CN102967798B - A kind of fault alarm method of power equipment and system - Google Patents
A kind of fault alarm method of power equipment and system Download PDFInfo
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- CN102967798B CN102967798B CN201210460157.3A CN201210460157A CN102967798B CN 102967798 B CN102967798 B CN 102967798B CN 201210460157 A CN201210460157 A CN 201210460157A CN 102967798 B CN102967798 B CN 102967798B
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Abstract
The present invention, in electric power system fault monitoring technical field, provides a kind of fault alarm method and system of power equipment.Wherein method comprises the following steps: set up the judge collection under a certain environmental factor, and it at least comprises normal temperature district and two, Faulty Temperature district element; Carry out thermometric to the power equipment under same environmental factor, and set up set of factors according to the temperature recorded, it comprises the absolute temperature of power equipment and relative temperature two elements of power equipment; In turn simple element evaluation and fuzzy comprehensive evoluation are carried out to set of factors and judge collection, obtains failure prediction matrix, press maximum subjection principle by each element in failure prediction matrix, determine the fault alarm result of power equipment.The fault alarm method of power equipment provided by the invention the thought of Fuzzy comprehensive evaluation is applied among the fault alarm field to power equipment, consider the environmental factor affecting power equipment temperature, achieve the reliable monitoring to power equipment running state.
Description
Technical field
The invention belongs to electric power system fault monitoring technical field, particularly relate to a kind of fault alarm method and system of power equipment.
Background technology
The critical role of the power equipment such as high voltage transmission line, distribution equipment in electric system, it is once break down, the serious consequences such as huge property loss and bad social influence can be caused, therefore, carry out reliable malfunction monitoring and send warning message in time seeming particularly important to power equipment in electric system.
Because power equipment is when breaking down, generally all can be attended by the phenomenon that heating is abnormal, by just can the running status of monitoring electrical equipment to the temperature monitoring of power equipment.The fault alarm method of the power equipment that prior art provides realizes the temperature monitoring of power equipment by infrared measurement of temperature equipment, temperature profile determination alarm threshold value when running according to power equipment specifically, and the temperature working as the power equipment that infrared temperature measuring equipment detects exceedes this alarm threshold value alarm.
But power equipment, particularly outfield high voltage electric power equip ment are subject to the impact of the environmental factors such as four seasons weather, strong sunlight irradiation, heavy rain, foggy weather, false alarm action is usually there is, poor reliability when making the fault alarm method applying the power equipment that prior art provides carry out malfunction monitoring to power equipment.
Summary of the invention
The object of the embodiment of the present invention is the fault alarm method providing a kind of power equipment, be intended to solve when the fault alarm method applying the power equipment that prior art provides carries out malfunction monitoring to power equipment and false alarm action usually occur, the problem of poor reliability.
The embodiment of the present invention is achieved in that a kind of fault alarm method of power equipment, said method comprising the steps of:
Set up the judge collection under a certain environmental factor, described judge collection at least comprises normal temperature district and two, Faulty Temperature district element;
Carry out thermometric to the power equipment under same described environmental factor, and set up set of factors according to the temperature recorded, described set of factors comprises the absolute temperature of described power equipment and relative temperature two elements of described power equipment;
In turn simple element evaluation and fuzzy comprehensive evoluation are carried out to described set of factors and described judge collection, obtains failure prediction matrix, press maximum subjection principle by each element in described failure prediction matrix, determine the fault alarm result of described power equipment;
The step of the described judge collection set up under a certain environmental factor is further comprising the steps of:
The multiple not temperature values in the same time of power equipment described in collection in worksite under a certain environmental factor;
Calculate the difference of the temperature value of adjacent moment in described multiple not temperature value in the same time, obtain multiple temperature change value of described power equipment;
Described multiple temperature value and described multiple temperature change value are carried out Frequency statistics respectively, thus determines that the dividing value of the humidity province of each element is concentrated in described judge, comprise the dividing value of described multiple temperature value and the dividing value of described multiple temperature change value;
The subordinate function of temperature and degree of membership relation thereof is characterized according to one, and the dividing value of the described multiple temperature value obtained, set up the judge collection of an absolute temperature;
The subordinate function of temperature and degree of membership relation thereof is characterized according to one, and the dividing value of the described multiple temperature change value obtained, set up the judge collection of a relative temperature.
