CN105678388A - Baseline-based method for analyzing health state of operation, maintenance and management system - Google Patents
Baseline-based method for analyzing health state of operation, maintenance and management system Download PDFInfo
- Publication number
- CN105678388A CN105678388A CN201610012262.9A CN201610012262A CN105678388A CN 105678388 A CN105678388 A CN 105678388A CN 201610012262 A CN201610012262 A CN 201610012262A CN 105678388 A CN105678388 A CN 105678388A
- Authority
- CN
- China
- Prior art keywords
- management
- data
- baseline
- management object
- analysis method
- 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.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/20—Administration of product repair or maintenance
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Medical Treatment And Welfare Office Work (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
Abstract
The invention discloses a baseline-based method for analyzing health state of operation, maintenance and management system. According to the method, firstly, the real-time condition of a management object index is acquired continuously and periodically based on a preset management rule. Meanwhile, the real-time condition is stored to form historical data. Secondly, the healthy running reference line of the management object index, which varies along with the time, is obtained through the quartile algorithm according to the historical data. Thirdly, with the reference line as a center, a reasonable deviation amplitude range is set according to the percentages of history data points above and below the deviation amplitude thereof. If the data of the management object index fluctuate within the reasonable deviation amplitude range, the management object index is judged to be in the normal state. Otherwise, the management object index is judged to be in the out-of-range state. Fourthly, the health trend of the operation, maintenance and management system can be judged according to the statistics on the out-of-range frequency. Finally, by utilizing the healthy running reference line extracted based on the quartile algorithm, the reference line is closer to the operation normal value of the above index. The deviation amplitude percentage and other parameters are set by users, so that the method is simple and easy to understand. Meanwhile, the judgment standard of the method is more accurate, so that the judgment is more accurate.
Description
Technical field
The present invention relates to operation management technical field, particularly relate to a kind of operation management health analysis method based on baseline.
Background technology
Along with the deep development of informatization, IT system is increasingly becoming the critical infrastructures that core business processes; In order to ensure network, server, database IT resource properly functioning, it is necessary to be maintained; Can producing alarm when system occurs abnormal in time and notify operation maintenance personnel, operation maintenance personnel positions abnormal according to alarm, diagnosis, and completes corresponding attended operation. In the management of O&M, it is different for having a lot of management objects, thus they need the index monitored to be different, and the density of supervision is different, the criterion that whether normal index is is different, it has been found that Analysis of The Disposal, disposal operations after index deviation are also different. But there have a lot of management object to be usually to be identical or approximate, at present, for all management objects, typically by diverse supervision index, monitor that density, criterion, Analysis of The Disposal and disposal operations carry out operation management, thus when encountering identical or approximate, a lot of is exactly repeating operation management so that operation management is complicated.
And in operation management process, how the state for index is analyzed and judges it is a crucial problem, it is related to management quality and the efficiency of management of operation management system, it is therefore desirable to reasonable analysis method improves management quality and the efficiency of management of operation management system.
Summary of the invention
In view of current operation management technical field above shortcomings, the present invention provides a kind of operation management health analysis method based on baseline, health analysis judgement is carried out, it is judged that standard is more accurate, it is judged that more accurate by the datum line of baseline and upper and lower deviation oscillation.
For reaching above-mentioned purpose, embodiments of the invention adopt the following technical scheme that
A kind of operation management health analysis method based on baseline, the described operation management health analysis method based on baseline comprises the following steps:
By the real time status of preset management rule continuously, periodically acquisition management object index, and preserved with history of forming data;
Obtain, by quartile algorithm computing, the data and curves that described management object index temporally changes according to described historical data---healthy operation datum line;
Centered by described datum line, the size of reasonable deviation oscillation is set according to historical record data point percentage ratio in upper and lower deviation oscillation;
If described management object achievement data fluctuates in reasonable deviation oscillation, then it is judged as normal condition, is otherwise out-of-range conditions;
The healthy trend of operation management system is judged by adding up the frequent degree crossed the border.
