Public road deflection detection method

Abstract

The invention relates to a public road deflection detection method, which comprises the following steps of: 1, arranging a bearing plate on a road to be detected, arranging a central sensor at the central position of the bearing plate, and arranging a plurality of peripheral sensors around the central sensor; step 2, carrying out free falling body pre-impact on the bearing plate; and step 3, carrying out multiple free falling body impacts on the bearing plate by using a drop hammer with actual load weight, enabling the center sensor to record multiple deflection measurement values, and calculating a deflection measurement value standard deviation S of multiple impact tests at the center sensor by taking an arithmetic mean value of the multiple deflection measurement values as a deflection measurement mean value # imgabs0 #. According to the invention, the vehicle load can be effectively simulated, so that the actual bearing capacity of the road can be evaluated more effectively.

Description

Technical Field

[0001] The present invention relates to the technical field of public road detection, and particularly relates to a method for detecting the deflection of a public road. Background Art

[0002] Currently, the commonly used deflection test methods mainly include the Benkelman beam method. The Benkelman beam method is a commonly used method for detecting the deflection of subgrade and pavement. By loading with a load-carrying vehicle and measuring the rebound deflection with a dial gauge, this method is applicable to various subgrades and pavements, can be used to evaluate their overall bearing capacity, and can also provide a basis for pavement structure design. Its working principle is relatively simple and it is also relatively easy to operate. During the test, only need to place the end of the measuring beam at a measuring point about 10 cm in front of the double-wheel gap of the rear axle of the measuring vehicle, support the rear one-third of the beam on the base through a fulcrum, and install a dial gauge at the end of the beam. When the vehicle travels at a low speed, record the reading of the dial gauge, and record the reading again after the vehicle has left. The difference between the two readings can be regarded as the rebound deflection value.

[0003] As a typical static deflection detection method, the Benkelman beam method mainly measures the maximum rebound deflection value under vehicle load. Since the Benkelman beam method fails to effectively simulate the action of vehicle load, its detection results are difficult to evaluate the actual bearing capacity of the road. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for detecting the deflection of a public road, which can effectively simulate vehicle load, so as to make a more effective evaluation of the actual bearing capacity of the road.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A method for detecting the deflection of a public road, comprising the following steps:

[0007] Step 1: Set a bearing plate on the road to be measured, set a central sensor at the center position of the bearing plate, and set a plurality of peripheral sensors around the central sensor;

[0008] Step 2: Conduct a free-fall pre-impact on the bearing plate;

[0009] Step 3: Use a drop hammer with the actual load weight to conduct multiple free-fall impacts on the bearing plate, so that the central sensor records multiple deflection measurement values, and take the arithmetic mean of the multiple deflection measurement values as the average deflection measurement value Calculate the standard deviation S of the deflection measurement values of multiple impact tests at the central sensor, n is the number of free-fall impacts, calculate the coefficient of variation C v , If the coefficient of variation C v is greater than 10%, retesting is required;

[0010] Step 4: Repeat step 3 multiple times by increasing the load weight step by step, and plot the average deflection measurement of the center sensor at different load weights P and the corresponding load weight P. The curve relationship is fitted by a polynomial model: a and b are unknown coefficients. If b is greater than 0, it indicates that the roadbed is softened or hollow.

[0011] Step 5: Verify the measured data of step 4 and record the deflection measurement value under the jth load weight as D j实测 , the predicted value of the above polynomial model is D j预测 , through D j实测 、D j预测 and D j实测 Average value Calculate the coefficient of determination R 2 ,

[0012]

[0013] If R 2 If it is greater than 0.95, it is determined that the road has a nonlinear response;

[0014] Step 6: Calculate the representative deflection value L r , Z is the coefficient related to the confidence level, and Z is 1.5-2.0, corresponding to 90% to 95% confidence.

[0015] Specifically, in step 1, 7-9 peripheral sensors are set around the central sensor.

[0016] Specifically, in step 2, a drop weight of 50% of the actual load weight is used to perform 1-2 free-fall pre-impacts on the bearing plate.

