Asphalt pavement crack diagnosis method based on wireless piezoelectric sensor

Abstract

The invention discloses an asphalt pavement crack diagnosis method based on wireless piezoelectric sensors. The method comprises the following steps: linearly burying a plurality of self-made wireless piezoelectric sensors at the bottom of an asphalt pavement according to a preset interval; wherein each wireless piezoelectric sensor corresponds to one point location, each wireless piezoelectric sensor comprises a piezoelectric transduction and sensing module and a data acquisition and wireless transmission module, and the piezoelectric transduction and sensing module and the data acquisition and wireless transmission module are packaged into an integral structure through three-dimensional (3D) printing; the piezoelectric transduction and sensing module is used for automatically collecting voltage signals generated when a vehicle passes through the upper portion of the corresponding wireless piezoelectric sensor; and interpreting the voltage signal through the data acquisition and wireless transmission module, determining a target point location with abnormal voltage signal amplitude output, and performing crack size prediction based on the voltage signal amplitudes of the target point location under different loads. The method can reduce the pavement monitoring cost and is high in crack size prediction accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of asphalt pavement health monitoring, and relates to but is not limited to an asphalt pavement crack diagnosis method based on a wireless piezoelectric sensor. Background Art

[0002] Asphalt pavement is one of the important transportation infrastructures. Under the coupling of environment and load, asphalt pavement will first show hidden damage such as micro cracks, and gradually develop into macroscopic diseases such as cracks, which will affect the performance and service life of the pavement. By quantitatively monitoring the number and width of cracks on the road, a scientific basis can be provided for the formulation of targeted treatment measures to prevent minor damage from further development. Therefore, effective and timely monitoring of hidden damage on asphalt pavement is extremely important for scientifically taking maintenance measures to maintain the performance of the pavement.

[0003] The existing monitoring methods for pavement structure damage mainly use external evaluation technology and on-site sensing technology. External evaluation technology is used to detect pavement stress, damage and surface function, including bending, acoustic emission, ground penetrating radar, ultrasound, infrared thermal imaging and imaging technology. However, external evaluation technology lacks spontaneity and has lag. The detection process requires a large amount of manpower and equipment, and it is unable to monitor pavement micro-damage and development process.

[0004] The emergence of smart materials has provided an effective way for health monitoring and damage diagnosis of engineering structures such as asphalt pavements. Among the many smart materials, piezoelectric ceramics (PZT for short) have the superior characteristics of integrated sensing and driving, providing a new idea for health monitoring and damage diagnosis of asphalt pavements. Summary of the invention

[0005] In view of this, an embodiment of the present invention provides an asphalt pavement crack diagnosis method based on a wireless piezoelectric sensor, which at least solves the problem that the existing monitoring methods lack autonomy and hysteresis, and cannot predict hidden cracks in the pavement and their crack sizes.

[0006] The technical solutions of the embodiments of the present invention are as follows:

[0007] The embodiment of the present invention provides a method for diagnosing cracks in an asphalt pavement based on a wireless piezoelectric sensor, comprising:

[0008] A plurality of self-made wireless piezoelectric sensors are buried in a straight line at the bottom of the asphalt pavement at preset intervals; each of the wireless piezoelectric sensors corresponds to a point, and each of the wireless piezoelectric sensors includes a piezoelectric transducer and sensor module, a data acquisition and wireless transmission module, and is packaged into an integral structure through 3D printing; the voltage signal generated when a vehicle passes over the corresponding wireless piezoelectric sensor is automatically collected through the piezoelectric transducer and sensor module; the voltage signal is interpreted through the data acquisition and wireless transmission module to determine the target point with abnormal voltage signal amplitude output, and the crack size is predicted based on the voltage signal amplitude of the target point under different loads.

[0009] Furthermore, the crack size prediction based on the voltage signal amplitude of the target point under different loads includes: fitting a group of equations for the voltage signal amplitude corresponding to the target point under different loads, and solving two unknowns, namely, crack width and crack depth, in the group of equations when the objective function is minimized; wherein the objective function is the error between the predicted value and the measured value of the crack size.

[0010] Furthermore, the method also includes: when the road is not open to traffic and N years after the road is opened to traffic, a group of vehicles with different loads are used to vertically roll over each of the wireless piezoelectric sensors along the driving direction; the voltage signal amplitude output by each of the multiple self-made wireless piezoelectric sensors under each load is collected; the voltage signal amplitude changes corresponding to each point when the road is not open to traffic and N years after the road is opened to traffic under the same vehicle load are compared; and the point where the voltage signal amplitude decreases is used as the target point.