According to one aspect of the present invention, the described real time status by preset management rule continuously, periodically acquisition management object index, and being preserved with history of forming data concretely: each management object and each monitoring point are carried out data acquisition continuous, substantial amounts of by the management rule preset by monitoring standard module, are preserved the real time status information collected with history of forming data.
According to one aspect of the present invention, described management rule is formulated according to the Monitoring Rules for management object and monitoring point on described monitoring standard module.
According to one aspect of the present invention, described obtain, by quartile algorithm computing, the data and curves that described management object index temporally changes according to described historical data---healthy run in datum line historical data concretely: the historical data gathering within the management object normal operation cycle and preserving.
According to one aspect of the present invention, described historical record data point percentage ratio in upper and lower deviation oscillation is configured by user.
According to one aspect of the present invention, the described operation management health analysis method based on baseline includes: by finding to cross the border real-time calling Intelligent treatment strategy.
According to one aspect of the present invention, described Intelligent treatment strategy is analyzed based on described healthy trend, to decide whether to take measures and take which type of measure.
Advantage of the invention process: the operation management health analysis method based on baseline of the present invention, by the real time status of preset management rule continuously, periodically acquisition management object index, and is preserved with history of forming data; Obtain, by quartile algorithm computing, the data and curves that described management object index temporally changes according to described historical data---healthy operation datum line; Centered by described datum line, the size of reasonable deviation oscillation is set according to historical record data point percentage ratio in upper and lower deviation oscillation; If described management object achievement data fluctuates in reasonable deviation oscillation, then it is judged as normal condition, is otherwise out-of-range conditions; The healthy trend of operation management system is judged by adding up the frequent degree crossed the border; After collection continues for some time, quartile algorithm is used to extract " health standards " the namely healthy operation datum line of each management object that " with period dimension " associates so that datum line is more nearly the normal value that certain index is run; And the parameters such as the percentage ratio of deviation oscillation are by user setup, it is easily understood, it is possible to allow user hold more accurately from macroscopically the Stringency of baseline monitoring being had; Criterion is more accurate, it is judged that more accurate. Constantly collecting each monitoring point service data, compare with these period health standards, draw health status deviation value, when deviation value crosses tolerance band, then triggering processes; System can be obtained and run health degree trend, it has been found that problem sign is pointed out, and prevents trouble before it happens, and improves operation management quality and efficiency.
Accompanying drawing explanation
In order to be illustrated more clearly that the technical scheme in the embodiment of the present invention, the accompanying drawing used required in embodiment will be briefly described below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the premise not paying creative work, it is also possible to obtain other accompanying drawing according to these accompanying drawings.
Fig. 1 is a kind of operation management health analysis method schematic diagram based on baseline of the present invention.
Detailed description of the invention
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is only a part of embodiment of the present invention, rather than whole embodiments. Based on the embodiment in the present invention, the every other embodiment that those of ordinary skill in the art obtain under not making creative work premise, broadly fall into the scope of protection of the invention.
As it is shown in figure 1, a kind of operation management health analysis method based on baseline, the described operation management health analysis method based on baseline comprises the following steps:
Step S1: by the real time status of preset management rule continuously, periodically acquisition management object index, and preserved with history of forming data;
Described step S1 is by the real time status of preset management rule continuously, periodically acquisition management object index, and preserved can be for the detailed description of the invention of history of forming data: each management object and each monitoring point are carried out data acquisition continuous, substantial amounts of by the management rule preset by monitoring standard module. Such as, if the preset management rule of monitoring standard module is " utilization rate gathering CPU ", then by monitoring standard module, the utilization rate of CPU is carried out continuously, the cycle, substantial amounts of collection. The real time status data of the corresponding management object index collected being preserved, form substantial amounts of historical data with the time for axle, this is that future, we carried out systematic analysis " data " basis.
In actual applications, described management rule is formulated according to the Monitoring Rules for management object and monitoring point on described monitoring standard module.
