Autonomously configured audit link presentation method, apparatus, device, and medium

Abstract

Embodiments of the present disclosure disclose an autonomous configured audit link display method, device, equipment and medium. A specific embodiment of the method comprises: in response to detecting a tree node processing operation, adjusting a target audit business process tree model to obtain an adjusted tree model; in response to detecting a task configuration operation and there being historical configuration task information that is the same as the content of the first audit node configuration information, generating corresponding configuration node information; generating corresponding configuration task information; in response to receiving a data retrieval operation, retrieving a data set associated with the configuration task information; generating a business analysis result; generating a packaged link from the business analysis result, the configuration task information, the adjusted tree model and the data set; and displaying the packaged link on a business information retrieval interface. The embodiment can efficiently and quickly generate audit results corresponding to the configuration task information configured for the target audit business.

Description

Technical Field

[0001] The embodiments disclosed herein relate to the field of computer technology, and more specifically to a method, apparatus, device, and medium for displaying self-configured audit links. Background Technology

[0002] Currently, auditing is a crucial part of daily operations. The typical approach to generating audit results is as follows: First, multiple audit nodes associated with the audit are manually input. Then, the configuration conditions for each of these audit nodes are manually configured. Next, the corresponding dataset is retrieved via database queries using the configured audit nodes. Finally, audit results are generated based on the analysis performed by relevant analysts.

[0003] However, the inventors discovered that when using the above method to generate audit results, the following technical problems often arise:

[0004] First, the configuration efficiency of audit nodes and configuration conditions is low, often resulting in missing audit nodes or conditions. This not only leads to inaccurate and inefficient subsequent audit results, but also wastes a lot of human and material resources.

[0005] Second, the detection of abnormalities in power equipment is not accurate enough.

[0006] The information disclosed in this background section is only intended to enhance the understanding of the background of the inventive concept, and therefore may contain information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0007] The summary portion of this disclosure is intended to provide a brief overview of the concepts, which will be described in detail in the detailed description portion later. This summary portion is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0008] Some embodiments of this disclosure propose a self-configurable audit link display method, apparatus, device, and medium to address one or more of the technical problems mentioned in the background section above.

[0009] In a first aspect, some embodiments of this disclosure provide a self-configurable audit link display method, including: in response to detecting a tree node processing operation on a target audit business process tree model displayed on an audit process maintenance interface, adjusting the tree model nodes of the target audit business process tree model to obtain an adjusted tree model, wherein the audit process maintenance interface is an interface in an audit business platform used to maintain the business process of the target audit business, and the target audit business process tree model represents the node association relationship of multiple audit nodes corresponding to the target audit business; in response to detecting a task configuration operation on a task information configuration interface, and that there is no historical configuration task information in the historical commonly used configuration task information set that has the same content as the first audit node configuration information, generating corresponding configuration node information according to the first audit node configuration information, wherein the task information configuration interface is an interface in the audit business platform used to maintain the business process of the target audit business, and the tree model represents the node association relationship of multiple audit nodes corresponding to the target audit business; The interface for configuring task information includes the first audit node configuration information, which is the information entered in the task information configuration interface. Based on the configuration node information and the first task configuration information entered in the task information configuration interface, corresponding configuration task information is generated. In response to receiving a data retrieval operation for the configuration task information, a dataset associated with the configuration task information is retrieved from the target database. Based on the dataset, business analysis results for the target audit business are generated. The business analysis results, the configuration task information, the adjusted tree model, and the dataset are linked and packaged to generate a packaged link. The packaged link is displayed in encrypted form on the business information retrieval interface, allowing relevant personnel to retrieve the business analysis results corresponding to the packaged link through decryption. The business information retrieval interface is the interface in the audit business platform used to retrieve business information corresponding to the audit business.

[0010] Secondly, some embodiments of this disclosure provide a self-configurable audit link display device, including: a tree model node adjustment unit, configured to adjust the tree model nodes of the target audit business process tree model in response to detecting a tree node processing operation on the target audit business process tree model displayed on the audit process maintenance interface, to obtain an adjusted tree model, wherein the audit process maintenance interface is an interface in the audit business platform used to maintain the business process of the target audit business, and the target audit business process tree model represents the node association relationship of multiple audit nodes corresponding to the target audit business; and a first generation unit, configured to generate corresponding configuration node information based on the first audit node configuration information in response to detecting a task configuration operation on the task information configuration interface, and that there is no historical configuration task information in the historical commonly used configuration task information set that has the same content as the first audit node configuration information, wherein the task information configuration interface is the audit business The platform includes an interface for configuring task information, where the first audit node configuration information is the information entered in the task information configuration interface; a second generation unit is configured to generate corresponding configuration task information based on the configuration node information and the first task configuration information entered in the task information configuration interface; a retrieval unit is configured to retrieve a dataset associated with the configuration task information from a target database in response to a data retrieval operation received for the configuration task information; a packaging unit is configured to link and package the business analysis results, the configuration task information, the adjusted tree model, and the dataset to generate a packaged link; and a display unit is configured to display the packaged link in encrypted form on the business information retrieval interface, allowing relevant personnel to retrieve the business analysis results corresponding to the packaged link through decryption. The business information retrieval interface is the interface in the audit business platform used to retrieve business information corresponding to the audit business.

[0011] Thirdly, some embodiments of this disclosure provide an electronic device, including: one or more processors; and a storage device having one or more programs stored thereon, such that when the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any implementation of the first aspect.

[0012] Fourthly, some embodiments of this disclosure provide a computer-readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method as described in any implementation of the first aspect.

