CN109872077B - Method and device for evaluating state of cooling water system of double-water internal cooling synchronous phase modifier - Google Patents
Method and device for evaluating state of cooling water system of double-water internal cooling synchronous phase modifier Download PDFInfo
- Publication number
- CN109872077B CN109872077B CN201910178117.1A CN201910178117A CN109872077B CN 109872077 B CN109872077 B CN 109872077B CN 201910178117 A CN201910178117 A CN 201910178117A CN 109872077 B CN109872077 B CN 109872077B
- Authority
- CN
- China
- Prior art keywords
- evaluation
- cooling water
- index
- water system
- cloud
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 239000000498 cooling water Substances 0.000 title claims abstract description 88
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 72
- 230000001360 synchronised effect Effects 0.000 title claims abstract description 47
- 238000000034 method Methods 0.000 title claims abstract description 29
- 238000001816 cooling Methods 0.000 title claims abstract description 26
- 239000003607 modifier Substances 0.000 title claims abstract description 18
- 238000011156 evaluation Methods 0.000 claims abstract description 125
- 230000036541 health Effects 0.000 claims abstract description 63
- 230000006866 deterioration Effects 0.000 claims description 21
- 230000015556 catabolic process Effects 0.000 claims description 11
- 238000006731 degradation reaction Methods 0.000 claims description 11
- 238000007781 pre-processing Methods 0.000 claims description 10
- 230000004927 fusion Effects 0.000 claims description 7
- 239000003513 alkali Substances 0.000 claims description 4
- 238000012544 monitoring process Methods 0.000 claims description 4
- 238000013139 quantization Methods 0.000 claims description 4
- 230000008859 change Effects 0.000 claims description 3
- 230000005494 condensation Effects 0.000 claims description 3
- 238000009833 condensation Methods 0.000 claims description 3
- 238000012854 evaluation process Methods 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 2
- 230000003862 health status Effects 0.000 claims 1
- 238000002474 experimental method Methods 0.000 description 6
- 238000012423 maintenance Methods 0.000 description 6
- 230000005540 biological transmission Effects 0.000 description 4
- 230000003449 preventive effect Effects 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 description 2
- 230000009471 action Effects 0.000 description 2
- 238000004804 winding Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 229910052802 copper Inorganic materials 0.000 description 1
- 239000010949 copper Substances 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 229910052760 oxygen Inorganic materials 0.000 description 1
- 239000001301 oxygen Substances 0.000 description 1
- 230000002035 prolonged effect Effects 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 238000005496 tempering Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Images
Landscapes
- Tests Of Circuit Breakers, Generators, And Electric Motors (AREA)
Abstract
The invention provides a state evaluation method and a device for a double-water-internal-cooling synchronous phase modifier cooling water system, which solve the problem of real-time evaluation of the health state of a stator cooling water system and a rotor cooling water system of a double-water-internal-cooling synchronous motor. The method adopts an entropy weight method to determine the dynamic weight of each index in real time, determines the similarity between the cloud to be evaluated and each standard cloud based on the similar cloud, and determines the health state of the cooling water system by adopting a maximum similarity principle. The invention can reflect the real health state of the stator cooling water system and the rotor cooling water system of the double-water internal cooling synchronous motor, and can realize the online state evaluation of the cooling water system.
Description
Technical Field
The invention relates to the field of synchronous motor index evaluation, operation maintenance and repair, in particular to a state evaluation method and device for a double-water-cooled synchronous motor.
Background
In recent years, with continuous planning and production of extra-high voltage direct current transmission projects, a converter needs to consume a large amount of reactive power in the transmission process. If the power grid fails, reactive power to be absorbed is greatly increased in the process of rapid dynamic adjustment; when the voltage of the power grid is too high, reactive power needs to be released so as to meet the requirement of the power grid on the voltage stability. It can be seen that the lack or excess of reactive power will cause instability of ac voltage, and in severe cases, the safe and stable operation of the whole ac and dc system may be endangered. The synchronous phase modulator is easy to adjust, and can emit reactive power and absorb the reactive power, so that the synchronous phase modulator is applied to extra-high voltage alternating current and direct current transmission projects.
In view of the small number of synchronous phase modulators of the new generation, the short running time, and the complex and variable running environment and the load, the reliability needs to be checked in time. Therefore, in order to ensure the efficient operation and safe and stable operation of a large phase modulation unit in an extra-high voltage alternating current and direct current transmission project, the health state of the phase modulation unit needs to be correctly evaluated, so that the maintenance and overhaul are reasonably arranged, and the service life of the phase modulation unit is prolonged.
