Unit commissioning phase equipment health state monitoring method and device, equipment and medium

Abstract

The application discloses a kind of nuclear power unit debugging start-up phase equipment health state monitoring method, device, electronic equipment and readable storage medium, applied to nuclear power plant equipment state monitoring technical field.Therein, method includes based on the target measuring point of the equipment of nuclear power unit debugging start-up phase condition change data, determines the current operating condition of equipment;Monitoring equipment operating condition, to obtain the current operating parameter of equipment and the alarm data made by equipment response exception;According to current operating condition, current operating parameter and alarm data determine the health state of equipment.The present application can realize the precise monitoring of the health state of nuclear power unit debugging start-up phase equipment.

Description

Technical Field

[0001] This application relates to the field of nuclear power plant equipment condition monitoring technology, and in particular to a method, device, electronic equipment and readable storage medium for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit. Background Technology

[0002] A nuclear power unit is a basic power generation unit consisting of a reactor, its associated turbine generator set, and the systems and facilities required to maintain normal operation and ensure safety. The stable operation phase of a nuclear power plant is currently the focus of equipment condition monitoring. However, the commissioning and startup phase is characterized by a large number of test projects, complex equipment conditions, interwoven test logic, and stringent operating parameters, making equipment risk control during commissioning particularly challenging. Currently, the analysis and evaluation of specific multi-system and transient unit operations are typically conducted by the test supervisor based on the technical requirements of the commissioning outline and test procedures, combined with transient processes and historical test data. This monitoring process is discontinuous and delayed. Consequently, during the commissioning and startup testing of a nuclear power unit, improper control parameter settings, thermodynamic performance mismatches, and other factors can easily lead to unplanned reactor shutdowns, major equipment damage, and other accidents. This is especially problematic for new projects, first-time adopters of new technologies, or nuclear power units undergoing significant design improvements.

[0003] Therefore, accurately monitoring the health status of equipment during the commissioning and startup phase of nuclear power units is a technical problem that needs to be solved by technicians in this field. Summary of the Invention

[0004] This application provides a method, apparatus, electronic device, and readable storage medium for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit, which can achieve accurate monitoring of the health status of equipment during the commissioning and startup phase of a nuclear power unit.

[0005] To solve the above-mentioned technical problems, this application provides the following technical solution:

[0006] This application provides a method for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit, including:

[0007] Based on the operating condition change data of the target measuring points of the equipment during the commissioning and startup phase of the nuclear power unit, the current operating condition of the equipment is determined.

[0008] Monitor the operation of the equipment to obtain the current operating parameters of the equipment and the alarm data generated by the equipment in response to abnormalities;

[0009] The health status of the device is determined based on the current operating conditions, the current operating parameters, and the alarm data.

[0010] Optionally, determining the current operating condition of the equipment based on the operating condition change data of the target measuring points of the equipment during the commissioning and startup phase of the nuclear power unit includes:

[0011] Acquire historical data of the target measurement point from the current moment forward by a preset time window width;

[0012] Calculate the rate of change of the measurement points within the current window;

[0013] If the rate of change is greater than or equal to the preset benchmark rate of change, then all data in the current window are the operating condition change point data at the current moment;

[0014] The data of all operating condition change points of the target measuring point are spliced ​​together in chronological order to form operating condition change segment data;

[0015] The dynamic time planning algorithm is invoked to calculate the shape similarity between the operating condition change segment data and the historical data of each operating condition of the equipment, and the operating condition with the highest similarity is taken as the current operating condition of the equipment.

[0016] Optionally, the step of stitching together all the operating condition change point data of the target measuring point in chronological order into operating condition change segment data includes:

[0017] If the rate of change of the measured point data within the current window at the current moment is less than the preset baseline rate of change, then the operating condition change point data of all moments before the current moment will be spliced ​​together in chronological order to form operating condition change segment data.

[0018] Optionally, monitoring the operation of the device includes:

[0019] The operating status data of the device from the starting point of the current operating condition change to the starting point of the next operating condition change is obtained as the operating status data of the current operating condition. The operating status data includes operating condition change segment data and stable operating condition data.

[0020] Based on the pre-set multi-level and multi-class weighted alarm mechanism for stable operating conditions under the current operating conditions, corresponding stable operating condition alarm events are generated according to the stable operating condition data obtained during the monitoring process.

[0021] Based on the pre-set upper limit of the rate of change threshold of the measuring points under the current working condition, a corresponding alarm event for the changing working condition is generated according to the data of the changing working condition segments obtained during the monitoring process.

[0022] The alarm data is obtained by statistically analyzing the alarm events under stable operating conditions and the alarm events under changing operating conditions.

