Device and method for detecting void ratio of drainage asphalt pavement

Abstract

The drainage asphalt pavement void ratio detection device comprises a device shell, the device shell is of a barrel-shaped structure with an opening in the lower end, the opening lower end of the device shell is in sealed connection with the upper surface of a detected pavement, and a supporting plate is arranged in the middle of the interior of the device shell; a fixing device is arranged between the center of the upper surface of the supporting plate and the top face in the device shell and is of a Chinese character'zhong '-shaped structure, and the center of the supporting plate and the top face of the device shell are each provided with an opening identical to the interior of the fixing device, so that gas at the lower end in the device shell penetrates through the interior of the fixing device and is exhausted from the upper end. The method does not need to perform coring excavation on the detected pavement, does not damage the pavement structure, has no influence on the quality of the detected pavement, can greatly improve the detection speed of the void ratio of the drainage asphalt pavement, and provides lossless, accurate and efficient data support for pavement detection maintenance or repair decision.

Description

Technical Field

[0001] The invention relates to the technical field of asphalt pavement drainage detection technology, in particular to a drainage asphalt pavement void ratio detection device and a detection method thereof. Background Art

[0002] OGFC (Open-Graded Friction Course) is a special drainage asphalt concrete pavement structure, which is characterized by the use of larger aggregates in the surface layer to increase the drainage performance of the pavement and reduce road noise. Void ratio detection is one of the important indicators for evaluating the quality of OGFC pavement. Void ratio refers to the proportion of voids between asphalt concrete aggregates in the pavement to the total volume. By detecting the void ratio, the density and durability of the pavement can be evaluated, and it helps determine whether maintenance or repair work is needed.

[0003] At present, there are two main types of methods for detecting the void ratio of pavement surface layers: density and physical indicators. Density detection methods mainly include core drilling method, nuclear density meter method, non-nuclear density meter method, etc., which determine the void ratio by detecting the pavement density or density-related indicators. These methods are highly accurate, but the core excavation and indoor test tests result in low work efficiency. Physical indicator detection methods mainly include water permeability coefficient method, which indirectly determines the void ratio by detecting relevant physical indicators of the pavement, but the water permeability coefficient method is time-consuming and cumbersome to operate. In order to further quickly, comprehensively and accurately evaluate the quality of OGFC pavement, it is necessary to develop a drainage asphalt pavement void ratio detection device. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the existing defects and provide a device for detecting the void ratio of a drainable asphalt pavement, which does not require coring and excavation of the detected pavement, does not damage the pavement structure, and has no effect on the quality of the detected pavement. It can greatly improve the detection speed of the void ratio of a drainable asphalt pavement, and provide non-destructive, accurate and efficient data support for pavement detection, maintenance or repair decisions, and can effectively solve the problems in the background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: A porosity detection device for a porous asphalt pavement, comprising a device housing. The device housing is a barrel-shaped structure with an open bottom end, and the open bottom end of the device housing is sealingly connected to the upper surface of the detection road surface. A support plate is arranged in the middle of the device housing. There is a fixing device between the center of the upper surface of the support plate and the inner top surface of the device housing. The fixing device is in the shape of a Chinese character 'zhong'. The center of the support plate and the top surface of the device housing are respectively provided with openings identical to those inside the fixing device, so that the gas at the lower end inside the device housing passes through the inside of the fixing device and is discharged from the upper end. An axial flow fan for blowing air to the outside of the device housing is arranged at the upper end inside the fixing device. A wind speed sensor for detecting the speed when the gas in the device housing is led out is fixed in the middle inside the fixing device through a bracket. A signal sensor for detecting wind pressure and temperature is arranged at the open upper end of the device housing. Moreover, a display and control terminal for controlling the device is arranged on the upper surface of the device housing, and a storage battery for supplying power to the device is arranged on the upper surface of the support plate.

