Intelligent electrically fused pipe fitting with leakage monitoring function, monitoring system and leakage monitoring method

Abstract

The application discloses an intelligent electrically fused pipe fitting with a leakage monitoring function, a monitoring system and a leakage monitoring method. The electrically fused pipe fitting is provided with a monitoring part. A monitoring sensor is installed in the monitoring part. A detection head of the sensor is exposed and flush with the inner wall of the monitoring part. The detection head comprises two electrodes, namely a contact a and a contact b. The monitoring sensor is connected with the monitoring system and is used for monitoring the leakage condition of a butt joint pipeline in the electrically fused pipe fitting in real time. A monitoring signal is sent to an embedded processor of a cloud platform layer through a communication unit for analysis and judgment. According to the analysis result, an alarm instruction or a maintenance instruction is sent to a person in charge, so that the leaking pipe fitting is maintained or the monitoring sensor is replaced and maintained. The application has the advantages of simple structure, high reliability, low-cost water immersion sensor for the core monitoring element, high compatibility of the overall structure with the traditional electrically fused pipe fitting, small change of the production process, limited cost increase and easy industrialization.

Description

Technical Field

[0001] This invention relates to the field of electrofusion pipe fittings technology, and in particular to an intelligent electrofusion pipe fitting with leakage monitoring function, a monitoring system, and a leakage monitoring method. Background Technology

[0002] Electrofusion is a reliable connection method widely used in plastic piping systems. It involves heating a resistance wire embedded in the pipe fitting, melting and fusing the contact surfaces of the fitting and pipe into a single, secure seal. However, over long-term use, factors such as installation quality, material aging, foundation settlement, or external damage can lead to leaks, even initially approved joints. Currently, leaks in buried or concealed pipe joints are often difficult to detect promptly, frequently only becoming apparent when they cause surface dampness, structural damage, or abnormal flow. By then, water wastage, secondary disasters, or significant repair costs may have already occurred.

[0003] Existing pipeline leak monitoring technologies mostly focus on overall monitoring of pipeline pressure and flow, or employ distributed fiber optic sensing technologies. These methods are complex and costly, making it difficult to provide low-cost, accurate condition monitoring for each critical joint. Therefore, there is an urgent need for a device that can be directly integrated into the pipe fitting itself, has a simple structure, high reliability, is easy to maintain, and can provide early leak warnings.

[0004] To address these issues, we designed an intelligent electrofusion fitting with leakage monitoring capabilities, a monitoring system, and a leakage monitoring method. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies where leakage at the electrofusion connection of plastic pipes is difficult to detect in a timely manner. This invention proposes an intelligent electrofusion pipe fitting, monitoring system, and leakage monitoring method with leakage monitoring function. It directly monitors the sealing structure where leakage may occur, and detects leakage in its early stages, thus achieving the goal of early warning and maintenance.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: An intelligent electrofusion fitting with leakage monitoring function is disclosed. Electrofusion wires are installed inside both sides of the fitting. A monitoring section is provided on the top of the fitting, and a monitoring sensor is installed inside the monitoring section. The probe of the monitoring sensor is exposed and flush with the inner wall of the monitoring section. Two probes are provided, namely contact a and contact b, which are two electrode contacts. Contact a and contact b are located on both sides of the lower inner wall of the monitoring section. The monitoring sensor is connected to a monitoring system to perform the task of monitoring leakage of the electrofusion fitting.

[0007] More preferably, the electro-fusion wire includes a main electro-fusion wire and an external electro-fusion wire. Both the main electro-fusion wire and the external electro-fusion wire are spirally arranged inside the electro-fusion fitting. One end of the main electro-fusion wire is connected to a main electro-fusion interface, and one end of the external electro-fusion wire is connected to an external electro-fusion interface. The main electro-fusion interface and the external electro-fusion interface are respectively located outside the electro-fusion fitting on both sides of the monitoring unit.