[0023] Optionally, determining the health status of the device based on the current operating conditions, the current operating parameters, and the alarm data includes:

[0024] Using the operating condition as the vertical axis and the measuring point as the horizontal axis, a weighted scoring matrix for assessing the health status of the equipment is generated, and the measuring points under each operating condition are scored and rated according to the degree of influence of different measuring points on the operating condition.

[0025] The alarm weight value of each measuring point is determined based on the importance level value of each measuring point and the alarm data of the current measuring point.

[0026] The original score value in the health status assessment weight scoring matrix is ​​updated based on the alarm weight value of each measuring point;

[0027] Based on the importance of each operating condition's impact on the health status of the equipment and the updated health status assessment weight scoring matrix, the operating condition weight value for each operating condition's impact on the health status of the equipment is determined.

[0028] The health status value of the equipment is determined based on the operating time of the equipment under different operating conditions and the operating condition weight value of each operating condition;

[0029] The health status of the device is obtained by comparing the health status value with the pre-set device health status standard information.

[0030] Optionally, determining the weight value of each operating condition's impact on the equipment's health status based on the importance of each operating condition's influence on the equipment's health status and the updated health status assessment weight scoring matrix includes:

[0031] The order relationship between each operating condition is determined based on the importance of its impact on the health status of the equipment, and the importance ratio between adjacent operating conditions is determined based on the order relationship.

[0032] Based on the aforementioned importance ratio, the subjective evaluation weight value for each working condition is calculated sequentially.

[0033] Based on the updated health status assessment weight scoring matrix, the proportion of each measuring point in each working condition is calculated;

[0034] For each working condition, the entropy weight of the current working condition is calculated based on the proportion of each measuring point in the current working condition;

[0035] Based on the subjective evaluation weight value and entropy weight of each working condition, the working condition weight value of the impact of each working condition on the health status of the equipment is calculated.

[0036] Optionally, determining the health status value of the equipment based on the operating time of the equipment under different operating conditions and the operating condition weight value of each operating condition includes:

[0037] The health status index calculation formula is invoked to calculate the health status value of the equipment based on the equipment's operating time under different operating conditions and the operating condition weight value of each operating condition; the health status index calculation formula is:

[0038]

[0039] In the formula, E s Here, e is the health status value of the device, and H is the exponent. i Let t be the weight value of the i-th working condition, t be the running time of the i-th working condition, and α be the correction coefficient.

[0040] Another aspect of this application provides a device for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit, comprising:

[0041] The operating condition identification module is used to determine the current operating condition of the equipment based on the operating condition change data of the target measuring points of the equipment during the commissioning and startup phase of the nuclear power unit.

[0042] The status monitoring module is used to monitor the operation of the device to obtain the current operating parameters of the device and the alarm data generated by the device in response to abnormalities.

[0043] The health status determination module is used to determine the health status of the device based on the current operating conditions, the current operating parameters, and the alarm data.

[0044] This application also provides an electronic device including a processor, which executes a computer program stored in a memory to implement the steps of the equipment health status monitoring method for the commissioning and startup phase of a nuclear power unit as described in any of the preceding claims.

[0045] Finally, this application also provides a readable storage medium storing a computer program that, when executed by a processor, implements the steps of the equipment health status monitoring method for the commissioning and startup phase of a nuclear power unit as described in any of the preceding claims.

[0046] The advantages of the technical solution provided in this application are that, in response to the problems of complex changes in operating conditions and discontinuous monitoring during the commissioning phase of nuclear power units, it comprehensively considers the impact of multiple operating conditions, multiple measuring points, and multiple parameters on the operating conditions of the equipment. This enables accurate monitoring of the health status of equipment during the commissioning and startup phase of nuclear power units, facilitating effective control, tracking, and evaluation of the power plant's operating status. The solution is simple to implement, reliable, and highly practical.

[0047] Furthermore, this application also provides a corresponding implementation device, electronic device, and readable storage medium for the equipment health status monitoring method during the commissioning and startup phase of a nuclear power unit, further making the method more practical. The device, electronic device, and readable storage medium have corresponding advantages.

[0048] It should be understood that the above general description and the following detailed description are merely exemplary and do not limit this application. Attached Figure Description

[0049] To more clearly illustrate the technical solutions of this application or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 A flowchart illustrating a method for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit, as provided in this application;

[0051] Figure 2 A structural diagram of a specific embodiment of the equipment health status monitoring device for the commissioning and startup phase of a nuclear power unit provided in this application;

[0052] Figure 3 A structural diagram of one specific embodiment of the electronic device provided in this application. Detailed Implementation

[0053] To enable those skilled in the art to better understand the present application, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only a part of the embodiments of the present application, and not all of them. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of the present application. The terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of the present application are intended to cover non-exclusive inclusion. The term "exemplary" means "used as an example, embodiment, or illustration." Any embodiment described herein as "exemplary" is not necessarily to be construed as superior to or better than other embodiments. Various non-limiting embodiments of the present application are described in detail below. To better illustrate the present application, numerous specific details are set forth in the following detailed description. Those skilled in the art should understand that the present application can be practiced without these specific details. In other instances, methods, means, elements, and circuits well known to those skilled in the art have not been described in detail in order to highlight the main points of the present application.