[0013] The above embodiments of this disclosure have the following beneficial effects: the self-configured audit link display method of some embodiments of this disclosure can efficiently and quickly generate audit results corresponding to the configuration task information configured for the target audit business. Specifically, the reason for the inefficient and slow generation of audit results is that the configuration efficiency of audit nodes and configuration conditions is low, often resulting in missing audit nodes or configuration conditions. This not only leads to inaccurate and inefficient subsequent audit results but also wastes a lot of manpower and resources. Based on this, the self-configured audit link display method of some embodiments of this disclosure firstly, in response to detecting the tree node processing operation of the target audit business process tree model displayed on the audit process maintenance interface, adjusts the tree model nodes of the target audit business process tree model to obtain the adjusted tree model. The audit process maintenance interface is the interface in the audit business platform used to maintain the business process of the target audit business, and the target audit business process tree model represents the node association relationship of multiple audit nodes corresponding to the target audit business. Here, the process tree model can explicitly display multiple audit nodes for the target audit business, avoiding the problem of missing configuration audit nodes caused by manual input of audit nodes. In addition, the audit process maintenance interface facilitates the maintenance of the target audit business process tree model, allowing for real-time adjustments to ensure its effectiveness. Next, in response to a detected task configuration operation on the task information configuration interface, and the absence of historically frequently used configuration task information identical to the first audit node configuration information in the historical commonly used configuration task information set, corresponding configuration node information is generated based on the first audit node configuration information. The task information configuration interface is the interface used for configuring task information within the audit business platform, and the first audit node configuration information is the information entered on the task information configuration interface. Here, the task information configuration interface facilitates audit node configuration. Furthermore, by determining whether historically frequently used configuration task information identical to the first audit node configuration information exists in the historical commonly used configuration task information set, the configuration efficiency of audit nodes can be effectively improved. Optionally, if historically frequently used configuration task information identical to the first audit node configuration information exists in the historical commonly used configuration task information set, reconfiguration is unnecessary; task configuration (i.e., conditional configuration) can be performed on the historically frequently used configuration information with identical content. Next, based on the configuration node information and the first task configuration information entered in the task information configuration interface, accurate configuration task information can be generated. Then, in response to receiving a data retrieval operation for the configuration task information, the dataset associated with the configuration task information is retrieved from the target database for subsequent business analysis of the target audit business.Furthermore, based on the aforementioned dataset, accurate business analysis results can be generated for the aforementioned target audit business. Then, the aforementioned business analysis results, the aforementioned configuration task information, the aforementioned adjusted tree model, and the aforementioned dataset are linked and packaged to generate a packaged link. Here, the link allows for convenient subsequent extraction of the business analysis results, configuration task information, adjusted tree model, and dataset. Finally, the aforementioned packaged link is displayed in encrypted form on the business information retrieval interface, allowing relevant personnel to retrieve the corresponding business analysis results by decryption. The aforementioned business information retrieval interface is the interface within the aforementioned audit business platform used to retrieve business information corresponding to the audit business. Attached Figure Description

[0014] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and elements are not necessarily drawn to scale.

[0015] Figure 1 This is a flowchart of some embodiments of the self-configured audit link display method according to this disclosure;

[0016] Figure 2 This is a schematic diagram of the structure of some embodiments of the self-configured audit link display device according to this disclosure;

[0017] Figure 3 This is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. Detailed Implementation

[0018] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0019] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.

[0020] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0021] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0022] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0023] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0024] refer to Figure 1 The diagram illustrates a flow 100 of some embodiments of a self-configurable audit link display method according to this disclosure. This self-configurable audit link display method includes the following steps:

[0025] Step 101: In response to detecting a tree node processing operation on the target audit business process tree model displayed on the audit process maintenance interface, the tree model nodes of the target audit business process tree model are adjusted to obtain the adjusted tree model.

[0026] In some embodiments, in response to detecting tree node processing operations on the target audit business process tree model displayed on the audit process maintenance interface, the executing entity of the self-configured audit link display method can adjust the tree model nodes of the target audit business process tree model to obtain an adjusted tree model. The audit process maintenance interface is an interface within the audit business platform used to maintain the business process of the target audit business. The target audit business process tree model represents the node relationships among multiple audit nodes corresponding to the target audit business. The target audit business process tree model can be a tree-structured model. Each audit business has a one-to-one corresponding audit business process tree model. The target audit business can be an audit business targeting various fields. For example, the target audit business can be the sales volume and electricity price management business in the power sector. The audit business platform can be a platform used to complete audit businesses. Tree node processing operations can be operations that perform various processing on the tree nodes in the target audit business process tree model.

[0027] As an example, for the target audit business being the sales volume and electricity price management business, the root node of the target audit business process tree model could be "Sales Volume and Electricity Price Management Business". The next level node of the root node can include, but is not limited to, at least one of the following: power factor adjustment electricity fee node, peak-valley time-of-use electricity price node, and basic electricity price node. The next level node of the power factor adjustment electricity fee node can include, but is not limited to, at least one of the following: a node where power factor assessment should have been implemented but was not, and a node where the applicable scope of users subject to power factor adjustment electricity fees does not conform to regulations. The next level node of the peak-valley time-of-use electricity price node can include, but is not limited to, at least one of the following: a node where time-of-use electricity pricing is not properly implemented (province). The next level node of the basic electricity price node can include, but is not limited to, at least one of the following: a node where basic electricity fees for high-voltage motors that have not passed through the receiving transformer are not collected, a node where the recorded demand value, actual demand value, and billed demand value are inconsistent, and a node where basic electricity fees are not charged to users who are normally exempt from basic electricity fees according to the electricity price.

[0028] For example, multiple audit points may include: power factor assessment points that should have been implemented but were not, points where the scope of application for power factor adjustment of electricity charges does not conform to regulations, points where power factor assessment should have been implemented but were not, and points where the scope of application for power factor adjustment of electricity charges does not conform to regulations.

[0029] In some optional implementations of certain embodiments, adjusting the tree model nodes of the aforementioned target audit business process tree model to obtain the adjusted tree model may include the following steps:

[0030] The first step is to determine the relationship between the audit node to be processed and the target audit business process tree model described above. The audit node to be processed can be any audit node awaiting node processing. Specifically, it can be an audit node to be added, an audit node to be deleted, or an audit node to be replaced. This relationship characterizes the node processing position of the audit node to be processed within the target audit business process tree model.

[0031] The second step is to determine that the above tree node processing operation is an audit node addition operation, and add the above audit node to be processed to the corresponding position in the above target audit business process tree model according to the above association relationship, so as to obtain the tree model after addition, which is used as the above adjusted tree model.

[0032] The third step is to determine that the above tree node processing operation is an audit node deletion operation, and based on the above association, delete the audit node corresponding to the above audit node to be processed from the above target audit business process tree model to obtain the deleted tree model, which is used as the above adjusted tree model.

[0033] Fourth step: In response to determining that the above tree node processing operation is an audit node replacement operation, based on the above association, the audit node corresponding to the above audit node to be processed in the above target audit business process tree model is replaced with the above audit node to be processed, and the replaced tree model is obtained as the above adjusted tree model.

[0034] Step 102: In response to detecting a task configuration operation on the task information configuration interface and the absence of historical configuration task information in the historical frequently used configuration task information set that has the same content as the first audit node configuration information, generate corresponding configuration node information based on the aforementioned first audit node configuration information.

[0035] In some embodiments, in response to detecting a task configuration operation on the task information configuration interface and the absence of historical configuration task information in the historical frequently used configuration task information set that has the same content as the first audit node configuration information, the execution entity can generate corresponding configuration node information based on the first audit node configuration information. The task information configuration interface is the interface in the audit business platform used for configuring task information, and the first audit node configuration information is the information entered on the task information configuration interface. The task configuration operation can be information for generating a new configuration task. The configuration task can be an audit task configured for a target audit business. The first audit node configuration information represents the configuration information of the selected audit node. For example, multiple audit nodes include: a first audit node, a second audit node, a third audit node, and a fourth audit node. The first audit node configuration information can represent the configuration information of selecting the first audit node and the fourth audit node. The historical frequently used configuration task information in the historical frequently used configuration task information set can be historically configured configuration tasks.

