A data processing method for ultrasonic underground detection

Abstract

The present invention relates to the field of data processing, and particularly to a data processing method for underground ultrasonic detection. The method includes: acquiring ultrasonic detection data collected at multiple detection points for a target area; segmenting the ultrasonic detection data, and determining the waveform anomaly degree of each detection point according to the obtained wave bands after segmentation; determining target detection points according to the waveform anomaly degree; calculating a first waveform distortion index by combining the waveform anomaly degree and the waveform characteristics of each wave band; obtaining a second waveform distortion index according to the difference between the target detection points and adjacent detection points; performing normalization processing on the second waveform distortion index, and judging whether each target detection point is an underground cavity area or a geological loosening area according to the normalization processing result. Through this method, the underground cavity area and the geological loosening area can be distinguished based on the ultrasonic detection data, and the accuracy of using the ultrasonic detection data to determine the cavity area can be improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and particularly to a data processing method for underground ultrasonic detection. Background Art

[0002] When constructing high-speed railways, it is necessary to pass through areas with strong karst development and mined-out areas of minerals, and the geological conditions are extremely complex. Therefore, before construction, it is necessary to conduct a comprehensive disaster investigation to detect the development scale and type of bad geological structures, including karst areas and mined-out areas, etc.

[0003] By using ultrasonic technology, the underground rock formation structure can be detected non-destructively, so as to determine the location, scale and characteristics of underground voids, and thus ensure the smooth progress of construction and minimize engineering risks. However, when using ultrasonic to detect the location of underground voids, due to the possible existence of geologically loose areas underground, the obtained waveforms and the waveforms of underground voids both have amplitude attenuation and waveform distortion. Therefore, it is difficult to distinguish only by the amplitude size of the waveforms. Based on this, it is necessary to study a data processing method for underground ultrasonic detection to distinguish void areas and geologically soft areas. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of the present invention is to provide a data processing method for underground ultrasonic detection, and the specific technical solution adopted is as follows:

[0005] The present invention provides a data processing method for underground ultrasonic detection, and the method includes:

[0006] Obtain ultrasonic detection data collected from multiple detection points in a target area;

[0007] Segment the ultrasonic detection data collected from each detection point according to a period, and determine the waveform abnormality degree of each detection point according to the obtained wave bands after segmentation;

[0008] Determine target detection points according to the waveform abnormality degree;

[0009] For each target detection point, calculate a first waveform distortion index by combining the waveform abnormality degree and the waveform characteristics of each wave band;

[0010] Update the first waveform distortion index according to the difference between the target detection point and adjacent detection points to obtain a second waveform distortion index;

[0011] Normalize the second waveform distortion index, and judge whether each target detection point is an underground void area or a geologically loose area according to the normalization result.

[0012] In some embodiments, determining the waveform abnormality degree of each detection point according to the wavebands obtained after segmentation includes:

[0013] Calculating the waveform attenuation degree corresponding to each detection point according to the reference amplitude and the amplitudes in each periodic waveband;

[0014] Obtaining the waveform attenuation speed corresponding to each detection point according to the reference amplitude, the number of periods corresponding to each detection point, and the minimum amplitude in all periods corresponding to each detection point;

[0015] Based on the waveform attenuation degree and the waveform attenuation speed, obtaining the waveform abnormality degree of each detection point.

[0016] In some embodiments, specifically determining the waveform abnormality degree of each detection point according to the wavebands obtained after segmentation includes:

[0017] Calculating the average value of the difference between the amplitude in each periodic waveband and the reference amplitude, and using the average value as the waveform attenuation degree corresponding to the detection point;

[0018] Dividing the difference between the reference amplitude and the minimum amplitude in all periods corresponding to each detection point by the corresponding number of periods to obtain the waveform attenuation speed corresponding to the detection point;

[0019] Using the product of the waveform attenuation degree and the waveform attenuation speed as the waveform abnormality degree corresponding to the detection point.

[0020] In some embodiments, determining the target detection point according to the waveform abnormality degree includes: normalizing the waveform abnormality degree to the range of [-1, 1], and using the detection points with the normalized index greater than 0 as the target detection points.

[0021] In some embodiments, for each target detection point, calculating a first waveform distortion index by combining the waveform abnormality degree and the waveform characteristics of each waveband includes:

[0022] Obtaining a first product based on the waveform abnormality degree and the detection time interval corresponding to the target detection point, where the detection time interval is the time difference between the ultrasonic wave emission time and the reception time;

[0023] Performing a normalization calculation on the first product to obtain a first parameter;

[0024] According to the first parameter and the difference between each waveband corresponding to the target detection point and the standard sine wave, obtaining the first waveform distortion index corresponding to the target detection point, where the standard sine wave is obtained according to the amplitude and frequency of a single waveband of the target detection point.