[0054] Please see first. Figure 1 , Figure 1 This application provides a flowchart illustrating a method for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit. This application may include the following:

[0055] S101: Determine the current operating condition of the equipment based on the operating condition change data of the target measuring points of the equipment during the commissioning and startup phase of the nuclear power unit.

[0056] In this embodiment, the equipment is in the commissioning and startup phase of the nuclear power unit. The equipment will operate under different operating conditions. For each operating condition, multiple measuring points that are crucial to the equipment's operation can be selected. The target measuring point is one or more of these multiple measuring points. The selection criterion is that the measuring point can accurately reflect the changes in the equipment's operating conditions. For ease of description, such measuring points that can accurately reflect the changes in the equipment's operating conditions are defined as target measuring points. The equipment operation is continuous and uninterrupted. The equipment's operating state from the current starting point of the operating condition change to the next starting point of the operating condition change belongs to the same operating condition. Operating condition change data refers to the operating data when the operating condition changes.

[0057] S102: Monitor the operation of the equipment to obtain the current operating parameters of the equipment and alarm data generated when the equipment responds to abnormalities.

[0058] This step is used to monitor the status of the equipment and collect the operating data of each measuring point under different operating conditions. Different alarm mechanisms are set for each measuring point according to different operating conditions. When the equipment is abnormal, an alarm event is generated in response to the equipment abnormality. The alarm data is the data of all alarm events.

[0059] S103: Determine the health status of the equipment based on the current operating conditions, current operating parameters, and alarm data.

[0060] Because the operating conditions of nuclear power units change complexly during the commissioning and startup phase, and the equipment operates discontinuously during monitoring, this step, by integrating the data from the first two steps, which have obtained data on multiple operating conditions, multiple measuring points, and multiple parameters that affect the health status of the equipment, can accurately determine the health status of the equipment during the commissioning and startup phase of a nuclear power unit.

[0061] The technical solution provided in this application addresses the problem of complex changes in operating conditions and discontinuous monitoring during the commissioning and startup phase of nuclear power units. It comprehensively considers the impact of multiple operating conditions, multiple measuring points, and multiple parameters on the operating conditions of the equipment, thereby enabling accurate monitoring of the health status of equipment during the commissioning and startup phase of nuclear power units. This facilitates effective control, tracking, and evaluation of the power plant's operating status, and the process is simple, easy to operate, reliable, and highly practical.

[0062] In the above embodiments, no limitation is made on how to determine the current operating condition of the equipment. This embodiment also provides an exemplary implementation for identifying the equipment operating condition, which may include the following steps:

[0063] Acquire historical data of the target measuring point from the current moment forward for a length equal to the width of a preset time window; calculate the rate of change of the measuring point data within the current window; if the rate of change is greater than or equal to the preset baseline rate of change, then all data within the current window are the operating condition change point data at the current moment; stitch all the operating condition change point data of the target measuring point into operating condition change segment data in chronological order; call the dynamic time planning algorithm to calculate the shape similarity between the operating condition change segment data and the historical data of each operating condition of the equipment, and take the operating condition with the highest similarity as the current operating condition of the equipment.

[0064] In this embodiment, the data segments of the equipment under all operating conditions are organized and their characteristic attributes are set, including: selecting m measurement points that are crucial to the operation of the equipment under each operating condition; setting different alarm thresholds for each measurement point under different operating conditions; classifying the importance of each operating condition to the health status of the equipment; and selecting target measurement points that can accurately reflect changes in the equipment's operating conditions. The time window width w and the baseline rate of change r for detecting changes in operating conditions are defined. The data processing procedure for the data obtained from the system is as follows: the system automatically obtains historical data of the equipment measurement points from the current moment forward by a length equal to the time window width w, and calculates the rate of change r of the measurement point data within this window. w =Δd / w, where Δd is the absolute value of the difference between the final value and the initial value of the data within the current window. For measuring points that can reflect changes in the operating conditions of the equipment, if the rate of change r w If the rate of change is greater than or equal to the baseline rate of change r, then all data within that window are marked as operating condition change point data. As time progresses, new operating condition data for the equipment is continuously generated. When the time duration of the new data exceeds w, the above data processing process is repeated until r is reached. w If the rate of change of the measured data within the current window is less than the preset baseline rate of change, then the data of the operating condition changes from all previous times are concatenated in chronological order to form the operating condition change segment s. Finally, based on the Dynamic Time Warping (DTW) algorithm, the shape similarity between the current operating condition change segment s and each historical operating condition data segment of the equipment can be calculated, and the segment with the highest similarity is taken as the operating condition of the same type. Of course, other methods can also be used to calculate the similarity, which does not affect the implementation of this application.

