Method and device for acquiring grass-shaped wave amplitude value of rail flaw detection car
By automatically acquiring the amplitude value of grass-like waves in the rail flaw detection vehicle, the problem of inaccurate gain adjustment caused by manual operation is solved, the accuracy and reliability of detection are improved, and false alarms and missed alarms are reduced.
Patent Information
- Application Number
- CN202511876440.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-12
- Publication Date
- 2026-04-07
AI Technical Summary
The gain adjustment of existing rail flaw detection vehicles relies on manual operation, which has problems such as subjective judgment bias and inaccurate acquisition of grass wave amplitude values, resulting in false alarms, missed alarms and inaccurate detection.
By acquiring each frame of echo signal within the inspection channel of the rail flaw detection vehicle, storing it in chronological order, and filtering out the maximum amplitude, the amplitude of the grass wave is automatically determined by combining the preset section and the number of inspection segments, thus reducing the influence of human factors.
It achieves accurate acquisition of grass wave amplitude values, reduces gain adjustment errors, improves detection accuracy and reliability, and reduces the risk of false alarms and missed alarms.
Smart Images
Figure CN121805428A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of nondestructive testing technology, specifically relating to a method and device for obtaining the amplitude of grass-like waves on a rail flaw detection vehicle. Background Technology
[0002] In the field of nondestructive testing of rails, rail flaw detection vehicles are core equipment for ensuring the safe service of rails. The sensitivity of their detection channels directly determines the accuracy of damage detection. Excessive sensitivity can easily lead to false triggering of the echo signal threshold, generating a large number of false alarms and increasing the cost of on-site verification. Insufficient sensitivity may miss rail damage, causing safety hazards. Therefore, it is necessary to adjust the gain of the detection channels to maintain optimal sensitivity. The key basis for gain adjustment is the amplitude value of the grass wave in the detection channel. Accurately obtaining the amplitude value of the grass wave is a prerequisite for achieving effective gain control.
[0003] Currently, the gain adjustment and grass wave acquisition of rail flaw detection vehicles mainly rely on manual operation, which has significant technical defects: on the one hand, subjective judgment deviations can easily lead to improper gain adjustment, which in turn can cause false or missed damage reports; on the other hand, the background noise extracted during existing grass wave acquisition is inaccurate and cannot provide a reliable reference for gain adjustment.
[0004] Therefore, a new method is urgently needed to solve the problems existing in the current technology. Summary of the Invention
[0005] This invention provides a method for obtaining the amplitude of grass-like waves on a rail flaw detection vehicle. This method accurately acquires the amplitude of grass-like waves in the detection channel of the rail flaw detection vehicle, reducing the impact of human factors on gain adjustment and providing data support for rail inspection. The method for obtaining the amplitude of grass-like waves on a rail flaw detection vehicle includes:
[0006] Acquire each frame of echo signal within the preset detection time gate interval in the inspection channel of the rail flaw detection vehicle, and store each frame of echo signal in chronological order of detection time; determine the maximum amplitude of each frame of echo signal as the first maximum amplitude of each frame of echo signal;
[0007] The number of frames of the stored echo signal is recounted each time the preset number of frames to be detected in the segment is reached. Each frame of echo signal in each segment is determined. The maximum amplitude value is selected from the first maximum amplitude value of each frame of echo signal in each segment and determined as the second maximum amplitude value of the segment.
[0008] When the number of inspection segments of the rail flaw detection vehicle reaches the preset number of inspection segments, the minimum amplitude value is selected from the second maximum amplitude values of all segments and determined as the grass wave amplitude value of the inspection channel of the rail flaw detection vehicle.
[0009] This invention provides a device for acquiring the amplitude of grass-like waves on a rail flaw detection vehicle. This device accurately acquires the amplitude of grass-like waves in the inspection channel of the rail flaw detection vehicle, reducing the impact of human factors on gain adjustment and providing data support for rail inspection. The device for acquiring the amplitude of grass-like waves on a rail flaw detection vehicle includes:
[0010] The first maximum amplitude determination module is used to acquire each frame of echo signal within the preset detection time gate interval in the detection channel of the rail flaw detection vehicle, and store each frame of echo signal in chronological order of detection time; the maximum amplitude of each frame of echo signal is determined as the first maximum amplitude of each frame of echo signal.
