Hydropower station safety management method and system based on Beidou No.3 public service

Abstract

The invention discloses a hydropower station safety management method and system based on Beidou No.3 public service, and relates to the technical field of hydropower station safety management, and the method comprises the steps: carrying out the real-time positioning of hydropower station facilities, transmitting the monitoring data and alarm information in real time through a Beidou No.3 short message communication function, carrying out the preprocessing of the collected monitoring data, and carrying out the early warning of the monitoring data. And performing deep analysis on the preprocessed data by using an artificial intelligence algorithm, identifying the operation mode and trend of the facility, predicting the potential safety hazard of the facility of the hydropower station, formulating a prevention measure and a safety plan according to a prediction result, synchronously executing the prevention measure and the safety plan through a Beidou No.3 time service function, evaluating the effect of the prevention measure, and performing early warning. And the safety management strategy is adjusted according to the actual situation. Accurate prediction, real-time monitoring and efficient emergency response of potential safety hazards of the hydropower station are achieved, and the real-time performance, accuracy and intelligent level of safety management of the hydropower station are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of hydropower station safety management, and in particular to a hydropower station safety management method and system based on BeiDou-3 public service. Background Art

[0002] With the rapid development of my country's hydropower industry, the safety management of hydropower stations has become the focus of industry attention. Traditional safety management methods mainly rely on ground monitoring systems and manual inspections, which have certain limitations in terms of accuracy, real-time and efficiency. In recent years, the development of satellite navigation technology has provided new solutions for the safety management of hydropower stations. In particular, the deployment of the BeiDou-3 satellite navigation system has been completed, providing strong technical support for the real-time monitoring and safety management of hydropower stations.

[0003] However, existing technologies still have shortcomings in practical applications. On the one hand, traditional monitoring systems often lack high-precision positioning capabilities, which makes it difficult to accurately grasp the location of facilities when monitoring hydropower station facilities, thus affecting the accurate prediction and rapid response to safety hazards. On the other hand, existing safety management methods are relatively simple in data processing and analysis, and lack the application of artificial intelligence technologies such as deep learning, resulting in inaccurate identification of facility operation modes and trends, making it difficult to detect potential safety hazards in advance. In addition, existing systems often lack effective synchronization mechanisms in the formulation and implementation of preventive measures and safety plans, resulting in insufficient timeliness and effectiveness in emergency response. Summary of the invention

[0004] In view of the above-mentioned existing problems, the present invention provides a hydropower station safety management method and system based on BeiDou-3 public services, which are used to solve the problems in the prior art of low positioning accuracy, low data transmission efficiency, insufficient data processing and analysis capabilities, inaccurate prediction of safety hazards, difficulty in simultaneous execution of preventive measures and safety plans, untimely emergency response, and unintelligent adjustment and optimization of safety management strategies.

[0005] In order to solve the above technical problems, a hydropower station safety management method based on BeiDou-3 public service is proposed, including:

[0006] Carry out real-time positioning of hydropower station facilities, transmit monitoring data and alarm information in real time through the BeiDou-3 short message communication function, and pre-process the collected monitoring data; use artificial intelligence algorithms to conduct in-depth analysis of the pre-processed data, identify the operation patterns and trends of the facilities, and predict the safety hazards of hydropower station facilities; formulate preventive measures and safety plans based on the prediction results, and synchronously implement preventive measures and safety plans through the BeiDou-3 timing function, evaluate the effectiveness of preventive measures, and adjust safety management strategies according to actual conditions.

[0007] As a preferred solution of the hydropower station safety management method based on BeiDou-3 public service described in the present invention, the positioning of the hydropower station facilities includes starting the BeiDou-3 receiver and setting it to continuous tracking mode, receiving satellite signals, and using RTK technology combined with differential correction data to calculate the position solution of the hydropower station facilities.

[0008] The solution formula for calculating the location of the hydropower station facilities is:

[0009] X=G -1 (Pb)

[0010] Among them, G is the design matrix, X is the facility location solution, P is the observation vector, and b is the deviation vector;

[0011] The transmission of monitoring data and alarm information includes encapsulating the positioning results and monitoring data into a short message format, encrypting the encapsulated data, sending the encrypted data packet through the Beidou-3 short message communication function, and the receiving end receiving the encrypted data packet and decrypting it. If abnormal data is monitored, an alarm message is immediately generated and transmitted.

[0012] As a preferred solution of the hydropower station safety management method based on BeiDou-3 public service described in the present invention, the preprocessing includes real-time positioning of hydropower station facilities, real-time transmission of monitoring data and alarm information through BeiDou-3 short message communication function, calculation of data mean and standard deviation, standardization processing and construction of a standardized data set.

[0013] The formula for calculating the mean and standard deviation of the data is:

[0014]

[0015] Among them, μ j is the mean of the jth feature, σ j is the standard deviation of the jth feature, N is the number of data points, and d ij is the j-th eigenvalue of the i-th data point, where i and j are variable indices.

[0016] The standardized formula is:

[0017]

[0018] Among them, μ j is the mean of the jth feature, σ j is the standard deviation of the jth feature, d ij is the jth eigenvalue of the ith data point, z ij is the standardized value of the jth feature of the ith data point, where i and j are variable indices.

[0019] As a preferred solution of the hydropower station safety management method based on BeiDou-3 public service described in the present invention, the artificial intelligence algorithm includes selecting facility operation status characteristics from the standardized data set for analysis, using a recurrent neural network to analyze the operation mode and trend of the facility, and using a training data set to train the model, adjusting the model parameters through a back propagation algorithm to minimize the loss function, after the model training is completed, using a verification data set to identify the facility operation mode, and using the trained model to predict the facility operation status.

[0020] The model training includes initializing model parameters, forward propagating training samples and true labels, calculating the difference between the model prediction value and the true label, quantifying the difference through the loss function, calculating the gradient of the loss function with respect to the model parameters by back propagation, and updating the model parameters by gradient descent.

[0021] The recurrent neural network formula is expressed as:

[0022] h t =σ(W h ·h t-1 +W x ·x t +b h )

[0023] y t =W y ·h t +b y

[0024] Among them, h t is the hidden state at time step t, x t is the input feature at time step t, W h and W x is the weight matrix, b h and b y is the bias term, σ is the activation function, y t is the output.

[0025] As a preferred solution of the hydropower station safety management method based on BeiDou-3 public service described in the present invention, the prediction of safety hazards of hydropower station facilities includes in-depth analysis of pre-processed data, identifying the operation modes and trends of the facilities, predicting safety hazards of hydropower station facilities, and scoring the safety hazards of the facilities.

[0026] As a preferred scheme of the hydropower station safety management method based on BeiDou-3 public service described in the present invention, the formulation of preventive measures and safety plans includes setting a safety hazard scoring threshold, formulating preventive measures and safety plans based on the prediction results, and synchronously executing emergency measures and safety plans through the BeiDou-3 timing function.

[0027] The set safety hazard scoring threshold includes setting the high - risk threshold at 0.25, the medium - risk threshold at 0.5, and the low - risk threshold at 0.75. When 0 < S ≤ 0.25, it indicates a high - risk safety hazard, and immediate emergency measures need to be taken, including immediately shutting down the machine for inspection, conducting a detailed inspection of equipment components, and preparing an emergency evacuation plan. When 0.25 < S ≤ 0.5, it indicates a medium - risk safety hazard, and it is necessary to strengthen monitoring and formulate preventive measures, arrange regular maintenance and inspections, and formulate an emergency response plan. When 0.5 < S ≤ 0.75, it indicates a relatively low - risk safety hazard, and regular inspections and normal monitoring need to be maintained, and the maintenance log and operation manual need to be updated. When 0.75 < S ≤ 1, it indicates that the facility is operating safely, and regular equipment inspections and monitoring are carried out.

[0028] As a preferred embodiment of the hydropower station safety management method based on the Beidou - 3 open service of the present invention, the evaluation of the effectiveness of preventive measures includes, after implementing the preventive measures, collecting relevant data and feedback, calculating whether the safety hazard score has been reduced to the safe area, analyzing the changes in safety hazards after the implementation of the measures, compiling a report on the effectiveness of preventive measures, adjusting the threshold setting, the content of preventive measures, and the implementation process according to the effectiveness of preventive measures, and updating the safety plan according to the actual situation.

[0029] The emergency measures include, when an emergency occurs in the hydropower station and the dam, using the Beidou satellite to locate the accident site and sending relevant information to the rescue center. The rescue center can monitor the location and status of rescue personnel in real - time through the background system, provide accurate navigation guidance and road condition information for rescue personnel through the Beidou navigation system, improve the rescue efficiency and accuracy. At the same time, the rescue personnel communicate with the command center in real - time through the Beidou satellite system to coordinate rescue operations.

[0030] Another object of the present invention is to provide a hydropower station safety management system based on the Beidou - 3 open service. The present invention optimizes the problem of low positioning accuracy and realizes the timely implementation of the emergency plan. The system of the present invention integrates the high - precision positioning, short message communication, and time - service functions of the Beidou - 3 satellite navigation system, combined with artificial intelligence algorithms, effectively solves the problems of low positioning accuracy, low data transmission efficiency, insufficient data processing and analysis capabilities, inaccurate prediction of safety hazards, difficulty in synchronously implementing preventive measures and safety plans, untimely emergency response, and non - intelligent adjustment and optimization of safety management strategies, realizes the accurate prediction, real - time monitoring, and efficient emergency response of hydropower station safety hazards, and significantly improves the real - time, accuracy, and intelligent level of hydropower station safety management.

[0031] As a preferred solution of the hydropower station safety management system based on BeiDou-3 public service described in the present invention, it is characterized by including a real-time positioning and data transmission module, a data preprocessing module, an artificial intelligence algorithm analysis module, a preventive measures and safety plan formulation module, and an effect evaluation and strategy adjustment module.

[0032] The real-time positioning and data transmission module is used to receive satellite signals, calculate the position solution of the hydropower station facilities using RTK technology and differential correction data, and encapsulate the positioning results and monitoring data into a short message format, which is encrypted and sent through the Beidou-3 short message communication function. The receiving end decrypts the data packet and generates and transmits an alarm message when abnormal data is detected.

[0033] The data preprocessing module is used to calculate the mean and standard deviation of the monitoring data, perform standardization processing, construct a standardized data set, and apply a standardized formula to transform the data set to eliminate the dimensional influence between different features.

[0034] The artificial intelligence algorithm analysis module is used to use a recurrent neural network to analyze the operating mode and trend of the facility, adjust the model parameters through a back-propagation algorithm, minimize the loss function, train a model that accurately predicts the operating status of the facility, use the trained model to predict the operating status of the facility, and identify potential safety hazards.

[0035] The preventive measures and safety plan formulation module is used to set high-risk, medium-risk and low-risk thresholds according to the safety hazard scores, and formulate preventive measures and safety plans.

[0036] The effect evaluation and strategy adjustment module is used to collect relevant data and feedback after the implementation of preventive measures, calculate whether the safety hazard score has been reduced, and analyze the changes in safety hazards after the implementation of measures.

[0037] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and is characterized in that when the processor executes the computer program, the steps of the method described in the method for safety management of hydropower stations based on the BeiDou-3 public service are implemented.

[0038] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of the method described in the safety management of a hydropower station based on the BeiDou-3 public service are implemented.

[0039] Beneficial effects of the invention: The invention integrates the high-precision positioning, short message communication and timing functions of BeiDou-3 and combines it with artificial intelligence algorithms to achieve real-time monitoring, in-depth analysis and prediction of potential safety hazards of hydropower station facilities. The invention not only improves the accuracy and efficiency of safety management, but also greatly enhances the ability of hydropower stations to respond to sudden safety incidents through intelligent preventive measures and safety plans, providing new ideas and technical support for safety management in the hydropower industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work, among which:

[0041] Figure 1 An overall flow chart of a hydropower station safety management method based on BeiDou-3 public service provided for one embodiment of the present invention.