[0025] In some embodiments, obtaining the first waveform distortion index corresponding to the target detection point according to the first parameter and the difference between each band corresponding to the target detection point and a standard sine wave includes:

[0026] Calculating the area of the original band formed by the original band corresponding to the target detection point in each period and the area of the standard sine wave formed by the standard sine wave corresponding to the target detection point in each period;

[0027] Calculating the average area difference corresponding to the target detection point according to the difference between the area of the original band and the area of the standard sine wave corresponding to the target detection point in each period;

[0028] Taking the product of the first parameter and the average area difference as the first waveform distortion index corresponding to the target detection point.

[0029] In some embodiments, updating the first waveform distortion index according to the difference between the target detection point and adjacent detection points to obtain the second waveform distortion index includes:

[0030] Based on the distance values between the target detection point and each of the adjacent detection points and the first waveform distortion index corresponding to each of the adjacent detection points, determining the distortion index adjustment coefficient corresponding to the target detection point, where the adjacent detection points are the M detection points with the smallest distance from the target detection point;

[0031] Multiplying the first waveform distortion index corresponding to the target detection point by the distortion index adjustment coefficient to obtain the second waveform distortion index corresponding to the target detection point.

[0032] In some embodiments, based on the distance values between the target detection point and each of the adjacent detection points and the first waveform distortion index corresponding to each of the adjacent detection points, determining the distortion index adjustment coefficient corresponding to the target detection point includes:

[0033] Obtaining the first distance of each adjacent detection point relative to the target detection point and obtaining a first coefficient based on the ratio of the first distance to the sum of the first distances corresponding to all the adjacent detection points;

[0034] Calculating the difference between the first waveform distortion index corresponding to each adjacent detection point and the first waveform distortion index corresponding to the target detection point and performing an exponential operation to obtain a second coefficient;

[0035] Based on the first coefficient and the second coefficient, obtaining the distortion index adjustment coefficient corresponding to the target detection point.

[0036] In some embodiments, obtaining the distortion index adjustment coefficient corresponding to the target detection point based on the first coefficient and the second coefficient includes:

[0037] Multiplying the first coefficient and the second coefficient corresponding to each adjacent detection point to obtain a second parameter corresponding to each adjacent detection point;

[0038] Based on the sum of the second parameters corresponding to all the adjacent detection points, obtaining the distortion index adjustment coefficient corresponding to the target detection point.

[0039] In some embodiments, normalizing the second waveform distortion index and determining whether each target detection point is an underground cavity area or a geological loosening area according to the normalization result includes:

[0040] Normalizing the second waveform distortion index to the range of [0, 1], and regarding the target detection point with the normalization result greater than or equal to the preset threshold as a geological loosening area, and regarding the target detection point with the normalization result less than the preset threshold as an underground cavity area; wherein the preset threshold is 0.5.

[0041] The present invention has the following beneficial effects:

[0042] (1) In the data processing method for ultrasonic underground detection provided in some embodiments of this specification, by combining the waveform abnormality degree corresponding to the detection point and the waveform characteristics of each wave band to calculate the first waveform distortion index, then obtaining the second waveform distortion index according to the difference between this detection point and the adjacent detection points, and finally determining whether the detection point is an underground cavity area or a geological loosening area according to the normalization result corresponding to the second waveform distortion index, it is possible to distinguish the underground cavity area and the geological loosening area based on the ultrasonic detection data, and improve the accuracy of using the ultrasonic detection data to determine the underground cavity area;

[0043] (2) In the data processing method for ultrasonic underground detection provided in some embodiments of this specification, by calculating the average value of the difference between the amplitude and the reference amplitude in each cycle wave band as the waveform attenuation degree of the corresponding detection point, dividing the difference between the reference amplitude and the minimum amplitude in all cycles corresponding to each detection point by the corresponding number of cycles to obtain the waveform attenuation speed of the corresponding detection point, and then taking the product of the waveform attenuation degree and the waveform attenuation speed as the waveform abnormality degree of the corresponding detection point, it can accurately reflect the influence of various underground structures on ultrasonic waves, and thus be used as a reference basis for screening the underground cavity area and the geological loosening area;