[0011] The second maximum amplitude determination module is used to recount when the number of frames of the stored echo signal reaches the preset number of detection frames in each segment, determine each frame of echo signal in each segment, and filter out the maximum amplitude from the first maximum amplitude of each frame of echo signal in each segment to determine the second maximum amplitude of the segment.
[0012] The grass wave amplitude determination module is used to select the minimum amplitude value from the second maximum amplitude values of all sections when the number of inspection sections of the rail flaw detection vehicle reaches the preset number of inspection sections, and determine it as the grass wave amplitude value of the inspection channel of the rail flaw detection vehicle.
[0013] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-mentioned method for obtaining the amplitude of grass-like waves of a rail flaw detection vehicle.
[0014] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for obtaining the amplitude of grass-like waves on a rail flaw detection vehicle.
[0015] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for obtaining the amplitude value of the grass-like wave of a rail flaw detection vehicle.
[0016] In this embodiment of the invention, each frame of echo signal within a preset detection time gate interval in the rail flaw detection vehicle's detection channel is acquired, and each frame of echo signal is stored in chronological order of detection time. The maximum amplitude of each frame of echo signal is determined as the first maximum amplitude of each frame of echo signal. The count is reset each time the number of stored echo signal frames reaches the preset number of detection frames for a given segment, and each frame of echo signal within each segment is determined. From the first maximum amplitude of each frame of echo signal within each segment, the maximum amplitude is selected and determined as the second maximum amplitude of that segment. When the number of detection segments of the rail flaw detection vehicle reaches the preset number of detection segments, the minimum amplitude is selected from the second maximum amplitudes of all segments and determined as the grass wave amplitude of the rail flaw detection vehicle's detection channel. This embodiment of the invention can accurately acquire the grass wave amplitude of the rail flaw detection vehicle's detection channel, which helps reduce the influence of human factors on gain adjustment and provides data support for rail inspection. Attached Figure Description
[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:
[0018] Figure 1 This is a diagram showing the sensor distribution inside the probe wheel of a rail flaw detection vehicle in existing technology.
[0019] Figure 2 This is a schematic diagram of the rail flaw detection echo in existing technology;
[0020] Figure 3 This is a display of the intended use of rail flaw detection technology (B).
[0021] Figure 4 This is a schematic diagram of grass-like waves in the prior art;
[0022] Figure 5 This is an example diagram illustrating the method for obtaining the amplitude of grass-like waves using a rail flaw detection vehicle in an embodiment of the present invention.
[0023] Figure 6 This is a structural example diagram of the device for obtaining the amplitude of grass-like waves on a rail flaw detection vehicle in an embodiment of the present invention;
[0024] Figure 7 This is a specific example diagram of the structure of the device for obtaining the amplitude of grass-like waves on a rail flaw detection vehicle in an embodiment of the present invention;
[0025] Figure 8 This is a specific example diagram of the structure of the device for obtaining the amplitude of grass-like waves on a rail flaw detection vehicle in an embodiment of the present invention;
[0026] Figure 9 This is a schematic diagram of the computer device structure according to an embodiment of the present invention. Detailed Implementation
[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0028] The inventors' research found that the current railway rail damage detection method mainly uses rail flaw detection vehicles as the primary means and small hand-pushed instruments as a supplement. Figure 1 Figure 1 shows the sensor distribution diagram inside the probe wheel of a rail flaw detection vehicle in the prior art. It includes the type, marking and detection direction of the sensors inside the probe wheel of the rail flaw detection vehicle. The side marking clearly indicates that the detection direction of the corresponding sensor is along the side of the rail. XF primary and XF secondary are exclusive markings for different detection channels, used to distinguish sensors with different functions inside the probe wheel.