[0042] Figure 2 A schematic diagram of sending early warning information for a hydropower station safety management method based on BeiDou-3 public service provided in one embodiment of the present invention.

[0043] Figure 3 A system solution flow chart of a hydropower station safety management system based on BeiDou-3 public service provided for one embodiment of the present invention. DETAILED DESCRIPTION

[0044] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0045] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0046] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it an embodiment that is mutually exclusive with other embodiments, either individually or selectively.

[0047] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0048] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0049] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0050] Example 1, reference Figure 1 and Figure 2 , which is the first embodiment of the present invention, and provides a hydropower station safety management method based on BeiDou-3 public service, including:

[0051] S1: Real-time positioning of hydropower station facilities, real-time transmission of monitoring data and alarm information through the BeiDou-3 short message communication function, and pre-processing of collected monitoring data.

[0052] The positioning of the hydropower station facilities includes starting the BeiDou-3 receiver and setting it to continuous tracking mode, receiving satellite signals, and using RTK technology combined with differential correction data to calculate the position solution of the hydropower station facilities.

[0053] The solution formula for calculating the location of the hydropower station facilities is:

[0054] X=G -1 (Pb)

[0055] Among them, G is the design matrix, X is the facility location solution, P is the observation vector, and b is the deviation vector.

[0056] The transmission of monitoring data and alarm information includes encapsulating the positioning results and monitoring data into a short message format, encrypting the encapsulated data, sending the encrypted data packet through the Beidou-3 short message communication function, and the receiving end receiving the encrypted data packet and decrypting it. If abnormal data is monitored, an alarm message is immediately generated and transmitted.

[0057] The preprocessing includes real-time positioning of hydropower station facilities, real-time transmission of monitoring data and alarm information through the Beidou-3 short message communication function, calculation of data mean and standard deviation, standardization processing and construction of a standardized data set.

[0058] The formula for calculating the mean and standard deviation of the data is:

[0059]

[0060] Among them, μ j is the mean of the jth feature, σ j is the standard deviation of the jth feature, N is the number of data points, and d ij is the j-th eigenvalue of the i-th data point, where i and j are variable indices.

[0061] The standardized formula is:

[0062]

[0063] Among them, μ j is the mean of the jth feature, σ j is the standard deviation of the jth feature, d ij is the jth eigenvalue of the ith data point, z ij is the standardized value of the jth feature of the ith data point, where i and j are variable indices.

[0064] S2: Use artificial intelligence algorithms to conduct in-depth analysis of pre-processed data, identify patterns and trends in facility operation, and predict safety hazards of hydropower station facilities.

[0065] Furthermore, the artificial intelligence algorithm includes selecting facility operation status characteristics from the standardized data set for analysis, using a recurrent neural network to analyze the operation mode and trend of the facility, and using a training data set to train the model, and adjusting the model parameters through a back propagation algorithm to minimize the loss function. After the model training is completed, the verification data set is used to identify the mode of facility operation, and the trained model is used to predict the operation status of the facility.

[0066] The model training includes initializing model parameters, forward propagating training samples and true labels, calculating the difference between the model prediction value and the true label, quantifying the difference through the loss function, calculating the gradient of the loss function with respect to the model parameters by back propagation, and updating the model parameters by gradient descent.

[0067] The recurrent neural network formula is expressed as:

[0068] h t =σ(W h ·h t-1 +W x ·x t +b h )

[0069] y t =W y ·h t +b y

[0070] Among them, h t is the hidden state at time step t, x t is the input feature at time step t, W h and W x is the weight matrix, b h and b y is the bias term, σ is the activation function, y t is the output.

[0071] The prediction of potential safety hazards of hydropower station facilities includes in-depth analysis of pre-processed data, identifying patterns and trends in facility operation, predicting potential safety hazards of hydropower station facilities, and scoring potential safety hazards of the facilities.

[0072] The safety hazard scoring formula is:

[0073]

[0074] Among them, S is the safety hazard score, H is the high-precision positioning data based on BeiDou-3, T is the temperature monitoring data, V is the vibration monitoring data, E is the environmental monitoring data, Q(H) is the positioning data influence function, F(T) is the temperature influence function, C(V) is the vibration influence function, A(E) is the environmental factor influence function, D(H,T,V,E) is the data comprehensive processing function, and e is the base of the natural logarithm.

[0075] S3: Based on the prediction results, formulate preventive measures and safety plans, and synchronously implement the preventive measures and safety plans through the BeiDou-3 timing function, evaluate the effectiveness of the preventive measures, and adjust the safety management strategy according to the actual situation.

[0076] Further, the formulation of preventive measures and safety plans includes setting a scoring threshold for potential safety hazards, formulating preventive measures and safety plans based on the prediction results, and synchronously implementing emergency measures and safety plans through the timekeeping function of Beidou-3 satellite navigation system.

[0077] For example Figure 2 , the setting of the scoring threshold for potential safety hazards includes setting the high-risk threshold at 0.25, the medium-risk threshold at 0.5, and the low-risk threshold at 0.75. When 0 < S ≤ 0.25, it indicates the existence of high-risk potential safety hazards, and immediate emergency measures need to be taken, such as immediately shutting down the equipment for inspection, conducting a detailed inspection of the equipment components, and preparing an emergency evacuation plan; when 0.25 < S ≤ 0.5, it indicates the existence of medium-risk potential safety hazards, and it is necessary to strengthen monitoring and formulate preventive measures, arrange regular maintenance and inspections, and formulate an emergency response plan; when 0.5 < S ≤ 0.75, it indicates the existence of low-risk potential safety hazards, and regular inspections and normal monitoring need to be maintained, and the maintenance log and operation manual need to be updated; when 0.75 < S ≤ 1, it indicates that the facility is operating safely, and regular equipment inspections and monitoring are required.

[0078] The evaluation of the effectiveness of preventive measures includes, after implementing the preventive measures, collecting relevant data and feedback, calculating whether the scoring of potential safety hazards has been reduced to the safe area, analyzing the changes in potential safety hazards after the implementation of the measures, compiling a report on the effectiveness of preventive measures, adjusting the threshold setting, the content of preventive measures, and the implementation process according to the effectiveness of preventive measures, and updating the safety plan according to the actual situation.

[0079] The emergency measures include, in the event of an emergency at a hydropower station or dam, using Beidou satellites to locate the accident site and sending relevant information to the rescue center. The rescue center can monitor the location and status of rescue personnel in real time through the background system, provide accurate navigation guidance and road conditions information for rescue personnel through the Beidou navigation system to improve the efficiency and accuracy of rescue. At the same time, rescue personnel can communicate with the command center in real time through the Beidou satellite system to coordinate rescue operations.

[0080] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not restrictive. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

[0081] Example 2, referring to Figure 3, which is the second embodiment of the present invention, provides a hydropower station safety management system based on the BeiDou-3 public service, including a real-time positioning and data transmission module 100, a data preprocessing module 200, an artificial intelligence algorithm analysis module 300, a preventive measures and safety plan formulation module 400, and an effect evaluation and strategy adjustment module 500.

[0082] The real-time positioning and data transmission module 100 is used to receive satellite signals, calculate the position solution of the hydropower station facilities using RTK technology and differential correction data, and encapsulate the positioning results and monitoring data into a short message format, which is encrypted and sent through the Beidou-3 short message communication function. The receiving end decrypts the data packet and generates and transmits an alarm message when abnormal data is detected.

[0083] The data preprocessing module 200 is used to calculate the mean and standard deviation of the monitoring data, perform standardization processing, construct a standardized data set, and apply a standardized formula to transform the data set to eliminate the dimensional effects between different features.

[0084] The artificial intelligence algorithm analysis module 300 is used to use a recurrent neural network to analyze the operating mode and trend of the facility, adjust the model parameters through a back propagation algorithm, minimize the loss function, train a model that accurately predicts the operating status of the facility, use the trained model to predict the operating status of the facility, and identify potential safety hazards.

[0085] The preventive measures and safety plan formulation module 400 is used to set high risk, medium risk and low risk thresholds according to the potential safety hazard scores, and formulate preventive measures and safety plans.

[0086] The effect evaluation and strategy adjustment module 500 is used to collect relevant data and feedback after the implementation of preventive measures, calculate whether the safety hazard score is reduced, and analyze the changes in safety hazards after the implementation of measures.

[0087] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0088] Embodiment 3, the third embodiment of the present invention, is different from the first two embodiments in that:

[0089] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program codes.

[0090] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0091] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0092] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

Claims

1. A hydropower station safety management method based on BeiDou-3 public service is characterized by: include, Real-time positioning of hydropower station facilities, real-time transmission of monitoring data and alarm information through the BeiDou-3 short message communication function, and pre-processing of collected monitoring data; Using artificial intelligence algorithms, we conduct in-depth analysis of pre-processed data to identify patterns and trends in facility operation and predict potential safety hazards of hydropower station facilities; Based on the prediction results, preventive measures and safety plans are formulated, and the preventive measures and safety plans are synchronously implemented through the Beidou-3 timing function, the effectiveness of the preventive measures is evaluated, and the safety management strategy is adjusted according to the actual situation.

2. The hydropower station safety management method based on BeiDou-3 public service as claimed in claim 1, characterized in that: The hydropower station facility positioning includes starting the BeiDou-3 receiver and setting it to a continuous tracking mode to receive satellite signals, and using RTK technology combined with differential correction data to calculate the position solution of the hydropower station facility; The solution formula for calculating the location of the hydropower station facilities is: X=G -1 (P-b) Among them, G is the design matrix, X is the facility location solution, P is the observation vector, and b is the deviation vector; The transmission of monitoring data and alarm information includes encapsulating the positioning results and monitoring data into a short message format, encrypting the encapsulated data, sending the encrypted data packet through the Beidou-3 short message communication function, and the receiving end receiving the encrypted data packet and decrypting it. If abnormal data is monitored, an alarm message is immediately generated and transmitted.

3. The hydropower station safety management method based on BeiDou-3 public service as claimed in claim 2 is characterized by: The preprocessing includes real-time positioning of hydropower station facilities, real-time transmission of monitoring data and alarm information through the Beidou-3 short message communication function, calculation of data mean and standard deviation, standardization processing and construction of a standardized data set; The formula for calculating the mean and standard deviation of the data is: Among them, μ j is the mean of the jth feature, σ j is the standard deviation of the jth feature, N is the number of data points, and d ij is the jth eigenvalue of the i-th data point, i and j are variable indices; The standardized formula is: Among them, μ j is the mean of the jth feature, σ j is the standard deviation of the jth feature, d ij is the jth eigenvalue of the ith data point, z ij is the standardized value of the jth feature of the ith data point, where i and j are variable indices.

4. The hydropower station safety management method based on BeiDou-3 public service as claimed in claim 3 is characterized by: The artificial intelligence algorithm includes selecting the operating status characteristics of the facility from the standardized data set for analysis, using a recurrent neural network to analyze the operating mode and trend of the facility, and using the training data set for model training, adjusting the model parameters through the back propagation algorithm to minimize the loss function, and after the model training is completed, using the verification data set to identify the mode of facility operation, and using the trained model to predict the operating status of the facility; The model training includes initializing model parameters, forward propagating training samples and true labels, calculating the difference between the model prediction value and the true label, quantifying the difference through a loss function, calculating the gradient of the loss function with respect to the model parameters through back propagation, and updating the model parameters through a gradient descent method; The recurrent neural network formula is expressed as: h t =σ(W h ·h t-1 +W x ·x t +b h ) y t =W y ·h t +b y Among them, h t is the hidden state at time step t, x t is the input feature at time step t, W h and W x is the weight matrix, b h and b y is the bias term, σ is the activation function, y t is the output.

5. The method for hydropower station safety management based on BeiDou-3 public service as claimed in claim 4, characterized in that: The prediction of potential safety hazards of hydropower station facilities includes in-depth analysis of pre-processed data, identifying patterns and trends in facility operation, predicting potential safety hazards of hydropower station facilities, and scoring potential safety hazards of the facilities.

6. The method for hydropower station safety management based on BeiDou-3 public service as claimed in claim 5, characterized in that: The formulation of preventive measures and safety plans includes setting a safety hazard scoring threshold, formulating preventive measures and safety plans based on the prediction results, and synchronously executing emergency measures and safety plans through the BeiDou-3 timing function; The setting of the safety hazard scoring threshold includes setting the high-risk threshold at 0.25, the medium-risk threshold at 0.5, and the low-risk threshold at 0.

75. When 0 < S ≤ 0.25, it indicates the existence of high-risk safety hazards, and immediate emergency measures need to be taken, such as immediately shutting down the machine for inspection, conducting a detailed inspection of equipment components, and preparing an emergency evacuation plan. When 0.25 < S ≤ 0.5, it indicates the existence of medium-risk safety hazards, and it is necessary to strengthen monitoring and formulate preventive measures, arrange regular maintenance and inspections, and formulate an emergency response plan. When 0.5 < S ≤ 0.75, it indicates the existence of relatively low-risk safety hazards, and regular inspections and normal monitoring need to be maintained, and the maintenance log and operation manual need to be updated. When 0.75 < S ≤ 1, it indicates that the facility is operating safely, and regular equipment inspections and monitoring are carried out.

7. The method for hydropower station safety management based on BeiDou-3 public service as claimed in claim 6, characterized in that: The evaluation of the effectiveness of preventive measures includes, after implementing the preventive measures, collecting relevant data and feedback, calculating whether the safety hazard score has been reduced to the safe area, analyzing the changes in safety hazards after the implementation of the measures, compiling a report on the effectiveness of preventive measures, adjusting the threshold setting, the content of preventive measures, and the implementation process according to the effectiveness of preventive measures, and updating the safety plan according to the actual situation. The emergency measures include, when an emergency occurs at a hydropower station and dam, using the Beidou satellite to locate the accident site and sending relevant information to the rescue center. The rescue center monitors the location and status of rescue personnel in real time through the background system, provides accurate navigation guidance and road condition information for rescue personnel through the Beidou navigation system, improves the rescue efficiency and accuracy. At the same time, the rescue personnel communicate with the command center in real time through the Beidou satellite system to coordinate rescue operations.

8. A system adopting the hydropower station safety management method based on BeiDou-3 public service as claimed in any one of claims 1 to 7, characterized in that: It includes a real-time positioning and data transmission module, a data preprocessing module, an artificial intelligence algorithm analysis module, a preventive measure and safety plan formulation module, and an effectiveness evaluation and strategy adjustment module. The real-time positioning and data transmission module is used to receive satellite signals, calculate the position solution of hydropower station facilities using RTK technology and differential correction data, encapsulate the positioning results and monitoring data into the short message format, encrypt them, and send them through the Beidou-3 short message communication function. The receiving end decrypts the data packet and generates an alarm message and transmits it when abnormal data is detected. The data preprocessing module is used to calculate the mean and standard deviation of the monitoring data, perform standardization processing, construct a standardized data set, and apply the standardization formula to transform the data set to eliminate the influence of dimensions between different features. The artificial intelligence algorithm analysis module is used to analyze the operation mode and trend of the facility using a recurrent neural network, adjust the model parameters through the backpropagation algorithm, minimize the loss function, train a model that can accurately predict the operation state of the facility, and use the trained model to predict the operation state of the facility and identify potential safety hazards. The preventive measure and safety plan formulation module is used to set the thresholds for high-risk, medium-risk, and low-risk according to the safety hazard score, and formulate preventive measures and safety plans. The effectiveness evaluation and strategy adjustment module is used to collect relevant data and feedback after implementing preventive measures, calculate whether the safety hazard score has decreased, and analyze the changes in safety hazards after the implementation of the measures.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the hydropower station safety management method based on BeiDou-3 public service described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the hydropower station safety management method based on BeiDou-3 public service described in any one of claims 1 to 7 are implemented.

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