Step S2: obtain, by quartile algorithm computing, the data and curves that described management object index temporally changes according to described historical data---healthy operation datum line;
In actual applications, described step S2 obtains, by quartile algorithm computing, the data and curves that described management object index temporally changes according to described historical data---and the detailed description of the invention of healthy operation datum line can be: based on these historical datas, take the working cycle that system runs well, such as a few days or a few week, the all real time status information collected by monitoring standard module in this time period preserve the historical data formed and extract, mathematically obtain the data and curves that certain management object key index temporally changes after quartile algorithm process---healthy operation datum line. such as, a time dependent data and curves is obtained according to the utilization rate of CPU properly functioning in certain time period. datum line is made to be more nearly the normal value that certain index is run by quartile algorithm.
In actual applications, described datum line can include day baseline and all baselines.
Day baseline: the data selecting nearest a few day properly functioning from the historical record of this index carry out comprehensive descision;
All baselines: the data selecting nearest a few week properly functioning from the historical record of this index carry out comprehensive descision.
In actual applications, the described healthy datum line that runs is a curve, and its abscissa is time shaft, and vertical coordinate refers to target value.
Such as, day baseline type, the scope of the abscissa of datum line was one day, from 0 o'clock to 24 o'clock.
Such as, all baseline types, the scope of the abscissa of datum line is one week, from the 0 of Monday to 24 points on Sunday.
In actual applications, for " the day baseline " of certain station server " CPU usage " index, its forming process can be as follows:
1, the cycle one period properly functioning is taken, as: within 2015, JIUYUE arrives JIUYUE 9 days on 6th, totally four days. Being mapped in a two-dimensional coordinate by the historical record point of these indexs all in this period of cycle, abscissa is the time, and vertical coordinate refers to target historical record value.
2, historical record points all in two coordinates are merged in " one day " and show, such as certain historical record point former (time: JIUYUE referred to target value in 9: 30: 30 on the 7th in 2015: 65%), after merging, the time removes date information, retains Hour Minute Second, forms new two-dimensional coordinate.
3, by certain " interval ", " one day " being divided into N number of point, interval can be 5 minutes, 10 minutes, 1 hour etc., if for 1 hour, then within one day, can be divided into 24 moment. Calculate the meansigma methods of each moment index: by the historical record point in the time range at 1/2 " interval " each before and after each moment, adopt quartile algorithm to calculate the meansigma methods within the scope of this.
4, connecting into straight line according to the value of data point in half interval before and after moment each in above-mentioned steps, this line is exactly the datum line of baseline.
Step S3: centered by described datum line, arranges the size of reasonable deviation oscillation according to historical record data point percentage ratio in upper and lower deviation oscillation;
Described step S3 is centered by described datum line, the size detailed description of the invention arranging reasonable deviation oscillation according to historical record data point percentage ratio in upper and lower deviation oscillation can be: it is considered that at IT ambient stable, business uses under stable premise, following normal business is carried out in process, the fluctuation of the important level of control instantaneous value of certain concrete object should in the rational fluctuation range being around datum line, centered by datum line, up and down reasonably fluctuation range we be called upper and lower deviation oscillation, the setting of reasonable deviation oscillation size is specifically carried out according to historical record data point percentage ratio in upper and lower deviation oscillation.
In actual applications, described historical record data point percentage ratio in upper and lower deviation oscillation is configured by user. And the parameters such as the percentage ratio of deviation oscillation are by user setup, it is easily understood, it is possible to allow user hold more accurately from macroscopically the Stringency of baseline monitoring being had; Criterion is more accurate, it is judged that more accurate.
In actual applications, described upper and lower deviation oscillation is formed after adding datum line and deviates thresholding up and down, and its method to set up can be as follows:
First point three types of deviation thresholding, user can be arbitrarily designated one of which: deviates thresholding, upper deviation thresholding, lower deviation thresholding up and down.