[0036] As an example, the aforementioned executing entity can package the node information of the audit nodes involved in the configuration information of the first audit node to generate the corresponding configuration node information.

[0037] Step 103: Generate corresponding configuration task information based on the above configuration node information and the first task configuration information entered in the above task information configuration interface.

[0038] In some embodiments, the executing entity can generate corresponding configuration task information based on the configuration node information and the first task configuration information entered in the task information configuration interface. The first task configuration information may include: basic task configuration information and task condition configuration information. For example, the basic task configuration information may include: task name information, task audit type information, information of the implementing units involved in the task, and remarks. The task condition configuration information may include: statistical time condition configuration information.

[0039] As an example, the aforementioned execution entity can package the configuration node information with the aforementioned first task configuration information to generate corresponding configuration task information.

[0040] Step 104: In response to receiving a data retrieval operation for the above configuration task information, retrieve the dataset associated with the above configuration task information from the target database.

[0041] In some embodiments, in response to receiving a data retrieval operation for the aforementioned configuration task information, the executing entity can retrieve a dataset associated with the aforementioned configuration task information from a target database. The data retrieval operation may be an operation to retrieve data related to the configuration task information.

[0042] Step 105: Based on the above dataset, generate business analysis results for the above target audit business.

[0043] In some embodiments, the aforementioned executing entity may generate business analysis results for the aforementioned target audit business based on the aforementioned dataset.

[0044] As an example, firstly, the aforementioned implementing entity can determine the audit model corresponding to the target audit business. This audit model can be a neural network model. For each audit business, a corresponding neural network model is pre-configured to achieve specialized audit analysis. For example, the audit model can be a model composed of multi-layer convolutional neural networks (CNNs). Then, the dataset is input into the audit model to generate business analysis results for the target audit business.

[0045] Step 106: Link and package the above business analysis results, the above configuration task information, the above adjusted tree model, and the above dataset to generate a packaged link.

[0046] In some embodiments, the aforementioned executing entity may link and package the aforementioned business analysis results, the aforementioned configuration task information, the aforementioned adjusted tree model, and the aforementioned dataset to generate a packaged link.

[0047] As an example, firstly, the aforementioned execution entity can package the aforementioned business analysis results, the aforementioned configuration task information, the aforementioned adjusted tree model, and the aforementioned dataset to generate a packaged file. Then, a packaged link for the packaged file is generated.

[0048] Step 107: Display the above-mentioned packaged link in encrypted form on the business information retrieval interface so that relevant personnel can retrieve the business analysis results corresponding to the packaged link by decryption.

[0049] In some embodiments, the aforementioned executing entity may display the packaged link in encrypted form on the business information retrieval interface, allowing relevant personnel to retrieve the business analysis results corresponding to the packaged link through decryption. The aforementioned business information retrieval interface is the interface within the aforementioned audit business platform used to retrieve business information corresponding to the audit business.

[0050] In some optional implementations of certain embodiments, after step 107, the steps further include:

[0051] The first step is to add the above configuration task information to the historical frequently used configuration task information set, resulting in the added configuration task information set.

[0052] The second step involves detecting a task configuration operation on the task information configuration interface, and recognizing that historically frequently used configuration task information contains identical content to the second audit node configuration information. Based on the aforementioned configuration node information and the second task configuration information entered on the task information configuration interface, the historically identical configuration task information is adjusted to obtain the adjusted configuration task information. The adjusted configuration task information corresponds to the same task configuration information as the aforementioned second task configuration information.

[0053] In some optional implementations of certain embodiments, after step 107, the steps further include:

[0054] The first step, in response to determining that the target audit engagement is an audit engagement targeting specific substation equipment, is to generate a predicted substation equipment problem based on the analysis results of the aforementioned engagement. The target substation equipment can be any substation equipment involved in the target audit engagement. The predicted substation equipment problem can characterize potential problems that may occur with the substation equipment within the corresponding time period of the dataset. For example, the predicted substation equipment problem could be a potential malfunction occurring with the substation equipment between November 1st and November 2nd.

[0055] The second step is to determine the responsible department information corresponding to the above-mentioned predicted substation equipment problems based on the above-mentioned configuration task information.

[0056] As an example, the aforementioned implementing entity can determine the responsible department information corresponding to the predicted substation equipment problem from the configuration task information.

[0057] The third step is to send the predicted substation equipment problems to the testing platform corresponding to the responsible department's information, so that the testing platform can perform substation equipment testing to address the predicted problems. The testing platform can be a platform for detecting whether the substation equipment is faulty.

[0058] Optionally, the above-mentioned anticipated substation equipment problems can be detected through the following steps:

[0059] The first step involves acquiring a first infrared imaging video of the target substation equipment captured by a first infrared camera within a predetermined time period, and acquiring a first recorded audio of the target substation equipment collected by a device sound collection device within the predetermined time period. The device sound collection device is a device installed on the target substation equipment to collect the operating sounds of the target substation equipment. The substation equipment can be the power equipment of a target substation. The target substation can be a substation where it is determined whether the power equipment is malfunctioning. For example, the substation equipment can be a transformer of the target substation. The predetermined time period can be a pre-historical predetermined time period relative to the current time. For example, the current time is 12:00 on January 12, 2021. The pre-historical predetermined time period can be: "0:00 on January 12, 2021 - 12:00 on January 12, 2021". The device sound collection device can be a sound collector.

[0060] The second step involves extracting frames from the first infrared imaging video at predetermined intervals to obtain a first infrared imaging image sequence. The first infrared imaging images in the first infrared imaging image sequence are arranged in chronological order.

[0061] As an example, the aforementioned execution entity can perform frame extraction processing on the aforementioned first infrared imaging video in 2-frame increments to obtain the first infrared imaging image sequence.

[0062] The third step is to generate a first spectrogram and a first timing diagram for the first recorded audio. The first spectrogram can represent the frequency transformation information of the first recorded audio. The first timing diagram can represent the transformation information between time and response of the first recorded audio.

[0063] As an example, the aforementioned execution entity can utilize the spectrogram generation device and the timing diagram generation device to generate a first spectrogram and a first timing diagram for the aforementioned first recorded audio.

[0064] Fourth, based on the first infrared imaging image sequence mentioned above, the execution entity can generate first detection information characterizing whether the target substation equipment has experienced equipment abnormality within the predetermined time period through various methods.

[0065] Fifth step: Based on the first spectrum diagram and the first timing diagram, generate second detection information to characterize whether the power equipment has an abnormality within the predetermined time period.

[0066] As an example, the aforementioned execution entity can determine a first substation equipment anomaly indicator for a frequency diagram and a second substation equipment anomaly indicator for a time sequence diagram. In response to determining that there is data in the dataset involved in the first frequency diagram that does not meet the first substation equipment anomaly indicator, or that there is data in the dataset involved in the first time sequence diagram that does not meet the second substation equipment anomaly indicator, second detection information characterizing that the aforementioned substation equipment has experienced an equipment anomaly within the aforementioned predetermined time period is generated.

