A method for detecting deflection of a public road

Abstract

The present application relates to a kind of public road deflection detection methods, comprising the following steps: step one: setting bearing plate in the road to be measured, setting a center sensor in the center position of bearing plate, setting several peripheral sensors around center sensor;Step two: free-fall pre-impact is carried out to bearing plate;Step three: with the drop hammer of actual load weight, bearing plate is impacted multiple times by free-fall, and center sensor records multiple deflection measurement values, and the arithmetic mean of multiple deflection measurement values is used as the deflection measurement average value, and the standard deviation S of the deflection measurement value of the multiple impact test of the center sensor is calculated.The present application can effectively simulate vehicle load, so as to make more effective evaluation to the actual bearing capacity of road.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of public road detection, in particular to a public road deflection detection method. BACKGROUND

[0002] At present, the commonly used deflection test methods mainly include the Beckman beam method, which is a commonly used method for detecting the deflection of roadbed and pavement. Through the loading of a truck and the measurement of a dial gauge, this method is suitable for various roadbeds and pavements, and can be used to evaluate the overall bearing capacity and provide a basis for pavement structure design. Its working principle is relatively simple and easy to operate. During testing, only the end of the measuring beam needs to be placed on the measuring point about 10 cm in front of the double-wheel wheel gap of the rear axle of the measuring vehicle, the rear third of the beam is supported on the base through the fulcrum, and a dial gauge is installed at the end of the beam. When the vehicle travels at a low speed, the reading of the dial gauge is recorded, and after the vehicle leaves, the reading is recorded again. The difference between the two readings is the rebound deflection value.

[0003] As a typical static deflection detection method, the Beckman beam method mainly measures the maximum rebound deflection value under the load of a vehicle. Since the Beckman beam method cannot effectively simulate the effect of driving load, its detection results are difficult to evaluate the actual bearing capacity of the road. SUMMARY

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

[0005] To achieve the above purpose, the present application provides the following technical scheme:

[0006] A public road deflection detection method, comprising the following steps:

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

[0008] Step 2: pre-impact of the free-fall of the bearing plate;

[0009] Step 3: multiple free-fall impacts of the bearing plate with a drop hammer of actual load weight, recording multiple deflection measurement values by the center sensor, and taking the arithmetic mean of the multiple deflection measurement values as the deflection measurement average value calculating the standard deviation S of the deflection measurement value of the multiple impact tests at the center sensor, n is the number of free-fall impacts, and the coefficient of variation C is calculated v , If the coefficient of variation C v is greater than 10%, retesting is required;

[0010] Step four: draw the curve relation between different load weight P and the deflection measurement average value of the center sensor corresponding to the load weight P by multiple times of step three with the load weight increasing step by step The curve relation is fitted by a polynomial model: a and b are to-be-determined coefficients, if b is greater than 0, it indicates that the road exists subgrade softening or voiding;

[0011] Step five: verifying the measurement data of step four, the deflection measurement value under the jth load weight is recorded as D j实测 , the predicted value predicted by the above polynomial model is D j预测 , the determination coefficient R j实测 is calculated by the average value of D j预测 , D j实测 and D 2 ,

[0012]

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

[0014] Step six: calculating the representative deflection value L r , Z is a coefficient related to the confidence level, Z takes 1.5-2.0, corresponding to 90%-95% confidence.

[0015] Specifically, in step one, 7-9 peripheral sensors are arranged around the center sensor.

[0016] Specifically, in step two, the load plate is pre-impacted by 1-2 times of free fall with a drop hammer of 50% of the actual load weight.

[0017] Specifically, in step three, the load plate is impacted by 3-5 times of free fall with a drop hammer of the actual load weight.

[0018] Specifically, in step one, the spacing between the peripheral sensor and the center sensor is less than 2.5m.

[0019] Specifically, in step four, the load weight is three levels, respectively 200KG, 240KG and 280KG.

[0020] Specifically, in step four, the interval of each load level is 1-2 minutes.

[0021] Compared with the prior art, the beneficial effects of the present application are:

[0022] ​The detection method of the present application simulates the vehicle load by the impact load generated by the free-falling hammer, and such impact load can effectively simulate the vehicle load. Meanwhile, by changing the hammer weight, the simulation of different vehicle loads can be realized. During the detection process, the sensor records 9 deflection values, and then the deflection basin is drawn. The whole detection process is accurately controlled by the computer.

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

[0024] The detection method of the present application belongs to the category of dynamic deflection detection, which can more effectively simulate the driving load, and can quickly and safely collect a large amount of deflection basin information, and has the advantage of not damaging the pavement. The detection of the present application 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 the high-precision displacement sensor. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the present application will be clearly and completely described below in combination with the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments.

