CN105116301A - Data auxiliary determining method based on dynamic statistics - Google Patents
Data auxiliary determining method based on dynamic statistics Download PDFInfo
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- CN105116301A CN105116301A CN201510507811.5A CN201510507811A CN105116301A CN 105116301 A CN105116301 A CN 105116301A CN 201510507811 A CN201510507811 A CN 201510507811A CN 105116301 A CN105116301 A CN 105116301A
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Abstract
The invention relates to a data auxiliary determining method based on dynamic statistics. The method sets an attention threshold section for acquired living-work detection data on the basis of a standard criterion, and specifically comprises a first determining step of performing preliminary decision according to the standard criterion; a statistic step of performing data statistics on the living-work detection data and setting the attention threshold section according to a statistical result; and a second determining step of performing auxiliary decision according to the living-work detection data of a tested device and the set attention threshold section. Compared with a method in the prior art, the method has advantages of high result precision and high auxiliary determining dependability.
Description
Technical field
The present invention relates to a kind of data processing method of live detection technical field, especially relate to a kind of data auxiliary judgment method based on dynamic statistics.
Background technology
In recent years, along with grid equipment maintenance is by the transformation of prophylactic repair to repair based on condition of component, state-detection obtains applying more and more widely.Live detection, as the important branch of state-detection, usually adopts portable instrumentation to carry out Site Detection to grid equipment under operation, has the features such as flexible, accurate, timely.Live detection test figure characterizes parameter as important equipment state, is one of Data Source carrying out grid equipment state evaluation.
At present, live detection business also exists some problem to be needed to solve: first, live detection data mainly rely on professional's hand-kept of site test, and this original mode exists that data standard is poor, measurement cannot carry out the defects such as filing statistical study easily.The second, the data class that live detection work on the spot is collected is many, quantity large, needs through very loaded down with trivial details tidal data recovering, arrangement and editing, not only inefficiency when writing analysis report, and the accuracy of data and integrality are also difficult to ensure.3rd, the development of live detection business is rapid, and the work efficiency of single team is far not by far up to the mark, and many team collaborations are imperative.But the participation of many team also brings the very different of course of work standardization and work product quality, and the management expectancy of standardized work is also urgent all the more.4th, although PMS system have accumulated a large amount of valuable data, because the reasons such as place, equipment, network cannot effectively utilize in the work on the spot of live detection.
The many establishing criterias of judgement of existing live detection data carry out, but there is certain defect in practice, as in infrared measurement of temperature about the judgement of exception being: 1, absolute temperature does not exceed standard; 2, the relative temperature rise of ABC three-phase does not exceed standard.As criterion, if certain equipment three-phase temperature is all higher, but relative temperature difference is little, and absolute temperature does not exceed standard, then this equipment is not judged to be exception.Trace it to its cause, existing criterion mainly for individual equipment, by ensure run in do not occur for the purpose of emergency.At present, live detection work develops to lean, from " ensureing emergency not to occur ", to " lean grasp equipment state " development (such as " outpatient service, emergency treatment " is to " health check-up "), original technical standard is incompatible with it, needs to further develop for target.
Summary of the invention
Object of the present invention is exactly provide that a kind of judged result precision is high, the credible high data auxiliary judgment method based on dynamic statistics of auxiliary judgment to overcome defect that above-mentioned prior art exists.
Object of the present invention can be achieved through the following technical solutions:
Based on a data auxiliary judgment method for dynamic statistics, the method sets on the basis of standard basis for estimation the live detection data gathered notes threshold interval, specifically comprises:
Preliminary the first determining step judged is carried out according to standard basis for estimation;
Data statistics is carried out to live detection data and sets the statistic procedure noting threshold interval according to statistics;
The second determining step of auxiliary judgment is carried out according to the live detection data of each equipment under test and set attention threshold interval.
Before carrying out described first determining step, equipment under test is divided into groups.
In described statistic procedure, the result of data statistics comprises maximal value, minimum value, mean value and mean square deviation.
Described attention threshold interval is (T
1, T
2), wherein, T
1=M-nS, T
2=M+nS, M are mean value, and S is mean square deviation, and n is constant, and n value is 1.6 ~ 1.7.
