Monitoring method, system and hardware equipment of fault recording device

Abstract

The present invention provides a monitoring method, system and hardware equipment for a fault recording device, including: collecting operating data in an electric power system in real time through sensors, analyzing the operating data based on an analysis model, and identifying potential abnormal patterns; automatically triggering a fault recording function of a fault recording device according to the potential abnormal pattern, and recording detailed data associated with the abnormal pattern; analyzing the detailed data to confirm whether a real fault exists, and generating a corresponding fault report, which is sent to a remote master station. In the present invention, potential abnormal patterns are quickly identified in the operating data collected in real time, and the fault recording function is automatically triggered, overcoming the current defects of low fault detection efficiency and inability to predict faults, which is of great significance for improving the fault detection efficiency and accuracy of the electric power system.

Description

Technical Field

[0001] The present invention relates to the technical field of fault recording, and in particular to a monitoring method, system and hardware equipment of a fault recording device. Background Art

[0002] The power system is one of the important infrastructures of modern society, and its stable operation is crucial to protecting residents' lives and industrial production. Faults are inevitable in power systems, which may cause power outages, equipment damage, and even safety accidents. Quickly and accurately detecting and locating faults in power systems is crucial to reducing losses and improving system reliability.

[0003] Problems with traditional fault detection methods: Traditional fault detection methods often rely on manual observation and empirical judgment, which is time-consuming and inefficient. As the scale of power systems expands, manual monitoring becomes increasingly unfeasible due to the huge amount of data that needs to be monitored. Manual judgment will miss some early or minor abnormal signals that may be precursors to major faults, i.e., it is impossible to predict faults in advance. Summary of the invention

[0004] The main purpose of the present invention is to provide a monitoring method, system and hardware equipment for a fault recording device, aiming to overcome the defects of low fault detection efficiency and inability to predict faults.

[0005] To achieve the above object, the present invention provides a monitoring method for a fault recording device, comprising the following steps:

[0006] Collecting operation data in the power system in real time through sensors, analyzing the operation data based on an analysis model, and identifying potential abnormal patterns;

[0007] According to the potential abnormal mode, automatically trigger the fault recording function of the fault recording device to record detailed data associated with the abnormal mode;

[0008] The detailed data is analyzed to confirm whether a real fault exists, and a corresponding fault report is generated and sent to a remote master station.

[0009] Furthermore, the fault recording device includes a management unit and a plurality of collection units;

[0010] The collection unit is used to collect detailed data related to the abnormal mode and send it to the management unit; the management unit is used to analyze the detailed data, and the management unit communicates with the remote master station through the service gateway.

[0011] Furthermore, before analyzing the operation data based on the analysis model, the method includes:

[0012] Obtaining the type and quantity of the operation data;

[0013] Obtaining an initial machine learning model pre-stored in a database; wherein the initial machine learning model is a pre-trained deep learning model;

[0014] Based on the types and quantities pre-stored in the database and the mapping relationship with the model parameters, the corresponding target model parameters are matched;

[0015] Based on the target model parameters, the model parameters of the initial machine learning model are updated to obtain the analysis model.

[0016] Further, the sending to the remote master station includes:

[0017] generating a request code based on the potential abnormal pattern;

[0018] An upload request instruction for generating a fault report is sent to a remote master station; wherein the upload request instruction carries the request code; the remote master station verifies the request code carried in the upload request instruction to confirm whether the upload request instruction is passed;

[0019] When receiving a feedback instruction from the remote master station indicating that the upload request instruction has been verified, the fault report is sent to the remote master station.

[0020] Further, the generating a request code based on the potential abnormal mode includes:

[0021] Obtain a standard character table; the standard character table includes cells of multiple rows and columns, each cell storing a character;

[0022] Obtaining a target serial number corresponding to the abnormal mode in a database; wherein the database stores serial numbers corresponding to each abnormal mode;

[0023] Based on the target sequence number, the standard character table is deformed to obtain a deformed data table;

[0024] Obtaining the probability corresponding to the abnormal pattern identified by the analysis model;

[0025] The request code is obtained based on the probability generation curve and the curve and the deformation data table.

[0026] Furthermore, the obtaining of the standard character table includes:

[0027] Acquire first identification information corresponding to the power system and second identification information corresponding to the fault recording device;

[0028] Concatenate the first identification information and the second identification information to obtain concatenated identification information;

[0029] A blank table is generated, and the characters in the concatenation identification information are added to the blank table one by one in sequence to obtain the standard character table.