[0008] More preferably, the weld formed by welding the main electrofusion wire to the outer pipe is the main sealing weld, the weld formed by welding the outer electrofusion wire to the outer pipe is the outer sealing weld, and the closed annular monitoring cavity formed between the main sealing weld and the outer sealing weld is the monitoring unit.

[0009] More preferably, the monitoring sensor is a water immersion sensor, which is fixedly installed inside the pipe wall of the monitoring unit.

[0010] More preferably, the contacts a and b of the probe are connected to the monitoring sensor via signal leads. One end of the signal lead is connected to the contacts a and b and then laid along a U-shaped channel on the inner surface of the monitoring part, passing through a sealing joint and connecting to the monitoring sensor.

[0011] Secondly, this invention proposes a monitoring system applied to the aforementioned intelligent electrofusion pipe fitting with leakage monitoring function. The monitoring system comprises a three-layer architecture consisting of a sensing layer, a transmission layer, and a platform layer, including: The sensing layer employs a signal processing unit to receive monitoring signals from a monitoring sensor embedded in the electrofusion fitting. The signal processing unit is connected to the monitoring sensor, receives the monitoring signals, and performs analog-to-digital conversion. The transmission layer establishes a connection with the signal processing unit and transmits the monitoring signal to the cloud platform layer for processing through the communication unit; The cloud platform layer uses embedded processors and storage units to analyze monitoring signals, store monitoring results, and issue alarm commands.

[0012] More preferably, the signal processing unit is configured to operate in dual modes as follows: In the sleep monitoring mode, the signal processing unit controls the communication unit to be in a deep sleep state, and polls the resistance value between the two probes of the monitoring sensor in a low-frequency pulse manner. When the reporting mode is activated, if the resistance value of the monitoring sensor is lower than a preset threshold and water immersion is determined, the signal processing unit immediately wakes up the communication unit, establishes a TCP connection, and sends a data packet containing a timestamp, the device ID of the monitoring sensor, and an alarm signal.

[0013] In a further preferred embodiment, in the sleep monitoring mode, the signal processing unit automatically wakes up the communication unit at preset time intervals, sends a heartbeat data packet to the cloud platform layer, and stores the data packet in the storage unit. The heartbeat data packet includes at least the online status indicator of the monitoring sensor, the remaining battery voltage value, the wireless signal strength, the ambient temperature data, and the running time since the last alarm.

[0014] More preferably, the cloud platform layer employs an embedded processor and storage unit to analyze monitoring signals and store monitoring results, and issue alarm commands, including: Decrypt and format-verify the received monitoring signal messages; Based on the battery voltage change curve in historical heartbeat data, a linear regression model is used to predict the remaining battery life. When there is an abnormal downward trend in battery voltage, a replacement warning is generated and sent to managers at different levels via SMS, APP push, email, or audible and visual alarms.

[0015] Thirdly, the present invention proposes a leakage monitoring method based on the monitoring system, the leakage monitoring method comprising the following steps: S1, System power-on initialization, the signal processing unit reads the parameters of the deployed monitoring sensors, performs a full-function self-test and sends the first online packet to the cloud platform layer; S2, normal monitoring, the system enters a low-power sleep state every [time period]. The time-wake-up signal processing unit polls the resistance value between the two probes of the monitoring sensor. If the resistance value is higher than the threshold Continue in low-power sleep mode; S3, alarm triggered, if the resistance value between the two probes is detected. Below the threshold If the leak is determined to be from the electrofusion fitting, immediately perform the following actions: Mark the current time as the alarm start time, wake up the communication unit, establish a TCP connection, and send a data packet containing the alarm signal. The data packet content includes the device ID of the monitoring sensor, the alarm type, and the alarm time. At the same time, the data packet information is stored in the storage unit. S4, heartbeat maintenance: if no alarm is triggered, the counter accumulates. When the preset period is reached, the communication unit is woken up to send a heartbeat data packet to update the status of the monitoring sensor device and battery information. S5, cloud-based decision-making: The cloud platform layer receives monitoring signal data. If it is alarm data, it immediately triggers an alarm command and records the accident file, generating a maintenance work order. If it is heartbeat data, it updates the health status of the monitoring sensors. If an abnormal downward trend in battery voltage is detected, a maintenance work order is generated.

