Equipment risk identification method and device, equipment, medium and product

Abstract

The invention discloses an equipment risk identification method and device, equipment, a medium and a product. The method comprises the following steps: in response to a risk identification request for target equipment, obtaining equipment operation parameters and equipment operation records of the target equipment; determining a device service level corresponding to the target device; determining an equipment health state of the target equipment according to the equipment operation record; determining a state change level of the target equipment according to the equipment operation parameters and the equipment service level; and generating a risk identification result of the target equipment according to the equipment health state and the state change level. According to the scheme of the embodiment, the equipment risk identification result of the target equipment can be generated according to the acquired equipment operation parameters, equipment operation records and equipment service levels of the target equipment, so that the acquisition efficiency and comprehensiveness of the equipment risk identification data are improved, and the identification efficiency and accuracy of the equipment risk are improved.

Description

Technical Field

[0001] This invention relates to the field of nuclear energy equipment health management technology, and in particular to a method, apparatus, equipment, medium and product for identifying equipment risks. Background Technology

[0002] With the continuous improvement of industrialization, the application scale of nuclear energy equipment is also increasing. Due to the special nature of nuclear energy equipment and the complexity of the operating environment, equipment health management, which identifies equipment risks, has become the key to ensuring the safe and reliable operation of nuclear energy equipment.

[0003] However, traditional equipment management methods often rely on maintenance personnel to interpret equipment operation data and records to identify risks in nuclear energy equipment. But nuclear energy equipment often contains many critical devices, resulting in an extremely large volume of equipment operation data. This makes it difficult for maintenance personnel to quickly identify data that can determine equipment risks, and it is also difficult to guarantee the comprehensiveness of the identified data. Similarly, relying on maintenance personnel to identify equipment risk characteristics in textual data such as equipment operation records is extremely inefficient and cannot quantify and correlate equipment risk characteristics in multi-source data. This makes it difficult to cope with the complex and ever-changing environmental conditions and equipment status of nuclear energy equipment, resulting in low efficiency and poor accuracy in identifying equipment risks.

[0004] Therefore, how to improve the efficiency and comprehensiveness of acquiring equipment risk identification data, and enhance the efficiency and accuracy of equipment risk identification, has become an urgent problem to be solved by those skilled in the art. Summary of the Invention

[0005] This invention provides a method, apparatus, device, medium, and product for identifying equipment risks, in order to improve the efficiency and comprehensiveness of acquiring equipment risk identification data and enhance the efficiency and accuracy of identifying equipment risks.

[0006] According to one aspect of the present invention, a method for identifying equipment risks is provided, comprising:

[0007] In response to a risk identification request for the target device, obtain the device operating parameters and device operating records of the target device;

[0008] Determine the device service level corresponding to the target device;

[0009] Based on the equipment operation records, determine the health status of the target equipment;

[0010] The status change level of the target device is determined based on the device's operating parameters and service level.

[0011] Based on the health status of the device and the level of status change, a risk identification result for the target device is generated.

[0012] According to another aspect of the present invention, a device risk identification apparatus is provided, comprising:

[0013] The device data acquisition module is used to acquire the device operating parameters and device operating records of the target device in response to a risk identification request for the target device;

[0014] The device level determination module is used to determine the device service level corresponding to the target device;

[0015] The device status determination module is used to determine the device health status of the target device based on the device operation record.

[0016] The equipment change level determination module is used to determine the status change level of the target equipment based on the equipment operating parameters and the equipment service level.

[0017] The result generation module is used to generate risk identification results for the target device based on the device's health status and the level of status change.

[0018] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: at least one processor; and

[0019] A memory communicatively connected to the at least one processor; wherein,

[0020] The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the device risk identification method according to any embodiment of the present invention.

[0021] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the device risk identification method according to any embodiment of the present invention.

[0022] According to another aspect of the present invention, a computer program product is provided, the computer program product comprising a computer program that, when executed by a processor, implements the device risk identification method according to any embodiment of the present invention.

