Water leakage point positioning method and device based on resistance gradient calculation

Abstract

The invention provides a water leakage point positioning method and device based on resistance gradient calculation, and the method comprises the steps: obtaining a total resistance value and a tail end resistance value of a water leakage induction rope, and reading a preset resistivity parameter per unit length; calculating the distance of a water leakage point based on the total resistance value, the tail end resistance value and the resistivity parameter per unit length; according to the mapping relation between the length of the induction rope and the physical position established in the installation and debugging stage, the distance of the water leakage point is converted into the physical position described by corresponding 3D coordinates or characters; the physical position information is combined with real-time monitoring data to generate alarm prompt information containing a specific water leakage point location, and the alarm prompt information is output to a monitoring interface, so that accurate positioning of the water leakage point can be realized, the fault response time is remarkably shortened, and through a multi-thread data acquisition and dynamic alarm judgment mechanism, the real-time performance and the alarm accuracy of the system are improved; and the false alarm and repeated alarm frequency is reduced.

Description

Technical Field

[0001] This invention relates to the field of power plant equipment room environmental monitoring and leak location, and in particular to a leak location method and device based on resistance gradient calculation. Background Technology

[0002] With the continuous improvement of the intelligence level of power systems, the stability and accuracy of the environmental monitoring system in power plant equipment rooms, as a key infrastructure for power operation, have become crucial supports for ensuring the safe operation of equipment. Among related technologies, a centralized monitoring system based on a serial server and Windows platform has been constructed through the collaborative operation of temperature and humidity detectors, noise transmitters, and leakage sensing ropes. Specifically, this system covers the entire process from data acquisition and transmission to alarm processing, including key aspects such as equipment access, threshold setting, real-time monitoring, and alarm triggering. It is widely used in power, communication, and data center fields, and is an important technical means to achieve unattended operation and efficient maintenance.

[0003] However, existing data center monitoring methods typically rely solely on sensor cables to detect leaks, failing to establish a mapping between physical location and electrical parameters. This results in inaccurate leak location, impacting operational efficiency and increasing equipment damage risks. Specifically, when environmental parameters approach alarm thresholds, system fluctuations can generate numerous duplicate alarms, leading to signal redundancy and interference. Furthermore, existing systems are often based on closed operating systems, presenting potential security vulnerabilities and high resource consumption, limiting their application in high-security, high-performance scenarios. Therefore, there is an urgent need for an environmental monitoring technology system capable of point-level location detection, reducing false alarm rates, and enhancing system security. Summary of the Invention

[0004] The present invention aims to at least partially solve one of the technical problems in the related art.

[0005] Therefore, the first objective of this invention is to propose a method for locating leak points based on resistance gradient calculation.

[0006] The second objective of this invention is to propose a leak location device based on resistance gradient calculation.

[0007] To achieve the above objectives, a first aspect of the present invention proposes a method for locating leak points based on resistance gradient calculation, comprising: S1, obtaining the total resistance value and end resistance value of the leak sensing rope, and reading a preset resistivity parameter per unit length; S2, calculating the distance to the leak point based on the total resistance value, end resistance value, and resistivity parameter per unit length; S3, converting the distance to the leak point into corresponding 3D coordinates or a textual description of the physical location according to the mapping relationship between the length of the sensing rope and the physical location established during the installation and commissioning phase; S4, combining the physical location information with real-time monitoring data to generate an alarm message containing the specific leak point location, and outputting it to the monitoring interface.

[0008] In one embodiment of the present invention, the step of obtaining the total resistance value and end resistance value of the leakage sensing rope and reading the preset unit length resistivity parameter further includes: S11, periodically collecting voltage and current data at both ends of the sensing rope through the leakage controller, and calculating the total resistance value and end resistance value according to Ohm's law; S12, reading the unit length resistivity ρ corresponding to the sensing rope model from the preset configuration database, wherein the ρ value is calibrated and stored during the installation and debugging stage according to the material characteristics.

[0009] In one embodiment of the present invention, the calculation of the distance to the leak point based on the total resistance value, the end resistance value, and the resistivity parameter per unit length further includes: S21, using a sliding window algorithm to smooth the resistance values ​​of multiple consecutive cycles to eliminate the influence of instantaneous interference on the calculation results; S22, comparing the calculated L value with a preset error tolerance range, and if it exceeds the error range, triggering a secondary verification mechanism to re-collect and calculate the distance to the leak point.

[0010] In one embodiment of the present invention, the step of converting the distance of the leak point into corresponding 3D coordinates or textual descriptions of the physical location based on the mapping relationship between the length of the sensing rope and the physical location established during the installation and commissioning phase further includes: S31, reading the starting point coordinates, direction vector, and installation path information of the sensing rope from the installation and commissioning database, and generating corresponding 3D coordinates by combining the calculated L value; S32, if the sensing rope is not configured with 3D coordinates, mapping the L value to a specific equipment name, pipeline number, or installation area description according to a preset textual description table.

[0011] In one embodiment of the present invention, the method further includes: S5, establishing an independent TCP connection thread for each serial port server through a multi-threading mechanism, and allocating a corresponding device list to each thread to achieve parallel data acquisition and processing; S6, when a thread acquires device alarm data, pushing the data to the alarm processing module, and initiating the corresponding alarm judgment process according to the alarm type.

[0012] To achieve the above objectives, a second aspect of the present invention provides a leak point location device based on resistance gradient calculation, comprising: a data acquisition module for acquiring the total resistance value and end resistance value of the leak sensing rope, and reading a preset resistivity parameter per unit length; a distance calculation module for calculating the leak point distance based on the total resistance value, end resistance value, and resistivity parameter per unit length; a position mapping module for converting the leak point distance into a corresponding 3D coordinate or textual description of the physical location according to the mapping relationship between the sensing rope length and the physical location established during the installation and commissioning phase; and an alarm generation module for combining the physical location information with real-time monitoring data to generate an alarm prompt message containing the specific leak point location, and outputting it to the monitoring interface.

[0013] In one embodiment of the present invention, the data acquisition module is further configured to: periodically acquire voltage and current data at both ends of the sensing rope through a leakage controller, and calculate the total resistance value and the end resistance value according to Ohm's law; read the unit length resistivity ρ corresponding to the sensing rope model from a preset configuration database, wherein the ρ value is calibrated and stored during the installation and debugging stage according to the material characteristics.

