Detection method and device for pre-judging railway mud pumping

Abstract

The invention discloses a detection method and device for pre-judging railway frost pumping. The method comprises the following steps: step 1, obtaining a roadbed filler coefficient, a cyclic load coefficient and a radar detection coefficient of a railway; step 2, calculating a railway frost pumping risk value based on a roadbed filler coefficient, a cyclic load coefficient and a radar detection coefficient; and step 3, setting a risk value threshold value, comparing the mud pumping risk value with the risk value threshold value, and when the mud pumping risk value is greater than or equal to the threshold value, pre-judging that mud pumping occurs. According to the method, the roadbed geological radar detection precision can be improved, roadbed filler and cyclic load are comprehensively considered, compared with the prior art, three necessary conditions of mud pumping are comprehensively considered, railway roadbed mud pumping is quantitatively and comprehensively pre-judged, and the requirements of resource saving and quality safety engineering construction are met.

Description

Technical Field

[0001] The invention relates to the technical field of geotechnical engineering, and in particular to a detection method and device for predicting railway mud bubbling. Background Art

[0002] Mud and mud are common roadbed diseases in railways. The causes and mechanisms of mud and mud diseases in railway roadbeds are relatively complex and are the result of the combined effects of multiple factors. At present, scholars at home and abroad believe that the necessary conditions for its occurrence include poor roadbed filling, the presence of free water and cyclic loads. Soil conditions are the prerequisite for mud and mud, and are also the internal cause of mud and mud. Free water affects the water content of the soil and is a necessary factor for the occurrence of mud and mud diseases. Load action is an external cause.

[0003] Commonly used methods for detecting mud bubbling include sensors and geological radar. They have the following defects:

[0004] 1. The sensors need to be installed inside the roadbed, and the number is large, which leads to low efficiency.

[0005] 2. Geological radar can detect free water and mud in the roadbed, but when interpreting roadbed diseases with geological radar, the interpretation results are qualitative evaluations by the interpreters, which puts forward high technical requirements for the interpreters. In addition, factors such as roadbed filling and cyclic load are not considered in the interpretation process. Summary of the invention

[0006] In view of the technical defects and technical drawbacks in the prior art, the embodiments of the present invention provide a detection method and device for predicting railway mud bubbling, which overcomes the above problems or at least partially solves the above problems. The specific scheme is as follows:

[0007] As a first aspect of the present invention, a detection method for predicting railway mud bubbling is provided, the method comprising:

[0008] Step 1, obtaining the railway roadbed filling coefficient, cyclic load coefficient and radar detection coefficient;

[0009] Step 2, calculating the risk value of railway mud overflow based on the roadbed filling coefficient, cyclic load coefficient and radar detection coefficient;

[0010] Step 3, setting a risk value threshold, comparing the risk value of mud overflow with the risk value threshold, and when the risk value of mud overflow is greater than or equal to the threshold, predicting the occurrence of mud overflow.

[0011] Furthermore, in step 1, the roadbed filling coefficient is determined by actual roadbed filling, and the cyclic load coefficient is determined by a train speed design plan.

[0012] Furthermore, the radar detection coefficient is obtained by measuring with geological radar detection equipment.

[0013] Furthermore, the geological radar detection equipment includes a rail cart and a geological radar, the geological radar is installed on the rail cart, the rail cart is located below the geological radar and has a hole, and the geological radar transmits and receives signals through the hole.

[0014] Furthermore, the radar detection coefficient measured by the geological radar detection equipment specifically includes:

[0015] The geological radar of the geological radar detection equipment emits high-frequency short-pulse electromagnetic waves to the target point road base underground and receives the radar reflected wave signal;

[0016] The correlation between the free water content of the roadbed and the geological radar reflection wave signal is obtained, and the free water content of the roadbed is analyzed based on the radar reflection wave signal, and the roadbed radar detection coefficient is calculated based on the free water content of the roadbed.

[0017] Furthermore, the radar reflected wave signal includes time-frequency characteristics, instantaneous amplitude, instantaneous frequency and instantaneous phase.

[0018] Furthermore, the method also includes: collecting radar reflection wave signals of roadbeds with different free water contents through geological radar, using the collected radar reflection wave signals as training sets to train a neural network to obtain a trained neural network; inputting the radar reflection wave signal of the current roadbed into the neural network, and outputting the current roadbed free water content through the neural network.