[0023] The technical solution of this invention, in response to a risk identification request for a target device, acquires the device's operating parameters and operating records; determines the device's corresponding service level; determines the target device's health status based on the operating records; determines the target device's status change level based on the operating parameters and service level; and generates a risk identification result for the target device based on the health status and status change level. This solution can determine the target device's health status based on the acquired operating parameters, and determine the target device's status change level based on the operating records and service level, thereby generating a risk identification result for the target device. This improves the efficiency and comprehensiveness of acquiring risk identification data and enhances the efficiency and accuracy of risk identification.

[0024] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a flowchart of a device risk identification method provided in Embodiment 1 of the present invention;

[0027] Figure 2 This is a flowchart of a device risk identification method provided in Embodiment 2 of the present invention;

[0028] Figure 3 This is a schematic diagram of the structure of an equipment risk identification device according to Embodiment 3 of the present invention;

[0029] Figure 4 This is a schematic diagram of the structure of an electronic device that implements the device risk identification method of this invention. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0032] Example 1

[0033] Figure 1 This is a flowchart of a method for identifying equipment risks according to Embodiment 1 of the present invention. This embodiment is applicable to situations where the efficiency of acquiring equipment risk identification data for nuclear energy equipment is low, and the efficiency of equipment risk identification is poor. This method can be executed by an equipment risk identification device, which can be implemented in hardware and / or software, and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0034] S110. In response to a risk identification request for the target device, obtain the device operating parameters and device operating records of the target device.

[0035] Equipment operation data refers to the set of real-time parameters generated by the target equipment during operation, specifically including runtime, temperature, pressure, speed, voltage, current, and output. Equipment operation records can be text data used to record all parameters generated during the equipment's usage cycle, specifically including technical documents, maintenance records, and historical fault reports.

[0036] Specifically, based on the risk identification request for the target equipment, pre-deployed parameter sensors, such as temperature and pressure sensors, can be used, as well as the target equipment's built-in instruments and control system, to obtain the target equipment's operational data. Furthermore, the target equipment's control system can be accessed through a pre-defined data interface to obtain the target equipment's operational records.

[0037] Optionally, after obtaining the device operation data and device operation records of the target device, the obtained device operation data and device operation records can be cleaned, abnormal data can be deleted and data can be completed to obtain adjusted device operation data and device operation records.

[0038] S120. Determine the equipment service level corresponding to the target equipment.

[0039] The equipment service level can be used to characterize the criticality of the target equipment in the business process and its impact on business objectives. Specifically, it can include core service equipment, important service equipment, and ordinary service equipment. Further, if the target equipment is core service equipment, its service level is Level 1; if it is important service equipment, its service level is Level 2; and if it is ordinary service equipment, its service level is Level 3. These levels can be pre-set by technical personnel based on actual circumstances. For example, if the target equipment is a reactor pressure vessel or containment vessel, which plays a crucial role in preventing the substantial release of core fission products into the environment, and its failure would lead to a serious nuclear leak accident, then the target equipment can be identified as core service equipment, and its service level is Level 1.

[0040] Specifically, the device identification information of the target device can be determined. Based on the device identification information, the associated device business function of the target device can be determined. Based on the device business characteristics, the corresponding device business level of the target device can be determined. The device business function can be the specific role that the target device plays during its service life. For example, if the target device is a reactor pressure vessel, then the device business function of the target device is to prevent the substantial release of core fission products into the environment when using the reactor pressure vessel. This embodiment does not impose specific limitations on this.

[0041] S130. Determine the health status of the target equipment based on the equipment operation records.

[0042] Equipment health status can be a comprehensive indicator reflecting the real-time operating status and potential risks of a target device, specifically including normal, warning, and fault status. Specifically, based on the target device's operating records, at least one risk keyword can be identified during the device's operating cycle. This risk keyword can be a descriptive term describing features affecting the target device's health status, such as fault, exceeding limits, aging, and cracks. Based on each risk descriptive term, it is determined whether the target device meets pre-defined equipment health identification conditions, and based on these conditions, the target device's equipment health status is determined.

