CN113282639B - Gas leakage data monitoring method and system, intelligent terminal and storage medium - Google Patents
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Abstract
The application relates to a method and a system for monitoring gas leakage data, an intelligent terminal and a storage medium, which belong to the field of gas monitoring, wherein the method comprises the steps of obtaining a first statistical request sent by an administrator; responding to the first statistical request, and acquiring early warning information of each user from a gas database; integrating the early warning information to generate statistical early warning information, wherein the statistical early warning information comprises basic information and early warning times; clustering the statistical early warning information according to the statistical early warning times and the basic information to generate a plurality of central point information and early warning lists, wherein the central point information comprises the corresponding central point early warning times; sequentially judging whether the early warning times of the central point are greater than a preset early warning time threshold value or not; and if the early warning times are larger than the early warning times threshold value, feeding back the early warning list corresponding to the early warning times of the central point to an administrator. This application has and is reducing under the prerequisite that the occurence of failure was revealed in the gas, the effect that the minimize influences people daily life.
Description
Technical Field
The application relates to the field of gas monitoring, in particular to a gas leakage data monitoring method, a gas leakage data monitoring system, an intelligent terminal and a storage medium.
Background
The gas leakage refers to the situation that gas leaks into air from a pipeline or a steel cylinder due to accidents, and when the mixing ratio of the gas and the air reaches a certain degree, any ignition spark is easy to ignite or explode, so that serious life and property losses are caused.
The invention with publication number CN109581929A provides a method and a device for processing gas leakage, and the method comprises the following steps: judging whether the gas leaks or not according to the monitored environmental parameters and the monitored human body parameters, wherein the environmental parameters comprise temperature, humidity, gas concentration and the like, and the human body parameters comprise body temperature, heart rate, pulse and the like; if the gas leaks, calculating the leakage grade of the gas; calculating and generating an influence index according to the leakage grade and the time length of the user entering the gas leakage environment; according to the influence index, a process action such as reducing the supply air or shutting off the valve is performed, thereby minimizing damage caused by gas leakage.
The related art described above has the following drawbacks: the potential value of gas leakage data is not developed, the current gas condition can only be detected and corresponding emergency operation can be executed, but inconvenience can be caused to daily life of people no matter gas supply is reduced or a valve is closed.
Disclosure of Invention
In order to reduce the influence on the daily life of people as much as possible on the premise of ensuring that the occurrence of gas leakage accidents is reduced, the application provides a gas leakage data monitoring method, a gas leakage data monitoring system, an intelligent terminal and a storage medium.
In a first aspect, the present application provides a gas leakage data monitoring method, which adopts the following technical scheme:
a gas leakage data monitoring method comprises the following steps:
acquiring a first statistical request sent by an administrator;
responding to the first statistical request, and acquiring early warning information of each user from a gas database;
integrating the early warning information to generate statistical early warning information of each user, wherein the statistical early warning information comprises basic information and early warning times, and the early warning times are the number of the early warning information of the corresponding user;
clustering the statistical early warning information according to the statistical early warning times and the basic information to generate a plurality of central point information and early warning lists corresponding to the central point information one by one, wherein the central point information comprises the corresponding central point early warning times;
sequentially judging whether the early warning times of the central point are greater than a preset early warning time threshold value or not;
and if the central point early warning times are larger than a preset early warning time threshold value, feeding back the central point information and the early warning list corresponding to the central point early warning times to the administrator.
Through adopting above-mentioned technical scheme, early warning information in with the gas database is clustered according to early warning number of times and basic information, divide into a plurality of different information groups, summarize the early warning information of group in with the central point information of every group, early warning information in every group all has similar early warning number of times and basic information, when the early warning number of times is too big, the suggestion user carries out the analysis according to the clustering result, thereby fully develop the potential value of revealing the data, utilize current gas to reveal data analysis and reveal the reason, in time compensate, prevent suffering from in the bud, under the prerequisite that reduces the possibility that the gas was revealed and takes place, reduce and cause the influence to people's daily life.
Optionally, the first statistical request includes a statistical time period input by the administrator; the early warning information also comprises early warning time;
the step of integrating the early warning information to generate statistical early warning information of each user specifically includes:
and integrating the early warning information of each user within the statistical time period of the early warning time to generate the statistical early warning information of each user.
