Mine multi-source signal visual centralized control method and device, electronic equipment and storage medium

Abstract

The invention provides a mine multi-source signal visual centralized control method and device, electronic equipment and a storage medium, and relates to the technical field of monitoring, and the method comprises the steps: packaging various heterogeneous signals from different source equipment into a standardized signal model carrying metadata, and carrying out the time synchronization and spatial position mapping of the standardized signal model, thereby achieving the visual centralized control of mine multi-source signals. A redundant architecture is adopted to deploy control nodes and implement a signal caching mechanism, collaborative analysis and alarm reasoning are performed on fused multi-source signals based on an intelligent analysis model, and a visual interface is driven to dynamically interact. The problems of serious signal island, complex and low-efficiency operation, insufficient emergency decision support and the like caused by lack of a unified signal processing mechanism in independent operation of various subsystems, incapability of space-time alignment of signals, interruption of visual display when a network or a node is abnormal, and lack of multi-source signal intelligent collaborative analysis and decision auxiliary functions in the prior art can be solved.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of monitoring, and in particular to a mine multi-source signal visual centralized control method and device, electronic equipment and storage medium. BACKGROUND

[0002] In high-risk industrial sites such as coal mines, mines and large thermal power plants, safety production is the core task. The central control room or dispatching command center of these places currently needs to process multiple types of signals synchronously, including high-definition video monitoring of underground tunnels, mining faces and other areas, industrial sensor data such as gas concentration and temperature, production execution system (MES), power monitoring system (SCADA), personnel positioning system related information, emergency communication signals such as emergency broadcasting and video conferencing, and third-party IPC camera signals of different brands and protocols.

[0003] However, the existing centralized control system has many shortcomings: the independent operation of various subsystems leads to serious signal island, and video, data and voice cannot be fused and displayed; signal switching requires multiple software or hardware panels to cooperate, which is complex, inefficient and prone to misoperation; there is a lack of unified visual interface, making it difficult to build a global situation map to support emergency decision-making; remote collaboration capability is weak, and management personnel cannot reverse control the signal source computer through mobile terminals; traditional splicing screens have problems such as inconsistent color, synchronization delay and insufficient resolution, affecting the identification of key information, so there is an urgent need for a visual centralized control platform designed for high-risk industrial scenes, supporting multiple protocols, high reliability and strong interaction. SUMMARY

[0004] The present disclosure provides a mine multi-source signal visual centralized control method and device, electronic equipment and storage medium. Its main purpose is to at least solve one of the technical problems in the related art to some extent.

[0005] According to a first aspect of the present disclosure, a mine multi-source signal visual centralized control method is provided, comprising: packaging multiple types of heterogeneous signals from different source devices into a standardized signal model carrying metadata; performing time synchronization and spatial position mapping on the standardized signal model to generate a spatio-temporal fusion situation map on a unified visual interface; deploying control nodes using a redundant architecture and implementing a signal caching mechanism to ensure the continuity of visual display when the network or node is abnormal; performing collaborative analysis and alarm reasoning on the fused multi-source signals based on an intelligent analysis model, and driving the visual interface to dynamically interact according to the reasoning result to assist decision-making.

[0006] Optionally, the time synchronization and spatial position mapping on the standardized signal model comprises: aligning the signal model with time information through a precise clock synchronization protocol; According to the spatial coordinate information carried by the signal model, the corresponding visual element is registered to the corresponding position in the unified industrial scene digital model.

[0007] Optionally, the control node is deployed using a redundant architecture and a signal buffering mechanism is implemented, including: The master control node and the standby control node are set, and the state synchronization between the two is maintained through a state monitoring mechanism; The key video signal is locally buffered at the edge side, and after the network is restored, the buffered signal is returned to the central system according to the time information.

[0008] Optionally, the intelligent analysis model is used to cooperatively analyze and alarm reason the fused multi-source signal, including: The same event or state represented by different modal signals is associated and identified using the intelligent analysis model; When the alarm linkage rule is met, a fusion alarm information is generated.

[0009] Optionally, it further includes: According to the localized data of the target industrial scene, the parameters of the intelligent analysis model are updated online and adaptively.