[0043] For example, if the target equipment is a steam generator in a nuclear power plant, risk keywords such as cracks, leaks, and wear can be obtained from the equipment operation records during the steam generator's operating cycle. Specifically, if no risk keywords associated with the steam generator are obtained from the equipment operation records, the health status of the target equipment's steam generator can be determined to be normal; if risk keywords associated with the steam generator, such as wear, malfunction, and cracks, are obtained from the equipment operation records, the health status of the target equipment's steam generator can be determined to be warning. This embodiment does not impose specific limitations on this.

[0044] Optionally, the health status of the target device is determined based on the device operation records, including: obtaining the number of risk keywords associated with the target device based on the device operation records and a preset text recognition model; matching the number of risk keywords with a preset threshold range to obtain the threshold range into which the number of words falls; and determining the health status of the target device based on the threshold range into which the number of words falls.

[0045] Specifically, the equipment operation records can be input into a pre-trained text recognition model to perform contextual content analysis on the technical documents, maintenance records, and historical fault reports included in the equipment operation records, thereby obtaining risk keywords associated with the target equipment in the equipment operation records. In particular, the text recognition model can be used to extract the text content in the equipment operation records used to record equipment risks and / or equipment faults of the target equipment, and the risk keywords associated with the target equipment can be determined based on the extracted text content.

[0046] For example, text data describing equipment risks and / or equipment failures of a target device can be extracted from the device operation log. Specifically, the target device is identified as consisting of five modules: A, B, C, D, and E. The operation log text records that module A is operating normally with no abnormal noise; module B has a high-temperature warning, with the bearing temperature exceeding the threshold; device C has increased vibration amplitude, potentially indicating an imbalance fault; module D has insufficient lubrication system pressure, requiring emergency maintenance; and module E is operating smoothly with all parameters normal. Therefore, the risk keywords associated with the target device can be identified as high temperature, vibration, insufficient pressure, abnormal noise, and failure.

[0047] Furthermore, the number of risk keywords associated with the target device is determined, and this number is matched against a pre-defined threshold range to obtain the threshold range into which the number of risk keywords falls. This threshold range can be pre-defined by technical personnel based on actual conditions and experience. Then, based on the threshold range into which the number of risk keywords associated with the target device falls, the device health status is determined. For example, the correspondence between the threshold range and the device health status can be as follows: if the number of risk keywords is 0, the corresponding device health status is normal; if the number of risk keywords is less than 5, the corresponding device health status is warning; if the number of risk keywords is 5 or more, the corresponding device health status is faulty. Based on the above example, it can be seen that risk keywords associated with the target device include high temperature, vibration, insufficient pressure, abnormal noise, and fault, thus determining the corresponding device health status as warning. This embodiment does not impose specific limitations on this.

[0048] S140. Determine the status change level of the target equipment based on the equipment operating parameters and equipment service level.

[0049] The status change level can be a trend indicator used to quantify the migration of the target equipment from its current healthy state to other healthy states, and can be either high or low. The parameter anomaly level of the target equipment can be determined based on its operating parameters; and a parameter anomaly score can be determined based on the parameter anomaly level. The parameter anomaly level can be a parameter that quantifies the degree to which the equipment's operating parameters deviate from the standard equipment operating parameters, while the parameter anomaly score can be used to quantify the magnitude of the change in the equipment's operating parameters. Specifically, the parameter anomaly level and corresponding parameter anomaly score of the target equipment can be determined based on the target equipment's operating parameters and its standard operating parameters. If the target equipment's operating parameters deviate from the normal range by 0-20%, the corresponding parameter anomaly level is determined to be Level 1, with a corresponding parameter anomaly score of 1; if the target equipment's operating parameters deviate from the normal range by 20%-50%, the corresponding parameter anomaly level is determined to be Level 2, with a corresponding parameter anomaly score of 2; and if the target equipment's operating parameters deviate from the normal range by more than 50%, the corresponding parameter anomaly level is determined to be Level 3, with a corresponding parameter anomaly score of 3. These specific levels can be preset by technical personnel based on the actual situation.

