Method and system for estimating output residual load capacity of intrinsic safety type direct-current power supply

Abstract

The invention relates to a method and a system for estimating the output residual load capacity of an intrinsic safety type direct-current power supply, and belongs to the technical field of intrinsic safety power supply of mining safety monitoring systems. Aiming at the problems of installation blindness and low maintenance efficiency caused by the fact that the loading capacity and the power supply distance of an intrinsic safety power supply cannot be predicted in the prior art, the method comprises the following steps: acquiring operation parameters of an underground intrinsic safety power supply and a sensor, and combining cable parameters with a correction coefficient optimized by a simulation platform; and inputting a power supply model established based on a circuit law for calculation. The core of the technical scheme is that the residual load capacity and the maximum power supply distance of the power supply are accurately estimated by using the model. The technical effects are that intelligent pre-estimation and early warning of supply and demand matching of the power supply sensor are realized, a theoretical basis can be provided for equipment installation without increasing hardware cost, the system maintenance efficiency and the operation reliability are obviously improved, and the labor intensity of workers is reduced.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of intrinsic safety power supply of mine safety monitoring system, and relates to an intrinsic safety DC power output residual load capacity estimation method and system. BACKGROUND

[0002] At present, in the actual operation and maintenance of the coal mine safety monitoring system, the intrinsic safety DC power supplies power for various sensors in the mine. These power supplies and sensors generally have a state monitoring function, which can upload their running state, working voltage, current and other parameters to the substation or central station through the system network, providing a preliminary data basis for intelligent management. However, in the key aspects of power supply safety and planning, the existing technology has significant deficiencies, which are embodied in the following two aspects: First, in terms of system maintenance and fault troubleshooting, the efficiency is low and the blindness is great. When an abnormality occurs in the power supply of a certain road in the mine, causing the sensor to drop out, the field maintenance personnel cannot quickly locate the root cause of the fault. The fault may be caused by insufficient output capacity of the power supply, excessive voltage drop caused by too long or damaged power supply cable, or sensor failure. Due to the lack of effective analysis tools, the maintenance personnel can only adopt the traditional method of replacing and troubleshooting in sections, which is a "blind elephant" type of troubleshooting method that not only consumes time and effort, but also leaves a serious safety hazard in the fault area during the period.

[0003] Second, in terms of system expansion and device installation, there is a lack of forward-looking theoretical guidance and data support. If a sensor needs to be added to the existing system, the staff cannot accurately answer two key questions: 1. Does the intrinsic safety DC power supply for this area have enough residual load capacity to drive the new device? 2. What is the maximum allowable power supply distance from the power supply to the installation location of the new sensor? Currently, these decisions are mostly estimated based on personal experience, lacking accurate calculation basis. This blindness is extremely likely to lead to two consequences: one is too conservative, wasting the actual load capacity of the power supply and the power supply distance of the cable, limiting the expansion of the system; the other is too aggressive, causing the power supply to be in a long-term overload edge after adding the new device or the unending sensor to work abnormally due to insufficient power supply voltage, thereby increasing the instability of the system.

[0004] The root cause of the problem is that the existing technology fails to effectively integrate and deeply utilize the dispersed power supply state parameters, sensor power consumption parameters and cable characteristic parameters in the system. Although the system collects data, it lacks an accurate power supply circuit model to convert these data into quantitative knowledge of the power supply load capacity and power supply distance. In other words, the existing technology stays at the "presentation" level of data, and does not develop to the "estimation" level of capacity.

[0005] Therefore, there is an urgent need in this field for a new technical solution that can fully utilize the existing data resources of the monitoring system under the premise of increasing hardware costs, and achieve accurate and intelligent prediction of the remaining load capacity and maximum power supply distance by establishing a scientific power supply model. This would fundamentally solve the aforementioned problems in maintenance and expansion, and provide key technical support for the intelligent and precise operation and maintenance of coal mine safety monitoring systems. Summary of the Invention

[0006] In view of this, the purpose of the present invention is to provide a method and system for predicting the residual load capacity of an intrinsically safe DC power supply output.