By adopting the technical scheme, the user can freely select the early warning information in a certain time period to generate the statistical early warning information and then perform clustering without judging all the statistical early warning information, so that the clustering is more targeted, and the use and the analysis of the user are facilitated.
Optionally, the gas database is generated by the following method:
acquiring the gas leakage amount of each user according to a preset period;
judging whether the gas leakage amount is larger than a preset first leakage amount threshold value or not;
and if the gas leakage amount is greater than a preset first leakage amount threshold value, generating corresponding early warning information, and recording the early warning information in the gas database.
By adopting the technical scheme, the leakage threshold value is preset, when the gas leakage is greater than the preset value, the early warning information can be automatically generated and stored in the gas database, the smaller gas leakage is recorded and the early warning is generated, and therefore the possibility of major accidents caused by the smaller gas leakage is reduced.
Optionally, the generating corresponding early warning information and recording the early warning information in the gas database further include:
acquiring the gas leakage amount of each user in real time;
judging whether the gas leakage amount is larger than a preset second leakage amount threshold value or not, wherein the second leakage amount threshold value is larger than the first leakage amount threshold value;
if the gas leakage amount is larger than a preset second leakage amount threshold value, generating alarm information, and recording the alarm information in the gas database;
and executing corresponding valve turn-off operation according to the alarm information.
Through adopting above-mentioned technical scheme, let out the gas leakage quantity and arouse the early warning after, carry out closer monitoring to it, let out when the gas leakage quantity is too big, generate alarm information and carry out the record to in time turn-off the valve that corresponds, use this as the bottom line, ensure user's safety.
Optionally, the alarm information includes an alarm time;
after the early warning information is integrated to generate the statistical early warning information of each user, the method further comprises the following steps:
acquiring alarm information of each user within the statistic time period at the alarm time;
calculating the number of the acquired alarm information, and generating the alarm times of each user;
and updating the early warning times of the statistical early warning information of the corresponding users according to the alarm times and a preset conversion coefficient so as to perform clustering.
By adopting the technical scheme, the clustering operation is not limited to the early warning information, and the gas leakage condition of the alarm information is more serious than the early warning information theoretically, so that the alarm information is converted, supplemented into the early warning information and clustered, and the generated central point information after clustering is more accurate.
Optionally, the method further includes:
acquiring a second statistical request sent by an administrator aiming at a certain user, wherein the second statistical request comprises a plurality of comparison time periods input by the administrator;
acquiring early warning information of the user according to the comparison time period;
calculating the number of early warning information of the early warning time belonging to each comparison time period from a gas database, and generating comparison early warning times, wherein the comparison early warning times correspond to the comparison time periods one by one;
generating average early warning times according to the number of the comparison information and the corresponding duration of the comparison time period;
and generating a historical curve according to the comparison time period and the average early warning times, and feeding back the historical curve to the administrator.
By adopting the technical scheme, the average occurrence frequency of the early warning frequency in each time period is calculated according to the comparison time periods divided by the administrator, so that the early warning information of a certain user is transversely compared, the administrator can conveniently observe whether the gas leakage condition of each user is improved, and the adopted measures can be evaluated.
Optionally, the method further includes:
obtaining the screening conditions input by the administrator,
screening the early warning information in a gas database according to the screening conditions to generate a display table;
acquiring an export request sent by an administrator, wherein the export request comprises an export file format;
exporting the presentation locally in the export file format in response to the export request.
By adopting the technical scheme, the administrator can obtain the required early warning information from the gas database through screening, and the early warning information is exported to the local for storage, so that the administrator can conveniently check the early warning information later.
In a second aspect, the present application provides a gas leakage data monitoring system, which adopts the following technical scheme:
a gas leak data monitoring system, comprising:
the early warning information statistics module is used for acquiring a first statistics request sent by an administrator; responding to the first statistical request, and acquiring early warning information of each user from a gas database; integrating the early warning information to generate statistical early warning information of each user, wherein the statistical early warning information comprises basic information and early warning times, and the early warning times are the number of the early warning information of the corresponding user;
the basic information clustering module is used for clustering the statistical early warning information according to the statistical early warning times and the basic information to generate a plurality of central point information and early warning lists corresponding to the central point information one by one, wherein the central point information comprises the corresponding central point early warning times;
the abnormity feedback module is used for sequentially judging whether the early warning times of the central point are greater than a preset early warning time threshold value; and if the central point early warning times are larger than a preset early warning time threshold value, feeding back the central point information and the early warning list corresponding to the central point early warning times to the administrator.
