CN105373118A - Intelligent equipment data acquisition method - Google Patents
Intelligent equipment data acquisition method Download PDFInfo
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- CN105373118A CN105373118A CN201510885584.XA CN201510885584A CN105373118A CN 105373118 A CN105373118 A CN 105373118A CN 201510885584 A CN201510885584 A CN 201510885584A CN 105373118 A CN105373118 A CN 105373118A
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- measuring point
- weights
- smart machine
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0221—Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/24—Pc safety
- G05B2219/24215—Scada supervisory control and data acquisition
Abstract
The invention discloses an intelligent equipment data acquisition method. The method comprises the following steps: S1, performing weight configuration on each measuring point needing acquisition according to a user attention degree, and storing weights into a database; S2, setting association rules for the measuring points, and storing the rules in the database; S3, sequencing the weights of the measuring points according to a priority algorithm, and starting acquiring data from an intelligent device according to a measuring point with the maximum weight; and S4, determining whether data acquisition succeeds, in case of success, analyzing returned data, performing matching on the association rules in the database so as to determine whether to dynamically change the weights of the corresponding measuring points, and in case of failure, continuously acquiring the data from the intelligent device according to a measuring point with a next larger weight. According to the invention, the acquisition speed and the efficiency of user attention measuring points are guaranteed, at the same time, the weights of the measuring points are dynamically changed in a data acquisition process according to the association rules, the data is acquired according to different states, and the acquisition frequency of the measuring points can change in real time.
Description
Technical field
The invention belongs to power & environment supervision data collecting field, particularly relate to a kind of smart machine collecting method.
Background technology
Dynamic environment monitoring (abbreviation power & environment supervision) refers to be concentrated for the power-equipment in all kinds of machine room and environmental variance
monitoring.Power & environment supervision system needs to each of distribution that independently power-equipment and building environment, machine room safety and protection monitoring object take remote measurement, the data (hereinafter referred to as measuring point) such as remote signalling gather, the running status of real-time detection smart machine, record and process related data, timely detecting fault, and do necessary remote control, remote regulating operation, in good time notice reporting process.
Power & environment supervision system storage also presents each appliance services object at platform interface, the smart machine of the corresponding actual access monitoring of each appliance services object, simultaneously each appliance services object has respective measuring point list, and each measuring point has oneself the attribute such as current collection value, acquisition time.When user clicks a certain platform device business object of access, supervisory system will export the information such as collection value, acquisition time of all measuring points of this appliance services object; When user checks the some concrete measuring point of this object, the measuring point numerical value exported may not be the actual current up-to-date numerical value of smart machine, and the acquisition time that measuring point is corresponding simultaneously likely exists delayed situation.Trace it to its cause, be because existing acquisition method be according to measuring point tab sequential regardless of emphasis one by one whereabouts smart machine read, only have and after waiting for previous measuring point collection success, could send out measuring point collection next.Along with the measuring point data of smart machine increases, and the acquisition time that each measuring point distributes is the same, the then overall measuring point image data cycle can be elongated, the measuring point data feedback that user pays close attention to also just becomes slower, therefore for the communication acquisition method of this kind with smart machine, need develop and optimize.
As shown in Figure 1, the process flow diagram of existing power & environment supervision gatherer process is described in figure, in figure, acquisition module order is concentrated from measuring point data and is obtained certain data, sends to smart machine, concentrates the next data of acquisition when data return Shi Zezai from measuring point data, if smart machine does not have feedback result, then need continuous wait, until exceed the time of setting, just obtain next data, each measuring point data does not distinguish emphasis, obtains in order at random.The significance level paid close attention to the measuring point of smart machine due to user is different, existing acquisition method is the method according to the impartial acquisition order of each measuring point acquisition time, along with the measuring point data of smart machine is more, and each measuring point average mark cuts acquisition time, the measuring point causing user to pay close attention to needs just to collect through the longer time, if in transmitting procedure, measuring point is lost simultaneously, also needing to increase one-period just can collect, can there is feedback situation not in time in the measuring point that user pays close attention to.
Summary of the invention
In order to solve prior art Problems existing, the invention provides a kind of smart machine collecting method, which ensure picking rate and efficiency that user pays close attention to measuring point, in data acquisition, dynamically change measuring point weights according to correlation rule simultaneously, achieve data acquisition according to different conditions, measuring point gathers frequency can real-time change.
The technical solution used in the present invention is as follows:
A kind of smart machine collecting method, comprises step as follows:
S1. according to user's degree of concern, weights configuration is carried out to each measuring point that need gather, and be stored in database;
S2. to measuring point setting correlation rule, and be stored in database;
S3. the weights of measuring point are according to the sequence of priority level algorithm, start to smart machine image data according to the measuring point of maximum weight;
S4. judge that whether data acquisition is successful, if success, analyze the data returned, the correlation rule in matching database, thus judge whether the weights dynamically changing corresponding measuring point; If failure, continue according to the measuring point of next larger weights to smart machine image data.