[0029] Figure 2 This is a schematic diagram of rail flaw detection echo in existing technology, such as... Figure 2 The image shows a forward 45-degree echo from a certain detection. At this time, the decision threshold is 40% (blue), the gain is 31dB, the time gate is between 4000-6000 points (50MHz sampling), and the gate width is 40us.
[0030] Figure 3 This is a display intent for rail flaw detection in existing technologies, such as... Figure 3 As shown, due to appropriate gain, when the damage echo meets the judgment criteria, a B-display point will be formed on the B-display image. The playback personnel will make a damage judgment based on the trend of the B-display image. If the gain is insufficient, the damage may not exceed the threshold, resulting in missed damage. If the gain is too large, it may continuously exceed the threshold, generating a large number of false alarms, which will reduce the reliability of the damage alarm, require more on-site verification, and reduce the efficiency of flaw detection.
[0031] Currently, the gain setting for rail flaw detection vehicles is generally achieved by first repeatedly testing on the calibration line to obtain the optimal reference sensitivity for each channel; then, during actual testing, the gain is adjusted according to the specific changes in the condition of the flaw detection vehicle to obtain the best detection data.
[0032] In actual testing, gain adjustment depends entirely on the operator's skill level, experience, and sense of responsibility. Operators generally use two methods for gain adjustment: 1. The grass-like wave method based on display A; 2. The sporadic clutter method based on the clutter morphology of display B in each channel.
[0033] Actual research has revealed that the sporadic clutter method based on the B-display has a large hysteresis characteristic. That is, it can only be detected, identified and adjusted when the sensitivity has deviated from the optimal value for a period of time and there is a continuous anomaly on the B-display. Therefore, false alarms and missed alarms are inevitable.
[0034] Therefore, in the automatic control of the flaw detection vehicle's sensitivity, the A-shaped straw wave should be used as the basis for gain adjustment.
[0035] Figure 4 This is a schematic diagram of grass-like waves in the prior art, such as... Figure 4 As shown, the grass-like echo inside its gate is called grass wave.
[0036] The A-wave pattern of rails is generally formed by two factors: one is the reflection from the rail grains, and the other is the delayed arrival of the inherent ultrasonic response formed by previous historical pulse emissions. The amplitude of the A-wave pattern essentially represents the actual measured noise floor. Only with a noise floor can the gain be adjusted to ensure that the noise floor does not exceed the threshold, thereby achieving the detection of the maximum signal-to-noise ratio of rail damage.
[0037] Based on the above research, the inventors proposed a method for obtaining the amplitude of grass-like waves in rail flaw detection vehicles according to embodiments of the present invention, which solves the problem of obtaining the amplitude of grass-like waves when adjusting the gain of flaw detection vehicles in the prior art; only by accurately obtaining the amplitude of grass-like waves can the gain of the channel be automatically adjusted according to the grass-like waves to achieve the optimal channel sensitivity and ensure the quality of the detection data.
[0038] Figure 5 This is an example diagram illustrating the method for obtaining the amplitude of grass-like waves using a rail flaw detection vehicle in an embodiment of the present invention. Figure 5 As shown, the method for obtaining the amplitude of the grass-like wave of this rail flaw detection vehicle includes:
[0039] Step 501: Obtain each frame of echo signal within the preset detection time gate interval in the inspection channel of the rail flaw detection vehicle, and store each frame of echo signal in chronological order of detection time; determine the maximum amplitude of each frame of echo signal as the first maximum amplitude of each frame of echo signal.
[0040] Step 502: Recount the stored echo signal frames each time the number of frames reaches the preset segment detection frame number, determine each frame of echo signal in each segment, and select the maximum amplitude value from the first maximum amplitude value of each frame of echo signal in each segment to determine the second maximum amplitude value of the segment.
[0041] Step 503: When the number of inspection segments of the rail flaw detection vehicle reaches the preset number of inspection segments, select the minimum amplitude value from the second maximum amplitude values of all segments and determine it as the grass wave amplitude value of the inspection channel of the rail flaw detection vehicle.
