Private system-based early warning device and method and storage medium

Abstract

The invention belongs to the technical field of communication, and discloses an early warning device and method based on a private system and a storage medium, and the device comprises a monitoring module which is used for monitoring the actual operation environment parameters of a mine to obtain a monitoring signal; the data processing module is used for generating an early warning signal when the monitoring signal is judged to exceed a preset threshold value, sending the early warning signal to the communication module by utilizing a cell broadcast service, and predicting and generating a risk analysis report according to historical data by utilizing a target mixed model; and the communication module is used for carrying out code conversion on the early warning signal by utilizing a character coding mechanism, converting the obtained coded data into a target early warning broadcast message and sending the target early warning broadcast message to an operator so as to remind the operator to take corresponding measures according to the risk analysis report, so that the early warning signal is accurately and quickly made, and the operation safety is improved.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to an early warning device and method based on a private system and a storage medium. Background Art

[0002] In industrial applications such as mines, wells, and remote areas, 4G / 5G base stations need to be deployed within enterprise intranets to support production activities. However, due to the complex operating environments of mines and wells, and the multiple potential hazards such as collapse, toxic gas leaks, fires, and explosions, real-time monitoring and early warning of the operating environment are necessary. However, traditional safety monitoring systems typically have limited functionality, fail to fully cover multiple risks, and have slow response times, making them difficult to meet the safety needs of modern mines and wells.

[0003] Therefore existing technology still needs to be improved and improved. Summary of the Invention

[0004] The present application provides an early warning device and method and a storage medium based on a proprietary system, aiming to solve the problems of slow early warning speed and poor accuracy in the prior art when providing early warning for an operating environment.

[0005] In a first aspect, an embodiment of the present application provides an early warning device based on a private system, comprising: a monitoring module, a data processing module, and a communication module connected in sequence; The monitoring module is used to monitor the actual operating environment parameters of the mine and obtain monitoring signals; The data processing module is configured to generate a warning signal when it is determined that the monitoring signal exceeds a preset threshold, send the warning signal to the communication module using a cell broadcast service, and generate a risk analysis report based on historical data prediction using a target hybrid model; The communication module is used to use a character encoding mechanism to encode the warning signal, convert the obtained encoded data into a target warning broadcast message, and send it to the operating personnel to remind the operating personnel to take corresponding measures according to the risk analysis report.

[0006] In some embodiments, the warning signal includes: a message type identifier, warning content, warning period, warning number, and warning level; The communication module includes: a gateway and multiple base stations; the gateway is connected to the data processing module and all the base stations respectively; the base stations are arranged at preset locations in the mine so that the base station signals cover the mine; The gateway is configured to send the warning signal to all the base stations; The base station is configured to select a corresponding signal identifier according to the message type identifier, and then encode the warning content using the character encoding mechanism to obtain the encoded data; The base station is used to encapsulate the signal identifier and the coded data into the target warning broadcast message, and send it to the operator according to the warning cycle and the number of warnings to remind the operator to take corresponding measures according to the risk analysis report.

[0007] In some embodiments, the historical data includes: historical accident data and industry standard ranges; The data processing module is specifically used to determine whether the actual operating environment parameters in the monitoring signal exceed the preset threshold of the standard operating environment parameters in the industry standard range, and when exceeded, send the warning signal to the communication module.

[0008] In some embodiments, the data processing module is specifically configured to preprocess the actual operating environment parameters and the accident parameters corresponding to the target sensor in the historical accident data, extract the target indicators and implicit features from the actual operating environment parameters and the accident parameters after obtaining the preprocessed data, and screen out redundant information from the initial hybrid model based on the implicit features to obtain the target hybrid model; The data processing module is specifically configured to use an attention mechanism to assign a corresponding weight to each of the pre-processed data, and then use the target hybrid model to predict the pre-processed data according to the target indicator and the weight to obtain the risk analysis report; Among them, the target indicators include: temperature change rate, vibration frequency, gas concentration and dust concentration; the implicit features include: redundant features and noise; the initial hybrid model includes: shallow model and deep model; the risk analysis report includes: the actual working environment parameters, risk type, risk level and emergency management plan.

[0009] In some embodiments, the base station is further configured to, after selecting a number value of a non-standard signal identifier from a reserved number range of a signal identifier, establish a mapping relationship between a non-standard message type identifier and the number value of the non-standard signal identifier to expand the scope of the warning service corresponding to the signal identifier; Among them, the signal identifier includes: a standard signal identifier and the non-standard signal identifier, and the message type identifier includes: a standard message type identifier and the non-standard message type identifier; each number value of the standard signal identifier corresponds to a public warning service; each number value of the non-standard signal identifier corresponds to a private warning service.

[0010] In some embodiments, the base station is further used to determine that the length of the encoded data exceeds a preset length, split the encoded data and encapsulate it together with the signal identifier to obtain the target warning broadcast signal.

[0011] In some embodiments, the private system-based early warning device further includes: a display module, the display module being connected to the data processing module; The display module is used to query the historical data, display the risk analysis report, and control the data processing module to stop sending the warning signal and control the monitoring module to stop working after receiving the remote shutdown instruction from the operator.

[0012] In a second aspect, an embodiment of the present application provides an early warning method based on a private system, comprising: Control and monitor the actual operating environment parameters of the mine to obtain monitoring signals; Determine whether the monitoring signal exceeds a preset threshold, generate an early warning signal if it does, and generate a risk analysis report based on historical data prediction using a target hybrid model; The control utilizes the cell broadcast service to receive the warning signal, and utilizes the character encoding mechanism to encode the warning signal, converts the obtained coded data into a target warning broadcast message, and sends it to the operating personnel to remind the operating personnel to take corresponding measures according to the risk analysis report.

[0013] In some embodiments, the historical data includes: historical accident data and industry standard ranges; the private system-based early warning method further includes: Preprocessing the actual operating environment parameters and the accident parameters corresponding to the target sensor in the historical accident data to obtain preprocessed data; The preprocessed data is learned using an online learning strategy to adjust the weight of the loss function in the target hybrid model so that the calculation result of the loss function reaches a target threshold.

[0014] In a third aspect, an embodiment of the present application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the private system-based early warning method as described above.

[0015] Compared with the existing technology, the present application provides an early warning device, method and storage medium based on a private system. The device monitors the actual operating environment parameters of the mine in real time, and generates an early warning signal when it determines that the monitoring signal exceeds the preset threshold. The early warning signal is sent in the private domain using the cell broadcast service, and a target hybrid model is used to generate a risk analysis report based on historical data prediction. The early warning signal is then encoded and converted using a character encoding mechanism and sent to the operating personnel to remind the operating personnel to take corresponding measures according to the risk analysis report, thereby realizing rapid and accurate monitoring of danger signals and making timely early warnings, greatly improving operational safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 A framework diagram of a private system-based early warning device provided by this application; Figure 2 An architecture diagram of the core functions of the existing 5G network PWS provided in this application; Figure 3 A diagram of the network architecture of the private system-based early warning device provided by this application; Figure 4 A flow chart of the private system-based early warning method provided by this application; Figure 5 This is a flow chart of the model adaptive optimization in the private system-based early warning method provided in this application.

[0018] Reference numerals: 10 - monitoring module; 20 - data processing module; 30 - communication module. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments.

[0020] The components of the embodiments of the present application generally described and illustrated in the drawings herein may be arranged and designed in a variety of different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed application, but rather merely represents selected embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative effort are within the scope of protection of the present application.

[0021] Hereinafter, the terms "including", "having" and their cognates used in various embodiments of the present application are intended only to indicate specific features, numbers, steps, operations, elements, components or combinations of the aforementioned items, and should not be understood as excluding the existence of one or more other features, numbers, steps, operations, elements, components or combinations of the aforementioned items or adding the possibility of one or more features, numbers, steps, operations, elements, components or combinations of the aforementioned items. In addition, the terms "first", "second", "third" and the like are only used to distinguish descriptions and should not be understood as indicating or implying relative importance.

[0022] Unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by those skilled in the art to which the various embodiments of the present application belong. The terms (such as those defined in commonly used dictionaries) will be interpreted as having the same meaning as in the context of the relevant technical field and will not be interpreted as having an idealized meaning or an overly formal meaning unless clearly defined in the various embodiments of the present application.

[0023] The present application provides an early warning device and method based on a private system, as well as a storage medium. This early warning method based on a private system monitors the actual operating environment parameters of a mine in real time, and generates an early warning signal when it determines that the monitoring signal exceeds a preset threshold. The early warning signal is sent within the private domain using a cell broadcast service, and a target hybrid model is used to generate a risk analysis report based on historical data prediction. The early warning signal is then encoded and converted using a character encoding mechanism and sent to the operator to remind the operator to take corresponding measures according to the risk analysis report, thereby achieving rapid and accurate monitoring of danger signals and issuing timely early warnings, greatly improving operational safety.

[0024] The following describes the design of the early warning method based on the private system through some specific embodiments.

[0025] See also Figure 1 The embodiment of the present application provides an early warning device based on a private system, comprising: a monitoring module 10, a data processing module 20 and a communication module 30 connected in sequence.

[0026] The monitoring module 10 is used to monitor the actual operating environment parameters of the mine and obtain monitoring signals.

[0027] The data processing module 20 is used to generate an early warning signal when it is determined that the monitoring signal exceeds a preset threshold, send the early warning signal to the communication module 30 using the cell broadcast service, and generate a risk analysis report based on historical data prediction using the target hybrid model.

[0028] The communication module 30 is used to convert the early warning signal into code using a character encoding mechanism, convert the obtained coded data into a target early warning broadcast message, and then send it to the operator to remind the operator to take corresponding measures according to the risk analysis report.

[0029] Among them, the early warning signal includes: message type identifier, warning content, warning cycle, number of warnings and warning level; historical data includes: historical accident data and industry standard range; risk analysis report includes: mine conditions (that is, actual operating environment parameters such as various gas concentrations, temperature and humidity, etc.), whether there is a risk, risk type and risk level, and corresponding emergency management plan, etc.; actual operating environment parameters include: harmful gas concentration, temperature and humidity, geological vibration parameters and dust concentration and other parameters.

[0030] Among them, the sources of historical data include two aspects: one is according to the relevant provisions of the national standard, which has relevant standards for oxygen concentration (minimum concentration), allowable methane concentration, carbon monoxide, carbon dioxide, hydrogen sulfide, relative humidity and rock microseismic energy for underground mine operations, that is, the scope of industry standards; the second is based on the actual local situation and the data from previous dangerous situations, that is, historical accident data.

[0031] Exemplarily, the detection module may include: a gas sensor, a temperature and humidity sensor, a vibration sensor, and a dust sensor, which are used to monitor actual operating environment parameters such as harmful gas concentration, temperature and humidity, geological vibration parameters, and dust concentration in the mine in real time, and generate detection signals.

[0032] Gas sensors are used to detect the concentration of toxic and harmful gases such as methane, carbon monoxide, and hydrogen sulfide. Temperature and humidity sensors monitor ambient temperature and humidity. Vibration sensors detect geological vibrations and provide early warning of collapse risks. Dust sensors monitor airborne dust concentrations to prevent pneumoconiosis.

[0033] The data processing module 20 then sets thresholds (i.e., preset thresholds) for various sensors, such as gas, temperature, humidity, and vibration, in accordance with national standards and local geological conditions. These thresholds are typically determined based on a combination of national standards (such as GB standards), industry specifications, and specific geological conditions.

[0034] Next, the data processing module 20 receives the monitoring signals collected by the sensor module and performs real-time analysis and processing. If the monitoring signal exceeds a preset threshold, it generates a warning signal and transmits it to the communication module 30 using CBC (Cell Broadcast Service). Furthermore, the data processing module 20 incorporates a built-in target hybrid model that generates risk analysis reports based on historical data (including historical accident data and industry standard ranges). The warning signal can also be analyzed for risk level, classified into different risk levels (e.g., low, medium, and high) according to national or local regulations, and the corresponding threshold ranges for each risk level are determined. For example, the lower explosive limit (LEL) of gas concentration, the appropriate temperature and humidity ranges, and the warning value of vibration intensity.

[0035] Finally, since the warning information sent by the data processing module 20 may be a piece of text or a picture, or a picture plus text, the communication module 30 needs to use a character encoding mechanism to convert the warning signal, for example, the warning signal is uniformly converted into UTF-16 encoding (UTF-16 is a Unicode character encoding standard specifically used to represent a global character set), and is encapsulated using SIB (System Information Block Type, a system information block defined in the wireless communication standard) 8 to obtain the target warning broadcast message and send it to the operating personnel to remind the operating personnel to take corresponding measures according to the risk analysis report.

[0036] It can be understood that in this application, the actual monitored operating environment parameters are analyzed, and a target hybrid model is used to generate a risk analysis report based on historical data predictions. When it is determined that the preset threshold is exceeded, a warning signal is generated, and the warning information is encoded and converted using a character encoding mechanism. The obtained encoded data is converted into a target warning broadcast message, so that the operating personnel can take corresponding measures according to the risk analysis report after receiving the target warning broadcast message, thereby realizing private information transmission in the absence of a core network and effectively improving signal security and quality.

[0037] In one implementation method, the data processing module 20 is specifically used to determine whether the actual operating environment parameters in the monitoring signal exceed the preset threshold of the standard operating environment parameters in the industry standard range, and when exceeded, send an early warning signal to the communication module 30.

[0038] For example, preset thresholds for standard operating environment parameters within the scope of industry standards can be referenced by consulting national standards (GB) or industry standards related to mining operations. For example, for gas sensors, reference can be made to GB / T 50497-2019, "General Technical Requirements for Coal Mine Safety Monitoring Systems," which specifies monitoring requirements for harmful gases such as carbon monoxide (CO), methane (CH4), and sulfur dioxide (SO2) in coal mine environments. For example, the permissible short-term exposure concentration of carbon monoxide is 30 mg / m³. For temperature and humidity sensors, reference can be made to GB / T 16425-2010, "Classification of Thermal Environments in Coal Mines," which classifies temperature and humidity conditions within mines and proposes corresponding control measures. Vibration sensors may refer to GB / T 10071-2018, "Measurement Methods and Evaluation Criteria for Vibration in Mining Machinery," which specifies measurement methods and evaluation criteria for the vibration characteristics of mining machinery during operation. Furthermore, local geological and environmental data can be collected: obtaining geological conditions, climate characteristics, and historical data (such as seismic activity, temperature ranges, and humidity fluctuations) for the target area. For example, detailed data can be obtained through the Meteorological Bureau, Geological Survey Bureau or third-party testing agencies.

