
and S100, acquiring electric energy metering values of the electric energy meter which are respectively metered at the same time for multiple continuous days.
And step S200, calculating the central distance from each metering value to two adjacent metering values.
Step S300, calculating the relative deviation degree of the center distance.
And step S400, if the relative deviation degree exceeds a set threshold, determining that the corresponding electric energy meter measures suspected faults, and marking corresponding time information. ,
in particular, suppose Xi＝{xi，xi+1，xi+2，…，xi+nThe n +1 metering values stored at the moment i of the electric energy meter for n +1 consecutive days are obtained, the electric energy meter generally stores 62 days of freezing data, therefore, n is 61, and the distance between the centers of the j-th electric energy meter metering value at the moment i is defined as:
define the relative deviation of the metric points at point j:
evaluating the abnormal measuring point by the relative deviation degree of the measuring point
It is determined that the greater the relative deviation degree, the more likely the measurement error point is. Conversely, the smaller the relative deviation degree, the lower the possibility of measurement abnormality. Normally, the relative deviation degree of the measuring points
Floating up and down at 1. If the relative deviation degree is more than 100, only reporting a suspected fault; if the relative deviation degree is (10,100)]If so, the corresponding electric energy meter is immediately maintained or replaced; and if the relative deviation degree is not more than 10, informing the operation and maintenance staff to carry out troubleshooting on the electric energy meter.
Further, the electric energy metering values metered by the electric energy meter are respectively obtained at the same time every day for a plurality of continuous days, the relative deviation degree of each day of the electric energy metering values is calculated, if the times that the relative deviation degree exceeds a set threshold value reach k times, suspected faults of the electric energy meter metering are reported, wherein k is an integer, and k is more than or equal to 3.
The HPLC carrier meter module is important equipment of the electricity utilization information acquisition system, acquires the acquisition value of the electric meter in real time by being installed on the intelligent electric meter, and transmits data by means of a power line until the data are transmitted to a main station. The HPLC module is generally provided with a built-in carrier and a main control chip, and has certain calculation and processing capabilities. The operation of the HPLC module is independent of the electric energy meter, is the best carrier for measuring, detecting and monitoring the normal operation of the electric energy meter, and is developed based on the advanced application of the HPLC module such as power failure reporting, low voltage detection, station area identification and the like. The invention also provides a high-speed power line carrier module based on the diagnosis of the flying of the electric energy meter, wherein the center distance abnormal point diagnosis algorithm is embedded into a main control chip of an HPLC module in a software mode, and the HPLC module automatically acquires the operation data of the electric energy meter and carries out the diagnosis of the metering abnormal point. The high-speed power line carrier module based on diagnosis of electric energy meter flying comprises an acquisition module and a main control chip, wherein the acquisition module is conventional, acquires the metering values of the electric energy meter frozen every day for continuous multiple days and sends the metering values to the main control module; the main control module mainly comprises a main control chip, and specifically comprises a center distance calculation unit, a deviation calculation unit, a comparison unit and an output unit, in combination with fig. 8.
The central distance calculating unit calculates the distance between each metering value and two adjacent metering values as the central distance of the metering value;
the deviation calculating unit calculates a relative deviation degree of the center distance; the comparison unit compares the relative deviation degree with a set threshold, outputs a suspected fault signal of the corresponding electric energy meter if the relative deviation degree exceeds the set threshold, and marks corresponding time information;
and the output unit accumulates the suspected fault signals of the electric energy meters output by the comparison unit, if the suspected fault signals of a certain electric energy meter exceed k, the suspected fault, the corresponding electric energy meter number and the time information are sent to the concentrator in a data message mode, the suspected fault, the corresponding electric energy meter number and the time information are reported to the master station after being aggregated, k is an integer and is more than or equal to 3.
The output unit judges suspected faults of the metering value of the electric energy meter on a certain day, adds the suspected faults to an HPLC protocol in the form of data messages and sends the data messages to the concentrator, the concentrator collects the suspected metering fault information of all the electric energy meters in the distribution area, and the suspected metering fault information is reported to the main station every day for a fixed time to inform operation and maintenance staff to process the suspected metering fault information in time.
The high-speed power line carrier module can not only quickly detect suspected metering abnormality, but also give an indication for the type of the abnormality, so that operation and maintenance personnel can conveniently maintain or replace the meter.