[0042] In this embodiment, the method may further include:
[0043] Based on the characteristic parameters of the rail flaw detection vehicle's inspection channel, the number of preset inspection frames and the number of preset inspection segments are determined; the characteristic parameters include: the probe type, inspection frequency, and target inspection depth of the inspection channel.
[0044] In a specific embodiment, for the forward 45-degree and backward 45-degree inspection channels of the rail flaw detection vehicle, based on its flaw detection requirements and according to the characteristic parameters of the inspection channel, such as probe type, inspection frequency, and target inspection depth, the preset number of inspection frames n and the preset number of inspection segments k are determined, and the corresponding inspection distance d is also specified.
[0045] First, we analyze the characteristic parameters: Taking the forward 45-degree detection channel as an example, its probe type is an oblique ultrasonic probe with a detection frequency of 50MHz, and the target detection depth covers the key damage area from the head to the waist of the rail; the backward 45-degree detection channel uses the same type of probe with the same detection frequency, and the target detection depth focuses on the bottom of the rail and the joint area.
[0046] Then, the parameters are determined: Based on the above characteristic parameters and the rule that the number of frames corresponds to 180-600 frames for every meter the rail flaw detection vehicle moves, the preset number of detection frames for the section is set to n=500 frames. Among them, the number of frames n needs to be adapted to the signal sampling requirements of the 50MHz detection frequency to ensure the integrity of the data in a single section; the preset number of detection segments is set to k=2, corresponding to a detection distance d=1 meter. That is, when the cumulative number of frames N=k×n=1000 frames, the movement distance of the flaw detection vehicle is 1 meter to ensure that the data covers the fixed reflector area to filter out its interference.
[0047] Finally, parameter adaptation and adjustment are performed: if the detection channel probe type is changed to vertical, or the detection frequency is adjusted to other values, or the target detection depth is expanded to the entire cross section of the rail, the preset section detection frame number n can be adjusted to 300 frames or 600 frames, and the preset detection segment number k can be adjusted to 3, so that the parameters match the feature parameters and ensure the accuracy of grass wave acquisition.
[0048] In this embodiment, the method may further include:
[0049] Based on the depth of the rail detection area corresponding to the detection channel and the propagation speed of ultrasonic waves in the rail, the duration range of the echo signal is calculated, and this duration range is determined as the preset detection duration gate interval.
[0050] In a specific embodiment, the propagation speed of ultrasonic waves in the rail is first determined and a fixed value is taken according to the material characteristics of the rail. At the same time, the target rail detection area depth corresponding to each detection channel is determined. For example, the target detection depth of the forward 45-degree detection channel covers the head to the waist of the rail, and the target detection depth of the backward 45-degree detection channel focuses on the bottom of the rail and the joint area.
[0051] Based on the relationship that echo signal propagation time = 2 × detection area depth / ultrasonic wave propagation speed, the duration range of echo signals in the forward 45-degree and backward 45-degree detection channels is calculated respectively.
[0052] The calculated echo signal duration range of the forward 45-degree detection channel is set as its preset detection duration gate interval. Similarly, the echo signal duration range of the backward 45-degree detection channel is set as its preset detection duration gate interval to ensure that only echo signals within the target detection area are collected for subsequent grass wave acquisition.
[0053] In step 501, each frame of echo signal within the preset detection time gate interval in the detection channel of the rail flaw detection vehicle is acquired, and each frame of echo signal is stored in chronological order of detection time; the maximum amplitude of each frame of echo signal is determined as the first maximum amplitude of each frame of echo signal.
[0054] In a specific embodiment, during the inspection of the rail flaw detection vehicle along the rail, the echo signal of the forward 45-degree detection channel is collected in real time, and each frame of echo signal within the preset detection time gate interval of 4000-6000 points (40us) is selected. Each frame of echo signal after selection is saved to ensure data traceability.
[0055] For each frame of echo signal stored in the gate interval, all amplitude data of the signal in that frame are traversed, and the maximum amplitude value is selected. This maximum value is determined as the first maximum amplitude value of the echo signal in that frame, providing basic data for the selection of the second maximum amplitude value in subsequent segments.