[0067] Step 6: Based on the first detection information and the second detection information mentioned above, generate the detection results for the aforementioned power equipment.

[0068] As an example, firstly, the executing entity can determine the information level corresponding to the first detection information and the information level corresponding to the second detection information. Then, the detection information with the highest corresponding information level among the first and second detection information is determined as the first detection information.

[0069] Optionally, the aforementioned execution entity may generate second detection information characterizing whether the aforementioned power equipment has experienced an abnormality within the aforementioned predetermined time period, based on the aforementioned first spectrum diagram and the aforementioned first timing diagram, including the following steps:

[0070] The first step is to extract a predetermined number of values ​​from the X-axis of the first spectrum diagram to obtain a predetermined number of points, thus obtaining the first point sequence.

[0071] The second step is to extract a predetermined number of values ​​from the X-axis of the first time series diagram to obtain a predetermined number of points, thus obtaining the second point sequence.

[0072] The third step is to input the above first point sequence into a pre-trained bidirectional long short-term memory (BiLSTM) artificial neural network model to generate the seventh sub-detection information.

[0073] The fourth step is to input the above second-point sequence into a pre-trained bidirectional long short-term memory artificial neural network model to generate the eighth sub-detection information.

[0074] Fifth step: In response to determining that either the seventh sub-detection information or the eighth sub-detection information indicates that the above-mentioned power equipment has experienced an equipment malfunction within the above-mentioned predetermined time period, generate second detection information indicating that the above-mentioned power equipment has experienced an equipment malfunction within the above-mentioned predetermined time period.

[0075] Step 6: In response to determining that the seventh and eighth sub-detection information indicates that the above-mentioned power equipment has not experienced any equipment abnormalities during the above-mentioned predetermined time period, generate second detection information indicating that the above-mentioned power equipment has not experienced any equipment abnormalities during the above-mentioned predetermined time period.

[0076] In some optional implementations of certain embodiments, generating second detection information characterizing whether the power equipment experiences an abnormality within the predetermined time period based on the first spectrum diagram and the first timing diagram may include the following steps:

[0077] The first step is to obtain the second recorded audio from the adjacent area corresponding to the aforementioned power equipment.

[0078] Among them, the adjacent area corresponding to the power equipment can be the site outside the substation.

[0079] The second step is to generate a second spectrogram and a second timing diagram for the second recorded audio.

[0080] As an example, the aforementioned execution entity can utilize the spectrogram generation device and the timing diagram generation device to generate a second spectrogram and a second timing diagram for the aforementioned second recorded audio.

[0081] The third step is to generate frequency difference information based on the first spectrum diagram and the second spectrum diagram mentioned above.

[0082] As an example, firstly, the executing entity can extract a predetermined number of values ​​from the X-axis of the first spectrogram to obtain a predetermined number of points, thus obtaining a first point sequence. Then, the executing entity can extract a predetermined number of values ​​from the X-axis of the second spectrogram to obtain a predetermined number of points, thus obtaining a third point sequence. There is a one-to-one correspondence between the x-coordinates of the first points in the first point sequence and the x-coordinates of the third points in the third point sequence. Finally, the y-coordinate value of each point in the first point sequence is subtracted from the y-coordinate value of the corresponding point in the third point sequence to generate a first subtracted y-coordinate value sequence, which serves as frequency difference information. For example, the first point sequence includes: a first target point, a second target point, and a third target point. The third point sequence includes: a fourth target point, a fifth target point, and a sixth target point. The x-coordinates of the first and fourth target points are the same. The x-coordinates of the second and fifth target points are the same. The x-coordinates of the third and sixth target points are the same. The first subtraction sequence of ordinate values ​​includes: the ordinate value of the first target point minus the ordinate value of the fourth target point, the ordinate value of the second target point minus the ordinate value of the fifth target point, and the ordinate value of the third target point minus the ordinate value of the sixth target point.

[0083] The fourth step is to generate the fifth sub-detection information based on the frequency difference information mentioned above.

[0084] As an example, in response to the existence of three consecutive first subtraction ordinate values ​​less than the first ordinate threshold in the sequence of first subtraction ordinate values ​​corresponding to the determined frequency difference information, a fifth sub-detection information is generated that characterizes the above-mentioned power equipment having an equipment abnormality within the above-mentioned predetermined time period.

[0085] Fifth step: Generate response difference information based on the first timing diagram and the second timing diagram mentioned above.

[0086] As an example, firstly, the executing entity can extract a predetermined number of values ​​from the X-axis of the first timeline diagram to obtain a predetermined number of points, thus obtaining a second point sequence. Then, the executing entity can extract a predetermined number of values ​​from the X-axis of the second timeline diagram to obtain a predetermined number of points, thus obtaining a fourth point sequence. There is a one-to-one correspondence between the x-coordinates of the second points in the second point sequence and the x-coordinates of the fourth points in the fourth point sequence. Finally, the y-coordinate value of each point in the second point sequence is subtracted from the y-coordinate value of the corresponding point in the fourth point sequence to generate a second subtracted y-coordinate value sequence, which serves as the response difference information. For example, the second point sequence includes: the seventh target point, the eighth target point, and the ninth target point. The fourth point sequence includes: the tenth target point, the eleventh target point, and the twelfth target point. The x-coordinates of the seventh and tenth target points are the same. The x-coordinates of the eighth and eleventh target points are the same. The x-coordinates of the ninth and twelfth target points are the same. The second subtraction sequence of ordinate values ​​includes: the ordinate value of the seventh target point minus the ordinate value of the tenth target point, the ordinate value of the eighth target point minus the ordinate value of the eleventh target point, and the ordinate value of the ninth target point minus the ordinate value of the twelfth target point.

[0087] Step 6: Based on the above response difference information, generate the sixth sub-detection information.

[0088] As an example, in response to the existence of three consecutive second subtraction ordinate values ​​less than the second ordinate threshold in the sequence of second subtraction ordinate values ​​corresponding to the determination of response difference information, a sixth sub-detection information is generated to characterize that the above-mentioned power equipment has an equipment abnormality within the above-mentioned predetermined time period.

[0089] Step 7: Generate the second detection information based on the fifth and sixth sub-detection information.

[0090] As an example, in response to determining that either the fifth sub-detection information or the sixth sub-detection information indicates that the substation equipment has experienced an equipment malfunction during the predetermined time period, a second detection information indicating that the substation equipment has experienced an equipment malfunction during the predetermined time period is generated.

[0091] The aforementioned "optional content," as one of the inventive points, solves the second technical problem of "insufficient accuracy in detecting abnormalities in power equipment." Based on this, this disclosure can generate more accurate second detection information by analyzing the differences between the first and second spectrum diagrams, and the differences between the first and second time-series diagrams, leading to more accurate subsequent detection results.