By adopting the technical scheme, the early warning information in the gas database is clustered, the central point information is generated according to the early warning information with similar early warning times and basic information, the central point information is fed back to a user, the user can conveniently investigate the cause of the larger early warning times, measures are taken in time, serious disasters caused by continuous development of the early warning information are avoided, the situation that gas leakage is prevented by directly breaking a brake is reduced as much as possible, and the influence on life of people is reduced while the safety of the gas is guaranteed.
In a third aspect, the present application provides an intelligent terminal, which adopts the following technical scheme:
an intelligent terminal comprising a memory and a processor, said memory having stored thereon a computer program that can be loaded by the processor and that executes the method according to the first aspect.
By adopting the technical scheme, the early warning information can be clustered, the central point information with similar basic information and early warning times is fed back to the user, the user can conveniently conduct troubleshooting and investigation, measures can be taken in time, and the gas leakage condition generated by the corresponding basic information can be solved in time, so that the situation is prevented from happening in the bud, and the influence on the daily life of people is reduced.
In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solutions:
a computer readable storage medium comprising a computer program stored thereon which is loadable by a processor and adapted to carry out the method of the first aspect.
By adopting the technical scheme, after the computer-readable storage medium is loaded into any computer, the computer can execute the gas leakage data monitoring method in the first aspect.
In summary, the present application includes at least one of the following beneficial technical effects:
1. the early warning information with similar early warning times and basic information is fed back to the administrator, so that the administrator can conveniently investigate the cause of larger early warning times, take measures in time to prevent the situation in the bud, reduce the situation that the gas leakage is prevented by directly switching off the brake as much as possible, and reduce the influence on the life of people while ensuring the safety of the gas;
2. according to the comparison time periods divided by the administrator, the average occurrence times of the early warning times in each time period is calculated and a historical curve is generated, so that the early warning information of a certain user is transversely compared, and the administrator can observe whether the gas leakage condition of each user is improved or not.
Drawings
Fig. 1 is a schematic flow chart of a gas leakage data monitoring method according to an embodiment of the present application.
Fig. 2 is a schematic flowchart of an embodiment of the present application, which is performed to facilitate analysis of leakage data of the same user.
Fig. 3 is a schematic flow chart of an embodiment of the present application for facilitating a user to view gas data locally.
Fig. 4 is a block diagram of a gas leakage data monitoring system according to an embodiment of the present application.
Description of reference numerals: 1. a pre-warning information statistics module; 2. a basic information clustering module; 3. an anomaly feedback module; 4. a database generation module; 5. a curve generation module; 6. and a file export module.
Detailed Description
The present application is described in further detail below with reference to figures 1-4.
The embodiment of the application discloses a gas leakage data monitoring method. Referring to fig. 1, the gas leakage data monitoring method includes:
s100: and acquiring a first statistical request sent by an administrator.
The first statistical request comprises a statistical time period input by an administrator, and the statistical time period is specific to a day. Specifically, the administrator may input the upper statistical time limit and the lower statistical time limit on an administrator terminal such as a computer, and then click a virtual button on a screen of the administrator terminal, integrate the upper statistical time limit and the lower statistical time limit as a statistical time period, and send a first statistical request including the statistical time period.
S200: and acquiring early warning information of each user from the gas database.
The gas database stores early warning information and alarm information of each gas user about gas leakage, the early warning information describes specific conditions of corresponding users when slight gas leakage occurs, the early warning information comprises early warning time, the early warning time is specific to minutes, each user can correspond to a plurality of pieces of early warning information, and the user is represented to have gas leakage for many times in a statistical time period.
The specific method of generating the gas database is as follows: according to a preset period, calculating and obtaining the gas leakage amount of each user according to a gas detection sensor installed in each user residence, then judging whether the gas leakage amount is larger than a preset first leakage amount threshold value or not, and if the gas leakage amount is smaller than or equal to the preset first leakage amount threshold value, continuing to judge the gas leakage amount of the next user; if the gas leakage amount is larger than a preset first leakage amount threshold value, generating early warning information, recording basic information such as time for generating early warning and a gas account number of a current user residence, and storing the generated early warning information into a gas database.