[0065] As can be seen from the above, this embodiment determines the operating condition change data by using the time window width and the baseline change rate for detecting operating condition changes, and calculates the similarity using a dynamic time planning algorithm, which can accurately identify the operating conditions of the equipment.

[0066] In the above embodiments, no limitation is made on the device status monitoring method. This embodiment also provides an exemplary implementation method for device status monitoring, which may include the following:

[0067] The system acquires operational status data of the equipment from the starting point of the current operating condition change to the starting point of the next operating condition change, which serves as the operational status data for the current operating condition. This operational status data includes operating condition change segment data and stable operating condition data. Based on a pre-set multi-level and multi-class weighted alarm mechanism for stable operating conditions under the current operating condition, corresponding stable operating condition alarm events are generated according to the stable operating condition data acquired during the monitoring process. Based on a pre-set upper limit of the change rate threshold of the measuring points under the current operating condition, corresponding changing operating condition alarm events are generated according to the operating condition change segment data acquired during the monitoring process. Alarm data is obtained by statistically analyzing stable operating condition alarm events and changing operating condition alarm events.

[0068] In this embodiment, since the equipment operation is continuous and uninterrupted, the equipment operating status from the current operating condition change point to the next operating condition change point belongs to the same operating condition. Under the same operating condition, the data is divided into operating condition change segment data and stable operating condition data. Different methods are used to determine equipment abnormalities under changing and steady-state operating conditions. This embodiment establishes a multi-level, multi-category weighted alarm mechanism for steady-state operating conditions, that is, setting multiple alarm types, and different types of alarms can be assigned weights simultaneously. For example, for steady-state operating data, six levels of fixed threshold alarms and six levels of dynamic threshold alarms can be set. For fixed threshold alarms, the fixed thresholds are set as [low low alarm, low alarm, low warning, high warning, high alarm, high high alarm], and the corresponding alarm weights are [c, b, a, a, b, c]. For dynamic threshold alarms, the dynamic thresholds are set as [low warning value k2 times, low warning value k1 times, low warning value, high warning value, high warning value k1 times, high warning value k2 times], and the corresponding alarm weights are [f, e, d, d, e, f]. Then the combined weight sequence h = [d, e, f, a, b, c], and the weight values ​​increase sequentially. For the set thresholds, a dynamic threshold lower threshold k² times the fixed threshold lower warning value is greater than or equal to the fixed threshold lower warning value, and a dynamic threshold higher threshold k² times the fixed threshold higher warning value is less than or equal to the fixed threshold higher warning value. The system alarms when a certain number of measuring point values ​​exceed the threshold. For data segments showing changes in operating conditions, this embodiment combines the physical characteristics of the measuring points and sets an upper limit r for the rate of change of the measuring points. u r w ≥r uThe system will then issue an alarm, and the alarm weight can be set to b. The weight values ​​a, b, c, d, e, f, as well as k2 and k1, can be flexibly selected and assigned according to the actual situation, as long as the aforementioned numerical relationship constraints are met. This application does not impose any restrictions on this.

[0069] As can be seen from the above, this embodiment improves the detection accuracy of equipment abnormalities and thus enhances the accuracy of judging the health status of the equipment by setting different alarm mechanisms for stable and changing operating conditions.

[0070] In the above embodiments, no limitation is made on how to determine the health status of the device. This embodiment also provides an exemplary implementation of the device health status, which may include the following steps:

[0071] Using operating conditions as the ordinate and measuring points as the abscissa, a health status assessment weighted scoring matrix for the equipment is generated. Measuring points under each operating condition are scored and rated according to their influence on the operating conditions. The alarm weight value for each measuring point is determined based on its importance level and current alarm data. The original scores in the health status assessment weighted scoring matrix are updated based on the alarm weight values ​​of each measuring point. The operating condition weight value for each operating condition is determined based on its importance in influencing the equipment's health status and the updated health status assessment weighted scoring matrix. The equipment's health status value is determined based on the equipment's runtime under different operating conditions and the operating condition weight value for each condition. The equipment's health status is obtained by comparing the health status value with pre-set equipment health status standards.