In described second determining step, the live detection data of each equipment under test and attention threshold interval are compared, the equipment under test corresponding to the live detection data do not belonged in attention threshold interval is marked.
When each equipment under test carries out live detection data acquisition, environmental factor is consistent with testing tool.
This data auxiliary judgment method is applied to infrared measurement of temperature, type local-discharge ultrasonic detects, office puts in chromatogram detection in ultra-high-frequency detection, oil, SF6 water content detection and leakage current of an arrester detection.
Compared with prior art, the present invention has the following advantages:
1) the present invention adds up detection data on the basis of standard basis for estimation, single devices state is combined with integral device state, improves the precision of judged result;
2) the present invention can evade the impact of each extraneous factor to greatest extent, improves the credibility of auxiliary judgment;
3) the present invention is applicable to the live detection method that all testing results represent with numeric form, applied widely.
Embodiment
Below in conjunction with specific embodiment, the present invention is described in detail.The present embodiment is implemented premised on technical solution of the present invention, give detailed embodiment and concrete operating process, but protection scope of the present invention is not limited to following embodiment.
The present embodiment provides a kind of data auxiliary judgment method based on dynamic statistics, and the method sets on the basis of standard basis for estimation the live detection data gathered notes threshold interval, specifically comprises:
First determining step, tentatively judges according to standard basis for estimation, before carrying out described first determining step, divides into groups to equipment under test.
Statistic procedure, carries out data statistics to live detection data, and notes threshold interval according to statistics setting.The result of data statistics comprises maximal value, minimum value, mean value and mean square deviation.Attention threshold interval is (T
1, T
2), wherein, T
1=M-nS, T
2=M+nS, M are mean value, and S is mean square deviation, and n is constant, and n value is 1.6 ~ 1.7.The present embodiment, n is taken as 1.65.
Second determining step, auxiliary judgment is carried out according to the live detection data of each equipment under test and set attention threshold interval, the live detection data of each equipment under test and attention threshold interval are compared, the equipment under test corresponding to the live detection data do not belonged in attention threshold interval is marked.
When each equipment under test carries out live detection data acquisition, environmental factor, testing tool are consistent with tester or close consistent, evade the impact of extraneous factor to greatest extent, improve the credibility of auxiliary judgment.
Above-mentioned data auxiliary judgment method can be applicable to infrared measurement of temperature, type local-discharge ultrasonic detects, office puts in chromatogram detection in ultra-high-frequency detection, oil, SF6 water content detection and leakage current of an arrester detection.
For infrared detection, above-mentioned data auxiliary judgment method can be described as:
1) in full station is detected, equipment is divided into groups by kind, voltage, as 500kV lightning arrester, 220kV lightning arrester etc.;
2) by live detection data according to standard basis for estimation " 1, absolute temperature do not exceed standard; 2, the relative temperature rise of ABC three-phase does not exceed standard " carry out just sentencing;
3) all for our station data are carried out real-time dynamic statistics analysis, obtain maximal value, minimum value, mean value and mean square deviation, and attention threshold interval is set;
4) by all detection data compared with attention threshold value, to not noticing that the data in threshold interval mark, and remind test group.
The testing results such as above-mentioned data auxiliary judgment method can be applicable to infrared measurement of temperature, type local-discharge ultrasonic detects, office puts that chromatogram in ultra-high-frequency detection, oil detects, SF6 water content detection and leakage current of an arrester detection can in the live detection method that represents of numeric form.
Concrete data explanation is carried out for infrared measurement of temperature.500kVMOA (lightning arrester) temperature measurement data is as shown in table 1.
Table 1500kVMOA temperature measurement data is analyzed
Judged result is as follows:
1) tentatively judge, detect data normal;
2) carry out data statistics, obtain statistics, as shown in table 2, calculate according to statistics and note threshold interval (12.28,15.27);
Table 2
| N | Minimum | Maximum | Mean | Std.Deviation |
| 30 | 12.70 | 16.40 | 13.7833 | .90557 |
3) by detection data with notice that threshold interval compares, to detect data be less than 12.28 or equipment more than 15.27 mark, remind tester, as in table 1 No. 4 main transformer 500kV lightning arrester A phase and No. 4 main transformer 500kV lightning arrester B phases.