[0016] Compared with existing technologies, the advantages of this invention are: It offers real-time and accurate monitoring, directly monitoring the periphery of the potentially leaking sealing structure. This allows for early detection of leaks before the medium spreads to the external environment, providing the earliest possible warning and precise location. Active monitoring and integration embed the monitoring function directly into standard connection components, creating an intelligent pipe fitting without the need for additional complex monitoring equipment, facilitating its adoption in new construction or renovation projects. Dual sealing and fail-safe features ensure that the external sealing weld not only forms the monitoring unit but also constitutes a second sealing barrier. Even if the main seal fails, it can prevent further leakage to a certain extent, improving the safety redundancy of the intelligent electrofusion pipe fitting. The monitoring unit's design ensures that the monitoring sensor is only sensitive to leaks between the two welds, avoiding false alarms caused by external moisture or accidental water splashes. This invention has a simple structure, high reliability, and the core monitoring element can use a simple and reliable water immersion sensor. The overall structure is highly compatible with traditional electrofusion pipe fittings, requires minimal changes to the production process, has limited cost increases, and is easy to industrialize. Maintenance is convenient. The health status of the joint can be monitored remotely through electrical signals without excavation or manual inspection, which greatly reduces operation and maintenance costs. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the overall structure of the intelligent electrofusion fitting with leakage monitoring function proposed in this invention. Figure 2 This is a partial cross-sectional schematic diagram of the intelligent electrofusion fitting with leakage monitoring function proposed in this invention; Figure 3 This is a schematic diagram showing the relationship between the position of the electrofusion wire and the monitoring unit of the intelligent electrofusion fitting with leakage monitoring function proposed in this invention; Figure 4 This is a partial cross-sectional schematic diagram of the monitoring section of the intelligent electrofusion fitting with leakage monitoring function proposed in this invention; Figure 5 This is a schematic diagram showing the connection between the monitoring sensor and the probe of the intelligent electrofusion fitting with leakage monitoring function proposed in this invention; Figure 6 This is a block diagram of the monitoring system for the intelligent electrofusion fitting proposed in this invention; Figure 7 This is a schematic diagram of the leakage monitoring method proposed in this invention.

[0018] The following are the labels in the diagram: 1. Electrofusion fitting; 2. Monitoring unit; 3. Main electrofusion wire; 4. Main electrofusion interface; 5. External electrofusion wire; 6. External sealing weld; 7. External electrofusion interface; 8. Main sealing weld; 9. Equipment compartment; 10. Signal lead; 11. Sealing strip; 21. Monitoring sensor; 211. Probe head. Detailed Implementation

[0019] 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.

[0020] To address the problem of real-time and accurate monitoring of pipe joint leakage in existing technologies, this invention provides an intelligent electrofusion fitting with leakage monitoring capabilities. This intelligent electrofusion fitting, based on standard electrofusion connection functions, is equipped with a leakage monitoring sensor and system. It can detect and signal leakage occurring immediately upon it happening inside the electrofusion fitting joint, thereby providing timely early warning and preventing the leakage from escalating.

[0021] Reference Figures 1-5 The intelligent electrofusion fitting with leakage monitoring function proposed in this invention has electrofusion wires installed inside both sides of the fitting 1. A monitoring part 2 is set on the top of the fitting 1, and a monitoring sensor 21 is installed inside the monitoring part 2. The probe head 211 of the monitoring sensor 21 is exposed and flush with the inner wall of the monitoring part 2. It should be noted that there are two probe heads 211 in this invention, namely contact a and contact b, which are two electrode contacts. Contact a and contact b are located on both sides of the lower inner wall of the monitoring part 2, preferably at the bottom of the monitoring part 2, so that any leakage can be detected in time. The monitoring sensor 21 is connected to the monitoring system. The monitoring sensor 21 monitors in real time whether there is any leakage of the conveying medium inside the electrofusion fitting 1 and transmits the monitoring signal to the monitoring system, thereby performing the task of monitoring leakage of the electrofusion fitting 1.