[0030] Furthermore, based on the target sequence number, the standard character table is deformed to obtain a deformed data table, including:

[0031] The number of columns of the standard character table is changed to a target number of columns, wherein the target number of columns is a number corresponding to the target serial number; characters are sequentially filled into the changed character table, and the order of the characters in the standard character table according to the row arrangement is maintained;

[0032] Determine whether the last row of the changed character table is filled;

[0033] If it is a filled state, the changed character table is used as the deformed data table; if it is not a filled state, the last row of the changed character table is deleted and used as the deformed data table.

[0034] Further, the generating curve based on the probability, and obtaining the request code based on the curve and the deformation data table, includes:

[0035] Establishing a two-dimensional coordinate system with the lower left corner vertex of the deformation data table as the coordinate origin;

[0036] In the two-dimensional coordinate system, a straight line is constructed through the coordinate origin; wherein the value corresponding to the probability is used as the slope of the straight line;

[0037] Generate two offset straight lines parallel to the straight line on both sides of the straight line, and the offsets of the two offset straight lines and the straight line are the same, both of which are preset values; wherein the straight line and the two offset straight lines constitute two channels;

[0038] In the deformation data table, channel characters in cells in two channels are obtained, and the channel characters are combined in sequence to obtain the request code.

[0039] The present invention also provides a monitoring system for a fault recording device, comprising:

[0040] A first analysis unit, configured to collect operation data in the power system in real time through sensors, analyze the operation data based on an analysis model, and identify potential abnormal patterns;

[0041] A recording unit, configured to automatically trigger a fault recording function of a fault recording device according to the potential abnormal mode, and record detailed data associated with the abnormal mode;

[0042] The second analysis unit is used to analyze the detailed data, confirm whether there is a real fault, generate a corresponding fault report, and send it to the remote master station.

[0043] The present invention also provides a hardware device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any one of the above methods when executing the computer program.

[0044] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned methods are implemented.

[0045] The monitoring method, system and hardware equipment of the fault recording device provided by the present invention include: collecting the operating data in the power system in real time through sensors, analyzing the operating data based on the analysis model, and identifying potential abnormal modes; according to the potential abnormal mode, automatically triggering the fault recording function of the fault recording device, recording detailed data associated with the abnormal mode; analyzing the detailed data to confirm whether there is a real fault, and generating a corresponding fault report, and sending it to a remote master station. In the present invention, potential abnormal modes are quickly identified in the real-time collected operating data, and the fault recording function is automatically triggered, which overcomes the current defects of low fault detection efficiency and inability to predict faults, and is of great significance for improving the fault detection efficiency and accuracy of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a schematic diagram of the steps of a monitoring method of a fault recording device in one embodiment of the present invention;

[0047] Figure 2 is an application schematic diagram of a fault recording device in one embodiment of the present invention;

[0048] Figure 3 It is a structural block diagram of a monitoring system of a fault recording device in one embodiment of the present invention;

[0049] Figure 4 It is a schematic block diagram of the structure of a hardware device according to an embodiment of the present invention.

[0050] The implementation, functional features and advantages of the present invention will be further described in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0052] Reference Figure 1 In one embodiment of the present invention, a monitoring method for a fault recording device is provided, comprising the following steps:

[0053] Step S1, collecting operation data in the power system in real time through sensors, analyzing the operation data based on an analysis model, and identifying potential abnormal patterns;

[0054] Step S2, according to the potential abnormal mode, automatically triggering the fault recording function of the fault recording device to record detailed data associated with the abnormal mode;

[0055] Step S3, analyzing the detailed data to confirm whether there is a real fault, and generating a corresponding fault report and sending it to the remote master station.

[0056] In this embodiment, in the daily operation of the power system, ensuring its safety and reliability is a vital task. To this end, an efficient fault recording device monitoring method is proposed, which aims to monitor abnormal conditions in the power system in real time and take prompt actions to mitigate the impact of potential faults.

[0057] As described in step S1 above, real-time data collection and analysis;

[0058] There are various types of sensors installed in the power system. These sensors are spread throughout the power network and can capture key operating data such as voltage, current, frequency, etc. in real time. The data collected by these sensors is transmitted to a central processing unit, which has an advanced analytical model built in. This model uses complex algorithms to analyze the data in real time to identify any abnormal patterns that deviate from the normal range. For example, if a sudden drop in voltage or an abnormal fluctuation in current is detected, this may be a sign of an impending failure.

[0059] As described in step S2 above, automatic fault recording function triggering: Once the analysis model identifies potential abnormal patterns, the next step is to automatically trigger the recording function of the fault recording device. This means that when an abnormality is detected, all detailed data associated with these abnormal patterns will be recorded immediately. This data includes waveforms before and after the fault, event sequences, etc., which are crucial for subsequent fault analysis. In this way, it can be ensured that even faults that occur in the shortest time can be fully recorded.