[0044] (3) In the data processing method for ultrasonic underground detection provided in some embodiments of this specification, a first waveform distortion index is calculated by combining the waveform anomaly degree corresponding to the detection point and the waveform characteristics of each wave band. Then, the first waveform distortion index is updated according to the difference between the detection point and the adjacent detection points to obtain a second waveform distortion index. By using this second waveform distortion index to determine whether each detection point is an underground cavity area or a geological loosening area, the type of the current detection point can be analyzed in combination with the ultrasonic detection conditions of the adjacent detection points, thereby improving the accuracy of the judgment result. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0046] Figure 1 It is an exemplary flowchart of a data processing method for ultrasonic underground detection provided by an embodiment of the present invention;

[0047] Figures 2 to 4 It is a waveform schematic diagram of ultrasonic detection data provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0048] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following will, in combination with the drawings and preferred embodiments, detail the specific implementation manner, structure, characteristics, and effects of a data processing method for ultrasonic underground detection proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0049] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0050] The following will specifically describe the specific solution of a data processing method for ultrasonic underground detection provided by the present invention in conjunction with the drawings.

[0051] Please refer to Figure 1 , which shows the exemplary flow step 100 of a data processing method for ultrasonic underground detection provided by an embodiment of the present invention. The method includes:

[0052] S110. Obtain the ultrasonic detection data collected from multiple detection points in the target area.

[0053] In some embodiments of the present invention, the ultrasonic detection data of the target area can be obtained through the following steps:

[0054] First, determine multiple detection points in the target area where ultrasonic detection is required. In the embodiments of the present invention, the distance between adjacent detection points can be the same or different.

[0055] Second, prepare an ultrasonic detector to ensure that the ultrasonic detector is in a working state. Among them, the generated wave of the ultrasonic detector is usually a sine wave, and the frequency and amplitude of its transmitted waveform can be adjusted according to specific needs.

[0056] Then, collect data. Specifically, in some embodiments, at each detection point, the ultrasonic detector can be placed on the ground surface or at a certain depth underground, and the ultrasonic detector is started to perform ultrasonic detection. It can be understood that the ultrasonic detector will send ultrasonic waves and record the waveform data reflected back.

[0057] Finally, record the data. During the detection process, the ultrasonic detector can record the ultrasonic detection data of each detection point. The ultrasonic detection data can include a waveform diagram and the corresponding detection time, etc. Usually, the data can be recorded through the built-in recording function of the ultrasonic detector or an external device. As Figures 2 to 4 shown, in some embodiments, for different detection points (detection positions, such as Figure 2 the position No. 1 shown, Figure 3 the position No. 2 shown, Figure 4 the position No. 3 shown, etc.), the obtained ultrasonic detection data may have waveform diagrams of different shapes, and different waveform diagrams can reflect different information.

[0058] S120. Segment the ultrasonic detection data collected from each detection point according to a period, and determine the waveform abnormality degree of each detection point according to the obtained wave band after segmentation.

[0059] In the underground rock formation structure, there generally exist hard rock formations, loose and soft rock formations, and underground cavities. Among them, the hard rock formations are usually solid geological materials. The ultrasonic emission waveform is usually sent underground with a relatively high amplitude and frequency. Since the hard rock structure is uniform, the propagation of ultrasonic waves is less interfered. Therefore, the energy loss of ultrasonic waves during propagation is small, the similarity between the ultrasonic emission waveform and the received waveform is relatively high, and a relatively stable amplitude is shown. In other words, the ultrasonic waveform collected for the rock formation is relatively stable and the waveform is relatively uniform. For the loose rock formations and underground cavity areas, the waveform will be reflected, refracted, and scattered in the underground structure, and the waveform may change, resulting in situations such as amplitude attenuation and waveform distortion. Therefore, it is necessary to determine the possibility of each detection point being a rock formation, a geological loosening area, or an underground cavity area according to the abnormal situation of the waveform.

[0060] In some embodiments of the present invention, in order to determine the information reflected by the ultrasonic detection data collected at each detection point, the ultrasonic detection data collected at each detection point can be segmented according to the period, and then the waveform abnormality degree of each detection point can be determined according to the obtained wave bands after segmentation.

[0061] Specifically, since the frequency of the received ultrasonic wave does not change while the amplitude decays, the period of the received waveform and the transmitted sine wave is the same. Based on this, the overall waveform of the ultrasonic detection data obtained at each detection point can be segmented by a period of a sine wave to segment the entire wave band corresponding to each detection point into N periods, and determine the peak value and valley value of each period, and determine the amplitude of the wave band of this period as half of the difference between the peak value and the valley value (that is, half of the sum of the absolute values of the peak value and the valley value).