Another object of the embodiment of the present invention is the failure warning system providing a kind of power equipment, and described system comprises:
Pass judgment on collection and set up unit, for setting up the judge collection under a certain environmental factor, described judge collection at least comprises normal temperature district and two, Faulty Temperature district element;
Set of factors sets up unit, for carrying out thermometric to the power equipment under same described environmental factor, and sets up set of factors according to the temperature recorded, and described set of factors comprises the absolute temperature of described power equipment and relative temperature two elements of described power equipment;
Pass judgment on unit, the judge collection that set of factors and described judge collection for setting up unit foundation to described set of factors set up unit foundation carries out simple element evaluation and fuzzy comprehensive evoluation in turn, obtain failure prediction matrix, and press maximum subjection principle by each element in described failure prediction matrix, determine the fault alarm result of described power equipment;
Described judge collection is set up unit and is comprised:
First temperature sensor, for the multiple not temperature values in the same time of power equipment described in collection in worksite under a certain environmental factor;
Computing module, for calculate that described first temperature sensor collects described multiple not temperature values in the same time in the difference of temperature value of adjacent moment, obtain multiple temperature change value of described power equipment;
Frequency statistics module, the described multiple temperature change value calculated for described multiple temperature value of being collected by described first temperature sensor and described computing module carries out Frequency statistics respectively, thus the dividing value of the humidity province of each element is concentrated in true described judge, comprise the dividing value of described multiple temperature value and the dividing value of described multiple temperature change value;
Absolute temperature is passed judgment on collection and is set up module, for characterizing the subordinate function of temperature and degree of membership relation thereof according to one, and the dividing value of described multiple temperature value that described Frequency statistics module is determined, set up the judge collection of an absolute temperature;
Relative temperature is passed judgment on collection and is set up module, for characterizing the subordinate function of temperature and degree of membership relation thereof according to one, and the dividing value of described multiple temperature change value that described Frequency statistics module is determined, set up the judge collection of a relative temperature.
The fault alarm method of the power equipment that the embodiment of the present invention provides the thought of Fuzzy comprehensive evaluation is applied among the fault alarm field to power equipment, consider the environmental factor affecting power equipment temperature, achieve the reliable monitoring to power equipment running state, be specially adapted to monitor the fault alarm of transformer station's mesohigh power equipment.
Accompanying drawing explanation
Fig. 1 is the fault alarm method process flow diagram of the power equipment that the embodiment of the present invention provides;
Fig. 2 is the distribution plan of the subordinate function that the embodiment of the present invention provides;
Fig. 3 is the failure warning system theory diagram of the power equipment that the embodiment of the present invention provides;
Fig. 4 is the concrete structure figure of Fig. 3.
Embodiment
In order to make object of the present invention, technical scheme and advantage clearly understand, below in conjunction with drawings and Examples, the present invention is further elaborated.Should be appreciated that specific embodiment described herein only in order to explain the present invention, be not intended to limit the present invention.
The thought of Fuzzy comprehensive evaluation is applied to the fault alarm field to power equipment by the fault alarm method of the power equipment that the embodiment of the present invention provides.
Fig. 1 shows the fault alarm method flow process of the power equipment that the embodiment of the present invention provides.
In step S101, set up the judge collection under a certain environmental factor, this judge collection at least comprises normal temperature district and two, Faulty Temperature district element.The element number that this judge collection comprises can increase according to actual needs, such as, in order to indicating that the temperature range that power equipment exists potential faults realizes fault pre-alarming, this judge collection can also comprise the early warning humidity province between normal temperature district and Faulty Temperature district.