[0006] Further, the display and control terminal is composed of a coordinate positioning chip, a control processing unit, a 4G communication module, an LCD module, and a storage module. Among them, the LCD module realizes human-computer interaction and transmits control signals to the control processing unit to realize the control of the detection device by the operator. When the operator selects to start the detection, the LCD module sends a start signal to the control processing unit. The control processing unit collects and processes this signal, and then sends a start signal to the axial flow fan to control the axial flow fan to work. The control processing unit is used to receive the wind speed signals sent by the signal sensor and the wind speed sensor. Through an algorithm, it determines that when the axial flow fan is working, the air wind speed in the passage of the fixing device reaches a balanced state, and then sends a stop signal to the axial flow fan. At the same time, the control processing unit calculates the wind speed signal, wind pressure signal, and temperature signal in the balanced state to obtain the pavement porosity, and collects and processes the coordinate information sent by the coordinate positioning chip, and then sends it to the 4G communication module. The 4G communication module processes the signal and sends it to the customer terminal through the 4G wireless network for viewing. The storage module stores the pavement porosity data, which is convenient for users to view historical data through the LCD module. At the same time, the historical data can also be exported through the USB transmission interface, and the data can be downloaded to the external storage device simply and quickly.

[0007] Further, a rubber sealing ring is arranged on the outer side of the lower end of the device housing, and the lower end of the cross-section of the rubber sealing ring is in a wavy structure.

[0008] Further, a handling handle is connected to the upper surface of the device housing by bolts. The handling handle is in an inverted U-shaped structure.

[0009] Furthermore, the wind speed sensor includes a connecting shell connected to the fixing device through a mounting frame, a rotating shaft is provided in the middle of the connecting shell, a rotating outer shell is provided on the upper end of the rotating shaft, blades are evenly provided on the outer side of the rotating outer shell, a detection protrusion is provided in the middle of the outer side of the rotating shaft, and a detection component for detecting the detection protrusion is provided inside the connecting shell.

[0010] A detection method for a drainage asphalt pavement void ratio detection device comprises the following steps: taking a handle to place the device on the upper surface of a detection pavement to be detected, the lower surface of the device housing is in sealed contact with the upper surface of the detection pavement, and an axial flow fan is operated to extract the gas at the lower end of the device housing to a negative pressure, while external gas passes through the detection pavement and enters the lower end of the device housing. When the airflow passes through a wind speed sensor, the wind speed sensor detects the wind speed of the airflow, and then the wind pressure and temperature are detected by the wind pressure sensor and temperature sensor on the signal sensor, thereby transmitting the wind pressure signal and temperature signal to a display and control terminal, and the wind speed sensor detects the wind speed information, thereby transmitting the wind speed signal to the display and control terminal, and the pavement void ratio is calculated by the display and control terminal.

[0011] Furthermore, the display and control terminal calculates in the following manner:

[0012] When the exhaust fan starts working:

[0013] When this condition is met, V i =V n ,

[0014] At this time, the void ratio:

[0015]

[0016] Where V n The n in the code represents the detection sampling sequence, which increases by 1 every 500ms. i represents the air velocity in equilibrium state, the signal unit is m / s, k3, k2 and k1 represent the regression coefficients of wind speed of asphalt pavement with different drainage properties, P represents the air pressure signal in equilibrium state, the unit is Pa, k P , k P1 and k P0 They represent the regression coefficients of air pressure of asphalt pavements with different drainage properties, T represents the air temperature signal in equilibrium state (unit: ℃), k1 represents the regression coefficient of air temperature, and ε represents the void space of asphalt pavement with different drainage properties (unit: %).

[0017] Furthermore, when processing wind pressure signals, temperature signals and wind speed signals, the validity of each sensor output data cannot be determined due to equipment hardware characteristic errors and environmental indifference. At the same time, there is a physical correlation between wind speed, wind pressure and temperature signals. If the data of a certain sensor deviates from the reasonable range of other signals, it may indicate that the output of the sensor is invalid. Therefore, the output data must be judged before fusion calculation. The authenticity of each sensor measurement data is judged based on the relationship and full use of prior knowledge.