After the gas leakage amount is larger than a preset first leakage amount threshold value, the gas leakage amount of the user is continuously obtained in real time, and the obtained gas leakage amount is compared with a preset second leakage amount threshold value. It should be noted that, the first leakage threshold and the second leakage threshold are both set by professional personnel, and the second leakage threshold is greater than the first leakage threshold, and when the gas leakage reaches the second leakage threshold, it indicates that the gas leakage is serious, and the possibility of dangerous accidents such as explosion or fire is great. Therefore, if the gas leakage amount is smaller than or equal to the preset second leakage amount threshold value, the gas leakage amount of the user is continuously obtained and judged; and if the gas leakage amount is larger than a preset second leakage amount threshold value, generating alarm information, recording the time for generating the alarm, the gas account number of the current user residence and other basic information, and storing the alarm information into a gas database.
S300: and integrating the acquired early warning information to generate statistical early warning information.
The statistical early warning information comprises basic information and statistical early warning times n, wherein n is more than or equal to 0. Specifically, for each user, the early warning information of the early warning time in the statistical time period is integrated to generate statistical early warning information, the statistical early warning information corresponds to the users one to one, the basic information consists of a plurality of basic values x, the basic values x can be specific contents of gas household numbers, geographic positions, service lives and the like of the users, and the statistical early warning times n are statistical early warning times of gas leakage of the users in the statistical time period, namely the number of the early warning information.
S400: and supplementing the statistical early warning information according to the warning information.
Wherein, the alarm information comprises a corresponding gas account number and alarm time, and the alarm time is specific to minutes. Specifically, for each user, acquiring alarm information of alarm time in a statistical time period, calculating the number of the acquired alarm information, generating the alarm times m of each user in the statistical time period, multiplying the preset conversion coefficient k by the alarm times m, adding the multiplication result m × k to the statistical early warning times n of the statistical early warning information with the same number of the gas users, and obtaining updated statistical early warning times
，
。
S500: and clustering the statistical early warning information according to the statistical early warning times and certain basic information to generate a plurality of pieces of central point information.
The central point information comprises central point early warning times and central point basic data. The basic data x may be data information such as age or geographical location that may be the reason for generating the early warning, and the administrator may select from the administrator terminal to determine the specific indication of the basic value x.
In particular, the updated statistical warning times
And describing each statistical early warning information by a certain basic value x, and clustering all the statistical early warning information by adopting a mean shift clustering algorithm: firstly, counting all the early warning times
A pieces of central point information which are uniformly distributed are randomly generated between the maximum value and the minimum value of the basic value x, and the central point information comprises a central pointNumber of alarm times
And center point base value
(ii) a Calculating the distance d and the distance between each statistical early warning information and the central point information
Then, comparing the distance d with a preset radius r, and adding the statistical early warning information into an early warning list of corresponding central point information when the distance d is smaller than or equal to the preset radius r; after all the statistical early warning information is judged, calculating to generate an average vector according to the early warning information in the early warning list, and moving the central point information according to the corresponding average vector obtained by calculation to finish updating; and then, regenerating an early warning list according to the updated central point information, and generating final central point information and an early warning list after iteration reaches a preset number of times.
S600: and sequentially judging whether the central point early warning times of the central point early warning information are greater than a preset early warning time threshold value.
Specifically, the central point early warning times of each central point early warning information are sequentially compared with a preset early warning time threshold, and if the central point early warning times of the current central point early warning information are greater than the preset early warning time threshold, the operation jumps to S700; and if the central point early warning times of the current central point early warning information are less than or equal to a preset early warning time threshold value, continuing to judge the next central point early warning times.
S700: and feeding back the central point information and the early warning list corresponding to the central point early warning times to an administrator.
Specifically, the central point information and the early warning list corresponding to the central point early warning times which are judged to be greater than the early warning time threshold are obtained, and the central point early warning times, the central point basic data and all the early warning information in the early warning list are displayed on a screen of an administrator terminal for an administrator to check.
To facilitate analysis of the leakage data of the same user, referring to fig. 2, the method further comprises:
s11: and acquiring a second statistical request sent by an administrator for a certain user.
The second statistical request comprises a plurality of comparison time periods input by the administrator, and no intersection exists among different comparison time periods. Specifically, the administrator may select or input a certain gas account number on the administrator terminal, then select or input a plurality of comparison time periods, and after the setting is completed, click a certain preset virtual button on the screen to send the second statistical request.