Claims (7)
1. based on a data auxiliary judgment method for dynamic statistics, it is characterized in that, the method sets on the basis of standard basis for estimation the live detection data gathered notes threshold interval, specifically comprises:
Preliminary the first determining step judged is carried out according to standard basis for estimation;
Data statistics is carried out to live detection data and sets the statistic procedure noting threshold interval according to statistics;
The second determining step of auxiliary judgment is carried out according to the live detection data of each equipment under test and set attention threshold interval.
2. the data auxiliary judgment method based on dynamic statistics according to claim 1, is characterized in that, before carrying out described first determining step, divide into groups to equipment under test.
3. the data auxiliary judgment method based on dynamic statistics according to claim 1, is characterized in that, in described statistic procedure, the result of data statistics comprises maximal value, minimum value, mean value and mean square deviation.
4. the data auxiliary judgment method based on dynamic statistics according to claim 3, it is characterized in that, described attention threshold interval is (T
1, T
2), wherein, T
1=M-nS, T
2=M+nS, M are mean value, and S is mean square deviation, and n is constant, and n value is 1.6 ~ 1.7.
5. the data auxiliary judgment method based on dynamic statistics according to claim 1, it is characterized in that, in described second determining step, the live detection data of each equipment under test and attention threshold interval are compared, the equipment under test corresponding to the live detection data do not belonged in attention threshold interval is marked.
6. the data auxiliary judgment method based on dynamic statistics according to claim 1, it is characterized in that, when each equipment under test carries out live detection data acquisition, environmental factor is consistent with testing tool.
7. the data auxiliary judgment method based on dynamic statistics according to claim 1, it is characterized in that, this data auxiliary judgment method is applied to infrared measurement of temperature, type local-discharge ultrasonic detects, office to put in ultra-high-frequency detection, oil that chromatogram detects, during SF6 water content detection and leakage current of an arrester detect.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108593006A (en) * | 2018-06-04 | 2018-09-28 | 广东新康博思信息技术有限公司 | It is a kind of based on the pollution source management system acquired in real time |
| CN108956869A (en) * | 2018-06-04 | 2018-12-07 | 广东新康博思信息技术有限公司 | It is a kind of based on the environmental quality management system acquired in real time |
| CN109000714A (en) * | 2018-05-31 | 2018-12-14 | 广东新康博思信息技术有限公司 | It is a kind of based on the pollution source monitoring system acquired in real time |
| CN109462112A (en) * | 2018-09-27 | 2019-03-12 | 珠海格力电器股份有限公司 | Connecting terminal processing method, processing unit and switching device |
| CN113704186A (en) * | 2021-11-01 | 2021-11-26 | 云账户技术(天津)有限公司 | Alarm event generation method and device, electronic equipment and readable storage medium |
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109000714A (en) * | 2018-05-31 | 2018-12-14 | 广东新康博思信息技术有限公司 | It is a kind of based on the pollution source monitoring system acquired in real time |
| CN108593006A (en) * | 2018-06-04 | 2018-09-28 | 广东新康博思信息技术有限公司 | It is a kind of based on the pollution source management system acquired in real time |
| CN108956869A (en) * | 2018-06-04 | 2018-12-07 | 广东新康博思信息技术有限公司 | It is a kind of based on the environmental quality management system acquired in real time |
| CN109462112A (en) * | 2018-09-27 | 2019-03-12 | 珠海格力电器股份有限公司 | Connecting terminal processing method, processing unit and switching device |
| CN109462112B (en) * | 2018-09-27 | 2020-11-13 | 珠海格力电器股份有限公司 | Terminal processing method, processing device and switching device |
| CN113704186A (en) * | 2021-11-01 | 2021-11-26 | 云账户技术(天津)有限公司 | Alarm event generation method and device, electronic equipment and readable storage medium |
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|---|---|
| CN105116301B (en) | 2017-09-29 |
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