[0022] The electrofusion fitting 1 has a socket for inserting an external pipe, and its structure is similar to that of a conventional electrofusion fitting, used to accommodate the end of the pipe to be connected.

[0023] The electrofusion fitting 1 includes a main electrofusion wire 3 and an external electrofusion wire 5, which are respectively located on both sides of the monitoring section 2. Both the main electrofusion wire 3 and the external electrofusion wire 5 are spirally arranged inside the electrofusion fitting 1. One end of the main electrofusion wire 3 is connected to the main electrofusion interface 4, and one end of the external electrofusion wire 5 is connected to the external electrofusion interface 7. The main electrofusion interface 4 and the external electrofusion interface 7 are respectively located on the outside of the electrofusion fitting 1 on both sides of the monitoring section 2.

[0024] The weld formed by welding the main electrofusion wire 3 to the external pipe is the main sealing weld 8, and the weld formed by welding the external electrofusion wire 5 to the external pipe is the external sealing weld 6. Between the main sealing weld 8 and the external sealing weld 6, a closed annular monitoring cavity is formed around the pipeline, which is the monitoring section 2.

[0025] The main electrofusion wire 3 is coiled and positioned at a predetermined position (usually the middle) on the inner wall of the electrofusion fitting 1. Power is supplied to the main electrofusion wire 3 through the main electrofusion interface 4. After being energized, the main electrofusion wire 3 heats up and melts the contact surface between the outer pipe and the electrofusion fitting 1, thereby achieving the connection of the main sealing structure. The weld formed at this time is the main sealing weld 8.

[0026] The external sealing fusion structure has multiple turns of external electrofusion wire 5 spirally arranged on the outer circumferential surface of the electrofusion fitting 1, generally near its end. When the outer pipe is inserted into place, power is supplied to the external electrofusion wire 5 through the external electrofusion interface 7, heating the external electrofusion wire 5 and fusing the inner wall of the socket of the electrofusion fitting 1 with the outer wall of the outer pipe, thereby forming an annular external sealing weld (a secondary sealing structure corresponding to the main sealing structure) between the inner wall of the electrofusion fitting 1 and the outer wall of the outer pipe. The weld formed in this state is the external sealing weld 6.

[0027] The external sealing weld 6, the inner wall of the electrofusion fitting 1, the outer wall of the outer pipe, and the main sealing weld 8 located further inside together define a closed, annular monitoring cavity surrounding the pipe, which is the aforementioned monitoring part 2, located on the periphery of the main sealing structure.

[0028] The monitoring sensor 21 is a water immersion sensor, which is fixedly installed inside the pipe wall of the monitoring section 2. The monitoring sensor 21 can be fixed in the equipment compartment 9 of the monitoring section 2 by means of a slot, adhesive, or pre-embedding. The two sides of the equipment compartment 9 are sealed with sealing strips 11 to prevent the external environment, especially external moisture, from entering the equipment compartment 9 and interfering with the monitoring accuracy of the monitoring sensor 21, ensuring long-term sealing and vibration resistance. The contacts a and b of the probe head 211 are connected to the monitoring sensor 21 through signal leads 10. One end of the signal lead 10 is connected to contacts a and b and then laid along a U-shaped channel pre-set on the inner surface of the monitoring section 2, passing through the sealing joint and connecting to the monitoring sensor 21. The monitoring sensor 21 is connected to the monitoring system for real-time monitoring of leakage in the connected pipe inside the electrofusion fitting 1.

