A health assessment method for hydro-generator units based on fault information

Abstract

This invention discloses a health assessment method for hydro-generator units based on fault information. The invention uses generator unit operation and maintenance fault mode information to conduct online quantitative health assessments of the generator unit and its key components. Fault mode information mainly includes fault prediction, fault diagnosis, and operation and maintenance result data. A generator unit health evaluation system is established through a mechanistic model. By understanding the frequency of fault modes and their impact on key components, the operating status of key components is quantitatively determined online. A correction coefficient for key components is introduced to dynamically correct the health status over time, making it more consistent with the unit's operating conditions. This guides the operation and maintenance of key components, ensures the reliability of key components, and extends the service life of the generator unit.

Description

Technical Field

[0001] The invention relates to a health assessment method for a hydro-generator set based on fault information. Background Art

[0002] As users' requirements for smart units gradually increase, the requirements for the technical level of generator set operation and maintenance are getting higher and higher. Keeping track of the operating status of the unit based on the internal mechanism of the generator set has become an important technical support for the intelligent operation and maintenance of the generator set.

[0003] The establishment of the health status evaluation system of the generator set has always been stuck in the application of status monitoring parameter indicators for comprehensive evaluation. Due to the influence of many changes in the operating conditions of the generator set, the real-time and accuracy of sensor measurement and data transmission, it is impossible to truly accurately grasp the operating status of the unit. Therefore, the health status evaluation of the generator set can only be accurate and practical by using fault information processed by data analysis.

[0004] In order to ensure that the health assessment results of the generator set are reliable, a health assessment method for the hydro-generator set based on fault information is urgently needed. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a method for health assessment through full life cycle fault information during the operation of a generator set. The technical solution of the present invention is specifically described as follows:

[0006] Step 1: Start the query service of fault mode information and health assessment model during the whole life cycle of the generator set;

[0007] Step 2: Obtain the health assessment model of the key component k of the generator set and the fault mode F to which the model belongs j , the fault mode object mainly includes the frequency of the fault F jf and the degree of impact on the components F ji ;

[0008] Step 3: Calculate the health of the jth specific failure mode

[0009] Step 4: The initial health degree H0 of key components when they are put into operation is calculated according to the abnormal detection model of the monitoring point to which they belong. The health degree H0 of key components when they are replaced is n Obtained based on statistics and experience of similar parts;

[0010] Step 5: Predetermine the maximum frequency value F allowed for various failure modes according to the formula jfmax and F jfst The value is set, the maximum frequency value F jfmax and frequency standard value F jfst Obtained according to statistics and experience;

[0011] Step 6: Calculate the health H of the kth key component based on the fault information kf , first of all, the severity of the fault mode F ji After normalization, the component health can be calculated in combination with the failure mode health;

[0012] Step 7: Calculate the correction coefficient ω(t) of the kth key component under the specific operating environment at time t;

[0013] Step 8: Calculate the dynamically corrected health H of the kth key component k ;

[0014] Step 9: Calculate the health of the generator set H g ;

[0015] Step 10: Divide the range of generator unit health evaluation indicators, and the evaluation indicators describe the operating status of the unit.

[0016] In the above-mentioned method for health assessment of a hydro-turbine generator set based on fault information, the steps of fault mode health, fault mode information acquisition and fault mode health calculation in step 3 are as follows:

[0017] Using the fault mode number as the query condition, the historical fault information of the jth specific fault mode is obtained from the database, including the occurrence frequency and the degree of impact on key components;

[0018] The health degree is calculated by combining the standard value and maximum value of the failure mode frequency as well as the health degree at the initial and replacement time. The determination formula is as follows:

[0019]

[0020] Where:

[0021] The health of the jth specific failure mode;

[0022] F jfmax : The maximum frequency value allowed for this failure mode;

[0023] F jfst : The standard value of the frequency allowed for this failure mode;

[0024] H n : Health level when the kth key component is replaced;

[0025] H0: initial health of the kth key component when it goes online;

[0026] The health of the jth specific failure mode is stored in the database to achieve regular update of the failure mode health status indicator.