[0092] In some optional implementations of certain embodiments, generating the detection result for the substation based on the first detection information and the second detection information may include the following steps:

[0093] The first step involves, in response to determining that either the first detection information or the second detection information indicates an equipment malfunction in the substation within the predetermined time period, acquiring a sequence of historical equipment output data for the substation within the predetermined time period. The historical equipment output data can be the operating data of the substation. For example, for a transformer, the historical equipment output data could include: output voltage, output current, and transformer power.

[0094] The second step is to input the above-mentioned historical device output data sequence into the detection result generation model to generate the above-mentioned detection results.

[0095] The detection result generation model can be any model that generates detection results. For example, the detection result generation model can be a temporal neural network. For example, the detection result generation model can be a Long Short-Term Memory (LSTM) network model.

[0096] In some optional implementations of certain embodiments, generating first detection information characterizing whether the substation equipment has experienced an abnormality within the predetermined time period based on the first infrared imaging image sequence may include the following steps:

[0097] First, for each first infrared imaging image in the first infrared imaging image sequence described above, perform the following first image processing steps:

[0098] Sub-step 1: In response to determining that the first infrared imaging image is not the initial infrared imaging image in the first infrared imaging image sequence, the pixel matrix corresponding to the first infrared imaging image is subtracted from the pixel matrix corresponding to the previous frame image of the first infrared imaging image to obtain the first subtraction matrix.

[0099] The initial infrared imaging image mentioned above can be the earliest corresponding first infrared imaging image in the first infrared imaging image sequence.

[0100] Optionally, in response to determining that the first infrared imaging image is the initial infrared imaging image in the first infrared imaging image sequence, the pixel matrix corresponding to the initial infrared imaging image is determined as the first subtraction matrix.

[0101] Sub-step 2: Divide each element of the first subtraction matrix by each element of the matrix corresponding to the first infrared imaging image to obtain the division matrix.

[0102] As an example, the aforementioned execution entity can divide each element in the first subtraction matrix by the element in the same position in the matrix corresponding to the first infrared imaging image to generate a division value and obtain a division matrix.

[0103] The second step is to generate first sub-detection information based on the obtained phase division matrix sequence, which characterizes whether the above-mentioned power equipment has experienced equipment abnormality within the above-mentioned predetermined time period.

[0104] As an example, the aforementioned execution entity can input the division matrix sequence into the detection information generation model to obtain the first sub-detection information. The detection information generation model can be a model that generates information characterizing whether the substation equipment has experienced an anomaly within the predetermined time period. For example, the detection information generation model can be a multi-layered, serially connected convolutional neural network.

[0105] Optionally, the aforementioned execution entity can generate first sub-detection information characterizing whether the aforementioned power equipment has experienced an abnormality within the aforementioned predetermined time period based on the obtained phase division matrix sequence, which may include the following steps:

[0106] Step 1: For each division matrix in the division matrix sequence, perform the following numerical determination steps:

[0107] Sub-step 1: Determine each element of the above division matrix.

[0108] Sub-step 2: Determine the number of elements among the above elements that exceed the first value. For example, the first value could be 0.7.

[0109] Sub-step 3: Divide the above number by the number of elements corresponding to each of the above elements to obtain the division value.

[0110] Step 2: Determine the division matrix whose corresponding division value is greater than the second value from the above division matrix sequence, and obtain at least one division matrix.

[0111] Step 3: In response to determining that there are three time-continuous division matrices in at least one division matrix, generate first sub-detection information characterizing that the above-mentioned power equipment has an equipment abnormality within the above-mentioned predetermined time period.

[0112] Step 4: In response to determining that there are no three time-continuous division matrices in at least one division matrix, generate first sub-detection information characterizing that no equipment abnormality has occurred in the aforementioned substation within the aforementioned predetermined time period.

[0113] The third step is to generate the first detection information based on the first sub-detection information.

[0114] As an example, the aforementioned executing entity may determine the aforementioned first sub-detection information as the aforementioned first detection information.

[0115] Optionally, generating the first detection information based on the first sub-detection information may include the following steps:

[0116] The first step is to acquire the second infrared imaging video of the site corresponding to the aforementioned power equipment within a predetermined time period, captured by the second infrared camera.

[0117] There is a one-to-one temporal correspondence between the frames of the first infrared imaging video and the frames of the second infrared imaging video. The site corresponding to the power equipment can be the area surrounding the substation.

[0118] The second step involves performing frame extraction on the second infrared imaging video at predetermined intervals to obtain a second infrared imaging image sequence.

[0119] Among them, the second infrared imaging image in the second infrared imaging image sequence has a time correspondence with the first infrared imaging image in the first infrared imaging image sequence.

[0120] Third, for each of the first infrared imaging images in the above first infrared imaging image sequence, perform the following second image processing steps:

[0121] Sub-step 1: Determine a second infrared imaging image that has a time correspondence with the first infrared imaging image mentioned above, and use it as the second target infrared imaging image.

[0122] Sub-step 2: Subtract the pixel matrix corresponding to the first infrared imaging image from the pixel matrix corresponding to the second target infrared imaging image to obtain the second subtraction matrix.

[0123] The fourth step is to generate second sub-detection information based on the obtained second subtraction matrix sequence, which characterizes whether the above-mentioned power equipment has experienced equipment abnormalities within the above-mentioned predetermined time period.

[0124] As an example, in response to determining that there are three temporally consecutive second subtraction matrices in the second subtraction matrix sequence, second sub-detection information is generated indicating that the power equipment experienced an anomaly during the predetermined time period. Similarly, in response to determining that there are no three temporally consecutive second subtraction matrices in the second subtraction matrix sequence, second sub-detection information is generated indicating that the power equipment did not experience an anomaly during the predetermined time period.

[0125] The fifth step is to acquire a diagram of the substation equipment. The resolution of this diagram is the same as that of the first infrared imaging image. For example, the resolution of the substation equipment diagram is 400×600. The resolution of the first infrared imaging image is also 400×600.

[0126] The sixth step is to determine the equipment component diagrams for each device in the aforementioned power equipment diagram. For example, for a transformer, the individual equipment components may include: tap changers, bushings, oil conservators, cooling devices, pressure relief valves, and gas relays.

[0127] Step 7: For each first infrared imaging image in the above first infrared imaging image sequence, perform the following third image processing step:

[0128] Sub-step 1: In response to determining that the first infrared imaging image is not the initial infrared imaging image in the first infrared imaging image sequence, the infrared imaging images are linked and displayed according to the device component diagrams of each device component to obtain a segmented infrared imaging component image set. There is a one-to-one correspondence between the segmented infrared imaging component images in the segmented infrared imaging component image set and the device components in the device component diagrams.

[0129] As an example, the aforementioned execution entity can perform image segmentation processing on the aforementioned infrared imaging image based on the distribution position of each device component in the device component diagram to obtain a segmented infrared imaging component atlas.

