Self-powered intelligent sensing PVC drainage pipe system based on piezoelectric energy harvesting

Abstract

The application discloses a self-powered intelligent sensing PVC drainage pipe system based on piezoelectric energy harvesting, relates to the cross technical field of high polymer materials and intelligent infrastructure, and comprises a pipe body module, an energy collection module, a sensing network and a data processing unit.The pipe body module is composed of a plurality of pipe body monomers, each pipe body monomer is a three-layer gradient composite structure, and the layers are connected through buckles.The energy collection module is used for collecting water flow vibration energy under different flow rates and storing the water flow vibration energy.The sensing network is used for monitoring the pipeline strain, corrosion and flow state in the pipe body monomer in real time.The data processing unit is used for realizing real-time monitoring, early warning and health prediction of the pipe body monomer state.The self-powered intelligent sensing PVC drainage pipe system based on piezoelectric energy harvesting can efficiently convert water flow kinetic energy into electric energy, realize real-time monitoring of all parameters of the pipeline, and improve portability and universality through modular structure design, and is suitable for different pipe diameters and medium scenes.

Description

Technical Field

[0001] This invention relates to the field of interdisciplinary technology of polymer materials and smart infrastructure, and in particular to a self-powered smart sensing PVC drainage pipe system based on piezoelectric energy harvesting. Background Technology

[0002] Traditional PVC drainage pipes hold over 60% of the global drainage pipe market share due to advantages such as readily available raw materials, low processing costs, and superior corrosion resistance compared to metal pipes. However, they have significant drawbacks in the upgrading of intelligent infrastructure: 1. Lagging condition monitoring In municipal underground pipe networks, 30% of the pipes are buried at a depth of more than 2 meters. Manual inspection requires the use of pipe robots or road excavation, and the troubleshooting cycle is 1-3 months, which is costly. Building drainage pipes are hidden in walls or ceilings, and leakage problems are only discovered after the walls become moldy and water seeps into the floors below. The repair costs for a single household are high and the repair cycle is long, which seriously affects the lives of the residents.

[0003] 2. External power supply dependency In municipal pipeline networks, the cost of mains power cabling for monitoring devices is 30,000 to 50,000 yuan per kilometer. The damp underground environment (relative humidity exceeding 85%) can easily lead to short circuits in the lines, and the annual maintenance cost accounts for 15-20% of the total investment. In high-rise buildings with more than 30 floors, solar power supply is affected by shading, and the power generation in winter is only 30-40% of that in summer. Backup lithium batteries (costing 800-1200 yuan per battery and with a lifespan of 3-5 years) are required, which increases the complexity and cost of the system.

[0004] 3. Waste of energy resources The water flow velocity in municipal drainage pipes varies with pipe diameter (DN300 pipe: 0.8-1.2 m / s; DN600 pipe: 1.2-1.8 m / s), with a flow rate of 0.5 m³ / s for DN400 pipes. 3 For example, each kilometer of water flow carries about 200W of kinetic energy, and the energy wasted annually is equivalent to 150 kilowatt-hours of electricity; the flow velocity of wastewater pipes in industrial parks reaches 2.5-3.0 m / s, making the energy waste even more prominent.

[0005] 4. Limited structural lifespan Traditional PVC pipes are susceptible to damage from water flow (wear rate increases 3-5 times when sediment content exceeds 5%), soil pressure (approximately 30 kPa at a depth of 3 meters underground), and temperature changes (from -10℃ to 60℃), which can easily cause micro-cracks of 0.05-0.1 mm. Without monitoring, the actual lifespan of pipes is only 15-20 years, which is 25-50% shorter than the designed lifespan (20-30 years). The cost of replacing them prematurely accounts for 20-30% of the municipal maintenance budget.