[0027] In the above-mentioned method for health assessment of a hydro-turbine generator set based on fault information, the steps of obtaining the health of components, the health of the failure mode of key components and calculating the health of key components in step 6 are as follows:

[0028] Using the key component number as the query condition, obtain the key component health assessment index system from the database, and obtain the relevant failure mode and impact degree of the kth key component;

[0029] The influence of the failure modes in all indicator systems is normalized, and the health of all failure modes is weighted and calculated. The judgment formula is as follows:

[0030]

[0031] Where:

[0032] H kf : The health of the kth key component;

[0033] The health of the jth specific failure mode;

[0034] F ji : Impact degree of the corresponding failure mode;

[0035] Using the key component number as the query condition, the health of the kth key component in the database is updated regularly.

[0036] In the above-mentioned method for health assessment of a hydro-turbine generator set based on fault information, the steps of obtaining correction coefficient information of key components and calculating correction coefficient in step seven are as follows:

[0037] Using the key component number as the query condition, obtain the correction coefficient and natural degradation coefficient of the operating environment of the key component from the database. Design life T s , assign value of water environment corrosion coefficient f1.

[0038] The natural degradation coefficient is calculated by combining multiple correction coefficients and the initial and replacement health status. The determination formula is as follows:

[0039]

[0040] Where:

[0041] Natural deterioration coefficient;

[0042] T s : Design life of this component;

[0043] f1: water environment corrosion coefficient;

[0044] Calculate the natural degradation coefficient of time node t0 and key components based on the initial health Real-time calculation of the health correction coefficient of key components, the determination formula is as follows:

[0045]

[0046] Where:

[0047] ω(t): Correction coefficient

[0048] Natural deterioration coefficient;

[0049] t0: initial health calculation time node;

[0050] Using the key component number as the query condition, the correction coefficient of the kth key component in the database is updated regularly, the workload coefficient f2 is calculated and updated on an annual basis, and the temperature field coefficient f4 is automatically selected on a quarterly basis.

[0051] In the above-mentioned method for health assessment of a hydro-turbine generator set based on fault information, the steps for calculating the corrected health of components and the corrected health of key components in step eight are as follows:

[0052] Query the health of the kth key component before correction based on the key component number H kf and the correction coefficient ω(t) at time t;

[0053] Combining the health before correction and the correction coefficient at time t, online real-time calculation is performed, and the judgment formula is as follows:

[0054] H k =H kf ω(t)

[0055] Where:

[0056] H k : The health of the kth key component after dynamic correction;

[0057] H kf : The health of the kth key component before correction;

[0058] ω(t): correction coefficient at time t;

[0059] Using the key component number as the query condition, the health of the kth key component in the database is corrected and updated, and the health status label is assigned as corrected.

[0060] In the above-mentioned method for health assessment of hydropower generator set based on fault information, the health of the generator set in step nine is combined with the key components H1…H in the generator set evaluation system. N The calculation steps are as follows:

[0061] Using the generator set number as the query condition, obtain the generator set health assessment index system from the database and obtain the H1…H N The health of key components;

[0062] Obtain the health of key components in the generator set health assessment index system, and use the principle that the lowest score of key components represents the health of the generator set. The judgment formula is as follows:

[0063] H g =min{H1…H N}

[0064] Where:

[0065] H g : Generator health;

[0066] H1: Health of the first key component;

[0067] H N : The health of the Nth key component;

[0068] The generator set number is used as the query condition to regularly update the health of the generator sets in the database.

[0069] In the above-mentioned method for health assessment of a hydro-turbine generator set based on fault information, the steps of evaluating the operating status of the generator set in step 10 by combining the operating status evaluation standard of the generator set with the health degree are as follows:

[0070] Obtain the generator set operating status evaluation index range and the health of the generator set from the database;

[0071] The health of the generator set is screened and matched with the range of the status evaluation index. The judgment formula is as follows:

[0072]

[0073] Where:

[0074] H g : Generator health;

[0075] The health assessment results can be calculated and the operating status of the generator set can be determined.

[0076] Due to the adoption of the above scheme, the beneficial effects of the present invention are:

[0077] 1. Facilitate the unit to carry out maintenance according to the situation. By mastering the quantitative evaluation results of the generator set and its key components, the indicator can be used to guide the key components to carry out emergency maintenance or extend the maintenance cycle, thus ensuring the safety and reliability of the unit and key components;

[0078] 2. Extend the service life of the generator set. By carrying out condition-based maintenance on the generator set, the maintenance cost of the generator set can be reduced, and the "non-stop" time of the generator set can be reduced, which can ensure the efficient and stable operation of the generator set and extend the service life of the generator set. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 It is a logic block diagram of the working principle of the method of the present invention.