The difference of the metering abnormal type, the calculated metering deviation degree
A significant difference was exhibited. When the point j is judged to be the deviation of the metering point through the three times of verification, when the point j is judged to be the deviation of the metering point
When the value is (100, infinity), the abnormality can be judged as an additive abnormal point, the additive abnormal point does not influence normal meter reading and charging, and the requirement on the urgency of operation and maintenance is low. When in use
A value of (10,100)]In time, the abnormality can be judged as an I-type innovation abnormal point, and the ammeter needs to be repaired or replaced at once. When in use
The value is at (1, 10)]In time, the abnormity can be judged to be a type II innovation abnormity point, and the measurement abnormity of the type II innovation abnormity point is determined more complexly, and an electric power operation and maintenance maintainer needs to use a special tool.
In one embodiment, the main control chip further comprises a fault judgment unit, and only reports suspected faults if the average value of the k pairs of deviation degrees is more than 100; and if the average value of the k relative deviation degrees is not more than 10, additionally informing the operation and maintenance staff of carrying out troubleshooting on the electric energy meter.
The electric energy meter flying detection based on the HPLC module does not depend on the electric energy meter and operates independently, and has higher reliability compared with self-diagnosis detection of the electric energy meter.
In the automatic diagnosis of the metering abnormal point of the intelligent electric meter, the metering value of the electric meter is actively acquired by an HPLC module according to a set period, for example, every day, the metering value is stored for 62 days, and the calculation is started. And performing primary calculation on the acquired data according to the center distance abnormal point detection algorithm, and marking the time information of the measured abnormal points obtained by diagnosis to finish primary diagnosis.
The same amount of data was obtained by HPLC for each time, the data was fixed at the start of the calculation, which corresponds to each calculation being performed off-line. The misdiagnosis can be avoided by means of redundancy judgment, and when the metering value of a certain time scale is judged to be abnormal for three or more times, the metering abnormality of the electric energy meter is considered to exist at the moment. At this time, the abnormal information is reported in a power line carrier mode.
In one embodiment, the HPLC module metric anomaly point diagnostic flow chart is shown in fig. 4 and comprises four steps:
step 1: and reading the curve data of the metering points at the moment i. The frozen electric quantity data of the electric energy meter is read regularly every day through an HPLC module.
Step 2: the center distances γ of the n measurement data points at the time i are calculated, respectively. The central distance of the metering value of the jth electric energy meter at the moment i is as follows:
and step 3: calculating the measurement deviation degree of n measurement data points
Degree of measurement point deviation at point j:
and 4, step 4: when measuring the degree of deviation
And m is a measurement abnormity judgment threshold, wherein m is 2, corresponding time information is marked, and measurement point flying abnormity information is output.
The method comprises the steps of diagnosing and simulating abnormal point data of the time-series electric energy meter by using a central distance abnormal point detection algorithm, injecting additive abnormal points, I-type innovation abnormal points and II-type innovation abnormal points into j-28 respectively, and performing a fault simulation result, wherein the simulation result is shown in figures 5-7. Deviation detection represents the best judgment of such data anomalies, with the gauge point deviation approaching 200 at position 28, much greater than 1. For the type I innovation abnormal point, the deviation degree algorithm also shows good judgment capability. The measurement points at the positions of the series 28 deviate by 100 degrees, which is also much greater than 1. The simulation result of the II type innovation abnormal point shows the good judgment of the deviation degree algorithm, and the center distance of the abnormal point at the beginning of the sequence 28 is nearly 4 times higher than that of the normal metering point.
In summary, the present invention provides a method for diagnosing a runaway of an electric energy meter and a high-speed power line carrier module, where the method includes: acquiring electric energy metering values of the electric energy meter which are respectively metered at the same time for a plurality of continuous days; calculating the distance between each metering value and two adjacent metering values as the central distance of the metering values; calculating the relative deviation degree of the center distance; if the relative deviation degree exceeds a set threshold value, judging that the corresponding electric energy meter measures suspected faults, and marking corresponding time information; and judging the fault type, and adopting different processing methods aiming at different types of faults. The invention adopts the distributed HPLC module to directly diagnose at the front end, thereby avoiding network congestion and time delay caused by the traditional method of summarizing data acquisition to the master station diagnosis. The abnormal type is judged according to the measurement deviation degree, so that operation and maintenance maintainers can distinguish the emergency degree of maintenance work and reasonably arrange the operation and maintenance work. Different suspected fault types are judged, so that maintenance personnel can be assisted to quickly locate the fault, and the maintenance efficiency is improved.