[0050] For example, if the normal operating temperature of the target device is 100℃, then when the operating temperature of the target device is detected to be 110℃, it can be determined that the device's operating parameters deviate from the normal value by 10%, and the corresponding parameter anomaly level can be determined as Level 1, with a score of 3. Further, if the operating temperature of the target device is 140℃, the parameter anomaly level is Level 2, with a corresponding parameter anomaly score of 2; if the operating temperature of the target device is 160℃, the parameter anomaly level is Level 3, with a corresponding parameter anomaly score of 1.

[0051] Furthermore, the abnormal parameter weight value of the target device can be determined based on the device's business level. This abnormal parameter weight value can characterize the degree of influence of the target device's business level on its operating parameters. Specifically, if the target device is a core business device, the abnormal parameter weight value is 3; if it is an important business device, the abnormal parameter weight value is 2; and if it is a normal business device, the abnormal parameter weight value is 1. Then, based on the abnormal parameter score and the abnormal parameter weight value, the device status score of the target device can be calculated, and the device change level of the target device can be determined based on the device status score. The device status score can be a parameter indicator used to quantify the change state of the target device's operating parameters. For example, if the target device is a core business device (i.e., the abnormal parameter weight value is 3) and the corresponding abnormal parameter score is 2, then the device status score of the target device can be determined to be 6, and the status change level of the target device can be determined to be high. This embodiment does not impose specific limitations on this.

[0052] S150. Based on the equipment health status and status change level, generate risk identification results for the target equipment.

[0053] The risk identification results include high-risk, medium-risk, and low-risk levels. The current operational capability of the target equipment can be reflected in its health status; specifically, a normal health status indicates that the equipment's operational capability can meet the required business functions. The risk evolution speed of the target equipment can also be reflected in its status change level; a low status change level indicates a slow transition from its current healthy state to another. Therefore, a risk identification result for the target equipment can be generated based on its current operational capability and corresponding risk evolution speed. Alternatively, it can combine historical health status and status change level identification results with the current health status and status change level to generate a risk identification result. For example, if the equipment health status is normal and the status change level is low in any given time period, the risk identification result for the target equipment can be low-risk; if the equipment health status is faulty or warning and the status change level is high, the risk identification result for the target equipment can be high-risk. Furthermore, if it is determined that the target equipment is in a normal health status or a low status change level, then a risk identification result of medium risk level can be generated for the target equipment.

[0054] Optionally, based on the equipment health status and status change level, a risk identification result for the target equipment is generated, including: determining the historical health status and historical change level of the target equipment in at least one historical time period; determining whether the target equipment meets the pre-set risk level identification conditions based on the historical health status and historical change level, as well as the equipment health status and status change level; if so, generating a risk identification result for the target equipment based on the risk level identification conditions met by the target equipment.

[0055] Specifically, for any historical time period, the historical health status and historical change status of the target equipment can be determined. Based on these, along with the equipment's health status and change level, it can be determined whether the target equipment meets pre-defined risk level identification conditions. Specifically, this can involve statistically analyzing the detection results of the target equipment's historical health status and the identification results of its historical change levels over a historical time period. This data, combined with the target equipment's health status and change level, determines the risk level identification conditions met by the target equipment. Based on these conditions, a risk identification result for the target equipment is generated. For example, if the historical health status is normal and the historical change level is low, and both the equipment's health status and change level are normal, then the target equipment's risk identification result is determined to be low-risk. Furthermore, if the historical health status is a warning or fault and the historical change level is high, and both the equipment's health status is a warning or fault and the change level is high, then the target equipment's risk identification result is determined to be high-risk. Optionally, the risk level identification condition can also be that only one condition is met in the detection results of the target equipment's health status and status change level, namely, the equipment health status is normal or the status change level is low, and in the preset number of detection processes, the total number of times the equipment health status is normal and the status change level is low is less than a preset threshold. In this case, the equipment risk identification result of the target equipment can be determined as high risk level. Specifically, it can be preset by technical personnel based on actual conditions or experience.