[0014] In one embodiment of the present invention, the distance calculation module is further configured to: use a sliding window algorithm to smooth the resistance values ​​of multiple consecutive cycles to eliminate the influence of instantaneous interference on the calculation results; compare the calculated L value with a preset error tolerance range, and if it exceeds the error range, trigger a secondary verification mechanism to re-collect and calculate the distance to the leak point.

[0015] In one embodiment of the present invention, the position mapping module is further configured to: read the starting point coordinates, direction vector and installation path information of the sensing rope from the installation and debugging database, and generate corresponding 3D coordinates by combining the calculated L value; if the sensing rope is not configured with 3D coordinates, then map the L value to a specific equipment name, pipeline number or installation area description according to a preset text description table.

[0016] In one embodiment of the present invention, it further includes: a connection management module, used to establish an independent TCP connection thread for each serial port server through a multi-threaded mechanism, and to allocate a corresponding device list for each thread to achieve parallel data acquisition and processing; and a data push module, used to push the data to the alarm processing module when a thread acquires device alarm data, and to start the corresponding alarm judgment process according to the alarm type.

[0017] The method and apparatus of this invention can accurately locate leak points, significantly improve operation and maintenance efficiency and reduce the risk of equipment damage. At the same time, by using multi-threaded data acquisition and dynamic alarm strategies, alarm delay and repetition are reduced, thereby improving the overall performance and stability of the system.

[0018] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0019] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart of a method for locating leak points based on resistance gradient calculation according to an embodiment of the present invention; Figure 2 This is a flowchart of another method for locating leak points based on resistance gradient calculation according to an embodiment of the present invention; Figure 3 This is a flowchart of another method for locating leak points based on resistance gradient calculation according to an embodiment of the present invention; Figure 4 This is a structural diagram of a leak point location device based on resistance gradient calculation according to an embodiment of the present invention. Detailed Implementation

[0020] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0021] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0022] The following description, with reference to the accompanying drawings, describes a method and apparatus for locating leak points based on resistance gradient calculation according to an embodiment of the present invention.

[0023] Example 1 Figure 1 This is a flowchart of a leak location method based on resistance gradient calculation according to an embodiment of the present invention, as shown below. Figure 1 As shown, it includes: S1, obtain the total resistance value and end resistance value of the leakage sensing rope, and read the preset resistivity parameter per unit length.

[0024] Specifically, in the leakage monitoring technology of this invention, obtaining the total resistance value and end resistance value of the leakage sensing rope, and reading the preset resistivity parameter per unit length, are key steps to achieve accurate leakage location. This step is based on the principle of resistance gradient change; by measuring the resistance difference of the sensing rope at different locations and combining it with its resistivity parameter per unit length, the precise location of the leak point is calculated.

[0025] In one embodiment of the present invention, the leakage sensing rope consists of two parallel conductive core wires, which are isolated by an insulating material. When liquid comes into contact with the sensing rope, a conductive path is formed, causing a change in the resistance value between the core wires. The leakage controller uses a high-precision impedance measurement circuit to collect the total resistance value of the sensing rope (i.e., the total resistance between the beginning and end of the sensing rope) and the end resistance value (i.e., the resistance between the end of the sensing rope and the controller), thereby obtaining the resistance difference between the leakage point and the controller. Further, the system reads the unit length resistivity parameter (in Ω / m) preset in a database or configuration file. This parameter is calibrated from the measured data of the sensing rope in a leak-free state, and is typically between 0.1 Ω / m and 1 Ω / m, depending on the core wire material, spacing, and insulation performance.

[0026] In one embodiment of the present invention, the system must, by way of example, ensure that the measurement accuracy is not less than 0.01Ω to improve positioning accuracy. The resistivity parameter per unit length needs to be calibrated during the installation and commissioning phase and stored according to the actual laying path, for example, by using 3D modeling or geographic coordinate mapping to map the resistance value to the physical spatial location.

[0027] Understandably, this procedure is widely used in locations with high environmental safety requirements, such as power plant computer rooms, data centers, and communication base stations. By monitoring the resistance changes of the induction rope in real time, the system can quickly locate abnormalities such as air conditioner leaks and pipe ruptures, significantly improving maintenance response efficiency.

[0028] The technical advantage of this step is that it achieves leak location accuracy from millimeters to centimeters by using the mathematical relationship between the resistance difference and the resistivity per unit length. This solves the problem in existing technologies that can only identify leaks in a region but cannot pinpoint the exact location. At the same time, combined with an alarm identification mechanism, it effectively avoids false alarms and repeated alarms, thereby improving system stability and reliability.

[0029] Furthermore, S1 includes: S11 periodically collects voltage and current data at both ends of the sensing rope through the leakage controller, and calculates the total resistance value and the end resistance value according to Ohm's law.

[0030] Specifically, this step involves periodically collecting voltage and current data from both ends of the sensing rope using a leak detector, and calculating the total resistance and end resistance based on Ohm's law to accurately locate the leak point. In some implementations, this process uses a high-precision analog-to-digital converter (ADC) module to synchronously sample the voltage and current of the sensing rope, with the sampling frequency typically set between 100Hz and 1kHz to ensure timely detection of resistance changes when liquid comes into contact with the sensing rope. The controller integrates a microprocessor unit (MPU) or digital signal processor (DSP) to execute the data processing algorithms.

[0031] In one embodiment of the invention, the sensing rope consists of two parallel conductive core wires, typically made of copper or tin-plated copper wire, which have good conductivity and corrosion resistance. When liquid comes into contact with the sensing rope, a conductive path is formed, causing a decrease in resistance. The controller calculates the total resistance by measuring the voltage (V) at both ends of the sensing rope and the current (I) flowing through it, according to Ohm's law R = V / I. Furthermore, by comparing the resistance difference at both ends of the sensing rope, the controller can deduce the resistance value of the leak point relative to the starting point of the sensing rope, i.e., the end resistance value. Combined with a pre-calibrated resistivity per unit length (ρ, in Ω / m), the physical location of the leak point can be calculated using the formula: Leak point location = (Total resistance - End resistance) / ρ.