[0007] To achieve the above objectives, the present invention provides the following technical solution: A method for estimating the residual load capacity of an intrinsically safe DC power supply, the method comprising the following steps: Step S101: Real-time acquisition of operating parameters, including the output voltage of the intrinsically safe DC power supply in the well. and maximum output current and the input voltage of at least one intrinsically safe sensor that has been connected. Rated power and work efficiency ; Step S102: Obtain configuration parameters, including the resistivity per unit length of the power supply cable. And the power load capacity correction coefficients obtained through simulation testing platform training to compensate for line losses and model errors. k ; Step S103: Input the operating parameters and the configuration parameters into the pre-established intrinsically safe power supply load prediction model; the intrinsically safe power supply load prediction model is constructed based on Kirchhoff's voltage law and is used to characterize the voltage and current relationship in the circuit composed of the intrinsically safe DC power supply, power supply cable and intrinsically safe sensor. Step S104: Based on the intrinsically safe power supply load prediction model, calculate the remaining load capacity of the intrinsically safe DC power supply under the current load. And the maximum power supply distance capable of normally powering the newly added intrinsically safe sensor. .

[0008] Furthermore, in step S103, the intrinsically safe power supply load prediction model satisfies the following voltage relationship:

[0009] in, This represents the current flowing through the power supply cable. Let be the one-way equivalent resistance of the power supply cable, and ,L This represents the current cable length.

[0010] Furthermore, the input voltage of the intrinsically safe sensor Based on its power and efficiency characteristics, it specifically satisfies the following sensor input voltage relationship: .

[0011] Furthermore, the calculation of the maximum power supply distance in step S104... Specifically, it includes: Combine the voltage relationship with the sensor input voltage relationship, and use the minimum operating voltage of the intrinsically safe sensor. Given the constraints, solve for the condition that guarantees Under the premise that the power supply cable can be subjected to the maximum equivalent resistance ; Based on the maximum equivalent resistance With resistivity per unit length Through formula The maximum power supply distance was calculated. .

[0012] Furthermore, the minimum operating voltage It is 9V.

[0013] Furthermore, the calculation of remaining load capacity in step S104 Specifically, this is achieved through the following formula:

[0014] Furthermore, the following constraints must be met during the calculation: This is to ensure that the power supply has remaining load-carrying capacity.

[0015] Furthermore, the method also includes: Step S105: Visually display the remaining load capacity in the system interface. and maximum power supply distance The calculation results; Step S106: When determining the remaining load capacity Below a preset threshold, or calculated based on the parameters of the proposed new sensor. When the voltage drops below its minimum operating voltage, a warning signal is generated and issued.

[0016] A prediction system for implementing the method, the system comprising: The parameter acquisition module is configured to acquire the operating parameters of the intrinsically safe DC power supply and the intrinsically safe sensor in real time through the monitoring system network; The parameter input module is configured to receive the resistance coefficient of the power supply cable input by the user. and the correction coefficient k ; The data processing module, which incorporates the intrinsically safe power supply load prediction model, is communicatively connected to the parameter acquisition module and the parameter input module. It receives the operating parameters and configuration parameters and performs calculations to output the remaining load capacity. and the maximum power supply distance ; The results display and early warning module is communicatively connected to the data processing module and is used to display the calculation results and issue an early warning when a mismatch between power supply and sensor demand is detected. The parameter acquisition module, parameter input module, data processing module, and result display and early warning module work together to complete the prediction process from data acquisition to result output.

[0017] Furthermore, the parameter acquisition module obtains the operating parameters from the substations or central station of the coal mine safety monitoring system.

[0018] Furthermore, the constraints used by the data processing module when performing calculations include: and .

[0019] The beneficial effects of this invention are as follows: (1) The core effect of this invention lies in achieving a leap from "empirical estimation" to "model-driven". This is achieved by establishing an accurate power supply model based on Kirchhoff's voltage law and introducing correction coefficients optimized by the simulation platform. k This model can accurately depict the dynamic relationships between power supplies, cables, and sensors. This enables the assessment of remaining load capacity. and maximum power supply distance The forecasting has changed from qualitative judgment to quantitative calculation, and the results have a clear theoretical basis, which greatly improves the scientificity and accuracy of the planning and fundamentally avoids system failures or resource waste caused by estimation errors.