[0006] Therefore, there is an urgent need for an integrated solution that combines "self-sufficiency in energy supply, intelligent sensing, and durable structure". Summary of the Invention

[0007] The purpose of this invention is to provide a self-powered intelligent sensing PVC drainage pipe system based on piezoelectric energy harvesting, which can efficiently convert water flow energy into electrical energy, realize real-time monitoring of all pipe parameters, and improve portability and versatility through modular structural design, adapting to different pipe diameters and media scenarios.

[0008] To achieve the above objectives, the present invention provides a self-powered intelligent sensing PVC drainage pipe system based on piezoelectric energy harvesting, comprising: The tube module consists of several tube units, each of which is a three-layer gradient composite structure. The layers are connected by snap-fit, and the length is 0.5m or 1m. An energy harvesting module is used to collect and store the vibrational energy of water flow at different flow rates. Sensor networks are used to monitor pipe strain, corrosion, and flow status within individual pipe units in real time. The data processing unit is used to realize real-time monitoring, early warning and health prediction of the individual pipe body status.

[0009] Preferably, the tube body consists of an inner wear-resistant tube, a middle piezoelectric sleeve disposed on the outer layer of the inner wear-resistant tube, and a replaceable protective sleeve disposed on the outer layer of the middle piezoelectric sleeve, wherein an energy management box is disposed on the outer side of the replaceable protective sleeve.

[0010] Preferably, the inner wear-resistant tube contains 8wt%-12wt% silicon carbide micro powder (particle size 5-10μm) and 2wt%-3wt% polytetrafluoroethylene micro powder, as well as microcapsule self-healing agent. The inner wall adopts a biomimetic shark skin texture, in which the diameter of the protrusions is 0.2mm-0.3mm and the spacing is 0.5mm. The middle piezoelectric sleeve is divided into a high-sensitivity layer and a high-energy storage layer along the radial direction of the tube body. The high-sensitivity layer contains PZT-5H piezoelectric ceramic fibers with a diameter of 30μm-50μm and a volume ratio of 40%. The high-energy storage layer contains PVDF-TrFE copolymer with a volume ratio of 60%. The high-sensitivity layer and the high-energy storage layer are composited by a coupling agent. The replaceable protective sleeves include three types: anti-seepage protective sleeve, lightweight protective sleeve, and acid and alkali resistant protective sleeve. The anti-seepage protective sleeve contains 3wt%-5wt% anti-seepage agent.

[0011] Preferably, a spiral guide groove is embedded in the inner wall of the pipe body, with a groove depth of 0.5mm-1.2mm and a spiral angle of 30°-60°, to guide water flow and enhance the vortex-induced vibration effect.

[0012] Preferably, the energy harvesting module includes a piezoelectric unit, an energy management circuit, and an energy storage unit. The piezoelectric unit is arranged in a 120° spiral along the inner wall of the tube unit and is fixed to the inner wall of the tube unit by an arc-shaped magnetic sheet and a plastic clip. The management rules of the energy management circuit are as follows: when the water flow velocity is in a steady state, i.e., the water flow velocity is 0.8m / s-2m / s, the perturbation observation method is adopted; when the water flow velocity is in a fluctuating state, i.e. the water flow velocity is >2m / s or <0.8m / s, the incremental conductivity method is switched; and an AI adaptive energy management algorithm is introduced, which predicts the flow velocity change trend based on historical water flow data and real-time sensor feedback, and dynamically adjusts the energy harvesting mode and energy storage distribution strategy through a lightweight neural network. The energy storage unit includes supercapacitors and micro batteries housed in an energy management box.

[0013] Preferably, the sensor network consists of a strain sensing array, a corrosion monitoring sensor assembly, and a flow monitoring assembly integrated in the piezoelectric unit; The strain sensing array is based on resistance strain gauges, with 3-5 monitoring points per meter of pipe to detect pipe deformation and external loads; The corrosion monitoring component includes a pH sensor and an ultrasonic thickness sensor, used to monitor pipe wall corrosion and wear. The flow monitoring component calculates the flow velocity by using the piezoelectric output frequency, with a measurement range of 0.1 m / s to 5 m / s.