[0018] N sensors are used for temperature measurement, X1, X2…XN represent the physical values ​​output by the N sensors, p(x1), p(x2)…p(XN) represent the probability density functions of X1, X2…XN, all of which obey the normal distribution; x1, x2…xN represent the samples of X1, X2…XN, respectively; then the confidence distance is

[0019]

[0020] Formula (1) represents the confidence distance of , and similarly, formula (2) represents the confidence distance of ; where

[0021]

[0022] According to the above formula, dij reflects the degree of support of the data output by sensor i for the data output by sensor j; similarly, the confidence distance matrix can be calculated by this method as follows:

[0023]

[0024] After obtaining the confidence distance matrix, it is necessary to establish a relationship matrix to judge the support degree and validity of the sensor output data; combining the concept of membership in fuzzy mathematics, the thresholds δ1 and δ2 are introduced; when the confidence distance meets the requirements, it means that the value output by temperature sensor i supports the value output by temperature sensor j; otherwise, it means that the value output by temperature sensor i does not support the value output by temperature sensor j, as shown in formula (5}

[0025]

[0026] Because N sensors measure the same temperature, the theoretical values ​​are the same. However, due to sensor accuracy and error, the measured values ​​have certain differences. The higher the support level among N sensors, the closer the sensor is to the true value. Therefore, the values ​​with high support level are selected for fusion calculation to further improve the accuracy.

[0027] Get the relationship matrix ψ

[0028]

[0029] Due to the continuous changes in operating conditions and changes in various parameters within the sensor itself, the uncertainty of the measured temperature value increases over time. Therefore, Bayesian estimation fusion needs to describe the changes in uncertain dynamics. The m valid data selected by the relationship matrix are expressed as (x1, x2, x3…xm). The conditional probability density function of the measured parameters can be obtained by the following formula:

[0030]

[0031] Where: μ is the measured parameter and obeys the normal distribution N(μ0,σ0), Xi also obeys the normal distribution N(μ,σk), so we can get

[0032]

[0033] Where:

[0034]

[0035] Substituting equation (10) and equation (11) into equation (9), it is easy to obtain p(μ|x1, x2, x3...x m ) also obeys the normal distribution, assuming that it obeys N(μN,σ N )Right now:

[0036]

[0037] Combining equation (9) and equation (11) we can get the result:

[0038]

[0039] The Bayesian estimation algorithm is used to determine the fault of the measured acquisition sensor; the specific steps can be summarized as follows:

[0040] First, obtain the value of each sensor; second, perform Bayesian estimation on the data of each sensor; third, set the difference between the measured sensor and the fusion result; fourth, calculate the difference between the measured sensor and the fusion result, and consider it a fault if the difference exceeds the value; according to the above steps, fault judgment can be made for each measured sensor.

[0041] Compared with the prior art, the beneficial effects of the present invention are: the drainage asphalt pavement void ratio detection device and detection method thereof have the following advantages:

[0042] 1. The drainage asphalt pavement void ratio detection device of the present invention does not require coring and excavation of the detected pavement, does not damage the pavement structure, and has no effect on the quality of the detected pavement.

[0043] 2. The present invention can greatly improve the detection speed of the void ratio of drainable asphalt pavement, and provide non-destructive, accurate and efficient data support for pavement inspection, maintenance or repair decisions.

[0044] 3. The present invention has a simple structure. The handle makes it easier to take the device. The rubber sealing ring with a wavy structure on the lower surface forms multiple seals between the lower surface of the device housing and the detection road surface, thereby making the connection and sealing between the device housing and the detection road surface better and making the detection more accurate.

[0045] 4. When the axial flow fan of the present invention is working, the airflow at the lower end of the device casing is extracted. When the airflow passes through the wind speed sensor, the blades and the rotating casing are driven by the airflow to rotate, and the rotating casing drives the rotating shaft to rotate. The rotating shaft drives the detection convex point to rotate, and the detection convex point is detected by the detection member to detect the wind speed of the airflow. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a schematic diagram of the structure of the present invention;

[0047] Figure 2 It is a schematic diagram of the front structure of the present invention;

[0048] Figure 3 It is a schematic diagram of the cross-sectional structure of the present invention;

[0049] Figure 4 It is a schematic diagram of the structure of the wind speed sensor of the present invention;

[0050] Figure 5 This is a schematic diagram of the structure of the rubber sealing ring of the present invention;

[0051] Figure 6 This is a schematic diagram of the airflow direction structure of the present invention;

[0052] Figure 7 This is a schematic diagram of the work flow structure of the display and control terminal of the present invention;

[0053] Figure 8 It is a schematic diagram of the signal detection process structure of the detection device of the present invention;

[0054] Fig. 9 It is a schematic diagram of the detection process structure of the present invention.