[0080] Figure 2 It is a logic block diagram of the calculation principle of the initial and replacement health of components. DETAILED DESCRIPTION

[0081] Specific implementation method 1: Figure 1 and Figure 2 As shown, this embodiment provides a method for health assessment of a hydro-generator set based on fault information, and the method is implemented by the following steps:

[0082] Step 1: Start the query service of fault mode information and health assessment model during the whole life cycle of the generator set;

[0083] Step 2: Obtain the health assessment model of the key component k of the generator set and the fault mode F to which the model belongs j , the fault mode object mainly includes the frequency of the fault F jf and the degree of impact on the components F ji ;

[0084] Step 3: Calculate the health of the jth specific failure mode

[0085] Step 4: The initial health degree H0 of key components when they are put into operation is calculated according to the abnormal detection model of the monitoring point to which they belong. The health degree H0 of key components when they are replaced is n Obtained based on statistics and experience of similar parts;

[0086] Step 5: Predetermine the maximum frequency value F allowed for various failure modes according to the formula jfmax and F jfst The value is set, the maximum frequency value F jfmax and frequency standard value F jfst Obtained according to statistics and experience;

[0087] Step 6: Calculate the health H of the kth key component based on the fault information kf, first of all, the severity of the fault mode F ji After normalization, the component health can be calculated in combination with the failure mode health;

[0088] Step 7: Calculate the correction coefficient ω(t) of the kth key component under the specific operating environment at time t;

[0089] Step 8: Calculate the dynamically corrected health H of the kth key component k ;

[0090] Step 9: Calculate the health of the generator set H g ;

[0091] Step 10: Divide the range of generator unit health evaluation indicators, and map the evaluation indicators to the unit operating status.

[0092] In this implementation, a quantitative assessment is performed based on the fault information of the generator set to improve the level of quantitative assessment of the health of the generator set. The fault information of the generator set throughout its life cycle is comprehensively utilized, and the fault diagnosis, fault prediction, operation and maintenance data of the generator set are stored in the historical fault database. Finally, the operating status of the generator set is accurately evaluated by combining the degree of impact of the fault information on key components and the frequency of occurrence, and the historical health level of the generator set is accurately grasped, guiding the generator set to perform condition maintenance.

[0093] Specific implementation method 2: Figure 1 and Figure 2 As shown, this implementation is to further limit step three described in the specific implementation mode one. In this implementation mode, the steps of failure mode health, failure mode information acquisition and failure mode health calculation in step three are as follows:

[0094] Using the fault mode number as the query condition, the historical fault information of the jth specific fault mode is obtained from the database, including the occurrence frequency and the degree of impact on key components;

[0095] The health degree is calculated by combining the standard value and maximum value of the failure mode frequency as well as the health degree at the initial and replacement time. The determination formula is as follows:

[0096]

[0097] Where:

[0098] The health of the jth specific failure mode;

[0099] F jfmax : The maximum frequency value allowed for this failure mode;

[0100] F jfst : The standard value of the frequency allowed for this failure mode;

[0101] H n : Health level when the kth key component is replaced;

[0102] H0: initial health of the kth key component when it goes online;

[0103] The health of the jth specific failure mode is stored in the database to achieve regular update of the failure mode health status indicator.

[0104] In this embodiment, computer automatic judgment and statistics are adopted to effectively record the historical occurrence of the fault mode, and the specific fault information of the fault mode can be obtained more efficiently.

[0105] Specific implementation method three: Figure 1 and Figure 2 As shown, this implementation is to further limit step six described in the specific implementation mode one. In this implementation, the steps of obtaining the health of components, the health of the failure mode of key components and calculating the health of key components in step six are as follows:

[0106] Using the key component number as the query condition, obtain the key component health assessment index system from the database, and obtain the relevant failure mode and impact degree of the kth key component;

[0107] The influence of the failure modes in all indicator systems is normalized, and the health of all failure modes is weighted and calculated. The judgment formula is as follows:

[0108]

[0109] Where:

[0110] H kf : The health of the kth key component;

[0111] The health of the jth specific failure mode;

[0112] F ji : Impact degree of the corresponding failure mode;

[0113] Using the key component number as the query condition, the health of the kth key component in the database is updated regularly.

[0114] Specific implementation method four: Figure 1 and Figure 2 As shown, this embodiment further limits step seven described in the specific embodiment one. In this embodiment, the steps of obtaining correction coefficient information of key components and calculating correction coefficient in step seven are as follows:

[0115] Using the key component number as the query condition, obtain the correction coefficient and natural degradation coefficient of the operating environment of the key component from the database. Design life T s , the water environment corrosion coefficient f1 is directly assigned.