[0014] Preferably, the data processing unit includes an integrated microcontroller (MCU) for data processing and a LoRa module for wireless transmission, both disposed in the energy management box.

[0015] Preferably, the signal output terminal of the sensor network is electrically connected to the signal input terminal of the MCU via an I2C / SPI bus, and the wireless signal terminal of the MCU is communicatively connected to the UART terminal of the LoRa module.

[0016] Therefore, the present invention employs the above-mentioned self-powered intelligent sensing PVC drainage pipe system based on piezoelectric energy harvesting, which has the following beneficial effects: (1) Through the resonance matching of the spiral guide channel and the gradient piezoelectric material design of the pipe module, the power generation per meter of pipe reaches 6.5-8mW (flow velocity 1.5m / s, which is 40-50% higher than the traditional 3.8-5.2mW), and it can still provide stable power supply when the flow velocity fluctuates (0.5-3m / s), thus solving the problem of external power supply dependence; (2) The addition of blockage warning and medium composition monitoring improves the warning accuracy of the five-dimensional sensor network, and the self-cleaning function reduces the monitoring error rate, avoiding misjudgment caused by contamination of traditional sensors. (3) Replaceable protective cover and high temperature resistant piezoelectric unit, suitable for municipal, building and industrial park scenarios; media composition monitoring supports industrial wastewater parameter identification, which expands the application scope compared to traditional systems that are only applicable to rainwater and sewage. (4) No external power supply or wiring is required, reducing annual maintenance costs; modular replacement reduces overall replacement costs; microcapsule self-healing agents reduce manual maintenance intervention and extend the actual life of the pipeline; (5) AI adaptive energy management improves the intelligence level of the system. By predictively adjusting the energy collection and distribution strategy, it improves the energy utilization efficiency and adapts to seasonal flow rate changes, ensuring stable power supply throughout the year. Furthermore, based on the pipeline health prediction model of edge computing, it issues maintenance warnings 3-6 months in advance, increases the proportion of planned maintenance, and reduces the rate of sudden failures.

[0017] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the overall structure of a self-powered intelligent sensing PVC drainage pipe system based on piezoelectric energy harvesting according to the present invention. Figure 2 This is an embodiment of the invention showing the arrangement of the spiral guide groove and the piezoelectric unit; Figure 3 This is a partial schematic diagram of the cross-section of a single tube body according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the energy management box according to an embodiment of the present invention; Figure 5 This is a flowchart of the AI ​​adaptive energy management algorithm according to an embodiment of the present invention; Figure Labels 1. Inner wear-resistant tube; 2. Middle piezoelectric sleeve; 3. Replaceable protective sleeve; 4. Piezoelectric unit; 5. Energy management box; 6. Supercapacitor; 7. Integrated microcontroller; 8. LoRa module. Detailed Implementation

[0019] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0020] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0021] Example Please see Figures 1-4 This invention provides a self-powered intelligent sensing PVC drainage pipe system based on piezoelectric energy harvesting, comprising: The tube module consists of several individual tube units, each with a three-layer gradient composite structure. It employs a gradient design of "inner layer for wear resistance and reinforcement, middle layer for piezoelectric energy storage, and outer layer for protection and adaptation." Each layer is connected by snap-fit ​​connections, allowing for easy removal and replacement. It is available in 0.5m or 1m lengths, compatible with pipe diameters from DN200 to DN800.