[0055] In the figure: 1 detection road surface, 2 rubber sealing ring, 3 device housing, 4 battery, 5 wind speed sensor, 51 blade, 52 connecting shell, 53 rotating shell, 54 rotating shaft, 55 detection convex point, 56 detection part, 6 axial flow fan, 7 signal sensor, 8 pick-up handle, 9 fixing device, 10 support plate, 11 display and control terminal. DETAILED DESCRIPTION

[0056] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0057] Please refer to Figure 1-9 , the present invention provides a technical solution: a void ratio detection device for a porous asphalt pavement, including a device housing 3. The device housing 3 is a barrel-shaped structure with an open lower end. The open lower end of the device housing 3 is hermetically connected to the upper surface of the detection road surface 1. A support plate 10 is arranged in the middle of the device housing 3. There is a fixing device 9 between the center of the upper surface of the support plate 10 and the inner top surface of the device housing 3. The fixing device 9 is in the shape of the Chinese character 'zhong'. Openings identical to the inside of the fixing device 9 are respectively arranged at the center of the support plate 10 and the top surface of the device housing 3. Thus, the gas at the lower end inside the device housing 3 passes through the inside of the fixing device 9 and is discharged from the upper end. An axial flow fan 6 that blows air to the outside of the device housing 3 is arranged at the upper end inside the fixing device 9. A wind speed sensor 5 for detecting the speed when the gas in the device housing 3 is led out is fixed in the middle of the inside of the fixing device 9 through a bracket. A signal sensor 7 for detecting wind pressure and temperature is arranged at the upper end opening of the device housing 3. Moreover, a display and control terminal 11 for controlling the device is arranged on the upper surface of the device housing 3. And a storage battery 4 for supplying electrical energy to the device is arranged on the upper surface of the support plate 10. The signal sensor 7 includes a wind pressure sensor and a temperature sensor. The wind pressure and temperature are detected by the wind pressure sensor and the temperature sensor. Thus, the wind pressure signal and the temperature signal are transmitted to the display and control terminal 11. The wind speed sensor 5 detects the wind speed information. Thus, the wind speed signal is transmitted to the display and control terminal 11.

[0058] The display and control terminal 11 is composed of a coordinate positioning chip, a control processing unit, a 4G communication module, an LCD module and a storage module, wherein the LCD module realizes human-computer interaction and transmits a control signal to the control processing unit to realize the operator's control over the detection equipment. When the operator chooses to start the detection, the LCD module sends a start signal to the control processing unit, and the control processing unit collects and processes the signal, and then sends a start signal to the axial flow fan 6 to control the axial flow fan 6 to work; the control processing unit is used to receive the wind speed signal sent by the signal sensor 7 and the wind speed sensor 5, and determines through the algorithm that the axial flow fan 6 is working, through the fixing device 9 The air speed in the channel reaches a balanced state, and then a stop signal is sent to the axial flow fan 6. At the same time, the control processing unit calculates the wind speed signal, wind pressure signal, and temperature signal in the balanced state to obtain the pavement void ratio, and collects and processes the coordinate information sent by the coordinate positioning chip, and then sends it to the 4G communication module. The 4G communication module processes the signal and sends it to the client terminal through the 4G wireless network for reference; the storage module stores the pavement void ratio data, which is convenient for users to view historical data through the LCD module. At the same time, the historical data can also be exported through the USB transmission interface, and the data can be downloaded to the external storage device simply and quickly.

[0059] A rubber sealing ring 2 is provided on the outer side of the lower end of the device housing 3. The lower end of the cross-section of the rubber sealing ring 2 is a wavy structure. The rubber sealing ring 2 with a wavy structure on the lower surface forms multiple seals between the lower surface of the device housing 3 and the detection road surface 1, thereby making the sealing effect of the connection between the device housing 3 and the detection road surface 1 better.