It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explaining the principles of the invention and are not to be construed as limiting the invention. Therefore, any modification, equivalent replacement, improvement and the like made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. Further, it is intended that the appended claims cover all such variations and modifications as fall within the scope and boundaries of the appended claims or the equivalents of such scope and boundaries.
Claims (8)
1. A method for diagnosing flying away of an electric energy meter is characterized by comprising the following steps:
acquiring electric energy metering values of the electric energy meter which are respectively metered at the same time for a plurality of continuous days;
calculating the central distance from each metering value to two adjacent metering values;
calculating the relative deviation degree of the center distance;
and if the relative deviation degree exceeds a set threshold value, judging that the corresponding electric energy meter measures suspected faults, and marking corresponding time information.
2. The method for diagnosing flying of the electric energy meter according to claim 1, wherein the electric energy metering value of the electric energy meter which is metered at the same time for a plurality of consecutive days is obtained every day, the relative deviation degree is calculated once, if the relative deviation degree of the electric energy meter in a certain day is judged to exceed the set threshold value k times, suspected faults of the electric energy meter metering are reported, k is an integer, and k is larger than or equal to 3.
3. The method for diagnosing flying of an electric energy meter according to claim 1 or 2,
the jth center distance is:
wherein xjRepresents the measurement of j day, n is more than or equal to j and more than or equal to 2;
the jth relative deviation degree is:
4. the method for diagnosing flying of an electric energy meter according to claim 2, wherein reporting suspected faults of the electric energy meter further comprises: if the average value of the k times of deviation degrees is more than 100, only reporting the suspected fault; and if the average value of the k relative deviation degrees is not more than 10, additionally informing the operation and maintenance staff of carrying out troubleshooting on the electric energy meter.
5. The method for diagnosing flying of an electric energy meter according to claim 2, wherein the reporting of suspected faults of the electric energy meter includes: the method comprises the steps that data messages are added to an HPLC protocol and sent to a concentrator, suspected metering fault information of all electric energy meters in a distribution area is collected by the concentrator, the suspected metering fault information is reported to a master station at fixed time every day, and the master station processes the suspected metering fault information.
6. A high-speed power line carrier module based on diagnosis of electric energy meter flying away is characterized by comprising an acquisition module and a main control module;
the acquisition module acquires the metering values of the electric energy meter frozen every day for a plurality of continuous days and sends the metering values to the main control module;
the main control module comprises a center distance calculation unit, a deviation calculation unit and a comparison unit; the central distance calculating unit reads the metering values of a plurality of continuous days and calculates the central distance from each metering value to two adjacent metering values; the deviation calculating unit calculates a relative deviation degree of the center distance; and the comparison unit compares the relative deviation degree with a set threshold, outputs a suspected fault signal of the corresponding electric energy meter if the relative deviation degree exceeds the set threshold, and marks corresponding time information.
7. The high-speed power line carrier module based on the diagnosis of the electric energy meter flying away according to claim 6, wherein the main control module further comprises an output unit, suspected fault signals of the electric energy meter output by the comparison unit are accumulated, if the suspected fault signals of a certain electric energy meter are accumulated to exceed k, the suspected fault, the corresponding electric energy meter number and the time information are sent to the concentrator in a data message mode, the suspected fault, the corresponding electric energy meter number and the time information are collected by the concentrator and then reported to the main station, wherein k is an integer and is not less than 3.
