CN107563620A - A kind of integrated evaluating method based on equipment life-cycle information - Google Patents
A kind of integrated evaluating method based on equipment life-cycle information Download PDFInfo
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Abstract
A kind of integrated evaluating method based on equipment life-cycle information, by classifying to equipment on-line monitoring data, test report, cost；Calculated using threshold values and trend model and obtain on-line monitoring conclusion, on-line monitoring conclusion value is obtained by standardizing assignment；Data item combination threshold values model is mapped by test report and calculates acquisition conclusion (of pressure testing), conclusion (of pressure testing) value is obtained by standardizing assignment；The optimal replacing of acquisition and the retired point of equipment theory are calculated by drawing theoretical life-span trend curve and actual cost trend curve, contrast judgement acquisition cost conclusion, cost conclusion value is obtained by standardizing assignment；Deduction of points method is weighted by variable weight based on on-line monitoring conclusion value, conclusion (of pressure testing) value and cost conclusion value and calculates acquisition equipment end-state, so as to realize the overall merit to the equipment life-cycle.
Description
Technical Field
The invention relates to the technical field of equipment full-life management, in particular to a comprehensive evaluation method which combines equipment on-line monitoring, testing and cost by utilizing an equipment full-life management technology.
Background
In the modern society of high-speed development of national economy and high dependence on electric power of people's life, electric power is the basis of modern urban groups and the economic operation of the whole society. With the construction and development of ultra-high and extra-high voltage transmission projects, the coverage area of the interconnected power grid is gradually enlarged, and the influence of the operation safety of power transmission and transformation equipment on the safe and reliable operation of the power grid is more prominent. According to the grid accident statistical data of nearly 10 years, the proportion of the grid accidents caused by the faults of the power transmission and transformation equipment and natural disasters to the grid accidents exceeds 50%, and the method brings great influence on safe and reliable operation of the grid. The method has the advantages of monitoring the running state of the power transmission and transformation equipment, diagnosing faults, evaluating states and managing the whole life cycle, and has important scientific significance and application value for improving the running reliability and the utilization rate of the power transmission and transformation equipment and realizing the optimized management of the equipment.
Disclosure of Invention
The invention aims to cover the panoramic information comprehensive evaluation of the basic asset information, the state information and the cost information of the power transmission and transformation equipment by utilizing the equipment full-life management technology, combining the equipment on-line monitoring, the test and the comprehensive evaluation of the cost and combining the current power production situation, realize the equipment full-life cycle analysis based on the panoramic information, improve the maintenance level and the management level of the power transmission and transformation equipment and play an important role in promoting the development of the intelligent power grid.
The purpose of the invention is realized by the following technical scheme:
1. a comprehensive evaluation method based on equipment life cycle information comprises the following steps:
step 1: forming a data base for evaluation and analysis by classifying the equipment online monitoring data, the test report and the cost;
step 2: forming an online monitoring diagnosis conclusion, carrying out threshold crossing judgment on online monitoring data and a threshold value, carrying out diagnosis on a change rate by combining trends to obtain an online monitoring diagnosis conclusion A, and carrying out standardized assignment on the conclusion:
1) And (4) normal: 0;
2) Threshold/trend warning: 1;
3) Threshold and trend early warning: 2;
the formula of the trend warning is as follows:
in the formula, is y 1 ，y 2 ，…，y t In order to monitor the sequence, it is proposed,and n is the moving average value at the moment of t +1 and is called the moving time interval. If the predicted value of the monitoring data rising gradient continuously exceeds the set threshold value, the equipment is in a fault precursor period, and an alarm is given in time, so that the fault spreading is effectively controlled, and the accident is avoided.