[0060] The upper surface of the device housing 3 is connected with a pick-up handle 8 by bolts. The pick-up handle 8 is an inverted U-shaped structure. The pick-up handle 8 makes it more convenient to pick up the device.

[0061] The wind speed sensor 5 includes a connecting shell 52 connected to the fixing device 9 through a mounting frame, a rotating shaft 54 ​​is rotatably connected in the middle of the connecting shell 52, a rotating shell 53 is arranged on the upper end of the rotating shaft 54, blades 51 are evenly arranged on the outer side of the rotating shell 53, a detection convex point 55 is arranged in the middle of the outer side of the rotating shaft 54, and a detection member 56 for detecting the detection convex point 55 is arranged inside the connecting shell 52. When the axial flow fan 6 is working, the airflow at the lower end of the device shell 3 is extracted, and when the airflow passes through the wind speed sensor 5, the blades 51 and the rotating shell 53 are driven to rotate by the airflow, the rotating shaft 54 ​​is driven to rotate by the rotating shell 53, the detection convex point 55 is driven to rotate by the rotating shaft 54, and the detection convex point 55 is detected by the detection member 56, so as to detect the wind speed of the airflow passing through. The drainage asphalt pavement void ratio detection device does not need to perform coring and excavation on the detection pavement, does not damage the pavement structure, has no effect on the detection pavement quality, can greatly improve the detection speed of the drainage asphalt pavement void ratio, and provides non-destructive, accurate and efficient data support for pavement detection maintenance or repair decisions.

[0062] A method for detecting a void ratio detection device for a drainable asphalt pavement is provided. The device is conveniently picked up by taking a handle 8, and then the device is placed on the upper surface of a detection pavement 1 to be detected. A rubber sealing ring 2 with a wavy structure on the lower surface forms multiple seals between the lower surface of the device housing 3 and the detection pavement 1, so that the connection and sealing effect between the device housing 3 and the detection pavement 1 is better. Then, an axial flow fan 6 is operated to extract the gas at the lower end of the device housing 3 to a negative pressure, and the external gas passes through the detection pavement 1 and enters the lower end of the device housing 3. When the airflow passes through the wind speed sensor 5, the airflow drives the blade 51 and the rotating housing 53 to rotate, and the rotating housing 53 drives the rotating shaft 54 ​​to rotate, and the rotating shaft 54 ​​drives the detection convex point 55 to rotate, and the detection convex point 55 is detected by the detection member 56 to detect the wind speed of the airflow, and then the wind pressure sensor and temperature sensor on the signal sensor 7 detect the wind pressure and temperature, thereby transmitting the wind pressure signal and the temperature signal to the display and control terminal 11, and the wind speed sensor 5 detects the wind speed information, thereby transmitting the wind speed signal to the display and control terminal 11;

[0063] The LCD module on the display and control terminal 11 sends a start signal to the control processing unit, which collects and processes the signal, and then sends a start signal to the axial flow fan 6 to control the axial flow fan 6 to work; the control processing unit is used to receive the wind speed signal sent by the signal sensor 7 and the wind speed sensor 5, and determines through an algorithm that when the axial flow fan 6 is working, the air wind speed in the channel of the fixing device 9 reaches a balanced state, and then sends a stop signal to the axial flow fan 6. At the same time, the control processing unit calculates the wind speed signal, wind pressure signal, and temperature signal in the balanced state to obtain the pavement void ratio, and collects and processes the coordinate information sent by the coordinate positioning chip, and then sends it to the 4G communication module. The 4G communication module processes the signal and sends it to the client terminal through the 4G wireless network for reference; the storage module stores the pavement void ratio data, which is convenient for users to view historical data through the LCD module, and can also export historical data through the USB transmission interface, so that the data can be downloaded to the external storage device easily and quickly;

[0064] The calculation formula of the display and control terminal 11 is:

[0065] When the exhaust fan starts working;

[0066]

[0067] <0.1, when this condition is met, V=Vn,

[0068] At this time, the void ratio:

[0069]

[0070] Where V n Represents the wind speed signal of the signal sensor when the detection starts; V n The n represents the detection sampling sequence, which increases by 1 every 500ms. V represents the air velocity signal in the equilibrium state in m / s. P represents the air pressure signal in the equilibrium state in Pa. T represents the air temperature signal in the equilibrium state in ℃. ε represents the void ratio in %.

