Mining industry multi-system joint alarm method

Abstract

The invention discloses a mining industry multi-system joint alarm method, which comprises the following steps of: receiving alarm information from a plurality of alarm systems, performing protocol conversion according to a communication protocol format of the alarm information, and verifying in a unified standardized data format; based on a preset rule base, distributing a basic priority score for the alarm information verified to be valid; generating a comprehensive priority value of each alarm through weighted calculation in combination with the area weight and the time weight of the alarm, and forming a global priority queue; and according to the global priority queue, an alarm signal instruction is generated according to a priority sequence, and a multi-mode output device is driven to output an alarm signal. According to the invention, multi-system independent alarm is changed into multi-system intelligent joint alarm, and an automatic alarm center capable of getting through a data barrier, carrying out intelligent analysis and decision making and realizing ordered output is constructed, so that the efficiency and reliability of mining safety monitoring and emergency response are integrally improved.

Description

Technical Field

[0001] This invention belongs to the field of multi-system joint alarm technology, specifically relating to a multi-system joint alarm method for the mining industry. Background Technology

[0002] As my country's mining industry develops towards deeper and more intensive mining, the underground production environment is becoming increasingly complex, and safety risks are escalating. To ensure safe production, mining enterprises have generally deployed various types of safety monitoring and alarm systems with different functions, such as fire alarm systems, gas leak alarm systems, water hazard monitoring and alarm systems, and roof pressure monitoring systems, forming a multi-layered safety protection system.

[0003] In the early stages of technological development, these systems were built and operated independently, achieving specialized monitoring of single disaster factors. With the popularization of the Internet of Things (IoT) and information technology, the industry entered a stage of system integration, giving rise to comprehensive monitoring platforms. These platforms aim to centrally display monitoring data from various independent systems on a single interface in the dispatch center, improving the convenience of information access. For example, Chinese patent CN201911073874.9, "A Method for Ground Safety Alarm and Control Linkage of Multi-System Coal Mines," embodies the idea of ​​integrating data from multiple systems and attempting to implement linked control.

[0004] However, this initial integration has not fundamentally solved the core problem of multi-system collaborative alarms. The existing technology still has the following technical issues that urgently need to be addressed:

[0005] First, system heterogeneity leads to information silos, making it impossible to process alarm information uniformly. Because different alarm systems are developed by different vendors at different times, the communication protocols (such as Modbus, PROFIBUS, and proprietary protocols) and data formats used vary greatly. Integrated monitoring platforms often only achieve superficial data centralization, failing to perform in-depth, standardized analysis and fusion of the underlying heterogeneous alarm information. This results in the inability to uniformly and fairly prioritize all alarms, creating a root cause for alarm conflicts.

[0006] Second, conflicting alarm signal outputs overload dispatchers' cognitive load. When multiple anomalies occur simultaneously underground, the alarm terminals of various independent systems trigger at the same time, causing different frequencies of beeps, different colored light signals, and pop-up messages on multiple display terminals in the dispatch room to intertwine and interfere with each other. Dispatchers struggle to quickly and accurately identify the most critical and urgent alarms amidst the chaotic alarm signals, not only delaying emergency response but also significantly increasing the risk of misjudgment.

[0007] Third, alarm priority management is static and rigid, failing to adapt to dynamic risks. Existing technologies either lack a priority management mechanism, treating all alarms equally, or can only preset fixed, single priorities based on alarm type. This static priority setting cannot reflect the dynamic changes in downhole risks. For example, in a water inrush accident with a sharp increase in water inflow, the urgency of a water hazard alarm may be far higher than that of equipment failures in the same area, and even comparable to gas anomalies. This makes the alarm output unable to accurately reflect the current actual risk level.

[0008] Therefore, existing technologies lack a method that can fundamentally break down the barriers between heterogeneous systems and intelligently and dynamically fuse and sort multi-source alarm information to ultimately achieve an orderly, efficient, and context-aware joint alarm system. Summary of the Invention

[0009] This invention provides a multi-system joint alarm method for the mining industry. By unifying the data into a standardized format, generating a global priority queue, and outputting alarm signals, it realizes intelligent and dynamic fusion and sorting of multi-source alarm information, ultimately achieving orderly, efficient, and context-aware joint alarm.

[0010] The technical solution adopted in this invention is as follows:

[0011] A multi-system joint alarm method for the mining industry includes:

[0012] It receives alarm information from multiple alarm systems, performs protocol conversion according to the communication protocol format of the alarm information, and performs verification in a standardized data format.

[0013] Based on a pre-defined rule base, basic priority scores are assigned to valid alarm information; combined with the regional and time weights of the alarm occurrence, a comprehensive priority value for each alarm is generated through weighted calculation, forming a global priority queue.

[0014] According to the global priority queue, alarm signal instructions are generated in priority order, and the multimodal output device is driven to output alarm signals in at least one of the sound, light, and text modes corresponding to the priority.

[0015] The multi-system joint alarm method for the mining industry disclosed in this invention also has the following additional technical features:

[0016] The protocol is converted according to the communication protocol format of the alarm information, specifically as follows:

[0017] Identify the communication protocol type of the alarm information;

[0018] If it is a private protocol, the corresponding protocol parsing plugin is invoked to extract the alarm field from the raw data according to the preset field mapping relationship;

[0019] The extracted alarm fields are assembled into standardized JSON format data.

[0020] The data is standardized and validated, specifically by implementing a three-level validation mechanism:

[0021] Field integrity validation is used to determine whether core fields are missing;

[0022] Format validity check is used to determine whether the time format, location information, and monitored value data type conform to the preset specifications.

[0023] Logical rationality verification is used to determine whether the monitored value exceeds the alarm threshold and whether the alarm device is online.

[0024] Assign basic priority scores as follows:

[0025] Based on the valid alarm information, determine the alarm type to obtain the basic priority score;

[0026] The basic priority score is adjusted based on field integrity verification and logical rationality verification.

[0027] The comprehensive priority value is specifically as follows:

[0028] Overall priority value = base priority score × regional weight × time weight;

[0029] The regional weight is determined based on the risk level of the alarm-occurring region and adjusted through location information verification in the format validity check; the time weight is determined based on the production period to which the alarm occurred and adjusted through time format verification in the format validity check.

[0030] After forming the global priority queue, it also includes:

[0031] When the first alarm message enters the global priority queue, the second alarm message associated with the first alarm message is obtained according to the correlation between the alarm messages, wherein the correlation is determined according to the regional location and time of the alarm message;

[0032] Based on the first alarm information and the second alarm information, determine the superimposed risk;

[0033] If it exists, the combined priority value of the first alarm information and the second alarm information is increased according to the preset rules, and the global priority queue is updated.

[0034] The correlation is determined based on the regional location and time of the alarm information, specifically:

[0035] Based on the location of the first alarm information, an association radius is defined. When the second alarm information is within the association radius, a location superposition risk is set, wherein the location superposition risk is negatively correlated with the location distance between the first alarm information and the second alarm information.

[0036] Based on the time of the first alarm information, an association window is defined. When the second alarm information is within the association window, a time superposition risk is set, wherein the time superposition risk is negatively correlated with the time difference between the first alarm information and the second alarm information.

[0037] The correlation is determined by combining the location-based risk and the time-based risk.

[0038] This invention also discloses a multi-system joint alarm system for the mining industry, used to implement the aforementioned multi-system joint alarm method for the mining industry, the system comprising:

[0039] The data access module is used to receive, convert protocols, and verify alarm information from multiple alarm systems.

[0040] The priority management module is communicatively connected to the data access module and is used to obtain the comprehensive priority value of alarm information and generate a global priority queue.

[0041] The alarm output module is communicatively connected to the priority management module and is used to drive the multimodal output device to output alarm signals according to the global priority queue.

[0042] In addition, the present invention also discloses a storage medium,

[0043] The storage medium stores a computer program.

[0044] When the computer program is executed, it implements the steps of the multi-system joint alarm method for the mining industry.

[0045] The present invention further discloses a processing apparatus, comprising:

[0046] Memory, used to store computer programs;

[0047] A processor is used to implement the steps of the multi-system joint alarm method for the mining industry when executing the computer program.

[0048] Due to the adoption of the above technical solution, the beneficial effects achieved by this invention are as follows:

[0049] 1. In this invention, protocol conversion is performed based on the communication protocol format of alarm information to unify it into a standardized data format. This enables the transformation of data from heterogeneous alarm systems from different manufacturers and using different protocols into a unified, standardized data object. This breaks down technical barriers between systems, allowing for consistent processing and evaluation of all alarm information. Deep data fusion can be achieved without replacing any existing independent alarm system hardware in the mine, significantly reducing the cost and difficulty of system modification and integration.

[0050] By combining the regional and temporal weights of alarm occurrences, a comprehensive priority value is generated for each alarm through weighted calculation. This expands priority determination from a single alarm type dimension to multiple dynamic dimensions such as space and time. This ensures that the same alarm type has a higher priority in high-risk areas (such as mining faces) than in low-risk areas (such as surface warehouses); and a higher priority during peak production periods than during shutdown and maintenance periods. The output priority queue more realistically reflects the dynamic changes and actual urgency of underground risks, avoiding misjudgments that may result from fixed priorities, and providing dispatchers with a scientific and accurate basis for decision-making.

[0051] Based on the global priority queue, alarm signal commands are generated in priority order, driving the multimodal output device to output at least one of the following modes: sound, light, and text, corresponding to the priority. This transforms the originally disordered and concurrent alarm signal output into a sequential and controllable process. High-priority alarms can be quickly identified by dispatchers through their differentiated output modes. This effectively eliminates signal masking and interference when multiple alarms are triggered simultaneously, ensuring that the most critical alarms are transmitted to personnel immediately, thus significantly shortening the cycle from receiving the alarm to making a correct response and ensuring underground safety.

[0052] In summary, this invention represents a qualitative leap from independent alarms across multiple systems to intelligent joint alarms across multiple systems. It constructs an automated alarm hub capable of breaking down data barriers, performing intelligent analysis and decision-making, and achieving orderly output, thereby comprehensively improving the efficiency and reliability of mining safety monitoring and emergency response. Attached Figure Description

[0053] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings:

[0054] Figure 1 This is a flowchart illustrating the multi-system joint alarm method for the mining industry according to one embodiment of the present invention. Detailed Implementation

[0055] To more clearly illustrate the overall concept of the present invention, a detailed description will be provided below with reference to the accompanying drawings and examples.

[0056] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0057] like Figure 1 As shown, a multi-system joint alarm method for the mining industry includes:

[0058] S100: Receives alarm information from multiple alarm systems, performs protocol conversion according to the communication protocol format of the alarm information, and performs verification in a standardized data format.

[0059] The core objective of this step is to resolve the information silo problem caused by the heterogeneity among multiple alarm systems in the mining industry, laying a solid data foundation for subsequent unified intelligent analysis and processing.

[0060] Multi-protocol access and identification: The system data access module's communication interface listens in parallel to multiple types of physical interfaces (such as serial ports, Ethernet ports) and network ports. Using a pre-built protocol feature library, the received raw data stream is parsed for header features (such as a specific magic number 0xAA55), port numbers, or device addresses to automatically identify its communication protocol type (such as Modbus RTU, TCP / IP, ZigBee, or a proprietary protocol).

[0061] Protocol conversion and data standardization employ a hybrid strategy of general adaptation and plug-in extension. For mainstream public protocols (such as Modbus and TCP / IP), the system has a built-in general parser that unpacks data according to standard protocol specifications and extracts key fields. For mining industry-specific protocols, a plug-in architecture is used. When a private protocol is identified, the corresponding protocol parsing plugin (such as a specific Python or Java script) is automatically invoked. This plugin contains the complete parsing logic for the private protocol, including:

[0062] Field mapping relationships map specific bytes or fields in a proprietary protocol to standard field names. For example, the 0x05 field in the proprietary protocol is mapped to monitorValue, and the 0x08 field is mapped to location.

[0063] Data format conversion converts the original binary and hexadecimal data into readable decimal numbers or strings, and performs the conversion according to a preset ratio (e.g., converting the hexadecimal value 0x04D2 into decimal 1234, and then dividing by 100 to obtain the actual pressure value of 12.34 MPa).

[0064] Ultimately, all alarm information is assembled into a unified standard JSON format. This format explicitly defines required fields (such as alarmType, alarmTime, location, monitorValue, threshold, deviceId) and optional extended fields.

[0065] It should be noted that in industrial scenarios such as mining, where reliability requirements are extremely high, directly using raw, heterogeneous alarm data for joint processing is both impractical and dangerous. Inconsistent protocols prevent the system from understanding all information; unreliable data will lead to errors in subsequent intelligent algorithms.

[0066] This approach employs a universal adaptation and plug-in expansion strategy, resulting in strong system compatibility and low modification costs. It can seamlessly integrate with various alarm systems, from mainstream to outdated, and from public to private, without requiring replacement of existing hardware. This significantly reduces the barriers and costs associated with technological upgrades for mining companies.

[0067] The system produces standardized, clean, and structured data, enabling subsequent priority management modules to perform calculations based on a consistent language and reliable data. This provides a high-quality data foundation for subsequent intelligent processing, ensuring the accuracy and reliability of the entire system's decisions.

[0068] S200: Based on a preset rule base, it assigns basic priority scores to valid alarm information; combining the regional weight and time weight of the alarm occurrence, it generates a comprehensive priority value for each alarm through weighted calculation and forms a global priority queue.

[0069] The core objective of this step is to address the problem of static or missing priorities in existing alarm systems. By introducing a multi-dimensional, quantifiable, and dynamic risk assessment model, the complex list of alarm information is transformed into a context-aware, ordered emergency response sequence. This aims to ensure that at any given time, dispatchers prioritize alarms with the highest overall risk, rather than simply pre-defined, critical alarms based on their type.

[0070] Basic priority allocation invokes a preset basic priority rule base. This rule base is indexed by alarm type and predefines the baseline importance of different alarm types. For example:

[0071] Level 1 (100 points): Disasters such as gas leaks and coal dust explosions that may immediately cause major casualties;

[0072] Level 2 (80 points): Disasters that develop rapidly and cause great harm, such as fires and flooding;

[0073] Level 3 (60 points): Abnormalities with potential risks, such as excessive roof pressure and abnormal water inflow.

[0074] Level 4 (40 points): General abnormalities such as equipment failure and slight exceedance of environmental parameters.

[0075] Upon receiving a valid alarm message, the system matches it according to its alarmType field (e.g., "gasLeak") and assigns the corresponding base score.

[0076] Dynamic weight acquisition introduces two dynamic context factors, region and time, to adjust the basic priority.

[0077] The process involves obtaining regional weights by maintaining a regional risk weight configuration table. Based on the location field (e.g., "undergroundWorkface_02") in the alarm information, the system matches the corresponding risk region and retrieves the appropriate weight value. For example:

[0078] High-risk areas (underground working faces, blasting zones): weighted at 1.2;

[0079] Medium-risk areas (transportation tunnels, electromechanical chambers): weight 1.0;

[0080] Low-risk areas (ground warehouses, office areas): weighted at 0.8.

[0081] In addition, time weighting is achieved by maintaining a production period weight configuration table and linking it to the mine's production schedule. Based on the alarm time (alarmTime), the current production status is automatically determined, and the corresponding weight value is obtained. For example:

[0082] Peak production period: weight 1.1 (high population density, more serious consequences);

[0083] Maintenance period: weighted at 0.9;

[0084] Production stoppage period: weight 0.7 (fewer personnel, relatively lower risk).

[0085] The overall priority value is calculated using a weighted product model. The overall priority value = base priority score × regional weight × time weight. This amplifies the score in high-risk scenarios, making the differences in the urgency of incidents more significant.

[0086] A global priority queue is generated, and all alarms to be processed are sorted according to their comprehensive priority value, forming a global dynamic queue. Specifically, they are sorted in descending order of comprehensive priority value; if the scores are the same, they are sorted in ascending order of alarm occurrence time (i.e., earlier occurrences take precedence). To achieve efficient sorting and real-time updates, this queue is typically implemented in software using efficient data structures such as max-heap.

[0087] It should be noted that in the complex and ever-changing downhole environment, the actual risk of an alarm is not solely determined by its type. Fixed priorities cannot address complex scenarios where low-risk alarms may escalate into major accidents in high-risk areas / time periods.

[0088] This step enables alarm priority to accurately reflect the overall risk level at what time, where, and what happened, achieving context-aware dynamic risk assessment. Through a clear mathematical calculation model, it transforms the previously vague judgments relying on dispatchers' personal experience into a repeatable and traceable quantitative process based on explicit rules, greatly improving the scientific rigor and objectivity of emergency decision-making.

[0089] Moreover, the generated global priority queue provides dispatchers and subsequent automated linkage systems with an exceptionally clear roadmap for action. It ensures that limited emergency resources and attention are always directed to the most critical emergencies, thereby significantly improving the overall efficiency and safety of mine disaster emergency response and ensuring optimal allocation of emergency resources.

[0090] S300: Based on the global priority queue, generate alarm signal instructions in priority order, and drive the multimodal output device to output alarm signals in at least one of the sound, light, and text modes corresponding to the priority.

[0091] The core purpose of this step is to solve the problem of conflicting and chaotic output signals when multiple alarms are triggered simultaneously, and to ensure that high-priority alarm information after intelligent sorting can be perceived and understood by dispatchers in a timely and unambiguous manner, thereby enabling effective action in actual command.

[0092] Alarm signal command generation: The signal generation unit of the alarm output module acts as the command center, reading information from the head of the generated global priority queue (i.e., the current highest priority alarm). Based on the level range (e.g., high, medium, low) into which the alarm's comprehensive priority value falls, a specific and differentiated set of control commands is generated. This set of commands precisely defines the actions that each subsequent output device should perform.

[0093] Driven by a multimodal output device, this system employs a multimodal fusion output strategy to enhance the transmission and recognition of key information by stimulating multiple sensory channels, including hearing and vision, of the dispatcher. Different priorities correspond to distinctly different output modes, creating a strong cognitive contrast.

[0094] Specifically, the sound device drives the industrial-grade audible and visual alarm to emit beeps with different characteristics. These include:

[0095] High priority triggers a high-frequency buzzer (2000Hz) that continuously emits sound at a default volume of 80dB, creating a strong sense of urgency with its sharp and continuous sound.

[0096] Medium priority triggers a mid-frequency buzzer (1000Hz), which sounds every 1 second at a volume of 60dB, serving as a reminder without being overly disturbing.

[0097] Low priority triggers a low-frequency beep (500Hz), which sounds every 2 seconds and only 3 times at a time, with a volume of 40dB, serving as an notification.

[0098] The lighting system drives the tri-color LED lights on the ceiling of the control room. This includes:

[0099] High priority, activates the red light cluster and operates in strobe mode (frequency 5Hz), which is extremely visually impactful;

[0100] Medium priority, activate the yellow light group, and operate in flashing mode (frequency 3Hz);

[0101] Low priority, activate the green light group, and operate in constant-on mode.

[0102] The display device driver provides differentiated displays on the control panel and operator console monitors. This includes:

[0103] High priority, full-screen display on the 55-inch main screen, red background, using 36-point large font, detailed content, forcibly occupying the visual focus;

[0104] Medium priority, displayed in the right 1 / 3 area of ​​the main screen, with a yellow background and using 24-point font;

[0105] Low priority, it is only displayed in green, 16-point font in the status bar of the console monitor, without interfering with the main interface.

[0106] Understandably, a high-priority alarm calculated intelligently might still be lost among a multitude of noisy signals due to conventional methods. Therefore, it is essential to establish a reinforced and differentiated output system that strictly corresponds to the priority queue; this is the ultimate guarantee for realizing the value of the entire solution.

[0107] This step transforms concurrent, chaotic signal outputs into sequential, hierarchical, and coordinated outputs, fundamentally eliminating mutual interference and masking between signals, transforming the control room environment from chaotic to orderly, and completely resolving the problem of multiple alarm signal conflicts.

[0108] Dispatchers no longer need to painstakingly distinguish between intertwined alarm signals. They can accurately determine the type and urgency of the most urgent situation based on intuitive features such as sound frequency, light color and flashing pattern, and screen display area. This significantly shortens information understanding and decision-making time, greatly reducing the cognitive load and risk of misjudgment for dispatchers.

[0109] In a preferred embodiment of the present invention, protocol conversion is performed according to the communication protocol format of the alarm information, specifically as follows:

[0110] Identify the communication protocol type of the alarm information;

[0111] If it is a private protocol, the corresponding protocol parsing plugin is invoked to extract the alarm field from the raw data according to the preset field mapping relationship;

[0112] The extracted alarm fields are assembled into standardized JSON format data.

[0113] The core objective of this implementation method is to specifically address the compatibility challenges of numerous non-standard, proprietary protocols defined by different vendors within the mining industry, under a unified access framework. It aims to achieve a scalable, maintainable, and loosely coupled protocol conversion mechanism, ensuring that even closed, proprietary alarm systems can be efficiently and accurately integrated into this unified alarm platform, thereby truly achieving the ultimate goal of seamless system-wide access.

[0114] The system uses a built-in protocol feature library as the basis for identification. When the raw data stream enters the protocol conversion unit, the unit performs rapid matching and analysis on its header features. The recognition engine traverses the feature library to tag the incoming data packets with protocol types, identifying public and private protocols.

[0115] This implementation uses a plug-in architecture to process identified private protocols, rather than hardcoding the parsing logic into the system kernel. When a protocol is identified as a private protocol, the corresponding parsing plugin is automatically loaded from the protocol parsing plugin library, enabling plugin invocation. This plugin pre-configures the complete parsing rules for that private protocol, with a core field mapping table for implementing field mapping.

[0116] All parsed fields, regardless of their source, are ultimately encapsulated into a unified data structure. JSON format is used as the standardized carrier because JSON has advantages such as clear structure, ease of parsing, and extremely high cross-platform support.

[0117] Understandably, the mining industry involves a complex mix of equipment sources, old and new systems, and numerous proprietary protocols. Adopting the traditional approach of customizing interfaces for each system would result in bloated core code, difficult maintenance, extremely high upgrade costs, and an inability to adapt to the needs of future integrated systems.

[0118] This implementation achieves exceptional system scalability and flexibility. When integrating a new alarm system using an unknown proprietary protocol, there is no need to modify, compile, or restart the system's core program. Technical personnel only need to write a corresponding parsing plugin according to the new protocol's specifications and register it in the system's plugin library. This significantly shortens the integration cycle and lowers the technical barrier.

[0119] For mining companies, this solution protects their investments in legacy systems and specialized equipment, eliminating the need for costly hardware replacements for integration. For system developers and maintainers, the modular approach simplifies and streamlines troubleshooting, protocol updates, and functional testing, significantly reducing long-term maintenance costs and risks.

[0120] In a preferred embodiment of the present invention, the data is standardized for verification, specifically including the execution of a three-level verification mechanism:

[0121] Field integrity validation is used to determine whether core fields are missing;

[0122] Format validity check is used to determine whether the time format, location information, and monitored value data type conform to the preset specifications.

[0123] Logical rationality verification is used to determine whether the monitored value exceeds the alarm threshold and whether the alarm device is online.

[0124] The core objective of this implementation method is to construct a multi-layered, in-depth data quality control system after protocol conversion. This ensures that every alarm message entering the core decision-making process is not only formatted uniformly but also complete, valid, and logically reliable. The ultimate goal is to prevent invalid, erroneous, or false data from contaminating the system and triggering false alarms, thereby guaranteeing the accuracy and reliability of the entire joint alarm system's decision output.

[0125] This three-tiered validation mechanism is interconnected, forming a progressively refined filtering system. The first tier, field integrity validation, performs a mandatory existence check. The system maintains a predefined list of core fields (e.g., alarmType, alarmTime, location, monitorValue, deviceId). The validation unit iterates through the received standardized JSON data, verifying that it completely contains all fields from the list.

[0126] If any core field is missing, the data is immediately deemed invalid and will not proceed to any further processing. It will be discarded and an error log containing information about the missing field will be recorded. At the same time, error codes such as "400 Bad Request" can be returned to the data source.

[0127] The second level is format validity validation: based on the completeness of the fields, it checks the standardization of data format and content. This goes beyond simple existence checks and enters the semantic level.

[0128] Specifically, the time format check ensures that the alarmTime field conforms to the ISO 8601 standard format. This ensures unambiguous parsing and correct sorting of time information.

[0129] The location information checks if the value of the `location` field exists in a predefined, valid list of mining area locations. This prevents area weight matching failures or erroneous actions due to incorrect location information.

[0130] The data type of the monitored value is confirmed to ensure that monitorValue and threshold are numeric and meet the precision requirements (e.g., retain 1-2 decimal places).

[0131] Data with incorrect formatting is also deemed invalid, and a specific error description is returned to facilitate quick location and repair of data source problems.

[0132] The third level, logical rationality verification, aims to identify data that is formatted correctly but whose content does not conform to common sense or business logic.

[0133] Specifically, the core of threshold logic validation is to determine whether the alarm triggering is reasonable. The execution logic checks if `monitorValue > threshold` is true. If the monitored value does not exceed the threshold, the alarm is not valid in business logic.

[0134] Device status verification uses the deviceId to query the device status management table to confirm whether the sensor or alarm device is currently online. If the device is offline, faulty, or under maintenance, the reliability of its alarm information is extremely low.

[0135] Data that does not exceed the threshold or is from offline devices is considered an invalid or suspicious alarm. This type of data will not be sent to the priority queue, but will be recorded in a dedicated log, and equipment maintenance personnel will be proactively notified for verification. This extends the functionality from passively receiving alarms to proactively discovering equipment faults.

[0136] It is important to understand that in the field of industrial safety monitoring, even minor data errors can lead to catastrophic decision-making consequences. A misformatted timestamp can cause events to be out of order; an off-list location can prevent emergency responders from finding the incident site; a false alarm caused by equipment malfunction can keep dispatchers busy and cause them to overlook real dangers.

[0137] This implementation systematically eliminates incomplete, distorted, and illogical data, ensuring that the data foundation upon which subsequent dynamic priority calculations rely is solid and reliable, directly enhancing the authority of the entire system's output results.

[0138] By intercepting a large number of invalid and suspicious alarms, the system avoids alarm fatigue caused by dispatchers frequently dealing with false alarms, ensuring that their attention and emergency resources can be focused on real and effective security threats, thereby improving the overall efficiency of security response.

[0139] As a preferred embodiment of this implementation, the allocation of basic priority scores is as follows:

[0140] Based on the valid alarm information, determine the alarm type to obtain the basic priority score;

[0141] The basic priority score is adjusted based on field integrity verification and logical rationality verification.

[0142] The core objective of this embodiment is to use the quality assessment results from the data access phase to influence alarm priority management. A correlation mechanism between data reliability and alarm urgency is established, aiming to differentiate alarms with varying data quality. This ensures that the final comprehensive priority reflects not only the potential risk of the disaster but also the reliability of the alarm information, thereby guiding dispatchers to prioritize alarms that are both urgent and reliable.

[0143] Obtaining a base score is the baseline step. The system queries the preset base priority rule base based on the alarmType field (such as "gasLeak") in the valid alarm information and assigns it an initial base priority score (for example, 100 points for a gas leak alarm).

[0144] It should be noted that a score adjustment module is introduced. This module receives detailed output from the aforementioned three-level verification mechanism and fine-tunes the base score according to predefined rules.

[0145] Adjustments are made based on field completeness checks: Although the data has passed completeness checks (i.e., all core fields are present), its richness can still be assessed. For example, if an alarm includes extended fields such as signalStrength and batteryLevel in addition to the core fields, it indicates more comprehensive information and higher credibility. Alarms with such complete information can be given a positive adjustment (e.g., a base score +5 points) to prioritize them.

[0146] It should be noted that format validation primarily ensures that the data format is correct. Generally, passing this validation is considered acceptable, and no further adjustments are needed; invalid data has already been filtered out.

[0147] Adjustments should be made based on logical rationality verification: Pay attention to the auxiliary credibility indicators generated during the verification process. Alarms issued by devices that are online and have good signal strength have the highest credibility, and their base scores should be maintained or adjusted positively.

[0148] Alarms from devices known to be unstable, with weak signals, or on the verge of maintenance are considered low in reliability even if they pass logical checks. For such alarms with questionable reliability, a negative adjustment (e.g., -10 points from the base score) is implemented to reduce their likelihood of entering the high-priority queue, thus avoiding unnecessary panic and resource redeployment caused by false alarms from single-point devices.

[0149] Understandably, in real industrial settings, false alarms from sensors, intermittent equipment malfunctions, and signal transmission interference are common occurrences. If all alarms that pass the most basic checks are treated equally, a false alarm caused by line interference will have the same initial weight as a genuine alarm from a properly functioning sensor, which will undoubtedly mislead decision-making.

[0150] This embodiment is driven by both risk and credibility, making the priority calculation model more complete. This results in a global priority queue that is not only ordered but also more resistant to interference, leading to higher overall decision-making quality.

[0151] By downgrading the priority of low-confidence alarms, the system can effectively suppress the consumption of scheduling resources by false alarms. Dispatchers can place greater trust in high-priority alarms pushed by the system, thereby focusing valuable attention and emergency resources on high-risk, high-confidence real threats, significantly improving the overall efficiency of emergency response.

[0152] Specifically, the comprehensive priority value is as follows:

[0153] Overall priority value = base priority score × regional weight × time weight;

[0154] The regional weight is determined based on the risk level of the alarm-occurring region and adjusted through location information verification in the format validity check; the time weight is determined based on the production period to which the alarm occurred and adjusted through time format verification in the format validity check.

[0155] The core objective of this embodiment is to integrate the various parameters (base score, regional weight, time weight) obtained into a single, quantifiable comprehensive priority value through a precisely defined adjustment process.

[0156] The overall priority value = base priority score × area weight × time weight, which can effectively amplify the role of key factors. For example, if an alarm with a high base score (such as gas leak, 100 points) also occurs in a high-risk area (1.2), its risk will be significantly emphasized (100 * 1.2 = 120), quickly creating a gap with alarms with low base scores (such as equipment failure, 40 * 1.2 = 48) that also occur in a high-risk area, making the queue ranking clearer.

[0157] Specifically, the regional weight is based on the inherent risk level of the alarm location. This level is pre-set based on mining safety regulations and experience assessments.

[0158] For example, high-risk areas (underground working faces, blasting zones): weight = 1.2;

[0159] Medium-risk areas (transportation tunnels, electromechanical chambers): weight = 1.0;

[0160] Low-risk areas (ground warehouses, office areas): weight = 0.8.

[0161] The time weight is based on the production activity period to which the alarm time belongs.

[0162] For example, peak production period (high population density, active production activities): weight = 1.1;

[0163] Maintenance period: Weight = 0.9;

[0164] Production stoppage period (few personnel): weight = 0.7.

[0165] Furthermore, it is understood that the regional weight in this embodiment is determined based on the risk level of the alarm occurrence area and adjusted through location information verification in the format validity check; the time weight is determined based on the production period to which the alarm occurs and adjusted through time format verification in the format validity check.

[0166] This makes the calculation of regional and time weights highly dependent on the accuracy of the `location` and `alarmTime` fields. Therefore, the reliability of the weight calculation is explicitly anchored to the previous format validity check.

[0167] Understandably, without a quantitative model, priority ranking will revert to fuzzy judgments relying on human experience; and without rigorous validation of input data, even the most perfect model will produce errors due to poor input quality. Therefore, strongly linking a clear mathematical model with prior data validation is a necessary technical measure to ensure the scientific, reliable, and automated nature of the entire dynamic priority calculation process.

[0168] This embodiment provides an objective, consistent, and interpretable ranking standard, completely eliminating the interference of subjective human factors. Furthermore, it can accurately capture the spatial and temporal dynamic characteristics of risk, achieving precise contextualized risk assessment.

[0169] This reliable overall priority value serves as the basis for decision-making for all subsequent advanced functions (such as linkage control), laying a solid foundation for the system's intelligent decision-making.

[0170] In a preferred embodiment of the present invention, after forming the global priority queue, the method further includes:

[0171] When the first alarm message enters the global priority queue, the second alarm message associated with the first alarm message is obtained according to the correlation between the alarm messages, wherein the correlation is determined according to the regional location and time of the alarm message;

[0172] Based on the first alarm information and the second alarm information, determine the superimposed risk;

[0173] If it exists, the combined priority value of the first alarm information and the second alarm information is increased according to the preset rules, and the global priority queue is updated.

[0174] The core objective of this implementation method is to overcome the limitations of a single alarm system by analyzing the correlation of alarm information from multiple systems to identify more severe disaster chain risks that may be triggered by the coupling of multiple independent events. The goal is to elevate the system's intelligence level from responding to single events to providing early warnings of potential complex risks. By dynamically prioritizing correlated alarms, it proactively alerts dispatchers to the possibility of disaster escalation, thereby achieving earlier and more accurate emergency intervention.

[0175] The associated alarm information retrieval unit is activated immediately upon the entry of the first alarm information (e.g., a fire alarm) into the queue.

[0176] The correlation is determined based on the regional location and time of the alarm information, specifically:

[0177] Based on the location of the first alarm information, an association radius is defined. When the second alarm information is within the association radius, a location superposition risk is set, wherein the location superposition risk is negatively correlated with the location distance between the first alarm information and the second alarm information.

[0178] Based on the time of the first alarm information, an association window is defined. When the second alarm information is within the association window, a time superposition risk is set, wherein the time superposition risk is negatively correlated with the time difference between the first alarm information and the second alarm information.

[0179] The correlation is determined by combining the location-based risk and the time-based risk.

[0180] In other words, a correlation radius (e.g., 50 meters) is defined centered on the location of the first alarm, forming a dynamic correlation area. All other alarm information whose locations fall within this area is retrieved as candidate second alarm information.

[0181] In addition, a correlation time window is set (e.g., ±3 minutes). Candidate alarm information within this window is filtered out based on the difference between the alarm time and the first alarm timestamp.

[0182] Ultimately, based on the alarm information related to space and time, the second alarm information was determined to be associated with the first alarm information.

[0183] To determine the overlapping risks, the information from the first and second alarms (such as "fire + excessive gas concentration") is used as input, and a predefined overlapping risk rule base is queried for logical judgment.

[0184] The rule base includes causal chain superposition, IF the first alarm is a fire AND there is a second alarm gas concentration >1.0% THEN there is a superposition risk of "fire may cause gas explosion".

[0185] The consequences are compounded and exacerbated. If the first alarm is water seepage AND there is a second alarm, power supply failure, then it is determined that there is a compound risk of "intensified water damage and possible failure of the drainage system".

[0186] Escape obstruction superposition: IF First alarm is any high priority disaster AND there is a second alarm main passage blockage / smoke THEN there is a superposition risk of "obstructing personnel evacuation".

[0187] Based on the identified overlapping risk types, a preset priority enhancement strategy is executed. In the overlapping risk rule base, each risk type corresponds to a priority adjustment amount (for example, the risk of "may cause an explosion" has an adjustment amount of +50 points).

[0188] The calculated correction amount is simultaneously added to the original combined priority value of the first alarm message and all associated second alarm messages.

[0189] The priority management module immediately reorders the global priority queue based on the revised new value. This action is likely to trigger the alarm output module's queue-jumping mechanism, allowing alarms that have escalated due to accumulated risks to immediately preempt output resources.

[0190] Understandably, in real-world mine disasters, isolated events are often not the most dangerous; the most dangerous are the disaster chains formed by the interaction of multiple factors. Therefore, setting up this step is crucial for achieving proactive disaster prevention and shifting the emergency response focus forward, and it is the core manifestation of this invention's move towards intelligent situational assessment.

[0191] This implementation method represents a leap from single-event response to disaster chain early warning, enabling the identification of complex risks. It proactively reveals to dispatchers the deeper systemic risks hidden behind multiple independent alarms, significantly improving the foresight and accuracy of emergency decision-making and making emergency response measures more targeted and effective.

[0192] This invention also provides a multi-system joint alarm system for the mining industry, used to implement the aforementioned multi-system joint alarm method for the mining industry, the system comprising:

[0193] The data access module is used to receive, convert protocols, and verify alarm information from multiple alarm systems.

[0194] The priority management module is communicatively connected to the data access module and is used to obtain the comprehensive priority value of alarm information and generate a global priority queue.

[0195] The alarm output module is communicatively connected to the priority management module and is used to drive the multimodal output device to output alarm signals according to the global priority queue.

[0196] Therefore, it can achieve any effect in the multi-system joint alarm method in the mining industry, which will not be elaborated here.

[0197] The present invention also provides a storage medium,

[0198] The storage medium stores a computer program.

[0199] When the computer program is executed, it implements the steps of the multi-system joint alarm method for the mining industry.

[0200] Therefore, it can achieve any effect in the multi-system joint alarm method in the mining industry, which will not be elaborated here.

[0201] The present invention further provides a processing apparatus, comprising:

[0202] Memory, used to store computer programs;

[0203] A processor is used to implement the steps of the multi-system joint alarm method for the mining industry when executing the computer program.

[0204] Therefore, it can achieve any effect in the multi-system joint alarm method in the mining industry, which will not be elaborated here.

[0205] For any parts not mentioned in this invention, existing technologies can be used or referenced.

[0206] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0207] The above description is merely an embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the present invention should be included within the scope of the claims of the present invention.

Claims

1. A method for a multi-system joint alarm in the mining industry, characterized in that, The application relates to an alarm information processing method and device. The application comprises the following steps: Receiving alarm information from multiple alarm systems, performing protocol conversion according to the communication protocol format of the alarm information, and checking in a standardized data format; Based on a preset rule base, assigning a basic priority score to the checked alarm information; combining the regional weight and time weight of the alarm occurrence, generating a comprehensive priority value of each alarm through weighted calculation, and forming a global priority queue; 2. The mining industry multi-system joint alarm method according to claim 1, characterized in that, According to the global priority queue, generating an alarm signal instruction in priority order, and driving a multi-modal output device to output an alarm signal in at least one of the sound, light and text modes corresponding to the priority. According to the communication protocol format of the alarm information, the protocol conversion is specifically as follows: Identifying the communication protocol type of the alarm information; If it is a private protocol, a corresponding protocol analysis plug-in is called, and alarm fields are extracted from the original data according to a preset field mapping relationship; 3. The mining industry multi-system joint alarm method according to claim 1 or 2, characterized in that, The extracted alarm fields are assembled into standardized JSON format data. The checking in a standardized data format specifically includes executing a three-level checking mechanism: Field integrity checking is used to judge whether the core field is missing; Format validity checking is used to judge whether the time format, location information and monitoring value data type conform to the preset specification; 4. The mining industry multi-system joint alarm method according to claim 3, characterized in that, Logical rationality checking is used to judge whether the monitoring value exceeds the alarm threshold and whether the alarm device is online. The basic priority score is specifically as follows: According to the checked alarm information, the alarm type is determined to obtain the basic priority score; 5. The mining industry multi-system joint alarm method according to claim 4, characterized in that, The basic priority score is adjusted according to the field integrity checking and the logical rationality checking. The comprehensive priority value is specifically as follows: Comprehensive priority value = basic priority score x regional weight x time weight; 6. The mining industry multi-system joint alarm method according to claim 1, characterized in that, Wherein, the regional weight is determined based on the risk level of the alarm occurrence area and is adjusted through the location information checking in the format validity checking; the time weight is determined based on the production period to which the alarm occurrence time belongs and is adjusted through the time format checking in the format validity checking. After forming the global priority queue, the following steps are further included: When the first alarm information enters the global priority queue, according to the correlation between the alarm information, the second alarm information associated with the first alarm information is obtained, wherein the correlation is determined according to the regional position and time of the alarm information; Based on the first alarm information and the second alarm information, the superimposed risk is judged; 7. The mining industry multi-system joint alarm method according to claim 6, characterized in that, If it exists, the comprehensive priority value of the first alarm information and the second alarm information is improved according to the preset rule, and the global priority queue is updated. The correlation is determined according to the regional position and time of the alarm information, and is specifically as follows: According to the position of the first alarm information, an associated radius is drawn, and when the second alarm information is within the associated radius, a position superimposed risk is set, wherein the position superimposed risk is negatively correlated with the position distance of the first alarm information and the second alarm information. According to the time of the first alarm information, a correlation window is delimited, when the second alarm information is within the correlation window, a time superposition risk is set, wherein the time superposition risk is negatively related to the time difference between the first alarm information and the second alarm information; According to the position superposition risk and the time superposition risk, the correlation is determined comprehensively.

8. A multi-system combined alarm system for the mining industry, characterized in that, For realizing the mining industry multi-system joint alarm method as claimed in any one of claims 1-7, the system comprises: a data access module, configured to receive, protocol convert and verify alarm information of multiple alarm systems; a priority management module, in communication connection with the data access module, configured to obtain a comprehensive priority value of the alarm information and generate a global priority queue; an alarm output module, in communication connection with the priority management module, configured to drive a multi-modal output device to output an alarm signal according to the global priority queue.

9. A storage medium, characterized in that: a computer program is stored on the storage medium, the computer program, when executed, implements the steps of the mining industry multi-system joint alarm method as claimed in any one of claims 1-7.

10. A processing device, characterized by comprise: a memory, configured to store a computer program; a processor, configured to execute the computer program to implement the steps of the mining industry multi-system joint alarm method as claimed in any one of claims 1-7.

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