8. The high-speed power line carrier module based on electric energy meter flying away diagnosis of claim 7, wherein the main control module further comprises a fault judgment unit, and if the average value of the k relative deviation degrees is greater than 100, only a suspected fault is reported; if the average value of the k relative deviation degrees is (10, 100), adding information for immediately maintaining or replacing the corresponding electric energy meter in the data message, and if the average value of the k relative deviation degrees is not more than 10, adding troubleshooting information of an operation and maintenance maintainer to the electric energy meter in the data message.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911145510.7A CN110927655B (en) | 2019-11-21 | 2019-11-21 | Diagnosis method for electric energy meter flying away and high-speed power line carrier module |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911145510.7A CN110927655B (en) | 2019-11-21 | 2019-11-21 | Diagnosis method for electric energy meter flying away and high-speed power line carrier module |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110927655A true CN110927655A (en) | 2020-03-27 |
| CN110927655B CN110927655B (en) | 2022-03-29 |
Family
ID=69851502
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911145510.7A Active CN110927655B (en) | 2019-11-21 | 2019-11-21 | Diagnosis method for electric energy meter flying away and high-speed power line carrier module |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110927655B (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111697997A (en) * | 2020-05-29 | 2020-09-22 | 国网河北省电力有限公司电力科学研究院 | HPLC module rapid detection device and method based on copy controller |
| CN112114990A (en) * | 2020-08-31 | 2020-12-22 | 宁波三星医疗电气股份有限公司 | Method for detecting version abnormity of carrier module |
| CN112819386A (en) * | 2021-03-05 | 2021-05-18 | 中国人民解放军国防科技大学 | Method, system and storage medium for generating time series data with abnormity |
| CN115909705A (en) * | 2023-03-03 | 2023-04-04 | 北京飞利信信息安全技术有限公司 | Data acquisition method, system, terminal and storage medium for HPLC dual-mode communication |
| CN117110975A (en) * | 2023-10-23 | 2023-11-24 | 石家庄科林电力设计院有限公司 | Misalignment detection method and device for multipath electric energy metering device |
| CN118604718A (en) * | 2024-08-08 | 2024-09-06 | 国网山西省电力公司营销服务中心 | Intelligent diagnosis method and system for electric energy metering faults |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE59608514D1 (en) * | 1995-07-21 | 2002-01-31 | Siemens Ag | ELECTRICITY METERS |
| CN103630869A (en) * | 2013-11-29 | 2014-03-12 | 国网安徽省电力公司 | Clustering algorithm-based exceptional event analysis method for evaluating whole state of electric meter |
| CN105182063A (en) * | 2015-09-28 | 2015-12-23 | 安特仪表集团有限公司 | Single-phase electric energy meter, maximum current continuous monitoring method and current variation monitoring method |
| CN106373025A (en) * | 2016-08-22 | 2017-02-01 | 重庆邮电大学 | Outlier detection-based real-time anti-power-theft monitoring method for power utilization information acquisition system |
| CN106707937A (en) * | 2017-01-11 | 2017-05-24 | 山信软件股份有限公司 | Rotary encoder abnormal state on-line monitoring method and device |
| CN109543083A (en) * | 2018-11-19 | 2019-03-29 | 国网陕西省电力公司电力科学研究院 | The detection method of abnormal data in a kind of polynary real-time data of power grid |
| CN110034785A (en) * | 2019-03-27 | 2019-07-19 | 国网山东省电力公司青岛供电公司 | The method that power-off fault quickly positions is realized based on power line carrier communication |
| CN110082699A (en) * | 2019-05-10 | 2019-08-02 | 国网天津市电力公司电力科学研究院 | A kind of low-voltage platform area intelligent electric energy meter kinematic error calculation method and its system |
-
2019
- 2019-11-21 CN CN201911145510.7A patent/CN110927655B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE59608514D1 (en) * | 1995-07-21 | 2002-01-31 | Siemens Ag | ELECTRICITY METERS |
| CN103630869A (en) * | 2013-11-29 | 2014-03-12 | 国网安徽省电力公司 | Clustering algorithm-based exceptional event analysis method for evaluating whole state of electric meter |
| CN105182063A (en) * | 2015-09-28 | 2015-12-23 | 安特仪表集团有限公司 | Single-phase electric energy meter, maximum current continuous monitoring method and current variation monitoring method |
| CN106373025A (en) * | 2016-08-22 | 2017-02-01 | 重庆邮电大学 | Outlier detection-based real-time anti-power-theft monitoring method for power utilization information acquisition system |
| CN106707937A (en) * | 2017-01-11 | 2017-05-24 | 山信软件股份有限公司 | Rotary encoder abnormal state on-line monitoring method and device |