S12: and acquiring all early warning information of the user according to the comparison time period.
Specifically, after receiving the second statistical request sent by the user, the comparison time periods input by the user are compared to obtain the upper time limit of the earliest comparison time period and the lower time limit of the latest comparison time period. And then acquiring all early warning information under the gas user number input by the user from the gas database, and screening and reserving the early warning information of the early warning time between the upper time limit and the lower time limit from the acquired early warning information.
S13: and calculating the number of the early warning information belonging to each comparison time period, and generating comparison early warning times.
And the comparison early warning times correspond to the comparison time periods one by one. Specifically, the comparison time periods input by the user are set in the order from near to far, then the early warning time of each early warning information is compared with each comparison time period in sequence, when a certain early warning time is judged to belong to a certain comparison time period, the comparison early warning frequency corresponding to the comparison time period is added with 1, the comparison early warning frequency is preset to 0, and the process jumps to S14 after all the early warning information are matched with the corresponding comparison time periods.
S14: and generating average early warning times according to the comparison time period and the comparison early warning times.
Specifically, the comparison time period input by the administrator is used as a cycle characteristic, the time upper limit of the current comparison time period is subtracted from the corresponding time lower limit to generate the duration of the comparison time period, and then the average early warning times of the comparison time period are generated by dividing the comparison early warning times corresponding to each comparison time period by the duration of the corresponding comparison time period. It should be noted that the average number of early warning times corresponds to the comparison time period.
S15: and generating a historical curve according to the comparison time period and the average early warning times, and feeding the historical curve back to the administrator.
Specifically, a rectangular coordinate system is established by taking the comparison time period as a horizontal axis and the average early warning times as a vertical axis, a history curve is generated in a linear fitting mode, and the rectangular coordinate system and the history curve are displayed on an administrator terminal for an administrator to check.
To facilitate the user viewing the gas data locally, referring to fig. 3, the method further comprises:
s21: and acquiring a screening request sent by an administrator.
Wherein the screening request includes screening conditions selected by the administrator, such as a gas number of A or
And
the age between, etc. Specifically, the administrator may perform check-in on the screening condition on the administrator terminal, then click a preset virtual button, and send the screening request.
S22: and responding to the screening request, and generating a display table according to the early warning information.
Specifically, after a screening request sent by an administrator is received, all the early warning information is screened in the gas database according to screening conditions selected by the administrator, the early warning information meeting the corresponding screening conditions is reserved, a display form is generated, and the display form is displayed on a display interface of the management terminal for the administrator to check.
S23: and acquiring an export request sent by an administrator.
Specifically, the administrator clicks another preset virtual button on the administrator interface, then selects an export file format as TXT or Excel in the appearing selection box, and after clicking the corresponding format, sends an export request for the current display form.
S24: and exporting the display list to the local in a preset format in response to the export request.
Specifically, after receiving the export request, the display list is exported to the local according to the selected file format, so that the query of an administrator is facilitated.
The implementation principle is as follows: acquiring a first statistical request sent by an administrator, responding to the first statistical request, integrating early warning information of each user in a gas database during a statistical time period to generate statistical early warning information, representing the corresponding user by using the early warning times of the statistical early warning information and a certain basic value, clustering according to the early warning times and the basic value to generate central point information and an early warning list, finally judging whether the central point early warning times of the central point information is greater than a preset early warning time threshold value, if so, feeding the corresponding central point information and the early warning list back to the administrator, so that the administrator can conveniently investigate the users with more early warning times according to the basic value during clustering, timely eliminate the leakage hidden danger caused by the basic value, and fully utilize the potential value of gas leakage data, the possibility of dangerous accidents caused by gas leakage can be reduced, and inconvenience to daily life of people can be avoided.
Based on the method, the embodiment of the application also discloses a gas leakage data monitoring system. Referring to fig. 4, the gas leakage data monitoring system includes an early warning information statistics module 1, a basic information clustering module 2, an anomaly feedback module 3, a database generation module 4, a curve generation module 5, and a file export module 6.
The early warning information statistics module 1 is used for acquiring a first statistics request sent by an administrator, acquiring early warning information meeting the statistics time period input by the administrator from a gas database, and integrating the acquired early warning information to generate statistics early warning information of each user.