And 3, step 3: forming a diagnosis conclusion of a test report, extracting a test value according to the test report, mapping the associated threshold value of the test value, early warning the threshold value to obtain a test conclusion B, wherein the test conclusion B is normal if all test items are normal, the test conclusion B with abnormal test items is abnormal, and carrying out standardized assignment on the result:
1) And (3) normal: 0
2) Abnormality: 1;
and 4, step 4: forming a cost conclusion based on the equipment life cycle event, and according to the theoretical operation years of various types of equipment, taking the initial cost of the purchase cost as a descending theoretical life trend curve C, curve C: y = aX + b, where b is the equipment procurement cost, a = equipment procurement cost/equipment theoretical operating life; taking the later cost caused by equipment accidents, faults and overhaul events after operation and maintenance as an increasing actual cost trend curve D, wherein the trend curve D = the equipment purchase cost + the equipment implementation cost + the equipment operation and maintenance cost step curve, when the curves C and D are intersected, the corresponding time coordinate of an intersection point E is the optimal replacement time of the equipment, and the corresponding cost is the residual value of the equipment; the corresponding time coordinate of the curve C and the intersection point G of the X axis is the theoretical decommissioning time of the equipment, the current cost state of the equipment is judged according to the time of the intersection point E, if the time of the intersection point E is not more than E, the equipment does not need to be replaced in normal operation, if the time of the intersection point E is more than E and less than G, the equipment is recommended to be replaced, and if the time of the intersection point E is more than G, the equipment is recommended to be decommissioned; and obtaining a cost conclusion F, and carrying out standardized assignment on the conclusion:
1) The normal operation does not need to be replaced: 0
2) And (4) replacement is recommended: 1
3) Proposed decommissioning of beyond-theoretical operating events: 2;
and 5: according to the standardized online monitoring diagnosis conclusion A, the test conclusion B and the cost conclusion F obtained in the steps, the comprehensive evaluation of the equipment is carried out through a variable weight weighting deduction method
The calculation rule of the weighted model deduction value is as follows:
(1) the data reliability is sorted into test, online monitoring and cost, and the sorting rule is from high to low;
(2) dynamically increasing the weight corresponding to the acquisition mode with higher deduction value;
reliability coefficients of different evaluation models: test 1.0, on-line monitoring 0.8 and cost 0.6.
The corresponding deduction value of the state quantity data acquired by different evaluation models is 0, and the weighted deduction value is 0; otherwise, the weighted score value is calculated as:
in the formula: n is a state quantity evaluation model; bi is a deduction value corresponding to the evaluation model in the ith; ai is a reliability coefficient of the ith evaluation model; a' i is a corrected reliability coefficient of the ith evaluation model;
in order to avoid that the accumulated deduction of a certain deduction element is too high to cause too low equipment evaluation score and too serious equipment state evaluation, a deduction upper limit is set for each deduction element, and the final grading result is presented in percentage.
The invention has the beneficial effects that: by the comprehensive evaluation method based on the equipment full-life information, various data such as environment information, operation information and online monitoring are combined, a series of equipment operation maintenance strategies according to the equipment health condition are formulated for equipment according to different equipment state evaluation results, support is provided, a more comprehensive and reasonable operation maintenance strategy is formulated, the equipment diagnosis level is improved, and the aims of reducing the potential safety hazard of power grid equipment and reducing the economic expenditure are fulfilled.
Drawings
FIG. 1 is a general flow diagram of the process of the present invention;
FIG. 2 is a flow chart of an online monitoring analysis.
Detailed Description
The invention relates to a comprehensive evaluation method based on equipment full-life information, which classifies equipment online monitoring data, test reports and cost; calculating by using a threshold value and a trend model to obtain an online monitoring conclusion, and obtaining an online monitoring conclusion value through standardized assignment; calculating by combining the test report mapping data item with a threshold value model to obtain a test conclusion, and obtaining a test conclusion value by standardized assignment; calculating to obtain an optimal replacement point and an equipment theoretical retirement point by drawing a theoretical life trend curve and an actual cost trend curve, comparing and judging to obtain a cost conclusion, and obtaining a cost conclusion value by standardized assignment; and calculating to obtain the final state of the equipment by a variable weight weighting deduction method based on the online monitoring conclusion value, the test conclusion value and the cost conclusion value, thereby realizing the comprehensive evaluation of the whole service life of the equipment. The flow chart is shown in fig. 1.