[0029] The leakage monitoring principle of sensor 21 is: When the pipeline system is operating normally and the joints are intact, the main sealing weld 8 effectively prevents the transported medium (water) from leaking out. At this time, the monitoring unit 2 remains dry, and the probe 211 of the monitoring sensor 21 is in a water-free state (e.g., high resistance / open state). Because the monitoring unit 2 is dry, according to the resistance formula... The resistance value between contact a and contact b At its maximum, the current signal is almost undetectable. If the main sealing weld 8 is defective and causes leakage of the conveying medium, the leaked water will first be confined to the monitoring section 2 between the main sealing weld 8 and the external sealing weld 6. As water accumulates, the probe 211 of the monitoring sensor 21 inside the monitoring section 2 will be wetted. When liquid (water) seeps into the monitoring section 2 and contacts contacts a and b, the electrical characteristics between the contacts (such as a decrease in resistance or a conductive state) will change significantly. The liquid acts as a conductor between the contacts, forming a conductive circuit between them. At this time, a current signal can be detected, indicating that liquid leakage has occurred at the fusion joint of the electrofusion fitting 1. The monitoring system receives the change in the monitoring signal, immediately issues an alarm command, notifies and records the fault location, and prompts maintenance personnel to handle it in a timely manner.

[0030] Reference Figure 6 In another implementation scenario, the present invention proposes a monitoring system for application to the aforementioned intelligent electrofusion pipe fittings with leakage monitoring function, thereby improving the level of intelligent monitoring of the intelligent electrofusion pipe fittings.

[0031] The monitoring system consists of a three-layer architecture: a sensing layer, a transmission layer, and a platform layer. The sensing layer uses a signal processing unit to receive monitoring signals from the monitoring sensor 21 embedded in the electrofusion fitting 1. The signal processing unit is connected to the monitoring sensor 21, receives the monitoring signals, and performs analog-to-digital conversion.

[0032] The transmission layer establishes a connection with the signal processing unit and transmits the monitoring signal to the cloud platform layer for processing through the communication unit. The communication unit adopts NB-IoT low-power wide area network wireless transmission technology and has a built-in TCP / IP protocol stack to leverage its low-power function.

[0033] The cloud platform layer uses embedded processors and storage units to analyze monitoring signals, store monitoring results, and issue alarm commands.

[0034] Understandably, the monitoring system is also equipped with batteries to provide power to the various electrical devices.

[0035] The signal processing unit can employ an embedded MCU, such as the STM32L4 series or ESP32-C3, featuring ultra-low power consumption and optional expansion. It periodically samples and detects contact resistance values ​​to determine if water leakage has occurred in monitoring unit 2, and controls the power on / off of the NB-IoT communication unit to save power. The signal processing unit is configured for dual-mode operation as follows: In the sleep monitoring mode, the signal processing unit controls the communication unit to be in a deep sleep state and polls the resistance value between the two probes 211 of the monitoring sensor 21 using low-frequency pulses. When the reporting mode is activated, if the resistance value of the monitoring sensor 21 is lower than the preset threshold and is determined to be water immersion, the signal processing unit immediately wakes up the communication unit, establishes a TCP connection and sends a data packet containing a timestamp, the device ID of the monitoring sensor 21 and an alarm signal.

[0036] In sleep monitoring mode, the signal processing unit automatically wakes up the communication unit at preset time intervals, sends heartbeat data packets to the cloud platform layer, and stores the data packets in the storage unit. The heartbeat data packets contain at least the online status indicator of the monitoring sensor 21, the remaining battery voltage value, the wireless signal strength, the ambient temperature data, and the running time since the last alarm.

[0037] At the cloud platform layer, an embedded processor and storage unit analyze monitoring signals and store monitoring results, and issue alarm commands. Monitoring signals are sent to the embedded processor via a communication unit for analysis and judgment. Based on the analysis results, alarm commands or maintenance commands are sent to the responsible personnel to facilitate repair of leaking pipe fittings or replacement and maintenance of monitoring sensors. The embedded processor performs the following operations: Decrypt and format-verify the received monitoring signal messages; Based on the battery voltage change curve in historical heartbeat data, a linear regression model is used to predict the remaining battery life. When there is an abnormal downward trend in battery voltage, a replacement warning is generated. According to the severity of leakage and the importance of pipelines, notifications are sent to managers at different levels via SMS, APP push, email or audible and visual alarms.

[0038] The following methods are used to decrypt and verify the format of the monitoring signal messages: 1. Message encryption and authentication mechanism: To prevent data from being eavesdropped on, tampered with, or forged, a combination of symmetric encryption and message authentication codes is used.