[0039] The preset thresholds can also be graded to distinguish normal, warning, and dangerous states, such as normal range: gas concentration <10ppm, warning range: 10ppm ≤ gas concentration <20ppm, and dangerous range: gas concentration ≥ 20ppm.

[0040] Then, in actual application, the actual operating environment parameters in the monitoring signal are compared with the preset thresholds of standard operating environment parameters in the industry standard range: If the actual operating environment parameters exceed the preset thresholds of the standard operating environment parameters, an early warning signal is generated and sent to the signal module.

[0041] It can be understood that in this application, the data processing module 20 performs real-time analysis on the monitored actual working environment parameters, and issues a warning signal when it exceeds the preset threshold, thereby issuing a timely and effective warning of danger, thereby greatly improving work safety.

[0042] In one implementation method, the data processing module 20 is specifically used to preprocess the actual operating environment parameters and the accident parameters corresponding to the target sensor in the historical accident data. After obtaining the preprocessed data, the target indicators and implicit features in the actual operating environment parameters and the accident parameters are extracted, and the initial mixed model is screened out redundant information based on the implicit features to obtain the target mixed model.

[0043] The data processing module 20 is specifically used to use the attention mechanism to assign corresponding weights to each preprocessed data, and then use the target hybrid model to predict the preprocessed data according to the target indicators and weights to obtain a risk analysis report.

[0044] Target indicators are defined using domain knowledge and include temperature change rate, vibration frequency, gas concentration, and dust concentration. Temperature change rate can reflect the changing trend of equipment operating status; abnormal temperature fluctuations may indicate equipment failure. For rotating machinery, vibrations of a specific frequency may indicate normal operation, while abnormal frequencies may indicate bearing wear or other mechanical issues. Implicit features include redundant features and noise.

[0045] The initial hybrid model combines a shallow model (such as XGBoost) with a deep model (such as LSTM), balancing computational efficiency and prediction accuracy. XGBoost (eXtreme Gradient Boosting) is a highly efficient machine learning algorithm based on the Gradient Boosting Decision Tree (GBDT); LSTM (Long Short-Term Memory) is a specialized recurrent neural network (RNN).

[0046] Exemplarily, the target mixture model is obtained as follows: The first stage is data acquisition: real-time acquisition of the actual operating environment parameters of the target sensors, as well as the accident parameters of the same target sensors in historical accident data. For example, accident parameters such as gas, temperature and humidity, vibration, and dust are acquired from target sensors such as gas sensors, temperature and humidity sensors, vibration sensors, and dust sensors. Then, the actual operating environment parameters and accident parameters are cleaned and normalized, and noise effects are eliminated, among other preprocessing steps, to construct preprocessed data, i.e., predicted data.

[0047] The second stage involves model construction: a sliding window mechanism is used to extract target indicators from the actual operating environment parameters and accident parameters. By using key indicators based on domain knowledge (i.e., target indicators) as foundational features, the model's interpretability and accuracy can be significantly improved. Dimensionality reduction techniques are also employed to extract implicit features from the actual operating environment parameters and accident parameters. This approach reduces feature redundancy, improves model training efficiency, and improves generalization. It effectively reduces the dimensionality of the feature space while retaining or enhancing information critical to the task. Subsequently, the initial hybrid model is filtered out of redundant information based on the implicit features to obtain the target hybrid model.

[0048] Among them, commonly used dimensionality reduction methods include: t-SNE and Autoencoder, etc. t-SNE: mainly used for visualization of high-dimensional data, and Autoencoder: automatically learns the compressed representation of data through neural networks, suitable for feature extraction of large-scale data sets.

[0049] The third stage is the prediction stage: In order to improve the focus of the target hybrid model on the target indicator, an attention mechanism is introduced (which can be a self-attention mechanism or a weighted attention mechanism, etc.), that is, a weight is assigned to each target feature in the preprocessed data, and different weights correspond to different levels of importance in the target features. This allows the target hybrid model to focus more on the parts that contribute more to the task, improve model performance, and have better interpretability.

[0050] Then, the target hybrid model is used to predict the preprocessed data according to the target indicators and weights to obtain a risk analysis report, including: actual working environment parameters, risk type, risk level and emergency management plan.

[0051] In one implementation method, the communication module 30 includes: a gateway and multiple base stations; the gateway is connected to the data processing module 20 and all base stations respectively; the base stations are set at preset locations in the mine to cover the mine with base station signals.

[0052] Gateway, used to send early warning signals to all base stations.

[0053] The base station is used to select a corresponding signal identifier according to the message type identifier, and then encode the warning content using a character encoding mechanism to obtain encoded data.

[0054] The base station is used to encapsulate the signal identifier and coded data into a target warning broadcast message, and send it to the operating personnel according to the warning cycle and number of warnings to remind the operating personnel to take corresponding measures according to the risk analysis report.

[0055] For demonstration purposes, please refer to Figure 2 , the architecture diagram of the core functions of PWS in the existing 5G network.

[0056] The following sections describe the following: UE (User Equipment): User equipment that receives broadcast messages; Uu interface: The wireless interface between the UE and the radio access network (RAN); AMF (Access and Mobility Management Function): Access and Mobility Management Function, responsible for message routing and user access management; (R)AN (Radio Access Network or Next Generation RAN): Radio Access Network or Next Generation RAN; CBC (Cell Broadcast Center) / CBE (Cell Broadcast Entity): Cell Broadcast Center / Cell Broadcast Entity, responsible for generating and distributing broadcast messages; PWS-IWF (Public Warning System - Interworking Function): Public Warning System Interworking Function, responsible for implementing the specific functional modules of radio broadcast; N2: The interface between NG-RAN and AMF; SBc (Session Border Controller): Session Border Controller, responsible for managing communication boundaries with the core network, terminals, or other network entities; N50: Reference point. The UE interacts with the AMF via the N1 interface to complete registration and mobility management. The AMF interacts with the (R)AN over the N2 interface to control user access and handover. The RAN delivers broadcast messages to the UE over the Uu interface. The CBC / CBE collaborates with the AMF or other broadcast centers over the N50 interface to implement the Public Weather Service (PWS) function.

[0057] Then, it can be seen Figure 2 The existing network framework mainly relies on the core network and CBC modules.

[0058] Then, refer to the network architecture in this application. Figure 3As shown, the IWU (Intelligent Warning Unit) integrates CBC and CBE related functions, while also adding visualization, historical backtracking, and self-learning capabilities. A gateway is a network device or functional entity used to connect two networks using different communication protocols, architectures, or technologies. It not only forwards data packets but also performs protocol conversion, format adaptation, or security processing on the data as needed. Small cells are typically used to supplement the coverage of macro cells. They are low-power wireless access points suitable for network coverage indoors or in high-density areas. 5GC, short for 5G Core Network, is a key component of the fifth-generation mobile communication system (5G). 5GC is responsible for managing network resource sets and user data. In this application, one small base station is set up in a mine above ground, and three small base stations are set up in a mine below ground.

[0059] Then, in the data processing module 20 (i.e. corresponding to Figure 3 After the IWU in the network generates an early warning signal, the IWU first transmits the early warning signal to the gateway, which then performs format adaptation or security processing on the early warning signal and forwards the early warning signal to all base stations.

[0060] Then, the base station selects the appropriate corresponding messageIdentifier (signal identifier) ​​according to the msgType (i.e., message type identifier) ​​in the warning signal, and uses a character encoding mechanism (such as UTF-16 encoding) to encode the warning content to obtain encoded data. Among them, UTF-16 is a Unicode character encoding standard specifically used to represent character sets worldwide.

[0061] Next, after encoding, the base station encapsulates the signal identifier and encoded data according to the SIB8 information format. This encapsulates the private warning signal using the SIB8 information format to generate the targeted warning broadcast signal. This encapsulation is then encoded using ASN1 (Abstract Syntax Notation One), an abstract syntax notation used to describe the structure of data objects, to produce a data packet. Finally, the data packet is periodically sent to the operator's terminal based on the broadcast cycle and broadcast frequency. Upon receiving the SIB8 message packet, the terminal automatically displays the warning information in a pop-up window. The terminal also emits a buzzer and vibrates to alert the user. Some terminals also provide voice notifications to remind operators to take appropriate measures based on the risk analysis report.

[0062] Exemplarily, in this application, the base station uses a character encoding mechanism to encode the warning content, encapsulates the signal identifier and the obtained encoded data into a target warning broadcast message, and then sends it periodically, thereby realizing fast and high-quality interaction of data with multiple platforms or multiple devices, improving data transmission efficiency and accuracy, and increasing the scope of data dissemination.

[0063] Furthermore, in another embodiment of the present application, the data processing module 20 determines whether the environment has returned to normal based on the collected monitoring data. If so, it sends an early warning cancellation request to the communication module 30. Upon receiving the early warning cancellation request, the base station in the communication module 30 also searches for the early warning service corresponding to the message type identifier based on msgType. If the early warning message is still being sent, it stops broadcasting the early warning information and responds with an early warning cancellation confirmation message. However, if the early warning message has reached the maximum number of transmissions and stops broadcasting, it directly responds with an early warning cancellation confirmation message.

[0064] In one implementation method, the base station is also used to establish a mapping relationship between the non-standard message type identifier and the number value of the non-standard signal identifier after selecting the number value of the non-standard signal identifier in the reserved number range of the signal identifier, so as to expand the scope of the early warning service corresponding to the signal identifier.

[0065] Among them, signal identifiers include: standard signal identifiers and non-standard signal identifiers, and message type identifiers include: standard message type identifiers and non-standard message type identifiers. The number value of the standard signal identifier corresponds to the standard message type identifier, and the number value of the non-standard signal identifier corresponds to the non-standard message type identifier. Each number value of the standard signal identifier corresponds to a public warning service; each number value of the non-standard signal identifier corresponds to a private warning service. Among them, the message type identifier corresponding to the number value of the standard signal identifier within the standard number range is the standard message type identifier. Similarly, the message type identifier corresponding to the number value of the non-standard signal identifier within the non-standard number range is the non-standard message type identifier.

[0066] For example, according to 3GPP TS 23.041, the standard range of signal identifiers in CIB8 messages (also known as CMAS CBS messages) is "4370-4400," representing the standard's range of public warning messages. Each value within this range corresponds to a specific public warning service (such as earthquake, tsunami, etc.). For example, "4370" might represent "earthquake alert," while "4380" might represent "tsunami alert." The reserved range of numbers "4423-6399" allows users to define new message types based on actual needs and map these messages to the system's internal msgType. msgType is an internally defined message type identifier used to distinguish different warning contents.

[0067] Since this application is a privatized early warning alarm system, the content and type of its warning information exceeds the standardized scope of CMAS CBS information. Therefore, first select the number value of the non-standard signal identifier from the reserved number range of signal identifiers, and establish a mapping relationship between the non-standard message type identifier and the number value of the non-standard signal identifier: First, define a private msgType, which is a non-standard message type identifier. For example, `msgType=1` indicates "gas concentration exceeds the standard"; `msgType=2` indicates "temperature is too high"; and `msgType=3` indicates "abnormal vibration."

[0068] Next, select the appropriate messageIdentifier, i.e., the non-standard signal identifier. For each non-standard message type identifier, the system selects an unused messageIdentifier value in the range 4423-6399 for binding to achieve the mapping. For example: `msgType=1` maps to `messageIdentifier=4500`; `msgType=2` maps to `messageIdentifier=4501`; `msgType=3` maps to `messageIdentifier=4502`, and so on.

[0069] Finally, a mapping table is established to record the correspondence between the non-standard message type identifier and the number value of the non-standard signal identifier. Then, when the system detects a risk, it first generates the corresponding msgType and converts it into the corresponding messageIdentifier according to the mapping table.

[0070] It can be understood that in this application, by customizing the non-standard signal identifiers selected in the reserved number range as the corresponding message type identifiers, the scope of use of the message type identifiers is expanded, and the types and functions of the warning information are expanded. It is not only compatible with the standard public warning services (4370-4400 range), but also supports the privatized warning needs in complex environments such as mines and mine shafts.

[0071] In one implementation method, the base station is further configured to, after determining that the length of the coded data exceeds a preset length, split the coded data and encapsulate the data together with the signal identifier to obtain a target early warning broadcast signal.

[0072] For example, since each CBS-Message-Information-Page in CB Data can only hold 82 bytes of data, if the encoded warning message exceeds 82 bytes (the preset length), further fragmentation is required. Specifically, the UTF-16 encoded data is divided into pages according to the CB Data format. Each fragment is then transmitted separately. After receiving all the fragments, the terminal reassembles them into a complete warning message according to the protocol. This encapsulates the fragmented encoded data with the signal identifier to produce the targeted warning broadcast signal.

[0073] It can be understood that in this application, the encoded data exceeding the preset length is divided into pieces to adapt to the limitation of the CBS system on the length of a single message. In one implementation method, the private system-based early warning device further includes: a display module, which is connected to the data processing module 20 .

[0074] The display module is used to query historical data, display risk analysis reports, and control the data processing module 20 to stop sending warning signals and control the monitoring module 10 to stop working after receiving the remote shutdown command from the operator.

[0075] Exemplarily, in the embodiment of the present application, the display module can also be used to display the monitoring signal in real time, for example, displaying the real-time data of each environmental parameter in the form of a chart, and can also support historical data query, and can support historical data query by time, location, and parameter type. At the same time, the risk analysis report will also be displayed.

[0076] In addition, the display module can also be used for remote control, that is, when receiving a shutdown instruction input by the operator on the display page of the display module, or after receiving a remote shutdown instruction from the operator, the control data processing module 20 stops sending the warning signal, and the control monitoring module 10 stops working.

[0077] See also Figure 4, an embodiment of the present application provides an early warning method based on a private system, comprising steps S100-S300: S100, controlling the monitoring of actual operating environment parameters of the mine to obtain monitoring signals.

[0078] Demonstratively, various pre-set sensors (i.e., monitoring module 10) are controlled to monitor the actual working environment parameters in the mine (including: harmful gas concentration, temperature and humidity, geological vibration parameters and dust concentration, etc.). For example, the gas sensor monitors the harmful gas in the mine, the temperature and humidity sensor monitors the temperature and humidity in the mine, etc., and obtains the monitoring signal.

[0079] It can be understood that by using various sensors for targeted real-time monitoring, it is possible to quickly and accurately obtain environmental parameters inside the mine, providing effective and accurate data for predicting early warning signals.

[0080] S200: Determine whether the monitoring signal exceeds a preset threshold, generate a warning signal when it exceeds the threshold, and generate a risk analysis report based on historical data prediction using a target hybrid model.

[0081] Exemplarily, after obtaining the monitoring signal, the data processing module 20 determines whether the actual operating environment parameters in the monitoring signal exceed the preset thresholds of the standard operating environment parameters within the industry standard range, such as the comprehensive standard AQ 1029-2019 "Coal Mine Safety Monitoring System and Detection Instrument Use Management Specifications": It specifies in detail the monitoring and management requirements of harmful gases, temperature, humidity, vibration and other parameters in the mine. If the comparison shows that it exceeds the preset threshold, an early warning signal is generated.

[0082] In addition, a pre-built target hybrid model will be used to predict and generate risk analysis reports (including actual operating environment parameters, risk types, risk levels and emergency management plans) based on historical data (including historical accident data and industry standard ranges).

[0083] It can be understood that in this application, by monitoring the monitoring signals and generating early warning signals when the preset threshold is exceeded, and using the target hybrid model to generate a risk analysis report based on historical data prediction, real-time monitoring and early warning of actual working environment parameters are achieved, effectively protecting the personal safety of the operating personnel, and generating detailed risk analysis reports so that the operating personnel can conduct targeted maintenance.

[0084] S300, control the use of cell broadcast service to receive warning signals, and use the character encoding mechanism to encode the warning signals, convert the obtained coded data into a target warning broadcast message and send it to the operating personnel to remind the operating personnel to take corresponding measures according to the risk analysis report.

[0085] Exemplarily, after generating the warning signal, the control communication module 30 utilizes the cell broadcast service to receive the warning signal, and utilizes the character encoding mechanism to encode the warning signal, for example, using UTF-16 encoding to encode the warning signal. After obtaining the encoded data, the obtained encoded data is converted into a target warning broadcast message and sent to the operating personnel to remind the operating personnel to take corresponding measures according to the risk analysis report.

[0086] It can be understood that in this application, the character encoding mechanism is used for encoding conversion, and the encoded data is converted into a target early warning broadcast signal, that is, the encoded data is encapsulated using the SIB8 signal format, and the target early warning broadcast signal is obtained and sent out, thereby realizing signal interaction between multiple platforms or multiple devices, improving the adaptability of the system, and integrating the functions of the core network (such as CBC or CBCF, that is, Cell Broadcast Center or Cell Broadcast Function) into the local system, and broadcasting in the form of SIB8 broadcast signals, eliminating dependence on the core network, and realizing the need to consider the support or restrictions of the external network, and realizing a more freely deployed private system, providing a high degree of independence and flexibility, which not only improves the security of the system, but also provides customers with greater autonomy.

[0087] In one implementation, see Figure 5 , the early warning method based on the private system also includes: S10, preprocessing the actual operating environment parameters and the accident parameters corresponding to the target sensor in the historical accident data to obtain preprocessed data; S20. Use an online learning strategy to learn the preprocessed data to adjust the weight of the loss function in the target hybrid model so that the calculation result of the loss function reaches the target threshold.

[0088] For example, the online optimization process of the model after training is completed: After the target hybrid model is obtained through training, the actual operating environment parameters and the accident parameters corresponding to the target sensor in the historical accident data are cleaned, normalized, and the noise influence is eliminated, and other preprocessing operations are performed to obtain preprocessed data.

[0089] Then, a part of the preprocessed data is used to adaptively optimize the target mixed data: that is, the preprocessed data is learned using an online learning strategy, that is, feature extraction is performed on the preprocessed data to adjust the initial weights of the shallow model and the deep model in the target mixed model in the total loss function according to the extracted features, so that the calculation result of the loss function reaches the target threshold, such as 0.001, or the overall error of the loss function is minimized, thereby continuously updating the model parameters to adapt to changes in data distribution, so as to achieve the purpose of adaptively balancing the response speed of the model, minimizing the overall loss and improving the accuracy of the early warning.

[0090] The present application also provides a computer-readable storage medium for storing the computer program used in the terminal device. For example, the computer-readable storage medium may include, but is not limited to, various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0091] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and structure diagrams in the accompanying drawings show the possible architectures, functions and operations of the devices, methods and computer program products according to the multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, program segment or a part of the code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in an alternative implementation, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the structure diagram and / or flowchart, as well as the combination of boxes in the structure diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or can be implemented using a combination of dedicated hardware and computer instructions.

[0092] In addition, the functional modules or units in the various embodiments of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0093] If the functions are implemented in the form of software function modules 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 this application, or the part that contributes to the existing technology, or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a smart phone, personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of this application.

[0094] The above is only a specific implementation method of the present application, but the scope of protection of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the scope of protection of the present application.

Claims

1. An early warning device based on a private system, characterized in that: include: A monitoring module, a data processing module and a communication module connected in sequence; The monitoring module is used to monitor the actual operating environment parameters of the mine and obtain monitoring signals; The data processing module is configured to generate a warning signal when it is determined that the monitoring signal exceeds a preset threshold, send the warning signal to the communication module using a cell broadcast service, and generate a risk analysis report based on historical data prediction using a target hybrid model; The communication module is used to use a character encoding mechanism to encode the warning signal, convert the obtained encoded data into a target warning broadcast message, and send it to the operating personnel to remind the operating personnel to take corresponding measures according to the risk analysis report.

2. The private system-based early warning device according to claim 1, characterized in that: The warning signal includes: message type identifier, warning content, warning period, warning number and warning level; The communication module includes: a gateway and multiple base stations; the gateway is connected to the data processing module and all the base stations respectively; the base stations are arranged at preset locations in the mine so that the base station signals cover the mine; The gateway is configured to send the warning signal to all the base stations; The base station is configured to select a corresponding signal identifier according to the message type identifier, and then encode the warning content using the character encoding mechanism to obtain the encoded data; The base station is used to encapsulate the signal identifier and the coded data into the target warning broadcast message, and send it to the operator according to the warning cycle and the number of warnings to remind the operator to take corresponding measures according to the risk analysis report.

3. The private system-based early warning device according to claim 1, characterized in that: The historical data includes: historical accident data and industry standard range; The data processing module is specifically used to determine whether the actual operating environment parameters in the monitoring signal exceed the preset threshold of the standard operating environment parameters in the industry standard range, and when exceeded, send the warning signal to the communication module.

4. The private system-based early warning device according to claim 3, characterized in that: The data processing module is specifically configured to preprocess the actual operating environment parameters and the accident parameters corresponding to the target sensor in the historical accident data, extract the target indicators and implicit features from the actual operating environment parameters and the accident parameters after obtaining the preprocessed data, and screen out redundant information from the initial hybrid model based on the implicit features to obtain the target hybrid model; The data processing module is specifically configured to use an attention mechanism to assign a corresponding weight to each of the pre-processed data, and then use the target hybrid model to predict the pre-processed data according to the target indicator and the weight to obtain the risk analysis report; Among them, the target indicators include: temperature change rate, vibration frequency, gas concentration and dust concentration; the implicit features include: redundant features and noise; the initial hybrid model includes: shallow model and deep model; the risk analysis report includes: the actual working environment parameters, risk type, risk level and emergency management plan.

5. The private system-based early warning device according to claim 2, characterized in that: The base station is further configured to, after selecting a number value of a non-standard signal identifier from a reserved number range of signal identifiers, establish a mapping relationship between a non-standard message type identifier and the number value of the non-standard signal identifier to expand the scope of the warning service corresponding to the signal identifier; Among them, the signal identifier includes: a standard signal identifier and the non-standard signal identifier, and the message type identifier includes: a standard message type identifier and the non-standard message type identifier; each number value of the standard signal identifier corresponds to a public warning service; each number value of the non-standard signal identifier corresponds to a private warning service.

6. The private system-based early warning device according to claim 2, characterized in that: The base station is further configured to, after determining that the length of the coded data exceeds a preset length, split the coded data and encapsulate the data together with the signal identifier to obtain the target early warning broadcast signal.

7. The private system-based early warning device according to claim 1, characterized in that: Also includes: a display module connected to the data processing module; The display module is used to query the historical data, display the risk analysis report, and control the data processing module to stop sending the warning signal and control the monitoring module to stop working after receiving the remote shutdown instruction from the operator.

8. An early warning method based on a private system, characterized in that: include: Control and monitor the actual operating environment parameters of the mine to obtain monitoring signals; Determine whether the monitoring signal exceeds a preset threshold, generate an early warning signal if it does, and generate a risk analysis report based on historical data prediction using a target hybrid model; The control utilizes the cell broadcast service to receive the warning signal, and utilizes the character encoding mechanism to encode the warning signal, converts the obtained coded data into a target warning broadcast message, and sends it to the operating personnel to remind the operating personnel to take corresponding measures according to the risk analysis report.

9. The private system-based early warning method according to claim 8, characterized in that: The historical data includes: historical accident data and industry standard range; the method further includes: Preprocessing the actual operating environment parameters and the accident parameters corresponding to the target sensor in the historical accident data to obtain preprocessed data; The preprocessed data is learned using an online learning strategy to adjust the weight of the loss function in the target hybrid model so that the calculation result of the loss function reaches a target threshold.

10. A computer-readable storage medium, characterized in that A computer program is stored, and when the computer program is executed by a processor, the steps of the early warning method based on the private system as described in any one of claims 8 to 9 are implemented.

Images