And the basic information clustering module 2 is used for updating the counting early warning times in the counting early warning information according to the alarm information, clustering the counting early warning information according to the updated counting early warning times and a certain basic information in the counting early warning information, and generating a plurality of central point information and early warning lists corresponding to the central point information.
And the abnormity feedback module 3 is used for sequentially judging whether the central point early warning times are greater than a preset early warning time threshold value, and if the central point early warning times are greater than the preset early warning time threshold value, feeding back the central point information and the early warning list corresponding to the central point early warning to the user.
And the database generation module 4 is used for acquiring the gas leakage amount of each user, comparing the gas leakage amount with the first gas leakage threshold value and the second gas leakage threshold value, generating early warning information or alarm information when the conditions are met, and storing the generated early warning information or alarm information into a gas database.
And the curve generation module 5 is configured to acquire a second statistical request sent by an administrator for a certain user, classify all the early warning information of the user into the corresponding comparison time period, generate comparison early warning times, generate an average early warning time according to the duration of the comparison time period, and then draw and generate a history curve to feed back the history curve to the administrator.
And the file export module 6 is used for feeding back the display list generated after screening to the administrator.
The embodiment of the application also discloses an intelligent terminal, which comprises a memory and a processor, wherein the memory is stored with a computer program which can be loaded by the processor and can execute the gas leakage data monitoring method.
The embodiment of the present application further discloses a computer readable storage medium, which stores a computer program that can be loaded by a processor and execute the gas leakage data monitoring method as described above, and the computer readable storage medium includes, for example: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above examples are only used to illustrate the technical solutions of the present application, and do not limit the scope of protection of the application. It is to be understood that the embodiments described are only some of the embodiments of the present application and not all of them. All other embodiments, which can be derived by a person skilled in the art from these embodiments without making any inventive step, are within the scope of the present application.
Claims (9)
1. A gas leakage data monitoring method is characterized by comprising the following steps:
acquiring a first statistical request sent by an administrator, wherein the first statistical request comprises a statistical time period input by the administrator;
responding to the first statistical request, acquiring early warning information of each user from a gas database, wherein the early warning information further comprises early warning time, the early warning information describes specific conditions when slight gas leakage occurs to the corresponding user, and each user can correspond to a plurality of pieces of the early warning information and represents that the user has multiple gas leakage within the statistical time period;
integrating the early warning information of each user within the statistical time period of the early warning time to generate statistical early warning information of each user; supplementing the statistical early warning information according to alarm information, wherein the alarm information comprises a corresponding gas household number and alarm time; for each user, acquiring alarm information of the alarm time in the statistical time period, and calculating the number of the alarm information; generating the alarm times m of each user in the statistical time period, multiplying the alarm times m by a preset conversion coefficient k, and adding the product result m × k and the statistical early warning times n of the statistical early warning information with the same gas user number to obtain updated statistical early warning times n ', namely n' = n + m × k;
randomly generating a pieces of uniformly distributed central point information between the maximum value and the minimum value of all statistical early warning times n' and the maximum value and the minimum value of the basic value x, wherein the central point information comprises the central point early warning timesA number n 'and a base value x' of the center point; calculating a distance d between each statistical early warning information and the central point information, wherein a calculation formula of the distance d is as follows:
(ii) a Comparing the distance d with a preset radius r, and adding the statistical early warning information into an early warning list of corresponding central point information when the distance d is smaller than or equal to the radius r; after all the statistical early warning information is judged, calculating and generating an average vector according to the early warning information in the early warning list; moving the central point information according to the corresponding average vector obtained by calculation to finish updating; regenerating an early warning list according to the updated central point information, and generating final central point information and an early warning list after iteration reaches a preset number of times, wherein the central point information comprises corresponding central point early warning times;
sequentially judging whether the early warning times of the central point are greater than a preset early warning time threshold value or not;
and if the central point early warning times are larger than a preset early warning time threshold value, feeding back the central point information and the early warning list corresponding to the central point early warning times to the administrator.
2. The gas leak data monitoring method of claim 1, wherein the gas database is generated by:
acquiring the gas leakage amount of each user according to a preset period;
judging whether the gas leakage amount is larger than a preset first leakage amount threshold value or not;
and if the gas leakage amount is greater than a preset first leakage amount threshold value, generating corresponding early warning information, and recording the early warning information in the gas database.