[0056] Optionally, after generating risk identification results for the target equipment based on the equipment health status and status change level, the method further includes: determining the equipment risk information of the target equipment and its corresponding equipment risk type; generating a risk control strategy for the target equipment based on the equipment risk information and equipment risk type; executing the risk control strategy and generating a risk control report for the target equipment; adjusting the risk identification results for the target equipment based on the risk control report, obtaining the adjusted risk identification results, and providing feedback.

[0057] The equipment risk information can be a detailed description and risk assessment of adverse factors that may occur during the service life of the target equipment. Specifically, it may include the equipment name, equipment number, risk description, and risk assessment results. Equipment risk types may include mechanical risk, electrical risk, human risk, and environmental risk. Specifically, after determining the equipment risk identification results for the target equipment, the equipment risk information and corresponding equipment risk type of the target equipment can be determined based on these results. A risk management strategy for the target equipment can then be generated. For example, if the target equipment is a control rod assembly, and the equipment risk identification result for the target equipment is high-risk, then the equipment risk information for the target equipment could be: control rod jamming and high rise / fall delay, leading to reactor power control failure, causing a sudden rise or fall in reactor core power. Furthermore, the equipment risk type for the target equipment could be determined to be a mechanical failure, i.e., a failure of the control rod drive mechanism. Based on this, a risk management strategy for the target equipment can be generated. The specific management strategy can be as follows: First, redundant drive mechanisms can be used to raise / lower the control rods, thereby maintaining the reactor at a subcritical depth. Then, the core of the faulty control rod can be removed to check the wear and jamming of mechanical parts. Finally, the drive mechanism can be inspected and maintained during the reactor shutdown and refueling.

[0058] Furthermore, by implementing this risk management strategy, equipment risks of the target equipment are detected and eliminated. After risk management is completed, a risk management report for the target equipment is generated. This report may include a description of the equipment risk, risk assessment results, risk management measures, and risk management results. Based on this risk assessment report, the risk identification results for the target equipment are adjusted to obtain adjusted risk identification results, which are then fed back. For example, the risk identification result of the target equipment may be adjusted from a high-level risk to a medium-level risk. The target equipment is then monitored in real time until it is determined that the risk identification result of the target equipment has been reduced to a low-level risk.

[0059] The technical solution of this invention, in response to a risk identification request for a target device, acquires the device's operating parameters and operating records; determines the device's corresponding service level; determines the target device's health status based on the operating records; determines the target device's status change level based on the operating parameters and service level; and generates a risk identification result for the target device based on the health status and status change level. This solution can determine the target device's health status based on the acquired operating records, and determine the target device's status change level based on the operating parameters and service level, thereby generating a risk identification result for the target device. This improves the efficiency and comprehensiveness of acquiring risk identification data and enhances the efficiency and accuracy of risk identification.

[0060] Example 2

[0061] Figure 2 This is a flowchart of a device risk identification method provided in Embodiment 2 of the present invention. Based on the above embodiments, this embodiment further optimizes the above device risk identification method.

[0062] Furthermore, the step "determine the status change level of the target equipment based on the equipment operating parameters and equipment service level" is refined into "comparing the equipment operating parameters with pre-set abnormal parameter thresholds to obtain the comparison results; if the comparison results determine that the equipment operating parameters are normal operating parameters, then determining the change amplitude of the equipment operating parameters within a preset time period; determining the status change score of the target equipment based on the change amplitude and the abnormal parameter thresholds; and determining the status change level of the target equipment based on the status change score and the equipment service level." This improves the method for identifying equipment risks. Figure 2 As shown, the method includes:

[0063] S210. In response to a risk identification request for the target device, obtain the device operating parameters and device operating records of the target device.

[0064] S220. Determine the equipment service level corresponding to the target equipment.

[0065] S230. Determine the health status of the target equipment based on the equipment operation records.

[0066] S240. Compare the equipment operating parameters with the preset abnormal parameter thresholds to obtain the numerical comparison results.