Particularly, step S101 can comprise the following steps: on-the-spot infrared thermometer or other temperature sensor of adopting gathers the multiple not temperature values in the same time of power equipment under a certain environmental factor, the temperature value in each moment both can be the temperature of a sampled point on this power equipment, also can the mean value of temperature of multiple sampled points preferably on this power equipment, to improve judge precision; Calculate the difference of the temperature value of adjacent moment in the plurality of not temperature value in the same time, obtain multiple temperature change value of this power equipment; The plurality of temperature value and multiple temperature change value are carried out Frequency statistics respectively, thus determines the dividing value passing judgment on the humidity province of concentrating each element, comprise the dividing value of multiple temperature value and the dividing value of multiple temperature change value; The subordinate function of temperature and degree of membership relation thereof is characterized according to one, and the dividing value of the multiple temperature values obtained, set up the judge collection of an absolute temperature; The subordinate function of temperature and degree of membership relation thereof is characterized according to one, and the dividing value of the multiple temperature change value obtained, set up the judge collection of a relative temperature.
Environmental factor wherein can be the various factors temperature acquisition of power equipment being had to certain influence, as season, ambient temperature and humidity, equipment self-growth sexual dysfunction etc., certainly, when do not consider environmental factor on pass judgment on degree of accuracy impact or not high to judge accuracy requirement, on-the-spot also can be not limited to a certain environmental factor to the collection of power equipment temperature value under.
In step s 102, application infrared thermometer or other temperature sensor carry out thermometric to the power equipment under same environmental factor, and set up set of factors according to the temperature recorded, this set of factors comprises the absolute temperature of this power equipment and relative temperature two elements of this power equipment.
Similarly, absolute temperature both can be the temperature of a sampled point on this power equipment, also can the mean value of temperature of multiple sampled points preferably on this power equipment, to improve judge precision; Relative temperature both can be the temperature difference of a sampled point adjacent moment on this power equipment, also can divide the mean value of other adjacent moment temperature difference, to improve judge precision by the multiple sampled points preferably on this power equipment.
In step s 103, in turn simple element evaluation and fuzzy comprehensive evoluation are carried out to set of factors and judge collection, obtains failure prediction matrix, press maximum subjection principle by each element in this failure prediction matrix, determine the fault alarm result of this power equipment.
Wherein, in turn simple element evaluation and fuzzy comprehensive evoluation are carried out to set of factors and judge collection, the step obtaining failure prediction matrix can further include following steps: carry out simple element evaluation to set of factors and judge collection: the judge collection absolute temperature in set of factors being mapped as absolute temperature according to corresponding subordinate function, namely the degree of membership that each element is concentrated in the judge of absolute temperature to absolute temperature is calculated, such as, when the judge collection of absolute temperature comprises normal temperature district and Faulty Temperature district, the degree of membership that absolute temperature is under the jurisdiction of normal temperature district and Faulty Temperature district is respectively calculated according to subordinate function, same method, relative temperature in set of factors is mapped as the judge collection of relative temperature according to corresponding subordinate function, the judge collection of the absolute temperature after mapping and judge collection formation one fuzzy matrix of relative temperature, fuzzy comprehensive evoluation is carried out to set of factors and judge collection: definition absolute temperature and relative temperature to the weighted value of power equipment running state reflection degree, form a weight matrix respectively, this weight matrix and fuzzy matrix are carried out Comprehensive Evaluation according to minimax computing principle, obtains failure prediction matrix.
The fault alarm method of the power equipment that the embodiment of the present invention provides the thought of Fuzzy comprehensive evaluation is applied among the fault alarm field to power equipment, consider the environmental factor affecting power equipment temperature, achieve the reliable monitoring to power equipment running state.