[0032] In one embodiment of the present invention, the total length of the sensing rope is typically between 10 and 100 meters. The resistivity per unit length needs to be determined through actual measurement during the installation and commissioning phase, and the error range should be controlled within ±5%. The alarm trigger threshold can be set according to different environments; for example, an alarm is triggered when the total resistance drops by more than 20%. In practical applications, this step is deployed in critical facilities such as power plant machine rooms to monitor areas prone to leakage, such as below air conditioners and around pipes, in real time, enabling rapid location of fault points and improving operation and maintenance efficiency.

[0033] The technical advantage of this step is that, compared to traditional solutions that can only determine whether there is a leak, this method achieves precise location of the leak point through resistance gradient analysis, effectively improving the system's fault response capability and maintenance efficiency, and has significant innovation and practicality.

[0034] S12, read the unit length resistivity ρ corresponding to the model of the sensing rope from the preset configuration database. The ρ value is calibrated and stored during the installation and debugging stage according to the material characteristics.

[0035] Specifically, this step involves reading the resistivity ρ per unit length corresponding to the model of the sensing rope from a preset configuration database. This ρ value is obtained and stored through calibration during the installation and commissioning phase for subsequent precise location of leaks. This step is a key step in realizing the location-based leak detection function, and its technical principle is based on the linear relationship between the resistance gradient change of the sensing rope and its physical length.

[0036] In one embodiment of the present invention, the sensing rope consists of two parallel conductive core wires. When liquid comes into contact with the core wires, a conductive path is formed between the two wires, causing a decrease in resistance. The leak controller calculates the physical distance of the leak point relative to the starting point of the sensing rope by measuring the resistance values ​​at both ends of the sensing rope and combining this with a pre-calibrated resistivity per unit length ρ. The specific formula is: Leak point location = (Total resistance - End resistance) / ρ. The calibration of ρ needs to be performed during the installation and commissioning phase. This is done by injecting standard liquid at a known location, measuring the corresponding resistance change, thereby establishing a length-resistance mapping relationship, and writing the ρ value into the configuration database for real-time use by the monitoring software.

[0037] In one embodiment of the invention, the calibration accuracy of the ρ value directly affects the positioning error. In some implementations, the calibration process needs to be performed in an interference-free environment, using a high-precision multimeter (e.g., 0.01Ω resolution) to measure the resistance change, and calculating the result in conjunction with the actual laying length of the induction rope (typically within 100m). The ρ value can be stored in floating-point format, and it is recommended to retain the accuracy to four decimal places to ensure the accuracy of the calculation result. Furthermore, the system supports ρ value configurations for various induction rope models; each model needs to be calibrated and stored independently to accommodate induction ropes of different materials and structures.

[0038] Understandably, this step is widely used in locations with high environmental safety requirements, such as power plant computer rooms, data centers, and communication base stations. Upon detecting a water leak alarm, the monitoring software immediately reads the corresponding ρ value from the database and combines it with the currently measured resistance value to calculate the location. This clearly displays the distance and physical location of the leak point in the alarm information (such as a 3D diagram or text label), significantly improving maintenance response efficiency.

[0039] The technical advantage of this step lies in achieving millimeter-level location of leaks by precisely reading the ρ value, solving the problem in existing technologies that can only detect area leaks but cannot pinpoint the exact location. Simultaneously, the dynamic configuration mechanism of the ρ value enhances the system's adaptability and scalability, providing a solid foundation for building a high-precision, low-false-alarm-rate environmental monitoring system. S2, based on the total resistance value, the end resistance value, and the resistivity parameter per unit length, calculate the distance to the leak point.

[0040] Specifically, this step is based on the total resistance value. Terminal resistance value and resistivity per unit length Through formula Calculate the distance to the leak point This is the core algorithm component for achieving precise leak location in this invention. This method utilizes the resistive characteristics of a leak-sensing rope, combining physical measurements with mathematical modeling to accurately locate the leak point, thereby significantly improving the response efficiency and operational accuracy of the data center environment monitoring system.

[0041] In one embodiment of the present invention, the leakage sensing rope consists of two parallel conductive core wires, which are isolated by an insulating material. When liquid (such as water) comes into contact with the core wires, a conductive path is formed, causing a change in the resistance between the core wires. The leakage controller measures the total resistance at both ends of the sensing rope. and end resistance And combined with the pre-calibrated resistivity per unit length (Unit: Ω / m) Calculate the distance between the leak point and the controller. This formula is based on Ohm's law and the principle of series resistance. It assumes that the induction rope is a uniform conductor and the liquid contact point is a single leakage point, thus establishing a linear relationship between the resistance difference and the physical distance.

[0042] In one embodiment of the invention, by way of example, resistivity per unit length The total resistance needs to be determined through actual measurements during the installation and commissioning phase. Calibration is typically performed in a laboratory environment using a standard-length induction rope to ensure stability under varying environmental humidity and temperature conditions. and end resistance The data is acquired by a high-precision impedance measurement module, with a measurement accuracy typically required to be within ±0.5% to ensure that the positioning error does not exceed ±1%. In addition, the system also needs to set a resistance change threshold to determine whether an effective leakage has occurred, avoiding misjudgments caused by environmental interference.

[0043] Understandably, this procedure is suitable for environmental monitoring systems in power plant computer rooms, data centers, communication base stations, and other environments where high accuracy in locating leaks is required. By laying induction ropes along potential leak paths such as pipes, floors, and walls, and configuring corresponding physical location mapping tables (such as 3D coordinates or text annotations) in the monitoring software, the system can quickly calculate and display the specific location of the leak point when abnormal resistance changes are detected, assisting maintenance personnel in efficiently locating and handling faults.

[0044] The technical advantage of this step lies in the fact that, compared to traditional solutions that can only detect whether there is a leak, this invention achieves distance-level location of the leak point through resistance difference calculation, improving the timeliness and accuracy of fault response. At the same time, this method is simple in structure, cost-controllable, and has good engineering practicality and scalability, making it an important technical support for building intelligent, unattended environmental monitoring systems.

[0045] Furthermore, S2 includes: S21. A sliding window algorithm is used to smooth the resistance values ​​of multiple consecutive cycles in order to eliminate the influence of instantaneous interference on the calculation results.