[0020] (2) This invention brings about a qualitative leap in operation and maintenance efficiency and a significant reduction in total life cycle cost. Specifically, it is reflected in: Improved maintenance efficiency: When a power supply anomaly occurs, the system can quickly calculate key parameters to help maintenance personnel accurately locate whether the fault originates from the power supply, cable, or load. This transforms the traditional "blind troubleshooting" into "precise location," greatly shortening the troubleshooting time and reducing the workload of maintenance personnel.

[0021] Significant economic benefits: This method requires no additional hardware sensors or modifications to existing circuits; it achieves "zero-cost" efficiency gains solely through software algorithms that mine and utilize existing system data. Simultaneously, accurate capacity forecasting avoids the blind expansion or descent of power supply equipment, optimizing asset allocation and saving on fixed asset investment.

[0022] Proactive decision support: When adding sensors to the system, simulations can be performed in advance to provide quantitative decision-making basis for equipment selection and installation location planning, realizing the transformation from "post-event remediation" to "pre-event planning".

[0023] (3) This invention significantly enhances the reliability and safety of power supply for coal mine safety monitoring systems. Through real-time or pre-emptive prediction and early warning, it can effectively prevent unexpected restarts or power outages caused by power overload, ensuring the uninterrupted operation of the monitoring system 24 / 7. At the same time, it ensures that the working voltage at the sensor terminal is always higher than its minimum requirement (e.g., 9V), eliminating the risk of data distortion or equipment offline caused by insufficient voltage from the source of power supply, and providing a deeper level of technical protection for safe production underground.

[0024] (4) This invention provides a key "data-driven" foundational capability for intelligent mines. It transforms isolated equipment status parameters into system-level insights with guiding significance, driving the intelligent upgrade of power supply management from passive response to proactive early warning. For example... Figure 2 The integrated forecasting system shown perfectly meets the needs of intelligent mine construction for system integration, data fusion, and intelligent decision-making.

[0025] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0026] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein: Figure 1 An equivalent circuit model for an intrinsically safe power supply remotely powering a sensor; Figure 2 A schematic diagram illustrating a method for estimating the residual load capacity of an intrinsically safe DC power supply. Figure 3 This is a system architecture diagram of the present invention. Detailed Implementation

[0027] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0028] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the invention. To better illustrate the embodiments of the invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0029] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "front," and "rear" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present invention. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0030] Example 1: Dynamic Prediction Process Based on Power Supply Model Please see Figure 1 and Figure 2 This embodiment elaborates on the dynamic execution flow of the core method of the present invention, focusing on demonstrating how to use real-time data for calculation and decision-making.

[0031] Step 1: System Initialization and Parameter Presetting Before the system is put into use, initial configuration is required. This includes: Equipment parameter library construction: Pre-store standard parameters of various intrinsically safe sensors in the system database, such as rated power. and typical work efficiency .

[0032] Cable parameter entry: Enter the resistivity per unit length of commonly used power supply cables in mines. .

[0033] Calibration of the correction coefficient: This is crucial for ensuring the accuracy of this invention. A test platform simulating the downhole environment is built on the ground. Combined tests are conducted using power supplies, cables, and sensors of different specifications. Through data fitting and optimization algorithms, a high-precision power supply load capacity correction coefficient is trained and determined. k This coefficient is used to compensate for losses in actual circuits, such as contact resistance and temperature drift, which are not reflected in the ideal model. k Values ​​are pre-loaded into the system.

[0034] Step 2: Real-time Data Acquisition and Input During system operation, data acquisition is performed automatically and continuously through the existing data network of the coal mine safety monitoring system (such as industrial Ethernet, CAN bus, etc.). Real-time output voltage collected from intrinsically safe DC power supply. and the maximum output current specified on its nameplate or in the agreement. .