[0022] The pipe unit consists of an inner wear-resistant pipe 1, a middle piezoelectric sleeve 2 placed outside the inner wear-resistant pipe 1, and a replaceable protective sleeve 3 placed outside the middle piezoelectric sleeve 2. An energy management box 5 is located on the outer side of the replaceable protective sleeve 3. The inner wear-resistant pipe 1 contains 8wt%-12wt% silicon carbide micropowder (particle size 5-10μm) and 2wt%-3wt% polytetrafluoroethylene micropowder, forming a dual-effect layer of "rigid wear resistance + lubrication and anti-sticking," reducing the wear rate by 60-70% compared to traditional PVC. It also includes a microcapsule self-healing agent (urea-formaldehyde resin encapsulating epoxy resin, capsule diameter 10-50μm, addition amount 3-5wt%). When microcracks appear on the inner wall of the inner wear-resistant pipe 1, the capsule ruptures and releases the repair agent, completing self-repair within 24 hours with a repair efficiency ≥90%, extending the pipe's lifespan. The self-healing microcapsules can be formulated with different repair agents for different media (acidic, alkaline), improving environmental adaptability. The inner wall features a biomimetic shark skin texture, with raised dots of 0.2mm-0.3mm in diameter and 0.5mm in spacing. This texture reduces water flow resistance by 15-20% and prevents debris from adhering. Manufacturing process parameters: extrusion temperature 160-170℃, screw speed 30-40 r / min, melt pressure 15-20 MPa.

[0023] The middle piezoelectric sleeve 2 is radially divided into a high-sensitivity layer (near the inner layer) and a high-energy storage layer (near the outer layer). The high-sensitivity layer contains PZT-5H piezoelectric ceramic fibers with a diameter of 30μm-50μm and a volume ratio of 40%, preferentially responding to minute vibrations in water flow. The high-energy storage layer contains PVDF-TrFE copolymer with a volume ratio of 60%, enhancing charge storage capacity. The high-sensitivity layer and the high-energy storage layer are composited using a coupling agent. Manufacturing process parameters: extrusion temperature 155-165℃, ultrasonic dispersion technology to ensure uniform distribution of PZT fibers, cooling rate 5-8℃ / min.

[0024] The replaceable protective sleeve 3 includes three types: an anti-seepage protective sleeve, a lightweight protective sleeve, and an acid and alkali resistant protective sleeve. The anti-seepage protective sleeve contains 3wt%-5wt% anti-seepage agent. The anti-seepage protective sleeve uses a PVC layer with 3-5wt% anti-seepage agent added (anti-seepage pressure ≥0.3MPa), while the lightweight protective sleeve uses a lightweight foamed PVC layer (density ≤1.2g / cm³). 3 The acid and alkali resistant protective sleeve uses an acid and alkali resistant PVC layer (resistant to corrosion of 30% sulfuric acid / sodium hydroxide), and is suitable for municipal underground scenarios, building ceiling scenarios and industrial park scenarios.

[0025] Preparation process parameters: Extrusion temperature 160-170℃, after extrusion, dual cooling of air cooling and water cooling is adopted, and the cooling time is ≥5min.

[0026] The inner wall of the pipe body is embedded with spiral guide grooves, with a groove depth of 0.5mm-1.2mm and a spiral angle of 30°-60°, to guide water flow and enhance vortex-induced vibration effect. The surface of the spiral guide grooves can be coated with a 0.1-0.2mm thick polytetrafluoroethylene coating to further reduce water flow resistance and debris adhesion rate (adhesion rate <5%).

[0027] The energy harvesting module is used to collect and store the vibrational energy of water flow at different flow rates. The module includes a piezoelectric unit 4, an energy management circuit, and an energy storage unit. The piezoelectric unit 4 is sheet-shaped and spirally arranged at 120° along the inner wall of the individual pipe unit, covering 30-50% of the pipe's inner surface area. It is fixed to the inner wall of the individual pipe unit by arc-shaped magnetic sheets and plastic clips. The arc-shaped magnetic sheets (made of neodymium iron boron, with an attraction force ≥5N) are attracted to the inner wall of the pipe and then secured again by plastic clips. It can be disassembled and replaced individually (maintenance time reduced to 10-15 minutes per unit). A three-dimensional composite structure of "PZT-5H fiber + PVDF-TrFE + carbon nanotubes" is adopted: PZT-5H fibers (50-100μm in diameter) are arranged along the pipe axis to improve longitudinal vibration response; PVDF-TrFE copolymer (melting point 150-160℃) serves as the matrix to enhance flexible adhesion; 1-1.5wt% of single-walled carbon nanotubes (1-2nm in diameter) are added to construct a conductive network and reduce charge loss. The piezoelectric unit 4 can be selected in different temperature-resistant versions according to the pipe medium temperature: ordinary PZT-5H is used for normal temperature scenarios (-10℃ to 60℃); PZT-4 is used for high temperature scenarios (60℃ to 100℃), suitable for industrial high-temperature wastewater scenarios.