The present invention is applied in power & environment supervision collection field, acquisition module is provided with in power & environment supervision system, acquisition module meeting accessing database, the measuring point correlation rule of measuring point weights that user preset puts and customization is preserved in database, give weights size according to the height of significance level to these measuring point datas, the measuring point large according to weights preferentially obtains to smart machine.And the collection acquisition of smart machine data is gathered by the acquisition module in power & environment supervision system.When acquisition module starts, accessing database, reads measuring point weights configuration information, generates measuring point weights object; Load the weights management object of measuring point; From database, read all devices information, generate device object list, and by device object and measuring point weights object association.
The present invention is set with correlation rule from different the present invention of being of prior art, when receiving smart machine return data, analyzes this data content, reads the value information of measuring point arrangement, is confirmed whether to mate correlation rule.
Further, described correlation rule includes and judges whether data acquisition set value corresponding to measuring point is in the condition of abnormality, and this measuring point and other which measuring point arrangement incidence relation.
When the data acquisition set value that measuring point is corresponding occurs abnormal, then dynamically change the weights of this measuring point, dynamically change the weights of the measuring point relevant with it simultaneously, make relevant measuring point also have the priority level paid close attention to; Not there is exception in the data acquisition set value corresponding when measuring point, then continues according to the measuring point of next larger weights to smart machine image data.
Timing inquiry weights repository in operational process, when changing appears in weights, corresponding measuring point gathers priority orders and changes, and uses the rearrangement of priority level algorithm, automatically according to priority gathers the data of smart machine.
Further, what described priority level algorithm sequence adopted is Of Bubble Sort Algorithm.
Further, divide high, medium and low interval to the weights of measuring point, by the interval frequency increasing it and gather, be in the interval times of collection of different weights different.
Compared with prior art, the beneficial effect that the present invention has is:
1., according to measuring point importance, the weights of configuration measuring point, data acquisition carries out the collection of different frequency according to the weights of measuring point, ensures picking rate and the efficiency of important measuring point.
2. configuration association rule, according to correlation rule dynamic conditioning measuring point weights in gatherer process, data acquisition is according to different conditions, and measuring point gathers frequency real-time change.
Accompanying drawing explanation
Fig. 1: the process flow diagram of existing power & environment supervision gatherer process;
Fig. 2: the process flow diagram of smart machine gatherer process of the present invention;
Fig. 3: acquisition module of the present invention starts workflow diagram.
Embodiment
Below in conjunction with drawings and Examples, the present invention is described in further detail.
Embodiment:
As shown in Figure 2, a kind of smart machine collecting method, comprises step as follows:
S1. according to user's degree of concern, weights configuration is carried out to each measuring point that need gather, and be stored in database;
S2. to measuring point setting correlation rule, and be stored in database;
S3. the weights of measuring point are according to the sequence of priority level algorithm, start to smart machine image data according to the measuring point of maximum weight;
S4. judge that whether data acquisition is successful, if success, analyze the data returned, the correlation rule in matching database, thus judge whether the weights dynamically changing corresponding measuring point; If failure, continue according to the measuring point of next larger weights to smart machine image data.
It is gathered by the acquisition module in power & environment supervision system that the collection of smart machine data obtains.As shown in Figure 3, when acquisition module starts, accessing database, reads measuring point weights configuration information, generates measuring point weights object; Load the weights management object of measuring point; From database, read all devices information, generate device object list, and by device object and measuring point weights object association.
Described correlation rule includes and judges whether data acquisition set value corresponding to measuring point is in the condition of abnormality, and this measuring point and other which measuring point arrangement incidence relation.When the data acquisition set value that measuring point is corresponding occurs abnormal, then dynamically change the weights of this measuring point, dynamically change the weights of the measuring point relevant with it simultaneously, make relevant measuring point also have the priority level paid close attention to; Not there is exception in the data acquisition set value corresponding when measuring point, then continues according to the measuring point of next larger weights to smart machine image data.
Timing inquiry weights repository in operational process, when changing appears in weights, corresponding measuring point gathers priority orders and changes, and uses the rearrangement of priority level algorithm, automatically according to priority gathers the data of smart machine.
What described priority level algorithm sequence adopted is Of Bubble Sort Algorithm.
Divide high, medium and low interval to the weights of measuring point, by the interval frequency increasing it and gather, be in the interval times of collection of different weights different.