[0072] In this embodiment, if there are n operating conditions and m measuring points, the equipment health status assessment weighted scoring matrix S, with the operating conditions as the vertical axis and the measuring points as the horizontal axis, has a size of n*m. The measuring points are scored and rated according to their importance to the operating conditions, with scores divided into 5 levels, from 1 to 5 representing the least important to the most important. The health status assessment weighted scoring matrix S is then updated by weighting the scores in the matrix. Specifically, if a measuring point currently triggers an alarm, its score = original score × alarm weight value μ. The alarm weight value is calculated as follows: if the importance level of the measuring point is g, then the alarm event weight sequence h′ = g × h. If the current measuring point triggers an alarm, its alarm weight μ ∈ h′. When no alarm occurs at the measuring point, μ = 1. To further improve the accuracy of subsequent data processing, the weighted scoring matrix is ​​normalized after updating. To facilitate standardization and improve practicality, equipment health levels can be predefined, and the range of health status indexes for each level can be given as standard information for equipment health status, as shown in Table 1. After calculating the health status value, the equipment health status level can be determined by seeing which range of the health status value it falls within.

[0073] Table 1 Equipment Health Status Assessment Level Table

[0074]

[0075]

[0076] As an exemplary embodiment, this embodiment also provides a method for calculating the working condition weight value, which may include the following:

[0077] The order relationship between operating conditions is determined based on the importance of each operating condition's impact on the equipment's health status, and the importance ratio between adjacent operating conditions is determined based on the order relationship. Based on the importance ratio, the subjective evaluation weight value of each operating condition is calculated sequentially. Based on the updated health status assessment weight scoring matrix, the proportion of each measuring point in each operating condition is calculated. For each operating condition, the entropy weight of the current operating condition is calculated based on the proportion of each measuring point in the current operating condition. Based on the subjective evaluation weight value and entropy weight of each operating condition, the operating condition weight value of each operating condition's impact on the equipment's health status is calculated.

[0078] In this embodiment, the order relationship between each operating condition can be determined based on the importance of its impact on the equipment's health status. For example, it can be represented as C1 > C2 > C3 > ... > C n Where n is the total number of operating conditions, and C represents the order relationship. Based on the order relationship between operating conditions, the importance ratio r between adjacent operating conditions can be determined. kLet k = 2, 3, ..., n. For each working condition, first calculate the information entropy value of the current working condition based on the proportion of each measuring point in the current working condition, and then calculate the entropy weight of the current working condition based on the information entropy value. The subjective evaluation weight w of the k-th working condition can be calculated by calling the subjective evaluation weight calculation formula. k Then based on w k-1 =w k ×r k The subjective evaluation weight for the (k-1)th working condition can be calculated using the following formula:

[0079]

[0080] The formula for calculating the proportion of each measuring point in each working condition can be called to calculate the proportion p. ij The formula for calculating the proportion of the measuring points is expressed as:

[0081]

[0082] Among them, s ij For the normalized measurement score of the j-th measurement point under the i-th working condition, the information entropy value e of the i-th working condition is calculated using the information entropy calculation formula. i The formula for calculating information entropy can be expressed as:

[0083]

[0084] The entropy weight calculation formula can be invoked to calculate the entropy weight v in each working condition. i The entropy weight calculation formula can be expressed as:

[0085]

[0086] The weight calculation formula can be invoked to calculate the final weight H of the impact on the equipment health status under each operating condition. i The weight calculation formula can be expressed as:

[0087]

[0088] As an exemplary embodiment, after determining the weight values ​​of each operating condition, the equipment health status in this embodiment is related to the current operating condition of the equipment and the runtime under the current operating condition. The health status index calculation formula can be invoked to calculate the equipment's health status value based on the runtime of the equipment under different operating conditions and the weight values ​​of each operating condition. The health status index calculation formula is:

[0089]

[0090] In the formula, E s The health status value of the device, e is the exponent, H iLet t be the weight value of the i-th working condition, t be the running time of the i-th working condition, and α be the correction coefficient.

[0091] It should be noted that there is no strict order of execution for the steps in this application. As long as they conform to a logical order, these steps can be executed simultaneously or in a certain preset order. Figure 1 This is just an illustrative example and does not mean that this is the only possible execution order.

[0092] This application also provides a corresponding device for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit, further enhancing the practicality of the method. The device can be described from both a functional module perspective and a hardware perspective. The following describes the device for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit provided in this application. This device is used to implement the method for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit provided in this application. In this embodiment, the device may include or be divided into one or more program modules. These program modules are stored in a storage medium and executed by one or more processors, thus completing the method for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit disclosed in Embodiment 1. The program module referred to in this application is a series of computer program instruction segments capable of performing specific functions, which are more suitable than the program itself for describing the execution process of the device for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit in the storage medium. The following description will specifically introduce the functions of each program module in this embodiment. The device for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit described below can be referred to in correspondence with the method for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit described above.

[0093] From the perspective of functional modules, see Figure 2 , Figure 2 A structural diagram of the equipment health status monitoring device for the commissioning and startup phase of a nuclear power unit provided in this application, in one specific embodiment, shows that the device may include:

[0094] The operating condition identification module 201 is used to determine the current operating condition of the equipment based on the operating condition change data of the target measuring points of the equipment during the commissioning and startup phase of the nuclear power unit.