[0010] Optionally, the visual interface is driven by the reasoning result to perform dynamic interaction to assist decision-making, including: Receiving and verifying the reverse control instruction of the specified layer in the visual interface from the mobile terminal; The verified reverse control instruction is converted into a control command for the corresponding source device and sent.

[0011] According to a second aspect of the present disclosure, a mine multi-source signal visual centralized control device is provided, including: The encapsulation unit is used to encapsulate multi-type heterogeneous signals from different source devices into standardized signal models carrying metadata; The mapping unit is used to perform time synchronization and spatial position mapping on the standardized signal model to generate a spatio-temporal fusion situation map on a unified visual interface; The deployment unit is used to deploy the control node using a redundant architecture and implement a signal buffering mechanism to ensure the continuity of visual display when the network or node is abnormal; The analysis unit is used to cooperatively analyze and alarm reason the fused multi-source signal based on an intelligent analysis model, and drive the visual interface to perform dynamic interaction to assist decision-making according to the reasoning result.

[0012] Optionally, the mapping unit is further used for: The signal model with time information is clock-aligned through a precise clock synchronization protocol; According to the spatial coordinate information carried by the signal model, the corresponding visual element is registered to the corresponding position in the unified industrial scene digital model.

[0013] Optionally, the deployment unit is further configured to: Set a master control node and a backup control node, and maintain state synchronization between the two through a state monitoring mechanism; Locally cache key video signals on the edge side, and after network recovery, return the cached signals to the central system according to the time information.

[0014] Optionally, the analysis unit is further configured to: Correlate and identify the same event or state represented by different modal signals using the intelligent analysis model; When the preset alarm linkage rule is met, generate a fusion alarm information.

[0015] Optionally, the method further comprises: An updating unit configured to perform online adaptive updating of parameters of the intelligent analysis model according to localized data of the target industrial scene.

[0016] Optionally, the analysis unit is further configured to: Receive and verify reverse control instructions for a specified layer in the visualization interface from a mobile terminal; Convert the verified reverse control instructions into control commands for the corresponding source device and send them.

[0017] According to a third aspect of the present disclosure, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of the first aspect.

[0018] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to perform the method of the first aspect.

[0019] According to a fifth aspect of the present disclosure, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the method of the first aspect.

[0020] The mining multi-source signal visual centralized control method, device, electronic equipment, and storage medium disclosed herein encapsulate multiple heterogeneous signals from different source devices into standardized signal models carrying metadata. These standardized signal models are then time-synchronized and spatially mapped. A redundant architecture is used to deploy control nodes and a signal caching mechanism is implemented. Furthermore, an intelligent analysis model is used to perform collaborative analysis and alarm reasoning on the fused multi-source signals, driving dynamic interaction through a visual interface. Therefore, this method addresses existing technologies that suffer from severe signal silos, complex and inefficient operation, and insufficient emergency decision support due to the lack of a unified signal processing mechanism for independent operation of various subsystems, inability to align signals in time and space, interruption of visualization during network or node anomalies, and a lack of intelligent collaborative analysis and decision support for multi-source signals. The method achieves unified scheduling of multi-source heterogeneous signals, spatiotemporal fusion visualization, continuous visualization assurance in abnormal scenarios, and intelligent alarm and decision support, thereby improving the integration, reliability, and intelligence level of safety monitoring in high-risk industrial scenarios.

[0021] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0022] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein: Figure 1 A flowchart illustrating a method for visual centralized control of multi-source signals in a mine, provided in an embodiment of this disclosure; Figure 2 This is a schematic diagram of the structure of a mine multi-source signal visual centralized control device provided in an embodiment of the present disclosure; Figure 3 A schematic block diagram of an example electronic device provided for embodiments of this disclosure. Detailed Implementation

[0023] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0024] The following description, with reference to the accompanying drawings, outlines a method and apparatus for visual centralized control of multi-source signals in mines, as well as electronic devices and storage media, representing embodiments of this disclosure.

[0025] Figure 1 This is a flowchart illustrating a method for visual centralized control of multi-source signals in a mine, as provided in an embodiment of this disclosure.