[0011] Furthermore, the system of equations is expressed as follows:

[0012]

[0013] Where P i is the load used in the i-th test, V i is the voltage signal amplitude corresponding to the target point during the i-th test, the value range of i is {1, 2, ..., n}, n is the load type; W is the crack width, and H is the crack depth.

[0014] Furthermore, the piezoelectric transducer and sensor module is composed of 5 piezoelectric elements stacked in parallel; the piezoelectric element is a disc with a diameter of 20 mm and a thickness of 2 mm, and is prepared by hot pressing and polarization of piezoelectric ceramic PZT-5H and polyvinylidene fluoride PVDF in a ratio of 4:96 or 6:94, and an external addition of carbon black with a mass fraction of 0.2% to 0.3%, the hot pressing temperature is 200°C to 220°C, the hot pressing pressure is 40MPa to 45MPa, the polarization time is 30 to 35 minutes, the polarization electric field strength is 2kV / mm to 3kV / mm, and the polarization temperature is 120°C to 140°C.

[0015] Furthermore, the external packaging shape of the overall structure is a cylinder, the outer diameter of the cylinder is 20 to 22 cm, and the inner diameter is 18 to 20 cm; the packaging structure includes three parts from top to bottom: a top cover, an intermediate shell and a bottom shell; wherein, the data acquisition and wireless transmission module is placed in the bottom shell, and buffer rubber pads are placed in the upper and lower ends of the bottom shell for load buffering; the piezoelectric transducer and sensor module is placed in the intermediate shell, and is connected to the data acquisition and wireless transmission module from the bottom of the intermediate shell through a wire, the gap part of the intermediate shell is filled with epoxy resin, and a rubber gasket is placed on the top and then the top cover is covered.

[0016] Furthermore, the core chip of the data acquisition and wireless transmission module is STM32WLE5CC, a supercapacitor is used as an energy storage device, and the wireless module of the core chip selects the LORA mode.

[0017] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0018] In an embodiment of the present invention, a self-made wireless piezoelectric sensor is buried in a straight line inside the asphalt pavement at preset intervals. When a vehicle passes over the wireless piezoelectric sensor, a voltage signal is generated. Then, for the target point where the voltage signal amplitude output is abnormal, the voltage signal amplitude under different loads is collected to perform multi-objective planning and solve to obtain the crack size, which can reduce the cost of pavement monitoring. The method of the present invention is reliable, simple and fast, and suitable for large-scale promotion and application; and the crack size obtained is highly accurate. This method is not only suitable for crack monitoring of asphalt pavements, but can also be extended to other types of pavement monitoring, bridge health monitoring and other fields, providing effective technical support for the maintenance and management of infrastructure. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work, among which:

[0020] Figure 1 A schematic diagram of a flow chart of a method for diagnosing cracks in an asphalt pavement based on a wireless piezoelectric sensor provided in an embodiment of the present invention;

[0021] Figure 2 A schematic diagram of the structure of a wireless piezoelectric sensor provided in an embodiment of the present invention;

[0022] Figure 3 A schematic diagram of the preparation process of a piezoelectric element provided in an embodiment of the present invention;

[0023] Figure 4 A physical picture of a wireless piezoelectric sensor provided by an embodiment of the present invention;

[0024] Figure 5 A schematic diagram of the actual output voltage of the wireless piezoelectric sensor provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. The following embodiments are used to illustrate the present invention, but are not used to limit the scope of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0026] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0027] It should be pointed out that the terms "first\second\third" involved in the embodiments of the present invention are only used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that "first\second\third" can be interchanged in a specific order or sequence where permitted, so that the embodiments of the present invention described here can be implemented in an order other than that illustrated or described here.

[0028] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by those skilled in the art in the field to which the embodiments of the present invention belong. It should also be understood that terms such as those defined in general dictionaries should be understood to have meanings consistent with those in the context of the prior art, and will not be interpreted with idealized or overly formal meanings unless specifically defined as here.