[0060] As described in step S3 above: Fault confirmation and reporting: The last step is to conduct an in-depth analysis of the recorded detailed data to confirm whether a fault has actually occurred. This process involves the use of diagnostic algorithms to help distinguish between real faults and false alarms. Once the existence of a real fault is confirmed, a detailed fault report is automatically generated and sent to a remote monitoring center or master station. This report not only contains basic information about the fault, but also includes recommended countermeasures and possible cause analysis so that maintenance personnel can respond quickly and take appropriate repair measures. It is understandable that the above-mentioned diagnostic method for analyzing detailed data can be a pre-configured algorithm that has been pre-trained.

[0061] Through the above steps, a closed-loop fault monitoring system is established, which can detect anomalies in time, accurately record faults and quickly notify relevant personnel. This method greatly improves the reliability of the power system and reduces the power outage time and economic losses caused by faults. In short, this monitoring method quickly identifies potential abnormal patterns in real-time collected operating data and automatically triggers the fault recording function, overcoming the current defects of low fault detection efficiency and inability to predict faults, which is of great significance for improving the fault detection efficiency and accuracy of the power system.

[0062] Reference Figure 2 , in one embodiment, the fault recording device includes a management unit and a plurality of acquisition units;

[0063] The collection unit is used to collect detailed data related to the abnormal mode and send it to the management unit; the management unit is used to analyze the detailed data, and the management unit communicates with the remote master station through the service gateway.

[0064] In this embodiment, the fault recording device includes a management unit and a plurality of collection units, each of which collects various signals in the power system as the detailed data through the collection execution unit. The management unit is used to analyze the detailed data collected by the collection unit, and can send the analysis results to the remote master station through the V / GOOSE message and the DL / T 860 communication message via the service gateway. The management unit can also communicate with the integrated application host through the DL / T 860 communication message.

[0065] In this embodiment, the general technical parameters of the above-mentioned fault recording device include:

[0066] Environmental conditions

[0067] 1.1.1 Normal working atmospheric conditions

[0068] The normal atmospheric conditions for the fault recording device are as follows:

[0069] a) Ambient temperature: -10℃~+55℃;

[0070] b) Relative humidity: 5% to 95% (there should be no condensation or ice inside the device);

[0071] c) Atmospheric pressure: 80kPa~106kPa.

[0072] 1.1.2. Test normal atmospheric conditions

[0073] Unless otherwise specified, the ambient atmospheric conditions for measuring and testing the device are as follows:

[0074] a) Ambient temperature: +15℃~+35℃;

[0075] b) Relative humidity: 25% to 75%;

[0076] c) Atmospheric pressure: 80kPa~106kPa.

[0077] 1.1.3. Baseline test atmospheric conditions

[0078] The ambient atmospheric conditions for testing the inherent accuracy of the device are as follows:

[0079] a) Ambient temperature: +20℃±5℃;

[0080] b) Relative humidity: 45% to 75%;

[0081] c) Atmospheric pressure: 86kPa~106kPa.

[0082] 1.1.4 Storage and transportation environment conditions

[0083] The storage and transportation environment conditions of the device are as follows:

[0084] a) The storage environment temperature is -25℃~+55℃, and the relative humidity is not more than 85%;

[0085] b) The transportation environment temperature is -25℃~+70℃, and the relative humidity is not more than 85%

[0086] 1.2 Rated electrical parameters

[0087] The rated electrical parameters of the device are as follows:

[0088] a) AC voltage rating UN: 100V;

[0089] b) AC current rating IN: 1A, 5A;

[0090] c) Rated frequency fN: 50Hz;

[0091] d) DC voltage: 0V~600V.

[0092] 1.3 DC working power supply

[0093] DC working power supply of the device:

[0094] a) Rated voltage UdN: 220V, 110V;

[0095] b) Allowable deviation: -20% to +15%;

[0096] c) Ripple coefficient: not more than 5.

[0097] In one embodiment, before analyzing the operation data based on the analysis model, the process includes:

[0098] Obtaining the type and quantity of the operation data;

[0099] Obtaining an initial machine learning model pre-stored in a database; wherein the initial machine learning model is a pre-trained deep learning model;

[0100] Based on the types and quantities pre-stored in the database and the mapping relationship with the model parameters, the corresponding target model parameters are matched;

[0101] Based on the target model parameters, the model parameters of the initial machine learning model are updated to obtain the analysis model.

[0102] In this embodiment, first, real-time operation data is collected from the power system. These data usually include but are not limited to key indicators such as voltage, current, power, frequency, etc. Through the sensor network, these data are continuously transmitted to the central processing unit. At this stage, it is necessary to determine the specific type of data collected (such as voltage data, current data, etc.) and the amount of each type of data. This information is crucial for the subsequent selection of a suitable analysis model.