[0039] Each monitoring sensor 21 is programmed with a unique device ID and MasterKey (128 bits) at the factory. The MasterKey is encrypted and stored in a high-density database in the storage unit, and plaintext hardcoding in the code is strictly prohibited. The actual data (such as water leakage status, battery voltage status) is encrypted using the MasterKey and a vector generated by a random number or an incrementing counter using AES.

[0040] 2. Cloud-based decryption: Extract the device ID of monitoring sensor 21 and read the device ID from the report text area.

[0041] The key is retrieved by querying the corresponding MasterKey from the high-density database based on the device ID. If not found, it is discarded and an unauthorized access is logged.

[0042] The original text data is decrypted using symmetric encryption (AES-128-CBC) on the AES-encrypted real data using the MasterKey and a random number or an incrementing counter.

[0043] After successful decryption, schema verification can be used to enter a strict format validation stage: Verify that all required fields exist and verify the message data type (e.g., battery voltage must be a number, not a string).

[0044] Verify whether dev_id conforms to the preset format, verify the timestamp format, check whether type is a predefined type, and check whether leak_status is only 0 or 1.

[0045] Battery voltage must be within a physically feasible range (e.g., 2.0V -4.2V). A reading of 50V or -1V indicates a sensor malfunction or data error, and should be marked as abnormal data rather than normal business data. Signal strength is typically between -120dBm and -30dBm; readings outside this range are considered invalid.

[0046] Intelligent electrofusion fitting monitoring nodes are typically deployed in enclosed underground environments, making battery replacement extremely costly. By collecting historical heartbeat data, including battery voltage change curves, current pulses, temperature, and timestamps, a linear regression model is constructed to predict the remaining battery life, accurately predict battery voltage decline trends, calculate the remaining usable days, and generate replacement alerts when abnormal battery voltage decline trends are observed, thus generating replacement work orders in advance.

[0047] Historical heartbeat records for each monitoring sensor 21 are extracted from the time-series database of the cloud platform layer. The historical heartbeat records include data reporting timestamps, battery load voltage, peak operating current, ambient temperature, and cumulative wake-up counts.

[0048] Because fluctuations in underground environmental temperature and the strength of communication signals can affect instantaneous voltage readings, directly fitting the original data results in a large error. Therefore, it is necessary to process historical heartbeat records by using outlier removal, temperature normalization, and moving average filtering.

[0049] Use the 3-Sigma principle or the isolated forest algorithm to remove noise caused by sudden voltage drops due to strong instantaneous interference.

[0050] Using the Arrhenius equation or empirical formulas, all voltage values ​​are corrected to the equivalent voltage at standard temperature. : ; in, The original observed voltage (measured value) includes temperature noise and instantaneous load fluctuations, reflecting the current true operating voltage state of the monitoring sensor 21. For the temperature coefficient, a value of 0.002v / ℃ can be selected. This indicates the standard reference temperature, which can be set to 25℃. This indicates the ambient temperature at the time of monitoring.

[0051] Moving average filtering uses a weighted moving average to calculate the heartbeat voltage over multiple consecutive cycles, eliminating random fluctuations and creating a smooth voltage change curve.

[0052] Construct a univariate linear regression model to predict the remaining battery capacity: ; In the formula, Indicates the discharge rate. For battery life, This indicates the battery's reference voltage level, i.e., the remaining battery capacity.

[0053] The input variable is time. The output variable is the equivalent voltage. ; The slope can be calculated using the least squares method based on historical heartbeat records. and intercept .

[0054] Set the battery failure threshold voltage to The predicted remaining battery life is: ; in, This is the latest smoothed voltage value. By predicting the remaining battery life, the lifespan of the monitoring sensor 21 can be predicted, thereby enabling intelligent management and efficient operation and maintenance of the smart electrofusion fitting.