[0026] like Figure 1 As shown, the method includes the following steps: Step 101: Encapsulate the various heterogeneous signals from different source devices into a standardized signal model carrying metadata.

[0027] In the embodiments of this disclosure, to address the technical problem of unified access and scheduling of multi-source heterogeneous signals, this step uniformly encapsulates various heterogeneous signals (including video streams, sensor data streams, control commands, etc.) from different types of source devices to form a standardized signal model (i.e., a signal unit) carrying metadata. This metadata contains key information characterizing the core attributes of the signal, supporting subsequent signal identification, scheduling, and fusion processing. This standardized encapsulation eliminates signal heterogeneity caused by different source devices and protocols, providing a unified access and processing benchmark for all types of signals. As one implementation method, the metadata can be set to information such as signal type, source device identifier, protocol type, refresh rate, security level, and geographical coordinates, supporting dynamic registration of new access devices. Simultaneously, priority tags can be assigned to different types of signals to ensure priority processing of critical signals.

[0028] The embodiments disclosed herein effectively break down signal silos between different source devices, realize unified access and standardized representation of multiple heterogeneous signals, lay the foundation for subsequent unified scheduling and fusion processing of signals, significantly improve the universality and efficiency of multi-source signal access, and reduce the processing complexity caused by signal heterogeneity.

[0029] Step 102: Perform time synchronization and spatial location mapping on the standardized signal model to generate a spatiotemporal fusion situation map on a unified visualization interface.

[0030] In the embodiments of this disclosure, to address the issue of fusion display failure caused by asynchronous time and spatial location of standardized multi-source signals, this step performs time synchronization calibration and spatial location mapping operations on the encapsulated standardized signal models (i.e., signal units). By unifying the time reference and spatial coordinate system, the spatiotemporal differences between different source signals are eliminated, ensuring consistency of various signals in the time dimension and clearly corresponding to actual scene locations in the spatial dimension. This allows for the integration into a spatiotemporally fused global situation map within a unified visualization interface, intuitively presenting the on-site status corresponding to the signals. As one implementation method, timestamp synchronization correction technology can be used to achieve high-precision time alignment of signals, and the signals can be projected onto a 3D scene model or 2D base map according to real geographic coordinates. Specific types of data can also be integrated into the situation map in a visual overlay format.

[0031] Existing technologies suffer from the problem of spatiotemporal misalignment of multi-source signals and the inability to intuitively correlate them. This embodiment achieves spatiotemporal fusion and global visualization of multiple types of signals, making the on-site situation clearly discernible and providing accurate scenario-based information support for status assessment and emergency decision-making in safety monitoring.

[0032] Step 103: Deploy control nodes using a redundant architecture and implement a signal caching mechanism to ensure the continuity of visualization in the event of network or node anomalies.

[0033] In the embodiments of this disclosure, to address the technical problem of easily interrupted visualization and inability to continuously present the on-site status when the network is interrupted or the control node fails, this step deploys the control node using a redundant architecture and establishes a signal caching mechanism. The redundant architecture ensures the continuous availability of the control node, while the signal cache retains key signal data. These two mechanisms work together to ensure that even in the event of network connectivity anomalies or control node failures, the visualization interface can maintain continuous display based on cached data or the normal operation of redundant nodes, avoiding interruptions in on-site status monitoring due to anomalies. As one implementation method, the control node can adopt a primary / backup collaborative deployment mode, and the signal cache can be executed at the edge, temporarily storing key signals and retransmitting the data after the anomaly is resolved.

[0034] This embodiment can avoid the impact of network or node anomalies on visual monitoring, ensure the continuous stability of safety monitoring in high-risk industrial scenarios, improve the reliability and risk resistance of the centralized control platform, and provide a guarantee for uninterrupted status monitoring and emergency response.

[0035] Step 104: Based on the intelligent analysis model, perform collaborative analysis and alarm reasoning on the fused multi-source signals, and drive the visualization interface to perform dynamic interaction based on the reasoning results to assist decision-making.