[0103] Next, a pre-trained deep learning model is obtained from the database as the initial model. This model has been trained on a large amount of historical data and has a certain generalization ability. It is worth noting that due to the complexity and diversity of the power system, a single model may not be able to adapt to all scenarios, so the model needs to be adjusted according to the type and quantity of data currently collected.

[0104] In order to make the initial model better adapt to the current specific situation, it is necessary to select appropriate target model parameters based on the mapping relationship between the data types and quantities stored in the database and the model parameters. The mapping relationship here refers to which specific parameter settings the model should use to achieve the best effect under different data types and quantities. For example, if a large amount of voltage data is collected, it may be necessary to increase the feature weights related to voltage and reduce the impact of other types of data.

[0105] Then, based on the matched target model parameters, the initial machine learning model is updated. This process usually involves fine-tuning the model's weights, biases and other parameters to make it more suitable for the characteristics of the current data set. In this way, the model's performance on new data can be significantly improved, enabling it to more accurately identify abnormal patterns.

[0106] Finally, the model with updated parameters becomes the required analysis model, which will play an important role in real-time data flow, helping to quickly and accurately identify potential abnormal patterns, thereby triggering the fault recording function and providing detailed data support for subsequent fault analysis.

[0107] Through the above steps, an analysis model that can dynamically adapt to different operating environments is constructed. This method not only improves the accuracy of fault detection, but also enables the fault recording device to capture important information more efficiently, thereby ensuring the stable operation of the power system.

[0108] In one embodiment, the sending to the remote master station includes:

[0109] generating a request code based on the potential abnormal pattern;

[0110] An upload request instruction for generating a fault report is sent to a remote master station; wherein the upload request instruction carries the request code; the remote master station verifies the request code carried in the upload request instruction to confirm whether the upload request instruction is passed;

[0111] When receiving a feedback instruction from the remote master station indicating that the upload request instruction has been verified, the fault report is sent to the remote master station.

[0112] In this embodiment, during the power system monitoring process, once the monitoring device detects a potential abnormal mode, it is necessary to promptly report the relevant information to the remote master station for further analysis and processing. In order to ensure the security and reliability of this process, a communication mechanism based on request code verification is designed. The following are the specific steps:

[0113] When the monitoring device finds a potential abnormal pattern, it automatically generates a unique request code based on the characteristics of the abnormal pattern. This request code is calculated based on the specific information of the current abnormal pattern and can be regarded as the identity of the abnormal event. This is done to ensure that each abnormal event has a unique corresponding identifier to facilitate subsequent tracking and processing.

[0114] Subsequently, an upload request instruction containing the request code is generated and sent to the remote master station. In addition to the request code, the upload request instruction may also contain some basic metadata, such as the ID of the monitoring device, the timestamp of the abnormality, etc. This information helps the remote master station understand the basic background of the request.

[0115] After receiving the upload request command, the remote master station will first verify the request code carried in it. This process is mainly to confirm the validity and authenticity of the upload request command. After the verification is passed, the remote master station will send a feedback command to the monitoring device, indicating that it is ready to receive a detailed fault report.

[0116] Once the monitoring device receives the feedback command from the remote master station and confirms that the upload request command has been verified, it will send a detailed fault report to the remote master station. The fault report contains all the data and information related to the abnormal mode, such as the specific characteristics of the abnormal mode, duration, possible cause analysis, etc., so that the remote master station can conduct in-depth analysis and take appropriate measures.

[0117] Through the above process, it can be ensured that only verified and true fault reports will be sent to the remote master station, thus avoiding unnecessary communication burden and protecting the security of the system. In addition, the verification mechanism based on the request code can also improve the response efficiency of the system and ensure that key information can be communicated in a timely and effective manner.

[0118] The entire process achieves safe and efficient transmission of fault reports through the generation, verification and feedback mechanism of request codes, which not only strengthens the security of the power system monitoring network, but also improves the efficiency and accuracy of remote fault diagnosis.

[0119] In one embodiment, generating a request code based on the potential abnormal pattern includes:

[0120] Obtain a standard character table; the standard character table includes cells of multiple rows and columns, each cell storing a character;

[0121] Obtaining a target serial number corresponding to the abnormal mode in a database; wherein the database stores serial numbers corresponding to each abnormal mode;

[0122] Based on the target sequence number, the standard character table is deformed to obtain a deformed data table;

[0123] Obtaining the probability corresponding to the abnormal pattern identified by the analysis model;

[0124] The request code is obtained based on the probability generation curve and the curve and the deformation data table.

[0125] In this embodiment, first, a predefined standard character table needs to be obtained. The table consists of multiple cells, each of which stores a specific character. This character table can be regarded as a two-dimensional array, and each row and column corresponds to a different character set. For example, the first row may be the English letters AZ, the second row may be the numbers 0-9, and so on.