[0130] Sub-step 2: Determine the average pixel value of the pixel matrix corresponding to each segmented infrared imaging component in the above segmented infrared imaging component set, and obtain the set of average pixel values.

[0131] The eighth step is to generate third sub-detection information based on the obtained pixel average value set sequence.

[0132] As an example, firstly, a pixel threshold is determined for each device component. This is the anomaly threshold corresponding to the device component. When the average number of pixels in the area corresponding to a device component is greater than the anomaly threshold, it is determined that the device component has an anomaly within a predetermined time period. Then, for each first infrared imaging image in the first infrared imaging image sequence, it is determined whether the average value of each pixel in the corresponding pixel average value set of the first infrared imaging image is greater than the corresponding anomaly threshold. There is a one-to-one correspondence between the average pixel value in the pixel average value set and each segmented infrared imaging component image in the segmented infrared imaging component image set. Finally, for each first infrared imaging image in the first infrared imaging image sequence, in response to determining that there is a situation where the average pixel value is greater than the corresponding anomaly threshold, third sub-detection information characterizing whether the substation equipment has an anomaly within the predetermined time period is generated.

[0133] Step nine involves inputting each of the first infrared imaging images in the aforementioned first infrared imaging image sequence into the brightness level generation model to generate brightness levels, resulting in a brightness level sequence. The brightness level is a brightness transformation level based on the brightness of the target substation equipment during normal operation. For example, the brightness of the substation equipment during normal operation is set as the base brightness, i.e., brightness level 1. Subsequently, when the substation equipment operates abnormally, it is usually accompanied by abnormal frequency vibrations. This vibration causes a corresponding change in the phase of the light reflected from the object's surface. By monitoring and amplifying the brightness changes of pixels in the image captured by the infrared camera, these minute vibrations can be observed. Therefore, based on this, brightness changes can be further divided into: brightness level 2, brightness level 3, and brightness level 4. The image brightness corresponding to brightness level 2 is greater than that corresponding to brightness level 1. The image brightness corresponding to brightness level 3 is greater than that corresponding to brightness level 2. The image brightness corresponding to brightness level 4 is greater than that corresponding to brightness level 3.

[0134] The brightness level generation model can be any model that generates brightness levels. This brightness level generation model can be a classification model. For example, it can be a convolutional neural network model.

[0135] Step 10: Generate the fourth sub-detection information based on the above brightness level sequence.

[0136] As an example, in response to the determination that there are three or more consecutive brightness levels of 1 in the brightness level sequence, a fourth detection message is generated to characterize whether the above-mentioned power equipment has experienced an equipment malfunction within the above-mentioned predetermined time period.

[0137] Step 11: Generate the first detection information based on the first sub-detection information, the second sub-detection information, the third sub-detection information, and the fourth sub-detection information.

[0138] As an example, firstly, the executing entity can determine the information level corresponding to the first sub-detection information, the information level corresponding to the second sub-detection information, the information level corresponding to the third sub-detection information, and the information level corresponding to the fourth sub-detection information. Then, the detection information with the highest corresponding information level among the first, second, third, and fourth sub-detection information is determined as the first detection information.

[0139] The above embodiments of this disclosure have the following beneficial effects: the self-configured audit link display method of some embodiments of this disclosure can efficiently and quickly generate audit results corresponding to the configuration task information configured for the target audit business. Specifically, the reason for the inefficient and slow generation of audit results is that the configuration efficiency of audit nodes and configuration conditions is low, often resulting in missing audit nodes or configuration conditions. This not only leads to inaccurate and inefficient subsequent audit results but also wastes a lot of manpower and resources. Based on this, the self-configured audit link display method of some embodiments of this disclosure firstly, in response to detecting the tree node processing operation of the target audit business process tree model displayed on the audit process maintenance interface, adjusts the tree model nodes of the target audit business process tree model to obtain the adjusted tree model. The audit process maintenance interface is the interface in the audit business platform used to maintain the business process of the target audit business, and the target audit business process tree model represents the node association relationship of multiple audit nodes corresponding to the target audit business. Here, the process tree model can explicitly display multiple audit nodes for the target audit business, avoiding the problem of missing configuration audit nodes caused by manual input of audit nodes. In addition, the audit process maintenance interface facilitates the maintenance of the target audit business process tree model, allowing for real-time adjustments to ensure its effectiveness. Next, in response to a detected task configuration operation on the task information configuration interface, and the absence of historically frequently used configuration task information identical to the first audit node configuration information in the historical commonly used configuration task information set, corresponding configuration node information is generated based on the first audit node configuration information. The task information configuration interface is the interface used for configuring task information within the audit business platform, and the first audit node configuration information is the information entered on the task information configuration interface. Here, the task information configuration interface facilitates audit node configuration. Furthermore, by determining whether historically frequently used configuration task information identical to the first audit node configuration information exists in the historical commonly used configuration task information set, the configuration efficiency of audit nodes can be effectively improved. Optionally, if historically frequently used configuration task information identical to the first audit node configuration information exists in the historical commonly used configuration task information set, reconfiguration is unnecessary; task configuration (i.e., conditional configuration) can be performed on the historically frequently used configuration information with identical content. Next, based on the configuration node information and the first task configuration information entered in the task information configuration interface, accurate configuration task information can be generated. Then, in response to receiving a data retrieval operation for the configuration task information, the dataset associated with the configuration task information is retrieved from the target database for subsequent business analysis of the target audit business.Furthermore, based on the aforementioned dataset, accurate business analysis results can be generated for the aforementioned target audit business. Then, the aforementioned business analysis results, the aforementioned configuration task information, the aforementioned adjusted tree model, and the aforementioned dataset are linked and packaged to generate a packaged link. Here, the link allows for convenient subsequent extraction of the business analysis results, configuration task information, adjusted tree model, and dataset. Finally, the aforementioned packaged link is displayed in encrypted form on the business information retrieval interface, allowing relevant personnel to retrieve the corresponding business analysis results by decryption. The aforementioned business information retrieval interface is the interface within the aforementioned audit business platform used to retrieve business information corresponding to the audit business.

[0140] Further reference Figure 2 As an implementation of the methods shown in the above figures, this disclosure provides some embodiments of a self-configurable audit link display device, which are similar to... Figure 1 Corresponding to the method embodiments shown, this self-configured audit link display device can be specifically applied to various electronic devices.