[0116] The natural degradation coefficient is calculated by combining multiple correction coefficients and the initial and replacement health status. The determination formula is as follows:

[0117]

[0118] Where:

[0119] Natural deterioration coefficient;

[0120] T s : Design life of this component;

[0121] f1: water environment corrosion coefficient;

[0122] Calculate the natural degradation coefficient of time node t0 and key components based on the initial health Real-time calculation of the health correction coefficient of key components, the determination formula is as follows:

[0123]

[0124] Where:

[0125] ω(t): Correction coefficient

[0126] Natural deterioration coefficient;

[0127] t0: initial health calculation time node;

[0128] Using the key component number as the query condition, the correction coefficient of the kth key component in the database is updated regularly, the workload coefficient f2 is calculated and updated on an annual basis, and the temperature field coefficient f4 is automatically selected on a quarterly basis.

[0129] In this implementation, a correction factor is introduced, and the source of the correction factor is mainly obtained from laboratory fatigue and destruction experiments. Taking the environmental factors of the generator set into consideration in the health calculation process can improve the calculation accuracy of the health.

[0130] Specific implementation method five: Figure 1 and Figure 2 As shown, this embodiment further limits step eight described in the specific embodiment one. In this embodiment, the steps of calculating the corrected health of the components and the corrected health of the key components in step eight are as follows:

[0131] Query the health of the kth key component before correction based on the key component number H kf and the correction coefficient ω(t) at time t;

[0132] Combining the health before correction and the correction coefficient at time t, online real-time calculation is performed, and the judgment formula is as follows:

[0133] H k =H kf ω(t)

[0134] Where:

[0135] H k : The health of the kth key component after dynamic correction;

[0136] H kf : The health of the kth key component before correction;

[0137] ω(t): correction coefficient at time t;

[0138] Using the key component number as the query condition, the health of the kth key component in the database is corrected and updated, and the health status label is assigned as corrected.

[0139] In this embodiment, a correction coefficient that changes with time is introduced into the component health so that the component health conforms to the fatigue aging phenomenon and the maintenance cycle is more consistent with the actual results of the power plant.

[0140] Specific implementation method six: Figure 1 and Figure 2 As shown, this embodiment further limits step nine described in the specific embodiment one. In this embodiment, the health of the generator set in step nine is combined with the key components H1…H in the generator set evaluation system. N The calculation steps are as follows:

[0141] Using the generator set number as the query condition, obtain the generator set health assessment index system from the database and obtain the H1…H N The health of key components;

[0142] Obtain the health of key components in the generator set health assessment index system, and use the principle that the lowest score of key components represents the health of the generator set. The judgment formula is as follows:

[0143] H g =min{H1…H N}

[0144] Where:

[0145] H g : Generator health;

[0146] H1: Health of the first key component;

[0147] H N : The health of the Nth key component;

[0148] The generator set number is used as the query condition to regularly update the health of the generator sets in the database.

[0149] In this implementation, the health of the generator set follows the principle of minimum subordination, so that the health of the generator set represents the most dangerous state of the unit, quickly locates the key components that are most likely to have problems, and improves the emergency response efficiency of operation and maintenance personnel.

[0150] Specific implementation method seven: Figure 1 and Figure 2 As shown, this embodiment further limits step ten described in the specific embodiment one. In this embodiment, the operating state of the generator set in step ten, the steps of evaluating the operating state in combination with the generator set operating state evaluation standard and health are as follows:

[0151] Obtain the generator set operating status evaluation index range and the health of the generator set from the database;

[0152] The health of the generator set is screened and matched with the range of the status evaluation index. The judgment formula is as follows:

[0153]

[0154] Where:

[0155] H g : Generator health;

[0156] The health assessment results can be calculated and the operating status of the generator set can be determined.

[0157] In this implementation, a corresponding relationship is established between the health range of the generator set and the operating status of the set, so that the operation and maintenance personnel can quickly grasp the health status of key components and the set, and accurately and quickly guide the operation and maintenance personnel to respond based on the health assessment results.