[0019] Furthermore, the roadbed radar detection coefficient is calculated based on the free water content of the roadbed, and the calculation formula is as follows:

[0020] r3 = β*f;

[0021] Where r3 is the radar detection coefficient, β is the conversion factor, and f is the free water content of the roadbed.

[0022] Furthermore, in step 2, the risk value of railway mud spillage is calculated based on the roadbed filling coefficient, the cyclic load coefficient and the radar detection coefficient, and the calculation formula is as follows:

[0023] A=r1+r2+r3;

[0024] Where A is the risk value of mud overflow, r1 is the roadbed filling coefficient, r2 is the cyclic load coefficient, and r3 is the radar detection coefficient.

[0025] As a second aspect of the present invention, a detection device for predicting railway mud bubbling is provided, the device comprising: a parameter acquisition module, a calculation module and a judgment module;

[0026] The parameter acquisition module is used to obtain the railway roadbed filling coefficient, cyclic load coefficient and radar detection coefficient;

[0027] The calculation module is used to calculate the risk value of railway mud overflow based on the roadbed filling coefficient, the cyclic load coefficient and the radar detection coefficient;

[0028] The judgment module is used to set a risk value threshold, compare the risk value of mud boiling with the risk value threshold, and predict the occurrence of mud boiling when the risk value of mud boiling is greater than or equal to the threshold.

[0029] The present invention has the following beneficial effects:

[0030] 1. The present invention can not only improve the accuracy of roadbed geological radar detection, but also comprehensively consider roadbed filling materials and cyclic loads. Compared with the prior art, the present invention comprehensively considers the three necessary conditions for mud bubbling, quantitatively and comprehensively predicts mud bubbling of railway roadbed, and meets the requirements of resource conservation and quality and safety engineering construction.

[0031] 2. The present invention opens a rectangular hole at the bottom of the geological radar in the cart, which improves the accuracy of the geological radar detection results and is easy to operate. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A flow chart of a detection method for predicting railway mud bubbling provided by an embodiment of the present invention.

[0033] Figure 2 A schematic longitudinal section diagram of a detection device provided by an embodiment of the present invention;

[0034] Figure 3 A schematic plan view of a detection device provided by an embodiment of the present invention;

[0035] Figure 4 A schematic cross-sectional view of a detection device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0037] As an embodiment of the present invention, a detection method for predicting railway mud bubbling is provided, the method comprising:

[0038] Step 1, obtaining the railway roadbed filling coefficient, cyclic load coefficient and radar detection coefficient;

[0039] Step 2, calculating the risk value of railway mud overflow based on the roadbed filling coefficient, cyclic load coefficient and radar detection coefficient;

[0040] Step 3, setting a risk value threshold, comparing the risk value of mud overflow with the risk value threshold, and when the risk value of mud overflow is greater than or equal to the threshold, predicting the occurrence of mud overflow.

[0041] The present invention can not only improve the accuracy of roadbed geological radar detection, but also comprehensively consider roadbed filling materials and cyclic loads, quantitatively and comprehensively predict railway roadbed mud bubbling, and meet the requirements of resource conservation and quality safety engineering construction.

[0042] See also Figure 1 As shown, in the embodiment of the present invention, the risk value threshold is 0.6. When the risk value of mud overflowing is greater than or equal to 0.6, there is a risk of mud overflowing; otherwise, there is no risk of mud overflowing.

[0043] Among them, in step 2, the risk value of railway mud overflow is calculated based on the roadbed filling coefficient, cyclic load coefficient and radar detection coefficient, and the calculation formula is as follows:

[0044] A=r1+r2+r3;

[0045] Where A is the risk value of mud overflow, r1 is the roadbed filling coefficient, r2 is the cyclic load coefficient, and r3 is the radar detection coefficient.

[0046] Optionally, the present invention determines the roadbed filling coefficient through actual roadbed filling, and determines the cyclic load coefficient through the train speed design plan, referring to Tables 1 and 2 below. For groups A, B, and C of roadbed filling, the corresponding roadbed filling coefficients are 0.05, 0.2, and 0.25, respectively. For the train speed design plans of 350km / h, 250km / h, and 120km / h, the corresponding cyclic load coefficients are 0.2, 0.1, and 0.05, respectively.