[0062] Furthermore, for the wave bands obtained after segmentation, the following formula can be used to calculate the waveform abnormality degree of each detection point:

[0063]

[0064] Among them, represents the waveform abnormality degree corresponding to the vth detection point; represents the number of periods of the wave band corresponding to the vth detection point; is the reference amplitude, which represents the amplitude of the waveform of the ultrasonic wave emitted by the current detection point (prior information); represents the amplitude in the ith period wave band of the vth detection point; represents the minimum amplitude among all periods of the vth detection point.

[0065] In the above formula, It can represent the waveform attenuation degree of the sine wave in each period of the entire waveform. It can represent the waveform attenuation degree of the overall waveform corresponding to the current detection point. The larger this value is, the greater the attenuation of the waveform at the current detection point and the more abnormal the waveform. It represents the waveform attenuation range of the current detection point. It represents the waveform attenuation speed corresponding to the current detection point. The larger this value is, the more serious the waveform attenuation and the higher the abnormality degree of the waveform at the current detection point.

[0066] Specifically, in some embodiments of the present invention, the waveform attenuation degree corresponding to each detection point can be calculated according to the reference amplitude ( ), and the amplitude in each period band ( ); then, according to the reference amplitude ( ), the number of periods corresponding to each detection point ( ), and the minimum amplitude in all periods corresponding to each detection point ( ), the waveform attenuation speed corresponding to each detection point ( ) is obtained; finally, based on the waveform attenuation degree ( ) and the waveform attenuation speed ( ), the waveform abnormality degree of each detection point ( ) is obtained.

[0067] More specifically, in some embodiments, the average value of the difference between the amplitude in each period band ( ) and the reference amplitude ( ) can be calculated ( ), and this average value ( ) is used as the waveform attenuation degree of the corresponding detection point. Then, the difference between the reference amplitude ( ) and the minimum amplitude in all periods corresponding to each detection point ( ) ( ) is divided by the corresponding number of periods ( ) to obtain the waveform attenuation speed of the corresponding detection point ( ). Finally, the product of this waveform attenuation degree ( ) and the waveform attenuation speed ( ) ( ) is used as the waveform abnormality degree of the corresponding detection point.

[0068] S130, determine the target detection point according to the waveform abnormality degree.

[0069] After calculating the waveform abnormality degree corresponding to each detection point through the above steps, the waveform abnormality degree corresponding to each detection point can be normalized to the range of [-1, 1] (for example, using linear normalization), and the detection points with the normalized index greater than 0 are used as target detection points. Specifically, the detection points with the normalized index greater than 0 indicate that they are underground cavity or geological loosening areas. In the subsequent process, only the detection points corresponding to the underground cavity or geological loosening areas (i.e., the detection points with the above-mentioned normalized index greater than 0) can be used as target detection points for further analysis and processing.

[0070] S140. For each target detection point, calculate the first waveform distortion index by combining the waveform abnormality degree and the waveform characteristics of each frequency band.

[0071] In the geological loosening area, the underground medium may be loose or uneven. When ultrasonic waves propagate, the amplitude will become smaller, and the propagation speed is different, resulting in a relatively long signal propagation time. At the same time, due to the inhomogeneity of the medium, phenomena such as refraction and reflection of ultrasonic waves will occur, so the possibility of distortion of this underground medium is relatively large, and the degree of distortion of the waveform is also relatively serious. Relatively speaking, an underground cavity is usually a closed space. When ultrasonic waves propagate, they may encounter less resistance and energy loss. Therefore, the amplitude attenuation may be relatively small. Moreover, the medium inside the underground cavity is relatively uniform, and there may be less interference during propagation, so the waveform distortion may be relatively small, and the propagation speed of ultrasonic waves may be relatively fast and stable.

[0072] Based on the above analysis, in some embodiments, after dividing the waveform of each detection point into single-cycle frequency bands, the amplitude of the single-cycle frequency band can be determined. And the area of the frequency band of this frequency band (that is, the original frequency band area mentioned later). Among them, the amplitude of the single-cycle frequency band is half of the sum of the absolute values of the peak value and the valley value, and the frequency band area can refer to the area of the region enclosed by the perpendiculars drawn from the endpoints of each cycle frequency band to the horizontal axis and the horizontal axis.

