CN117250496A - Spring energy storage detection method and system of GIS circuit breaker - Google Patents
Spring energy storage detection method and system of GIS circuit breaker Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/327—Testing of circuit interrupters, switches or circuit-breakers
- G01R31/3271—Testing of circuit interrupters, switches or circuit-breakers of high voltage or medium voltage devices
- G01R31/3275—Fault detection or status indication
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
Abstract
The invention discloses a spring energy storage detection method and a spring energy storage detection system for a GIS breaker, which are used for acquiring running state data of a spring mechanism of the GIS breaker; performing primary fault judgment on the running state data according to a preset fault running state threshold range; outputting a judging result of the GIS breaker spring mechanism as a normal state result if the running state data is not in the fault running state threshold range; and if the running state data is within the fault running state threshold range, performing secondary fault judgment according to the running state data, and outputting a judgment result of the GIS breaker spring mechanism as a fault state result. According to the invention, first fault judgment is carried out based on the fault running state threshold range, so that the normal state of the GIS breaker spring mechanism is distinguished, and second fault judgment is carried out on running state data in the fault running state range, so that a specific type of fault state is output.
Description
Technical Field
The invention relates to the field of equipment detection, in particular to a spring energy storage detection method and system of a GIS breaker.
Background
A gas insulated substation (Gas Insulated Substation, abbreviated GIS) is a category of substation. In a gas-insulated substation, most of the electrical equipment is directly or indirectly sealed in a pipe tree consisting of metal pipes and bushings, without any switches, lines and terminals being visible from the outside. The breaker in the GIS is required to realize the breaking action through the spring mechanism, so that the state of the spring mechanism is detected, and the state of the spring mechanism is judged through detected data, so that the spring mechanism is maintained or replaced conveniently.
In the use process of the GIS breaker, maintenance is often required to be started until the GIS breaker has a problem, which affects the use efficiency of the GIS breaker. Especially when spring mechanism goes wrong, can influence GIS's operation safety.
Therefore, a spring energy storage detection strategy of the GIS breaker is needed, so that the operation fault of the spring mechanism of the GIS breaker is detected timely.
Disclosure of Invention
The embodiment of the invention provides a spring energy storage detection method of a GIS breaker, which is used for timely detecting the operation fault of a spring mechanism of the GIS breaker.
In order to solve the above problems, an embodiment of the present invention provides a spring energy storage detection method of a GIS circuit breaker, including:
Acquiring running state data of a spring mechanism of the GIS breaker;
performing primary fault judgment on the running state data according to a preset fault running state threshold range to obtain spring elastic force fault data, opening and closing speed fault data, opening and closing coil current fault data and energy storage motor current fault data;
outputting a judging result of the GIS breaker spring mechanism as a normal state result if the running state data is not in the fault running state threshold range;
if the running state data is within the fault running state threshold value range, performing secondary fault judgment according to the running state data to obtain a spring elastic force fault type, a switching-on and switching-off speed fault type, a switching-on and switching-off coil current fault type and an energy storage motor current fault type, and outputting a judging result of the GIS breaker spring mechanism as a fault state result; wherein the fault state result comprises: spring elastic force fault data and spring elastic force fault type, opening and closing speed fault data and opening and closing speed fault type, opening and closing coil current fault data and opening and closing coil current fault type, and energy storage motor current fault data and energy storage motor current fault type.
As an improvement of the above-described aspect, the operation state data includes: spring force data, opening and closing speed data, opening and closing coil current data and energy storage motor current data; the fault operating state threshold range includes: spring elastic force fault threshold range, switching-on and switching-off speed fault threshold range, switching-on and switching-off coil current fault threshold range and energy storage motor current fault threshold range.
As an improvement of the above solution, the performing, according to a preset threshold range of the fault running state, a fault judgment on the running state data includes:
judging spring elastic force data, opening and closing speed data, opening and closing coil current data and energy storage motor current data according to a preset spring elastic force fault threshold range, opening and closing speed fault threshold range, opening and closing coil current fault threshold range and energy storage motor current fault threshold range;
if the spring force data is not in the spring force fault threshold range, the opening and closing speed data is not in the opening and closing speed fault threshold range, the opening and closing coil current data is not in the opening and closing coil current fault threshold range and the energy storage motor current data is not in the energy storage motor current fault threshold range, judging that the GIS breaker spring mechanism is in a normal state;
And if the spring elastic force data is in the spring elastic force fault threshold range, or the opening and closing speed data is in the opening and closing speed fault threshold range, or the opening and closing coil current data is in the opening and closing coil current fault threshold range, or the energy storage motor current data is in the energy storage motor current fault threshold range, judging that the GIS breaker spring mechanism is in a fault state.