[0067] The abnormal parameter threshold can be a parameter value used to determine whether the operating parameters of the target device are abnormal. Specifically, the operating parameters of the target device can be compared with a pre-set abnormal parameter threshold. If the operating parameter is greater than the abnormal parameter threshold, it can be determined that the operating parameters of the target device are out of standard, and the risk identification result of the target device is determined to be high-risk. Furthermore, if the operating parameter is not greater than the abnormal parameter threshold, it can be determined that the operating parameters of the target device are normal. For example, if the standard operating temperature of the target device is 100℃, the corresponding abnormal parameter threshold can be 150℃. If the operating temperature in the operating parameters of the target device is 120℃, it can be determined that the operating parameters of the target device are normal; if the operating temperature in the operating parameters of the target device is 170℃, it can be determined that the operating parameters of the target device are out of standard, and the risk identification result of the target device is determined to be high-risk. This embodiment does not impose specific limitations on this.

[0068] S250. If the equipment operating parameters are determined to be normal operating parameters based on the numerical comparison results, then the change range of the equipment operating parameters within the preset time period is determined.

[0069] The change range value can be the fluctuation value of the equipment operating parameters of the target equipment within a certain period of time. For example, if the operating temperature of the target equipment rises from 95℃ to 120℃ within a preset time period, the change range value of the operating temperature of the target equipment can be determined to be 35℃.

[0070] S260. Determine the state change score corresponding to the target device based on the change amplitude value and the abnormal parameter threshold.

[0071] The state change score can be a parameter index used to quantify the degree of change of the operating parameters of a target device over a certain period of time. Specifically, it can be calculated as the quotient between the change range of the target device's operating parameters and a pre-set abnormal parameter threshold, and this quotient is determined as the state change score corresponding to the target device. For example, continuing the previous example, if the change range of the target device's operating temperature is 35℃ and the pre-set abnormal parameter threshold is 150℃, then the state change score corresponding to the target device can be determined to be 0.23.

[0072] S270. Determine the status change level of the target device based on the status change score and the device service level.

[0073] Optionally, the status change level of the target device is determined based on the status change score and the device service level, including: determining the initial status change level of the target device based on the status change score; determining whether the target device meets the pre-set status level adjustment requirements based on the device service level; if so, adjusting the initial status change level of the target device and determining the adjusted initial status change level as the status change level of the target device.

[0074] The initial state change level can be determined solely based on the state change score of the target device. Specifically, the state change score of the target device can be compared with a pre-set change score threshold, and the initial state change level of the target device can be determined based on the comparison result. If the state change score is less than the threshold, the initial state change level of the target device can be determined as a low change level; if the state change score is greater than or equal to the threshold, the initial state change level of the target device can be determined as a high change level.

[0075] Furthermore, based on the target device's service level, it can be determined whether the initial state change level of the target device needs to be adjusted. Specifically, if the target device's service level is core or important business equipment, then it can be determined that the initial state change level needs to be adjusted, and this adjustment can be made from a low change level to a high change level. If the target device's service level is ordinary business equipment, then it can be determined that no adjustment is needed. Therefore, the adjusted initial state change level can be determined as the target device's state change level.

[0076] S280. Generate risk identification results for the target equipment based on the equipment health status and status change level.

[0077] The technical solution of this invention compares the device operating parameters with a pre-set abnormal parameter threshold to obtain a comparison result. If the comparison result determines that the device operating parameters are normal operating parameters, the change range of the device operating parameters within a preset time period is determined. Based on the change range and the abnormal parameter threshold, a state change score corresponding to the target device is determined. Based on the state change score and the device service level, the state change level of the target device is determined. This embodiment compares the obtained device operating parameters of the target device with pre-set parameter thresholds, determines the device change state of the target device based on the comparison result and the device service level, and associates the device operating parameters with the device service level to achieve intelligent identification of the device change state of the target device. This approach is more closely aligned with the actual application scenario of the target device, improves the accuracy of device risk assessment, and enhances the health management capabilities of the target device.