[0126] Next, the serial number corresponding to the abnormal pattern is searched from the database. The database stores all known abnormal patterns and their corresponding serial numbers, which are used to uniquely identify each abnormal pattern. By matching the currently detected abnormal pattern, its record in the database can be found, and then its target serial number can be obtained.

[0127] The standard character table is deformed using the obtained target sequence number. Here, a preset algorithm can be used, such as selecting the target sequence number as an index value to select certain rows or columns in the character table, or directly using the target sequence number to replace characters in certain cells in the character table. In this way, the original standard character table becomes a deformed data table in which the order or distribution of the characters is changed.

[0128] By analyzing the model (such as the machine learning model), the probability of the currently detected abnormal pattern occurring can be determined. This probability reflects the credibility of the abnormal pattern, which is critical for the subsequent generation of the request code.

[0129] Based on the probability of abnormal mode occurrence, a probability curve is generated. This curve can be a simple linear function or a nonlinear function, depending on the needs of the actual application. The purpose of the probability curve is to map the probability to a specific range of values ​​for subsequent operations.

[0130] The last step is to generate a request code based on the probability curve and the previously deformed data table. Specifically, characters in the deformed data table can be selected according to the points on the probability curve to form the final request code. For example, in one embodiment, if a point on the probability curve corresponds to 0.65, then the character in the 6th row and 5th column of the deformed data table can be taken, and so on, until a complete request code is generated.

[0131] Through the above steps, it can be ensured that each generated request code is generated based on the actual detected abnormal pattern and its probability, thereby ensuring the uniqueness and validity of the request code. This method not only enhances the security of data transmission, but also improves the intelligence of the monitoring system.

[0132] The entire process generates a unique request code by combining the sequence number and occurrence probability of the abnormal pattern and the deformation of the standard character table, which not only ensures the secure transmission of information but also reflects the intelligence level of the system.

[0133] In one embodiment, obtaining the standard character table includes:

[0134] Acquire first identification information corresponding to the power system and second identification information corresponding to the fault recording device;

[0135] Concatenate the first identification information and the second identification information to obtain concatenated identification information;

[0136] A blank table is generated, and the characters in the concatenation identification information are added to the blank table one by one in sequence to obtain the standard character table.

[0137] In this embodiment, the power system usually includes various devices and components, each of which has its own unique identification information. It is necessary to extract the first identification information of the part related to this operation from the current power system. It is a string representing the type or version of the power system.

[0138] The fault recording device is a device in the power system used to record the changes in electrical quantities before and after a fault. Similarly, each fault recording device also has its own specific identification information, such as a serial number or model, etc. It is necessary to extract the second identification information from the currently used fault recording device.

[0139] The first identification information and the second identification information obtained above are concatenated to form a new string, namely, "concatenated identification information". This concatenation process can be simply completed by connecting two strings. For example, if the first identification information is "PS123" and the second identification information is "FR456", then the concatenated identification information is "PS123FR456".

[0140] Next, create a blank table consisting of multiple cells, each of which can store one character. Then fill the characters in the concatenated identification information into the cells of the blank table one by one in a certain order until it is full. For example, if the concatenated identification information is "PS123FR456", then the first row and first column of the table will be filled with "P", the first row and second column will be filled with "S", and so on, until all characters are placed in the table.

[0141] When all characters are correctly filled into the blank table, a standard character table is obtained. This character table contains information specific to the current power system and fault recording device, which can be used for subsequent operations, such as generating request codes, etc.

[0142] In this way, the uniqueness of the standard character table can be ensured, and it can also be closely related to the specific conditions of the current power system and fault recording device. This method not only helps to improve the safety and reliability of the system, but also ensures the accurate recording and transmission of abnormal patterns.

[0143] In one embodiment, the step of deforming the standard character table based on the target sequence number to obtain a deformed data table includes:

[0144] The number of columns of the standard character table is changed to a target number of columns, wherein the target number of columns is a number corresponding to the target serial number; characters are sequentially filled into the changed character table, and the order of the characters in the standard character table according to the row arrangement is maintained;

[0145] Determine whether the last row of the changed character table is filled;

[0146] If it is a filled state, the changed character table is used as the deformed data table; if it is not a filled state, the last row of the changed character table is deleted and used as the deformed data table.

[0147] In this embodiment, first, the role of the target serial number needs to be clarified, which determines the target number of columns of the standard character table to be transformed. For example, if the target serial number is 3, it means that the new transformed data table will have 3 columns.

[0148] Next, the number of columns of the standard character table is changed based on the target number. This means that the standard character table needs to be transformed and its number of columns is set to the number corresponding to the target number. For example, if the target number is 3, then the transformed table will have 3 columns.

[0149] In the transformed table, the characters are refilled in the order of the rows in the original standard character table. That is, the characters in the original table will be filled in the transformed table in the order of each row from left to right, and so on. The purpose of this is to ensure that the relative position relationship of the characters remains unchanged, only their arrangement is changed.

[0150] After the characters are filled in, check whether the last row of the transformed table is filled. If all cells in the last row have been filled with characters, no further operation is required. However, if there are empty cells in the last row that have not been filled with characters, it means that the row is not completely filled.

[0151] If the last row is filled, the table can be used directly as a deformation data table.

[0152] If the last row is not filled, that is, there are empty cells, this row needs to be deleted. In this way, the remaining table becomes the final deformed data table.

[0153] Through this deformation processing, a deformation data table with different numbers of columns can be generated according to different target serial numbers, so as to adapt to different application scenarios. At the same time, it can make the subsequent generation of verification codes more diverse and provide higher security.

[0154] In summary, the above method can not only flexibly adjust the table structure, but also ensure the integrity of the original data. It helps data management and transmission in the power system, and also simplifies the data processing process. In this way, the standard character table can be used more effectively to organize and transmit data.

[0155] In one embodiment, the generating the curve based on the probability, obtaining the request code based on the curve and the deformation data table, comprises:

[0156] Establishing a two-dimensional coordinate system with the lower left corner vertex of the deformation data table as the coordinate origin;

[0157] In the two-dimensional coordinate system, a straight line is constructed through the coordinate origin; wherein the value corresponding to the probability is used as the slope of the straight line;

[0158] Generate two offset straight lines parallel to the straight line on both sides of the straight line, and the offsets of the two offset straight lines and the straight line are the same, both of which are preset values; wherein the straight line and the two offset straight lines constitute two channels;

[0159] In the deformation data table, channel characters in cells in two channels are obtained, and the channel characters are combined in sequence to obtain the request code.

[0160] In this embodiment, in order to achieve effective encoding and decoding of data, a method based on probability generation curve is proposed to generate request code. This method combines the deformation data table and the probability generation curve, extracts the character sequence by establishing a two-dimensional coordinate system and defining a specific channel, and then forms a request code.

[0161] First, a two-dimensional coordinate system needs to be established based on the deformation data table. The lower left corner vertex of the deformation data table is used as the coordinate origin, which means the coordinate of the vertex is (0,0). The X axis is established along the horizontal direction of the data table, and the Y axis is established along the vertical direction.

[0162] Next, we need to construct a straight line that will pass through the origin of the coordinate system. The slope of this straight line is determined by a specific probability value, that is, the probability corresponding to the abnormal pattern identified by the analysis model. Assuming that the probability value corresponding to the abnormal pattern is P, this probability value can be converted into a slope value k, and then a straight line with a slope of k can be constructed.

[0163] In order to extract the characters in the channel, it is necessary to define two offset lines parallel to the above-mentioned slope line in the two-dimensional coordinate system. The distance (offset) between these two lines and the slope line is a preset value d. In this way, two channel areas are formed between the slope line and these two parallel lines.

[0164] Then, it is necessary to extract the characters located in these two channels from the deformation data table. Specifically, characters whose center points of cells fall in the channels, or characters whose entire cells are located in the channels, will be found. These characters will be selected according to their relative position order in the table. In one embodiment, since the coordinate system is established from the lower left corner, the order of selecting characters will follow the principle of moving from the lower left to the upper right. Of course, it can also be selected according to its original order in the deformation data table.

[0165] The last step is to combine the extracted channel characters in order to form a request code. The order of these characters is determined by their positions in the deformation data table, and this order is determined by the path direction in the coordinate system. It can also be determined according to their original order in the deformation data table, which is not limited here.

[0166] Through the above steps, a request code can be generated from the deformation data table, which contains the characters selected along the specified path (i.e., the slope straight line and its channel generated by probability). This method can not only be used to encrypt or decrypt information, but also can be used for error detection and correction during data transmission.

[0167] The advantage of this method is that it can generate different request codes according to different probability values, which increases the flexibility and security of encoding. At the same time, through the selection and processing of the deformation data table, this method can also be applied to various application scenarios that require data encoding.