[0029] The present invention buries the wireless piezoelectric intelligent sensor inside the asphalt pavement, and the positive and negative charge centers inside the PZT are relatively displaced to produce polarized charges of opposite signs, thereby generating a potential difference (voltage). At the same time, pavement structure damage will cause changes in pavement strain and voltage signals. Therefore, by analyzing the change law of strain or voltage signals with traffic load, according to this principle, the monitoring and intelligent diagnosis of pavement structure damage can be achieved.

[0030] Piezoelectric effect: Piezoelectric sensors generate an electric charge when subjected to an external force. This effect is called the piezoelectric effect. In this method, piezoelectric sensors are used to detect changes in stress on the road surface when a vehicle passes by, thereby detecting cracks.

[0031] By analyzing the changes in the voltage signal, the location and width of the crack can be determined. This usually involves mathematical modeling and analysis of the changes in the signal amplitude.

[0032] Figure 1 A schematic diagram of a process for diagnosing cracks in an asphalt pavement based on a wireless piezoelectric sensor is provided in an embodiment of the present invention. Figure 1 As shown, the method comprises at least the following steps:

[0033] Step S110, step S110, bury multiple self-made wireless piezoelectric sensors at the bottom of the asphalt pavement in a three-point combination array with a spacing of D; wherein each wireless piezoelectric sensor corresponds to a point, and each wireless piezoelectric sensor includes a piezoelectric transducer and sensing module, a data acquisition and wireless transmission module, and is packaged into an integral structure through 3D printing.

[0034] Here, the homemade wireless piezoelectric sensor is a piezoelectric intelligent sensor with high sensitivity, long-term stability and wireless transmission capability. According to the size of the asphalt pavement and the expected monitoring area, multiple wireless piezoelectric sensors are deployed in a straight line, and the distance between any two adjacent wireless piezoelectric sensors is fixed, such as 1 meter to 1.5 meters, where each wireless piezoelectric sensor corresponds to a point. It should be noted that this deployment should ensure that the entire monitoring area is fully covered, while taking into account the distance between sensors to avoid mutual interference. This configuration helps to improve the accuracy and resolution of the measurement, especially in determining the pavement pressure distribution and identifying local damage.

[0035] Piezoelectric transducer and sensor module: The core part of each wireless piezoelectric sensor. When a vehicle passes over the wireless sensor network, the piezoelectric transducer and sensor module will be affected by the vehicle load and generate a voltage output. Piezoelectric materials (such as PZT, lead zirconate titanate) can generate electric charge in response to pressure changes, thereby realizing electrical measurement of pressure.

[0036] Data acquisition and wireless transmission module: responsible for collecting the electrical signals generated by the piezoelectric sensor, performing analog-to-digital conversion and data processing, and then transmitting the data to the central monitoring system through wireless communication methods (such as Wi-Fi, Bluetooth, LoRa, etc.).

[0037] Homemade wireless piezoelectric sensors need to be able to adapt to the high temperature and harsh environment of asphalt pavement, so material selection and packaging design need to consider factors such as heat resistance, waterproofness and chemical corrosion resistance. Using 3D printing technology, the shell of the wireless piezoelectric sensor can be customized to adapt to different installation environments and mechanical requirements, ensuring the stability and durability of the wireless piezoelectric sensor. 3D printing can also integrate microelectronic devices to achieve integrated manufacturing of wireless piezoelectric sensors, improve production efficiency and reduce costs.

[0038] Step S120, automatically collecting the voltage signal generated when the vehicle passes over the corresponding wireless piezoelectric sensor through the piezoelectric transducer and sensor module.

[0039] Here, the piezoelectric transducer and sensor module is responsible for converting the mechanical stress generated when a vehicle passes over the wireless piezoelectric sensor into a voltage signal. First, the sensor array allows for continuous, distributed monitoring of the road surface. When a vehicle passes by, the piezoelectric transducer and sensor module can capture the voltage changes caused by the slight deformation of the road surface, which is related to the vehicle load and the condition of the road surface.

[0040] Step S130, interpreting the voltage signal through the data acquisition and wireless transmission module, determining the target point where the voltage signal amplitude output is abnormal, and predicting the crack size based on the voltage signal amplitude of the target point under different loads.