[0028] The energy management circuit, based on a traditional AC-DC converter, incorporates a "dual-mode maximum power point tracking" function: when the water flow velocity is stable between 0.8 m / s and 2 m / s, it employs a perturbation observation method; when the water flow velocity is greater than 2 m / s or less than 0.8 m / s, it switches to an incremental conductance method. Furthermore, it introduces an AI adaptive energy management algorithm, which, based on historical water flow data and real-time sensor feedback, predicts flow velocity change trends through a lightweight neural network, dynamically adjusting the energy harvesting mode and energy storage allocation strategy to improve energy utilization efficiency. The AI ​​adaptive energy management algorithm supports a federated learning mode, allowing multiple pipeline nodes to share model updates without uploading raw data, protecting data privacy while enhancing model generalization capabilities.

[0029] like Figure 5 The AI ​​adaptive energy management algorithm process is as follows: S1. System initialization, loading historical water flow data and preset operating parameters; S2. Real-time data acquisition, including real-time acquisition of flow velocity v, piezoelectric output power p, supercapacitor voltage Uc, and lithium battery power Soc. S3, dual-dimensional analysis, based on collected real-time data, performs multi-dimensional analysis of the system's operating status, including real-time status assessment and trend prediction; Real-time status assessment to determine whether the flow velocity is within the stable range of 0.8–2 m / s. If the flow rate is stable (0.8–2 m / s), the MPPT algorithm is used: perturbation and observation method (tracking accuracy ±5%). If not, then it is a fluctuating flow velocity (v<0.8 m / s or v>2 m / s), in which case the MPPT algorithm is used: incremental conductance method (response time<100 ms); Trend prediction: Using a lightweight neural network, predict flow rate changes for the next hour. S4. Capacity allocation decision: Based on the forecast results and energy storage status, three scenarios are handled, and energy utilization efficiency is monitored in real time. Scenario 1: If the predicted flow rate increases and there is sufficient energy storage (Uc≥2.45 V and Soc≥80%), the sensor will be powered first, and excess energy will be stored in the lithium battery. Scenario 2: If the predicted flow rate decreases and energy storage is insufficient (Uc < 3.0 V and Soc < 30%), adjust the piezoelectric element collection mode and prioritize power supply from supercapacitor 6. Scenario 3: Predicted stable flow rate + moderately balanced energy distribution in energy storage, with sensor power supply and supercapacitor 6 and battery working together for energy storage; S5. Energy utilization rate monitoring (target 75%-80%), and efficiency assessment and optimization based on energy utilization efficiency; Inefficiency not meeting standards: Optimize algorithm parameters and return to the "real-time data acquisition" stage; Efficiency targets achieved: Update the historical database and iterate the model, return to the "real-time data acquisition" stage, and provide feedback to the next cycle.

[0030] The energy storage unit includes a supercapacitor 6 and a micro battery housed in the energy management box 5. The supercapacitor 6 (capacity 0.5-1F, withstand voltage 5.5V) is responsible for short-term high-frequency power supply; the micro lithium-sulfur battery (capacity 50-100mAh, energy density 400Wh / kg) is responsible for long-term backup power supply, solving the problem of power interruption when traditional single energy storage fluctuates flow rate.