[0046] Specifically, in this invention, a sliding window algorithm is used to smooth the resistance values ​​of multiple consecutive cycles. Its core purpose is to eliminate abnormal data points caused by transient interference (such as electromagnetic noise, environmental fluctuations, or poor equipment contact), thereby improving the accuracy and stability of leak detection. This step, as a key component of data preprocessing in environmental monitoring software, directly affects the acquisition and analysis of the resistance values ​​of the leak sensing rope.

[0047] In one embodiment of the present invention, the sliding window algorithm sets a fixed-length window (e.g., 5 sampling periods). Each time a new data point arrives, it is added to the window queue, and the oldest collected data point is removed, thus ensuring that the window always contains the resistance values ​​of the most recent N periods. Subsequently, a weighted average or moving average is applied to the data within the window to smooth fluctuations. In some implementations, an exponentially weighted moving average (EWMA) algorithm can be used, where the weighting coefficient α can be adjusted according to the system response speed and stability requirements, typically ranging from 0.1 to 0.3, to balance real-time performance and anti-interference capability.

[0048] In one embodiment of the present invention, the length (N) of the sliding window directly affects the system's ability to suppress transient interference and its response speed to real changes. In this invention, N is typically set to 5-10 sampling periods, with a sampling frequency of 1-2 seconds / time, meeting the basic real-time requirements of industrial monitoring systems. Furthermore, the smoothed resistance value needs to be compared with a preset resistivity per unit length (Ω / m) to calculate the leak location. The calculation formula is: Leak location = (Total resistance - End resistance) / Resistance per unit length. This formula requires the measurement error between the total resistance and the end resistance to be controlled within ±5% to ensure positioning accuracy.

[0049] Understandably, this algorithm is suitable for industrial scenarios with high environmental stability requirements, such as power plant computer rooms. Especially in areas below air conditioning systems or with dense piping, where liquid contact can cause instantaneous resistance changes, the sliding window smoothing process can effectively filter out such noise and avoid misjudgments. Combined with physical location mapping using 3D maps or text annotations, maintenance personnel can quickly locate fault points, improving response efficiency.

[0050] This step yields significant technical benefits, not only improving the robustness of leak detection but also reducing false alarm rates and the frequency of repeated alarms, thereby enhancing system availability and the trust of maintenance personnel. By introducing a sliding window algorithm, this invention effectively improves upon the problem in existing technologies that "can only identify area leaks but cannot pinpoint the exact location" at the data processing level, demonstrating high engineering practical value and innovation.

[0051] S22. The calculated L value is compared with the preset error tolerance range. If it exceeds the error range, a secondary verification mechanism is triggered to re-collect and calculate the distance to the leak point.

[0052] Specifically, this step involves comparing the calculated distance to the leak point (L value) with a preset error tolerance range in the leak detection system. If the distance exceeds the error tolerance range, a secondary verification mechanism is triggered to re-acquire and calculate the distance to the leak point. This step is crucial for achieving high-precision leak location and reducing false alarms.

[0053] In one embodiment of the present invention, the calculation of the leakage point distance L is based on the principle of resistance gradient change of the leakage sensing rope. The sensing rope consists of two parallel conductive core wires. When liquid comes into contact, a short circuit path is formed between the two core wires, causing the resistance value to drop. The leakage controller calculates the leakage point distance by measuring the resistance values ​​at both ends of the cable and combining them with the resistivity per unit length (typically 0.1Ω / m to 0.5Ω / m, depending on the material and installation environment), using the formula: L = (R_total - R_end) / R_per_unit. Where R_total is the total resistance, R_end is the end resistance, and R_per_unit is the resistivity per unit length. During the system initialization phase, the physical position of each leakage rope needs to be adjusted, and each distance point needs to be mapped to a 3D spatial coordinate or a textual description of its physical location to ensure the interpretability of the calculation results.

[0054] In one embodiment of the present invention, the system's preset error tolerance range is typically set to an L value range of ±5% to ±10%, and the specific value can be adjusted according to the complexity of the on-site environment and the installation accuracy of the sensing rope. For example, if the calculated L value is 12.3 meters and the error tolerance is ±10%, then the allowable error range is 11.07 meters to 13.53 meters. If the actual calculated value exceeds this range, it is determined to be abnormal, triggering a secondary verification mechanism.

[0055] Understandably, this mechanism is suitable for environments with high requirements for leak location accuracy, such as power plant computer rooms, data centers, and industrial plants. In actual deployment, the system may experience calculation deviations due to factors such as poor contact of the sensing rope, electromagnetic interference, or instantaneous liquid splashing. Secondary verification can effectively eliminate such interference, ensuring the accuracy and reliability of alarm information.

[0056] From a technical perspective, this step, by introducing error tolerance and a secondary verification mechanism, significantly improves the robustness and accuracy of leak location, avoiding false alarms or missed alarms caused by instantaneous errors, and enhancing the system's intelligence and operational efficiency. Furthermore, combining multi-threaded data acquisition with the low-latency characteristics of the Linux system enables rapid response and high-concurrency processing, providing a solid guarantee for real-time monitoring in unattended environments. S3. Based on the mapping relationship between the length of the sensing rope and the physical location established during the installation and commissioning phase, the distance to the leak point is converted into the corresponding 3D coordinates or a textual description of the physical location.

[0057] Specifically, in this invention, the step of "converting the distance to the leak point into corresponding 3D coordinates or textual descriptions of the physical location based on the mapping relationship between the length of the sensing rope and the physical location established during the installation and commissioning phase" is the core step in achieving accurate leak location. This step, based on the principle of resistance gradient change in the sensing rope and combined with the physical space mapping model established during the initial installation and commissioning process, converts the detected leak distance information into intuitively identifiable 3D coordinates or textual descriptions, thereby significantly improving maintenance response efficiency and fault location accuracy.

[0058] In one embodiment of the present invention, the leakage sensing rope consists of two parallel conductive core wires. Its resistivity (ρ) per unit length is determined by laboratory testing or on-site calibration before installation, typically between 0.05 Ω / m and 0.2 Ω / m, with the specific value depending on material properties and the installation environment. When liquid comes into contact with the sensing rope, a short circuit or partial conductivity will form at the contact point, causing a decrease in resistance. The leakage controller measures the resistance difference (ΔR) between the two ends of the sensing rope and, combined with the known total length (L) and resistance per unit length (R_per_unit), calculates the physical distance from the leak point to the starting point of the sensing rope using the formula: Leak point location = (ΔR × L) / R_total. This calculation process needs to be implemented in software, typically written in C++ or Python, and possesses high-precision floating-point arithmetic capabilities.