[0036] In the embodiments of this disclosure, to address the technical problems in the prior art such as lack of deep intelligent analysis after multi-source signal fusion, insufficient alarm accuracy, and inability of the visualization interface to assist decision-making, this step, based on a preset intelligent analysis model, performs collaborative analysis and alarm reasoning on the multi-source standardized signal model after spatiotemporal fusion processing. It mines the correlation logic and abnormal features between signals, and then drives a unified visualization interface to perform corresponding dynamic interactive operations based on the alarm results or status judgment conclusions derived from the reasoning. This provides direct decision support for on-site safety monitoring and emergency response. As one implementation method, the intelligent analysis model can integrate a lightweight reasoning module to achieve multimodal alarm fusion, correlation reasoning, and repetitive alarm suppression. Dynamic interaction may include key area highlighting, local magnification, or status prompts.

[0037] By intelligently interpreting and accurately alarming multi-source fusion signals, and presenting the analysis results intuitively through dynamic interaction of a visual interface, the level of intelligence and alarm reliability of security monitoring is effectively improved, providing accurate and efficient technical support for on-site decision-making and helping to quickly respond to various security risks.

[0038] The mining multi-source signal visual centralized control method disclosed herein encapsulates multiple heterogeneous signals from different source devices into standardized signal models carrying metadata. It performs time synchronization and spatial location mapping on the standardized signal models, deploys control nodes using a redundant architecture and implements a signal caching mechanism, and uses an intelligent analysis model to perform collaborative analysis and alarm reasoning on the fused multi-source signals, driving dynamic interaction through a visual interface. Therefore, it can solve problems in existing technologies such as the lack of a unified signal processing mechanism due to the independent operation of various subsystems, the inability to align signals in time and space, the interruption of visualization display when the network or node is abnormal, the lack of intelligent collaborative analysis and decision support functions for multi-source signals leading to severe signal silos, complex and inefficient operation, and insufficient emergency decision support. It achieves the technical effects of unified scheduling of multi-source heterogeneous signals, spatiotemporal fusion visualization display, continuous visualization assurance in abnormal scenarios, and intelligent alarm and decision support, improving the integration, reliability, and intelligence level of safety monitoring in high-risk industrial scenarios.

[0039] As a specific implementation of this disclosure, based on the basic scheme, the time synchronization and spatial location mapping of the standardized signal model is further defined as follows: clock alignment of the signal model with time information is performed through a precision clock synchronization protocol; and the corresponding visualization elements are registered to the corresponding positions in a unified industrial scene digital model according to the spatial coordinate information carried by the signal model.

[0040] Specifically, PTP (Precision Clock Synchronization Protocol) is adopted as the core clock synchronization mechanism. Nanosecond-level clock alignment is performed on the time information carried by the standardized signal model (i.e., signal unit). A hardware marking module is embedded at the signal acquisition end to write the precise timestamp of the signal generation moment into the metadata. Then, the protocol's built-in calibration algorithm eliminates clock drift and transmission delays from different source devices, ensuring strict consistency of various signals such as video streams and sensor data streams in the time dimension. For spatial location mapping, the geographic coordinate information recorded in the signal model metadata (such as tunnel number, equipment installation latitude and longitude, and area division markers) is extracted. The corresponding visual elements of the signal (such as camera monitoring field outline, sensor status indicator lights, and equipment operation icons) are registered to the corresponding spatial points in a pre-constructed unified industrial scene digital model (such as a 3D mine model or a 2D GIS geographic base map) according to a 1:1 real-world scale and orientation, enabling precise spatial binding between the visual elements and the actual equipment and work area on site.

[0041] High-precision time synchronization of multi-source signals was achieved through the PTP protocol. Combined with the accurate mapping of geographic coordinates and industrial scene digital models, the temporal consistency and spatial authenticity of the spatiotemporal fusion situation map were ensured. This allowed monitoring personnel to intuitively obtain on-site status information from the same spatiotemporal source, effectively improving the accuracy of status assessment and providing a reliable spatiotemporal reference for emergency response decisions.

[0042] As a specific implementation of this disclosure, based on the basic scheme, the deployment of control nodes with a redundant architecture and the implementation of a signal caching mechanism are further defined, including: setting up a master control node and a backup control node, and maintaining state synchronization between the two through a state monitoring mechanism; caching key video signals locally at the edge, and transmitting the cached signals back to the central system according to time information after network recovery.