[0017] Specifically, in step three, a drop hammer with actual load weight is used to perform free-fall impact on the bearing plate 3-5 times.

[0018] Specifically, in step 1, the distance between the peripheral sensors and the central sensor is less than 2.5 m.

[0019] Specifically, in step 4, the load weight is divided into three levels, namely 200KG, 240KG, and 280KG.

[0020] Specifically, in step 4, the interval between each level of loading is 1-2 minutes.

[0021] Compared with the prior art, the present invention has the following beneficial effects:

[0022] The detection method of the present invention simulates vehicle loads through the impact load generated by a free-falling hammer. This impact load can effectively simulate vehicle loads. At the same time, by changing the weight of the hammer, the simulation of different vehicle loads can be achieved. During the detection process, the sensor will record 9 deflection values, and then draw a deflection basin. The entire detection process is precisely controlled by a computer.

[0023] The impact load generated instantaneously by the falling hammer acts on the bearing plate. At this time, sensors distributed at different distances will detect the deformation of the surface of the structural layer and transmit these signals to the computer for processing in real time. Based on the received signals, the computer can automatically calculate key data such as load, average deflection, measuring point spacing, standard deviation, coefficient of variation, and representative deflection value. In addition, the instrument can further back-calculate the elastic modulus of each layer of material, providing strong support for pavement structure design.

[0024] The detection method of the present invention belongs to the category of dynamic deflection detection. It can more effectively simulate the action of vehicle loads, can quickly and safely collect a large amount of deflection basin information, and has the advantage of not damaging the road surface. The detection of the present invention not only eliminates various influencing factors such as human reading error and air pressure change error, but also ensures the accuracy of the test results due to its high-precision displacement sensor. Specific Embodiments

[0025] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments.

[0026] A method for detecting the deflection of a public road includes the following steps:

[0027] Step 1: Set a bearing plate on the road to be measured, set a central sensor at the center position of the bearing plate, and set several peripheral sensors around the central sensor;

[0028] Step 2: Conduct a free-fall pre-impact on the bearing plate;

[0029] Step 3: Conduct multiple free-fall impacts on the bearing plate with a falling hammer of the actual load weight, so that the central sensor records multiple deflection measurement values, and take the arithmetic mean of the multiple deflection measurement values as the average deflection measurement value Calculate the standard deviation of the deflection measurement values of multiple impact tests at the central sensor n is the number of free-fall impacts, calculate the coefficient of variation C v , If the coefficient of variation C v is greater than 10%, remeasurement is required;

[0030] Step 4: Repeat step 3 multiple times by increasing the load weight step by step, and plot the average deflection measurement of the center sensor at different load weights P and the corresponding load weight P. The curve relationship is fitted by a polynomial model: a and b are unknown coefficients. If b is greater than 0, it indicates that the roadbed is softened or hollow.

[0031] Step 5: Verify the measured data of step 4 and record the deflection measurement value under the jth load weight as D j实测 , the predicted value of the above polynomial model is D j预测 , through D j实测 、D j预测 and D j实测 Average value Calculate the coefficient of determination R 2 ,

[0032]

[0033] If R 2 If it is greater than 0.95, it is determined that the road has a nonlinear response;

[0034] Step 6: Calculate the representative deflection value L r , Z is the coefficient related to the confidence level, and Z is 1.5-2.0, corresponding to 90% to 95% confidence.

[0035] Specifically, in step 1, 7-9 peripheral sensors are set around the central sensor.

[0036] Specifically, in step 2, a drop weight of 50% of the actual load weight is used to perform 1-2 free-fall pre-impacts on the bearing plate.

[0037] Specifically, in step three, a drop hammer with actual load weight is used to perform free-fall impact on the bearing plate 3-5 times.

[0038] Specifically, in step 1, the distance between the peripheral sensors and the central sensor is less than 2.5 m.

[0039] Specifically, in step 4, the load weight is divided into three levels, namely 200KG, 240KG, and 280KG.

[0040] Specifically, in step 4, the interval between each level of loading is 1-2 minutes.