[0071] When processing wind pressure signals, temperature signals and wind speed signals, the validity of each sensor output data cannot be determined due to equipment hardware characteristic errors and environmental indifference (such as the air flow characteristics described by the Bernoulli equation); at the same time, there is a physical correlation between wind speed, wind pressure and temperature signals. If the data of a sensor deviates from the reasonable range of other signals, it may indicate that the output of the sensor is invalid. Therefore, the output data must be judged before the fusion calculation. The authenticity of each sensor measurement data is judged based on the relationship and full use of prior knowledge.

[0072] N sensors are used for temperature measurement. X1, X2…XN represent the physical values ​​output by the N sensors. p(x1), p(x2)…p(xN) represent the probability density functions of X1, X2…XN, which all obey the normal distribution. x1, x2…xN represent the samples of X1, X2…XN. Then the confidence distance is

[0073]

[0074] Formula {1} represents the confidence distance of , and similarly, formula {2} represents the confidence distance of ; where

[0075]

[0076]

[0077] According to the above formula, dij reflects the degree of support of the data output by sensor i for the data output by sensor j; similarly, the confidence distance matrix can be calculated by this method as follows:

[0078]

[0079] After obtaining the confidence distance matrix, it is necessary to establish a relationship matrix to judge the support degree and validity of the sensor output data; combining the concept of membership in fuzzy mathematics, the thresholds δ1 and δ2 are introduced; when the confidence distance meets the requirements, it means that the value output by temperature sensor i supports the value output by temperature sensor j; otherwise, it means that the value output by temperature sensor i does not support the value output by temperature sensor j, as shown in formula (5}

[0080]

[0081] Because N sensors measure the same temperature, the theoretical values ​​are the same. However, due to sensor accuracy and error, the measured values ​​have certain differences. The higher the support level among N sensors, the closer the sensor is to the true value. Therefore, the values ​​with high support level are selected for fusion calculation to further improve the accuracy.

[0082] Get the relationship matrix ψ

[0083]

[0084] Due to the continuous changes in operating conditions and changes in various parameters within the sensor itself, the uncertainty of the measured temperature value increases over time. Therefore, Bayesian estimation fusion needs to describe the changes in uncertain dynamics. The m valid data selected by the relationship matrix are expressed as (x1, x2, x3…xm). The conditional probability density function of the measured parameters can be obtained by the following formula:

[0085]

[0086] Where: μ is the measured parameter and obeys the normal distribution N(u0,σ0), Xi also obeys the normal distribution N(μ,σk), so we can get

[0087]

[0088] Where:

[0089]

[0090] Substituting equation (10) and equation (11) into equation (9), it is easy to obtain p(μ|x1, x2, x3...x m ) also obeys the normal distribution, assuming that it obeys N(μN,σ N )Right now:

[0091]

[0092] Combining equation (9) and equation (11) we can get the result:

[0093]

[0094] The Bayesian estimation algorithm is used to determine the fault of the measured acquisition sensor; the specific steps can be summarized as follows:

[0095] First, obtain the value of each sensor; second, perform Bayesian estimation on the data of each sensor; third, set the difference between the measured sensor and the fusion result; fourth, calculate the difference between the measured sensor and the fusion result, and consider it a fault if the difference exceeds the value; according to the above steps, fault judgment can be made for each measured sensor.

[0096] While the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that many changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the invention.