[0043] Specifically, the control nodes are deployed in a dual-active redundant architecture with a primary control node and a backup control node. A high-frequency status monitoring mechanism is established between the two, using heartbeat detection at ≤500ms intervals to exchange operational status data in real time. The primary control node will synchronize key information such as signal scheduling instructions, device connection status, and visualized configuration parameters to the backup control node in real time, ensuring that the backup node always maintains the same operational status as the primary control node and can immediately take over the work when the primary control node fails. At the same time, local storage modules are configured on the edge nodes to perform local caching operations on standardized key video signals (such as video streams from core areas such as underground mining faces, gas monitoring points, and belt conveyor lines). The video data is segmented and stored according to timestamp order and indexed. The caching duration is set to the most recent 30 minutes of key data. When the network is restored after an interruption, the edge nodes will automatically establish a connection with the central system and, based on the timestamp information of the cached data, transmit the cached key video signals back to the central storage system in chronological order to complete the data restoration.

[0044] Seamless failover is achieved through high-frequency status synchronization of primary and backup control nodes. Combined with local caching and accurate backhaul of key video at the edge, the loss of critical monitoring data is avoided when the network or node is abnormal, and the continuous stability of the visualization display is guaranteed. This significantly improves the fault resistance and data integrity of the centralized control platform, providing reliable support for uninterrupted monitoring in high-risk industrial scenarios.

[0045] As a specific implementation of this disclosure, based on the basic scheme, the method of performing collaborative analysis and alarm reasoning on the fused multi-source signals based on the intelligent analysis model is further defined as follows: using the intelligent analysis model to identify the same event or state represented by different modal signals; and generating fused alarm information when the alarm linkage rules are found to be in accordance with the preset alarm linkage rules.

[0046] Specifically, the intelligent analysis model employs a lightweight AI inference module deployed on edge nodes, pre-loaded with a multimodal signal association and recognition algorithm optimized for high-risk industrial scenarios. This algorithm can extract event features and state parameters from different modal signals such as video streams and sensor data streams, and perform cross-modal association matching on multi-source heterogeneous signals representing the same on-site event or equipment state. For example, it can perform association verification on the image features of "person falling to the ground" in video signals, the sensor data of "abnormal heart rate" reported by the vital signs monitoring system, and the location information of "staying in a fixed area for more than a preset time" fed back by the personnel positioning system to confirm whether they point to the same safety event. Meanwhile, the platform has a built-in configurable alarm linkage rule library. The rule library has preset alarm levels and trigger conditions corresponding to different event combinations. When the event features identified by the intelligent analysis model completely match a preset rule in the library (such as when the video detects "smoke and flame" and the temperature sensor reading exceeds the threshold and the smoke concentration sensor data is abnormal, the key information of each modal signal (including event occurrence time, spatial coordinates, signal source device ID, and core parameter values) is automatically integrated to generate structured fused alarm information. In the process of generation, correlation reasoning and repeated alarm suppression logic are executed to avoid multiple repeated alarms caused by the same event.

[0047] By associating and identifying multimodal signals and linking alarms according to preset rules, the accuracy and completeness of alarm information are greatly improved, effectively avoiding the problems of false alarms and missed alarms caused by single-modal signals. At the same time, by integrating key information through alarm fusion, redundant alarm interference is reduced, enabling monitoring personnel to quickly and accurately grasp the on-site security situation and providing efficient and reliable decision-making basis for emergency response.

[0048] As a specific implementation of this disclosure, based on the basic solution, the embodiment of this disclosure further includes: online adaptive updating of the parameters of the intelligent analysis model according to localized data of the target industrial scenario.