[0073] Since the waveforms obtained by the ultrasonic detector for underground cavities or geological loosening areas are distorted, the waveforms may be damaged or deformed. In some embodiments of the present invention, a standard sine wave can be regenerated according to the amplitude and frequency of a single cycle, and the area of the frequency band of the regenerated standard sine wave can be determined. (that is, the standard sine wave area mentioned later, and its determination method is the same as that of the frequency band area ), and then by determining the difference in the frequency band area between the original frequency band and the standard sine wave, the distortion degree of the original waveform can be determined.

[0074] Specifically, in some embodiments, for each target detection point, the first waveform distortion index corresponding to each target detection point can be calculated by combining the aforementioned waveform anomaly degree and the waveform features of each frequency band. This calculation process can be expressed as follows:

[0075]

[0076] Wherein, represents the first waveform distortion index corresponding to the v-th target detection point; () represents the normalization operation; represents the waveform anomaly degree corresponding to the waveform of the v-th target detection point; represents the detection time interval corresponding to the v-th target detection point, that is, the time difference between the ultrasonic wave emission time and the reception time; and respectively represent the original band area corresponding to the i-th cycle band of the v-th target detection point and the standard sine wave area corresponding to the regenerated standard sine wave; represents the number of cycles of the band corresponding to the v-th target detection point.

[0077] In other words, in some embodiments, based on the aforementioned waveform anomaly degree and the detection time interval corresponding to the target detection point , the first product ( ) can be obtained; then, the normalization calculation is performed on this first product to obtain the first parameter ( ); finally, according to this first parameter and the difference between each band corresponding to the target detection point and the standard sine wave, the first waveform distortion index corresponding to the target detection point is obtained.

[0078] Specifically, in some embodiments of the present invention, the original band area ( ) formed by the original band corresponding to the target detection point in each cycle and the standard sine wave area ( ) formed by the standard sine wave corresponding to the target detection point in each cycle can be calculated; then, according to the difference between the original band area and the standard sine wave area corresponding to the target detection point in each cycle, the average area difference ( ) corresponding to the target detection point is calculated; finally, the product ( ) of this first parameter and the average area difference is used as the first waveform distortion index corresponding to the target detection point.

[0079] It should be noted that in the above formula, represents the area difference between the original band and the regenerated standard sine wave within a single cycle, Represents the average value of the area difference between the original waveband within all periods of the current detection point and the regenerated standard sine wave. The larger this value is, the more severe the waveform distortion degree of the current detection point is. Represents the detection time interval of the detection point. The larger this value is, the greater the possibility that the current detection point is a geologically loose area. Represents the waveform abnormality degree corresponding to the current detection point. The larger this value is, the greater the amplitude attenuation degree and the more severe the attenuation, indicating that the possibility that the current detection point is a geologically loose area is relatively large.

[0080] S150, update the first waveform distortion index according to the difference between the target detection point and adjacent detection points to obtain the second waveform distortion index.

[0081] When using an ultrasonic detector to detect underground rock formations at each detection point in the target area, the detection points at similar positions may be in the same rock formation area. Therefore, the rock formation area situation of the current detection point can be further determined through the information of adjacent detection points around. If the waveform distortion indexes corresponding to the current detection point shown by all adjacent detection points of the current detection point are relatively large, then the waveform distortion index corresponding to the current detection point can be further increased.

[0082] Based on this, in some embodiments of the present invention, for any target detection point, the positional relationship between other adjacent detection points and the current target detection point can be determined. For example, it can be determined that the M (M is taken as 5 in the present invention) detection points with the smallest distance from the current target detection point are the adjacent detection points corresponding to the current target detection point, and then the difference between the adjacent detection points and the current target detection point is determined to update the first waveform distortion index corresponding to the current target detection point , to obtain the second waveform distortion index . This process can be expressed as follows:

[0083]

[0084] Among them, Represents the first waveform distortion index corresponding to the v-th target detection point, Represents the second waveform distortion index corresponding to the v-th target detection point (that is, the waveform distortion index obtained after updating the first waveform distortion index ); Represents the first waveform distortion index of the i-th adjacent detection point corresponding to the v-th target detection point (in this embodiment, this adjacent detection point can be regarded as the target detection point, and the first waveform distortion index corresponding to each adjacent detection point can be calculated by referring to the foregoing calculation method of the first waveform distortion index), Represents the positional distance value between the i-th adjacent detection point corresponding to the v-th target detection point and the v-th target detection point. represents the position distance value between the k-th neighboring detection point corresponding to the v-th target detection point and the v-th target detection point, represents the number of neighboring detection points corresponding to the target detection point, and in the present invention, M is 5; () represents the exponential operation with the natural constant e as the base.