[0031] A sensor network is used to monitor the strain, corrosion, and flow status within a single pipe unit in real time. The sensor network consists of a strain sensor array, a corrosion monitoring sensor assembly, and a flow monitoring assembly integrated in piezoelectric unit 4.

[0032] The strain sensing array is based on resistance strain gauges, with 3-5 monitoring points per meter of pipe to detect pipe deformation and external loads.

[0033] The corrosion monitoring component includes a pH sensor and an ultrasonic thickness sensor, used to monitor pipe wall corrosion and wear.

[0034] The flow monitoring component calculates the flow velocity by outputting a piezoelectric frequency, with a measurement range of 0.1m / s-5m / s and an accuracy of ±0.1m / s.

[0035] The data processing unit is used for real-time monitoring, early warning, and health prediction of individual pipe conditions. It can be connected to the municipal smart pipeline network platform, supports the NB-IoT transmission protocol (transmission distance ≥10km), and enables collaborative monitoring and scheduling of multiple pipelines. The data processing unit includes an integrated microcontroller 7 (MCU) for data processing and a LoRa module 8 for wireless transmission, both located in the energy management box 5. The MCU is an STM32L431, employing the LZ77 variant compression algorithm (optimized for pipeline monitoring data, compression rate ≥60%) to reduce data transmission volume. The LoRa module 8 is a low-power model (model RA-02), operating at 868MHz (EU) / 915MHz (North America), with a transmit power of 17dBm, a transmission distance ≥2km (open environment), and a receive sensitivity of -148dBm.

[0036] The signal output terminal of the sensor network is electrically connected to the signal input terminal of the MCU via the I2C / SPI bus, and the wireless signal terminal of the MCU is connected to the UART terminal of the LoRa module 8.

[0037] The data acquisition adds a "dynamic threshold adjustment" function to the traditional event-driven approach: the monitoring threshold is preset according to the pipeline usage scenario (such as the municipal pipeline blockage threshold is flow velocity <0.3m / s, and the building pipeline leakage threshold is strain >500με). When the parameter is close to the threshold, the sampling frequency is automatically increased (from 6 hours / time to 10 minutes / time), avoiding the missed and false alarm problems of traditional fixed sampling, and the early warning accuracy is improved to more than 90%.

[0038] The data processing unit incorporates a micro MCU to perform local data preprocessing (such as anomaly data filtering and trend analysis), and only uploads valid data to the cloud, reducing cloud computing power requirements (energy consumption is reduced by 30-40%).

[0039] An integrated pipeline health prediction model, running on an edge computing platform, combines time series analysis (ARIMA algorithm) with machine learning (Support Vector Machine SVM) to predict the remaining lifespan and failure risk of pipelines, issuing maintenance warnings 3-6 months in advance, thereby increasing the planned maintenance rate to over 85%.

[0040] Therefore, the present invention adopts the above-mentioned self-powered intelligent sensing PVC drainage pipe system based on piezoelectric energy harvesting. Based on the integrated design of "bionic flow field optimization - gradient piezoelectric energy harvesting - modular sensing - quick installation and adaptation", it can not only efficiently convert water kinetic energy into electrical energy and realize real-time monitoring of all pipe parameters, but also improve portability and versatility through modular structural design, adapting to different pipe diameters and media scenarios.

[0041] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A self-powered intelligent sensing PVC drainage pipe system based on piezoelectric energy harvesting, characterized in that, include: The tube module consists of several tube units, each of which is a three-layer gradient composite structure. The layers are connected by snap-fit, and the length is 0.5m or 1m. An energy harvesting module is used to collect and store the vibrational energy of water flow at different flow rates. Sensor networks are used to monitor pipe strain, corrosion, and flow status within individual pipe units in real time. The data processing unit is used to realize real-time monitoring, early warning and health prediction of the individual pipe body status.