[0059] During the installation and commissioning phase, maintenance personnel need to physically mark the coordinates of each section of the sensor rope. For example, they can use a laser rangefinder or 3D modeling tools (such as AutoCAD or Revit) to record the 3D coordinates (x, y, z) of the starting point, ending point, and key nodes of the sensor rope, and establish a distance-coordinate mapping table. This table can be stored in a MySQL database as the basis for subsequent alarm analysis. Alternatively, a text description can be used, such as "3 meters below air conditioner A" or "1.2 meters in front of the 5th row of server racks on the east wall of the computer room".

[0060] Understandably, this procedure is widely applicable to locations with high environmental safety requirements, such as power plant computer rooms, data centers, and communication base stations. When the monitoring software detects a water leakage alarm, it can immediately call up the mapping table to convert the calculated leakage distance into 3D coordinates or text descriptions, and push this information to the operation and maintenance platform or mobile terminal for quick location and handling.

[0061] The technical advantage of this step is that, compared to the traditional method of only indicating "leaking in a certain area," this invention achieves leak location with millimeter-level accuracy, effectively reducing false alarms and duplicate alerts. By mapping physical distance to 3D coordinates, the system's visualization capabilities are further enhanced, providing reliable data support for intelligent operation and maintenance.

[0062] Furthermore, S3 includes: S31, read the starting coordinates, direction vector and installation path information of the sensing rope from the installation and debugging database, and generate the corresponding 3D coordinates by combining them with the calculated L value.

[0063] Specifically, in the implementation of the environmental monitoring software of this invention, reading the starting coordinates, direction vector, and installation path information of the sensing rope from the installation and debugging database, and generating corresponding 3D coordinates by combining this information with the calculated leakage distance L, is one of the core steps for achieving accurate leak location. This step, through spatial geometric modeling and database information fusion, maps the one-dimensional leakage distance to a specific location point in three-dimensional space, thereby providing maintenance personnel with an intuitive and accurate basis for fault location.

[0064] In one embodiment of the present invention, this step first reads the installation metadata of the sensing rope, including the starting coordinates, through a MySQL database query interface. The system includes a direction vector (dx, dy, dz) and topological information about the installation path. The direction vector describes the extension direction of the sensing rope in three-dimensional space and is usually preset and stored through installation records at the construction site or CAD drawings. The installation path information is used to handle possible bends and segments of the sensing rope in complex spaces, ensuring the continuity and accuracy of coordinate calculations.

[0065] In one embodiment of the present invention, the starting coordinates are typically expressed in millimeters or meters with an accuracy requirement of ±10mm to meet the high-precision positioning requirements of equipment layout within the computer room. The direction vector needs to be normalized to ensure its modulus is 1, so that the displacement of the leak point can be calculated proportionally later. The resistivity parameter per unit length (ρ) needs to be obtained through actual measurement during the installation and commissioning phase, typically 0.01~0.1Ω / m, and is used to calculate the distance L from the leak point. The formula for calculating the value of L is: L = (R_total - R_end) / ρ, where R_total is the total resistance of the induction rope, and R_end is the end resistance.

[0066] Understandably, this step is suitable for locations with high environmental safety requirements, such as power plant computer rooms and data centers. By mapping the leak point to 3D coordinates, the system can interface with BIM modeling or 3D visualization platforms to achieve spatial positioning and alarm linkage, thereby improving operation and maintenance response efficiency.

[0067] In terms of technical effectiveness, this step effectively solves the problem in existing technologies that can only identify the area of ​​leakage but cannot accurately locate it. Combined with multi-threaded data acquisition and alarm judgment mechanisms, it further improves the real-time performance and accuracy of the system, providing key technical support for building an intelligent, unattended data center monitoring system.

[0068] S32, if the sensing rope is not configured with 3D coordinates, the L value is mapped to a specific equipment name, pipeline number or installation area description according to the preset text description table.

[0069] Specifically, in some implementations, when the sensing rope is not configured with 3D coordinate information, the system will map the L value of the sensing rope (i.e., the length from the leak point to the starting point of the sensing rope) to a specific equipment name, pipeline number, or installation area description based on a preset text description table. This step is a key step in achieving accurate leak location, and its technical implementation is based on a geographic information recording and database mapping mechanism during equipment installation.

[0070] In one embodiment of the present invention, the mapping process relies on a "sensor rope-physical location" correspondence table previously established in the system database. This table is typically stored in a MySQL database as structured data and includes fields such as `sensor_id` (unique identifier for the sensor rope), `start_position` (starting point coordinates or area description), `end_position` (ending point coordinates or area description), `length` (total length), and `mapping_table` (segment mapping table). The `mapping_table` is a nested structure in JSON or XML format, recording the correspondence between the lengths of each segment of the sensor rope and the actual device or area. When the system detects a leak at a distance L, it iterates through this mapping table to match the interval containing the value of L, thereby determining the corresponding device or area name.

[0071] In one embodiment of the present invention, the value of L is calculated based on the formula: ,in To determine the total resistance of the sensing rope, For the end resistance, Resistivity per unit length, typically expressed in Ω / m. In practical deployments, The system needs to be calibrated based on the material properties of the sensing rope, with typical values ​​between 0.1 and 0.5 Ω / m. The system also needs to have a mapping accuracy threshold set, such as ±0.5m, to ensure that the positioning error is within an acceptable range.

[0072] Understandably, this step is widely used in locations requiring high-precision environmental monitoring, such as power plant computer rooms, data centers, and industrial plants. Especially in the absence of BIM modeling or 3D visualization systems, achieving rapid location through text description tables helps maintenance personnel respond quickly and reduces troubleshooting time.

[0073] The technical advantage of this step is that it effectively compensates for the shortcomings of traditional leak detection systems, which can only determine whether there is a leak but cannot accurately locate it. It improves the intelligence level and operation and maintenance efficiency of the system, and has significant practical value and innovation.