The novel high-capacity synchronous phase modulator is complex in structure, and is used for timely emitting heat generated when the motor runs, controlling the temperature rise of the motor and ensuring the normal running of a cooling system of the motor. The double-water internal cooling mode is one of the important cooling modes of the novel high-capacity synchronous phase modifier, and the performance of a cooling water system which is used as an important auxiliary system of the double-water internal cooling synchronous motor directly influences the economical efficiency and the reliability of the operation of the motor. Due to the important position of the cooling water cooling system in the safe and stable operation of the synchronous motor, the health state of the cooling water system needs to be accurately evaluated, and the hidden trouble of the cooling water system needs to be discovered and eliminated in time.
The novel large-capacity synchronous phase modulator is provided with a large number of sensors, can monitor some important physical quantities in time, but how to utilize the monitored quantities to make correct evaluation on the health state of a cooling water system of a camera is not reported at present. The reliability of synchronous motors is usually determined by preventive experiments before commissioning and during certain operating periods if the motor needs to be maintained.
The preventive experiment of the synchronous motor cooling water system is usually a water cut-off experiment and a hollow lead through-flow experiment, and the daily maintenance and the running state analysis of the water system are also insufficient: preventive experiments generally have long time intervals and are difficult to guide routine maintenance; the health state evaluation of the whole water system of the synchronous motor by a preventive experiment is not comprehensive enough, and the hidden trouble is difficult to find in time.
Disclosure of Invention
At present, no evaluation method for a cooling water system of a synchronous phase modifier exists. The method can provide a specific fault subsystem when a system has slight faults and faults, and is convenient for searching fault parts and implementing maintenance. Meanwhile, the method can evaluate the online state of the system.
Specifically, the invention provides a state evaluation method of a double-water internal cooling synchronous phase modifier cooling water system, which is characterized by comprising the following steps of:
s1: establishing a state evaluation index system of a double-water internal cooling synchronous phase modifier cooling water system;
s2: grading the health state of the cooling water system;
s3, preprocessing the evaluation index;
s4: and evaluating the health state of the cooling water system.
Further, step S1 specifically includes:
s11: dividing a stator cooling water system and a rotor cooling water system into a plurality of subsystems respectively;
s12: and establishing an evaluation index system aiming at each subsystem, selecting physical quantity capable of reflecting the running state of the subsystem, and combining the sensor installed on the synchronous phase modulator to establish the evaluation index system.
Further, the air conditioner is provided with a fan,
the subsystem of the stator cooling water system comprises a stator hollow strand, a water tank, a water pump, a heat exchanger, a water filter, an ion exchanger and an alkali adding device; the subsystem of the rotor cooling water system comprises a rotor hollow lead, a water tank, a water pump, a heat exchanger and a water filter.
Further, in step S2, according to the characteristics of the cooling water system in the motor and the operation experience of the synchronous generator, the health condition of the cooling water system is divided into four levels, which are: good, normal, early warning, failure.
Wherein step S3 includes:
s31, selecting three-phase load symmetry of the synchronous phase modulator, and evaluating the health state of the cooling water system;
s32: the evaluation index is subjected to quantitative tempering, the dimensionless index is represented by a deterioration degree, and the smaller the value of the deterioration degree, the better the performance of the corresponding health state is represented.
In step S32, the evaluation indexes are classified into two types, an upper and lower interval type and an upper limit value type, according to the data characteristics of the evaluation indexes, and different methods are used to perform de-dimensionalization on different types of indexes; wherein the upper and lower interval type means: when the index value is in a certain interval, the indexes are normal; when the upper limit and the lower limit are exceeded, a fault is indicated; the upper limit value type index means that the index value cannot exceed a certain value, otherwise, the shutdown processing should be performed.
Further, the deterioration degree of the upper and lower section type index is:
wherein g (x) is the degree of deterioration, x is a quantization index, and xmax、xminThe upper limit value and the lower limit value of the index are respectively, and alpha-beta is the range of the allowable value of the index.
Further, as for the upper limit value type index, the deterioration degree thereof is
Wherein g (x) is deterioration degree, x is quantization index, delta is allowable value of normal operationmaxIs the upper limit of the indicator.
Further, if the degradation degree g is 1, it is determined that the state at this time is a failure state, and the evaluation process is ended.
Further, if g ≠ 1, it proceeds to step S4.