1) Firstly, collecting equipment on-line monitoring data, test reports and cost data, and classifying according to equipment themes to form a data base for evaluation and analysis;
2) Carrying out threshold value early warning on the online monitoring data corresponding to a threshold value table, wherein the threshold values are shown as follows;
monitoring a bus PT: voltage (-5%)
Capacitive devices (including cannula, CT, CVT, OY): capacitance (-5% to 5%), dielectric loss (< 1% (2%))
A lightning arrester: resistance-capacitance ratio (< 30%), resistive current (-120%), full current (-10%)
A main transformer: iron core current (< 0.5A), oil temperature (< 90 ℃), oil level (10%), H2 (150 ul/l), total hydrocarbons (150 ul/l), C2H2 (5 ul/l (110-220 kV), 1ul/l (500 kV))
A circuit breaker: cumulative on-off current (< 1000 kA), on-off stroke (200-210 mm), on-off speed (5-5.2 m/s)
Partial discharge: discharge intensity (< 65 dBm), discharge frequency (< 50%)
Secondly, performing trend analysis on the selected period of time to obtain a trend analysis conclusion, wherein a trend analysis formula is as follows:
in the formula, is y 1 ，y 2 ，…，y t In order to monitor the sequence, it is proposed,the moving average at time t +1 is denoted as the moving time interval.
If the predicted value of the ascending gradient of the monitoring data continuously exceeds the set threshold value, the equipment can be considered to be in the state before the fault
And in a megaperiod, timely alarming is carried out, so that the fault spreading can be effectively controlled, and the accident can be avoided.
3) Extracting the test items in the test report, and performing threshold analysis corresponding to test thresholds, wherein the thresholds are as follows: acquisition trial
And (6) checking a conclusion value.
Insulation test:
(1) Insulation resistance:
r15 (> 200M, <30% aspect ratio), R60 (> 200M, <30% aspect ratio), R10 (> 200M, <30% aspect ratio), absorptance (> 1.3), polarization index (> 1.5)
(2) Tg δ% of winding
tgδ％(<.6％(500kV),<0.8％(<220kV))
Capacitance (aspect ratio < 10%)
(3) Iron core grounding current
Iron core to ground (G omega) (> 0.5, vertical ratio < 30%)
Clamp to ground (G omega) (> 0.5, vertical ratio < 30%)
4) Forming a cost conclusion based on the equipment life cycle event, and according to the theoretical operation years of various types of equipment, taking the initial cost of the purchase cost as a descending trend curve C: y = aX + b, where b is the equipment procurement cost, a = - (equipment procurement cost/equipment theoretical operating life). Taking the later cost caused by equipment accidents, faults and maintenance events after operation and maintenance as an increasing trend curve D, wherein the trend curve D = the step curve of equipment purchase cost + equipment implementation cost + equipment operation and maintenance cost, and when the curves C and D are intersected, the corresponding time coordinate of the intersection point E is the optimal replacement time of the equipment, and the corresponding cost is the residual value of the equipment; and the corresponding time coordinate of the intersection point G of the curve C and the X axis is the theoretical decommissioning time of the equipment, the current cost state of the equipment is judged according to the time of the intersection point E, if the time of the intersection point E is not more than E, the equipment does not need to be replaced in normal operation, if the time of the intersection point E is more than E and less than G, the equipment is recommended to be replaced, and if the time of the intersection point E is more than G, the equipment is recommended to be decommissioned. A cost conclusion is obtained.
5) According to the standardized online monitoring diagnosis conclusion, the test conclusion and the cost conclusion obtained in the steps, the comprehensive evaluation of the equipment is carried out through a variable weight weighting deduction method
The corresponding deduction value of the state quantity data acquired by different evaluation models is 0, and the weighted deduction value is 0; otherwise, the weighted score value is calculated as:
in the formula: n is a state quantity evaluation model; bi is a deduction value corresponding to the evaluation model in the ith; ai is a reliability coefficient of the ith evaluation model; a' i is the corrected reliability coefficient of the ith evaluation model.
The specific embodiment is as follows:
extracting several groups of online monitoring data, test reports and cost for analysis:
and (3) online monitoring data:
H2：113、102、151、157、156
C2H2：0、0、6、6.5、6.3
total hydrocarbons: 107. 101, 103, 100, 105
List letter description:
h2: hydrogen gas
C2H2: acetylene
Calculating the abnormal hydrogen and acetylene threshold values through threshold value analysis and calculation, calculating the abnormal hydrogen and acetylene trend through trend analysis and calculation, and obtaining an online monitoring conclusion 2
The test data are as follows:
tanδ/％：1992.04.22(0.1)、1995.01.18(0.65)、1995.04.11(1.75)
the tg delta of the winding is calculated to exceed the standard through analysis and calculation of a test threshold, and the test conclusion is 1
The equipment is put into operation in 1992 and 25 years till now according to ledger arrangement, the retirement time is 2012 according to a cost curve theory, and the cost conclusion is 2
And calculating by a variable weight weighting deduction method to obtain the equipment state of 1.4, wherein the equipment state is abnormal.
Claims (1)
1. A comprehensive evaluation method based on equipment life cycle information is characterized by comprising the following steps:
step 1: forming a data base for evaluation and analysis by classifying the equipment online monitoring data, the test report and the cost;
and 2, step: forming an online monitoring diagnosis conclusion, carrying out threshold crossing judgment on online monitoring data and a threshold value, carrying out diagnosis on a change rate by combining trends to obtain an online monitoring diagnosis conclusion A, and carrying out standardized assignment on the conclusion:
1) And (4) normal: 0;
2) Threshold/trend warning: 1;
3) Threshold and trend early warning: 2;
the formula of the trend warning is as follows:
in the formula, is y 1 ，y 2 ，…，y t In order to monitor the sequence of events,and n is the moving average value at the moment of t +1 and is called the moving time interval. If the predicted value of the monitoring data rising gradient continuously exceeds the set threshold value, the equipment is in a fault precursor period, and an alarm is given in time to effectively control the fault spreading and avoid accidents;
and step 3: forming a diagnosis conclusion of a test report, extracting a test value according to the test report, mapping the associated threshold value of the test value, early warning the threshold value to obtain a test conclusion B, wherein the test conclusion B is normal if all test items are normal, the test conclusion B with abnormal test items is abnormal, and carrying out standardized assignment on the result:
1) And (3) normal: 0
2) Abnormality: 1;
and 4, step 4: forming a cost conclusion based on the equipment life cycle event, and according to the theoretical operation years of various types of equipment, taking the initial cost of the purchase cost as a descending theoretical life trend curve C, curve C: y = aX + b, where b is the equipment procurement cost, a = equipment procurement cost/equipment theoretical operating life; taking the later cost caused by equipment accidents, faults and overhaul events after operation and maintenance as an increasing actual cost trend curve D, wherein the trend curve D = the equipment purchase cost + the equipment implementation cost + the equipment operation and maintenance cost step curve, when the curves C and D are intersected, the corresponding time coordinate of an intersection point E is the optimal replacement time of the equipment, and the corresponding cost is the residual value of the equipment; the corresponding time coordinate of an intersection point G of the curve C and the X axis is the theoretical decommissioning time of the equipment, the cost state of the equipment at present is judged according to the time of the intersection point E, if the cost state is not more than E, the equipment does not need to be replaced when the cost state is normal operation, if the cost state is more than E, the equipment is recommended to be replaced when the cost state is less than E, and if the cost state is more than G, the equipment is recommended to be decommissioned when the cost state is more than G; and (5) obtaining a cost conclusion F, and carrying out standardized assignment on the conclusion:
1) The normal operation does not need to be replaced: 0
2) And (4) replacement is recommended: 1
3) Out-of-service recommended by theoretical operating events: 2;
and 5: according to the standardized online monitoring diagnosis conclusion A, the standardized test conclusion B and the standardized cost conclusion F obtained in the steps, the comprehensive evaluation of the equipment is carried out through a variable weight weighting deduction method
The calculation rule of the weighted model deduction value is as follows:
(1) the data reliability is sorted from test to online monitoring and the cost is reduced, and the sorting rule is from high to low;
(2) dynamically increasing the weight corresponding to the acquisition mode with higher deduction value;
reliability coefficients of different evaluation models: test 1.0, on-line monitoring 0.8 and cost 0.6.
The corresponding deduction value of the state quantity data acquired by different evaluation models is 0, and the weighted deduction value is 0; otherwise, the weighted score value is calculated as:
in the formula: n is a state quantity evaluation model; bi is a deduction value corresponding to the evaluation model in the ith; ai is a reliability coefficient of the ith evaluation model; a' i is a correction reliability coefficient of the ith evaluation model;
in order to avoid that the accumulated deduction of a certain deduction element is too high to cause too low equipment evaluation score and too serious equipment state evaluation, a deduction upper limit is set for each deduction element, and the final grading result is presented in percentage.
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| CN110203249A (en) * | 2019-06-12 | 2019-09-06 | 中国神华能源股份有限公司 | Train repairs processing method, device and the storage medium of journey |
| CN110210161A (en) * | 2019-06-12 | 2019-09-06 | 中国神华能源股份有限公司 | Appraisal procedure, device and the storage medium of rail vehicle health status |
| CN110222436A (en) * | 2019-06-12 | 2019-09-10 | 中国神华能源股份有限公司 | Appraisal procedure, device and the storage medium of Train Parts health status |
| CN110222437A (en) * | 2019-06-12 | 2019-09-10 | 中国神华能源股份有限公司 | Appraisal procedure, device and the storage medium of train car team health status |
| CN115754866A (en) * | 2022-11-04 | 2023-03-07 | 国网山东省电力公司电力科学研究院 | System and method for monitoring and early warning of whole life cycle of relay protection tester |
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| CN109241096A (en) * | 2018-08-01 | 2019-01-18 | 北京京东金融科技控股有限公司 | Data processing method, device and system |
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| CN110210161A (en) * | 2019-06-12 | 2019-09-06 | 中国神华能源股份有限公司 | Appraisal procedure, device and the storage medium of rail vehicle health status |
| CN110222436A (en) * | 2019-06-12 | 2019-09-10 | 中国神华能源股份有限公司 | Appraisal procedure, device and the storage medium of Train Parts health status |
| CN110222437A (en) * | 2019-06-12 | 2019-09-10 | 中国神华能源股份有限公司 | Appraisal procedure, device and the storage medium of train car team health status |
| CN110203249B (en) * | 2019-06-12 | 2020-09-04 | 中国神华能源股份有限公司 | Train repair process method, device and storage medium |
| CN110210161B (en) * | 2019-06-12 | 2021-04-06 | 中国神华能源股份有限公司 | Method and device for evaluating health state of train and storage medium |
| CN110222436B (en) * | 2019-06-12 | 2021-04-20 | 中国神华能源股份有限公司 | Method and device for evaluating health state of train parts and storage medium |
| CN110222437B (en) * | 2019-06-12 | 2021-05-11 | 中国神华能源股份有限公司 | Method and device for evaluating health status of train, and storage medium |
| CN115754866A (en) * | 2022-11-04 | 2023-03-07 | 国网山东省电力公司电力科学研究院 | System and method for monitoring and early warning of whole life cycle of relay protection tester |
| CN115754866B (en) * | 2022-11-04 | 2024-03-26 | 国网山东省电力公司电力科学研究院 | Relay protection tester full life cycle monitoring and early warning system and method |
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Application publication date: 20180109 |