[0074] S4. Combine the physical location information with real-time monitoring data to generate an alarm message containing the specific leak location, and output it to the monitoring interface.

[0075] Specifically, the core of this step lies in fusing physical location information with real-time monitoring data to generate an alarm message containing the specific location of the leak, and then outputting this information to the monitoring interface. This process plays a crucial role in the centralized monitoring system of power plant generator rooms, solving the problem in existing technologies where leak alarms can only locate the area or equipment, but cannot accurately pinpoint the specific location.

[0076] In one embodiment of the present invention, the leakage sensing rope consists of two parallel conductive core wires, and its working principle is based on the change in conductivity caused by liquid contact. When liquid comes into contact with the sensing rope, the resistance value between the core wires changes. The leakage controller calculates the precise distance of the leakage point by measuring the resistance difference between the two ends of the cable and combining it with a pre-set resistivity parameter per unit length (e.g., 0.5Ω / m). The formula is: Leakage point location = (Total resistance - End resistance) / Resistance per unit length. During the installation phase, each leakage rope needs to be debugged, and its correspondence with the actual physical location needs to be recorded. This is usually stored in a database in the form of a 3D model or coordinate mapping table to ensure that subsequent alarm information can be accurately mapped to the spatial location.

[0077] In one embodiment of the present invention, the system exemplarily requires configuring an alarm threshold, an alarm identification time (e.g., set to 30 seconds), and an alarm recovery hysteresis value (e.g., set to 10% of the threshold). The alarm identification time is used to filter transient anomalies and improve alarm accuracy; the hysteresis value strategy effectively avoids repeated alarms caused by small fluctuations in values. Furthermore, the system implements parallel data acquisition through a multi-threaded mechanism, with each thread independently handling a serial port server connection, improving data processing efficiency and reducing latency.

[0078] Understandably, this procedure is widely used in locations with high environmental safety requirements, such as power plant computer rooms and data centers. When the monitoring software detects a water leak, it can immediately display the specific location on the monitoring interface in a graphical way (such as 3D map marking) or in text form (such as "The leak point is located in the 3rd row, 2nd column of Area A"), assisting maintenance personnel in quickly locating and handling the fault.

[0079] The technical benefits of this step are that it significantly improves the accuracy and response efficiency of water leakage alarms, reduces the false alarm rate and the frequency of repeated alarms, thereby enhancing the system's intelligent operation and maintenance capabilities and improving the timeliness and accuracy of equipment maintenance.

[0080] Also includes: S5 uses a multi-threading mechanism to establish an independent TCP connection thread for each serial port server and assigns a corresponding device list to each thread to achieve parallel data acquisition and processing.

[0081] Specifically, in the steps of this invention, an independent TCP connection thread is established for each serial port server through a multi-threaded mechanism, and a corresponding device list is assigned to each thread to achieve parallel data acquisition and processing. This technique has significant innovation and practicality in centralized monitoring systems for power plant generator rooms.

[0082] In one embodiment of the present invention, during the operation of the environmental monitoring software, information on all serial port servers and their connected devices is first read from the MySQL database, including parameters such as device type, communication protocol, baud rate, data bits, and stop bits. Subsequently, the software establishes an independent network connection via TCP / IP protocol based on the IP address and port number of the serial port server. In some implementations, each serial port server corresponds to an independent thread, which is responsible for maintaining the stability of the TCP connection and periodically sending data acquisition commands to the serial port server. Since serial port servers typically use half-duplex communication, meaning they can only communicate with one device at a time, each thread employs a polling mechanism to sequentially access its managed device list, ensuring the orderliness and completeness of data acquisition.

[0083] In one embodiment of the present invention, key parameters in this step include TCP connection timeout (recommended to be set to 3-5 seconds), polling interval (usually 1-3 seconds), and maximum number of threads in the thread pool (recommended not to exceed twice the number of CPU cores, depending on the server hardware configuration). Furthermore, communication parameters for each device, such as baud rate (9600-115200 bps), data bits (7 or 8 bits), parity bits (even, odd, or no parity), and stop bits (1 or 2 bits), must be configured in the database to ensure that the threads can correctly parse the data frames returned by the devices.

[0084] Understandably, this step is widely used in environmental monitoring scenarios requiring high real-time performance and multi-device access, such as power plant computer rooms, data centers, and industrial control systems. In actual deployments, each serial port server may connect to multiple temperature and humidity sensors, noise transmitters, or water leakage detection modules. Through multi-threading mechanisms, the system's concurrent processing capabilities can be effectively improved, avoiding data acquisition delays caused by serial communication blockages.

[0085] Understandably, by allocating an independent thread to each serial port server, the system achieves parallel acquisition and processing of device data, significantly reducing data acquisition response time and improving overall monitoring efficiency. Simultaneously, the thread isolation mechanism enhances system stability and fault tolerance; even if a serial port server experiences a communication failure, it will not affect the data acquisition process of other devices. This technique effectively solves the efficiency bottleneck caused by serial communication in existing systems, providing reliable support for achieving high-precision, low-latency environmental monitoring.

[0086] S6: When a thread collects device alarm data, it pushes the data to the alarm processing module and starts the corresponding alarm judgment process according to the alarm type.

[0087] Specifically, when a thread collects device alarm data, it pushes the data to the alarm processing module and initiates the corresponding alarm judgment process based on the alarm type. This is one of the key steps in achieving efficient and accurate alarm management in the environmental monitoring system according to this invention. This step is based on the collaborative design of a multi-threaded architecture and alarm judgment strategy, aiming to improve the system's response speed and judgment accuracy to abnormal events.

[0088] In one embodiment of the present invention, the system establishes an independent working thread for each serial port server to achieve concurrent data acquisition from the temperature and humidity detector, the water leakage sensing rope, and the noise transmitter. After completing device polling, each thread parses the raw data string returned by the device, extracts key parameters (such as temperature value, humidity value, noise intensity, resistance value, etc.), and encapsulates it into a structured alarm data object. This object contains fields such as device ID, data channel, real-time value, and acquisition timestamp. Subsequently, the alarm data is pushed to the alarm processing module through a message queue or event bus mechanism. The alarm processing module calls the corresponding alarm judgment sub-process according to the alarm type in the data object (such as water leakage alarm, over-temperature alarm, etc.).