2. The self-powered intelligent sensing PVC drainage pipe system based on piezoelectric energy harvesting according to claim 1, characterized in that: The tube unit consists of an inner wear-resistant tube, a middle piezoelectric sleeve placed on the outer layer of the inner wear-resistant tube, and a replaceable protective sleeve placed on the outer layer of the middle piezoelectric sleeve. An energy management box is installed on the outside of the replaceable protective sleeve.

3. The self-powered intelligent sensing PVC drainage pipe system based on piezoelectric energy harvesting according to claim 2, characterized in that: The inner wear-resistant tube contains 8wt%-12wt% silicon carbide micro powder and 2wt%-3wt% polytetrafluoroethylene micro powder, as well as microcapsule self-healing agent. The inner wall adopts a biomimetic shark skin texture, in which the diameter of the protrusions is 0.2mm-0.3mm and the spacing is 0.5mm. The middle piezoelectric sleeve is divided into a high-sensitivity layer and a high-energy storage layer along the radial direction of the tube body. The high-sensitivity layer contains PZT-5H piezoelectric ceramic fibers with a diameter of 30μm-50μm and a volume ratio of 40%. The high-energy storage layer contains PVDF-TrFE copolymer with a volume ratio of 60%. The high-sensitivity layer and the high-energy storage layer are composited by a coupling agent. The replaceable protective sleeves include three types: anti-seepage protective sleeve, lightweight protective sleeve, and acid and alkali resistant protective sleeve. The anti-seepage protective sleeve contains 3wt%-5wt% anti-seepage agent.

4. The self-powered intelligent sensing PVC drainage pipe system based on piezoelectric energy harvesting according to claim 3, characterized in that: The inner wall of the pipe body is embedded with a spiral guide groove with a depth of 0.5mm-1.2mm and a spiral angle of 30°-60°, which is used to guide the water flow and enhance the vortex-induced vibration effect.

5. The self-powered intelligent sensing PVC drainage pipe system based on piezoelectric energy harvesting according to claim 4, characterized in that: The energy harvesting module includes a piezoelectric unit, an energy management circuit, and an energy storage unit. The piezoelectric unit is arranged in a 120° spiral along the inner wall of the tube unit and is fixed to the inner wall of the tube unit by an arc-shaped magnetic sheet and plastic clips. The management rules of the energy management circuit are as follows: when the water flow velocity is 0.8m / s-2m / s, the perturbation observation method is adopted; when the water flow velocity is >2m / s or <0.8m / s, the incremental conductivity method is switched; and an AI adaptive energy management algorithm is introduced, which predicts the flow velocity change trend based on historical water flow data and real-time sensor feedback, and dynamically adjusts the energy harvesting mode and energy storage distribution strategy through a lightweight neural network. The energy storage unit includes supercapacitors and micro batteries housed in an energy management box.

6. The self-powered intelligent sensing PVC drainage pipe system based on piezoelectric energy harvesting according to claim 5, characterized in that: The sensor network consists of a strain sensing array, a corrosion monitoring sensor assembly, and a flow monitoring assembly integrated in a piezoelectric unit; The strain sensing array is based on resistance strain gauges, with 3-5 monitoring points per meter of pipe to detect pipe deformation and external loads; The corrosion monitoring component includes a pH sensor and an ultrasonic thickness sensor, used to monitor pipe wall corrosion and wear. The flow monitoring component calculates the flow velocity by using the piezoelectric output frequency, with a measurement range of 0.1 m / s to 5 m / s.

7. A self-powered intelligent sensing PVC drainage pipe system based on piezoelectric energy harvesting according to claim 6, characterized in that: The data processing unit includes an integrated microcontroller (MCU) and a LoRa module located in the energy management box.

8. The self-powered intelligent sensing PVC drainage pipe system based on piezoelectric energy harvesting according to claim 7, characterized in that: The signal output terminal of the sensor network is electrically connected to the signal input terminal of the MCU via the I2C / SPI bus, and the wireless signal terminal of the MCU is connected to the UART terminal of the LoRa module.

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