[0085] Specifically, in some embodiments of the present invention, based on the distance value between the target detection point and each neighboring detection point ( ), and the first waveform distortion index corresponding to each neighboring detection point ( ), the distortion index adjustment coefficient corresponding to the target detection point can be determined; then, the first waveform distortion index corresponding to the target detection point ( ), and the distortion index adjustment coefficient are multiplied to obtain the second waveform distortion index corresponding to the target detection point ( ).

[0086] In some embodiments, the distortion index adjustment coefficient corresponding to the foregoing target detection point can be determined in the following manner:

[0087] First, obtain the first distance of each neighboring detection point relative to the target detection point ( ), and based on the ratio of the sum of the first distances corresponding to all neighboring detection points ( ) to this first distance, obtain the first coefficient ( ).

[0088] Then, calculate the difference between the first waveform distortion index corresponding to each neighboring detection point ( ) and the first waveform distortion index corresponding to the target detection point ( ), and perform an exponential operation to obtain the second coefficient ( ). In the embodiments of the present invention, this exponential operation can be an exponential operation with the natural constant e as the base.

[0089] Finally, based on the foregoing first coefficient ( ) and second coefficient ( ), obtain the distortion index adjustment coefficient corresponding to the target detection point.

[0090] Specifically, in some embodiments, the first coefficient and the second coefficient corresponding to each neighboring detection point can be multiplied to obtain the second parameter corresponding to each neighboring detection point ( ); then, based on the sum of the second parameters corresponding to all neighboring detection points ( ), obtain the distortion index adjustment coefficient corresponding to the target detection point ( ).

[0091] It should be noted that in the above formula, the first coefficient represents the ratio of the sum of the distances of all adjacent detection points to the distances of each adjacent detection point relative to the target detection point. The larger this value is, the smaller the distance between the current adjacent detection point and the current target detection point compared to other detection points, indicating a greater possibility that two target detection points detect the same rock stratum area, and indicating that the adjacent detection point has a greater weight on the waveform distortion index of the current target detection point. represents the difference in the waveform distortion index (the first waveform distortion index) between the adjacent detection point and the current target detection point. The larger this value is, the greater the difference in the waveform distortion index corresponding to the target detection point and the waveform distortion index corresponding to the relevant detection point, and thus the greater the waveform distortion index that needs to be corrected; can represent the overall repair index of the adjacent detection point to the current target detection point.

[0092] S160. Normalize the second waveform distortion index, and determine whether each of the target detection points is an underground cavity area or a geological loosening area according to the normalization result.

[0093] After obtaining the second waveform distortion index corresponding to each target detection point through the above steps ( ), the second waveform distortion index can be normalized to the range of [0, 1] (for example, using linear normalization), and the geological loosening area and the underground cavity area can be distinguished based on the normalization result.

[0094] It can be understood that since ultrasonic waves may encounter different resistances and energy losses during the propagation process in the geological loosening area, the waveform distortion may be relatively large; while the internal medium of the underground cavity is relatively uniform and may be less interfered during propagation, and the waveform distortion may be relatively small. Therefore, after normalizing the foregoing second waveform distortion index, the geological loosening area and the underground cavity area can be distinguished by this normalization result. For example, in some embodiments, a target detection point with a normalization result greater than or equal to a preset threshold can be regarded as a geological loosening area, and a target detection point with a normalization result less than the preset threshold can be regarded as an underground cavity area. In some embodiments, the foregoing preset threshold can be set to 0.5.

[0095] It can be understood that after processing the ultrasonic detection data collected for the target area through the above steps S110~S160, it is possible to determine that each detection point is a geological loosening area or an underground cavity area.

[0096] Further, in some embodiments, an electronic map of the target area can be obtained from a map provider or a relevant institution, and then the detection point positions corresponding to the underground cavities and the geological loosening areas are marked on the electronic map. The electronic map marked with the detection point positions of the underground cavities and the geological loosening areas and the detection data such as the ultrasonic waveforms collected at the detection point positions are uploaded to the construction background system to ensure that relevant staff can view the uploaded electronic map and ultrasonic waveforms for the reference of the construction unit.

[0097] Those skilled in the art should understand that Figure 1 Steps S110 to S160 in the data processing method for ultrasonic underground detection shown can be implemented using computer-executable instructions and / or included in processor control code. For example, such code is provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. In some embodiments, each step in the method can be implemented by hardware, software, or a combination of software and hardware. Among them, the hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware.