Claims

1. A device for detecting void content of a drainable asphalt pavement, comprising a device housing (3), characterized in that: The device housing (3) is a barrel-shaped structure with an open lower end. The open lower end of the device housing (3) is sealingly connected to the upper surface of the detection road surface (1). A support plate (10) is arranged in the middle of the device housing (3). A fixing device (9) is provided between the center of the upper surface of the support plate (10) and the inner top surface of the device housing (3). The fixing device (9) is in the shape of the Chinese character 'zhong'. Openings identical to the inside of the fixing device (9) are respectively arranged at the center of the support plate (10) and the top surface of the device housing (3). Thus, the gas at the lower end inside the device housing (3) passes through the inside of the fixing device (9) and is discharged from the upper end. An axial flow fan (6) for blowing air to the outside of the device housing (3) is arranged at the upper end inside the fixing device (9). An anemometer (5) for detecting the speed when the gas in the device housing (3) is led out is fixed in the middle of the fixing device (9) through a bracket. A signal sensor (7) for detecting wind pressure and temperature is arranged at the open upper end of the device housing (3). Moreover, a display and control terminal (11) for controlling the device is arranged on the upper surface of the device housing (3). And a storage battery (4) for supplying power to the device is arranged on the upper surface of the support plate (10).

2. A device for detecting void ratio of a drainable asphalt pavement according to claim 1, characterized in that: The display and control terminal (11) consists of a coordinate positioning chip, a control processing unit, a 4G communication module, an LCD module, and a storage module. Among them, the LCD module realizes human-machine interaction and transmits control signals to the control processing unit to realize the control of the detection device by the operator. When the operator selects to start the detection, the LCD module sends a start signal to the control processing unit. The control processing unit collects and processes this signal, and then sends a start signal to the axial flow fan (6) to control the axial flow fan (6) to work. The control processing unit is used to receive the wind speed signals sent by the signal sensor (7) and the anemometer (5). Through an algorithm, it determines that when the axial flow fan (6) is working, the air speed in the channel of the fixing device (9) reaches an equilibrium state, and then sends a stop signal to the axial flow fan (6). At the same time, the control processing unit calculates the wind speed signal, wind pressure signal, and temperature signal in the equilibrium state to obtain the road surface void ratio, and collects and processes the coordinate information sent by the coordinate positioning chip, and then sends it to the 4G communication module. The 4G communication module processes the signal and sends it to the customer terminal through the 4G wireless network for viewing. The storage module stores the road surface void ratio data, which is convenient for the user to view historical data through the LCD module. At the same time, the historical data can also be exported through the USB transmission interface, and the data can be downloaded to the external storage device simply and quickly.

3. The device for detecting void ratio of a drainable asphalt pavement according to claim 1, characterized in that: A rubber sealing ring (2) is arranged on the outer side of the lower end of the device housing (3). The lower end of the cross-section of the rubber sealing ring (2) is in a wavy structure.

4. The device for detecting void ratio of a drainable asphalt pavement according to claim 1, characterized in that: A handling handle (8) is connected to the upper surface of the device housing (3) by bolts. The handling handle (8) is in an inverted U-shaped structure.

5. The device for detecting void ratio of a drainable asphalt pavement according to claim 1, characterized in that: The wind speed sensor (5) comprises a connecting shell (52) connected to a fixing device (9) via a mounting frame, a rotating shaft (54) is provided in the middle of the connecting shell (52) for rotational connection, a rotating shell (53) is provided at the upper end of the rotating shaft (54), blades (51) are evenly provided on the outer side of the rotating shell (53), a detection convex point (55) is provided in the middle of the outer side of the rotating shaft (54), and a detection member (56) for detecting the detection convex point (55) is provided in the interior of the connecting shell (52).

6. The detection method of the void ratio detection device of a drainable asphalt pavement according to claim 1 is characterized by: By taking the handle (8), the device is placed on the upper surface of the detection road surface (1) to be detected, and the lower surface of the device housing (3) is in sealed contact with the upper surface of the detection road surface (1). The axial flow fan (6) works to extract the gas at the lower end of the device housing (3) to a negative pressure, and the external gas enters the lower end of the device housing (3) through the detection road surface (1). When the airflow passes through the wind speed sensor (5), the wind speed sensor (5) detects the wind speed of the airflow, and then the wind pressure and temperature are detected by the wind pressure sensor and temperature sensor on the signal sensor (7), thereby transmitting the wind pressure signal and the temperature signal to the display and control terminal (11), and the wind speed sensor (5) detects the wind speed information, thereby transmitting the wind speed signal to the display and control terminal (11), and the display and control terminal (11) calculates the three signals to obtain the road surface void ratio.