[0041] Here, after data collection, the data collection and wireless transmission module needs to interpret these voltage signals. The interpretation process may include steps such as signal filtering, amplification, and digitization so that useful information can be extracted from it. The embodiment of the present invention mainly extracts the voltage signal amplitude. By monitoring and interpreting the voltage signals of multiple points, the system can identify which points have abnormal voltage signal amplitudes, such as a significant decrease in the voltage signal amplitude. These abnormal points may be areas where there are problems (such as cracks) in the asphalt pavement structure. Further analyze the changes in the voltage signal amplitude of these points under different loads (for example, 1kN, 3kN, 5kN, 7kN, 9kN, etc.). By analyzing this change, a prediction model is constructed to predict the size or severity of the cracks. The prediction model can be determined based on some empirical formulas, machine learning models, or expert systems.

[0042] In an embodiment of the present invention, a plurality of self-made wireless piezoelectric sensors are linearly buried at the bottom of the asphalt pavement at preset intervals to monitor the voltage signal generated when a vehicle passes by in real time to achieve automatic positioning of cracks. Thus, by utilizing the sensitivity of wireless piezoelectric sensors and wireless communication technology, an efficient and accurate method for detecting pavement cracks is provided. The method can monitor the pavement condition in real time, detect cracks in time, and accurately locate the crack position through a three-point combination array and signal processing technology. The wireless piezoelectric sensors used can transmit data wirelessly, which is convenient for remote monitoring and maintenance. At the same time, the application of 3D printing technology helps to reduce the manufacturing cost of wireless piezoelectric sensors.

[0043] In some embodiments, the above-mentioned step S130 "predicting the crack size based on the voltage signal amplitude of the target point under different loads" is implemented by the following steps: fitting a set of equations for the voltage signal amplitude corresponding to the target point under different loads, and solving the two unknowns of crack width and crack depth in the set of equations when the objective function is minimized; wherein, the objective function is the error between the predicted value of the crack size and the measured value.

[0044] Here, the voltage signal amplitude corresponding to the target point under different loads is recorded, and the actual size of the crack near the target point is obtained by on-site core drilling. The equation group is fitted based on multiple records and test data, where the objective function can use mean square error (MSE), sum of absolute error (SAE), etc. as error metrics. An optimization algorithm (such as gradient descent method, Newton method, etc.) is used to solve the crack width W and crack depth D in the equation group when the objective function is minimized. This usually involves an iterative process to minimize the objective function by continuously adjusting the values ​​of W and D.

[0045] In some embodiments, the system of equations is expressed as follows:

[0046]

[0047] Where P i is the load used in the i-th test, V i is the voltage signal amplitude corresponding to the target point during the i-th test, the value range of i is {1, 2, ..., n}, n is the load type; W is the crack width, and H is the crack depth.

[0048] Here, in the implementation, loads P1, P2, ....... , P n Carry out n tests, collect the voltage signal amplitude output by the wireless piezoelectric sensor corresponding to the target point in each test, substitute it into the equation group together with the corresponding load, and use the multi-objective planning algorithm to solve the unknowns W and H in the equation group to minimize the value of the objective function.

[0049] In some embodiments, the method also includes: when the road is not open to traffic and N years after the road is opened to traffic, a group of vehicles with different loads are used to roll over each of the wireless piezoelectric sensors vertically along the driving direction; collecting the voltage signal amplitude output by each of the multiple homemade wireless piezoelectric sensors under each load; comparing the changes in the voltage signal amplitude corresponding to each point when the road is not open to traffic and N years after the road is opened to traffic under the same vehicle load; and taking the point where the voltage signal amplitude decreases as the target point.

[0050] Here, the experimental phase begins after a group of wireless piezoelectric sensors are deployed at preset intervals on the asphalt pavement to be tested. First, before the road is opened to traffic, a group of vehicles with different loads are used to roll over each wireless piezoelectric sensor vertically along the driving direction. The voltage signal amplitude output by each wireless piezoelectric sensor under each load is recorded. Then, N years after the road is opened to traffic, the above experimental process is repeated, using the same vehicle and load to roll over each wireless piezoelectric sensor and record the voltage signal amplitude.

[0051] Finally, compare the changes in the voltage signal amplitude corresponding to each point when the road was not opened to traffic and N years after the road was opened to traffic under the same vehicle load. Analyze the reasons for this change, especially pay attention to those points where the voltage signal amplitude has dropped significantly. Based on the comparison results, the points where the voltage signal amplitude has dropped are taken as target points. These points may correspond to hidden cracks or structural damage on the road surface. The reason is that the decrease in voltage signal amplitude may be caused by factors such as fatigue of the road material, formation or expansion of cracks, and changes in the coupling state between the sensor and the road surface.