[0098] In summary, the beneficial effects that the present invention may bring include, but are not limited to: (1) In the data processing method for ultrasonic underground detection provided in some embodiments of this specification, by combining the waveform anomaly degree corresponding to the detection point and the waveform characteristics of each wave band to calculate the first waveform distortion index, then obtaining the second waveform distortion index based on the difference between this detection point and adjacent detection points, and finally judging whether the detection point is an underground cavity area or a geological loosening area according to the normalization processing result corresponding to the second waveform distortion index, it is possible to distinguish the underground cavity area and the geological loosening area based on ultrasonic detection data, and improve the accuracy of using ultrasonic detection data to determine the underground cavity area; (2) In the data processing method for ultrasonic underground detection provided in some embodiments of this specification, by calculating the average value of the difference between the amplitude in each cycle wave band and the reference amplitude as the waveform attenuation degree of the corresponding detection point, dividing the difference between the reference amplitude and the minimum amplitude in all cycles corresponding to each detection point by the corresponding number of cycles to obtain the waveform attenuation speed of the corresponding detection point, and then using the product of the waveform attenuation degree and the waveform attenuation speed as the waveform anomaly degree of the corresponding detection point, it can accurately reflect the influence of various underground structures on ultrasonic waves, thereby serving as a reference basis for screening the underground cavity area and the geological loosening area; (3) In the data processing method for ultrasonic underground detection provided in some embodiments of this specification, by combining the waveform anomaly degree corresponding to the detection point and the waveform characteristics of each wave band to calculate the first waveform distortion index, then updating the first waveform distortion index according to the difference between the detection point and adjacent detection points to obtain the second waveform distortion index, and judging whether each detection point is an underground cavity area or a geological loosening area through the second waveform distortion index, it is possible to analyze the type of the current detection point by combining the ultrasonic detection conditions of adjacent detection points, thereby improving the accuracy of the judgment result.

[0099] It should be noted that different embodiments may produce different beneficial effects. In different embodiments, the possible beneficial effects may be a combination of any one or several of the above, or any other beneficial effects that may be obtained.

[0100] It should also be noted that: the above sequence of the embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be beneficial.

[0101] Each embodiment in this specification is described in a progressive manner. The same or similar parts among the embodiments can be referred to each other, and the key point of each embodiment is to illustrate the differences from other embodiments.

[0102] The basic concepts of the present invention have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only an example. Although not explicitly stated here, those skilled in the art may make various modifications, improvements, and corrections to this specification. Such modifications, improvements, and corrections are suggested in this specification, so such modifications, improvements, and corrections still fall within the scope of the exemplary embodiments of this specification.