Further, step S4 specifically includes:
s41: establishing standard clouds with four health levels;
s42: calculating the weight of each evaluation index;
s43: in a time period to be evaluated, utilizing monitoring data of each evaluation index of the cooling water system to calculate the digital characteristics of a cloud model of the cooling water system in the time period;
s44: the similarity between the cloud to be evaluated and the standard cloud is solved;
s45: the evaluation results are given.
Further, in step S41, the normal cloud is composed of a large number of cloud droplets, and its model characteristics are represented by three parameters (Ex, En, He); wherein Ex is an expected value of a normal cloud, represents a central value of cloud droplets in spatial distribution, and represents a digital feature of a certain concept; en is entropy, represents the uncertainty of qualitative concept, is determined by randomness and ambiguity of the concept together, the smaller En, the higher the concentration degree of the concept, the more reliable the observation result; he is super-entropy and represents uncertainty of entropy, and the smaller the He is, the higher the condensation degree of cloud droplets is, and the smaller the influence of external factors on uncertainty of observation errors is.
Further, step S42 specifically includes:
determining the real-time weight of each index by using the information entropy, and considering the influence of the running state change on the health degree of the cooling water system; the method comprises the following specific steps:
firstly, defining the entropy value of each evaluation index according to the information entropy theory as follows:
in the formula: n is the number of samples of each index, m is the number of evaluation indexes, gijThe deterioration degree of the ith evaluation index in j samples; in consideration of the case where the degree of degradation is zero, 0ln0 is defined as 0;
the weight expression of each evaluation index is:
in the formula, wiIs the weight of each evaluation index,
further, step S43 includes:
firstly, carrying out data fusion on the degradation degree of each evaluation index by adopting weight, and then solving the digital characteristics C (Ex, En, He) of the cloud model in the state to be evaluated by utilizing the fused data; the method comprises the following specific steps:
the first step is as follows: solving the fusion value of the evaluation indexes in each group of samples by using the weight;
the second step is that: and solving the digital characteristics of the cloud to be evaluated by using the fused degradation degree: expected value Ex, entropy En, sample variance S2And super entropy He;
further, step S44 includes:
the similarity between the cloud C (Ex, En, He) to be evaluated and the standard cloud Cj (Exj, Enj, Hej) is calculated by the following method:
the first step is as follows: generating M normal random numbers of cloud to be evaluated
En′＝NORM(En,He2) And xi＝NORM(Ex,En′2)(i＝1,……,M)
The second step is that: calculating xiDegree of membership in a standard cloud Cj (Exj, Enj, Hej)
The third step: similarity between the cloud to be evaluated and the standard cloud under each health state is calculated
Further, the corresponding state with the maximum similarity is taken as the final evaluation result.
The invention also provides a device for realizing the method, which comprises the following steps:
a state evaluation index system building module is used for building a state evaluation index system of the cooling water system of the double-water internal cooling synchronous phase modifier;
the health state grade division module is used for dividing the health condition of the water cooling system into different grades;
the state evaluation index preprocessing module is used for preprocessing the evaluation index;
the health state evaluation module is used for evaluating the health state of the water cooling system in a period to be evaluated;
and the evaluation result giving module is used for giving the health state of the water cooling system in the time period to be evaluated.
Compared with the prior art, the invention has the following beneficial technical effects:
the method can avoid the subjectivity of evaluation, ensure the objectivity of the evaluation result, accurately reflect the health state of the synchronous motor cooling water system, and provide a specific fault subsystem when the system has slight fault or serious fault, so that the fault part can be conveniently searched and maintained. Meanwhile, the method can realize online state evaluation and lay a foundation for state maintenance.
Drawings
Fig. 1 is a structural view of a cooling water system of a synchronous condenser of the present invention.
Fig. 2 shows a standard cloud of four health states established by the present invention.
Fig. 3 shows an evaluation flow chart of the cooling water system according to the present invention.
Fig. 4 shows an evaluation cloud of the stator cooling water system of the present invention.
Fig. 5 shows a block diagram of an apparatus for implementing the evaluation method of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the drawings of the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the described embodiments of the invention, are within the scope of the invention.
The state evaluation method of the double-water internal cooling synchronous phase modifier cooling water system is as follows.
1. State evaluation index system for establishing double-water internal cooling synchronous phase modifier cooling water system
1.1 dividing the stator cooling water system and the rotor cooling water system into a plurality of subsystems respectively
Fig. 1 shows a structural diagram of a stator cooling water system and a rotor cooling water system of a synchronous condenser.
As shown in fig. 1, the stator cooling water system is a closed self-circulation system. The cooling water in the stator water tank is pushed by the water pump to enter the heat exchanger, then flows into the stator coil and the outgoing line of the synchronous motor through the water filter, the water cut-off protection device and the like, takes away the heat generated by the stator winding, and flows back to the stator water tank to complete a water circulation. In order to ensure the quality of the stator cooling water, bypass cooling water is adopted for control. And one part of the cooling water after passing through the water filter enters the ion exchanger and the alkali adding device and then returns to the stator water tank, so that the conductivity and the pH value of the cooling water are controlled, and the corrosion of the cooling water on the copper wire is avoided.
The rotor cooling water system is an open self-circulation system. The cooling water in the rotor water tank is pushed by a water pump to enter a heat exchanger, a water filter, a water break protection device and the like, flows into a central hole of a wire outlet end to enter a rotor water inlet chamber, then flows into a hollow lead in a rotor bar through an insulating water conduit under the action of centrifugal force, flows out from the other end (non-wire outlet end) of a coil through the insulating water conduit, takes away heat generated by a rotor winding, is thrown into a water collecting tank, and finally returns to the rotor water tank under the action of gravity.
According to the structure of the stator cooling water system and the rotor cooling water system, the stator cooling water system and the rotor cooling water system are divided into a plurality of subsystems respectively. The subsystem of the stator cooling water system comprises a stator hollow strand, a water tank, a water pump, a heat exchanger, a water filter, an ion exchanger and an alkali adding device. The subsystem of the rotor cooling water system comprises a rotor hollow lead, a water tank, a water pump, a heat exchanger and a water filter.
1.2, establishing an evaluation index system for each subsystem, selecting physical quantities capable of reflecting the running state of the subsystem, and combining the installed sensors of the synchronous phase modulator to establish the evaluation index systems as shown in tables 1 and 2.
TABLE 1 evaluation index system for stator cooling water system
TABLE 2 evaluation index system for rotor cooling water system
2. Status ranking
The health condition of the synchronous phase modulator is a gradual fuzzy process and is difficult to quantitatively express, so that the health condition of the synchronous phase modulator is described by adopting a qualitative method. According to the characteristics of the cold water system in the motor and the operation experience of the synchronous generator, a four-level evaluation mechanism is adopted to divide the health state of the synchronous phase modifier, and the health state of the cold water system in the synchronous phase modifier is divided into four levels, which are respectively: good, normal, early warning, failure. The health condition corresponding to each grade is shown in table 3.
TABLE 3 meanings of different health states
3. Preprocessing the evaluation index
3.1 selection of evaluation index data.
If the health evaluation is only carried out on the cooling water system, in order to simplify the evaluation process, the operating data of the synchronous phase modulator under the condition that the three-phase load is symmetrical, namely the three-phase current and the three-phase voltage are respectively symmetrical can be selected to evaluate the health state of the cooling water system.
3.2 Dedimensionalization of evaluation index
Because the structure of the internal cooling water is complex, the evaluation indexes have more dimensions and larger numerical difference, and for the convenience of evaluation, the evaluation indexes in different numerical ranges are subjected to dimensionless transformation and converted into the same numerical range, and usually the interval of [0,1] is taken. According to the data characteristics of the evaluation indexes, the evaluation indexes are divided into two types: upper and lower interval types and upper limit type. And for different types of indexes, adopting different methods to perform de-dimensionalization. The dimensionless index is represented by a deterioration degree, and the smaller the value of the deterioration degree, the better the performance corresponding to the state of health.
(1) Upper and lower interval type index
For the upper and lower interval type indexes, when the index value is in a certain interval, the indexes are normal. When the upper and lower limits are exceeded, a fault is declared. Among such indicators are: the water inlet and outlet temperature, the water inlet and outlet pressure difference, the water surface liquid level of the water tank, the outlet pressure, the voltage, the current and the power of the water pump, the pH value of cooling water, the conductivity and the flow of water and the like of the stator and rotor coils. The deterioration degree is calculated by
xmax、xminThe upper limit value and the lower limit value of the index are respectively, and alpha-beta is the range of the allowable value of the index.
(2) Upper limit type index
For the upper limit type index, it is required that the value thereof does not exceed a certain value, otherwise, the shutdown process should be performed. For example, the outlet water temperature difference, the dissolved oxygen amount of water, the copper content of water, the hardness of water and the like of the stator same-layer wire rod are required to be lower than a certain limit value, and the lower the numerical value is, the better the numerical value is. Has a degree of deterioration of
Delta is an allowable value for normal operation, xmaxIs the upper limit of the indicator.
4. Health state evaluation method
Because the health state of the equipment is a fuzzy and qualitative concept, and the cloud model better describes the fuzziness and randomness of things, the qualitative concept of the health state is quantified through normal cloud in order to describe the health state of the cold water system in the phase modulator. Firstly, quantifying four health grades of a cooling water system into a certain numerical value in normal cloud distribution; then according to the time interval to be evaluated and the monitoring data of each index of the cooling water system, the cloud digital characteristic and the cloud model of the cooling water system in the time interval are worked out; and finally, comparing the cloud to be evaluated with the standard clouds with the four health grades, and taking the grade with the maximum closeness as a final evaluation result.
4.1 establishing Standard clouds of four health classes
A normal cloud is composed of a large number of cloud droplets, and its model characteristics are represented by three parameters (Ex, En, He). Wherein Ex is an expected value of a normal cloud, represents a central value of cloud droplets in spatial distribution, and represents a digital feature of a certain concept; en is entropy, represents the uncertainty of qualitative concept, is determined by randomness and ambiguity of the concept together, the smaller En, the higher the concentration degree of the concept, the more reliable the observation result; he is super-entropy and represents uncertainty of entropy, and the smaller the He is, the higher the condensation degree of cloud droplets is, and the smaller the influence of external factors on uncertainty of observation errors is. The numerical characteristics of the four health class standard clouds expressed in degrees of deterioration are shown in table 4. Fig. 2 shows a standard cloud of four health conditions.
Table 4 digital signatures of standard clouds corresponding to health states
| Health grade | Good/ |
Normal/c 2 | Pre-alarm/c 3 | Fault/c 4 |
| Expected |
0 | 0.33 | 0.66 | 1 |
| Entropy En | 0.1 | 0.1 | 0.1 | 0.1 |
| Super entropy He | 0.01 | 0.01 | 0.01 | 0.01 |
4.2 weighting each evaluation index
Since the sensitivity of each evaluation index to the evaluation result is different, the effect of each evaluation index on the evaluation of the state is also different, and the degree of influence of each evaluation index on the evaluation result is represented by a weight. In order to avoid the interference of artificial subjective factors and ensure the objectivity of an evaluation result, the real-time weight of each index is determined by using the information entropy, and the influence of the change of the running state on the health degree of the cooling water system is considered.
Firstly, defining the entropy value of each evaluation index according to the information entropy theory as follows:
in formula (3): n is the number of samples of each index, m is the number of evaluation indexes, gijThe deterioration degree of the i-th evaluation index in j samples. In consideration of the case where the degree of degradation is zero, 0ln0 is defined as 0.
The weight expression of each evaluation index is:
in the formula, wiIs the weight of each evaluation index,
4.3 solving the digital characteristics of the cloud model in the period to be evaluated
Firstly, data fusion is carried out on the degradation degree of each evaluation index by adopting the weight, and then the digital characteristics C (Ex, En, He) of the cloud model in the state to be evaluated are obtained by utilizing the fused data. The method comprises the following specific steps:
the first step is as follows: solving the fusion value of the evaluation indexes in each group of samples by using the weight;
the second step is that: and solving the digital characteristics of the cloud to be evaluated by using the fused degradation degree: expected value Ex, entropy En, sample variance S2And super entropy He;
4.4 similarity between the cloud to be evaluated and the standard cloud is obtained
The similarity between the cloud C (Ex, En, He) to be evaluated and the standard cloud Cj (Exj, Enj, Hej) is calculated by the following method:
the first step is as follows: m normal random numbers E for generating cloud to be evaluatedn′＝NORM(En,He2) And xi＝NORM(Ex,En′2)(i＝1,……,M)
The second step is that: calculating xiDegree of membership in a standard cloud Cj (Exj, Enj, Hej)
The third step: similarity between the cloud to be evaluated and the standard cloud under each health state is calculated
4) Giving the evaluation results
And taking the corresponding state with the maximum similarity as a final evaluation result.
Fig. 5 shows a block diagram of an apparatus for implementing the evaluation method of the present invention.
As shown in fig. 5, the apparatus includes the following parts: the system comprises a state evaluation index system building module, a health state grade dividing module, a state evaluation index preprocessing module, a health state evaluation module and an evaluation result giving module.
The functions of the modules are as follows:
a state evaluation index system building module is used for building a state evaluation index system of the cooling water system of the double-water internal cooling synchronous phase modifier;
the health state grade division module is used for dividing the health condition of the water cooling system into different grades;
the state evaluation index preprocessing module is used for preprocessing the evaluation index;
the health state evaluation module is used for evaluating the health state of the water cooling system in a period to be evaluated;
and the evaluation result giving module is used for giving the health state of the water cooling system in the time period to be evaluated.
The implementation process and the evaluation effect of the evaluation method are described below by taking a stator cooling water system of a 300Mvar synchronous phase modifier of a certain converter station as an example.
Firstly, collecting the operation data of the indexes, selecting the operation data when the three-phase voltage and the three-phase current of the phase modulator are symmetrical as the source data of state evaluation, and then evaluating according to the flow shown in fig. 3. According to the monitoring data, an expected value Ex, an entropy value En and a super entropy He of the cloud to be evaluated are calculated, the obtained cloud c to be evaluated is shown in fig. 4, the cloud to be evaluated is compared with each standard cloud, and the similarity between the cloud to be evaluated and each standard cloud obtained through calculation is shown in table 5. As can be seen from table 5, the stator cooling water system of the phase modulator was in a normal state, which is consistent with the actual situation.
TABLE 5 similarity of the cloud to be evaluated to the respective standard clouds
| Good/ |
Normal/c 2 | Pre-alarm/c 3 | Fault/c 4 | Evaluation results |
| 0.2498 | 0.4330 | 0.0172 | 6.1349e-06 | Is normal |
While the best mode for carrying out the invention has been described in detail and illustrated in the accompanying drawings, it is to be understood that the same is by way of illustration and example only and is not to be taken by way of limitation, the scope of the invention should be determined by the appended claims and any changes or modifications which fall within the true spirit and scope of the invention should be construed as broadly described herein.
Claims (9)
1. A state evaluation method for a double-water internal cooling synchronous phase modifier cooling water system is characterized by comprising the following steps:
s1: the state evaluation index system for establishing the cooling water system of the double-water internal cooling synchronous phase modifier comprises the following steps:
s11: the method comprises the following steps of dividing a stator cooling water system and a rotor cooling water system into a plurality of subsystems respectively, wherein the subsystems of the stator cooling water system comprise stator hollow strands, a water tank, a water pump, a heat exchanger, a water filter, an ion exchanger and an alkali adding device; the subsystem of the rotor cooling water system comprises a rotor hollow lead, a water tank, a water pump, a heat exchanger and a water filter;
s12: establishing an evaluation index system for each subsystem, selecting physical quantity capable of reflecting the running state of the subsystem, and establishing the evaluation index system by combining with a sensor installed on a synchronous phase modulator;
s2: grading the health state of the cooling water system;
s3, preprocessing the evaluation index, including:
s31, selecting three-phase load symmetry of the synchronous phase modulator, and evaluating the health state of the cooling water system;
s32: de-dimensionalizing the evaluation index, and expressing the dimensionless index by using a deterioration degree, wherein the smaller the numerical value of the deterioration degree is, the better the performance of the corresponding health state is expressed;
s4: evaluating the health status of the cooling water system, comprising:
s41: establishing standard clouds with four health levels;
s42: calculating the weight of each evaluation index;
s43: in a time period to be evaluated, the monitoring data of each evaluation index of the cooling water system is utilized to calculate the cloud model and the digital characteristics of the cooling water system in the time period, and the method comprises the following steps:
firstly, carrying out data fusion on the degradation degree of each evaluation index by adopting weight, and then solving the digital characteristics C (Ex, En and He) of a cloud model in a state to be evaluated by utilizing the fused data, wherein a normal cloud is formed by a large number of cloud droplets, and the model characteristics are represented by three parameters Ex, En and He; wherein Ex is an expected value of a normal cloud, represents a central value of cloud droplets in spatial distribution, and represents a digital feature of a certain concept; en is entropy, represents the uncertainty of qualitative concept, is determined by randomness and ambiguity of the concept together, the smaller En, the higher the concentration degree of the concept, the more reliable the observation result; he is super-entropy and represents uncertainty of entropy, and the smaller the He is, the higher the condensation degree of cloud droplets is, and the smaller the influence of external factors on the uncertainty of observation errors is represented; the method comprises the following specific steps:
the first step is as follows: solving the fusion value of the evaluation indexes in each group of samples by using the weight;
wherein, gijThe deterioration degree of the ith evaluation index in j samples; w is aiIs the weight of each evaluation index,
m is the number of evaluation indexes;
the second step is that: and solving the digital characteristics of the cloud to be evaluated by using the fused degradation degree: expected value Ex, entropy En, sample variance S2And super entropy He;
wherein N is the number of samples of each index, gjCalculating a fusion value for the first step;
s44: the similarity between the cloud to be evaluated and the standard cloud is solved; the method comprises the following steps:
the similarity between the cloud C (Ex, En, He) to be evaluated and the standard cloud Cj (Exj, Enj, Hej) is calculated by the following method, wherein Exj, Enj, Hej respectively represent the expected value, entropy and super entropy of the jth standard cloud:
the first step is as follows: generating M normal random numbers of cloud to be evaluated
En′＝NORM(En，He2) And xi＝NORM(Ex，En′2)i＝1,……,M
The second step is that: calculating a normal random number xiDegree of membership in a standard cloud Cj (Exj, Enj, Hej)
The third step: similarity between the cloud to be evaluated and the standard cloud under each health state is calculated
S45: and giving an evaluation result, and taking the corresponding state with the maximum similarity as a final evaluation result.
2. The evaluation method according to claim 1,
in step S2, according to the characteristics of the cooling water system in the motor and the operation experience of the synchronous generator, the health condition of the cooling water system is divided into four levels, which are: good, normal, early warning, failure.
3. The evaluation method according to claim 1, wherein in step S32, the evaluation index is classified into two types, an upper and lower interval type and an upper limit value type, according to the data characteristics of the evaluation index, and de-dimensionalization is performed by different methods for different types of indexes; wherein the upper and lower interval type means: when the index value is in a certain interval, the indexes are normal; when the upper limit and the lower limit are exceeded, a fault is indicated; the upper limit value type index means that the index value cannot exceed a certain value, otherwise, the shutdown processing should be performed.
4. The evaluation method according to claim 3, wherein the deterioration degree of the upper and lower interval type index is:
wherein g (x) is the degree of deterioration, x is a quantization index, and xmax、xminThe upper limit value and the lower limit value of the index are respectively, and alpha-beta is the range of the allowable value of the index.
5. The evaluation method according to claim 3, wherein the degree of deterioration of the upper limit type index is
Wherein g (x) is deterioration degree, x is quantization index, delta is allowable value of normal operationmaxIs an indexUpper limit value of (d).
6. The evaluation method according to claim 4 or 5, wherein if the degree of degradation g is 1, it is determined that the state at that time is a failure state, and the evaluation process is ended.
7. The evaluation method according to claim 4 or 5, wherein if g ≠ 1, then it proceeds to step S4.
8. The evaluation method according to claim 1, wherein step S42 specifically includes:
determining the real-time weight of each index by using the information entropy, and considering the influence of the running state change on the health degree of the cooling water system; the method comprises the following specific steps:
firstly, defining the entropy value of each evaluation index according to the information entropy theory as follows:
in the formula: n is the number of samples of each index, m is the number of evaluation indexes, gijThe deterioration degree of the ith evaluation index in j samples; in consideration of the case where the degree of degradation is zero, 0ln0 is defined as 0;
the weight expression of each evaluation index is:
in the formula, wiIs the weight of each evaluation index,
9. a state evaluation device of a double-water internal-cooling synchronous phase modifier cooling water system for realizing the method according to any one of claims 1 to 8, comprising:
a state evaluation index system building module is used for building a state evaluation index system of the cooling water system of the double-water internal cooling synchronous phase modifier;
the health state grading module is used for grading the health state of the cooling water system into different grades;
the state evaluation index preprocessing module is used for preprocessing the evaluation index;
the health state evaluation module is used for evaluating the health state of the cooling water system in the time period to be evaluated;
and the evaluation result giving module is used for giving the health state of the cooling water system in the time period to be evaluated.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910178117.1A CN109872077B (en) | 2019-03-08 | 2019-03-08 | Method and device for evaluating state of cooling water system of double-water internal cooling synchronous phase modifier |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910178117.1A CN109872077B (en) | 2019-03-08 | 2019-03-08 | Method and device for evaluating state of cooling water system of double-water internal cooling synchronous phase modifier |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109872077A CN109872077A (en) | 2019-06-11 |
| CN109872077B true CN109872077B (en) | 2021-10-08 |
Family
ID=66920111
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910178117.1A Active CN109872077B (en) | 2019-03-08 | 2019-03-08 | Method and device for evaluating state of cooling water system of double-water internal cooling synchronous phase modifier |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109872077B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110428151A (en) * | 2019-07-18 | 2019-11-08 | 国网山东省电力公司电力科学研究院 | A kind of method for evaluating state of synchronous capacitor oil system |
| CN110932490B (en) * | 2019-11-22 | 2021-10-15 | 上海电气电站设备有限公司 | Method for calculating forced excitation temperature of rotor of double-water internal cooling non-salient pole synchronous motor |
| CN113128832A (en) * | 2021-03-16 | 2021-07-16 | 国网湖南省电力有限公司 | Operation state online diagnosis method and system for auxiliary system of large phase modulator |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101858312A (en) * | 2010-05-31 | 2010-10-13 | 重庆大学 | System and method thereof for evaluating real-time running state of wind generating set |
| CN104331532A (en) * | 2014-09-12 | 2015-02-04 | 广东电网公司江门供电局 | Power transformer state evaluation method based on rough set-cloud model |
| WO2018195251A1 (en) * | 2017-04-20 | 2018-10-25 | Schneider Electric USA, Inc. | Systems and methods for managing building signature intelligent electronic devices |
-
2019
- 2019-03-08 CN CN201910178117.1A patent/CN109872077B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101858312A (en) * | 2010-05-31 | 2010-10-13 | 重庆大学 | System and method thereof for evaluating real-time running state of wind generating set |
| CN104331532A (en) * | 2014-09-12 | 2015-02-04 | 广东电网公司江门供电局 | Power transformer state evaluation method based on rough set-cloud model |
| WO2018195251A1 (en) * | 2017-04-20 | 2018-10-25 | Schneider Electric USA, Inc. | Systems and methods for managing building signature intelligent electronic devices |
Non-Patent Citations (2)
| Title |
|---|
| 基于大数据分析的风电机组运行状态评估方法研究;江顺辉;《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》;20170215(第02期);第C042-1242页 * |
| 改进熵权－正态云模型在边坡稳定性评价中的应用;赵军，宋扬;《水电能源科学》;20160430;第34卷(第4期);第120-122,165页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109872077A (en) | 2019-06-11 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109872077B (en) | Method and device for evaluating state of cooling water system of double-water internal cooling synchronous phase modifier | |
| CN107701468B (en) | A kind of online integrated monitoring of mixed-flow pump and device | |
| CN107482692B (en) | Active control method, device and system for wind power plant | |
| CN110428168A (en) | It is a kind of meter and energy storage multiple-energy-source distribution system coordinated scheduling integrated evaluating method | |
| CN109447441B (en) | Transient stability risk assessment method considering uncertainty of new energy unit | |
| CN111327070B (en) | Wind farm energy management method and system | |
| CN109188227A (en) | Double-fed wind driven generator insulation state evaluation method and system | |
| CN112179655A (en) | Turbo generator fault early warning method based on threshold classification | |
| CN108347352A (en) | The diagnostic method of information system and equipment performance in a kind of electric system | |
| CN110674120A (en) | Wind power plant data cleaning method and device | |
| CN112070353B (en) | Method and system for accurately detecting energy efficiency of data center | |
| CN112990627B (en) | Power quality evaluation method | |
| CN111652479A (en) | Data driving method for dynamic security assessment of power system | |
| CN113128005B (en) | Power grid node clustering and frequency safety analysis method and system based on dynamic characteristics | |
| CN117175695B (en) | Photovoltaic micro-grid power generation method and system based on diesel generator set | |
| Zhu et al. | Rapid quantification of demand response potential of building HAVC system via data-driven model | |
| CN116771610A (en) | Method for adjusting fault evaluation value of variable pitch system of wind turbine | |
| CN108493991A (en) | A kind of Wind turbines power distribution computational methods based on Wind turbines health degree | |
| CN114169718A (en) | Method for improving reliability of wind turbine generator based on state evaluation of wind turbine generator | |
| Botsaris et al. | Systemic assessment and analysis of factors affect the reliability of a wind turbine | |
| CN114662809A (en) | Method and system for evaluating electric energy quality of power supply in comprehensive energy park | |
| CN113128832A (en) | Operation state online diagnosis method and system for auxiliary system of large phase modulator | |
| CN106887848A (en) | Voltage power-less real-time control method based on Fuzzy Pattern Recognition | |
| CN111219287A (en) | Remote service life evaluating system for hydroelectric generating set | |
| CN112907025A (en) | Pump station machine pump health comprehensive evaluation method based on fuzzy hierarchy method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |