CN111383428B - Online meter state monitoring and early warning method - Google Patents
Online meter state monitoring and early warning method Download PDFInfo
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- CN111383428B CN111383428B CN202010471349.9A CN202010471349A CN111383428B CN 111383428 B CN111383428 B CN 111383428B CN 202010471349 A CN202010471349 A CN 202010471349A CN 111383428 B CN111383428 B CN 111383428B
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/182—Level alarms, e.g. alarms responsive to variables exceeding a threshold
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- G—PHYSICS
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- G08C—TRANSMISSION SYSTEMS FOR MEASURED VALUES, CONTROL OR SIMILAR SIGNALS
- G08C19/00—Electric signal transmission systems
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- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
- Y04S20/30—Smart metering, e.g. specially adapted for remote reading
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Abstract
The invention relates to an online meter state monitoring and early warning method, which comprises the following steps: importing original meter reading data of a meter to form a consumption data set; calculating and counting the characteristic quantity of the consumption data set; comparing the remote data in a certain time period of the meter with the characteristic quantity obtained by learning in the original meter reading data totality so as to obtain the state code of the meter; constructing an early warning rule engine of the meter according to the state code of the meter; and sending the early warning information output by the early warning rule engine. The invention judges the running state of the meter by counting the characteristic quantity of the imported original meter reading data, realizes the online state monitoring of the meter, acquires the running state of the meter in time and improves the initiative and the efficiency of operation and maintenance work.
Description
Technical Field
The invention relates to the technical field of town gas Internet of things application, in particular to an online meter state monitoring and early warning method.
Background
The remote meter reading is gradually applied as an important means for improving the service efficiency and the service quality in the gas industry, but in an actual application scene, due to the complexity of the meter reading network arrangement environment, meters and networks are affected by factors such as natural environment erosion under complex conditions or artificial damage of a third party, and the like, and faults are inevitable.
Because the operation and maintenance mode of the meter and the network is still in the stage of after-event response, the state of the meter is not effectively monitored, and the quality of the remote meter reading service is influenced. In order to realize the operation and maintenance mode of the meter for prevention in advance, the remote meter reading service quality is further improved, and the meter is continuously monitored in time.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provide an online meter state monitoring and early warning method, which is used for monitoring the online state of a meter, acquiring the running state of the meter in time and improving the initiative of operation and maintenance.
In order to achieve the above object, the embodiments of the present invention provide the following technical solutions:
an online meter state monitoring and early warning method comprises the following steps:
step S1: importing original meter reading data of a meter to form a consumption data set;
step S2: calculating and counting the characteristic quantity of the consumption data set;
step S3: comparing the remote data in a period of time with the characteristic quantity obtained by learning in the original meter reading data population according to the meter, thereby obtaining the state code of the meter;
step S4: constructing an early warning rule engine of the meter according to the state code of the meter;
step S5: and sending the early warning information output by the early warning rule engine.
Further, in order to better implement the present invention, the step S1 specifically includes the following steps:
step S1-1: importing original meter reading data of meter history, and cleaning to form a meter reading data set; the meter reading data set comprises a label, meter reading time and meter reading data, wherein the meter reading time is taken as an integral point;
step S1-2: performing first-order difference on the meter reading data set to obtain a consumption data set; the usage data set comprises a table number, a gas usage time period and usage.
Further, in order to better implement the present invention, the step S2 specifically includes the following steps:
step S2-1: grouping the data sets of the consumption according to the meter numbers, respectively counting the number of meter reading data of each meter according to the day, and further calculating the frequency of the data quantity obtained by the number of the meter reading data of all the meters every day; selecting the data quantity of the frequency top n as a characteristic quantity estimated value of a set frequency set of the meter according to the type total number n of the meter;
step S2-2: and calculating the frequency value of the recording time point of the meter reading data by taking the data volume of all the meters as a standard, setting a quantile numerical value after sequencing from high to low, and taking the recording time point accumulated to the quantile numerical value as the characteristic quantity estimated value of the sending time point of the set data of the meters when the frequency value accumulated to the recording time point reaches the quantile numerical value.
Further, for better implementing the present invention, the status code of step S3 is a three-bit binary number, wherein:
when the first bit is 0, the meter has no uploading data in the time interval, and when the first bit is 1, the meter has uploading data in the time interval;
when the second bit is 0, the data volume read by the meter in the time period is abnormal, and when the second bit is 1, the data volume read by the meter in the time period is abnormal;
the third bit is 0, which indicates that the reading time of the meter in the time period is not abnormal, and 1, which indicates that the reading time of the meter in the time period is abnormal.