[0089] In one embodiment of the present invention, the alarm determination process exemplarily relies on alarm configuration information read from a MySQL database, including alarm thresholds (e.g., a temperature threshold set to 35°C), alarm identification time (e.g., an alarm is triggered only if the threshold is exceeded for 10 consecutive seconds), and alarm recovery hysteresis (e.g., recovery is considered only if the temperature drops below 32°C). These parameters can be flexibly configured according to different device types and environmental characteristics, complying with the alarm management specifications in IT service management standards such as ISO / IEC 20000-1.

[0090] Understandably, this step is widely used in locations with high environmental stability requirements, such as power plant computer rooms and data centers. Through multi-threaded data acquisition and alarm type-driven judgment mechanisms, the system can maintain low-latency response in high-concurrency environments, ensuring the real-time nature and accuracy of alarm information.

[0091] The technical advantage of this step is that it effectively avoids false alarms and duplicate alarms caused by instantaneous fluctuations, improving the stability and operational efficiency of the alarm system. At the same time, the modular decision-making process design enhances the system's scalability and maintainability, providing a reliable data foundation for subsequent alarm analysis and automated handling.

[0092] The leak location method based on resistance gradient calculation in this invention establishes an independent TCP connection thread for each serial port server and performs parallel data acquisition and processing. This enables the system to respond more efficiently to alarm information from multiple devices and initiates a targeted judgment process based on the alarm type. This further improves the real-time performance and accuracy of leak location, reduces system latency and resource consumption, and enhances overall monitoring efficiency and stability.

[0093] Example 2 Existing leak alarms indicate a leak in an air conditioner or a general area, but do not specify the exact location of the leak. If environmental conditions reach or fluctuate above the alarm threshold, multiple duplicate alarms and recovery messages will be generated. This invention proposes a leak location method based on resistance gradient calculation, specifically as follows: Figure 2 and Figure 3 As shown: Install temperature and humidity detectors in each monitoring area, lay leakage sensing ropes under air conditioners or other locations where leakage may occur, and install noise transmitters at the construction site.

[0094] Temperature and humidity detectors, water leakage detectors, and noise transmitters are centrally connected to a serial port server.

[0095] Implementation of leak detection: The leak detection rope consists of two parallel conductive core wires. When liquid comes into contact with the wires, the change in conductivity causes a change in the resistance gradient. The leak controller calculates the leak location by measuring the difference in resistance at both ends of the cable and combining this with the resistivity parameter per unit length: Leak location = (Total resistance - End resistance) / Resistance per unit length. During installation, the actual physical location corresponding to each leak distance in each rope is debugged and recorded, represented in 3D graphics or text. The monitoring software reads the total length of the leak detection rope in real time and simultaneously checks for leak alarms. If a leak is detected, the leak distance is read, and a leak alarm is generated, specifying the alarm distance and leak location, allowing maintenance personnel to locate and address the fault as early as possible.

[0096] The monitoring server uses the openEuler operating system, which is open source and uses the Linux kernel. Compared to Windows, Linux is completely open source, with transparent code, allowing global developers to review and fix vulnerabilities, reducing potential security risks. In terms of system resource consumption, Linux systems use less memory and CPU, leaving more memory and CPU available for applications under the same configuration.

[0097] Environmental monitoring software implementation process: First, the device information for the monitored temperature, humidity, water leakage, noise transmitters, and serial port server is read from the MySQL database. After reading, the connection information for the serial port server is obtained from the device information, and a connection is established via TCP network. Once the connection is successful, a dedicated worker thread is set up for each TCP connection to handle device monitoring. Multiple threads simultaneously collect data from the devices, improving data acquisition efficiency, reducing real-time data acquisition latency, and providing the worker thread with a list of devices connected to the current TCP connection.

[0098] The device monitoring thread starts and polls the list of devices. Because the devices use half-duplex communication, it can only communicate with one device at a time. Communication with the next device can only begin after the first communication is complete. The thread sends data acquisition commands to the devices, which then return a real-time data string. Upon receiving the real-time data string, the thread extracts the valid data and reads the corresponding alarm configuration information for the data channel from the database. From this information, it extracts the alarm threshold, alarm identification time, and alarm recovery hysteresis.

[0099] The determination of device data alarm triggering assumes the data channel is currently in a normal state. It checks if the real-time value exceeds the alarm threshold. If it does, it checks if the duration of the value exceeding the threshold reaches the alarm identification time. Using duration for determination ensures the accuracy of alarm submission and avoids false alarms caused by a momentary value exceeding the alarm threshold followed by an immediate return to normal. If the alarm identification time is reached, an alarm message is generated, and the data channel is set to alarm status.

[0100] The determination of device data alarm recovery is based on the following: If the data channel is currently in an alarm state, check if the real-time value is lower than the hysteresis value. Using the hysteresis value strategy can prevent the real-time operating value from fluctuating slightly around the alarm threshold, which could lead to too many duplicate alarms. If it is lower than the hysteresis value, continue to check if the duration has reached the alarm identification time. If it has, then it is determined that the data channel has recovered from the alarm state to the normal state.

[0101] In summary, the beneficial effects of this invention are as follows: Location-based leak detection accurately pinpoints the exact location of leaks; the use of the open-source system openEuler improves network security and application performance; alarm identification time and alarm recovery hysteresis are used to avoid false alarms and duplicate alarms; and multi-threaded environmental monitoring reduces the latency of real-time monitoring values.

[0102] Example 3 Figure 4 This is a schematic diagram of a leak location device based on resistance gradient calculation according to an embodiment of the present invention. Figure 4As shown, the leak location device 10 based on resistance gradient calculation includes: The data acquisition module 100 is used to acquire the total resistance value and end resistance value of the leakage sensing rope, and read the preset resistivity parameter per unit length. The distance calculation module 200 is used to calculate the distance to the leak point based on the total resistance value, the end resistance value, and the resistivity parameter per unit length. The location mapping module 300 is used to convert the distance of the leak point into corresponding 3D coordinates or text descriptions of the physical location based on the mapping relationship between the length of the sensing rope and the physical location established during the installation and commissioning phase. The alarm generation module 400 is used to combine the physical location information with real-time monitoring data to generate alarm prompt information containing the specific water leakage point and output it to the monitoring interface.