[0047] Roadbed filling Group A Group B Group C <![CDATA[r1]]> 0.05 0.2 0.25

[0048] Table 1 Reference value of roadbed filling coefficient (r1)

[0049] Load Type 350km / h 250km / h 120km / h <![CDATA[r2]]> 0.2 0.1 0.05

[0050] Table 2 Reference values ​​of cyclic load factor (r2)

[0051] Optionally, the radar detection coefficient is obtained by measuring with a geological radar detection device.

[0052] Through the analysis of radar reflection signals and the railway roadbed detection examples, it is shown that there is a significant correlation between the time-frequency characteristics, instantaneous amplitude, instantaneous frequency and instantaneous phase of the roadbed free water and the geological radar reflection wave signal. The detection example shows that after the roadbed contains water, the high-frequency end of the radar waveform is significantly attenuated and the frequency is chaotic compared to the dry roadbed, and the radar wave reflection amplitude becomes stronger. Therefore, the frequency and amplitude attributes can be used as the basis for judging the abnormal water content of the roadbed.

[0053] Based on this, the present invention designs a method for calculating the roadbed radar detection coefficient based on the radar reflection wave signal, which specifically includes:

[0054] The geological radar of the geological radar detection equipment emits high-frequency short-pulse electromagnetic waves to the target point road base underground and receives the radar reflected wave signal;

[0055] The correlation between the free water content of the roadbed and the geological radar reflection wave signal is obtained, and the free water content of the roadbed is analyzed based on the radar reflection wave signal, and the roadbed radar detection coefficient is calculated based on the free water content of the roadbed.

[0056] The radar reflected wave signal includes time-frequency characteristics, instantaneous amplitude, instantaneous frequency and instantaneous phase.

[0057] Alternatively, see Figures 2 to 4 The geological radar detection equipment includes a track trolley 1 and a geological radar 2. The track trolley travels on a railway track 3. The geological radar is installed on the track trolley 1. The track trolley 1 opens a rectangular hole 4 at the bottom of the geological radar. The area of ​​the hole 4 is slightly smaller than the geological radar. The geological radar can transmit and receive reflected signals through the hole 4 to detect roadbed diseases and predict whether mud will occur in the roadbed. The rectangular hole 4 can improve the problem of inaccurate data collection caused by poor and discontinuous receiving signals of the geological radar antenna during railway roadbed geological radar detection due to the bottom plate structure of the track trolley 1, thereby improving the accuracy of the detection results.

[0058] Wherein, the rail cart includes: a running wheel group, including a front wheel group and a rear wheel group, each of the front wheel group and the rear wheel group includes a wheel axle and a pair of running wheels arranged at both ends of the wheel axle and used for running on the rails; a frame, including a bracket arranged above the running wheel group, and the bottom of the bracket is connected to the wheel axle; wherein the geological radar is placed above the rectangular hole 4 at the bottom of the bracket.

[0059] Optionally, after the geological radar collects the original data along the roadbed, it is also necessary to perform data preprocessing, including energy balancing, noise suppression, and resolution improvement. The radar detection coefficient is determined comprehensively through the geological radar's instantaneous amplitude, instantaneous frequency, instantaneous phase, and time-frequency characteristics.

[0060] Optionally, the method also includes: collecting radar reflection wave signals of roadbeds with different free water contents through geological radar, using the collected radar reflection wave signals as training sets to train a neural network to obtain a trained neural network; inputting the radar reflection wave signal of the current roadbed into the neural network, and outputting the current roadbed free water content through the neural network.

[0061] The roadbed radar detection coefficient is calculated based on the free water content of the roadbed. The calculation formula is as follows:

[0062] r3 = β*f;

[0063] Where r3 is the radar detection coefficient, β is the conversion factor, and f is the free water content of the roadbed.

[0064] In the above embodiment, based on the trained neural network, when the radar reflection wave signal is received, the free water content of the roadbed can be obtained in real time through the neural network, and the radar detection coefficient can be further calculated.