[0095] The status monitoring module 202 is used to monitor the operation of the equipment in order to obtain the current operating parameters of the equipment and the alarm data generated by the equipment in response to abnormalities.

[0096] The health status determination module 203 is used to determine the health status of the equipment based on the current operating conditions, current operating parameters, and alarm data.

[0097] Optionally, in some embodiments of this example, the above-mentioned operating condition identification module 201 can also be used to: acquire historical data of the target measuring point from the current moment forward with a length equal to the width of a preset time window; calculate the rate of change of the measuring point data within the current window; if the rate of change is greater than or equal to the preset baseline rate of change, then all data within the current window are the operating condition change point data at the current moment; splice all the operating condition change point data of the target measuring point into operating condition change segment data in chronological order; call a dynamic time planning algorithm to calculate the shape similarity between the operating condition change segment data and the historical data of each operating condition of the equipment, and take the operating condition with the highest similarity as the current operating condition of the equipment.

[0098] As an optional implementation of the above embodiments, the above-mentioned working condition identification module 201 can be further used to: if the rate of change of the measured point data in the current window at the current moment is less than the preset benchmark rate of change, then the working condition change point data of all moments before the current moment are spliced ​​together in chronological order to form working condition change segment data.

[0099] Optionally, in some other embodiments of this example, the status monitoring module 202 may also be used to: acquire the operating status data of the equipment from the starting point of the current operating condition change to the starting point of the next operating condition change, as the operating status data of the current operating condition, the operating status data including operating condition change segment data and stable operating condition data; generate corresponding stable operating condition alarm events based on the stable operating condition data acquired during the monitoring process according to a pre-set multi-level and multi-class weighted alarm mechanism for stable operating conditions under the current operating condition; generate corresponding changing operating condition alarm events based on the operating condition change segment data acquired during the monitoring process according to a pre-set upper limit of the change rate threshold of the measuring points under the current operating condition; and obtain alarm data by statistically analyzing stable operating condition alarm events and changing operating condition alarm events.

[0100] Optionally, in some further embodiments of this example, the health status determination module 203 may also be used to: generate a health status assessment weight scoring matrix for the equipment with the operating condition as the vertical axis and the measuring point as the horizontal axis, and score and rate the measuring points under each operating condition according to the degree of influence of different measuring points on the operating condition; determine the alarm weight value of each measuring point based on the importance level value of each measuring point and the alarm data of the current measuring point; update the original score value in the health status assessment weight scoring matrix based on the alarm weight value of each measuring point; determine the operating condition weight value of each operating condition on the health status of the equipment based on the importance of the influence of each operating condition on the health status of the equipment and the updated health status assessment weight scoring matrix; determine the health status value of the equipment based on the running time of the equipment under different operating conditions and the operating condition weight value of each operating condition; and obtain the health status of the equipment by comparing the health status value with the pre-set equipment health status standard information.

[0101] As an optional implementation of the above embodiments, the health status determination module 203 can be further used to: determine the order relationship between each working condition based on the importance of the influence of each working condition on the health status of the equipment, and determine the importance ratio between adjacent working conditions based on the order relationship; calculate the subjective evaluation weight value of each working condition in sequence based on the importance ratio; calculate the proportion of each measuring point in each working condition based on the updated health status assessment weight scoring matrix; calculate the entropy weight of the current working condition based on the proportion of each measuring point in the current working condition for each working condition; and calculate the working condition weight value of the influence of each working condition on the health status of the equipment based on the subjective evaluation weight value and entropy weight of each working condition.

[0102] As another optional implementation of the above embodiments, the health status determination module 203 can be further used to: call the health status index calculation formula, and calculate the health status value of the equipment based on the running time of the equipment under different operating conditions and the operating condition weight value of each operating condition; the health status index calculation formula is:

[0103]

[0104] In the formula, E s The health status value of the device, e is the exponent, H i Let t be the weight value of the i-th working condition, t be the running time of the i-th working condition, and α be the correction coefficient.

[0105] The functions of each module of the equipment health status monitoring device during the commissioning and startup phase of the nuclear power unit in this application can be specifically implemented according to the methods in the above method embodiments. The specific implementation process can be referred to the relevant descriptions in the above method embodiments, which will not be repeated here.

[0106] As can be seen from the above, this embodiment can achieve accurate monitoring of the health status of equipment during the commissioning and startup phase of a nuclear power unit.