For the ease of understanding, comprise normal temperature district, early warning humidity province and Faulty Temperature district below to pass judgment on collection, subordinate function is that example illustrates above-mentioned implementation step for rising half trapezoidal profile:
First, the judge collection V=﹛ V under a certain environmental factor is set up
1, V
2, V
3﹜=﹛ normal temperature district, early warning humidity province, Faulty Temperature Qu ﹜, its Membership Function Distribution as shown in Figure 2, wherein, horizontal ordinate T representation temperature, ordinate μ represents degree of membership, with
represent the distribution function of normal temperature district V1 respectively, the distribution function of early warning humidity province V2, the distribution function of Faulty Temperature district V3, then this subordinate function expression formula be:
Wherein, for the judge collection of absolute temperature, T
1, T
2, T
3, T
4, T
5, T
6, T
7, T
8be the dividing value of the multiple temperature values obtained; For the judge collection of relative temperature, T
1, T
2, T
3, T
4, T
5, T
6, T
7, T
8be the dividing value of the multiple temperature change value obtained.
Afterwards, according to the temperature-measuring results to the power equipment under same environmental factor, set up a set of factors U=﹛ U
1, U
2﹜=﹛ absolute temperature, to Wen Du ﹜.
To in set of factors and pass judgment on collection and carry out simple element evaluation: calculate absolute temperature U according to as above subordinate function expression formula
1to the degree of membership U in normal temperature district
11, absolute temperature U
1to the degree of membership U of early warning humidity province
12, absolute temperature U
1to the degree of membership U in Faulty Temperature district
13; Similarly, relative temperature U is calculated according to as above subordinate function expression formula
2to the degree of membership U in normal temperature district
21, relative temperature U
2to the degree of membership U of early warning humidity province
22, relative temperature U
2to the degree of membership U in Faulty Temperature district
23, thus obtain a fuzzy matrix R, this fuzzy matrix R is expressed as:
Fuzzy comprehensive evoluation is carried out to set of factors and judge collection: definition absolute temperature and relative temperature are respectively to the weighted value of power equipment running state reflection degree, due in actual applications, absolute temperature indicates the temperature of power equipment, relative temperature indicates the temperature changing trend of power equipment, absolute temperature is compared to relative temperature, the operation conditions showing power equipment that can be clearer and more definite, therefore, definition absolute temperature weighted value is greater than the weighted value of relative temperature, according to practical experience, the weighted value of definition absolute temperature is 0.6, the weighted value of relative temperature is 0.4 comparatively reasonable, the weight matrix A=[0.6 now formed, 0.4], weight matrix A and fuzzy matrix R is carried out Comprehensive Evaluation according to minimax computing principle, obtain failure prediction matrix
failure prediction matrix
specifically be expressed as:
If A=is (a
ij)
m × n, R=(r
ij)
n × s, then
i=1,2 ..., m; J=1,2 ..., wherein, " ∨ ", " ∧ " represent and get large, minimizing operation s. respectively.In the embodiment of the present invention, failure prediction matrix
be the matrix of a 1*3, each element representation in this matrix is to the Comprehensive Evaluation of power equipment temperature, and correspondence passes judgment on Ji ﹛ normal temperature district respectively, early warning humidity province, each element in Faulty Temperature Qu ﹜.
Finally, by maximum subjection principle, get
the element of middle degree of membership maximal value is as final comprehensive decision value, and the humidity province of its representative is the fault alarm result of this power equipment.
Fig. 3 is the failure warning system theory diagram of the power equipment that the embodiment of the present invention provides, and for convenience of explanation, illustrate only the part relevant to the embodiment of the present invention.
The failure warning system of the power equipment that the embodiment of the present invention provides comprises: pass judgment on collection and set up unit 11, for setting up the judge collection under a certain environmental factor, this judge collection at least comprises normal temperature district and two, Faulty Temperature district element; Set of factors sets up unit 12, for carrying out thermometric to the power equipment under same environmental factor, and sets up set of factors according to the temperature recorded, and this set of factors comprises the absolute temperature of this power equipment and relative temperature two elements of this power equipment; Pass judgment on unit 13, for carrying out simple element evaluation and fuzzy comprehensive evoluation in turn to set of factors and judge collection, obtaining failure prediction matrix, and pressing maximum subjection principle by each element in this failure prediction matrix, determining the fault alarm result of this power equipment.