[0158] The above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, it should be clear to those skilled in the art that the technical solutions described in the above embodiments may be modified, or some or all of the technical features therein may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for health assessment of a hydro-generator unit based on fault information, the characteristics of which include: Follow these steps: Step 1: Start the query service of fault mode information and health assessment model during the whole life cycle of the generator set; Step 2: Obtain the health assessment model of the key component k of the generator set and the fault mode F to which the model belongs j , the fault mode object mainly includes the frequency of the fault F jf and the degree of impact on the components F ji ; Step 3: Predetermine the maximum frequency value F allowed for various failure modes according to the formula jfmax and F jfst The value is set, the maximum frequency value F jfmax and frequency standard value F jfst Obtained according to statistics and experience; Step 4: The initial health degree H0 of key components when they are put into operation is calculated according to the abnormal detection model of the monitoring point to which they belong. The health degree H0 of key components when they are replaced is n Obtained based on statistics and experience of similar parts; Step 5: Calculate the health of the jth specific failure mode Using the fault mode number as the query condition, the historical fault information of the jth specific fault mode is obtained from the database, including the occurrence frequency and the degree of impact on key components; The health degree is calculated by combining the standard value and maximum value of the failure mode frequency and the health degree of key components at the initial and replacement time. The determination formula is as follows: Where: The health of the jth specific failure mode; F jfmax : The maximum frequency value allowed for this failure mode; F jfst : The standard value of the frequency allowed for this failure mode; H n : Health level when the kth key component is replaced; H0: initial health of the kth key component when it goes online; The health of the jth specific fault mode is stored in the database to achieve regular update of the fault mode health status indicator; Step 6: Calculate the health H of the kth key component based on the fault information kf ; Using the key component number as the query condition, obtain the key component health assessment index system from the database, and obtain the relevant failure mode and impact degree of the kth key component; The severity of the failure mode F ji After normalization, the component health can be calculated in combination with the failure mode health. The key component number is used as the query condition to obtain the key component health assessment index system from the database, and the failure mode and impact degree related to the kth key component are obtained; The influence of the failure modes in all indicator systems is normalized, and the health of all failure modes is weighted and calculated. The judgment formula is as follows: Where: H kf : The health of the kth key component; The health of the jth specific failure mode; F ji : Impact degree of the corresponding failure mode; Using the key component number as the query condition, the health of the kth key component in the database is regularly updated; Step 7: Calculate the correction coefficient ω(t) of the kth key component under the specific operating environment at time t; Using the key component number as the query condition, obtain the correction coefficient and natural degradation coefficient of the operating environment of the key component from the database. Design life T s , directly assign the water environment corrosion coefficient f1; The natural degradation coefficient is calculated by combining multiple correction coefficients and the initial and replacement health status. The determination formula is as follows: Where: Natural deterioration coefficient; T s : Design life of this component; f1: water environment corrosion coefficient; Calculate the natural degradation coefficient of time node t0 and key components based on the initial health Real-time calculation of the health correction coefficient of key components, the determination formula is as follows: Where: ω(t): correction coefficient; Natural deterioration coefficient; t0: initial health calculation time node; Using the key component number as the query condition, the correction coefficient of the kth key component in the database is updated regularly, the workload coefficient f2 is calculated and updated on an annual basis, and the temperature field coefficient f4 is automatically selected on a quarterly basis; Step 8: Calculate the dynamically corrected health H of the kth key component k ; Query the health of the kth key component before correction based on the key component number H kf and the correction coefficient ω(t) at time t; Combining the health before correction and the correction coefficient at time t, online real-time calculation is performed, and the judgment formula is as follows: H k =H kf ·ω(t) Where: H k : The health of the kth key component after dynamic correction; H kf : The health of the kth key component before correction; ω(t): correction coefficient at time t; Using the key component number as the query condition, the health of the kth key component in the database is corrected and updated, and the health status label is assigned as corrected; Step 9: Calculate the health of the generator set H g ; Using the generator set number as the query condition, the generator set health assessment index system is obtained from the database, and the H1...H N The health of key components; Obtain the health of key components in the generator set health assessment index system, and use the principle that the lowest score of key components represents the health of the generator set. The judgment formula is as follows: H g =min{H1···H N } Where: H g : Generator health; H1: Health of the first key component; H N : The health of the Nth key component; Using the generator set number as the query condition, the health of the generator sets in the database is regularly updated; Step 10: Divide the range of health evaluation indicators of the generator set, and the evaluation indicators describe the operating status of the unit; Obtain the generator set operating status evaluation index range and the health of the generator set from the database; The health of the generator set is screened and matched with the range of the status evaluation index. The judgment formula is as follows: Where: H g : Generator health; The health assessment results can be calculated and the operating status of the generator set can be determined.

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