Claims

1. A data processing method for ultrasonic underground detection, characterized in that: The method comprises: Acquire ultrasonic detection data collected from multiple detection points in the target area; The ultrasonic detection data collected at each detection point is segmented according to the period, and the degree of waveform abnormality of each detection point is determined according to the band obtained after segmentation; Determining a target detection point according to the degree of waveform abnormality; For each target detection point, a first waveform distortion index is calculated by combining the waveform abnormality degree and the waveform characteristics of each band; updating the first waveform distortion index according to the difference between the target detection point and the adjacent detection point to obtain a second waveform distortion index; Normalizing the second waveform distortion index, and judging each of the target detection points as an underground cavity area or a geological loose area according to the normalization result; The first waveform distortion index is calculated for each target detection point in combination with the waveform abnormality degree and the waveform characteristics of each band, including: A first product is obtained based on the waveform abnormality degree and the detection time interval corresponding to the target detection point, wherein the detection time interval is the time difference between the ultrasonic emission time and the reception time; Performing normalization calculation on the first product to obtain a first parameter; According to the first parameter and the difference between each band corresponding to the target detection point and the standard sine wave, a first waveform distortion index corresponding to the target detection point is obtained, wherein the standard sine wave is obtained according to the amplitude and frequency of a single band of the target detection point; The first waveform distortion index corresponding to the target detection point is obtained according to the first parameter and the difference between each wave band corresponding to the target detection point and the standard sine wave, including: Calculate the original band area formed by the original band corresponding to the target detection point in each cycle, and the standard sine wave area formed by the standard sine wave corresponding to the target detection point in each cycle; Calculate the area difference mean corresponding to the target detection point according to the difference between the original band area and the standard sine wave area corresponding to the target detection point in each cycle; Taking the product of the first parameter and the mean value of the area difference as the first waveform distortion index corresponding to the target detection point; The calculation formula corresponding to the first waveform distortion index is: in, represents the first waveform distortion index corresponding to the vth target detection point; () indicates normalization operation; Indicates the degree of waveform abnormality corresponding to the waveform of the vth target detection point; represents the detection time interval of the vth target detection point; and They represent the original band area corresponding to the i-th periodic band of the v-th target detection point and the standard sine wave area corresponding to the regenerated standard sine wave; Indicates the number of cycles of the band corresponding to the vth target detection point; The updating of the first waveform distortion index according to the difference between the target detection point and the adjacent detection point to obtain the second waveform distortion index includes: Determine the distortion index adjustment coefficient corresponding to the target detection point based on the distance value between the target detection point and each of the adjacent detection points and the first waveform distortion index corresponding to each of the adjacent detection points, wherein the adjacent detection points are M detection points with the smallest distance from the target detection point; Multiplying the first waveform distortion index corresponding to the target detection point and the distortion index adjustment coefficient to obtain a second waveform distortion index corresponding to the target detection point; The step of determining the distortion index adjustment coefficient corresponding to the target detection point based on the distance value between the target detection point and each of the adjacent detection points and the first waveform distortion index corresponding to each of the adjacent detection points includes: Acquire a first distance of each of the neighboring detection points relative to the target detection point, and obtain a first coefficient based on a ratio of the first distance to the sum of the first distances corresponding to all the neighboring detection points; Calculating the difference between the first waveform distortion index corresponding to each of the adjacent detection points and the first waveform distortion index corresponding to the target detection point, and performing exponential operation to obtain a second coefficient; Based on the first coefficient and the second coefficient, obtaining a distortion index adjustment coefficient corresponding to the target detection point; The obtaining, based on the first coefficient and the second coefficient, a distortion index adjustment coefficient corresponding to the target detection point includes: Multiplying the first coefficient and the second coefficient corresponding to each of the neighboring detection points to obtain a second parameter corresponding to each of the neighboring detection points; Obtaining a distortion index adjustment coefficient corresponding to the target detection point based on the sum of the second parameters corresponding to all the adjacent detection points; The calculation formula corresponding to the second waveform distortion index is: in, represents the second waveform distortion index corresponding to the vth target detection point; It represents the first waveform distortion index of the ith neighboring detection point corresponding to the vth target detection point. It represents the position distance value between the i-th neighboring detection point corresponding to the v-th target detection point and the v-th target detection point. It represents the position distance value between the kth neighboring detection point corresponding to the vth target detection point and the vth target detection point. Indicates the number of neighboring detection points corresponding to the target detection point, () represents an exponential operation with the natural constant e as the base.

2. A data processing method for ultrasonic underground detection according to claim 1, characterized in that: Determining the degree of waveform abnormality of each detection point according to the segmented wave bands includes: According to the reference amplitude and the amplitude in each periodic band, the attenuation degree of the waveform corresponding to each detection point is calculated; Obtaining a waveform decay speed corresponding to each detection point according to the reference amplitude, the number of cycles corresponding to each detection point, and the minimum amplitude of all cycles corresponding to each detection point; Based on the waveform attenuation degree and the waveform attenuation speed, the waveform abnormality degree of each detection point is obtained.

3. A data processing method for ultrasonic underground detection as claimed in claim 2, characterized in that: Determining the degree of waveform abnormality of each detection point according to the segmented wave bands specifically includes: Calculate the average value of the difference between the amplitude in each periodic band and the reference amplitude, and use the average value as the waveform attenuation degree of the corresponding detection point; The difference between the reference amplitude and the minimum amplitude in all cycles corresponding to each detection point is divided by the corresponding number of cycles to obtain the waveform decay speed of the corresponding detection point; The product of the waveform attenuation degree and the waveform attenuation speed is used as the waveform abnormality degree of the corresponding detection point.

4. A data processing method for ultrasonic underground detection according to claim 1, characterized in that: The determining of the target detection point according to the waveform abnormality degree includes: normalizing the waveform abnormality degree to a range of [-1, 1], and taking the detection point whose normalization index is greater than 0 as the target detection point.

5. A data processing method for ultrasonic underground detection as claimed in claim 1, characterized in that: The normalizing process is performed on the second waveform distortion index, and judging each of the target detection points as an underground cavity area or a geological loose area according to the normalization process result, including: The second waveform distortion index is normalized to the range of [0,1], and the target detection points whose normalized processing results are greater than or equal to the preset threshold are regarded as geological loose areas, and the target detection points whose normalized processing results are less than the preset threshold are regarded as underground void areas; wherein the preset threshold is 0.5.

Images