Further, in order to better implement the present invention, the warning rule engine of step S4 includes:
when the state code of the meter is 100, the meter is normal and no early warning is given;
when the state codes of the meters are 000, 001, 010 and 011, the meters are abnormal and cannot be read, and the early warning level is 4 levels;
when the state code of the meter is 111, the meter is abnormal, the read data volume is abnormal, the reading time point is abnormal, and the early warning level is 3 levels;
when the state code of the meter is 110, the meter is abnormal, the read data volume is abnormal, and the early warning level is 2 level;
when the state code of the meter is 101, the meter is abnormal, the reading time point is abnormal, and the early warning level is 1 level.
Further, in order to better implement the present invention, the step S5 specifically includes the following steps:
and sending the early warning information output by the early warning rule engine to a worker for early warning in a mail or short message mode.
Further, in order to better implement the present invention, the step of importing the original meter reading data of the meter includes:
the meter uploads original meter reading data to a meter reading data server through a transmission network;
and importing original meter reading data remotely transmitted by a meter from a meter reading data server.
An online meter state monitoring and early warning system, comprising:
the data import module is used for importing original meter reading data of the meter and forming a consumption data set;
the data characteristic learning module is used for calculating and counting the characteristic quantity of the consumption data set;
the meter state representation module is used for obtaining a state code of the meter in a time period;
the early warning rule engine module is used for constructing an early warning rule engine of the meter according to the state code of the meter;
and the early warning information output module is used for sending the early warning information output by the early warning rule engine.
Compared with the prior art, the invention has the beneficial effects that:
the invention judges the running state of the meter by counting the characteristic quantity of the imported original meter reading data, realizes the online state monitoring of the meter, acquires the running state of the meter in time and improves the initiative and the efficiency of operation and maintenance work.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a flow chart of a monitoring and early warning method of the present invention;
FIG. 2 is a block diagram of a monitoring and early warning system according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
Example 1:
the invention is realized by the following technical scheme, as shown in figure 1, an online meter state monitoring and early warning method comprises the following steps:
step S1: and importing original meter reading data of the meter to form a consumption data set.
The meter transmits the original meter reading data to a meter reading data server through a transmission network, and the original meter reading data remotely transmitted by the meter reading data server is imported. Cleaning the imported original meter reading data to form a meter reading data set; the meter reading data set comprises a label, meter reading time and meter reading data, wherein the meter reading time is taken as an integral point.
Then, performing first-order difference on the meter reading data set to obtain a consumption data set; the usage data set comprises a table number, a gas usage time period and usage.
Step S2: and carrying out characteristic quantity calculation and statistics on the consumption data set.
Grouping the data sets of the consumption according to the meter numbers, respectively counting the number of meter reading data of each meter according to the day, and further calculating the frequency of the data quantity obtained by the number of the meter reading data of all the meters every day; according to the total number n of types of the table, the data quantity of the frequency top n is selected as the characteristic quantity estimated value of the table setting frequency set.
And calculating the frequency value of the recording time point of the meter reading data by taking the data volume of all the meters as a standard, setting a quantile numerical value after sequencing from high to low, and taking the recording time point accumulated to the quantile numerical value as the characteristic quantity estimated value of the sending time point of the set data of the meters when the frequency value accumulated to the recording time point reaches the quantile numerical value.
Step S3: and comparing the remote data in a certain period of time of the meter, such as the remote data in one month, with the characteristic quantity obtained by learning in the original meter reading data population to obtain the state code of the meter.
The state code is a three-bit binary number, wherein:
when the first bit is 0, the meter has no uploading data in the time interval, and when the first bit is 1, the meter has uploading data in the time interval;
when the second bit is 0, the data volume read by the meter in the time period is abnormal, and when the second bit is 1, the data volume read by the meter in the time period is abnormal;
the third bit is 0, which indicates that the reading time of the meter in the time period is not abnormal, and 1, which indicates that the reading time of the meter in the time period is abnormal.
Step S4: and constructing an early warning rule engine of the meter according to the state code of the meter.
The early warning rule engine includes:
when the state code of the meter is 100, the meter is normal and no early warning is given;
when the state codes of the meters are 000, 001, 010 and 011, the meters are abnormal and cannot be read, and the early warning level is 4 levels;
when the state code of the meter is 111, the meter is abnormal, the read data volume is abnormal, the reading time point is abnormal, and the early warning level is 3 levels;
when the state code of the meter is 110, the meter is abnormal, the read data volume is abnormal, and the early warning level is 2 level;
when the state code of the meter is 101, the meter is abnormal, the reading time point is abnormal, and the early warning level is 1 level.
Step S5: and sending the early warning information output by the early warning rule engine.
And sending the early warning information output by the early warning rule engine to a worker for early warning in a mail or short message mode.