[0052] In some embodiments, the piezoelectric transducer and sensor module is composed of 5 piezoelectric elements stacked in parallel; the piezoelectric element is a disc with a diameter of 20 mm and a thickness of 2 mm, and is prepared by hot pressing and polarization of piezoelectric ceramic PZT-5H and polyvinylidene fluoride PVDF in a ratio of 4:96 or 6:94, and an external addition of 0.2% to 0.3% carbon black by mass fraction, the hot pressing temperature is 200°C to 220°C, the hot pressing pressure is 40MPa to 45MPa, the polarization time is 30 to 35 minutes, the polarization electric field strength is 2kV / mm to 3kV / mm, and the polarization temperature is 120°C to 140°C.

[0053] Here, the piezoelectric transducer and sensor module consists of five piezoelectric elements stacked in parallel. This design aims to increase the output voltage and current of the piezoelectric effect, thereby enhancing the module's transducer efficiency and sensing sensitivity.

[0054] Shape and size of piezoelectric element: The piezoelectric element is a disc with a diameter of 20 mm and a thickness of 2 mm. This size design not only ensures sufficient piezoelectric effect output, but also facilitates the assembly and packaging of the module.

[0055] Material ratio of piezoelectric elements: Piezoelectric elements are made of piezoelectric ceramics PZT-5H and polyvinylidene fluoride PVDF in a specific ratio (4:96 or 6:94). This composite material combines the high piezoelectric constant of PZT-5H and the flexibility of PVDF, making the piezoelectric element have better comprehensive performance.

[0056] Carbon black addition: 0.2% to 0.3% carbon black is added. The addition of carbon black can improve the conductivity and mechanical properties of piezoelectric materials, thereby improving the stability and reliability of the piezoelectric effect.

[0057] Hot-pressing polarization is a key step in the preparation of piezoelectric materials, which gives piezoelectric materials the piezoelectric effect. The selection of polarization parameters has an important influence on the performance of piezoelectric materials and requires precise control to ensure the quality of piezoelectric components.

[0058] Due to the use of composite materials and high-performance preparation technology, the piezoelectric transducer and sensor module has the advantages of high output voltage, high sensitivity, good stability, etc. At the same time, due to the parallel stacking design, the module's transducer efficiency and sensor sensitivity are further improved.

[0059] In some embodiments, the external packaging shape of the overall structure is a cylinder, the outer diameter of the cylinder is 20 to 22 cm, and the inner diameter is 18 to 20 cm; the packaging structure includes three parts from top to bottom, namely, a top cover, an intermediate shell and a bottom shell; wherein, the data acquisition and wireless transmission module is placed in the bottom shell, and buffer rubber pads are placed in the upper and lower ends of the bottom shell for load buffering; the piezoelectric transducer and sensor module is placed in the intermediate shell, and is connected to the data acquisition and wireless transmission module from the bottom of the intermediate shell through a wire, the gap part of the intermediate shell is filled with epoxy resin, and a rubber gasket is placed on the top and then the top cover is covered.

[0060] Here, the wireless piezoelectric sensor is packaged into a cylindrical shape through 3D printing technology. This design is not only easy to install and bury, but also provides sufficient protection and support. The packaging structure consists of three parts: the top cover, the middle shell and the bottom shell from top to bottom. Each part has a specific function and role. The top cover is located at the top of the cylinder and plays a role of protection and sealing. The top cover may also be provided with an interface or channel to connect with wires or other external devices. The middle shell is the main part of the cylinder, and the piezoelectric transducer and sensor module is placed inside. The piezoelectric transducer and sensor module is connected to the data acquisition and wireless transmission module from the bottom of the middle shell through a wire. The gap part of the middle shell is filled with epoxy resin to improve the overall strength and stability of the structure. The top cover is covered after the rubber gasket is placed on the top to ensure the tight packaging and waterproof and dustproof performance of the internal components. The bottom shell is located at the bottom of the cylinder, and the data acquisition and wireless transmission module is placed inside. Buffer rubber pads are placed at the upper and lower ends of the bottom shell to reduce the impact and damage of the load on the internal components of the sensor. The material and thickness of the cushioning rubber pad should be selected according to actual needs to ensure a good cushioning effect.