As an improvement of the above solution, the performing secondary fault judgment according to the running state data to obtain a spring elastic force fault type, a switching-on/off speed fault type, a switching-on/off coil current fault type and an energy storage motor current fault type, and outputting a judgment result of the GIS circuit breaker spring mechanism as a fault state result, including:
inputting the running state data into a preset spring energy storage detection model, and performing secondary fault judgment to obtain a spring elastic force fault type, a switching-on and switching-off speed fault type, a switching-on and switching-off coil current fault type and an energy storage motor current fault type; the spring energy storage detection model is obtained by inputting a plurality of training samples marked with fault positions and fault types of the GIS breaker spring mechanism into a neural network for training;
And combining the spring elastic force fault type, the opening and closing speed fault type, the opening and closing coil current fault type and the energy storage motor current fault type, and obtaining spring elastic force fault data, opening and closing speed fault data, opening and closing coil current fault data and energy storage motor current fault data to obtain a fault state result of the GIS breaker spring mechanism.
As an improvement of the scheme, the training method of the spring energy storage detection model comprises the following steps:
acquiring historical operation data of a plurality of GIS breaker spring mechanisms;
sequencing each data point in the historical operation data according to a time sequence, and performing data supplementing operation on the historical operation data according to a preset time granularity through an interpolation method to obtain historical fault data; the data supplementing operation specifically comprises the following steps: performing missing identification operation on the time corresponding to each data point in the historical operation data according to a preset time granularity; if the time of the data point is lost, carrying out data supplementation by an interpolation method, and carrying out data supplementation operation on the next data point until all data point operations are executed after completing the data supplementation of the time-lost data point; if the time of the data point is not lost, directly carrying out data supplementing operation on the next data point until all data point operations are executed;
Determining a first reference data point and a second reference data point, and mapping the historical fault data on a first plane by taking the first reference data point as a center to obtain a first data sequence; mapping the historical fault data to a second plane by taking a second datum point as a center to obtain a second data sequence; determining data points with differences between the first data sequence and the second data sequence as data for marking fault positions and fault types, and obtaining training samples; wherein the training sample comprises: the device comprises a spring elastic force fault training sample, an opening and closing speed fault training sample, an opening and closing coil current fault training sample and an energy storage motor current fault training sample;
and inputting the spring elastic force fault training sample, the opening and closing speed fault training sample, the opening and closing coil current fault training sample and the energy storage motor current fault training sample into a neural network for training to obtain the spring energy storage detection model.
As an improvement of the above solution, after the outputting of the result of the judgment of the spring mechanism of the GIS circuit breaker is a fault state result, the method further includes:
according to a preset analytic hierarchy process, weight distribution is carried out on fault state results of the GIS breaker spring mechanism, and weighted calculation is carried out on the fault state results after the weight distribution, so that fault emergency degree evaluation values of the GIS breaker spring mechanism are obtained;
And determining maintenance processing time of the GIS breaker spring mechanism according to the fault emergency degree evaluation value, generating a maintenance processing instruction based on the maintenance processing time and the fault judgment result, and transmitting the maintenance processing instruction to a user side so that the user side reminds maintenance personnel to maintain the GIS breaker spring mechanism according to the maintenance processing instruction.
As an improvement of the above solution, the weighting calculation is performed on the fault status result after the weight is allocated, to obtain the fault emergency degree evaluation value of the spring mechanism of the GIS circuit breaker, including:
substituting spring elastic force fault data, opening and closing speed fault data, opening and closing coil current fault data and energy storage motor current fault data after weight distribution into a preset weighted summation formula, and calculating a fault emergency degree evaluation value of a GIS breaker spring mechanism; wherein the weighted summation formula is:
in the method, in the process of the invention,for failure emergency degree evaluation value, < >>For the first weight, ++>For the second weight, ++>For the third weight->For the fourth weight, ++>For spring force failure data, < >>For the switching speed fault data, < >>For switching on/off coil current fault data, +. >And the current fault data of the energy storage motor.
Correspondingly, an embodiment of the invention also provides a spring energy storage detection system of the GIS breaker, which comprises: the system comprises a data acquisition module, a data judgment module, a normal state judgment module and a fault state judgment module;
the data acquisition module is used for acquiring the running state data of the spring mechanism of the GIS breaker;
the data judging module is used for carrying out primary fault judgment on the running state data according to a preset fault running state threshold range;
the normal state judging module is used for outputting a judging result of the GIS breaker spring mechanism as a normal state result if the running state data is not in the fault running state threshold range;
and the fault state judging module is used for carrying out secondary fault judgment according to the running state data if the running state data is in the fault running state threshold range and outputting a judging result of the GIS breaker spring mechanism as a fault state result.
Correspondingly, an embodiment of the invention also provides a computer terminal device, which comprises a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, wherein the spring energy storage detection method of the GIS breaker is realized when the processor executes the computer program.
Correspondingly, an embodiment of the invention also provides a computer readable storage medium, which comprises a stored computer program, wherein the computer program is used for controlling equipment where the computer readable storage medium is located to execute the spring energy storage detection method of the GIS breaker.
From the above, the invention has the following beneficial effects:
the invention provides a spring energy storage detection method of a GIS breaker, which is used for acquiring running state data of a spring mechanism of the GIS breaker; performing primary fault judgment on the running state data according to a preset fault running state threshold range; outputting a judging result of the GIS breaker spring mechanism as a normal state result if the running state data is not in the fault running state threshold range; and if the running state data is within the fault running state threshold range, performing secondary fault judgment according to the running state data, and outputting a judgment result of the GIS breaker spring mechanism as a fault state result. The invention can collect the operation state data of the spring mechanism of the GIS breaker, judge the operation state data, timely detect the operation fault of the spring mechanism of the GIS breaker, analyze the operation state data, firstly carry out primary fault judgment based on the threshold range of the fault operation state, thereby distinguishing the normal state of the spring mechanism of the GIS breaker, and carry out secondary fault judgment on the operation state data in the range of the fault operation state, thereby outputting the specific type of fault state.
Drawings
Fig. 1 is a schematic flow chart of a spring energy storage detection method of a GIS circuit breaker according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a spring energy storage detection system of a GIS circuit breaker according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an AHP analytic hierarchy process relationship provided by one embodiment of the present invention;
fig. 4 is a schematic structural diagram of a terminal device according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to fig. 1, fig. 1 is a flow chart of a spring energy storage detection method of a GIS circuit breaker according to an embodiment of the present invention, as shown in fig. 1, the embodiment includes steps 101 to 104, and the steps are specifically as follows:
step 101: and acquiring the running state data of the spring mechanism of the GIS breaker.
In a specific embodiment, a spring force sensor is arranged at a spring of a GIS breaker spring mechanism, a speed measuring sensor is arranged at a brake switch of the GIS breaker spring mechanism, a first current sensor is arranged at a switching-on/off coil of the GIS breaker spring mechanism, and a second current sensor is arranged at an energy storage motor of the GIS breaker spring mechanism; and generating the running state data of the GIS breaker spring mechanism by receiving the data transmitted by the spring force sensor, the speed measuring sensor, the first current sensor and the second current sensor.
Step 102: and performing primary fault judgment on the running state data according to a preset fault running state threshold range to obtain spring elastic force fault data, opening and closing speed fault data, opening and closing coil current fault data and energy storage motor current fault data.
In this embodiment, the operation state data includes: spring force data, opening and closing speed data, opening and closing coil current data and energy storage motor current data; the fault operating state threshold range includes: spring elastic force fault threshold range, switching-on and switching-off speed fault threshold range, switching-on and switching-off coil current fault threshold range and energy storage motor current fault threshold range.
In this embodiment, the performing, according to the preset fault running state threshold range, a fault judgment on the running state data includes:
judging spring elastic force data, opening and closing speed data, opening and closing coil current data and energy storage motor current data according to a preset spring elastic force fault threshold range, opening and closing speed fault threshold range, opening and closing coil current fault threshold range and energy storage motor current fault threshold range;
if the spring force data is not in the spring force fault threshold range, the opening and closing speed data is not in the opening and closing speed fault threshold range, the opening and closing coil current data is not in the opening and closing coil current fault threshold range and the energy storage motor current data is not in the energy storage motor current fault threshold range, judging that the GIS breaker spring mechanism is in a normal state;
and if the spring elastic force data is in the spring elastic force fault threshold range, or the opening and closing speed data is in the opening and closing speed fault threshold range, or the opening and closing coil current data is in the opening and closing coil current fault threshold range, or the energy storage motor current data is in the energy storage motor current fault threshold range, judging that the GIS breaker spring mechanism is in a fault state.
In a specific embodiment, the spring elastic force fault threshold range, the opening and closing speed fault threshold range, the opening and closing coil current fault threshold range and the energy storage motor current fault threshold range can be adaptively adjusted according to actual use scenes of users, and different threshold ranges can be adjusted according to the model and the use scenes of the GIS circuit breaker.
In a specific embodiment, if all of the four operation state data (spring force data, opening and closing speed data, opening and closing coil current data and energy storage motor current data) are not in the four preset fault operation state ranges (spring force fault threshold range, opening and closing speed fault threshold range, opening and closing coil current fault threshold range and energy storage motor current fault threshold range), the spring mechanism of the GIS circuit breaker under the condition is judged to be normal. If one or more of the four operating states are in the preset corresponding four fault operating state ranges, judging that the GIS breaker spring mechanism has the operating fault.
Step 103: and if the running state data is not in the fault running state threshold range, outputting a judging result of the GIS breaker spring mechanism as a normal state result.
In this embodiment, if the judgment result of the GIS circuit breaker spring mechanism is a normal state result, no warning is issued, and the reception and judgment of the operation state data is maintained.
Step 104: if the running state data is within the fault running state threshold value range, performing secondary fault judgment according to the running state data to obtain a spring elastic force fault type, a switching-on and switching-off speed fault type, a switching-on and switching-off coil current fault type and an energy storage motor current fault type, and outputting a judging result of the GIS breaker spring mechanism as a fault state result; wherein the fault state result comprises: spring elastic force fault data and spring elastic force fault type, opening and closing speed fault data and opening and closing speed fault type, opening and closing coil current fault data and opening and closing coil current fault type, and energy storage motor current fault data and energy storage motor current fault type.
In this embodiment, the performing secondary fault judgment according to the running state data, to obtain a spring elastic force fault type, a switching-on/off speed fault type, a switching-on/off coil current fault type, and an energy storage motor current fault type, and outputting a judgment result of the GIS circuit breaker spring mechanism as a fault state result, includes:
Inputting the running state data into a preset spring energy storage detection model, and performing secondary fault judgment to obtain a spring elastic force fault type, a switching-on and switching-off speed fault type, a switching-on and switching-off coil current fault type and an energy storage motor current fault type; the spring energy storage detection model is obtained by inputting a plurality of training samples marked with fault positions and fault types of the GIS breaker spring mechanism into a neural network for training;
and combining the spring elastic force fault type, the opening and closing speed fault type, the opening and closing coil current fault type and the energy storage motor current fault type, and obtaining spring elastic force fault data, opening and closing speed fault data, opening and closing coil current fault data and energy storage motor current fault data to obtain a fault state result of the GIS breaker spring mechanism.
In this embodiment, the training method of the spring energy storage detection model includes:
acquiring historical operation data of a plurality of GIS breaker spring mechanisms;
sequencing each data point in the historical operation data according to a time sequence, and performing data supplementing operation on the historical operation data according to a preset time granularity through an interpolation method to obtain historical fault data; the data supplementing operation specifically comprises the following steps: performing missing identification operation on the time corresponding to each data point in the historical operation data according to a preset time granularity; if the time of the data point is lost, carrying out data supplementation by an interpolation method, and carrying out data supplementation operation on the next data point until all data point operations are executed after completing the data supplementation of the time-lost data point; if the time of the data point is not lost, directly carrying out data supplementing operation on the next data point until all data point operations are executed;
Determining a first reference data point and a second reference data point, and mapping the historical fault data on a first plane by taking the first reference data point as a center to obtain a first data sequence; mapping the historical fault data to a second plane by taking a second datum point as a center to obtain a second data sequence; determining data points with differences between the first data sequence and the second data sequence as data for marking fault positions and fault types, and obtaining training samples; wherein the training sample comprises: the device comprises a spring elastic force fault training sample, an opening and closing speed fault training sample, an opening and closing coil current fault training sample and an energy storage motor current fault training sample;
and inputting the spring elastic force fault training sample, the opening and closing speed fault training sample, the opening and closing coil current fault training sample and the energy storage motor current fault training sample into a neural network for training to obtain the spring energy storage detection model.
In a specific embodiment, the neural network adopted by the invention adopts a BP neural network optimization algorithm to train the historical fault data of the marked GIS breaker spring mechanism, so that the running state of the GIS breaker spring mechanism can be judged based on spring force data, opening and closing speed data, opening and closing coil current data and energy storage motor current data.
In a specific embodiment, the training process: the method comprises the steps that historical operation data after classification marking is used for determining historical fault data as training samples, and because the numerical ranges of spring force, opening and closing speed, opening and closing coil current and energy storage motor current are large in difference, a neural network classifies and trains a plurality of training samples marked with fault types which are input one by one, so that the correlation between the spring force fault training samples, the opening and closing speed fault training samples, the opening and closing coil current fault training samples and the energy storage motor current fault training samples and the fault types marked by the spring force fault training samples, the opening and closing speed fault training samples, the opening and closing coil current fault training samples and the energy storage motor current fault training samples can be respectively learned, and a spring energy storage detection model is obtained through training;
the application process comprises the following steps: after the spring energy storage detection model obtains operation data, the operation data can be automatically classified into spring elastic force data, opening and closing speed data, opening and closing coil current data and energy storage motor current data, fault type identification is carried out on the spring elastic force data, the opening and closing speed data, the opening and closing coil current data and the energy storage motor current data respectively through the spring energy storage detection model, and the spring elastic force fault type corresponding to the spring elastic force data, the opening and closing speed fault type corresponding to the opening and closing speed data, the opening and closing coil current fault type corresponding to the opening and closing coil current data and the energy storage motor current fault type corresponding to the energy storage motor current data are output.
In a specific embodiment, the spring force failure types include: failure of the spring and breakage of the spring; the switching speed fault types include: the opening and closing is too slow, and the opening and closing is not tight; the switching-on/off coil current fault types include: the opening and closing coil is short-circuited and the opening and closing coil is open-circuited; the energy storage motor current fault types include: the energy storage motor is short-circuited, broken and overloaded.
In a specific embodiment, the time granularity is adaptively adjusted by a user, and the data supplementing operation can enable the historical operation data to be more complete, so that training sample features obtained based on the complete historical operation data are continuous, and the neural network can better conduct classification and discrimination.
More preferably, the two reference data points are arranged completely differently, two data sequences can be obtained by mapping the two reference data points onto the two planes, and repeated data can be screened out by performing difference comparison on the two data sequences, so that a user can better perform sample labeling, and the efficiency of user sample labeling is improved.
In this embodiment, after the outputting the result of the determination of the GIS breaker spring mechanism is a fault state result, the method further includes:
According to a preset analytic hierarchy process, weight distribution is carried out on fault state results of the GIS breaker spring mechanism, and weighted calculation is carried out on the fault state results after the weight distribution, so that fault emergency degree evaluation values of the GIS breaker spring mechanism are obtained;
and determining maintenance processing time of the GIS breaker spring mechanism according to the fault emergency degree evaluation value, generating a maintenance processing instruction based on the maintenance processing time and the fault judgment result, and transmitting the maintenance processing instruction to a user side so that the user side reminds maintenance personnel to maintain the GIS breaker spring mechanism according to the maintenance processing instruction.
In a specific embodiment, referring to fig. 3, the weight distribution is performed by using AHP hierarchical analysis, referring to fig. 3, a relationship diagram is constructed: the target layer is fault severity, and the criterion layer is four items of spring force, opening and closing speed, opening and closing coil current and energy storage motor current; the corresponding scheme layers can be primary, secondary and tertiary hazards.
Scoring by 10 experts, taking a scoring average value of the 10 experts by a 5-score scale method, scoring the importance degree between any two criterion layers, and constructing a judgment matrix according to the scoring result;
Carrying out solving operation through the SPSSAU judgment matrix to obtain an operation result, and obtaining a first weight, a second weight, a third weight, a fourth weight, a maximum characteristic root and a CI value (CI= (maximum characteristic root-n)/(n-1));
consistency judgment is required according to the CI value, the CI value is searched according to the order of a judgment matrix and a random consistency RI table preset by SPSSAU, and CR is calculated based on the CI value(ii) confirming whether the calculation result meets consistency; if yes, calculating the first weight, the second weight, the third weight and the fourth weight to perform fault emergency degree assessment value; if not, the expert scoring is re-acquired to perform weight calculation.
In this embodiment, the weighting calculation is performed on the fault state result after the weight is allocated, to obtain the fault emergency degree evaluation value of the spring mechanism of the GIS circuit breaker, including:
substituting spring elastic force fault data, opening and closing speed fault data, opening and closing coil current fault data and energy storage motor current fault data after weight distribution into a preset weighted summation formula, and calculating a fault emergency degree evaluation value of a GIS breaker spring mechanism; wherein the weighted summation formula is:
In the method, in the process of the invention,for failure emergency degree evaluation value, < >>For the first weight, ++>For the second weight, ++>For the third weight->For the fourth weight, ++>For spring force failure data, < >>For the switching speed fault data, < >>For switching on/off coil current fault data, +.>And the current fault data of the energy storage motor.
For better illustration, the following examples are given:
acquiring spring force data, opening and closing speed data, opening and closing coil current data and energy storage motor current data of a spring mechanism of the GIS breaker; carrying out primary fault judgment on spring force data and a spring force fault threshold range (three parameter ranges are divided based on actual conditions and respectively represent primary danger, secondary danger and tertiary danger), and judging that the spring force is the primary danger at the moment, wherein the spring force fault data is 1; comparing the opening and closing speed data with an opening and closing speed fault threshold range (three parameter ranges are divided based on actual conditions and respectively represent primary danger, secondary danger and tertiary danger), and judging that the opening and closing speed is the secondary danger at the moment, wherein the opening and closing speed fault data is 2; comparing the current data of the opening and closing coil with the current fault threshold range (dividing three parameter ranges based on actual conditions and respectively representing primary danger, secondary danger and tertiary danger) of the opening and closing coil, and judging that the current of the opening and closing coil is the tertiary danger at the moment, wherein the current fault data of the opening and closing coil is 3; comparing the current data of the energy storage motor with the current fault threshold range of the energy storage motor (dividing three parameter ranges based on actual conditions and respectively representing primary danger, secondary danger and tertiary danger), and judging that the current of the energy storage motor is not dangerous at the moment (namely not in the fault threshold range), wherein the fault data of the energy storage current is 0;
After the spring elastic force data, the opening and closing speed data, the opening and closing coil current data and the energy storage motor current data are found to belong to the fault threshold range, inputting the original spring elastic force data, the opening and closing speed data, the opening and closing coil current data and the energy storage motor current data into a trained spring energy storage detection model to carry out secondary fault judgment of fault types, checking whether the fault belongs to single-equipment fault or multi-equipment concurrent fault according to the output fault types (the spring elastic force fault type, the opening and closing speed fault type, the opening and closing coil current fault type and the energy storage motor current fault type), and carrying out fault positioning according to the output result;
and then, calculating a fault emergency degree evaluation value by once judging the calculated spring elastic force fault data, the calculated opening and closing speed fault data, the calculated opening and closing coil current fault data and the calculated energy storage motor current fault data and combining the first weight, the second weight, the third weight and the fourth weight which are obtained through a hierarchical analysis method, so that whether the fault needs emergency treatment or not is judged according to the fault emergency degree evaluation value, and further, the work arrangement of maintenance personnel is determined.
Referring to fig. 2, fig. 2 is a schematic structural diagram of a spring energy storage detection system of a GIS circuit breaker according to an embodiment of the present invention, including: a data acquisition module 201, a data judgment module 202, a normal state judgment module 203 and a fault state judgment module 204;
the data acquisition module is used for acquiring the running state data of the spring mechanism of the GIS breaker;
the data judging module is used for carrying out primary fault judgment on the running state data according to a preset fault running state threshold range to obtain spring elastic force fault data, opening and closing speed fault data, opening and closing coil current fault data and energy storage motor current fault data;
the normal state judging module is used for outputting a judging result of the GIS breaker spring mechanism as a normal state result if the running state data is not in the fault running state threshold range;
the fault state judging module is used for carrying out secondary fault judgment according to the running state data if the running state data is in the fault running state threshold range, obtaining a spring elastic force fault type, a switching-on and switching-off speed fault type, a switching-on and switching-off coil current fault type and an energy storage motor current fault type, and outputting a judging result of the GIS breaker spring mechanism as a fault state result; wherein the fault state result comprises: spring elastic force fault data and spring elastic force fault type, opening and closing speed fault data and opening and closing speed fault type, opening and closing coil current fault data and opening and closing coil current fault type, and energy storage motor current fault data and energy storage motor current fault type.
The embodiment of the system item corresponds to the embodiment of the method item of the invention, and the spring energy storage detection method of the GIS breaker provided by any one of the embodiment of the method item of the invention can be realized.
According to the embodiment, the running state data of the spring mechanism of the GIS breaker is obtained; performing primary fault judgment on the running state data according to a preset fault running state threshold range; outputting a judging result of the GIS breaker spring mechanism as a normal state result if the running state data is not in the fault running state threshold range; and if the running state data is within the fault running state threshold range, performing secondary fault judgment according to the running state data, and outputting a judgment result of the GIS breaker spring mechanism as a fault state result. The invention can collect the operation state data of the spring mechanism of the GIS breaker, judge the operation state data, timely detect the operation fault of the spring mechanism of the GIS breaker, analyze the operation state data, firstly carry out primary fault judgment based on the threshold range of the fault operation state, thereby distinguishing the normal state of the spring mechanism of the GIS breaker, and carry out secondary fault judgment on the operation state data in the range of the fault operation state, thereby outputting the specific type of fault state.
Example two
Referring to fig. 4, fig. 4 is a schematic structural diagram of a terminal device according to an embodiment of the present invention.
A terminal device of this embodiment includes: a processor 401, a memory 402 and a computer program stored in the memory 402 and executable on the processor 401. The processor 401, when executing the computer program, implements the steps in the embodiments of the spring energy storage detection method of each GIS circuit breaker, for example, all the steps of the spring energy storage detection method of the GIS circuit breaker shown in fig. 1. Alternatively, the processor may implement functions of each module in the above-described device embodiments when executing the computer program, for example: all modules of the spring energy storage detection device of the GIS breaker shown in figure 2.
In addition, the embodiment of the invention also provides a computer readable storage medium, which comprises a stored computer program, wherein when the computer program runs, the equipment where the computer readable storage medium is located is controlled to execute the spring energy storage detection method of the GIS breaker.
It will be appreciated by those skilled in the art that the schematic diagram is merely an example of a terminal device and does not constitute a limitation of the terminal device, and may include more or less components than illustrated, or may combine certain components, or different components, e.g., the terminal device may further include an input-output device, a network access device, a bus, etc.
The processor 401 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, and the processor 401 is a control center of the terminal device, and connects various parts of the entire terminal device using various interfaces and lines.
The memory 402 may be used to store the computer program and/or module, and the processor 401 may implement various functions of the terminal device by running or executing the computer program and/or module stored in the memory and invoking data stored in the memory 402. The memory 402 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data (such as audio data, phonebook, etc.) created according to the use of the handset, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart Media Card (SMC), secure Digital (SD) Card, flash Card (Flash Card), at least one disk storage device, flash memory device, or other volatile solid-state storage device.
Wherein the terminal device integrated modules/units may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as stand alone products. Based on such understanding, the present invention may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth.
It should be noted that the above-described apparatus embodiments are merely illustrative, and the units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, in the drawings of the embodiment of the device provided by the invention, the connection relation between the modules represents that the modules have communication connection, and can be specifically implemented as one or more communication buses or signal lines. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
While the foregoing is directed to the preferred embodiments of the present invention, it will be appreciated by those skilled in the art that changes and modifications may be made without departing from the principles of the invention, such changes and modifications are also intended to be within the scope of the invention.
Claims (10)
1. The spring energy storage detection method of the GIS breaker is characterized by comprising the following steps of:
Acquiring running state data of a spring mechanism of the GIS breaker;
performing primary fault judgment on the running state data according to a preset fault running state threshold range to obtain spring elastic force fault data, opening and closing speed fault data, opening and closing coil current fault data and energy storage motor current fault data;
outputting a judging result of the GIS breaker spring mechanism as a normal state result if the running state data is not in the fault running state threshold range;
if the running state data is within the fault running state threshold value range, performing secondary fault judgment according to the running state data to obtain a spring elastic force fault type, a switching-on and switching-off speed fault type, a switching-on and switching-off coil current fault type and an energy storage motor current fault type, and outputting a judging result of the GIS breaker spring mechanism as a fault state result; wherein the fault state result comprises: spring elastic force fault data and spring elastic force fault type, opening and closing speed fault data and opening and closing speed fault type, opening and closing coil current fault data and opening and closing coil current fault type, and energy storage motor current fault data and energy storage motor current fault type.
2. The method for detecting spring stored energy of a GIS circuit breaker according to claim 1, wherein the operating state data comprises: spring force data, opening and closing speed data, opening and closing coil current data and energy storage motor current data; the fault operating state threshold range includes: spring elastic force fault threshold range, switching-on and switching-off speed fault threshold range, switching-on and switching-off coil current fault threshold range and energy storage motor current fault threshold range.
3. The method for detecting the spring energy storage of the GIS circuit breaker according to claim 2, wherein the performing a fault judgment on the operation state data according to a preset fault operation state threshold range includes:
judging spring elastic force data, opening and closing speed data, opening and closing coil current data and energy storage motor current data according to a preset spring elastic force fault threshold range, opening and closing speed fault threshold range, opening and closing coil current fault threshold range and energy storage motor current fault threshold range;
if the spring force data is not in the spring force fault threshold range, the opening and closing speed data is not in the opening and closing speed fault threshold range, the opening and closing coil current data is not in the opening and closing coil current fault threshold range and the energy storage motor current data is not in the energy storage motor current fault threshold range, judging that the GIS breaker spring mechanism is in a normal state;
And if the spring elastic force data is in the spring elastic force fault threshold range, or the opening and closing speed data is in the opening and closing speed fault threshold range, or the opening and closing coil current data is in the opening and closing coil current fault threshold range, or the energy storage motor current data is in the energy storage motor current fault threshold range, judging that the GIS breaker spring mechanism is in a fault state.
4. The method for detecting the spring energy storage of the GIS circuit breaker according to claim 2, wherein the performing the secondary fault judgment according to the operation state data, obtaining a spring elastic force fault type, a switching speed fault type, a switching coil current fault type and an energy storage motor current fault type, and outputting a judgment result of the GIS circuit breaker spring mechanism as a fault state result, includes:
inputting the running state data into a preset spring energy storage detection model, and performing secondary fault judgment to obtain a spring elastic force fault type, a switching-on and switching-off speed fault type, a switching-on and switching-off coil current fault type and an energy storage motor current fault type; the spring energy storage detection model is obtained by inputting a plurality of training samples marked with fault positions and fault types of the GIS breaker spring mechanism into a neural network for training;
And combining the spring elastic force fault type, the opening and closing speed fault type, the opening and closing coil current fault type and the energy storage motor current fault type, and obtaining spring elastic force fault data, opening and closing speed fault data, opening and closing coil current fault data and energy storage motor current fault data to obtain a fault state result of the GIS breaker spring mechanism.
5. The method for detecting the spring energy storage of the GIS breaker according to claim 4, wherein the training method of the spring energy storage detection model comprises the following steps:
acquiring historical operation data of a plurality of GIS breaker spring mechanisms;
sequencing each data point in the historical operation data according to a time sequence, and performing data supplementing operation on the historical operation data according to a preset time granularity through an interpolation method to obtain historical fault data; the data supplementing operation specifically comprises the following steps: performing missing identification operation on the time corresponding to each data point in the historical operation data according to a preset time granularity; if the time of the data point is lost, carrying out data supplementation by an interpolation method, and carrying out data supplementation operation on the next data point until all data point operations are executed after completing the data supplementation of the time-lost data point; if the time of the data point is not lost, directly carrying out data supplementing operation on the next data point until all data point operations are executed;
Determining a first reference data point and a second reference data point, and mapping the historical fault data on a first plane by taking the first reference data point as a center to obtain a first data sequence; mapping the historical fault data to a second plane by taking a second datum point as a center to obtain a second data sequence; determining data points with differences between the first data sequence and the second data sequence as data for marking fault positions and fault types, and obtaining training samples; wherein the training sample comprises: the device comprises a spring elastic force fault training sample, an opening and closing speed fault training sample, an opening and closing coil current fault training sample and an energy storage motor current fault training sample;
and inputting the spring elastic force fault training sample, the opening and closing speed fault training sample, the opening and closing coil current fault training sample and the energy storage motor current fault training sample into a neural network for training to obtain the spring energy storage detection model.
6. The method for detecting spring stored energy of a GIS circuit breaker according to any one of claims 1 to 5, further comprising, after the outputting of the determination result of the GIS circuit breaker spring mechanism as the failure state result:
According to a preset analytic hierarchy process, weight distribution is carried out on fault state results of the GIS breaker spring mechanism, and weighted calculation is carried out on the fault state results after the weight distribution, so that fault emergency degree evaluation values of the GIS breaker spring mechanism are obtained;
and determining maintenance processing time of the GIS breaker spring mechanism according to the fault emergency degree evaluation value, generating a maintenance processing instruction based on the maintenance processing time and the fault judgment result, and transmitting the maintenance processing instruction to a user side so that the user side reminds maintenance personnel to maintain the GIS breaker spring mechanism according to the maintenance processing instruction.
7. The method for detecting the spring energy storage of the GIS circuit breaker according to claim 6, wherein the step of performing weighted calculation on the fault state result after the weight is allocated to obtain the fault emergency degree evaluation value of the GIS circuit breaker spring mechanism comprises the following steps:
substituting spring elastic force fault data, opening and closing speed fault data, opening and closing coil current fault data and energy storage motor current fault data after weight distribution into a preset weighted summation formula, and calculating a fault emergency degree evaluation value of a GIS breaker spring mechanism; wherein the weighted summation formula is:
In the method, in the process of the invention,for failure emergency degree evaluation value, < >>For the first weight, ++>For the second weight, ++>For the third weight->For the fourth weight, ++>For spring force failure data, < >>For the switching speed fault data, < >>For switching on/off coil current fault data, +.>And the current fault data of the energy storage motor.
8. A spring energy storage detection system of a GIS circuit breaker, comprising: the system comprises a data acquisition module, a data judgment module, a normal state judgment module and a fault state judgment module;
the data acquisition module is used for acquiring the running state data of the spring mechanism of the GIS breaker;
the data judging module is used for carrying out primary fault judgment on the running state data according to a preset fault running state threshold range to obtain spring elastic force fault data, opening and closing speed fault data, opening and closing coil current fault data and energy storage motor current fault data;
the normal state judging module is used for outputting a judging result of the GIS breaker spring mechanism as a normal state result if the running state data is not in the fault running state threshold range;
the fault state judging module is used for carrying out secondary fault judgment according to the running state data if the running state data is in the fault running state threshold range, obtaining a spring elastic force fault type, a switching-on and switching-off speed fault type, a switching-on and switching-off coil current fault type and an energy storage motor current fault type, and outputting a judging result of the GIS breaker spring mechanism as a fault state result; wherein the fault state result comprises: spring elastic force fault data and spring elastic force fault type, opening and closing speed fault data and opening and closing speed fault type, opening and closing coil current fault data and opening and closing coil current fault type, and energy storage motor current fault data and energy storage motor current fault type.
9. A computer terminal device, characterized by comprising a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, the processor implementing a spring energy storage detection method of a GIS circuit breaker according to any one of claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored computer program, wherein the computer program when run controls a device in which the computer readable storage medium is located to perform a method for detecting the spring energy storage of a GIS circuit breaker according to any one of claims 1 to 7.
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