Based on the monitoring and early warning method, as shown in fig. 2, the invention also provides an online meter state monitoring and early warning system, which comprises:
the data import module is used for importing original meter reading data of the meter and forming a consumption data set;
the data characteristic learning module is used for calculating and counting the characteristic quantity of the consumption data set;
the meter state representation module is used for obtaining a state code of the meter in a time period;
the early warning rule engine module is used for constructing an early warning rule engine of the meter according to the state code of the meter;
and the early warning information output module is used for sending the early warning information output by the early warning rule engine.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (5)
1. An online meter state monitoring and early warning method is characterized in that: the method comprises the following steps:
step S1: importing original meter reading data of a meter to form a consumption data set;
step S2: calculating and counting the characteristic quantity of the consumption data set;
step S3: comparing the remote data in a certain time period of the meter with the characteristic quantity obtained by learning in the original meter reading data totality so as to obtain the state code of the meter;
step S4: constructing an early warning rule engine of the meter according to the state code of the meter;
step S5: sending early warning information output by an early warning rule engine;
the step S1 specifically includes the following steps:
step S1-1: importing original meter reading data of meter history, and cleaning to form a meter reading data set; the meter reading data set comprises a label, meter reading time and meter reading data, wherein the meter reading time is taken as an integral point;
step S1-2: performing first-order difference on the meter reading data set to obtain a consumption data set; the usage data set comprises a table number, a gas consumption time period and usage;
the step S2 specifically includes the following steps:
step S2-1: grouping the data sets of the consumption according to the meter numbers, respectively counting the number of meter reading data of each meter according to the day, and further calculating the frequency of the data quantity obtained by the number of the meter reading data of all the meters every day; selecting the data quantity of the frequency top n as a characteristic quantity estimated value of a set frequency set of the meter according to the type total number n of the meter;
step S2-2: and calculating the frequency value of the recording time point of the meter reading data by taking the data volume of all the meters as a standard, setting a quantile numerical value after sequencing from high to low, and taking the recording time point accumulated to the quantile numerical value as the characteristic quantity estimated value of the sending time point of the set data of the meters when the frequency value accumulated to the recording time point reaches the quantile numerical value.
2. The online meter state monitoring and early warning method according to claim 1, characterized in that: the status code in step S3 is a three-digit binary number, wherein:
when the first bit is 0, the meter has no uploading data in the time interval, and when the first bit is 1, the meter has uploading data in the time interval;
when the second bit is 0, the data volume read by the meter in the time period is abnormal, and when the second bit is 1, the data volume read by the meter in the time period is abnormal;
the third bit is 0, which indicates that the reading time of the meter in the time period is not abnormal, and 1, which indicates that the reading time of the meter in the time period is abnormal.
3. The online meter state monitoring and early warning method according to claim 2, characterized in that: the early warning rule engine of step S4 includes:
when the state code of the meter is 100, the meter is normal and no early warning is given;
when the state codes of the meters are 000, 001, 010 and 011, the meters are abnormal and cannot be read, and the early warning level is 4 levels;
when the state code of the meter is 111, the meter is abnormal, the read data volume is abnormal, the reading time point is abnormal, and the early warning level is 3 levels;
when the state code of the meter is 110, the meter is abnormal, the read data volume is abnormal, and the early warning level is 2 level;
when the state code of the meter is 101, the meter is abnormal, the reading time point is abnormal, and the early warning level is 1 level.
4. The online meter state monitoring and early warning method according to claim 3, characterized in that: the step S5 specifically includes the following steps:
and sending the early warning information output by the early warning rule engine to a worker for early warning in a mail or short message mode.
5. The online meter state monitoring and early warning method according to any one of claims 1 to 4, characterized in that: the step of importing the original meter reading data of the meter comprises the following steps:
the meter uploads original meter reading data to a meter reading data server through a transmission network;
and importing original meter reading data remotely transmitted by a meter from a meter reading data server.
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| CN202010471349.9A CN111383428B (en) | 2020-05-29 | 2020-05-29 | Online meter state monitoring and early warning method |
| KR1020210067929A KR102406589B1 (en) | 2020-05-29 | 2021-05-26 | Eerly warning method by monitoring the online meter status |
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| US20090055237A1 (en) * | 2007-08-23 | 2009-02-26 | Henry Bruce P | System and method for managing inherent project uncertainty |
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Address after: No. 536, Section 1, airport 1st Road, Southwest Airport, Shuangliu District, Chengdu, Sichuan 610211 Patentee after: Chengdu Qianjia Technology Co.,Ltd. Address before: No. 536, Section 1, airport 1st Road, Southwest Airport, Shuangliu District, Chengdu, Sichuan 610211 Patentee before: Chengdu Qianjia Technology Co.,Ltd. |