Judge less than certain value if index only requires over baseline, such as " memory usage " index, user is only concerned either with or without exceeding certain threshold value, then this threshold value exactly on deviate thresholding, should first calculate deviation oscillation, upper deviation thresholding=datum line+upper deviation oscillation.
Judge to be not less than certain value if index only requires over baseline, such as " connection number " index, user is only concerned either with or without lower than certain threshold value, then this threshold value deviates thresholding down exactly, should first calculate lower deviation oscillation, lower deviation thresholding=datum line-lower deviation oscillation.
If index and needs judge in certain interval, such as " temperature " index, whether user is concerned about in certain temperature range, so this threshold value is exactly deviate thresholding up and down, should first calculate upper and lower deviation oscillation, upper deviation thresholding=datum line+upper deviation oscillation, lower deviation thresholding=datum line-lower deviation oscillation.
Step S4: if described management object achievement data fluctuates in reasonable deviation oscillation, be then judged as normal condition, is otherwise out-of-range conditions;
If described step S4 described management object achievement data fluctuates in reasonable deviation oscillation, then it is judged as normal condition, otherwise the detailed description of the invention for out-of-range conditions can be: the data fluctuations between deviation oscillation is normal up and down, it is called health, and beyond the fluctuation of deviation oscillation, we are called and cross the border.
Such as, user closes central server " CPU usage " index whether in certain interval, then we need to calculate deviation oscillation and lower deviation oscillation, can carry out as follows:
1, user selects the type of deviation thresholding: deviate thresholding, upper deviation thresholding, lower deviation thresholding up and down.
2, the parameter of user setup deviation thresholding: deviation thresholding is further added by relaxing certain surplus under just ensureing the premise that these indexs cross the border number of times less than the P1% gathering sum, and surplus is the P2% of deviation oscillation.
Wherein user should arrange the value of P1, P2.
3, the system parameter according to user setup, calculate deviation oscillation, lower deviation oscillation, after guaranteeing to use this deviation oscillation, with the data point of historical record relatively after the number of times that crosses the border meet the setting of user, wherein the scope of the data point of historical record is consistent with calculating the scope that datum line selects.
4, datum line, upper deviation thresholding, lower deviation thresholding are it has been determined that the desired value of subsequent acquisition uses upper deviation thresholding or lower deviation thresholding to carry out judgement of crossing the border.
Such as 19: 30: 30 on the 18th November in 2015, the value that server " CPU usage " collects is 80%, when so judging according to " day baseline ", first determine when 19: 30: 30, the upper deviation threshold value that baseline is corresponding, lower deviation threshold value, assume its respectively 23%, 11%, it is clear that 80% in deviation interval, then cognizance index value is crossed the border.
Step S5: judge the healthy trend of operation management system by adding up the frequent degree crossed the border.
Described step S5 judges that by the frequent degree that statistics is crossed the border the detailed description of the invention of the healthy trend of operation management system can be: more boundary treaty is frequent, imply that the hidden danger of service operation is more big, more unhealthy, then the healthy trend of operation management system can be judged by adding up the frequent degree crossed the border.
Advantage of the invention process: the operation management health analysis method based on baseline of the present invention, by the real time status of preset management rule continuously, periodically acquisition management object index, and is preserved with history of forming data; Obtain, by quartile algorithm computing, the data and curves that described management object index temporally changes according to described historical data---healthy operation datum line; Centered by described datum line, the size of reasonable deviation oscillation is set according to historical record data point percentage ratio in upper and lower deviation oscillation; If described management object achievement data fluctuates in reasonable deviation oscillation, then it is judged as normal condition, is otherwise out-of-range conditions; The healthy trend of operation management system is judged by adding up the frequent degree crossed the border; After collection continues for some time, quartile algorithm is used to extract " health standards " the namely healthy operation datum line of each management object that " with period dimension " associates so that datum line is more nearly the normal value that certain index is run; And the parameters such as the percentage ratio of deviation oscillation are by user setup, it is easily understood, it is possible to allow user hold more accurately from macroscopically the Stringency of baseline monitoring being had;Criterion is more accurate, it is judged that more accurate. Constantly collecting each monitoring point service data, compare with these period health standards, draw health status deviation value, when deviation value crosses tolerance band, then triggering processes; System can be obtained and run health degree trend, it has been found that problem sign is pointed out, and prevents trouble before it happens, and improves operation management quality and efficiency.