[0061] The packaging structure achieved by 3D printing technology has the advantages of compact structure, light weight and easy installation. The cushioning rubber pad and epoxy resin filling layer inside the packaging structure provide good protection and support, and can resist the erosion of external loads and environmental factors. The precise coordination of piezoelectric transducer and sensor module and data acquisition and wireless transmission module ensures the accurate monitoring and real-time data transmission of abnormal conditions such as road cracks by the sensor.

[0062] In summary, the 3D printed packaging structure of the wireless piezoelectric sensor has a unique shape and size design as well as a reasonable internal component layout and packaging method, which provides a reliable technical guarantee for its application in the fields of pavement crack monitoring.

[0063] In some embodiments, the core chip of the data acquisition and wireless transmission module is STM32WLE5CC, a supercapacitor is used as an energy storage device, and the wireless module of the core chip selects the LORA mode.

[0064] Here, the core chip of the data acquisition and wireless transmission module is STM32WLE5CC. This is a low-power chip that integrates a microcontroller (MCU) and wireless communication functions, suitable for various Internet of Things (IoT) applications. Supercapacitors are used as energy storage devices. Supercapacitors are a new type of electrical energy storage device with the advantages of fast charging speed, long service life, and strong environmental adaptability. The wireless module of the core chip uses LORA. LORA (Long Range) is a low-power wide area network communication technology with the characteristics of long transmission distance, low power consumption, and strong anti-interference ability.

[0065] The data acquisition and wireless transmission module uses the STM32WLE5CC core chip, supercapacitor as energy storage and LORA wireless communication technology, and has the following application advantages and characteristics:

[0066] Low power consumption: The entire module has a low power consumption design and is suitable for application scenarios that require long-term operation and energy collection. Long-distance communication: LORA technology ensures long-distance and stable communication between modules, which is suitable for remote data transmission between devices in IoT applications. High reliability: The combination of supercapacitor and LORA technology improves the reliability and stability of the module and can work normally in harsh environments. Easy to integrate: The STM32WLE5CC core chip has rich peripheral interfaces and powerful processing capabilities, which is easy to integrate and expand with other sensors and systems.

[0067] In summary, this data acquisition and wireless transmission module has a unique combination of core chip, energy storage and wireless communication technology, which provides reliable technical guarantee for its wide application in Internet of Things applications.

[0068] The above-mentioned asphalt pavement crack diagnosis method based on wireless piezoelectric sensor is described below in conjunction with a specific embodiment. However, it should be noted that this specific embodiment is only for better illustrating the present invention and does not constitute an improper limitation to the present invention.

[0069] First, the wireless piezoelectric sensor of the embodiment of the present invention is made by itself, and its specific composition structure is as follows: Figure 2 As shown, the left side is an assembly schematic diagram, and the right side is a cross-sectional diagram. It can be seen that the wireless piezoelectric sensor mainly includes a piezoelectric transducer and sensor module 21, a data acquisition and wireless transmission module 22, and an external package consisting of a top cover 23, a rubber gasket 24, an intermediate shell 25, and a bottom shell 26. The data acquisition and wireless transmission module 22 is placed in the bottom shell 26, and the buffer rubber pads 27 are placed at the upper and lower ends for load buffering. The intermediate shell 25 is placed on the bottom shell 26, and the piezoelectric transducer and sensor module 21 is placed inside. The wire is connected to the data acquisition and wireless transmission module 22 through the bottom of the intermediate shell 25, and the gap is filled with epoxy resin. The rubber gasket 24 is placed on the top, and the top cover 23 is added to complete the assembly.

[0070] like Figure 2 As shown in the right side cross-sectional view, the piezoelectric transducer and sensor module 21 is composed of 5 composite piezoelectric elements 211 stacked in parallel, and the piezoelectric element 211 is a round piece with a diameter of 20 mm and a thickness of 2 mm. Figure 3The figure shows the preparation process of piezoelectric elements. First, the materials are mixed and pressed. The piezoelectric ceramic PZT-5H and polyvinylidene fluoride PVDF are mixed in a ratio of 4:96, and carbon black with a mass fraction of 0.3% is added for ball milling. The mixed material is pressed by hot pressing and polarization. The hot pressing temperature is 200°C, the hot pressing pressure is 45MPa, the polarization time is 30min, the polarization electric field strength is 3kV / mm, and the polarization temperature is 120°C. Secondly, the disc is polished and back-silvered. Finally, the material is polarized and tested, including piezoelectric properties, dielectric properties, mechanical properties, and microstructure.