[0049] Specifically, the intelligent analysis model (i.e., the lightweight AI inference module deployed on the edge node) reserves an online adaptive update interface. First, it collects localized data of the target industrial scenario through the platform data acquisition module, including equipment operation history data specific to the scenario (such as vibration threshold of a specific model of belt conveyor, drift data of local gas sensors), geological environmental parameters (such as coal seam thickness and geological structure distribution in the mining area), historical safety event cases (including multimodal signal data when alarms are triggered, false alarm / missed alarm correction records), and on-site operation specification data. After denoising and normalizing the collected localized data, effective training samples are selected and key features are labeled. Based on the incremental training algorithm, the model can fine-tune the model parameters online by utilizing the idle computing power of edge nodes without interrupting the existing monitoring service. The feature extraction weights and decision boundaries of the model are iteratively optimized by gradient descent. After each parameter update, offline verification is automatically performed (accuracy and recall are calculated using local historical labeled data). When the verification indicators meet the preset threshold (such as alarm accuracy ≥ 95%), the updated parameters are automatically overwritten and take effect. At the same time, parameter update logs (including update time, data source, and parameter change range) are retained for traceability.

[0050] By integrating localized data from the target industrial scenario for online adaptive model updates, the intelligent analysis model can accurately adapt to the unique environmental and equipment characteristics of different scenarios, significantly reducing the probability of false alarms and missed alarms caused by scenario differences. Furthermore, model optimization can be completed without interrupting system operation, ensuring the continuity of monitoring services and further improving the reliability and relevance of intelligent alarms and event recognition.

[0051] As a specific implementation of this disclosure, based on the basic solution, the method of driving the visualization interface to perform dynamic interaction based on the reasoning result to assist decision-making is further defined as follows: receiving and verifying the reverse control command from the mobile terminal to a specified layer in the visualization interface; converting the verified reverse control command into a control command for the corresponding source device and sending it.

[0052] Specifically, after a mobile terminal (APP or Web terminal) initiates a reverse control command on a specified layer in the visualization interface (such as retrieving specific monitoring footage, adjusting the PTZ camera's perspective, starting or stopping the target device, etc.), the platform first initiates a three-level security authentication process: verifying the validity of the initiator's account password, verifying the legality of the dynamic token (a one-time verification code generated based on a time synchronization mechanism), and checking whether the IP address or physical location of the operating terminal is within the preset electronic fence of the operating area (such as the dedicated IP segment of the dispatch room or the geographical range of a designated office area). Only after all three levels of authentication are passed will the platform receive the reverse control command and perform format verification. Subsequently, the platform uses its built-in protocol conversion module to convert the verified reverse control command into a standardized control command according to the communication protocol supported by the target source device, clearly specifying the command type, target device ID, operation parameters, and other core information. The control command is sent to the corresponding source device through an independent transmission channel isolated from the video stream. At the same time, the platform automatically generates a digital work order, fully recording the operator's identity information, command initiation time, specific command content, and the response status of the controlled device, forming a fully traceable operation record.

[0053] The three-level security authentication mechanism ensures the operational security of reverse control commands. Combined with protocol conversion, it enables compatible control of different types of source devices. The entire operation is traceable, which meets the requirements of safety production audit. It effectively improves the reliability and compliance of remote collaborative control, allowing managers to safely and accurately remotely control related equipment, and assists in efficient emergency response and daily monitoring management.

[0054] It should be noted that the embodiments of this disclosure may include multiple steps. For ease of description, these steps are numbered, but these numbers are not a limitation on the execution time slots or execution order between the steps; these steps can be implemented in any order, and the embodiments of this disclosure do not limit this.

[0055] Corresponding to the aforementioned method for visual centralized control of multi-source signals in mines, this disclosure also proposes a device for visual centralized control of multi-source signals in mines. Since the device embodiments of this disclosure correspond to the method embodiments described above, details not disclosed in the device embodiments can be referred to the method embodiments described above, and will not be repeated here.

[0056] Figure 2 This is a schematic diagram of the structure of a multi-source signal visual centralized control device for mines provided in an embodiment of this disclosure, as shown below. Figure 2 As shown, it includes: The encapsulation unit 21 is used to encapsulate multiple heterogeneous signals from different source devices into a standardized signal model carrying metadata; Mapping unit 22 is used to perform time synchronization and spatial location mapping on the standardized signal model to generate a spatiotemporal fusion situation map on a unified visualization interface. Deployment unit 23 is used to deploy control nodes with a redundant architecture and implement a signal caching mechanism to ensure the continuity of visualization in the event of network or node anomalies. Analysis unit 24 is used to perform collaborative analysis and alarm reasoning on the fused multi-source signals based on the intelligent analysis model, and drive the visualization interface to perform dynamic interaction based on the reasoning results to assist decision-making.

[0057] The mining multi-source signal visual centralized control device disclosed herein encapsulates various heterogeneous signals from different source devices into standardized signal models carrying metadata. It performs time synchronization and spatial location mapping on the standardized signal models, deploys control nodes using a redundant architecture, implements a signal caching mechanism, and uses an intelligent analysis model to perform collaborative analysis and alarm reasoning on the fused multi-source signals, driving dynamic interaction through a visual interface. Therefore, it can solve problems in existing technologies such as the lack of a unified signal processing mechanism due to the independent operation of various subsystems, the inability to align signals in time and space, the interruption of visualization display when the network or node is abnormal, the lack of intelligent collaborative analysis and decision support functions for multi-source signals leading to severe signal silos, complex and inefficient operation, and insufficient emergency decision support. It achieves the technical effects of unified scheduling of multi-source heterogeneous signals, spatiotemporal fusion visualization display, continuous visualization assurance in abnormal scenarios, and intelligent alarm and decision support, improving the integration, reliability, and intelligence level of safety monitoring in high-risk industrial scenarios.

[0058] Furthermore, in one possible implementation of this embodiment, the mapping unit 22 is also used for: Clock alignment of signal models with time information is performed using a precision clock synchronization protocol; Based on the spatial coordinate information carried by the signal model, its corresponding visualization elements are registered to the corresponding positions in the unified industrial scene digital model.

[0059] Furthermore, in one possible implementation of this embodiment, the deployment unit 23 is also used for: Set up a master control node and a backup control node, and maintain their state synchronization through a status monitoring mechanism; Key video signals are locally cached at the edge and then transmitted back to the central system based on time information after the network is restored.

[0060] Furthermore, in one possible implementation of this embodiment, the analysis unit 24 is also used for: The intelligent analysis model is used to identify the correlation between the same event or state represented by different modal signals; When a preset alarm linkage rule is identified, a fused alarm message is generated.

[0061] Furthermore, in one possible implementation of this embodiment, such as Figure 2 As shown, it also includes: The update unit 25 is used to perform online adaptive updates of the parameters of the intelligent analysis model based on the localized data of the target industrial scenario.

[0062] Furthermore, in one possible implementation of this embodiment, the analysis unit 24 is also used for: Receive and verify reverse control commands from the mobile terminal for a specified layer in the visual interface; The verified reverse control commands are converted into control commands for the corresponding source devices and sent.

[0063] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of this embodiment, and the principle is the same, so it is not limited in this embodiment.

[0064] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0065] Figure 3 A schematic block diagram of an example electronic device 300 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0066] like Figure 3 As shown, the electronic device 300 includes a computing unit 301, which can perform various appropriate actions and processes based on a computer program stored in ROM (Read-Only Memory) 302 or a computer program loaded from storage unit 308 into RAM (Random Access Memory) 303. The RAM 303 may also store various programs and data required for the operation of the electronic device 300. The computing unit 301, ROM 302, and RAM 303 are interconnected via a bus 304. An I / O (Input / Output) interface 305 is also connected to the bus 304.

[0067] Multiple components in electronic device 300 are connected to I / O interface 305, including: input unit 306, such as keyboard, mouse, etc.; output unit 307, such as various types of displays, speakers, etc.; storage unit 308, such as disk, optical disk, etc.; and communication unit 309, such as network card, modem, wireless transceiver, etc. Communication unit 309 allows electronic device 300 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0068] The computing unit 301 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, CPUs (Central Processing Units), GPUs (Graphics Processing Units), various special-purpose AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, DSPs (Digital Signal Processors), and any suitable processor, controller, microcontroller, etc. The computing unit 301 performs the various methods and processes described above, such as the mine multi-source signal visual centralized control method. For example, in some embodiments, the mine multi-source signal visual centralized control method can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 300 via ROM 302 and / or communication unit 309. When the computer program is loaded into RAM 303 and executed by the computing unit 301, one or more steps of the methods described above can be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to perform the aforementioned mine multi-source signal visual centralized control method by any other suitable means (e.g., by means of firmware).