The above; being only the specific embodiment of the present invention, but protection scope of the present invention is not limited thereto, any those skilled in the art is in technical scope disclosed by the invention; the change that can readily occur in or replacement, all should be encompassed within protection scope of the present invention. Therefore, protection scope of the present invention should be as the criterion with described scope of the claims.
Claims (7)
1. the operation management health analysis method based on baseline, it is characterised in that the described operation management health analysis method based on baseline comprises the following steps:
By the real time status of preset management rule continuously, periodically acquisition management object index, and preserved with history of forming data;
Obtain, by quartile algorithm computing, the data and curves that described management object index temporally changes according to described historical data---healthy operation datum line;
Centered by described datum line, the size of reasonable deviation oscillation is set according to historical record data point percentage ratio in upper and lower deviation oscillation;
If described management object achievement data fluctuates in reasonable deviation oscillation, then it is judged as normal condition, is otherwise out-of-range conditions;
The healthy trend of operation management system is judged by adding up the frequent degree crossed the border.
2. the operation management health analysis method based on baseline according to claim 1, it is characterized in that, the described real time status by preset management rule continuously, periodically acquisition management object index, and being preserved with history of forming data concretely: each management object and each monitoring point are carried out data acquisition continuous, substantial amounts of by the management rule preset by monitoring standard module, are preserved the real time status information collected with history of forming data.
3. the operation management health analysis method based on baseline according to claim 2, it is characterised in that described management rule is formulated according to the Monitoring Rules for management object and monitoring point on described monitoring standard module.
4. the operation management health analysis method based on baseline according to claim 1, it is characterized in that, described obtain, by quartile algorithm computing, the data and curves that described management object index temporally changes according to described historical data---healthy run in datum line historical data concretely: the historical data gathering within the management object normal operation cycle and preserving.
5. according to the operation management health analysis method based on baseline one of Claims 1-4 Suo Shu, it is characterised in that described historical record data point percentage ratio in upper and lower deviation oscillation is configured by user.
6. the operation management health analysis method based on baseline according to claim 5, it is characterised in that the described operation management health analysis method based on baseline includes: by finding to cross the border real-time calling Intelligent treatment strategy.
7. the operation management health analysis method based on baseline according to claim 6, it is characterised in that described Intelligent treatment strategy is analyzed based on described healthy trend, to decide whether to take measures and take which type of measure.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610012262.9A CN105678388A (en) | 2016-01-08 | 2016-01-08 | Baseline-based method for analyzing health state of operation, maintenance and management system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610012262.9A CN105678388A (en) | 2016-01-08 | 2016-01-08 | Baseline-based method for analyzing health state of operation, maintenance and management system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105678388A true CN105678388A (en) | 2016-06-15 |
Family
ID=56299650
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610012262.9A Pending CN105678388A (en) | 2016-01-08 | 2016-01-08 | Baseline-based method for analyzing health state of operation, maintenance and management system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105678388A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106683340A (en) * | 2016-12-15 | 2017-05-17 | 歌尔股份有限公司 | User behavior monitoring method and wearable equipment |