[0041] The beneficial effects of the present invention are as follows:

[0042] In the present invention, the impact load generated by a freely falling hammer is used to simulate the vehicle load. This impact load can effectively simulate the vehicle load. At the same time, by changing the weight of the hammer and the height of the heavy hammer, the simulation of different vehicle loads can be achieved. During the detection process, the sensor will record 9 deflection values and then draw a deflection basin. The entire detection process is precisely controlled by a computer.

[0043] The impact load generated at the moment when the hammer falls acts on the bearing plate. At this time, sensors distributed at different distances will detect the deformation of the surface of the structural layer and transmit these signals to the computer for processing in real time. Based on the received signals, the computer can automatically calculate key data such as load, average deflection, measuring point spacing, standard deviation, coefficient of variation, and representative deflection value. In addition, the instrument can further back-calculate the elastic modulus of each layer of material, providing strong support for the pavement structure design.

[0044] The detection method of the present invention belongs to the category of dynamic deflection detection. It can more effectively simulate the action of vehicle load, can quickly and safely collect a large amount of deflection basin information, and has the advantage of not damaging the road surface. The detection of the present invention not only eliminates various influencing factors such as artificial reading error and air pressure change error, but also ensures the accuracy of the test results due to its high-precision displacement sensor.

[0045] The above is only a preferred embodiment of the present invention and does not impose any form of limitation on the present invention. Although the present invention has been disclosed as above with the preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to form equivalent embodiments by using the above-disclosed technical content without departing from the technical solution of the present invention. However, as long as it does not depart from the technical solution content of the present invention, any brief modification, equivalent change, and modification made to the above embodiment based on the technical essence of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A method for detecting the deflection of a public road, characterized in that, Including the following steps: Step 1: Set a bearing plate on the road to be measured, set a central sensor at the center position of the bearing plate, and set several peripheral sensors around the central sensor; Step 2: Conduct a free-fall pre-impact on the bearing plate; Step 3: Use a drop hammer with the actual load weight to conduct multiple free - fall impacts on the bearing plate, so that the central sensor records multiple deflection measurement values, and take the arithmetic mean of the multiple deflection measurement values as the average deflection measurement value Calculate the standard deviation of the deflection measurement values for multiple impact tests at the central sensor n is the number of free - fall impacts, calculate the coefficient of variation If the coefficient of variation C v is greater than 10%, re - measurement is required; Step 4: Gradually increase the load weight and perform Step 3 multiple times to plot the curve relationship between different load weights P and the average deflection measurement of the center sensor corresponding to the load weight P, and fit it through a polynomial model: where a and b are undetermined coefficients. If b is greater than 0, it indicates that there is subgrade softening or voiding in the road; ​ Step 5: Verify the measurement data in Step 4. Denote the deflection measurement value under the j-th load weight as D j实测 , and the predicted value predicted by the above polynomial model is D j预测 . Through D j实测 , D j预测 and D j实测 's average value Calculate the coefficient of determination R 2 , If R 2 is greater than 0.95, it is determined that the road has a non-linear response; Step 6: Calculate the representative deflection value L r , where Z is a coefficient related to the confidence level, and Z ranges from 1.5 to 2.0, corresponding to a confidence level of 90% to 95%.

2. The method for detecting the deflection of a public road according to claim 1, wherein: In Step 1, set 7 - 9 peripheral sensors around the central sensor.

3. The deflection detection method for public roads according to claim 1, characterized in that: In Step 2, conduct 1 - 2 free-fall pre-impacts on the bearing plate with a drop hammer of 50% of the actual load weight.

4. The deflection detection method for public roads according to claim 1, characterized in that: In Step 3, conduct 3 - 5 free-fall impacts on the bearing plate with a drop hammer of the actual load weight.

5. The deflection detection method for public roads according to claim 1, characterized in that: In Step 1, the distance between the peripheral sensors and the central sensor is less than 2.5m.

6. The deflection detection method for public roads according to claim 1, wherein: In Step 4, the load weights are in three levels, which are 200KG, 240KG, and 280KG respectively.

7. The method for detecting the deflection of a public road according to claim 1, wherein: In Step 4, the loading interval for each level is 1 - 2 minutes.

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