| CN109543083A (en) * | 2018-11-19 | 2019-03-29 | 国网陕西省电力公司电力科学研究院 | The detection method of abnormal data in a kind of polynary real-time data of power grid |
| CN110034785A (en) * | 2019-03-27 | 2019-07-19 | 国网山东省电力公司青岛供电公司 | The method that power-off fault quickly positions is realized based on power line carrier communication |
| CN110082699A (en) * | 2019-05-10 | 2019-08-02 | 国网天津市电力公司电力科学研究院 | A kind of low-voltage platform area intelligent electric energy meter kinematic error calculation method and its system |
Non-Patent Citations (2)
| Title |
|---|
| 李亦非等: "基于局部异常点检测算法的电能表飞走异常智能分析", 《电测与仪表》 * |
| 杨金成 等: "智能电表故障辨识模型研究", 《电器与能效管理技术》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111697997A (en) * | 2020-05-29 | 2020-09-22 | 国网河北省电力有限公司电力科学研究院 | HPLC module rapid detection device and method based on copy controller |
| CN112114990A (en) * | 2020-08-31 | 2020-12-22 | 宁波三星医疗电气股份有限公司 | Method for detecting version abnormity of carrier module |
| CN112114990B (en) * | 2020-08-31 | 2022-04-26 | 宁波三星医疗电气股份有限公司 | Method for detecting version abnormity of carrier module |
| CN112819386A (en) * | 2021-03-05 | 2021-05-18 | 中国人民解放军国防科技大学 | Method, system and storage medium for generating time series data with abnormity |
| CN115909705A (en) * | 2023-03-03 | 2023-04-04 | 北京飞利信信息安全技术有限公司 | Data acquisition method, system, terminal and storage medium for HPLC dual-mode communication |
| CN117110975A (en) * | 2023-10-23 | 2023-11-24 | 石家庄科林电力设计院有限公司 | Misalignment detection method and device for multipath electric energy metering device |
| CN117110975B (en) * | 2023-10-23 | 2024-02-09 | 石家庄科林电力设计院有限公司 | Misalignment detection method and device for multipath electric energy metering device |
| CN118604718A (en) * | 2024-08-08 | 2024-09-06 | 国网山西省电力公司营销服务中心 | Intelligent diagnosis method and system for electric energy metering faults |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110927655B (en) | 2022-03-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110927655B (en) | Diagnosis method for electric energy meter flying away and high-speed power line carrier module | |
| US7469190B2 (en) | Automated system approach to analyzing harmonic distortion in an electric power system | |
| JP6301791B2 (en) | Distribution network failure sign diagnosis system and method | |
| US20140278162A1 (en) | Detecting and locating power outages via low voltage grid mapping | |
| US20150212138A1 (en) | Method for detecting open-circuit faults in electric power distribution system, and power distribution facilities management system | |
| US8000911B2 (en) | Automated hierarchical classification for utility systems with multiple sources | |
| CN110309981A (en) | A kind of power station Decision-making of Condition-based Maintenance system based on industrial big data | |
| CN109142965A (en) | A kind of big data fusion distribution network failure is accurately positioned new method and its device | |
| CN102141808A (en) | Embedded type fault pre-diagnosis system and method for steam turbine generator unit | |
| CN115065591B (en) | Electric vehicle charging pile fault early warning system and method based on state space model | |
| US11740266B2 (en) | Systems and methods for monitoring energy-related data in an electrical system | |
| CN114280414A (en) | Low-voltage distribution network fault positioning system and method based on topology dynamic identification | |
| CN103308859A (en) | Monitoring system and monitoring method for statuses of storage batteries | |
| CN110018437B (en) | Gateway electric energy metering device online monitoring method and system for shunt inspection | |
| WO2017158921A1 (en) | Disconnection detection apparatus | |
| CN107561470B (en) | A kind of fault detector evaluation of running status system | |
| CN115877313A (en) | Power metering detection system | |
| CN104714205A (en) | Electricity meter misplacement detection system and method thereof | |
| CN112684300B (en) | Active power distribution network fault diagnosis method and device using bidirectional monitoring information | |
| CN113590368A (en) | Abnormal equipment diagnosis method and system based on edge-edge coordination | |
| Eikeland et al. | Uncovering contributing factors to interruptions in the power grid: An Arctic Case. Energies 2022, 15, 305 | |
| CN204086497U (en) | Battery pack intelligent diagnosis system in relay station and microwave station | |
| CN117977807B (en) | Real-time monitoring method for remote photovoltaic power system | |
| CN112186893B (en) | Security and protection early warning method based on big data analysis | |
| CN210111696U (en) | Novel acquisition terminal with platform area diagnosis and self-diagnosis functions |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |