CN112257984A - State monitoring method based on health degree evaluation of power equipment - Google Patents
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Abstract
The invention provides a state monitoring method based on health degree evaluation of electric power equipment. The method comprises the following steps: obtaining a scoring configuration P of each functional position type of the power equipment standing book example, and obtaining a state monitoring condition Q of each equipment in each system of the unit set; calculating to obtain the health degree F of each system of the unit set; acquiring a comprehensive value Z of the health degree of unit set equipment; when the comprehensive value Z of the health degree of the unit set equipment or the system health degree F is lower than the threshold value delta1When the system health degree F continuously decreases for times which are accumulated to exceed delta2The degree of system health F once decreases by more than delta3And if not, the monitoring is continuously executed according to the equipment health degree evaluation and refresh frequency, so that the continuous monitoring of the health degree of the power equipment is realized. The invention relates to quantitative analysis of the status monitoring status of power equipmentTechnical methods are provided.
Description
Technical Field
The invention relates to the technical field of electrical equipment, in particular to a state monitoring method based on health degree evaluation of electrical equipment.
Background
The state monitoring data analysis theme of the power plant state monitoring system is more. The status monitoring data analysis topics of different functional location types differ. The analysis of the condition monitoring data of different types of products at the same functional position also has differences. The state monitoring data analysis of the same functional position type, the same product type and different measuring points or different types of measuring points also has difference. The analysis subjects of the state monitoring data obtained by different analysis methods of the same functional position type, the same product type and the same measuring point or the same type of measuring point also have differences.
The instances of each state monitoring data analysis theme are numerous and distributed on different pages, and the monitoring comprehensiveness of each theme is ensured by the regular traversal of operation and maintenance personnel according to the perfect management requirements, but the real-time performance and the integrity are greatly maintained.
In the document (CN107016235B, an equipment operation state health degree evaluation method based on multi-feature adaptive fusion), time domain characteristic parameters and frequency domain characteristic parameters of an equipment rotor component and process variable characteristic parameters of a current working condition are calculated for a vibration signal of each measurement surface of the equipment rotor component, and an index set is calculated and obtained according to a hierarchical structure of an equipment membership relationship to obtain a health degree. The document (CN109615275A, a comprehensive evaluation method for health of power communication network equipment) is a new index calculation method for performing difference balance statistics on index data sets of multiple equipment of the same type to obtain a refinement. The literature (CN111199257A fault diagnosis method and apparatus for high-speed rail driving equipment) is based on a signal analysis method, and extracts fault features from one or more collected original data signals of the high-speed rail driving equipment to perform initial diagnosis, and then fuses the initial diagnosis results on the basis to obtain the final diagnosis result of the high-speed rail driving equipment. Therefore, the existing technology focuses on a statistical method for performing special evaluation on component fault characteristics and comparing index differences to form final indexes. From the perspective of equipment structure/equipment attribute, the overall health degree of the equipment is not evaluated by using the power equipment ledger technology such as functional position type, category and the like. An evaluation method for finding a short system health degree board specially aiming at power equipment is also lacked.
When configuring the state monitoring data analysis theme, the invention sets the alarm threshold value for the measured value, the statistical value and the relative value, and comprehensively monitors the state monitoring examples of each unit set according to the equipment health degree evaluation and refresh frequency. When the real-time value exceeds the limit, the statistical value exceeds the limit and the relative value is degraded, the health degree value of the equipment is influenced, and the comprehensive monitoring of each system of the unit set is realized according to the numerical characteristic of the health degree evaluation of the equipment.
In addition, the invention provides a visual angle organization state monitoring data analysis example adopting the functional position type and the category of the power equipment standing book by combining engineering experience, and realizes the self-adaptive integration of the state monitoring data analysis result. The characteristics of the analysis result of the state monitoring data are comprehensively considered, the relevant evaluation method is standardized and is handed to a computer to complete, so that the state monitoring method based on the evaluation of the health degree of the power equipment realizes automatic detection and control, and technical support is provided for comprehensively knowing the state monitoring condition of the equipment in real time and tracking the state of the equipment.
In summary, the present invention comprehensively considers the analysis characteristics of each topic of the power equipment state monitoring, organizes and integrates the function position type and the category attribute of the power equipment ledger according to the monitoring results of the measured value, the statistical value and the relative value, evaluates the equipment health degree of each system of the unit set according to the equipment health degree evaluation and refresh frequency, and further comprehensively monitors the whole unit set, thereby providing technical methods for monitoring the whole performance of the power equipment in real time and for online research and judgment of the whole performance of the system according to the state monitoring condition of each subsystem.
Disclosure of Invention
The invention provides a state monitoring method based on the health degree evaluation of electric equipment, which comprehensively considers the analysis characteristics of each theme of the state monitoring of the electric equipment, integrates the function position type and the class attribute of an electric equipment machine account according to the monitoring results of an actual measurement value, a statistic value and a relative value, evaluates the health degree of each system of a unit set according to the equipment health degree evaluation refreshing frequency, further comprehensively monitors the whole unit set, provides a technical method for monitoring the whole performance of the electric equipment in real time for technical personnel, and also provides a technical method for researching and judging the whole performance of the system on line according to the state monitoring condition of each subsystem.
The purpose of the invention is realized by at least one of the following technical solutions.
A state monitoring method based on health degree evaluation of electric power equipment comprises the following steps:
s1, obtaining the scoring configuration P of each functional position type of the power equipment standing book example, and obtaining the state monitoring condition Q of each equipment in each system of the unit set;
s2, calculating the health degree F of each system of the unit set;
s3, acquiring a comprehensive score Z of the health degree of the unit set equipment;
s4, when the comprehensive score Z of the health degree of the unit set equipment or the system health degree F is lower than the threshold value delta1When the system light character board turns red, an alarm is sent out, and the step S8 is skipped; when the comprehensive value Z of the health degree of the unit set equipment and the system health degree F are not lower than the threshold value delta1When the system works, the light word plate does not change color and does not send out an alarm;
s5, when the system health degree F continuously decreases for a time number accumulated to exceed delta2When the system is in the second time, the light word plate turns orange and gives an alarm, and the step goes to step S8; when the system health degree F continuously decreases for a number of times which is accumulated to be not more than delta2When the system is used, the light character plate does not change color and does not send out an alarm;
s6, when the single drop amplitude of the system health degree F exceeds delta3When the system light character board turns yellow and gives an alarm, the step goes to step S8; when the system health degree F continuously decreases for a number of times which is accumulated to be not more than delta3When the system light word plate does not change color, the alarm is not sent out;
s7, jumping to the step S1 to continue execution according to the equipment health degree evaluation refreshing frequency, and realizing continuous monitoring of the health degree of the power equipment;
s8, the operator on duty confirms the alarm judgment and resets to the step S1 to continue monitoring.
Further, in step S1, the electric power equipment ledger refers to a two-dimensional table with the equipment ledger data ID as a primary key, and the electric power equipment ledger at least includes the following ledger fields:
equipment ledger data ID, equipment type, equipment model, manufacturer, technical parameters, and functional location type.
Further, in step S1, the scoring configuration P at least includes a function location type G and a deduction standard B; the state monitoring condition Q of each device in the system comprises an analog quantity monitoring QM and a switching value monitoring QK, wherein the analog quantity monitoring QM comprises a time scale MT, a measured value MZ and a statistic MJ, and the switching value monitoring QK comprises a time scale KT, a state KZ and a statistic KJ.
Further, step S2 includes the steps of:
s2.1, let i equal to 1, system XTiThe current score is FiAcquiring the number of the systems of the unit set to be N;
s2.2, acquiring system XTiType of functional position GiTo obtain system XTiType of functional position GiAnalog quantity monitoring example QM of lower-stage all-state monitoring example XTTiiAnd switching value monitoring example QKi；
S2.3 Slave function location type GiDeduction criterion BiIn-process acquisition analog quantity out-of-limit deduction score KFMiAnd switching value out-of-limit deduction value KFKi(ii) a Slave functional location type GiDeduction criterion BiIn-process acquisition analog quantity statistic out-of-limit deduction score KFTMiOff-limit deduction value KFTK of sum switching value statisticsi(ii) a Slave functional location type GiDeduction criterion BiObtaining analog quantity statistic state score KFZMiSum-switch statistic state score KFZKi；
S2.4, analog quantity monitoring QMiIf there is an analog quantity monitoring instance with an analog quantity value MZ out-of-limit, then the system XTiDegree of health of (F)i＝Fi-KFMi(ii) a Switching value monitoring QKiIf a preset alarm switching value appears in a switching value monitoring example, namely the switching value state KZ is met, the system XTiDegree of health of (F)i＝Fi-KFKi；
S2.5, analog quantity monitoring QMiIf the analog quantity statistic MJ exceeds the limit in the analog quantity monitoring example, the system XTiDegree of health of (F)i＝Fi-KFTMi(ii) a Switching value monitoring QKiIf the switching value statistic KJ exceeds the limit in any switching value monitoring example, the system XTiDegree of health of (F)i＝Fi-KFTKi；
S2.6, transverse comparison and System XTiAnalog monitoring instances of the same class, System XTiIf there is the monitoring instance with the worst numerical characteristic performance, then system XTiDegree of health of (F)i＝Fi-KFZMi(ii) a Transverse contrast and System XTiOn-off monitoring examples of the same class, System XTiIf there is the monitoring instance with the worst numerical characteristic performance, then system XTiDegree of health of (F)i＝Fi-KFZKi；
S2.7, if FiIs negative, then Fi0; when the system XTiIs reset, then Fi＝100；
S2.8, i is i +1, if the value of i is not greater than N, go to step S2.2, otherwise go to step S2.9;
s2.9, health degree F of each system of unit set is Fi，i∈[1,N]。
Further, step S3 includes the steps of:
s3.1, setting j to be 1, and acquiring the number E of unit units;
s3.2, acquiring the health degree F of all systems of the j unit set;
s3.3, taking the minimum value of the health degree F as the comprehensive score Z of the health degree of the unit set equipment of the ith unit setj；
S3.4, j is j +1, if j is not greater than E, go to step S3.2, otherwise go to step S3.5;
s3.5, comprehensive score Z of health degree of unit equipment is Zj，j∈[1,E]。
Further, the analog quantity out-of-limit deduction score KFMiAnd switching value out-of-limit deduction value KFKiAre both 50; the off-limit deduction score KFTM of the analog quantity statisticiIs 5; the switch quantity statistic out-of-limit deduction score KFTKiIs 10; the analog quantity statistic state score KFZMiIs 2; the switch quantity statistic state deduction score KFZKiIs 3.
Further, in step S4, the threshold δ is set1Is a user preset variable;
in step S5, the threshold δ2Is a user preset variable;
in step S6, the threshold δ3Is a user preset variable;
in step S7, the device health degree evaluation refresh frequency is a user preset variable.
Furthermore, the system light character board is an equipment state indicating module arranged on a main monitoring picture of each unit of the plant station, and can emit white light, red light, orange light and yellow light, wherein white represents that the unit is in a normal state, red represents that the unit is abnormal, orange represents that the performance of the unit is continuously reduced, and yellow represents that the performance of the unit is obviously reduced; one unit set is provided with a system light word plate, and when the unit set equipment or unit set equipment subordinate to the system is in an abnormal state, the corresponding light word plate changes color and gives an alarm.
Furthermore, each system of the unit set is a next-stage function grouping system of the unit set, and comprises a ball valve system, a generator system, a water turbine system, a speed regulator system, a tail gate system, an excitation system and a cooling system.
Compared with the prior art, the invention fills the blank of the engineering field, and has the following advantages and technical effects:
(1) according to the invention, alarm setting of the measured value, the statistical value and the relative value in the state monitoring data analysis theme is adopted, so that comprehensive monitoring of each system state monitoring instance of each unit set is realized according to the equipment health degree evaluation refreshing frequency, and comprehensive monitoring of state monitoring data analysis is realized according to the numerical characteristic of the equipment health degree evaluation.
(2) According to the invention, the status monitoring data analysis examples are organized by adopting the functional position types and the visual angles of the types of the standing book of the power equipment, so that the self-adaptive integration of the status monitoring data analysis results is realized, the characteristics of the status monitoring data analysis results are comprehensively considered, the relevant evaluation methods are standardized, and the automatic detection and control of the status monitoring method based on the health degree evaluation of the power equipment are realized.
(3) The invention provides a technical method for monitoring the overall performance of the power equipment in real time, also provides a technical method for researching and judging the overall performance of the system on line according to the state monitoring condition of each subsystem, and provides a technical method for quantitative analysis of the state monitoring status of the power equipment.
Drawings
Fig. 1 is a flowchart of a state monitoring method based on health evaluation of an electrical device in this example.
Detailed Description
The following description of the embodiments of the present invention is provided in connection with the accompanying drawings and examples, but the invention is not limited thereto. It is noted that the processes described below, if not specifically described in detail, are all realizable or understandable by those skilled in the art with reference to the prior art.
Example (b):
in this embodiment, a state monitoring data analysis and evaluation example of a #1 unit set of a power plant is introduced, and the types of the functional positions of the #1 unit set include a ball valve system, a generator system, a water turbine system, a speed regulator system, a tail gate system, an excitation system and a cooling system. The functional position type equipment of the four unit units of the power plant is the same type equipment. The power plant ball valve system has 8 state monitoring system data analysis examples which are respectively the running time analysis of ball valve oil pumps of #1 to #4 units and the opening efficiency analysis of ball valves of #1 to #4 units. The power plant generator system has 4 state monitoring system data analysis examples which are respectively identified for abnormal switching value events of the #1 to #4 units. The power plant water turbine system has 4 state monitoring system data analysis examples which are respectively monitoring water guide shoe temperature and temperature rise of the units from #1 to # 4.
A state monitoring method based on health evaluation of electrical equipment, as shown in fig. 1, includes the following steps:
s1, obtaining the scoring configuration P of each functional position type of the power equipment standing book example, and obtaining the state monitoring condition Q of each equipment in each system of the unit set;
the electric power equipment standing book is a two-dimensional table taking equipment standing book data ID as a main key word, and at least comprises the following standing book fields:
equipment ledger data ID, equipment type, equipment model, manufacturer, technical parameters, and functional location type.
The scoring configuration P at least comprises a function position type G and a deduction standard B; the state monitoring condition Q of each device in the system comprises an analog quantity monitoring QM and a switching value monitoring QK, wherein the analog quantity monitoring QM comprises a time scale MT, a measured value MZ and a statistic MJ, and the switching value monitoring QK comprises a time scale KT, a state KZ and a statistic KJ.
In this embodiment, a specific scoring configuration P and a state monitoring condition Q of the device are shown in table 1 and table 2, respectively.
TABLE 1 Scoring configuration P
TABLE 2 State monitoring of the devices Q
S2, calculating a health degree F of each system of the unit set, in this embodiment, the method includes the following steps:
s2.1, setting i to 1, system XT1Being a ball valve system, its current score F1The number of the unit set is 100, and N is 7;
s2.2. System XT1Type of functional position G1For a ball valve system, all state monitoring examples XTT1, switching value monitoring example QK1That is, the lower the statistical value of the running time statistical example of the ball valve oil pump of the #1 unit is, the lowest the opening efficiency of the ball valve of the #1 unit is, as shown in table 1.
S2.3 functional location type G shown in Table 11Obtaining a deduction criterion B1Analog quantity out-of-limit deduction value KFMiAnd switching value out-of-limit deduction value KFKiAre both 50; the off-limit deduction score KFTM of the analog quantity statisticiIs 5; the switch quantity statistic out-of-limit deduction score KFTKiIs 10; the analog quantity statistic state score KFZMiIs 2; the switch quantity statistic state deduction score KFZKiIs 3.
S2.4. switching value monitoring QK1If the switching value statistic KJ exceeds the limit in the switching value monitoring example, the system XT1Degree of health of (F)1＝F1-KFTK1＝100-10＝90；
S2.5. transverse comparison and System XT1On-off monitoring examples of the same class, System XT1In the monitoring examples with the worst numerical characteristic performance (#1 unit ball valve opening efficiency is lowest), system XT1Degree of health of (F)1＝F1-KFZK1＝90-3＝87；
S2.6.i＝i+1＝2；
S2.7. System XT2Type of functional position G2For the generator system, #1 unit does not need state monitoring of deduction, as shown in table 1, the health degree of the generator system F2＝100；
S2.8.i + 1-3; system XT3Type of functional position G3QM appears for analog quantity monitoring example of XTT3 of all state monitoring examples of water turbine system3Namely, after the power generation working condition is operated for 30min under full load, in the comparison of four units in the whole plant, the temperature of the water guide bearing bush temperature measuring point of the #1 unit is the highest, as shown in table 1.
S2.9 functional location type G shown in Table 13Obtaining a deduction criterion B3；
S2.10. transverse comparison and System XT3Analog monitoring instances of the same class, System XT3Of which the numerical characteristics perform the worstMonitoring example (after the power generation working condition runs for 30min under full load, in the comparison of four units in the whole plant, the temperature of a #1 unit water guide bearing bush temperature measuring point is highest), and system XT3Degree of health of (F)1＝F1-KFZK1＝100-2＝98；
S2.11. likewise, System XT4(governor system), System XT5(Tail gate System), System XT6(excitation system), System XT7(Cooling System), #1 Unit State monitoring without deduction, health degree F, as shown in Table 14＝F5＝F6＝F7＝100；
S2.12. the health degree F of each system of the unit set is {87,100,98,100 }.
S3, acquiring a comprehensive score Z of the health degree of the unit set equipment, wherein the method comprises the following steps:
s3.1, setting j to be 1, and acquiring the number E of unit units to be 4;
s3.2, acquiring health degrees F of all systems of the subordinate unit set of the 1 st unit set, wherein the health degrees F are {87,100,98,100 };
s3.3. 1 st unit machine set equipment health degree comprehensive score Z1＝87；
S3.4.j＝j+1；
S3.5, acquiring health degrees F of all systems of the subordinate unit group of the 2 nd unit group, wherein the health degrees F are {100,50,100 };
s3.6. comprehensive score Z of equipment health degree of 2 nd unit set2＝50；
S3.7. similarly, the comprehensive value Z of the health degree of the 3 rd unit set equipment3Integrated score Z of equipment health of 4 th unit plant (100;)4＝100；
And S3.8, the comprehensive score Z of the health degree of the unit set equipment is {87,50,100 }.
S4, when the comprehensive score Z of the health degree of the unit set equipment or the system health degree F is lower than the threshold value delta1When the system light board changes to red and gives an alarm, the step goes to step S8, in this embodiment, the threshold value δ is set1Is 60 minutes; when the comprehensive value Z of the health degree of the unit set equipment and the system health degree F are not lower than the threshold value delta1When the system works, the light word plate does not change color and does not send out an alarm;
in this embodiment, the comprehensive score Z of the health degree of the unit set equipment2Or #2 unit generator system health degree F2When the number is lower than the threshold value of 60, the light word plates of the generator systems of the #2 unit and the #2 unit change to red and send out an alarm;
s5, when the system health degree F continuously decreases for a time number accumulated to exceed delta2Then, the system light board turns orange and gives an alarm, and the step goes to step S8, in this embodiment, the threshold value δ is set2Is 3; when the system health degree F continuously decreases for a number of times which is accumulated to be not more than delta2When the system is used, the light character plate does not change color and does not send out an alarm;
s6, when the single drop amplitude of the system health degree F exceeds delta3When the system light word plate turns yellow and gives an alarm, the step goes to step S8, in this embodiment, the threshold value delta is3Is divided into 2 parts; when the system health degree F continuously decreases for a number of times which is accumulated to be not more than delta3When the system light word plate does not change color, the alarm is not sent out;
in this embodiment, the health degree F single-drop amplitude of the ball valve system and the water turbine system of the #1 unit and the generator system of the #2 unit exceeds δ3The light character plate of the ball valve system and the water turbine system of the #1 unit and the generator system of the #2 unit turns yellow and gives an alarm;
s7, in the embodiment, the step S1 is skipped to continue to be executed according to the equipment health degree evaluation refresh frequency of 0.5Hz, and the continuous monitoring of the health degree of the electric power equipment is realized.
S8, the operator on duty confirms the alarm judgment and resets to the step S1 to continue monitoring.
The invention provides a state monitoring method based on the health degree evaluation of the power equipment, which integrates the function position type and the class attribute of the machine account of the power equipment by using an automatic detection and control mode according to the monitoring results of an actual measurement value, a statistical value and a relative value, evaluates the health degree of the equipment for each system of a unit set according to the evaluation and refresh frequency of the health degree of the equipment, further comprehensively monitors the whole unit set, and provides a technical method for monitoring the whole performance of the power equipment in real time for technical personnel and a technical method for researching and judging the whole performance of the system on line according to the state monitoring condition of each subsystem.
Claims (9)
1. A state monitoring method based on health degree evaluation of electric power equipment is characterized by comprising the following steps:
s1, obtaining the scoring configuration P of each functional position type of the power equipment standing book example, and obtaining the state monitoring condition Q of each equipment in each system of the unit set;
s2, calculating the health degree F of each system of the unit set;
s3, acquiring a comprehensive score Z of the health degree of the unit set equipment;
s4, when the comprehensive score Z of the health degree of the unit set equipment or the system health degree F is lower than the threshold value delta1When the system light character board turns red, an alarm is sent out, and the step S8 is skipped; when the comprehensive value Z of the health degree of the unit set equipment and the system health degree F are not lower than the threshold value delta1When the system works, the light word plate does not change color and does not send out an alarm;
s5, when the system health degree F continuously decreases for a time number accumulated to exceed delta2When the system is in the second time, the light word plate turns orange and gives an alarm, and the step goes to step S8; when the system health degree F continuously decreases for a number of times which is accumulated to be not more than delta2When the system is used, the light character plate does not change color and does not send out an alarm;
s6, when the single drop amplitude of the system health degree F exceeds delta3When the system light character board turns yellow and gives an alarm, the step goes to step S8; when the system health degree F continuously decreases for a number of times which is accumulated to be not more than delta3When the system light word plate does not change color, the alarm is not sent out;
s7, jumping to the step S1 to continue execution according to the equipment health degree evaluation refreshing frequency, and realizing continuous monitoring of the health degree of the power equipment;
s8, the operator on duty confirms the alarm judgment and resets to the step S1 to continue monitoring.
2. The method for monitoring the state based on the health degree evaluation of the electric power equipment as claimed in claim 1, wherein in step S1, the electric power equipment standing book is a two-dimensional table with equipment standing book data ID as a primary key, and the electric power equipment standing book at least comprises the following standing book fields:
equipment ledger data ID, equipment type, equipment model, manufacturer, technical parameters, and functional location type.
3. The method for monitoring the state based on the health degree evaluation of the power equipment as claimed in claim 1, wherein in step S1, the scoring configuration P at least comprises a function position type G, a deduction criterion B; the state monitoring condition Q of each device in the system comprises an analog quantity monitoring QM and a switching value monitoring QK, wherein the analog quantity monitoring QM comprises a time scale MT, a measured value MZ and a statistic MJ, and the switching value monitoring QK comprises a time scale KT, a state KZ and a statistic KJ.
4. The condition monitoring method based on the health degree evaluation of the power equipment as claimed in claim 2, wherein the step S2 comprises the following steps:
s2.1, let i equal to 1, system XTiThe current score is FiAcquiring the number of the systems of the unit set to be N;
s2.2, acquiring system XTiType of functional position GiTo obtain system XTiType of functional position GiAnalog quantity monitoring example QM of lower-stage all-state monitoring example XTTiiAnd switching value monitoring example QKi；
S2.3 Slave function location type GiDeduction criterion BiIn-process acquisition analog quantity out-of-limit deduction score KFMiAnd switching value out-of-limit deduction value KFKi(ii) a Slave functional location type GiDeduction criterion BiIn-process acquisition analog quantity statistic out-of-limit deduction score KFTMiOff-limit deduction value KFTK of sum switching value statisticsi(ii) a Slave functional location type GiDeduction criterion BiObtaining analog quantity statistic state score KFZMiSum-switch statistic state score KFZKi；
S2.4, analog quantity monitoring QMiIf there is an analog quantity monitoring instance with an analog quantity value MZ out-of-limit, then the system XTiDegree of health of (F)i＝Fi-KFMi(ii) a Switching value monitoring QKiIf a preset alarm switching value appears in a switching value monitoring example, namely the switching value state KZ is met, the system XTiDegree of health of (F)i＝Fi-KFKi；
S2.5, analog quantity monitoring QMiIf the analog quantity statistic MJ exceeds the limit in the analog quantity monitoring example, the system XTiDegree of health of (F)i＝Fi-KFTMi(ii) a Switching value monitoring QKiIf the switching value statistic KJ exceeds the limit in any switching value monitoring example, the system XTiDegree of health of (F)i＝Fi-KFTKi；
S2.6, transverse comparison and System XTiAnalog monitoring instances of the same class, System XTiIf there is the monitoring instance with the worst numerical characteristic performance, then system XTiDegree of health of (F)i＝Fi-KFZMi(ii) a Transverse contrast and System XTiOn-off monitoring examples of the same class, System XTiIf there is the monitoring instance with the worst numerical characteristic performance, then system XTiDegree of health of (F)i＝Fi-KFZKi；
S2.7, if FiIs negative, then Fi0; when the system XTiIs reset, then Fi＝100；
S2.8, i is i +1, if the value of i is not greater than N, go to step S2.2, otherwise go to step S2.9;
s2.9, health degree F of each system of unit set is Fi，i∈[1,N]。
5. The condition monitoring method based on the health degree evaluation of the power equipment as claimed in claim 1, wherein the step S3 comprises the following steps:
s3.1, setting j to be 1, and acquiring the number E of unit units;
s3.2, acquiring the health degree F of all systems of the j unit set;
s3.3, taking the minimum value of the health degree F as the comprehensive score Z of the health degree of the unit set equipment of the ith unit setj；
S3.4, j is j +1, if j is not greater than E, go to step S3.2, otherwise go to step S3.5;
s3.5, comprehensive score Z of health degree of unit equipment is Zj，j∈[1,E]。
6. The state monitoring method based on power equipment health degree evaluation according to claim 4, characterized in that the analog quantity out-of-limit deduction score KFMiAnd switching value out-of-limit deduction value KFKiAre both 50; the off-limit deduction score KFTM of the analog quantity statisticiIs 5; the switch quantity statistic out-of-limit deduction score KFTKiIs 10; the analog quantity statistic state score KFZMiIs 2; the switch quantity statistic state deduction score KFZKiIs 3.
7. The condition monitoring method based on the health degree evaluation of the power equipment as claimed in claim 1, wherein in step S4, the threshold value δ is1Is a user preset variable;
in step S5, the threshold δ2Is a user preset variable;
in step S6, the threshold δ3Is a user preset variable;
in step S7, the device health degree evaluation refresh frequency is a user preset variable.
8. The state monitoring method based on the health degree evaluation of the power equipment as claimed in claim 1, wherein the system light word is an equipment state indicating module arranged on a main monitoring screen of each unit set of the plant station, and can emit white light, red light, orange light and yellow light, wherein white light indicates that the unit set is in a normal state, red light indicates that the unit set is abnormal, orange light indicates that the performance of the unit set is continuously reduced, and yellow light indicates that the performance of the unit set is obviously reduced; one unit set is provided with a system light word plate, and when the unit set equipment or unit set equipment subordinate to the system is in an abnormal state, the corresponding light word plate changes color and gives an alarm.
9. The state monitoring method based on the health degree evaluation of the power equipment according to any one of claims 1 to 8, wherein each system of the unit set is a next-stage function grouping system of the unit set, and comprises a ball valve system, a generator system, a water turbine system, a speed regulator system, a tail gate system, an excitation system and a cooling system.
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