Fig. 4 shows the concrete structure of Fig. 3.
Wherein, pass judgment on collection and set up unit 11 and specifically comprise: the first temperature sensor 111, for the multiple not temperature values in the same time of collection in worksite power equipment under a certain environmental factor; Computing module 112, for calculate that the first temperature sensor 111 collects multiple not temperature values in the same time in the difference of temperature value of adjacent moment, obtain multiple temperature change value of this power equipment; Frequency statistics module 113, the multiple temperature change value calculated for multiple temperature value of being collected by the first temperature sensor 111 and computing module 112 carry out Frequency statistics respectively, thus determine the dividing value passing judgment on the humidity province of concentrating each element, comprise the dividing value of multiple temperature value and the dividing value of multiple temperature change value; Absolute temperature is passed judgment on collection and is set up module 114, for characterizing the subordinate function of temperature and degree of membership relation thereof according to one, and the dividing value of multiple temperature values that Frequency statistics module 113 is determined, set up the judge collection of an absolute temperature; Relative temperature is passed judgment on collection and is set up module 115, for characterizing the subordinate function of temperature and degree of membership relation thereof according to one, and the dividing value of multiple temperature change value that Frequency statistics module 113 is determined, set up the judge collection of a relative temperature.
Wherein, set of factors is set up unit 12 and is specifically comprised: the second temperature sensor 121, for carrying out thermometric to the power equipment under same environmental factor; Set of factors sets up module 122, sets up set of factors for the temperature recorded according to the second temperature sensor 121.
Wherein, pass judgment on unit 13 specifically to comprise: simple element evaluation module 131, be mapped as absolute temperature for absolute temperature set of factors set up in set of factors that module 122 sets up according to corresponding subordinate function and pass judgment on the judge collection that the absolute temperature that module 114 is set up set up by collection, relative temperature set of factors set up in the set of factors that module 122 sets up is mapped as relative temperature according to corresponding subordinate function and passes judgment on the judge collection that the relative temperature that module 115 is set up set up by collection, the judge collection of the absolute temperature after mapping and judge collection formation one fuzzy matrix of relative temperature; Fuzzy comprehensive evoluation module 132, for defining absolute temperature and relative temperature respectively to the weighted value of power equipment running state reflection degree, form a weight matrix, and the fuzzy matrix this weight matrix and simple element evaluation module 131 formed carries out Comprehensive Evaluation according to minimax computing principle, obtains failure prediction matrix; Alarming result output module 133, for each element in the failure prediction matrix that obtained by fuzzy comprehensive evoluation module 132 by maximum subjection principle, determines the fault alarm result of this power equipment.
The fault alarm method of the power equipment that the embodiment of the present invention provides the thought of Fuzzy comprehensive evaluation is applied among the fault alarm field to power equipment, consider the environmental factor affecting power equipment temperature, achieve the reliable monitoring to power equipment running state, be specially adapted to monitor the fault alarm of transformer station's mesohigh power equipment.
One of ordinary skill in the art will appreciate that all or part of step realized in above-described embodiment method is that the hardware that can control to be correlated with by program completes, described program can be stored in a computer read/write memory medium, described storage medium, as ROM/RAM, disk, CD etc.
The foregoing is only preferred embodiment of the present invention, not in order to limit the present invention, all any amendments done within the spirit and principles in the present invention, equivalent replacement and improvement etc., all should be included within protection scope of the present invention.
Claims (8)
1. a fault alarm method for power equipment, is characterized in that, said method comprising the steps of:
Set up the judge collection under a certain environmental factor, described judge collection at least comprises normal temperature district and two, Faulty Temperature district element;
Carry out thermometric to the power equipment under same described environmental factor, and set up set of factors according to the temperature recorded, described set of factors comprises the absolute temperature of described power equipment and relative temperature two elements of described power equipment;
In turn simple element evaluation and fuzzy comprehensive evoluation are carried out to described set of factors and described judge collection, obtains failure prediction matrix, press maximum subjection principle by each element in described failure prediction matrix, determine the fault alarm result of described power equipment;
The step of the described judge collection set up under a certain environmental factor is further comprising the steps of:
The multiple not temperature values in the same time of power equipment described in collection in worksite under a certain environmental factor;
Calculate the difference of the temperature value of adjacent moment in described multiple not temperature value in the same time, obtain multiple temperature change value of described power equipment;
Described multiple temperature value and described multiple temperature change value are carried out Frequency statistics respectively, thus determines that the dividing value of the humidity province of each element is concentrated in described judge, comprise the dividing value of described multiple temperature value and the dividing value of described multiple temperature change value;
The subordinate function of temperature and degree of membership relation thereof is characterized according to one, and the dividing value of the described multiple temperature value obtained, set up the judge collection of an absolute temperature;
The subordinate function of temperature and degree of membership relation thereof is characterized according to one, and the dividing value of the described multiple temperature change value obtained, set up the judge collection of a relative temperature.
2. the fault alarm method of power equipment as claimed in claim 1, is characterized in that, describedly carries out simple element evaluation and fuzzy comprehensive evoluation in turn to described set of factors and described judge collection, and the step obtaining failure prediction matrix is further comprising the steps of:
Described absolute temperature in described set of factors is mapped to the judge collection of described absolute temperature according to corresponding described subordinate function, thus calculates the degree of membership that each element is concentrated in the judge of absolute temperature to absolute temperature; Described relative temperature in described set of factors is mapped to the judge collection of described relative temperature according to corresponding described subordinate function, thus calculates the degree of membership that each element is concentrated in the judge of relative temperature to relative temperature; The judge collection of the described absolute temperature after mapping and judge collection formation one fuzzy matrix of described relative temperature;
Define described absolute temperature and described relative temperature respectively to the weighted value of described power equipment running state reflection degree, form a weight matrix;
Described weight matrix and described fuzzy matrix are carried out Comprehensive Evaluation according to minimax computing principle, obtains described failure prediction matrix.
3. the fault alarm method of the power equipment as described in any one of claim 1 to 2, it is characterized in that, judge collection under described environmental factor comprises normal temperature district, early warning humidity province and Faulty Temperature district, and described early warning humidity province is between described normal temperature district and described Faulty Temperature district.
4. the fault alarm method of power equipment as claimed in claim 3, is characterized in that, described subordinate function adopts and rises half trapezoidal profile.
5. the fault alarm method of power equipment as claimed in claim 3, is characterized in that, the weighted value of described absolute temperature to described power equipment running state reflection degree is greater than the weighted value of described relative temperature to described power equipment running state reflection degree.
6. the fault alarm method of power equipment as claimed in claim 5, is characterized in that, the weighted value of described absolute temperature to described power equipment running state reflection degree is 0.6; The weighted value of described relative temperature to described power equipment running state reflection degree is 0.4.
7. a failure warning system for power equipment, is characterized in that, described system comprises:
Pass judgment on collection and set up unit, for setting up the judge collection under a certain environmental factor, described judge collection at least comprises normal temperature district and two, Faulty Temperature district element;
Set of factors sets up unit, for carrying out thermometric to the power equipment under same described environmental factor, and sets up set of factors according to the temperature recorded, and described set of factors comprises the absolute temperature of described power equipment and relative temperature two elements of described power equipment;
Pass judgment on unit, the judge collection that set of factors and described judge collection for setting up unit foundation to described set of factors set up unit foundation carries out simple element evaluation and fuzzy comprehensive evoluation in turn, obtain failure prediction matrix, and press maximum subjection principle by each element in described failure prediction matrix, determine the fault alarm result of described power equipment;
Described judge collection is set up unit and is comprised:
First temperature sensor, for the multiple not temperature values in the same time of power equipment described in collection in worksite under a certain environmental factor;
Computing module, for calculate that described first temperature sensor collects described multiple not temperature values in the same time in the difference of temperature value of adjacent moment, obtain multiple temperature change value of described power equipment;
Frequency statistics module, the described multiple temperature change value calculated for described multiple temperature value of being collected by described first temperature sensor and described computing module carries out Frequency statistics respectively, thus determine that the dividing value of the humidity province of each element is concentrated in described judge, comprise the dividing value of described multiple temperature value and the dividing value of described multiple temperature change value;
Absolute temperature is passed judgment on collection and is set up module, for characterizing the subordinate function of temperature and degree of membership relation thereof according to one, and the dividing value of described multiple temperature value that described Frequency statistics module is determined, set up the judge collection of an absolute temperature;
Relative temperature is passed judgment on collection and is set up module, for characterizing the subordinate function of temperature and degree of membership relation thereof according to one, and the dividing value of described multiple temperature change value that described Frequency statistics module is determined, set up the judge collection of a relative temperature.