[0055] like Figure 7 As shown, in another implementation scenario, the present invention proposes a leakage monitoring method based on the above-mentioned monitoring system, which includes the following steps: S1, the system powers on and initializes. The signal processing unit reads the parameters of the deployed monitoring sensor 21, performs a full-function self-test, and sends the first online packet to the cloud platform layer. S2, normal monitoring, the system enters a low-power sleep state every [time period]. The time-wake-up signal processing unit polls the resistance value between the two probes 211 of the monitoring sensor 21. If the resistance value is higher than the threshold Continue in low-power sleep mode; S3, alarm triggered, if the resistance value between the two detector heads 211 is detected. Below the threshold threshold The threshold value can be determined based on the general resistance of the liquid medium being transported. For example, when transporting conventional tap water, the threshold value is... The resistivity of tap water can be selected as a reference, approximately 14.3-33.3. The settings are configured, and if a leak is detected in electrofusion fitting 1, the following actions will be taken immediately: Mark the current time as the alarm start time, wake up the communication unit, establish a TCP connection, and send a data packet containing the alarm signal to the cloud platform layer. The data packet content includes the device ID of the monitoring sensor 21, the alarm type, and the alarm time. At the same time, the data packet information is stored in the storage unit. S4, heartbeat maintenance: if no alarm is triggered, the counter accumulates. When the preset period is reached, the communication unit is woken up to send a heartbeat data packet and update the status and battery information of the monitoring sensor 21. S5, cloud-based decision-making: The cloud platform layer receives monitoring signal data. If it is alarm data, it immediately triggers an alarm command and records an accident file, generates a maintenance work order, pushes a notification to the responsible person, and records a log for permanent archiving. If it is heartbeat data, it updates the health status of monitoring sensor 21. If an abnormal downward trend in battery voltage is detected, it generates a maintenance work order and replaces or maintains monitoring sensor 21.

[0056] It should be noted that any parts not covered in this invention are the same as or can be implemented using existing technology. The above description is merely a preferred embodiment of this invention, but the scope of protection of this invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in this invention, based on the technical solution and inventive concept of this invention, should be covered within the scope of protection of this invention.

Claims

1. An intelligent electrofusion fitting with leakage monitoring function, wherein electrofusion wires are installed inside both sides of the electrofusion fitting (1), characterized in that, A monitoring section (2) is provided on the upper part of the electrofusion fitting (1). A monitoring sensor (21) is provided inside the monitoring section (2). The probe (211) of the monitoring sensor (21) is exposed and flush with the inner wall of the monitoring section (2). Two probes (211) are provided, namely contact a and contact b. Contact a and contact b are located on both sides of the lower inner wall of the monitoring section (2). The monitoring sensor (21) is connected to the monitoring system to perform the task of monitoring the leakage of the electrofusion fitting (1).

2. The intelligent electrofusion fitting with leakage monitoring function according to claim 1, characterized in that, The electro-fusion wire includes a main electro-fusion wire (3) and an external electro-fusion wire (5). Both the main electro-fusion wire (3) and the external electro-fusion wire (5) are spirally arranged inside the electro-fusion fitting (1). One end of the main electro-fusion wire (3) is connected to the main electro-fusion interface (4), and one end of the external electro-fusion wire (5) is connected to the external electro-fusion interface (7). The main electro-fusion interface (4) and the external electro-fusion interface (7) are respectively located on the outside of the electro-fusion fitting (1) on both sides of the monitoring unit (2).

3. The intelligent electrofusion fitting with leakage monitoring function according to claim 2, characterized in that, The weld formed by welding the main electrofusion wire (3) to the outer pipe is the main sealing weld (8), and the weld formed by welding the outer electrofusion wire (5) to the outer pipe is the outer sealing weld (6). The closed annular monitoring cavity formed between the main sealing weld (8) and the outer sealing weld (6) is the monitoring part (2).

4. The intelligent electrofusion fitting with leakage monitoring function according to claim 3, characterized in that, The monitoring sensor (21) is a water immersion sensor, which is fixedly installed inside the pipe wall of the monitoring unit (2).