[0069] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), SOCs (System-on-Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0070] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0071] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, RAM, ROM, EPROM (Electrically Programmable Read-Only Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0072] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0073] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include LANs (Local Area Networks), WANs (Wide Area Networks), the Internet, and blockchain networks.

[0074] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service system that addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0075] It's important to note that artificial intelligence (AI) is the study of enabling computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). It encompasses both hardware and software technologies. AI hardware technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily include computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graph technologies.

[0076] The various numerical designations such as "first," "second," etc., used in this disclosure are merely for ease of description and are not intended to limit the scope of the embodiments of this disclosure, nor do they indicate a sequential order.

[0077] At least one of the features described in this disclosure can also be described as one or more, and multiple features can be two, three, four or more, and this disclosure does not impose any limitations. In the embodiments of this disclosure, for a technical feature, the technical features in that technical feature are distinguished by "first", "second", "third", "A", "B", "C" and "D", etc., and there is no sequential order or size order among the technical features described by "first", "second", "third", "A", "B", "C" and "D".

[0078] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0079] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A mine multi-source signal visual centralized control method, characterized in that, The method comprises the following steps: standardizing a plurality of heterogeneous signals from different source devices into a standardized signal model carrying metadata; time-synchronizing and spatially mapping the standardized signal model to generate a spatio-temporal fusion situation map on a unified visualization interface; deploying control nodes in a redundant architecture and implementing a signal caching mechanism to ensure continuity of visualization display in the event of network or node abnormalities; cooperatively analyzing and alarm reasoning the fused multi-source signals based on an intelligent analysis model, and driving the visualization interface to dynamically interact based on the reasoning results to assist decision-making.

2. The method of claim 1, wherein, The time-synchronizing and spatially mapping the standardized signal model comprises: clock aligning the signal model with time information through a precise clock synchronization protocol; registering the corresponding visualization elements of the signal model to the corresponding positions in the unified industrial scene digital model according to the spatial coordinate information carried by the signal model.

3. The method of claim 1, wherein, The deploying control nodes in a redundant architecture and implementing a signal caching mechanism comprises: setting up a master control node and a backup control node, and maintaining state synchronization between the two through a state monitoring mechanism; locally caching critical video signals on the edge side, and returning the cached signals to the central system according to the time information after the network recovers.

4. The method of claim 1, wherein, The cooperatively analyzing and alarm reasoning the fused multi-source signals based on an intelligent analysis model comprises: correlation identification of the same event or state represented by different modal signals using the intelligent analysis model; generating a fusion alarm information when the alarm linkage rule is met.

5. The method of claim 1, wherein, Further comprising: online adaptive updating the parameters of the intelligent analysis model according to the localized data of the target industrial scene.

6. The method of claim 1, wherein, The driving the visualization interface to dynamically interact based on the reasoning results to assist decision-making comprises: receiving and verifying the reverse control instructions of the specified layer in the visualization interface from the mobile terminal; converting the verified reverse control instructions into control commands for the corresponding source devices and sending them.

7. A mine multi-source signal visual centralized control device, characterized in that, The method comprises the following steps: a packaging unit for packaging a plurality of heterogeneous signals from different source devices into a standardized signal model carrying metadata, and hot-plugging and uniformly managing the signal model; a mapping unit for time-synchronizing and spatially mapping the standardized signal model to generate a spatio-temporal fusion situation map on a unified visualization interface; a deployment unit for deploying control nodes in a redundant architecture and implementing a signal caching mechanism to ensure continuity of visualization display in the event of network or node abnormalities; an analysis unit for cooperatively analyzing and alarm reasoning the fused multi-source signals based on an intelligent analysis model, and driving the visualization interface to dynamically interact based on the reasoning results to assist decision-making.

8. An electronic device, comprising: The method comprises the following steps: at least one processor; and a memory connected in communication with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-6.

9. A non-transitory computer-readable storage medium having stored thereon computer instructions, wherein, The computer instructions are used to make the computer perform the method of any one of claims 1-6.

10. A computer program product, characterised in that, comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-6.

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