[0035] Data collected from the connected sensors: their actual input voltage. .

[0036] Meanwhile, when users plan to add sensors or adjust wiring, they can input or select the model of the target sensor through the human-machine interface (the system will automatically call its parameter from the parameter library). and ) and the type of cable to be used (corresponding to its ).

[0037] Step 3: Power Supply Model Calculation and Analysis The data processing module calls a pre-established intrinsically safe power supply load prediction model for calculation. The theoretical basis of this model is... Figure 1 The equivalent circuit shown.

[0038] The calculation process is as follows: 1. Establish the voltage equation: According to Kirchhoff's voltage law, for the entire circuit, we have: in, For loop current, For single-pass cable resistance ( , L (Current cable length).

[0039] 2. Correlation of sensor terminal characteristics: The relationship between voltage, current, and power at the sensor terminal is as follows:

[0040] 3. Solve for key parameters simultaneously: Combine the above two equations, and use the sensor's lowest operating voltage (e.g., ...). Given the constraint of ≥9V, the maximum cable resistance that the system can support under the current configuration can be solved inversely. And then according to Calculate the maximum power supply distance .

[0041] 4. Calculate remaining load capacity: the remaining load capacity of the power supply. It is given by the following formula:

[0042] This calculation must satisfy the constraints. This is to ensure that there is remaining power capacity.

[0043] Step 4: Results Visualization and Intelligent Early Warning The calculation results will be displayed intuitively on the system monitoring interface in the form of numbers, percentage progress bars, or analog dashboards. More importantly, the system has built-in intelligent judgment logic: Warning triggered: If the calculated Negative values ​​or values ​​below the safety threshold, or values ​​calculated by newly added sensors. If the voltage drops below 9V, the system will immediately trigger a warning.

[0044] Warning format: Warning information is displayed on the interface in the form of a highlighted color, flashing icon or pop-up window, and can be linked to sound and light alarms or pushed to the mobile terminal of maintenance personnel to achieve proactive safety protection.

[0045] Example 2: Architecture and Collaborative Operation of an Integrated Prediction System The system architecture is as follows Figure 3 As shown.

[0046] This system, as an advanced application module of the coal mine safety monitoring system, mainly includes the following collaborative functional modules: Parameter Acquisition Module: This module acts as the system's "sensory nerves." Deeply integrated into the existing monitoring network, it interacts with the intrinsically safe power supply and sensors underground via standard industrial communication protocols such as OPC UA and Modbus TCP to obtain operating parameters. , , Automatic, real-time, and seamless data collection ensures the accuracy and timeliness of the data source.

[0047] Parameter Input Module: This module serves as the system's "configuration center." It provides a graphical user interface (such as a web configuration page) that allows administrators to manage and configure static parameters, including maintaining sensor parameter libraries, cable parameter libraries, and injecting critical correction coefficients. k This module ensures the flexibility and configurability of the system applications.

[0048] Data Processing Module: This module is the "brain" of the system. It is a high-performance embedded computing unit or server software module that internally embeds the intrinsically safe power supply load prediction model and all its calculation logic. It receives data from modules 101 and 102, performs model solving, and strictly enforces all constraints (such as...). >9V). The computing power of this module is the core of achieving accurate predictions.

[0049] Results Display and Early Warning Module: This module serves as the system's "decision output interface." It is typically presented on a large screen in the monitoring center or on an engineer's workstation screen. This module not only dynamically displays... and It can also display historical changes with trend charts, and immediately initiate a multi-level early warning process when the data processing module issues an early warning command, ensuring that information is perceived and processed in a timely manner.

[0050] System workflow: The parameter acquisition module and parameter input module converge the data stream to the data processing module. After completing the calculation, the data processing module sends the results and instructions to the result display and early warning module. The entire process forms a closed loop, realizing automation from data perception to intelligent decision-making, and providing a powerful intelligent tool for mine safety monitoring.