8. the failure warning system of power equipment as claimed in claim 7, it is characterized in that, described set of factors is set up unit and is also comprised:
Second temperature sensor, for carrying out thermometric to the described power equipment under same described environmental factor;
Set of factors sets up module, sets up set of factors for the temperature recorded according to described second temperature sensor;
Described judge unit also comprises:
Simple element evaluation module, be mapped to described absolute temperature for the described absolute temperature described set of factors set up in the described set of factors of module foundation according to corresponding described subordinate function and pass judgment on the judge collection that the described absolute temperature that module is set up set up by collection, thus calculate the degree of membership that each element is concentrated in the judge of absolute temperature to absolute temperature; The described relative temperature described set of factors set up in the described set of factors of module foundation is mapped to described relative temperature according to corresponding described subordinate function and passes judgment on the judge collection that the described relative temperature that module is set up set up by collection, thus calculates the degree of membership that each element is concentrated in the judge of relative temperature to relative temperature; The judge collection of the described absolute temperature after mapping and judge collection formation one fuzzy matrix of described relative temperature;
Fuzzy comprehensive evoluation module, for defining described absolute temperature and described relative temperature respectively to the weighted value of described power equipment running state reflection degree, form a weight matrix, and the described fuzzy matrix of described weight matrix and described simple element evaluation module composition is carried out Comprehensive Evaluation according to minimax computing principle, obtain described failure prediction matrix;
Alarming result output module, for each element in the described failure prediction matrix that obtained by described fuzzy comprehensive evoluation module by maximum subjection principle, determines the fault alarm result of described power equipment.
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| CN103308199A (en) * | 2013-06-03 | 2013-09-18 | 合肥天海电气技术有限公司 | Wireless temperature detecting monitoring system for grid operation equipment based on fuzzy processing |
| CN105427543A (en) * | 2015-12-17 | 2016-03-23 | 国网浙江省电力公司信息通信分公司 | Temperature early warning method and system based on smart grid |
| CN106932686B (en) * | 2017-03-21 | 2019-07-09 | 国网上海市电力公司 | Power grid exception rapid detection method based on minimax method of characteristic |
| CN108921452B (en) * | 2018-07-27 | 2021-04-09 | 华北电力大学（保定） | Power transmission line risk assessment composite early warning method based on fuzzy algorithm |
| CN109116319B (en) * | 2018-11-13 | 2023-02-28 | 北京无线电测量研究所 | Fault detection method for radar system |
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| CN102447593A (en) * | 2011-11-21 | 2012-05-09 | 福建星网锐捷网络有限公司 | Test method and device |
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| CN102759670A (en) * | 2011-12-31 | 2012-10-31 | 重庆大学 | Method for evaluating operation state of dry type transformer |
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| US7801648B2 (en) * | 2006-05-23 | 2010-09-21 | Hanbit Tech Inc. | Automatic trip device and control method thereof |
| CN102447593A (en) * | 2011-11-21 | 2012-05-09 | 福建星网锐捷网络有限公司 | Test method and device |
| CN102496069A (en) * | 2011-12-07 | 2012-06-13 | 山东电力集团公司青岛供电公司 | Cable multimode safe operation evaluation method based on fuzzy analytic hierarchy process (FAHP) |
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