[0107] The equipment health status monitoring device mentioned above during the commissioning and startup phase of a nuclear power unit is described from the perspective of functional modules. Furthermore, this application also provides an electronic device, which is described from the perspective of hardware. Figure 3 This is a schematic diagram of the structure of the electronic device provided in one embodiment of this application. For example... Figure 3 As shown, the electronic device includes a memory 30 for storing a computer program; and a processor 31 for executing the computer program to implement the steps of the equipment health status monitoring method during the commissioning and startup phase of a nuclear power unit as described in any of the above embodiments.

[0108] The processor 31 may include one or more processing cores, such as a quad-core processor or an octa-core processor. The processor 31 may also be a controller, microcontroller, microprocessor, or other data processing chip. The processor 31 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 31 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, the processor 31 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, the processor 31 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0109] The memory 30 may include one or more computer-readable storage media, which may be non-transitory. The memory 30 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the memory 30 may be an internal storage unit of an electronic device, such as a server hard drive. In other embodiments, the memory 30 may be an external storage device of an electronic device, such as a plug-in hard drive on a server, a Smart Media Card (SMC), a Secure Digital (SD) card, or a Flash Card. Furthermore, the memory 30 may include both internal and external storage units of the electronic device. The memory 30 can be used not only to store application software and various types of data installed in the electronic device, such as code in a program executing a method for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit, but also to temporarily store data that has been output or will be output. In this embodiment, the memory 30 is used to store at least the following computer program 301, which, after being loaded and executed by the processor 31, is capable of implementing the relevant steps of the equipment health status monitoring method during the commissioning and startup phase of a nuclear power unit disclosed in any of the foregoing embodiments. Additionally, the resources stored in the memory 30 may also include an operating system 302 and data 303, and the storage method may be temporary or permanent storage. The operating system 302 may include Windows, Unix, Linux, etc. The data 303 may include, but is not limited to, data corresponding to the equipment health status monitoring results during the commissioning and startup phase of a nuclear power unit.

[0110] In some embodiments, the aforementioned electronic device may further include a display screen 32, an input / output interface 33, a communication interface 34 (or network interface), a power supply 35, and a communication bus 36. The display screen 32 and input / output interface 33, such as a keyboard, are user interfaces; optional user interfaces may also include standard wired interfaces, wireless interfaces, etc. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a display screen or display unit, used to display information processed in the electronic device and to display a visual user interface. The communication interface 34 may optionally include a wired interface and / or a wireless interface, such as a Wi-Fi interface, a Bluetooth interface, etc., typically used to establish communication connections between the electronic device and other electronic devices. The communication bus 36 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. This bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0111] Those skilled in the art will understand that Figure 3 The structure shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, such as sensors 37 that perform various functions.

[0112] The functions of each functional module of the electronic device of this application can be specifically implemented according to the methods in the above method embodiments. The specific implementation process can be referred to the relevant descriptions in the above method embodiments, which will not be repeated here.

[0113] As can be seen from the above, this embodiment can achieve accurate monitoring of the health status of equipment during the commissioning and startup phase of a nuclear power unit.

[0114] It is understood that if the equipment health status monitoring method during the commissioning and startup phase of a nuclear power unit in the above embodiments is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the related technology, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and executes all or part of the steps of the methods in the various embodiments of this application. The aforementioned storage medium includes: USB flash drive, mobile hard drive, read-only memory (ROM), random access memory (RAM), electrically erasable programmable ROM, register, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, removable disk, CD-ROM, magnetic disk or optical disk, and other media capable of storing program code.

[0115] Based on this, this application also provides a readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the steps of the equipment health status monitoring method during the commissioning and startup phase of a nuclear power unit as described in any of the above embodiments are provided.

[0116] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the hardware disclosed in the embodiments, including devices and electronic equipment, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0117] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0118] The foregoing has provided a detailed description of a method, apparatus, electronic device, and readable storage medium for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit, as provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are merely for the purpose of helping to understand the method and its core ideas. It should be noted that those skilled in the art can make various improvements and modifications to this application without departing from its principles, and these improvements and modifications also fall within the protection scope of the claims of this application.