[0026] A public road deflection detection method, comprising the following steps:

[0027] Step one: setting a bearing plate on the road to be detected, setting a center sensor at the center position of the bearing plate, and setting a plurality of peripheral sensors around the center sensor;

[0028] Step two: pre-impact of the free-falling bearing plate;

[0029] Step three: multiple free-falling impacts of the bearing plate by the hammer with the actual load weight, so that the center sensor records multiple deflection measurement values, and the arithmetic mean of the multiple deflection measurement values is taken as the deflection measurement average value Calculate the standard deviation of the deflection measurement values of the multiple impact tests of the center sensor n is the number of free-falling impacts, and the coefficient of variation C is calculated v , If the coefficient of variation C v is greater than 10%, retesting is required;

[0030] Step four: draw the curve relation between different load weight P and the average value of deflection measurement of the center sensor corresponding to the load weight P by multiple times of step three with the load weight increased step by step a, b are undetermined coefficients, if b is greater than 0, it indicates that the road exists subgrade softening or voiding; a, b are undetermined coefficients, if b is greater than 0, it indicates that the road exists subgrade softening or voiding;

[0031] Step five: check the measurement data of step four, and record the deflection measurement value under the jth load weight as D j实测 , the predicted value predicted by the above polynomial model is D j预测 , the average value of D j实测 , D j预测 and D j实测 determines the coefficient R 2 ,

[0032]

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

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

[0035] Specifically, in step one, 7-9 peripheral sensors are arranged around the center sensor.

[0036] Specifically, in step two, the load plate is pre-impacted by 1-2 times of free fall with a drop hammer of 50% of the actual load weight.

[0037] Specifically, in step three, the load plate is impacted by 3-5 times of free fall with a drop hammer of the actual load weight.

[0038] Specifically, in step one, the distance between the peripheral sensor and the center sensor is less than 2.5m.

[0039] Specifically, in step four, the load weight is three levels, which are 200KG, 240KG and 280KG respectively.

[0040] Specifically, in step four, the interval of each load is 1-2 minutes.

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

[0042] ​The impact load generated by the free falling hammer simulates the vehicle load, and the impact load can effectively simulate the vehicle load.

[0043] The impact load generated by the falling hammer acts on the bearing plate, at this time, the sensors distributed at different distances detect the deformation of the surface of the structure layer, and transmit the signals to the computer in real time for processing.

[0044] The detection method of the present application belongs to the category of dynamic deflection detection, which can more effectively simulate the driving load, and can quickly and safely collect a large amount of deflection basin information, and has the advantage of not damaging the pavement.

[0045] The above is only a preferred embodiment of the present application, and does not limit the present application in any form. Although the present application has been disclosed as above, it is not intended to limit the present application. Any person skilled in the art can make some changes or modifications to the above disclosed technical content to obtain equivalent embodiments with equivalent changes, without departing from the technical solution of the present application. Any modification, equivalent change and modification of the above embodiments made in accordance with the technical essence of the present application shall still fall within the scope of the present application.

Claims

1. A method for detecting the deflection of public roads, characterized in that, Includes the following steps: Step 1: Set up a support plate on the road to be tested, set up a central sensor at the center of the support plate, and set up several peripheral sensors around the central sensor; Step 2: Perform free-fall pre-impact on the bearing plate; Step 3: Perform multiple free-fall impacts on the bearing plate with a drop hammer of actual load weight, causing the central sensor to record multiple deflection measurements. The arithmetic mean of these multiple deflection measurements is taken as the average deflection measurement. Calculate the standard deviation of the deflection measurements from 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 If the percentage is greater than 10%, a retest is required. Step 4: Repeat Step 3 multiple times by gradually increasing the load weight, and plot the average deflection measurement of the center sensor for each different load weight P. The curve relationship is fitted using a polynomial model: a and b are undetermined coefficients. If b is greater than 0, it indicates that the roadbed has softened or become hollow. Step 5: Verify the measurement data from Step 4, and record the deflection measurement value under the j-th load weight as D. j实测 The predicted value based on the above polynomial model is D. j预测 Through D j实测 D j预测 and D j实测 average Calculate the coefficient of determination R 2 , If R 2 If the value is greater than 0.95, the road is determined to have a nonlinear response. Step 6: Calculate the representative deflection value L r , Z is the coefficient related to the confidence level, with Z ranging from 1.5 to 2.0, corresponding to a confidence level of 90% to 95%.

2. The method for detecting the deflection of public roads according to claim 1, characterized in that: In step one, 7-9 peripheral sensors are set around the central sensor.

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

4. The method for detecting the deflection of public roads according to claim 1, characterized in that: In step three, the bearing plate is subjected to 3-5 free-fall impacts with a drop hammer of actual load weight.

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

6. The method for detecting the deflection of public roads according to claim 1, characterized in that: In step four, the load weights are divided into three levels: 200KG, 240KG, and 280KG.

7. The method for detecting the deflection of public roads according to claim 1, characterized in that: In step four, each loading stage is spaced 1-2 minutes apart.

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