3. The gas leakage data monitoring method according to claim 2, wherein the generating corresponding early warning information and recording the early warning information in the gas database further comprises:
acquiring the gas leakage amount of each user in real time;
judging whether the gas leakage amount is larger than a preset second leakage amount threshold value, wherein the second leakage amount threshold value is larger than the first leakage amount threshold value;
if the gas leakage amount is larger than a preset second leakage amount threshold value, generating alarm information, and recording the alarm information in the gas database;
and executing corresponding valve turn-off operation according to the alarm information.
4. The gas leakage data monitoring method according to claim 3, wherein the alarm information includes an alarm time;
after the early warning information is integrated to generate the statistical early warning information of each user, the method further comprises the following steps:
acquiring alarm information of each user within the statistical time period at the alarm time;
calculating the number of the acquired alarm information, and generating the alarm times of each user;
and updating the early warning times of the statistical early warning information of the corresponding users according to the alarm times and a preset conversion coefficient so as to perform clustering.
5. The gas leak data monitoring method of claim 1, further comprising:
acquiring a second statistical request sent by an administrator aiming at a certain user, wherein the second statistical request comprises a plurality of comparison time periods input by the administrator;
acquiring early warning information of the user according to the comparison time period;
calculating the number of early warning information of the early warning time belonging to each comparison time period from a gas database, and generating comparison early warning times, wherein the comparison early warning times correspond to the comparison time periods one by one;
generating average early warning times according to the comparison early warning times and the corresponding duration of the comparison time period;
and generating a historical curve according to the comparison time period and the average early warning times, and feeding back the historical curve to the administrator.
6. The gas leak data monitoring method of claim 1, further comprising:
the screening condition input by the administrator is obtained,
screening the early warning information in a gas database according to the screening conditions to generate a display table;
acquiring an export request sent by an administrator, wherein the export request comprises an export file format;
exporting the presentation locally in the export file format in response to the export request.
7. A gas leakage data monitoring system is characterized by comprising,
the early warning information statistical module (1) is used for acquiring a first statistical request sent by an administrator, wherein the first statistical request comprises a statistical time period input by the administrator; responding to the first statistical request, and acquiring early warning information of each user from a gas database, wherein the early warning information also comprises early warning time; the early warning information describes specific conditions when slight gas leakage occurs to the corresponding users, and each user can correspond to a plurality of pieces of the early warning information and represents that the user has multiple gas leakage within the statistical time period; integrating the early warning information of each user within the statistical time period of the early warning time to generate statistical early warning information of each user, and supplementing the statistical early warning information according to the warning information, wherein the warning information comprises a corresponding gas user number and the warning time; for each user, acquiring alarm information of the alarm time in the statistical time period, and calculating the number of the alarm information; generating the alarm times m of each user in the statistical time period, multiplying the alarm times m by a preset conversion coefficient k, and adding the product result m × k and the statistical early warning times n of the statistical early warning information with the same gas user number to obtain updated statistical early warning times n ', namely n' = n + m × k;
the basic information clustering module (2) is used for randomly generating a pieces of uniformly distributed central point information between the maximum value and the minimum value of all the statistical early warning times n ' and the maximum value and the minimum value of the basic value x, wherein the central point information comprises a central point early warning time n ' ' and a central point basic value x ' '; calculating a distance d between each statistical early warning information and the central point information, wherein a calculation formula of the distance d is as follows:
(ii) a Comparing the distance d with a preset radius r, and adding the statistical early warning information into an early warning list of corresponding central point information when the distance d is smaller than or equal to the radius r; after all the statistical early warning information is judged, calculating and generating an average vector according to the early warning information in the early warning list; moving the central point information according to the corresponding average vector obtained by calculation to finish updating; regenerating an early warning list according to the updated central point information, and generating final central point information and an early warning list after iteration reaches a preset number of times, wherein the central point information comprises corresponding central point early warning times;
the abnormity feedback module (3) is used for sequentially judging whether the early warning times of the central point are greater than a preset early warning time threshold value; and if the central point early warning times are larger than a preset early warning time threshold value, feeding back the central point information and the early warning list corresponding to the central point early warning times to the administrator.
8. An intelligent terminal, comprising a memory and a processor, the memory having stored thereon a computer program that can be loaded by the processor and that executes the method according to any one of claims 1 to 6.
9. A computer-readable storage medium, in which a computer program is stored which can be loaded by a processor and which executes the method of any one of claims 1 to 6.
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