| CN108718303A (en) * | 2018-05-09 | 2018-10-30 | 北京仁和诚信科技有限公司 | Safe operation management method and system |
| CN114064760A (en) * | 2021-11-18 | 2022-02-18 | 广州泰禾大数据服务有限公司 | Multi-dimensional early warning analysis and judgment method for data |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101964997A (en) * | 2009-07-21 | 2011-02-02 | ***通信集团黑龙江有限公司 | Method and device for carrying out early warning on network performance |
| CN102270271A (en) * | 2011-05-03 | 2011-12-07 | 北京中瑞泰科技有限公司 | Equipment failure early warning and optimizing method and system based on similarity curve |
| CN104954154A (en) * | 2014-03-24 | 2015-09-30 | 北京神州泰岳软件股份有限公司 | Method and system for operation and maintenance management platform monitoring and fault maintenance |
-
2016
- 2016-01-08 CN CN201610012262.9A patent/CN105678388A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101964997A (en) * | 2009-07-21 | 2011-02-02 | ***通信集团黑龙江有限公司 | Method and device for carrying out early warning on network performance |
| CN102270271A (en) * | 2011-05-03 | 2011-12-07 | 北京中瑞泰科技有限公司 | Equipment failure early warning and optimizing method and system based on similarity curve |
| CN104954154A (en) * | 2014-03-24 | 2015-09-30 | 北京神州泰岳软件股份有限公司 | Method and system for operation and maintenance management platform monitoring and fault maintenance |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106683340A (en) * | 2016-12-15 | 2017-05-17 | 歌尔股份有限公司 | User behavior monitoring method and wearable equipment |
| CN108718303A (en) * | 2018-05-09 | 2018-10-30 | 北京仁和诚信科技有限公司 | Safe operation management method and system |
| CN108718303B (en) * | 2018-05-09 | 2021-03-23 | 北京仁和诚信科技有限公司 | Safe operation and maintenance management method and system |
| CN114064760A (en) * | 2021-11-18 | 2022-02-18 | 广州泰禾大数据服务有限公司 | Multi-dimensional early warning analysis and judgment method for data |
| CN114064760B (en) * | 2021-11-18 | 2022-12-13 | 广州泰禾大数据服务有限公司 | Multi-dimensional early warning analysis and judgment method for data |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105515820A (en) | Health analysis method for operation and maintenance management | |
| CN105406991A (en) | Method and system for generating service threshold by historical data based on network monitoring indexes | |
| CN105159239B (en) | A kind of SPC strategies automatic update method and SPC Strategy Auto system | |
| CN107086944A (en) | A kind of method for detecting abnormality and device | |
| CN104636450B (en) | A kind of database table space monitoring method | |
| CN111506478A (en) | Method for realizing alarm management control based on artificial intelligence | |
| KR100982034B1 (en) | Monitoring method and system for database performance | |
| CN110912775B (en) | Internet of things enterprise network fault monitoring method and device | |
| CN105678388A (en) | Baseline-based method for analyzing health state of operation, maintenance and management system | |
| CN111324639A (en) | Data monitoring method and device and computer readable storage medium | |
| CN108572905A (en) | A kind of monitoring method and system based on Distributed Calculation | |
| CN110469496B (en) | Intelligent early warning method and system for water pump | |
| CN116389223B (en) | Artificial intelligence visual early warning system and method based on big data | |
| CN109063885A (en) | A kind of substation's exception metric data prediction technique | |
| CN107276808A (en) | A kind of optimization method of Traffic Anomaly monitoring | |
| CN115358155A (en) | Power big data abnormity early warning method, device, equipment and readable storage medium | |
| CN113592314A (en) | Silk making process quality evaluation method based on sigma level | |
| CN104731970B (en) | The quality testing and control method of the multi-source heterogeneous data of highway | |
| EP3906447B1 (en) | Method, system and computer program product for evaluation of energy consumption in industrial environments | |
| CN117560300B (en) | Intelligent internet of things flow prediction and optimization system | |
| CN112131081A (en) | Fault alarm parameter adjusting method and device, electronic equipment and storage medium | |
| CN117422938B (en) | Dam slope concrete structure anomaly analysis method based on three-dimensional analysis platform | |
| CN106709659A (en) | LNG gas station equipment management system | |
| WO2024119919A1 (en) | Power-grid operation state monitoring method and system based on multi-source distribution-network monitoring data | |
| CN117519006A (en) | Production line data processing method, device, computer equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20160615 |