[0051] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for estimating the residual load capacity of an intrinsically safe DC power supply, characterized in that: The method includes the following steps: Step S101: Real-time acquisition of operating parameters, including the output voltage of the intrinsically safe DC power supply in the well. and maximum output current and the input voltage of at least one intrinsically safe sensor that has been connected. Rated power and work efficiency ; Step S102: Obtain configuration parameters, including the resistivity per unit length of the power supply cable. And the power load capacity correction coefficients obtained through simulation testing platform training to compensate for line losses and model errors. k ; Step S103: Input the operating parameters and the configuration parameters into the pre-established intrinsically safe power supply load prediction model; the intrinsically safe power supply load prediction model is constructed based on Kirchhoff's voltage law and is used to characterize the voltage and current relationship in the circuit composed of the intrinsically safe DC power supply, power supply cable and intrinsically safe sensor. Step S104: Based on the intrinsically safe power supply load prediction model, calculate the remaining load capacity of the intrinsically safe DC power supply under the current load. And the maximum power supply distance capable of normally powering the newly added intrinsically safe sensor. .

2. The method for estimating the residual load capacity of an intrinsically safe DC power supply according to claim 1, characterized in that: In step S103, the intrinsically safe power supply load prediction model satisfies the following voltage relationship: in, This represents the current flowing through the power supply cable. Let be the one-way equivalent resistance of the power supply cable, and , L This represents the current cable length.

3. The method for estimating the residual load capacity of an intrinsically safe DC power supply according to claim 2, characterized in that: The input voltage of the intrinsically safe sensor Based on its power and efficiency characteristics, it specifically satisfies the following sensor input voltage relationship: 。 4. The method for estimating the residual load capacity of an intrinsically safe DC power supply according to claim 3, characterized in that: The calculation of the maximum power supply distance in step S104 Specifically, it includes: Combine the voltage relationship with the sensor input voltage relationship, and use the minimum operating voltage of the intrinsically safe sensor. Given the constraints, solve for the condition that guarantees Under the premise that the power supply cable can be subjected to the maximum equivalent resistance ; Based on the maximum equivalent resistance With resistivity per unit length Through formula The maximum power supply distance was calculated. .

5. The method for estimating the residual load capacity of an intrinsically safe DC power supply according to claim 4, characterized in that: The minimum operating voltage It is 9V.

6. The method for estimating the residual load capacity of an intrinsically safe DC power supply according to claim 2, characterized in that: The calculation of remaining load capacity in step S104 Specifically, this is achieved through the following formula: Furthermore, the following constraints must be met during the calculation: This is to ensure that the power supply has remaining load-carrying capacity.

7. The method for estimating the residual load capacity of an intrinsically safe DC power supply according to claim 1, characterized in that: The method further includes: Step S105: Visually display the remaining load capacity in the system interface. and maximum power supply distance The calculation results; Step S106: When determining the remaining load capacity Below a preset threshold, or calculated based on the parameters of the proposed new sensor. When the voltage drops below its minimum operating voltage, a warning signal is generated and issued.

8. A prediction system for implementing the method according to any one of claims 1 to 7, characterized in that: The system includes: The parameter acquisition module is configured to acquire the operating parameters of the intrinsically safe DC power supply and the intrinsically safe sensor in real time through the monitoring system network; The parameter input module is configured to receive the resistance coefficient of the power supply cable input by the user. and the correction coefficient k ; The data processing module, which incorporates the intrinsically safe power supply load prediction model, is communicatively connected to the parameter acquisition module and the parameter input module. It receives the operating parameters and configuration parameters and performs calculations to output the remaining load capacity. and the maximum power supply distance ; The results display and early warning module is communicatively connected to the data processing module and is used to display the calculation results and issue an early warning when a mismatch between power supply and sensor demand is detected. The parameter acquisition module, parameter input module, data processing module, and result display and early warning module work together to complete the prediction process from data acquisition to result output.

9. The prediction system according to claim 8, characterized in that: The parameter acquisition module obtains the operating parameters from the substations or central station of the coal mine safety monitoring system; the constraints used by the data processing module when performing calculations include: and .

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