[0168] In one embodiment, the step of deforming the standard character table based on the target sequence number to obtain a deformed data table includes:

[0169] Obtain all divisors of the target serial number as divisor serial numbers; calculate the average of all divisors to obtain an average number;

[0170] Obtain a preset transcoding table; the transcoding table includes three columns, the first column is a serial number, the second column is a character, and the third column is a transcoded character; the serial number, character, and mapping character of each row form a mapping relationship;

[0171] In the preset transcoding table, the transcoding characters corresponding to all divisor numbers are obtained as characters to be selected;

[0172] The characters to be selected are sequentially shifted to the end of the preset transcoding table, and other transcoding characters are shifted upward to fill the complete transcoding table;

[0173] Add the average number before each of the characters to be selected to obtain a deformation transcoding table;

[0174] Each character in the standard character table is transcoded based on the deformation transcoding table to obtain a deformation data table.

[0175] In this embodiment, in order to achieve effective data encoding, a method for transforming a standard character table based on a target sequence number is proposed to generate a transformed data table. This method reorders and replaces characters by using divisors of the target sequence number and a preset transcoding table.

[0176] First, we need to obtain all the divisors of the given target sequence number. These divisors will be used for character selection in the subsequent steps. Next, we calculate the average of these divisors, which will be used as an additional identifier in the subsequent steps.

[0177] Get a preset transcoding table, which contains three columns: sequence number, character, and transcoded character. Each row represents the mapping relationship between a character and its corresponding transcoded character. For example, the original character "A" in sequence number 1 can be mapped to the transcoded character "@".

[0178] In the preset transcoding table, all transcoding characters corresponding to the divisors of the target sequence number are selected. These transcoding characters are called candidate characters. These characters will be used for subsequent deformation operations.

[0179] Next, all the characters to be selected are moved to the end of the transcoding table in order. At the same time, other transcoding characters are shifted upward accordingly to fill the vacancies left by the characters to be selected. In this way, a new transcoding table is obtained, in which the characters to be selected are concentrated at the end of the table.

[0180] In the new transcoding table, the previously calculated average value is added before each candidate character. The average value serves as an additional identifier and can be used to restore the original character table in the subsequent decoding process.

[0181] The last step is to use this transformed transcoding table to transcode each character in the standard character table to generate a transformed data table. This step involves finding the corresponding transcoded character of each original character in the transformed transcoding table and replacing it in the transformed data table.

[0182] Through the above steps, a deformation data table based on the target sequence number can be generated from the standard character table. This method not only provides flexibility in data encoding, but also increases the security and complexity of encoding by introducing concepts such as divisors and averages.

[0183] In summary, the above technical solution can be widely used in cryptography, information security and other fields that require data to be securely encoded. By using different target serial numbers, a variety of different deformation data tables can be generated, thereby enhancing the data protection mechanism.

[0184] Reference Figure 3 In one embodiment of the present invention, a monitoring system for a fault recording device is provided, comprising:

[0185] A first analysis unit, configured to collect operation data in the power system in real time through sensors, analyze the operation data based on an analysis model, and identify potential abnormal patterns;

[0186] A recording unit, configured to automatically trigger a fault recording function of a fault recording device according to the potential abnormal mode, and record detailed data associated with the abnormal mode;

[0187] The second analysis unit is used to analyze the detailed data, confirm whether there is a real fault, generate a corresponding fault report, and send it to the remote master station.

[0188] In this embodiment, for the specific implementation of each unit in the above system embodiment, please refer to the above method embodiment, which will not be repeated here.

[0189] Reference Figure 3 In an embodiment of the present invention, a hardware device is also provided. The hardware device may be a server, and its internal structure may be as follows: Figure 3As shown. The hardware device includes a processor, a memory, a display screen, an input device, a network interface and a database connected through a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the hardware device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the hardware device is used to store the corresponding data in this embodiment. The network interface of the hardware device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the above method is implemented.

[0190] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the hardware device to which the solution of the present invention is applied.

[0191] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the above method is implemented. It can be understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0192] In summary, the monitoring method, system and hardware equipment of the fault recording device provided in the embodiment of the present invention include: collecting operating data in the power system in real time through sensors, analyzing the operating data based on the analysis model, and identifying potential abnormal patterns; automatically triggering the fault recording function of the fault recording device according to the potential abnormal pattern, and recording detailed data associated with the abnormal pattern; analyzing the detailed data to confirm whether there is a real fault, and generating a corresponding fault report, and sending it to a remote master station. In the present invention, potential abnormal patterns are quickly identified in the real-time collected operating data, and the fault recording function is automatically triggered, which overcomes the current defects of low fault detection efficiency and inability to predict faults, and is of great significance for improving the fault detection efficiency and accuracy of the power system.

[0193] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided by the present invention and used in the embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM.

[0194] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0195] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A monitoring method for a fault recording device, characterized in that: The following steps are involved: Collecting operation data in the power system in real time through sensors, analyzing the operation data based on an analysis model, and identifying potential abnormal patterns; According to the potential abnormal mode, automatically trigger the fault recording function of the fault recording device to record detailed data associated with the abnormal mode; Analyze the detailed data to confirm whether there is a real fault, generate a corresponding fault report, and send it to the remote master station; The sending to the remote master station comprises: generating a request code based on the potential abnormal pattern; An upload request instruction for generating a fault report is sent to a remote master station; wherein the upload request instruction carries the request code; the remote master station verifies the request code carried in the upload request instruction to confirm whether the upload request instruction is passed; Upon receiving a feedback instruction from the remote master station indicating that the upload request instruction has been verified, sending the fault report to the remote master station; The generating a request code based on the potential abnormal mode includes: Get the standard character table; Obtaining a target serial number corresponding to the abnormal mode in a database; wherein the database stores serial numbers corresponding to each abnormal mode; Based on the target sequence number, the standard character table is deformed to obtain a deformed data table; Obtaining the probability corresponding to the abnormal pattern identified by the analysis model; The request code is obtained based on the probability generation curve and the curve and the deformation data table.

2. The monitoring method of the fault recording device according to claim 1, characterized in that: The fault recording device includes a management unit and a plurality of collection units; The collection unit is used to collect detailed data related to the abnormal mode and send it to the management unit; the management unit is used to analyze the detailed data, and the management unit communicates with the remote master station through the service gateway.

3. The monitoring method of the fault recording device according to claim 1, characterized in that: Before analyzing the operation data based on the analysis model, the method includes: Obtaining the type and quantity of the operation data; Obtaining an initial machine learning model pre-stored in a database; wherein the initial machine learning model is a pre-trained deep learning model; Based on the types and quantities pre-stored in the database and the mapping relationship with the model parameters, the corresponding target model parameters are matched; Based on the target model parameters, the model parameters of the initial machine learning model are updated to obtain the analysis model.

4. The monitoring method of the fault recording device according to claim 1, characterized in that: The step of obtaining the standard character table includes: Acquire first identification information corresponding to the power system and second identification information corresponding to the fault recording device; Concatenate the first identification information and the second identification information to obtain concatenated identification information; A blank table is generated, and the characters in the concatenation identification information are added to the blank table one by one in sequence to obtain the standard character table.

5. The monitoring method of the fault recording device according to claim 1, characterized in that: The step of deforming the standard character table based on the target sequence number to obtain a deformed data table includes: The number of columns of the standard character table is changed to a target number of columns, wherein the target number of columns is a number corresponding to the target serial number; characters are sequentially filled into the changed character table, and the order of the characters in the standard character table according to the row arrangement is maintained; Determine whether the last row of the changed character table is filled; If it is a filled state, the changed character table is used as the deformed data table; if it is not a filled state, the last row of the changed character table is deleted and used as the deformed data table.

6. The monitoring method of the fault recording device according to claim 1, characterized in that: The generating curve based on the probability, and obtaining the request code based on the curve and the deformation data table, comprises: Establishing a two-dimensional coordinate system with the lower left corner vertex of the deformation data table as the coordinate origin; In the two-dimensional coordinate system, a straight line is constructed through the coordinate origin; wherein the value corresponding to the probability is used as the slope of the straight line; Generate two offset straight lines parallel to the straight line on both sides of the straight line, and the offsets of the two offset straight lines and the straight line are the same, both of which are preset values; wherein the straight line and the two offset straight lines constitute two channels; In the deformation data table, channel characters in cells in two channels are obtained, and the channel characters are combined in sequence to obtain the request code.

7. A monitoring system for a fault recording device, characterized in that: include: A first analysis unit, configured to collect operation data in the power system in real time through sensors, analyze the operation data based on an analysis model, and identify potential abnormal patterns; A recording unit, configured to automatically trigger a fault recording function of a fault recording device according to the potential abnormal mode, and record detailed data associated with the abnormal mode; A second analysis unit is used to analyze the detailed data, confirm whether there is a real fault, and generate a corresponding fault report and send it to the remote master station; The sending to the remote master station comprises: generating a request code based on the potential abnormal pattern; An upload request instruction for generating a fault report is sent to a remote master station; wherein the upload request instruction carries the request code; the remote master station verifies the request code carried in the upload request instruction to confirm whether the upload request instruction is passed; Upon receiving a feedback instruction from the remote master station indicating that the upload request instruction has been verified, sending the fault report to the remote master station; The generating a request code based on the potential abnormal mode includes: Get the standard character table; Obtaining a target serial number corresponding to the abnormal mode in a database; wherein the database stores serial numbers corresponding to each abnormal mode; Based on the target sequence number, the standard character table is deformed to obtain a deformed data table; Obtaining the probability corresponding to the abnormal pattern identified by the analysis model; The request code is obtained based on the probability generation curve and the curve and the deformation data table.

8. A hardware device, comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

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