Claims

1. A method for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit, characterized in that, include: Based on the operating condition change data of the target measuring points of the equipment during the commissioning and startup phase of the nuclear power unit, the current operating condition of the equipment is determined. Monitor the operation of the equipment to obtain the current operating parameters of the equipment and the alarm data generated by the equipment in response to abnormalities; The health status of the device is determined based on the current operating conditions, the current operating parameters, and the alarm data. The determination of the current operating condition of the equipment based on the operating condition change data of the target measuring points of the equipment during the commissioning and startup phase of the nuclear power unit includes: Acquire historical data of the target measurement point from the current moment forward by a preset time window width; Calculate the rate of change of the measurement points within the current window; If the rate of change is greater than or equal to the preset benchmark rate of change, then all data in the current window are the operating condition change point data at the current moment; The data of all operating condition change points of the target measuring point are spliced ​​together in chronological order to form operating condition change segment data; The dynamic time planning algorithm is called to calculate the shape similarity between the operating condition change segment data and the historical data of each operating condition of the equipment, and the operating condition with the highest similarity is taken as the current operating condition of the equipment. The monitoring of the device's operation includes: The operating status data of the device from the starting point of the current operating condition change to the starting point of the next operating condition change is obtained as the operating status data of the current operating condition. The operating status data includes operating condition change segment data and stable operating condition data. Based on the pre-set multi-level and multi-class weighted alarm mechanism for stable operating conditions under the current operating conditions, corresponding stable operating condition alarm events are generated according to the stable operating condition data obtained during the monitoring process. Based on the pre-set upper limit of the change rate threshold of the measuring points under the current working condition, a corresponding alarm event for the changing working condition is generated according to the data of the changing working condition segments obtained during the monitoring process. The alarm data is obtained by statistically analyzing the alarm events under stable operating conditions and the alarm events under changing operating conditions.

2. The method for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit according to claim 1, characterized in that, The step of stitching together all the operating condition change point data of the target measuring point in chronological order to form operating condition change segment data includes: If the rate of change of the measured point data within the current window at the current moment is less than the preset baseline rate of change, then the operating condition change point data of all moments before the current moment will be spliced ​​together in chronological order to form operating condition change segment data.

3. The method for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit according to claim 1 or 2, characterized in that, Determining the health status of the device based on the current operating conditions, the current operating parameters, and the alarm data includes: Using the operating condition as the vertical axis and the measuring point as the horizontal axis, a weighted scoring matrix for assessing the health status of the equipment is generated, and the measuring points under each operating condition are scored and rated according to the degree of influence of different measuring points on the operating condition. The alarm weight value of each measuring point is determined based on the importance level value of each measuring point and the alarm data of the current measuring point. The original score value in the health status assessment weight scoring matrix is ​​updated based on the alarm weight value of each measuring point; Based on the importance of each operating condition's impact on the health status of the equipment and the updated health status assessment weight scoring matrix, the operating condition weight value for each operating condition's impact on the health status of the equipment is determined. The health status value of the equipment is determined based on the operating time of the equipment under different operating conditions and the operating condition weight value of each operating condition; The health status of the device is obtained by comparing the health status value with the pre-set device health status standard information.

4. The method for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit according to claim 3, characterized in that, The determination of the weight value of each operating condition on the health status of the equipment, based on the importance of the impact of each operating condition on the health status of the equipment and the updated health status assessment weight scoring matrix, includes: The order relationship between each operating condition is determined based on the importance of its impact on the health status of the equipment, and the importance ratio between adjacent operating conditions is determined based on the order relationship. Based on the aforementioned importance ratio, the subjective evaluation weight value for each working condition is calculated sequentially. Based on the updated health status assessment weight scoring matrix, the proportion of each measuring point in each working condition is calculated; For each working condition, the entropy weight of the current working condition is calculated based on the proportion of each measuring point in the current working condition; Based on the subjective evaluation weight value and entropy weight of each working condition, the working condition weight value of the impact of each working condition on the health status of the equipment is calculated.

5. The method for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit according to claim 3, characterized in that, The step of determining the health status value of the equipment based on the operating time of the equipment under different operating conditions and the operating condition weight value of each operating condition includes: The health status index calculation formula is invoked to calculate the health status value of the equipment based on the equipment's operating time under different operating conditions and the operating condition weight value of each operating condition; the health status index calculation formula is: ； In the formula, E s Here, e is the health status value of the device, and H is the exponent. i Let t be the weight value of the i-th working condition, t be the running time of the i-th working condition, and α be the correction coefficient.

6. A device for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit, characterized in that, The method for monitoring the health status of equipment during the commissioning and startup phase of a nuclear power unit, as described in any one of claims 1 to 5, includes: The operating condition identification module is used to determine the current operating condition of the equipment based on the operating condition change data of the target measuring points of the equipment during the commissioning and startup phase of the nuclear power unit. The status monitoring module is used to monitor the operation of the device to obtain the current operating parameters of the device and the alarm data generated by the device in response to abnormalities. The health status determination module is used to determine the health status of the device based on the current operating conditions, the current operating parameters, and the alarm data.

7. An electronic device, characterized in that, It includes a processor and a memory, wherein the processor is used to execute a computer program stored in the memory to implement the steps of the equipment health status monitoring method for the commissioning and startup phase of a nuclear power unit as described in any one of claims 1 to 5.

8. A readable storage medium, characterized in that, The readable storage medium stores a computer program that, when executed by a processor, implements the steps of the equipment health status monitoring method for the commissioning and startup phase of a nuclear power unit as described in any one of claims 1 to 5.

Images