[0103] Furthermore, the data acquisition module is also used for: The leakage controller periodically collects voltage and current data at both ends of the sensing rope and calculates the total resistance and end resistance based on Ohm's law. The resistivity ρ per unit length corresponding to the model of the sensing rope is read from the preset configuration database. The ρ value is calibrated and stored during the installation and commissioning stage according to the material characteristics.

[0104] Furthermore, the distance calculation module is also used for: A sliding window algorithm is used to smooth the resistance values ​​of multiple consecutive cycles in order to eliminate the influence of transient interference on the calculation results. The calculated L value is compared with the preset error tolerance range. If it exceeds the error range, a secondary verification mechanism is triggered to re-collect and calculate the distance to the leak point.

[0105] Furthermore, the location mapping module is also used for: The starting point coordinates, direction vector, and installation path information of the sensing rope are read from the installation and debugging database, and the corresponding 3D coordinates are generated by combining them with the calculated L value. If the sensing rope is not configured with 3D coordinates, the L value will be mapped to a specific equipment name, pipeline number, or installation area description according to the preset text description table.

[0106] Furthermore, it also includes: The connection management module is used to establish an independent TCP connection thread for each serial port server through a multi-threaded mechanism, and to allocate a corresponding device list to each thread in order to achieve parallel data acquisition and processing. The data push module is used to push the alarm data collected by a certain thread to the alarm processing module and start the corresponding alarm judgment process according to the alarm type.

[0107] According to the embodiment of the present invention, the leak location device based on resistance gradient calculation establishes an independent TCP connection thread for each serial port server and performs parallel data acquisition and processing. The system can respond to alarm information from multiple devices more efficiently, and initiate a targeted judgment process based on the alarm type. This further improves the real-time performance and accuracy of leak location, reduces system latency and resource consumption, and enhances overall monitoring efficiency and stability.

[0108] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0109] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

Claims

1. A method for locating leak points based on resistance gradient calculation, characterized in that, include: S1, obtain the total resistance value and end resistance value of the leakage sensing rope, and read the preset resistivity parameter per unit length; S2, calculates the distance to the leak point based on the total resistance value, the end resistance value, and the resistivity per unit length parameter; S3, based on the mapping relationship between the length of the sensing rope and the physical location established during the installation and commissioning phase, convert the distance to the leak point into the corresponding 3D coordinates or text description of the physical location. S4 combines physical location information with real-time monitoring data to generate alarm notifications containing specific leak locations and outputs them to the monitoring interface.

2. The method as described in claim 1, characterized in that, S1 includes: S11, the leakage controller periodically collects the voltage and current data at both ends of the sensing rope, and calculates the total resistance value and the end resistance value according to Ohm's law; S12, read the unit length resistivity ρ corresponding to the model of the sensing rope from the preset configuration database. The ρ value is calibrated and stored during the installation and debugging stage according to the material characteristics.

3. The method as described in claim 1, characterized in that, S2 includes: S21, The sliding window algorithm is used to smooth the resistance values ​​of multiple consecutive cycles in order to eliminate the influence of instantaneous interference on the calculation results; S22. The calculated L value is compared with the preset error tolerance range. If it exceeds the error range, a secondary verification mechanism is triggered to re-collect and calculate the distance to the leak point.

4. The method as described in claim 1, characterized in that, S3 includes: S31, Read the starting point coordinates, direction vector and installation path information of the sensing rope from the installation and debugging database, and generate the corresponding 3D coordinates by combining them with the calculated L value; S32, if the sensing rope is not configured with 3D coordinates, the L value is mapped to a specific equipment name, pipeline number or installation area description according to the preset text description table.

5. The method as described in claim 1, characterized in that, Also includes: S5 uses a multi-threading mechanism to establish an independent TCP connection thread for each serial port server and assigns a corresponding device list to each thread to achieve parallel data acquisition and processing. S6: When a thread collects device alarm data, it pushes the data to the alarm processing module and starts the corresponding alarm judgment process according to the alarm type.

6. A leak point location device based on resistance gradient calculation, characterized in that, include: The data acquisition module is used to obtain the total resistance value and end resistance value of the leakage sensing rope, and read the preset resistivity parameter per unit length; The distance calculation module is used to calculate the distance to the leak point based on the total resistance value, the end resistance value, and the resistivity parameter per unit length. The location mapping module is used to convert the distance of the leak point into corresponding 3D coordinates or text descriptions of the physical location based on the mapping relationship between the length of the sensing rope and the physical location established during the installation and commissioning phase. The alarm generation module combines physical location information with real-time monitoring data to generate alarm prompts containing specific leak locations, and outputs them to the monitoring interface.

7. The apparatus as claimed in claim 6, characterized in that, The data acquisition module is also used for: The leakage controller periodically collects voltage and current data at both ends of the sensing rope and calculates the total resistance and end resistance based on Ohm's law. The resistivity ρ per unit length corresponding to the model of the sensing rope is read from the preset configuration database. The ρ value is calibrated and stored during the installation and commissioning stage according to the material characteristics.

8. The apparatus as claimed in claim 6, characterized in that, The distance calculation module is also used for: A sliding window algorithm is used to smooth the resistance values ​​of multiple consecutive cycles in order to eliminate the influence of transient interference on the calculation results. The calculated L value is compared with the preset error tolerance range. If it exceeds the error range, a secondary verification mechanism is triggered to re-collect and calculate the distance to the leak point.

9. The apparatus as claimed in claim 6, characterized in that, The position mapping module is also used for: The starting point coordinates, direction vector, and installation path information of the sensing rope are read from the installation and debugging database, and the corresponding 3D coordinates are generated by combining them with the calculated L value. If the sensing rope is not configured with 3D coordinates, the L value will be mapped to a specific equipment name, pipeline number, or installation area description according to the preset text description table.

10. The apparatus as claimed in claim 6, characterized in that, Also includes: The connection management module is used to establish an independent TCP connection thread for each serial port server through a multi-threaded mechanism, and to allocate a corresponding device list to each thread in order to achieve parallel data acquisition and processing. The data push module is used to push the alarm data collected by a certain thread to the alarm processing module and start the corresponding alarm judgment process according to the alarm type.

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