[0056] In step 502, the number of frames of the stored echo signal is recounted each time the preset number of detection frames for a segment is reached. Each frame of echo signal in each segment is determined. The maximum amplitude value is selected from the first maximum amplitude value of each frame of echo signal in each segment and determined as the second maximum amplitude value of the segment.
[0057] In a specific embodiment, for the forward 45-degree detection channel of the rail flaw detection vehicle, the preset number of detection frames n=500 frames has been set according to the characteristic parameters of the channel. In the process of acquiring the echo signal of each frame within the preset detection time gate interval of the forward 45-degree detection channel, determining the maximum value of the first amplitude of each frame and storing it, the number of stored echo signal frames is counted in real time.
[0058] When the number of stored echo signal frames reaches the preset detection frame count of 500 frames, it is determined that the data acquisition of one detection segment has been completed; from the first maximum amplitude value corresponding to each of the 500 echo signal frames, the value with the largest amplitude is selected.
[0059] The maximum amplitude value selected is determined as the second maximum amplitude value of the current detection segment, and this value is stored to provide segment data support for subsequent acquisition of grass wave amplitude values.
[0060] In the embodiment, within each segment, the maximum amplitude value is selected from the first maximum amplitude values of the echo signals in each frame and determined as the second maximum amplitude value of the segment. This may include:
[0061] The validity of the first maximum amplitude of the echo signal in each frame within each segment is verified. After removing abnormal amplitude data caused by instantaneous sensor interference, the second maximum amplitude is selected from the remaining valid first maximum amplitude values.
[0062] In a specific embodiment, after obtaining the first maximum amplitude value of the multi-frame echo signal in the channel, based on the historical normal detection data of the forward 45-degree detection channel, and combined with the characteristics of the grass wave being synthesized by the reflection of rail grains and the historical pulse delay response, the normal fluctuation range of the first maximum amplitude value is set, for example, ±3dB.
[0063] Compare the maximum first amplitude value of each frame with the set normal fluctuation range. If the maximum first amplitude value of a frame exceeds the range, it is determined to be abnormal amplitude data caused by instantaneous interference to the sensor.
[0064] The first maximum amplitude value that is determined to be abnormal is removed from the dataset, and the valid first maximum amplitude value within the normal fluctuation range is retained. Among the remaining valid first maximum amplitude values, the maximum amplitude value is selected and determined as the second maximum amplitude value of the segment, so as to ensure that the subsequent grass wave amplitude calculation is not affected by instantaneous interference data.
[0065] In step 503, when the number of inspection segments of the rail flaw detection vehicle reaches the preset number of inspection segments, the minimum amplitude value is selected from the second maximum amplitude values of all segments and determined as the grass wave amplitude value of the inspection channel of the rail flaw detection vehicle.
[0066] In a specific embodiment, after storing the second maximum value of each detection segment (500 frames), the number of completed detection segments is counted in real time; when the counted number of detection segments reaches the preset number of detection segments k=2, the second maximum value stored in each of the two detection segments is retrieved; based on the characteristic that there cannot be consecutive damaged frames in a fixed-length frame and the number of consecutive frames where damaged waves exist is very small, the value with the smallest amplitude is selected from the two second maximum values;
[0067] The minimum amplitude value selected is determined as the grass wave amplitude value of the forward 45-degree detection channel within 1000 frames (corresponding to a movement distance of 1 meter). This value can represent the noise floor synthesized from rail grain reflection and historical pulse delay response, providing a reference for subsequent automatic adjustment of channel gain.
[0068] In this embodiment, when the number of inspection segments of the rail flaw detection vehicle reaches the preset number of inspection segments, after selecting the minimum amplitude value from the second maximum amplitude values of all segments, the following may be included:
[0069] Record the detection time and rail mileage information corresponding to the second maximum amplitude value of each section. After filtering out the minimum amplitude value, associate and store the minimum amplitude value with the corresponding detection time and rail mileage information.