[0065] As another embodiment of the present invention, a detection device for predicting railway mud bubbling is also provided, the device comprising: a parameter acquisition module, a calculation module and a judgment module;

[0066] The parameter acquisition module is used to obtain the railway roadbed filling coefficient, cyclic load coefficient and radar detection coefficient;

[0067] The calculation module is used to calculate the risk value of railway mud overflow based on the roadbed filling coefficient, the cyclic load coefficient and the radar detection coefficient;

[0068] The judgment module is used to set a risk value threshold, compare the risk value of mud boiling with the risk value threshold, and predict the occurrence of mud boiling when the risk value of mud boiling is greater than or equal to the threshold.

[0069] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A detection method for predicting railway mud bubbling, characterized in that: The method comprises: Step 1, obtaining the railway roadbed filling coefficient, cyclic load coefficient and radar detection coefficient; Step 2, calculating the risk value of railway mud overflow based on the roadbed filling coefficient, cyclic load coefficient and radar detection coefficient; Step 3, setting a risk value threshold, comparing the risk value of mud overflow with the risk value threshold, and when the risk value of mud overflow is greater than or equal to the threshold, predicting the occurrence of mud overflow.

2. The detection method for predicting railway mud bubbling according to claim 1 is characterized in that: In step 1, the roadbed filling coefficient is determined by actual roadbed filling, and the cyclic load coefficient is determined by a train speed design plan.

3. The detection method for predicting railway mud bubbling according to claim 1, characterized in that: The radar detection coefficient is obtained by measuring with geological radar detection equipment.

4. The detection method for predicting railway mud bubbling according to claim 3 is characterized in that: The geological radar detection equipment includes a track cart and a geological radar. The geological radar is installed on the track cart. The track cart is located below the geological radar and has a hole. The geological radar transmits and receives signals through the hole.

5. The detection method for predicting railway mud bubbling according to claim 3 is characterized in that: The radar detection coefficient measured by the geological radar detection equipment specifically includes: The geological radar of the geological radar detection equipment emits high-frequency short-pulse electromagnetic waves to the target point road base underground and receives the radar reflected wave signal; The correlation between the free water content of the roadbed and the geological radar reflection wave signal is obtained, and the free water content of the roadbed is analyzed based on the radar reflection wave signal, and the roadbed radar detection coefficient is calculated based on the free water content of the roadbed.

6. The detection method for predicting railway mud bubbling according to claim 5, characterized in that: The radar reflected wave signal includes time-frequency characteristics, instantaneous amplitude, instantaneous frequency and instantaneous phase.

7. The detection method for predicting railway mud bubbling according to claim 5, characterized in that: The method also includes: collecting radar reflection wave signals of roadbeds with different free water contents through geological radar, training a neural network with the collected radar reflection wave signals as a training set to obtain a trained neural network; inputting the radar reflection wave signal of the current roadbed into the neural network, and outputting the current roadbed free water content through the neural network.

8. The detection method for predicting railway mud bubbling according to claim 5, characterized in that: The roadbed radar detection coefficient is calculated based on the free water content of the roadbed. The calculation formula is as follows: r3＝β*f； Where r3 is the radar detection coefficient, β is the conversion factor, and f is the free water content of the roadbed.

9. The detection method for predicting railway mud bubbling according to claim 1, characterized in that: In step 2, the risk value of railway mud spillage is calculated based on the roadbed filling coefficient, cyclic load coefficient and radar detection coefficient. The calculation formula is as follows: A＝r1+r2+r3； Where A is the risk value of mud overflow, r1 is the roadbed filling coefficient, r2 is the cyclic load coefficient, and r3 is the radar detection coefficient.

10. A detection device for predicting mud bubbling on railways, characterized in that: The device comprises: a parameter acquisition module, a calculation module and a judgment module; The parameter acquisition module is used to obtain the railway roadbed filling coefficient, cyclic load coefficient and radar detection coefficient; The calculation module is used to calculate the risk value of railway mud overflow based on the roadbed filling coefficient, the cyclic load coefficient and the radar detection coefficient; The judgment module is used to set a risk value threshold, compare the risk value of mud boiling with the risk value threshold, and predict the occurrence of mud boiling when the risk value of mud boiling is greater than or equal to the threshold.

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