[0078] Example 3

[0079] Figure 3 This is a schematic diagram of a device for identifying equipment risks according to Embodiment 3 of the present invention. The device for identifying equipment risks provided in this embodiment of the present invention is applicable to situations where the efficiency of acquiring equipment risk identification data for nuclear energy equipment is low, and the efficiency of equipment risk identification is poor. This device for identifying equipment risks can be implemented in hardware and / or software, such as... Figure 3 As shown, it specifically includes: a device data acquisition module 310, a device level determination module 320, a device status determination module 330, a device change level determination module 340, and a result generation module 350. Among them,

[0080] The device data acquisition module 310 is used to acquire the device operating parameters and device operating records of the target device in response to a risk identification request for the target device;

[0081] The device level determination module 320 is used to determine the device service level corresponding to the target device;

[0082] The device status determination module 330 is used to determine the device health status of the target device based on the device operation record;

[0083] The equipment change level determination module 340 is used to determine the status change level of the target equipment based on the equipment operating parameters and the equipment service level;

[0084] The result generation module 350 is used to generate a risk identification result for the target device based on the device's health status and the status change level.

[0085] This solution can determine the health status of the target device based on the acquired device operating parameters, and determine the status change status of the target device based on the device operation records and device service level. Based on this, it generates the device risk identification results for the target device, which improves the efficiency and comprehensiveness of acquiring device risk identification data and enhances the efficiency and accuracy of device risk identification.

[0086] Optionally, the result generation module 350 is specifically used to determine the historical health status and historical change level of the target device in at least one historical time period;

[0087] Based on the historical health status and the historical change level, as well as the device health status and the status change level, determine whether the target device meets the pre-set risk level identification conditions;

[0088] If so, a risk identification result for the target device is generated based on the risk level identification conditions met by the target device.

[0089] Optionally, the device may also include:

[0090] The equipment management strategy generation module is used to determine the equipment risk information of the target equipment and its corresponding equipment risk type after generating the risk identification result of the target equipment based on the equipment health status and the status change level.

[0091] Based on the equipment risk information and the equipment risk type, a risk management strategy for the target equipment is generated;

[0092] Execute the risk management strategy and generate a risk management report for the target device;

[0093] Based on the risk management report, the risk identification results for the target equipment are adjusted to obtain the adjusted risk identification results and then fed back.

[0094] Optionally, the device status determination module 330 is specifically used to obtain the number of risk keywords associated with the target device based on the device operation record and a preset text recognition model;

[0095] The number of risk keywords is matched with a pre-set threshold range to obtain the threshold range into which the number of keywords falls.

[0096] The health status of the target device is determined based on the number of words falling within a certain threshold range.

[0097] Optionally, the equipment change level determination module 340 is specifically used to compare the equipment operating parameters with a pre-set abnormal parameter threshold to obtain a numerical comparison result;

[0098] If the equipment operating parameters are determined to be normal operating parameters based on the numerical comparison results, then the change range of the equipment operating parameters within a preset time period is determined.

[0099] Based on the change magnitude value and the abnormal parameter threshold, the state change score corresponding to the target device is determined;

[0100] The state change level of the target device is determined based on the state change score and the device service level.

[0101] Optionally, the device change level determination module 340 is further configured to determine the initial state change level of the target device based on the state change score;

[0102] Based on the device service level, determine whether the target device meets the pre-set status level adjustment requirements;

[0103] If so, the initial state change level of the target device is adjusted, and the adjusted initial state change level is determined as the state change level of the target device.

[0104] The equipment risk identification device provided in this embodiment of the invention can execute the equipment risk identification method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0105] Example 4

[0106] Figure 4A schematic diagram of an electronic device 40 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0107] like Figure 4 As shown, the electronic device 40 includes at least one processor 41 and a memory, such as a read-only memory (ROM) 42 and a random access memory (RAM) 43, communicatively connected to the at least one processor 41. The memory stores computer programs executable by the at least one processor. The processor 41 can perform various appropriate actions and processes based on the computer program stored in the ROM 42 or loaded from storage unit 48 into the RAM 43. The RAM 43 can also store various programs and data required for the operation of the electronic device 40. The processor 41, ROM 42, and RAM 43 are interconnected via a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0108] Multiple components in electronic device 40 are connected to I / O interface 45, including: input unit 46, such as keyboard, mouse, etc.; output unit 47, such as various types of monitors, speakers, etc.; storage unit 48, such as disk, optical disk, etc.; and communication unit 49, such as network card, modem, wireless transceiver, etc. Communication unit 49 allows electronic device 40 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0109] Processor 41 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 41 performs the various methods and processes described above, such as device risk identification methods.