7. The detection method of the void ratio detection device for drainable asphalt pavement according to claim 6 is characterized by: The display and control terminal (11) calculates in the following manner: When the exhaust fan starts working: When this condition is met, V i =V n , At this time, the void ratio is: Where V n The n in the code represents the detection sampling sequence, which increases by l every 500ms. i represents the air velocity in equilibrium state, the signal unit is m / s, k3, k2 and k1 represent the regression coefficients of wind speed of asphalt pavement with different drainage properties, P represents the air pressure signal in equilibrium state, the unit is Pa, k F , k F1 and k F0 They represent the regression coefficients of air pressure of asphalt pavements with different drainage properties, T represents the air temperature signal in equilibrium state in ℃, k1 is the regression coefficient of air temperature, and ε represents the void ratio of asphalt pavement with different drainage properties in %.

8. The detection method of the void ratio detection device for drainable asphalt pavement according to claim 6 is characterized by: When processing wind pressure signals, temperature signals and wind speed signals, the validity of each sensor output data cannot be determined due to equipment hardware characteristic errors and environmental indifference. At the same time, there is a physical correlation between wind speed, wind pressure and temperature signals. If the data of a sensor deviates from the reasonable range of other signals, it may indicate that the output of the sensor is invalid. Therefore, the output data must be judged before fusion calculation. The authenticity of each sensor measurement data is judged based on the relationship and full use of prior knowledge. N sensors are used for temperature measurement. X1, X2…XN represent the physical values ​​output by the N sensors. p(x1), p(x2)…p(xN) represent the probability density functions of X1, X2…XN, which all obey the normal distribution. x1, x2…xN represent the samples of X1, X2…XN. Then the confidence distance is Formula (1) represents the confidence distance of , and similarly, formula (2) represents the confidence distance of ; where According to the above formula, dij reflects the degree of support of the data output by sensor i for the data output by sensor j; similarly, the confidence distance matrix can be calculated by this method as follows: After obtaining the confidence distance matrix, it is necessary to establish a relationship matrix to judge the support degree and validity of the sensor output data; combining the concept of membership in fuzzy mathematics, the thresholds δl and δ2 are introduced; when the confidence distance meets the requirements, it means that the value output by temperature sensor i supports the value output by temperature sensor j; otherwise, it means that the value output by temperature sensor i does not support the value output by temperature sensor j, as shown in formula (5} Because N sensors measure the same temperature, the theoretical values ​​are the same. However, due to sensor accuracy and error, the measured values ​​have certain differences. The higher the support level among N sensors, the closer the sensor is to the true value. Therefore, the values ​​with high support level are selected for fusion calculation to further improve the accuracy. Get the relationship matrix ψ Due to the continuous changes in operating conditions and changes in various parameters within the sensor itself, the uncertainty of the measured temperature value increases over time. Therefore, Bayesian estimation fusion needs to describe the dynamic changes of uncertainty. The m valid data selected by the relationship matrix are expressed as (xl, x2, x3...xm). The conditional probability density function of the measured parameters can be obtained by the following formula: Where: μ is the measured parameter and obeys the normal distribution N(μ0,σ0), Xi also obeys the normal distribution N(μ,σk), so we can get Where: Substituting equation (10) and equation (11) into equation (9), it is easy to obtain p(μ|x1, x2, x3...x m ) also obeys the normal distribution, assuming that it obeys N(μN,σ N )Right now: Combining equation (9) and equation (11) we can get the result: The Bayesian estimation algorithm is used to determine the fault of the measured acquisition sensor; the specific steps can be summarized as follows: First, obtain the value of each sensor; second, perform Bayesian estimation on the data of each sensor; third, set the difference between the measured sensor and the fusion result; fourth, calculate the difference between the measured sensor and the fusion result, and consider it a fault if the difference exceeds the value; according to the above steps, fault judgment can be made for each measured sensor.

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