5. The intelligent electrofusion fitting with leakage monitoring function according to claim 1, characterized in that, The contacts a and b of the probe (211) are connected to the monitoring sensor (21) via signal leads (10). One end of the signal lead (10) is connected to the contacts a and b and then laid along a U-shaped channel on the inner surface of the monitoring part (2), passing through a sealing joint and connecting to the monitoring sensor (21).

6. A monitoring system applied to intelligent electrofusion pipe fittings with leakage monitoring function as described in claims 1-5, characterized in that, The monitoring system consists of a three-layer architecture: a sensing layer, a transmission layer, and a platform layer, including: The sensing layer uses a signal processing unit to receive the monitoring signal from the monitoring sensor (21) embedded in the electrofusion fitting (1). The signal processing unit is connected to the monitoring sensor (21), receives the monitoring signal and performs analog-to-digital conversion. The transmission layer establishes a connection with the signal processing unit and transmits the monitoring signal to the cloud platform layer for processing through the communication unit; The cloud platform layer uses embedded processors and storage units to analyze monitoring signals, store monitoring results, and issue alarm commands.

7. The monitoring system according to claim 6, characterized in that, The signal processing unit is configured to operate in dual modes as follows: In the sleep monitoring mode, the signal processing unit controls the communication unit to be in a deep sleep state and polls the resistance value between the two probes (211) of the monitoring sensor (21) in a low-frequency pulse manner. When the reporting mode is activated, if the resistance value of the monitoring sensor (21) is lower than the preset threshold and is determined to be water immersion, the signal processing unit immediately wakes up the communication unit, establishes a TCP connection and sends a data packet containing a timestamp, the device ID of the monitoring sensor (21) and an alarm signal.

8. The monitoring system according to claim 7, characterized in that, In the sleep monitoring mode, the signal processing unit automatically wakes up the communication unit at a preset time interval, sends a heartbeat data packet to the cloud platform layer, and stores the data packet in the storage unit. The heartbeat data packet includes at least the online status identifier of the monitoring sensor (21), the remaining battery voltage value, the wireless signal strength, the ambient temperature data, and the running time since the last alarm.

9. The monitoring system according to claim 6, characterized in that, The cloud platform layer employs embedded processors and storage units to analyze monitoring signals and store monitoring results, and issues alarm commands, including: Decrypt and format-verify the received monitoring signal messages; Based on the battery voltage change curve in historical heartbeat data, a linear regression model is used to predict the remaining battery life. When there is an abnormal downward trend in battery voltage, a replacement warning is generated and sent to managers at different levels via SMS, APP push, email, or audible and visual alarms.

10. A leakage monitoring method based on the monitoring system according to any one of claims 6-9, characterized in that, Includes the following steps: S1, the system is powered on and initialized. The signal processing unit reads the parameters of the deployed monitoring sensor (21), performs a full-function self-test, and sends the first online packet to the cloud platform layer. S2, normal monitoring, the system enters a low-power sleep state every [time period]. The time-wake-up signal processing unit polls the resistance value between the two probes (211) of the monitoring sensor (21). If the resistance value is higher than the threshold Continue in low-power sleep mode; S3, alarm triggered, if the resistance value between the two probes (211) is... Below the threshold The leak was determined to be in the electrofusion fitting (1). Immediately perform the following actions: Mark the current time as the alarm start time, wake up the communication unit, establish a TCP connection, and send a data packet containing the alarm signal. The data packet content includes the device ID of the monitoring sensor (21), the alarm type, and the alarm time. At the same time, the data packet information is stored in the storage unit. S4, heartbeat maintenance. If no alarm is triggered, the counter is incremented. When the preset period is reached, the communication unit is woken up to send a heartbeat data packet and update the monitoring sensor (21) device status and battery information. S5, cloud-based decision-making: The cloud platform layer receives data from monitoring signals. If the data is alarm data, it immediately triggers an alarm command, records the accident file, and generates a maintenance work order. If the data is heartbeat, update the health status of the monitoring sensor (21). If an abnormal downward trend in battery voltage is found, generate a maintenance work order.

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