[0110] In some embodiments, the device risk identification method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 40 via ROM 42 and / or communication unit 49. When the computer program is loaded into RAM 43 and executed by processor 41, one or more steps of the device risk identification method described above may be performed. Alternatively, in other embodiments, processor 41 may be configured to perform the device risk identification method by any other suitable means (e.g., by means of firmware).

[0111] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0112] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0113] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0114] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0115] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0116] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system. It addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability.

[0117] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0118] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for identifying equipment risks, characterized in that, include: In response to a risk identification request for the target device, obtain the device operating parameters and device operating records of the target device; Determine the device service level corresponding to the target device; Based on the equipment operation records, determine the health status of the target equipment; The status change level of the target device is determined based on the device's operating parameters and service level. Based on the health status of the device and the level of status change, a risk identification result for the target device is generated.

2. The method according to claim 1, characterized in that, The step of generating a risk identification result for the target device based on the device's health status and the level of status change includes: Determine the historical health status and historical change level of the target device in at least one historical time period; Based on the historical health status and the historical change level, as well as the device health status and the status change level, determine whether the target device meets the pre-set risk level identification conditions; If so, a risk identification result for the target device is generated based on the risk level identification conditions met by the target device.

3. The method according to claim 1, characterized in that, After generating a risk identification result for the target device based on the device health status and the status change level, the method further includes: Determine the equipment risk information of the target equipment and its corresponding equipment risk type; Based on the equipment risk information and the equipment risk type, a risk management strategy for the target equipment is generated; Execute the risk management strategy and generate a risk management report for the target device; Based on the risk management report, the risk identification results for the target equipment are adjusted to obtain the adjusted risk identification results and then fed back.

4. The method according to claim 1, characterized in that, Determining the health status of the target device based on the device operation record includes: Based on the device operation records and a preset text recognition model, the number of risk keywords associated with the target device is obtained. The number of risk keywords is matched with a pre-set threshold range to obtain the threshold range into which the number of keywords falls. The health status of the target device is determined based on the number of words falling within a certain threshold range.

5. The method according to claim 1, characterized in that, Determining the state change level of the target device based on the device operating parameters and the device service level includes: The operating parameters of the equipment are compared with a pre-set threshold value for abnormal parameters to obtain the comparison result. If the equipment operating parameters are determined to be normal operating parameters based on the numerical comparison results, then the change range of the equipment operating parameters within a preset time period is determined. Based on the change magnitude value and the abnormal parameter threshold, the state change score corresponding to the target device is determined; The state change level of the target device is determined based on the state change score and the device service level.

6. The method according to claim 5, characterized in that, Determining the state change level of the target device based on the state change score and the device service level includes: The initial state change level of the target device is determined based on the state change score. Based on the device service level, determine whether the target device meets the pre-set status level adjustment requirements; If so, the initial state change level of the target device is adjusted, and the adjusted initial state change level is determined as the state change level of the target device.

7. A device for identifying equipment risks, characterized in that, include: The device data acquisition module is used to acquire the device operating parameters and device operating records of the target device in response to a risk identification request for the target device; The device level determination module is used to determine the device service level corresponding to the target device; The device status determination module is used to determine the device health status of the target device based on the device operation record. The equipment change level determination module is used to determine the status change level of the target equipment based on the equipment operating parameters and the equipment service level. The result generation module is used to generate risk identification results for the target device based on the device's health status and the level of status change.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that is executed by the at least one processor to enable the at least one processor to perform the device risk identification method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the device risk identification method according to any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the device risk identification method according to any one of claims 1-6.

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