[0141] like Figure 2As shown, a self-configured audit link display device 200 includes: a tree model node adjustment unit 201, a first generation unit 202, a second generation unit 203, a retrieval unit 204, a third generation unit 205, a packaging unit 206, and a display unit 207. The tree model node adjustment unit 201 is configured to adjust the tree model nodes of the target audit business process tree model displayed on the audit process maintenance interface in response to detecting a tree node processing operation on the target audit business process tree model displayed on the audit process maintenance interface, thereby obtaining an adjusted tree model. The audit process maintenance interface is an interface in the audit business platform used to maintain the business process of the target audit business, and the target audit business process tree model represents the node association relationship of multiple audit nodes corresponding to the target audit business. The first generation unit 202 is configured to generate corresponding configuration node information based on the first audit node configuration information in response to detecting a task configuration operation on the task information configuration interface and that there is no historical configuration task information in the historical commonly used configuration task information set that has the same content as the first audit node configuration information. The task information configuration interface is an interface in the audit business platform used to configure task information, and the first audit node configuration information is generated in the task information configuration interface. The system comprises: a first generation unit 203, configured to generate corresponding configuration task information based on the configuration node information and the first task configuration information input in the task information configuration interface; a second generation unit 204, configured to retrieve a dataset associated with the configuration task information from the target database in response to a data retrieval operation received for the configuration task information; a third generation unit 205, configured to generate business analysis results for the target audit business based on the dataset; a packaging unit 206, configured to link and package the business analysis results, the configuration task information, the adjusted tree model, and the dataset to generate a packaged link; and a display unit 207, configured to display the packaged link in encrypted form on the business information retrieval interface, allowing relevant personnel to retrieve the business analysis results corresponding to the packaged link by decryption. The business information retrieval interface is the interface in the audit business platform used to retrieve business information corresponding to the audit business.

[0142] It is understandable that the units recorded in the self-configured audit link display device 200 are related to the reference. Figure 1 The steps in the described method correspond to each other. Therefore, the operations, features, and beneficial effects described above for the method also apply to the self-configured audit link display device 200 and the units contained therein, and will not be repeated here.

[0143] The following is for reference. Figure 3It shows a schematic diagram of the structure of an electronic device (e.g., an electronic device) 300 suitable for implementing some embodiments of the present disclosure. Figure 3 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of this disclosure.

[0144] like Figure 3 As shown, the electronic device 300 may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. The RAM 303 also stores various programs and data required for the operation of the electronic device 300. The processing unit 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0145] Typically, the following devices can be connected to I / O interface 305: input devices 306 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 307 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 308 including, for example, magnetic tapes, hard disks, etc.; and communication devices 309. Communication device 309 allows electronic device 300 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 3 An electronic device 300 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 3 Each box shown can represent a device or multiple devices as needed.

[0146] In particular, according to some embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 309, or installed from storage device 308, or installed from ROM 302. When the computer program is executed by processing device 301, it performs the functions defined in the methods of some embodiments of this disclosure.

[0147] It should be noted that, in some embodiments of this disclosure, the computer-readable medium described above may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In some embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In some embodiments of this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0148] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0149] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to: in response to detecting a tree node processing operation on the target audit business process tree model displayed on the audit process maintenance interface, adjust the tree model nodes of the target audit business process tree model to obtain an adjusted tree model, wherein the aforementioned audit process maintenance interface is an interface in the audit business platform used to maintain the business process of the target audit business, and the aforementioned target audit business process tree model represents the node association relationship of multiple audit nodes corresponding to the target audit business; in response to detecting a task configuration operation on the task information configuration interface, and that there is no historical configuration task information in the historical commonly used configuration task information set that has the same content as the first audit node configuration information, generate corresponding configuration node information based on the aforementioned first audit node configuration information, wherein the aforementioned task information configuration interface is the audit business... The platform includes an interface for configuring task information. The first audit node configuration information is the information entered in the task information configuration interface. Based on the configuration node information and the first task configuration information entered in the task information configuration interface, corresponding configuration task information is generated. In response to receiving a data retrieval operation for the configuration task information, a dataset associated with the configuration task information is retrieved from the target database. Based on the dataset, a business analysis result for the target audit business is generated. The business analysis result, the configuration task information, the adjusted tree model, and the dataset are linked and packaged to generate a packaged link. The packaged link is displayed in encrypted form on the business information retrieval interface, allowing relevant personnel to retrieve the business analysis result corresponding to the packaged link through decryption. The business information retrieval interface is the interface in the audit business platform used to retrieve business information corresponding to the audit business.

[0150] Computer program code for performing operations of some embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0151] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0152] The units described in some embodiments of this disclosure can be implemented in software or hardware. The described units can also be housed in a processor; for example, a processor may be described as including: a tree model node adjustment unit, a first generation unit, a second generation unit, a retrieval unit, a third generation unit, a packaging unit, and a display unit. The names of these units do not necessarily limit the unit itself; for example, the third generation unit may also be described as "a unit that generates business analysis results for the aforementioned target audit business based on the aforementioned dataset."

[0153] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0154] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. A method for displaying a self-configurable audit link, comprising: In response to detecting a tree node processing operation on the target audit business process tree model displayed on the audit process maintenance interface, the tree model nodes of the target audit business process tree model are adjusted to obtain an adjusted tree model. The audit process maintenance interface is an interface in the audit business platform used to maintain the business process of the target audit business. The target audit business process tree model represents the node association relationship of multiple audit nodes corresponding to the target audit business. In response to detecting a task configuration operation on the task information configuration interface and the absence of historical configuration task information with identical content to the first audit node configuration information in the historical frequently used configuration task information set, corresponding configuration node information is generated based on the first audit node configuration information. The task information configuration interface is the interface in the audit business platform used for configuring task information, and the first audit node configuration information is the information entered on the task information configuration interface, representing the configuration information of the selected audit node. Based on the configuration node information and the first task configuration information entered in the task information configuration interface, corresponding configuration task information is generated. The first task configuration information includes: basic task configuration information and task condition configuration information. The basic task configuration information includes: task name information, task audit type information, information of the implementation unit involved in the task, and remarks information. The task condition configuration information includes: statistical time condition configuration information. In response to receiving a data retrieval operation for the configuration task information, retrieve the dataset associated with the configuration task information from the target database; Based on the dataset, generate business analysis results for the target audit business; The business analysis results, the configuration task information, the adjusted tree model, and the dataset are linked and packaged to generate a packaged link; The packaged link is displayed in encrypted form on the business information retrieval interface, so that relevant personnel can retrieve the business analysis results corresponding to the packaged link by decryption. The business information retrieval interface is the interface in the audit business platform used to retrieve the business information corresponding to the audit business.

2. The method according to claim 1, wherein, The method further includes: Add the configuration task information to the historical frequently used configuration task information set to obtain the configuration task information set after addition; In response to detecting a task configuration operation on the task information configuration interface, and the existence of historical configuration task information with the same content as the second audit node configuration information in the historical commonly used configuration task information set, the task configuration of the historical configuration task information with the same content is adjusted according to the configuration node information and the second task configuration information entered on the task information configuration interface, so as to obtain the adjusted configuration task information.