[0071] The core chip of the data acquisition and wireless transmission module is STM32WLE5CC, which uses supercapacitors as energy storage, connected by wires in the middle, and the core chip wireless module uses LORA.

[0072] like Figure 4 As shown, the assembled wireless piezoelectric sensor structure is packaged as a whole through 3D printing, and its external packaging shape is a cylinder, and the outer diameter of the cylinder is 20-22 cm, and the inner diameter is 18-20 cm. The packaging material is nylon-PA12.

[0073] After testing, the energy consumption of the wireless piezoelectric intelligent sensor for single data collection, calculation and wireless transmission is 0.004J. The electric energy collected from 120 standard vehicle passes can meet the needs of one data collection, calculation and wireless transmission. The signal receiving intensity within a range of 40m is -65dBm. The piezoelectric output and output power under 0.7MPa and 8Hz loads are 30.940V and 0.7678mW respectively. The compressive strength is 8.43MPa. The voltage output can still remain stable after 100,000 loads.

[0074] The wireless piezoelectric sensors are arranged in a three-point combination at the bottom of the asphalt surface layer with an interval of 0.5m, and a data receiving terminal is set up on the roadside. The vehicle loads with wheel loads of 1kN, 3kN, 5kN, 7kN, and 9kN are used for rolling. Figure 5 The figure shows the actual output voltage signal of the wireless piezoelectric sensor. The crack size is predicted for the sensor point where the abnormal signal appears (the output voltage is smaller than other points). The equation group for the output voltage under different loads is listed, as shown in formula (1), and the unknown variables W and H in the equation group are predicted.

[0075] Signal measurement when the road is not open to traffic: When the road is not open to traffic, vehicles with different loads are used for rolling, and the output signals of the five points are shown in Table 1.

[0076] Table 1 Sensor output signal amplitude when the vehicle is not open (V)

[0077]

[0078] 2) Signal measurement one year after opening to traffic: One year after opening to traffic (the average daily traffic volume is 4000 vehicles / day), vehicles with different loads were used for rolling, and the output signals of the five points are shown in Table 2.

[0079] Table 2: Sensor output signal amplitude (V) one year after opening to traffic

[0080]

[0081] Comparing Table 1 and Table 2, it can be seen that the voltage amplitude of point 2 has a significant drop. The voltage signal amplitude of point 2 under each load is collected to perform multi-objective planning and solving. Formula (1) is used as the prediction model, and the objective function is solved to minimize the error between the predicted value and the test value of the crack size, and the crack width and crack height are predicted. The hidden crack size (i.e., the measured value) and the predicted size result (i.e., the predicted value) near point 2 are obtained by on-site core drilling and testing as shown in Table 3. It can be obtained that the crack width error is 0.14 mm and the crack height error is 0.36 mm.

[0082] Table 3 Predicted and measured values ​​of crack size at point 2 one year after opening to traffic

[0083] type Crack width / mm Crack height / mm Predicted value 0.86 2.00 Measured value 1.00 1.64

[0084] 3) Signal measurement 2 years after opening to traffic: 2 years after opening to traffic (average daily traffic volume is 4000 vehicles / day), vehicles with different loads were used for rolling, and the output signals of the five points are shown in Table 4.

[0085] Table 4 Sensor output signal amplitude 2 years after opening to traffic (V)

[0086]

[0087]

[0088] Comparing Table 1 and Table 4, it can be seen that the voltage amplitude of point 2 and point 5 has a significant decrease. The signal amplitude of point 2 and point 5 is collected for multi-objective planning and solving. Formula (1) is used as the prediction model, and the objective function is solved to minimize the voltage prediction value and the test value, and the crack width and crack height are predicted. The hidden crack size and predicted size of point 2 and point 5 are tested on site, and the results are shown in Table 5.

[0089] Table 5 Predicted and measured values ​​of crack sizes at points 2 and 5 two years after opening to traffic

[0090]

[0091] Based on Table 5, it can be calculated that the crack width error at point 2 is 0.21 mm, and the crack height error is 1.18 mm; the crack width error at point 5 is 0.28 mm, and the crack height error is 0.66 mm.

[0092] It should be understood that "one embodiment" or "an embodiment" mentioned throughout the specification means that specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present invention. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present invention, the size of the serial number of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention. The serial numbers of the above-mentioned embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments.