[0070] In this embodiment, when the number of inspection segments of the rail flaw detection vehicle reaches the preset number of inspection segments, after selecting the minimum amplitude value from the maximum second amplitude values of all segments and determining it as the grass wave amplitude value of the rail flaw detection vehicle's inspection channel, the following may also be included:
[0071] Stability verification of grass wave amplitude values:
[0072] Repeat the above method to obtain multiple sets of grass wave amplitude values. If the fluctuation range of multiple sets of grass wave amplitude values does not exceed the preset threshold, the grass wave amplitude value is determined to be valid.
[0073] If the fluctuation range of multiple sets of grass wave amplitude values exceeds the preset threshold, the preset segment detection frame number or preset detection segment number will be readjusted, and the grass wave amplitude value will be reacquired.
[0074] In a specific embodiment, after determining the grass wave amplitude value of the detection channel, the aforementioned grass wave acquisition method is repeated, that is, n and k are determined according to the characteristic parameters, the first maximum amplitude value of the echo signal in each frame within the gate interval is obtained, the second maximum amplitude value is selected when n frames are reached, and the minimum value is selected as the grass wave amplitude value when k segments are reached, and three sets of grass wave amplitude value data are continuously acquired.
[0075] Set a preset fluctuation threshold for the grass wave amplitude. Combined with the stability characteristics of the grass wave at a detection frequency of 50MHz, set it to ±2dB. Calculate the fluctuation range of the three sets of grass wave amplitude values. If the fluctuation range does not exceed ±2dB, the previously obtained grass wave amplitude value is deemed valid and can be used as a reference noise floor for automatic channel gain adjustment.
[0076] If the fluctuation range of the three sets of grass wave amplitude values exceeds ±2dB, it is determined that the current preset segment detection frame number n or preset detection segment number k is not suitable, and the parameters need to be readjusted. For example, the preset segment detection frame number n is adjusted from 500 frames to 600 frames, or the preset detection segment number k is adjusted from 2 to 3. After adjustment, the above grass wave acquisition method is repeated until the fluctuation range of the acquired multiple sets of grass wave amplitude values does not exceed the preset threshold, so as to ensure the stability and effectiveness of the grass wave amplitude values.
[0077] This invention also provides a device for obtaining the amplitude of grass-like waves on a rail flaw detection vehicle, as described in the following embodiments. Since the principle by which this device solves the problem is similar to the method for obtaining the amplitude of grass-like waves on a rail flaw detection vehicle, the implementation of this device can refer to the implementation of the method for obtaining the amplitude of grass-like waves on a rail flaw detection vehicle; repeated details will not be elaborated further.
[0078] Figure 6 This is a structural example diagram of the device for acquiring the amplitude of grass-like waves on a rail flaw detection vehicle in an embodiment of the present invention, as shown below. Figure 6 As shown, the device includes:
[0079] The first maximum amplitude determination module 601 is used to acquire each frame of echo signal within the preset detection time gate interval in the detection channel of the rail flaw detection vehicle, store each frame of echo signal, and determine the maximum amplitude of each frame of echo signal as the first maximum amplitude of each frame of echo signal.
[0080] The second maximum amplitude determination module 602 is used to select the maximum amplitude from the first maximum amplitude of each frame of echo signal when the number of frames of stored echo signals reaches the preset number of detection frames for the segment, and determine it as the second maximum amplitude of the segment.
[0081] The grass wave amplitude determination module 603 is used to select the minimum amplitude value from the second maximum amplitude values of all sections when the number of inspection sections of the rail flaw detection vehicle reaches the preset number of inspection sections, and determine it as the grass wave amplitude value of the inspection channel of the rail flaw detection vehicle.
[0082] Figure 7 This is a specific example diagram illustrating the structure of the device for acquiring the amplitude of grass-like waves on a rail flaw detection vehicle, as described in an embodiment of the present invention. Figure 7 As shown in one embodiment, Figure 6 The device for acquiring the amplitude of grass-like waves of the rail flaw detection vehicle in the embodiment of the present invention may further include: a data acquisition module 701.