3. The method according to claim 1, wherein, The step of adjusting the tree model nodes of the target audit business process tree model to obtain the adjusted tree model includes: Determine the association between the audit node to be processed and the target audit business process tree model; In response to determining that the tree node processing operation is an audit node addition operation, the audit node to be processed is added to the corresponding position in the target audit business process tree model according to the association relationship, and the tree model after addition is obtained as the adjusted tree model. In response to determining that the tree node processing operation is an audit node deletion operation, according to the association relationship, the audit node corresponding to the audit node to be processed is deleted from the target audit business process tree model to obtain the deleted tree model, which is used as the adjusted tree model. In response to determining that the tree node processing operation is an audit node replacement operation, the audit node corresponding to the audit node to be processed in the target audit business process tree model is replaced with the audit node to be processed according to the association relationship, so as to obtain the replaced tree model, which is used as the adjusted tree model.

4. The method according to claim 1, wherein, The method further includes: In response to determining that the target audit business is an audit business targeting the target substation equipment, a predicted substation equipment problem is generated based on the business analysis results; Based on the configuration task information, determine the responsible department information corresponding to the estimated substation equipment problem; The estimated substation equipment problems are sent to the testing platform corresponding to the responsible department information, so that the testing platform can perform substation equipment testing for the estimated substation equipment problems.

5. The method according to claim 4, wherein, The predicted substation equipment problems are detected through the following steps: Acquire a first infrared imaging video of the target substation equipment captured by a first infrared camera within a predetermined time period, and acquire a first recorded audio of the target substation equipment collected by a device sound collection device within the predetermined time period, wherein the device sound collection device is a device installed on the target substation equipment for collecting the operating sound of the target substation equipment. At predetermined intervals, the first infrared imaging video is subjected to frame extraction processing to obtain the first infrared imaging image sequence. Generate a first spectrogram and a first timing diagram for the first recorded audio; Based on the first infrared imaging image sequence, first detection information is generated to characterize whether the target substation equipment has experienced an equipment abnormality within the predetermined time period; Based on the first spectrum diagram and the first time sequence diagram, second detection information is generated to characterize whether the target substation equipment has experienced equipment abnormality within the predetermined time period; Based on the first detection information and the second detection information, a detection result is generated for the target substation.

6. The method according to claim 5, wherein, The step of generating first detection information characterizing whether the target substation equipment has experienced an abnormality within the predetermined time period based on the first infrared imaging image sequence includes: For each first infrared imaging image in the first infrared imaging image sequence, the following first image processing steps are performed: In response to determining that the first infrared imaging image is not the initial infrared imaging image in the first infrared imaging image sequence, the pixel matrix corresponding to the first infrared imaging image is subtracted from the pixel matrix corresponding to the previous frame image of the first infrared imaging image to obtain the first subtraction matrix; Divide each element of the first subtraction matrix by each element of the matrix corresponding to the first infrared imaging image to obtain the division matrix; Based on the obtained phase division matrix sequence, first sub-detection information is generated to characterize whether the target substation equipment has experienced equipment abnormality within the predetermined time period; The first detection information is generated based on the first sub-detection information.

7. The method according to claim 6, wherein, The step of generating the first detection information based on the first sub-detection information includes: Acquire second infrared imaging video of the site corresponding to the target substation within a predetermined time period, captured by a second infrared camera; At every predetermined number of frames, the second infrared imaging video is subjected to frame extraction processing to obtain a second infrared imaging image sequence, wherein the second infrared imaging image in the second infrared imaging image sequence has a time correspondence with the first infrared imaging image in the first infrared imaging image sequence. For each first infrared imaging image in the first infrared imaging image sequence, the following second image processing step is performed: A second infrared imaging image that has a temporal correspondence with the first infrared imaging image is determined as the second target infrared imaging image; Subtract the pixel matrix corresponding to the second target infrared image from the pixel matrix corresponding to the first infrared image to obtain the second subtraction matrix; Based on the obtained second subtraction matrix sequence, a second sub-detection information is generated to characterize whether the target substation equipment has experienced an equipment abnormality within the predetermined time period; Obtain a diagram of the power equipment, wherein the resolution of the diagram is the same as that of the first infrared imaging image; Determine the equipment component diagram of each equipment component in the power equipment diagram; For each first infrared imaging image in the first infrared imaging image sequence, the following third image processing step is performed: In response to determining that the first infrared imaging image is not the initial infrared imaging image in the first infrared imaging image sequence, the infrared imaging images are linked and displayed according to the device component diagram of each device component to obtain a segmented infrared imaging component diagram set. The average pixel value of the pixel matrix corresponding to each segmented infrared imaging component image in the segmented infrared imaging component image set is determined to obtain the set of average pixel values; Based on the obtained pixel average value set sequence, generate third sub-detection information; Each first infrared imaging image in the first infrared imaging image sequence is input into the brightness level generation model to generate brightness levels, resulting in a brightness level sequence. The brightness level is a brightness transformation level based on the brightness of the target power equipment during normal operation. Based on the brightness level sequence, a fourth sub-detection information is generated; The first detection information is generated based on the first sub-detection information, the second sub-detection information, the third sub-detection information, and the fourth sub-detection information.

8. A self-configurable audit link display device, comprising: The tree model node adjustment unit is configured to adjust the tree model nodes of the target audit business process tree model in response to detecting a tree node processing operation for the target audit business process tree model displayed on the audit process maintenance interface, thereby obtaining an adjusted tree model. The audit process maintenance interface is an interface in the audit business platform used to maintain the business process of the target audit business, and the target audit business process tree model represents the node association relationship of multiple audit nodes corresponding to the target audit business. The first generation unit is configured to, in response to detecting a task configuration operation on the task information configuration interface and the absence of historical configuration task information in the historical frequently used configuration task information set that has the same content as the first audit node configuration information, generate corresponding configuration node information based on the first audit node configuration information. The task information configuration interface is an interface in the audit business platform used for configuring task information, and the first audit node configuration information is the information entered on the task information configuration interface, representing the configuration information of the selected audit node. The second generation unit is configured to generate corresponding configuration task information based on the configuration node information and the first task configuration information input in the task information configuration interface. The first task configuration information includes: basic task configuration information and task condition configuration information. The basic task configuration information includes: task name information, task audit type information, information of the implementing unit involved in the task, and remarks information. The task condition configuration information includes: statistical time condition configuration information. The retrieval unit is configured to retrieve a dataset associated with the configuration task information from a target database in response to receiving a data retrieval operation for the configuration task information; The third generation unit is configured to generate business analysis results for the target audit business based on the dataset; The packaging unit is configured to link and package the business analysis results, the configuration task information, the adjusted tree model, and the dataset to generate a packaged link; The display unit is configured to display the packaged link in encrypted form on the business information retrieval interface, so that relevant personnel can retrieve the business analysis results corresponding to the packaged link by decryption. The business information retrieval interface is the interface in the audit business platform used to retrieve the business information corresponding to the audit business.

9. An electronic device, comprising: One or more processors; Storage device, on which one or more programs are stored, When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-7.

10. A computer-readable medium having a computer program stored thereon, wherein, When the program is executed by the processor, it implements the method as described in any one of claims 1-7.

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