[0093] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0094] In the several embodiments provided by the present invention, it should be understood that the disclosed methods can be implemented in other ways. The methods disclosed in the several method embodiments provided by the present invention can be arbitrarily combined without conflict to obtain new method embodiments. The features disclosed in the several method embodiments provided by the present invention can be arbitrarily combined without conflict to obtain new method embodiments.

[0095] The above is only an embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for diagnosing cracks in asphalt pavement based on wireless piezoelectric sensors, characterized in that: include: Multiple self-made wireless piezoelectric sensors are buried in a straight line at the bottom of the asphalt pavement at preset intervals; wherein each of the wireless piezoelectric sensors corresponds to a point, and each of the wireless piezoelectric sensors includes a piezoelectric transducer and sensor module, a data acquisition and wireless transmission module, and is packaged into an integral structure through 3D printing; Automatically collect the voltage signal generated when the vehicle passes over the corresponding wireless piezoelectric sensor through the piezoelectric transducer and sensor module; The voltage signal is interpreted by the data acquisition and wireless transmission module to determine the target point where the voltage signal amplitude output is abnormal, and the crack size is predicted based on the voltage signal amplitude of the target point under different loads.

2. The asphalt pavement crack diagnosis method according to claim 1, characterized in that: The predicting of crack size based on the voltage signal amplitude of the target point under different loads includes: A voltage signal amplitude fitting equation group corresponding to the target point under different loads is performed to solve two unknowns, namely, crack width and crack depth, in the equation group when the objective function is minimized; The objective function is the error between the predicted value and the measured value of the crack size.

3. The asphalt pavement crack diagnosis method according to claim 1, characterized in that: The method further comprises: Before the road is opened to traffic and N years after the road is opened to traffic, a group of vehicles with different loads are used to roll over each of the wireless piezoelectric sensors vertically along the driving direction; Collecting the voltage signal amplitudes output by each of the plurality of self-made wireless piezoelectric sensors under each of the loads; Compare the changes in the voltage signal amplitude at each point under the same vehicle load when the vehicle is not open to traffic and N years after the vehicle is open to traffic; The point where the voltage signal amplitude decreases is used as the target point.

4. The asphalt pavement crack diagnosis method according to claim 2, characterized in that: The system of equations is expressed as follows: Where P i is the load used in the i-th test, V i is the voltage signal amplitude corresponding to the target point during the i-th test, the value range of i is {1, 2, ..., n}, n is the load type; W is the crack width, and H is the crack depth.

5. The asphalt pavement crack diagnosis method according to any one of claims 1 to 4, characterized in that: The piezoelectric transducer and sensor module is composed of 5 piezoelectric elements stacked in parallel; The piezoelectric element is a disc with a diameter of 20 mm and a thickness of 2 mm. It is prepared by hot pressing and polarization of piezoelectric ceramic PZT-5H and polyvinylidene fluoride PVDF in a ratio of 4:96 or 6:94, and an external addition of carbon black with a mass fraction of 0.2% to 0.3%. The hot pressing temperature is 200°C to 220°C, the hot pressing pressure is 40MPa to 45MPa, the polarization time is 30 to 35 minutes, the polarization electric field strength is 2kV / mm to 3kV / mm, and the polarization temperature is 120°C to 140°C.

6. The asphalt pavement crack diagnosis method according to any one of claims 1 to 4, characterized in that: The external packaging shape of the overall structure is a cylinder, the outer diameter of the cylinder is 20 to 22 cm, and the inner diameter is 18 to 20 cm; The packaging structure includes three parts from top to bottom: a top cover, an intermediate shell and a bottom shell; wherein, the data acquisition and wireless transmission module is placed in the bottom shell, and buffer rubber pads are placed in the upper and lower ends of the bottom shell for load buffering; the piezoelectric transducer and sensor module is placed in the intermediate shell, and is connected to the data acquisition and wireless transmission module through a wire from the bottom of the intermediate shell, the gap part of the intermediate shell is filled with epoxy resin, and the top cover is covered after a rubber gasket is placed on the top.

7. The asphalt pavement crack diagnosis method according to any one of claims 1 to 4, characterized in that: The core chip of the data acquisition and wireless transmission module is STM32WLE5CC, a super capacitor is used as an energy storage device, and the wireless module of the core chip selects the LORA mode.

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