[0083] In one embodiment, the data acquisition module 701 is specifically used for:
[0084] Based on the characteristic parameters of the rail flaw detection vehicle's inspection channel, the number of preset inspection frames and the number of preset inspection segments are determined; the characteristic parameters include: the probe type, inspection frequency, and target inspection depth of the inspection channel.
[0085] Figure 8 This is a specific example diagram illustrating the structure of the device for acquiring the amplitude of grass-like waves on a rail flaw detection vehicle, as described in an embodiment of the present invention. Figure 8 As shown in one embodiment, Figure 6 The device for obtaining the amplitude value of grass-like waves of the rail flaw detection vehicle in the embodiment of the present invention may further include: a preset detection time gate interval determination module 801.
[0086] In one embodiment, the preset detection duration gate interval determination module 801 is specifically used for:
[0087] Based on the depth of the rail detection area corresponding to the detection channel and the propagation speed of ultrasonic waves in the rail, the duration range of the echo signal is calculated, and this duration range is determined as the preset detection duration gate interval.
[0088] In one embodiment, the second amplitude maximum value determination module 602 is specifically used for:
[0089] The validity of the first maximum amplitude of the echo signal in each frame within each segment is verified. After removing abnormal amplitude data caused by instantaneous sensor interference, the second maximum amplitude is selected from the remaining valid first maximum amplitude values.
[0090] In one embodiment, the grass wave amplitude determination module 603 is specifically used for:
[0091] Record the detection time and rail mileage information corresponding to the second maximum amplitude value of each section. After filtering out the minimum amplitude value, associate and store the minimum amplitude value with the corresponding detection time and rail mileage information.
[0092] In one embodiment, the grass wave amplitude determination module 603 is specifically used for:
[0093] Stability verification of grass wave amplitude values:
[0094] Repeat the above method to obtain multiple sets of grass wave amplitude values. If the fluctuation range of multiple sets of grass wave amplitude values does not exceed the preset threshold, the grass wave amplitude value is determined to be valid.
[0095] If the fluctuation range of multiple sets of grass wave amplitude values exceeds the preset threshold, the preset segment detection frame number or preset detection segment number will be readjusted, and the grass wave amplitude value will be reacquired.
[0096] Based on the aforementioned inventive concept, such as Figure 9As shown, the present invention also proposes a computer device 900, including a memory 910, a processor 920, and a computer program 930 stored in the memory 910 and executable on the processor 920. When the processor 920 executes the computer program 930, it implements the aforementioned method for obtaining the amplitude value of grass-like waves of a rail flaw detection vehicle.
[0097] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for obtaining the amplitude of grass-like waves on a rail flaw detection vehicle.
[0098] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for obtaining the amplitude value of the grass-like wave of a rail flaw detection vehicle.
[0099] In this embodiment of the invention, each frame of echo signal within a preset detection time gate interval in the rail flaw detection vehicle's detection channel is acquired, and each frame of echo signal is stored in chronological order of detection time. The maximum amplitude of each frame of echo signal is determined as the first maximum amplitude of each frame of echo signal. The count is reset each time the number of stored echo signal frames reaches the preset number of detection frames for a given segment, and each frame of echo signal within each segment is determined. From the first maximum amplitude of each frame of echo signal within each segment, the maximum amplitude is selected and determined as the second maximum amplitude of that segment. When the number of detection segments of the rail flaw detection vehicle reaches the preset number of detection segments, the minimum amplitude is selected from the second maximum amplitudes of all segments and determined as the grass wave amplitude of the rail flaw detection vehicle's detection channel. This embodiment of the invention can accurately acquire the grass wave amplitude of the rail flaw detection vehicle's detection channel, which helps reduce the influence of human factors on gain adjustment and provides data support for rail inspection.
[0100] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0101] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0102] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0103] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0104] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.