In the present embodiment, with the three-phase voltage of collecting device for measuring point object, voltage does not change substantially under normal operation, and its attention rate is not high, but when voltage occurs too high or too low, its importance will improve, and gathering frequency just needs change.The present embodiment also with power failure alarm and alternating voltage for measuring point object, with in routine use, the power failure alarm measuring point that user need pay close attention to power supply, with the non-alternating voltage measuring point paid close attention to, when power failure alarm produces, ac voltage will become important, there is service logic relation in power failure alarm and alternating voltage, therefore need both configuration association rules, when power failure alarm really produces, correlation rule comes into force, and alternating voltage measuring point weights become large, changed by weights, quick obtaining is to corresponding alternating voltage numerical value.
Claims (8)
1. a smart machine collecting method, is characterized in that, comprises step as follows:
S1. according to user's degree of concern, weights configuration is carried out to each measuring point that need gather, and be stored in database;
S2. to measuring point setting correlation rule, and be stored in database;
S3. the weights of measuring point are according to the sequence of priority level algorithm, start to smart machine image data according to the measuring point of maximum weight;
S4. judge that whether data acquisition is successful, if success, analyze the data returned, the correlation rule in matching database, thus judge whether the weights dynamically changing corresponding measuring point; If failure, continue according to the measuring point of next larger weights to smart machine image data.
2. smart machine collecting method according to claim 1, is characterized in that, described correlation rule includes and judges whether data acquisition set value corresponding to measuring point is in the condition of abnormality, and this measuring point and other which measuring point arrangement incidence relation.
3. smart machine collecting method according to claim 2, it is characterized in that, when the data acquisition set value that measuring point is corresponding occurs abnormal, then dynamically change the weights of this measuring point, dynamically change the weights of the measuring point relevant with it simultaneously, make relevant measuring point also have the priority level paid close attention to; Not there is exception in the data acquisition set value corresponding when measuring point, then continues according to the measuring point of next larger weights to smart machine image data.
4. the smart machine collecting method according to claims 1 to 3 any one, it is characterized in that, timing inquiry weights repository in operational process, when changing appears in weights, corresponding measuring point gathers priority orders and changes, use the rearrangement of priority level algorithm, automatically according to priority gather the data of smart machine.
5. smart machine collecting method according to claim 4, is characterized in that, what described priority level algorithm sequence adopted is Of Bubble Sort Algorithm.
6. smart machine collecting method according to claim 1, is characterized in that, is undertaken by the acquisition module of power & environment supervision system to smart machine image data in step S3.
7. smart machine collecting method according to claim 6, is characterized in that, described acquisition module is provided with startup work before beginning data acquisition, and it is as follows that described startup work comprises step:
S71. accessing database, reads measuring point weights configuration information, generates measuring point weights object;
S72. the weights management object of measuring point is loaded;
S73. from database, read all devices information, generate device object list, and by device object and measuring point weights object association.
8. smart machine collecting method according to claim 1, is characterized in that, divides high, medium and low interval to the weights of measuring point, by the interval frequency increasing it and gather, is in the interval times of collection of different weights different.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107704371A (en) * | 2017-09-29 | 2018-02-16 | 郑州云海信息技术有限公司 | A kind of management method, device and the equipment of storage medium and storage system |
| CN108924933A (en) * | 2018-06-12 | 2018-11-30 | 浙江大华技术股份有限公司 | A kind of wireless data acquisition method and equipment |
| CN112140108A (en) * | 2020-09-07 | 2020-12-29 | 珠海格力电器股份有限公司 | Method, device and equipment for quickly responding to abnormal state and computer readable medium |
| CN113780755A (en) * | 2021-08-20 | 2021-12-10 | 阳光电源股份有限公司 | Measuring point scheduling method and device and power management system |
| WO2022016389A1 (en) * | 2020-07-21 | 2022-01-27 | Siemens Aktiengesellschaft | Multi-parameter dynamic sampling method and multi-parameter dynamic sampling device |
| CN114785705A (en) * | 2022-05-24 | 2022-07-22 | 蚂蚁区块链科技(上海)有限公司 | Equipment management method, device and system |
| CN115543729A (en) * | 2022-09-08 | 2022-12-30 | 华能信息技术有限公司 | Data acquisition method and system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107704371A (en) * | 2017-09-29 | 2018-02-16 | 郑州云海信息技术有限公司 | A kind of management method, device and the equipment of storage medium and storage system |
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| CN114785705A (en) * | 2022-05-24 | 2022-07-22 | 蚂蚁区块链科技(上海)有限公司 | Equipment management method, device and system |
| CN115543729A (en) * | 2022-09-08 | 2022-12-30 | 华能信息技术有限公司 | Data acquisition method and system |
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| CN105373118B (en) | 2018-11-16 |
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