Claims
1. A method for obtaining the amplitude of grass-like waves on a rail flaw detection vehicle, characterized in that, include: Acquire each frame of echo signal within the preset detection time gate interval in the inspection channel of the rail flaw detection vehicle, and store each frame of echo signal in chronological order of detection time; The maximum amplitude of the echo signal in each frame is determined as the first maximum amplitude of the echo signal in each frame. The number of frames of the stored echo signal is recounted each time the preset number of frames to be detected in the segment is reached. Each frame of echo signal in each segment is determined. The maximum amplitude value is selected from the first maximum amplitude value of each frame of echo signal in each segment and determined as the second maximum amplitude value of the segment. When the number of inspection segments of the rail flaw detection vehicle reaches the preset number of inspection segments, the minimum amplitude value is selected from the second maximum amplitude values of all segments and determined as the grass wave amplitude value of the inspection channel of the rail flaw detection vehicle.
2. The method as described in claim 1, characterized in that, Also includes: Based on the characteristic parameters of the rail flaw detection vehicle's inspection channel, determine the preset number of inspection frames and the preset number of inspection segments; The characteristic parameters include: the probe type of the detection channel, the detection frequency, and the target detection depth.
3. The method as described in claim 1, characterized in that, Also includes: Based on the depth of the rail detection area corresponding to the detection channel and the propagation speed of ultrasonic waves in the rail, the duration range of the echo signal is calculated, and this duration range is determined as the preset detection duration gate interval.
4. The method as described in claim 1, characterized in that, Within each segment, the maximum amplitude value is selected from the first maximum amplitude values of the echo signals in each frame, and determined as the second maximum amplitude value for that segment, including: The validity of the first maximum amplitude of the echo signal in each frame within each segment is verified. After removing abnormal amplitude data caused by instantaneous sensor interference, the second maximum amplitude is selected from the remaining valid first maximum amplitude values.
5. The method as described in claim 1, characterized in that, When the number of inspection sections of the rail flaw detection vehicle reaches the preset number of inspection sections, the minimum amplitude value is selected from the second maximum amplitude values of all sections, including: Record the detection time and rail mileage information corresponding to the second maximum amplitude value of each section. After filtering out the minimum amplitude value, associate and store the minimum amplitude value with the corresponding detection time and rail mileage information.
6. The method as described in claim 1, characterized in that, When the number of inspection segments of the rail flaw detection vehicle reaches the preset number of inspection segments, the minimum amplitude value is selected from the second maximum amplitude values of all segments and determined as the grass wave amplitude value of the rail flaw detection vehicle's inspection channel. This also includes: Stability verification of grass wave amplitude values: Repeat the above method to obtain multiple sets of grass wave amplitude values. If the fluctuation range of multiple sets of grass wave amplitude values does not exceed the preset threshold, the grass wave amplitude value is determined to be valid. If the fluctuation range of multiple sets of grass wave amplitude values exceeds the preset threshold, the preset segment detection frame number or preset detection segment number will be readjusted, and the grass wave amplitude value will be reacquired.
7. A device for acquiring the amplitude of grass-like waves on a rail flaw detection vehicle, characterized in that, include: The first maximum amplitude determination module is used to acquire each frame of echo signal within the preset detection time gate interval in the detection channel of the rail flaw detection vehicle, and store each frame of echo signal in the order of detection time. The maximum amplitude of the echo signal in each frame is determined as the first maximum amplitude of the echo signal in each frame. The second maximum amplitude determination module is used to recount when the number of frames of the stored echo signal reaches the preset number of detection frames in each segment, determine each frame of echo signal in each segment, and filter out the maximum amplitude from the first maximum amplitude of each frame of echo signal in each segment to determine the second maximum amplitude of the segment. The grass wave amplitude determination module is used to select the minimum amplitude value from the second maximum amplitude values of all sections when the number of inspection sections of the rail flaw detection vehicle reaches the preset number of inspection sections, and determine it as the grass wave amplitude value of the inspection channel of the rail flaw detection vehicle.
8. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method according to any one of claims 1-6.
9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1-6.
10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1-6.