An integrated equipment for water conservancy river channel dredging and bottom mud treatment

Abstract

The present invention relates to the field of data processing technology, and specifically to an integrated device for desilting and treating bottom mud in a water conservancy river, including: obtaining sonar signals and bucket wheel speed, decomposing sonar signals and dividing sonar signal components and sonar signals into a plurality of sonar signal component segments and sonar signal segments; according to the periodicity and energy in a single sonar signal component segment, combined with the difference between a plurality of sonar signal component segments, setting the wavelet threshold of the sonar signal component segment to denoise the sonar signal segment; reorganizing all sonar signal segments to obtain a denoised sonar signal; using the denoised sonar signal to find out the riverbed position, and setting the descent depth of the bucket wheel of the dredging ship to clean the mud at the bottom of the river. The present invention analyzes the noise components in each sonar signal component segment, adaptively assigns a wavelet threshold, and denoises it, so as to accurately identify the riverbed depth and avoid damage to the riverbed during the desilting process.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and specifically to an integrated device for desilting and treating bottom mud in a water conservancy river. Background Art

[0002] When a dredging ship is clearing the silt at the bottom of a river, it will push its bucket wheel deep into the riverbed and use it to clean the silt. In the process of cleaning the silt with the bucket wheel, in order to avoid damage to the riverbed when the bucket wheel is working, it is necessary to monitor the distance between the dredging ship and the riverbed in real time through a sonar system. The sonar signals collected in the river include the reflected sonar signals, the mechanical noise generated by the bucket wheel when working, and the random noise in the natural environment, which leads to complex components of the sonar signals. The traditional EMD decomposition cannot effectively decompose the noise components, so that each component in the sonar signal contains noise components. At this time, if only the high-frequency components are denoised according to the traditional method, a good denoising effect cannot be obtained. Summary of the invention

[0003] The present invention provides an integrated device for desilting and treating bottom mud in a water conservancy river channel, so as to solve the existing problem that the conventional EMD decomposition method has a poor denoising effect on the sonar signal collected by the desilting ship.

[0004] The integrated equipment for desilting and treating sediment in a water conservancy river of the present invention adopts the following technical scheme:

[0005] Includes the following modules:

[0006] A data acquisition module is used to obtain the sonar signal and the bucket wheel speed, decompose the sonar signal, and obtain several sonar signal components;

[0007] The independent signal analysis module is used to divide the sonar signal component and the sonar signal into a plurality of sonar signal component segments and sonar signal segments; obtain the sonar characteristics of the sonar signal component segment according to the periodicity and energy of the sonar signal component segment; obtain the confidence of the sonar signal segment according to the sonar characteristics of the sonar signal component segment corresponding to the sonar signal segment; obtain the noise factor of the sonar signal component segment according to the confidence of the sonar signal segment and the sonar characteristics of the corresponding sonar signal component segment;

[0008] The local signal analysis module is used to obtain the comparison segment and the target segment, wherein the target segment and the comparison segment are sonar signal component segments; obtain the characteristic difference between the comparison segment and the target segment according to the difference between the comparison segment and the target segment in instantaneous frequency and bucket wheel speed; obtain the natural noise change of the target segment according to the characteristic difference between the comparison segment and the target segment, the time sequence distance and the confidence of the sonar signal segment corresponding to the comparison segment;

[0009] The signal denoising module is used to obtain the natural noise content of the sonar signal component segment according to the natural noise change and noise factor of the sonar signal component segment, and denoise the sonar signal segment in combination with the corresponding bucket wheel speed to obtain a denoised sonar signal; the riverbed position is determined through the denoised sonar signal, and the descent depth of the dredging ship bucket wheel is set to clean the silt at the bottom of the river.

[0010] Preferably, the step of dividing the sonar signal components and the sonar signal into a plurality of sonar signal component segments and sonar signal segments comprises the following specific methods:

[0011] Preset a sonar signal segment length , split the sonar signal and the sonar signal component into several lengths Sonar signal segments and sonar signal component segments.

[0012] Preferably, the step of obtaining the sonar features of the sonar signal component segments includes the following specific methods:

[0013] The Hilbert transform is used to obtain the period in each sonar signal component segment and the instantaneous frequency of each data point in all sonar signal component segments;

[0014] For any sonar signal component segment, the maximum sonar feature of the sonar signal component segment is obtained according to the amplitude of the period in the sonar signal component segment and the amplitude of all maximum points in the sonar signal component segment. The specific calculation formula is:

[0015]

[0016] In the formula, Indicates the maximum sonar feature of the sonar signal component segment; Indicates the first component of the sonar signal The amplitude of the maximum point; Represents the mean value of the amplitude of all maximum points in the sonar signal component segment; Indicates the number of maximum points in the sonar signal component segment; Indicates the first component of the sonar signal The mean of the amplitude difference between a maximum point and its adjacent maximum points; Indicates the number of cycles in the sonar signal component segment; Indicates the first component of the sonar signal The amplitude of the cycle; represents an exponential function with a natural constant as base; represents the linear normalization function;

[0017] The minimum sonar feature of the sonar signal component segment is obtained, and the average of the maximum sonar feature of the sonar signal component segment and the minimum sonar feature of the sonar signal component segment is used as the sonar feature of the sonar signal component segment.

[0018] Preferably, the obtaining of the confidence of the sonar signal segment includes the following specific methods:

[0019] For any sonar signal segment, the sonar signal component segment with the largest sonar feature among the sonar signal component segments corresponding to the sonar signal segment is recorded as the reference component segment; the average of the differences in sonar features between the reference component segment and all the sonar signal component segments corresponding to the sonar signal segment is taken as the confidence of the sonar signal segment.

[0020] Preferably, the method of obtaining the noise factor of the sonar signal component segment includes:

[0021] For any sonar signal component segment, the difference between 1 and the sonar feature of the sonar signal component segment is multiplied by the confidence of the sonar signal segment corresponding to the sonar signal component segment, and the obtained product is used as the noise factor of the sonar signal component segment.

[0022] Preferably, the obtaining of the comparison segment and the target segment includes the following specific methods:

[0023] Preset a local segment number For any sonar signal segment, replace the sonar signal segments, recorded as local signal segments; all sonar signal component segments corresponding to the sonar signal segments are recorded as target segments, and all sonar signal component segments corresponding to all local signal segments are recorded as local signal component segments;

[0024] For any target segment, the local signal component segment with the same IMF component sequence number as the target segment is recorded as the comparison segment.

[0025] Preferably, the obtaining of the feature difference between the comparison segment and the target segment comprises the following specific methods:

[0026] For any target segment, the instantaneous frequency of each data point in the comparison segment and the target segment is obtained by using Hilbert transform, and the instantaneous frequency sequence of each comparison segment and the instantaneous frequency sequence of the target segment are obtained;

[0027] For any comparison segment, the DTW algorithm is used to match the instantaneous frequency sequence of the comparison segment with the instantaneous frequency sequence of the target segment to obtain several instantaneous frequency pairs; according to the instantaneous frequency in the instantaneous frequency pair and the bucket wheel speed corresponding to each instantaneous frequency in the instantaneous frequency pair, the characteristic difference between the comparison segment and the target segment is obtained. The specific calculation formula is:

[0028]

[0029] In the formula, Indicates the feature difference between the comparison segment and the target segment; represents the number of instantaneous frequency pairs; Indicates The first instantaneous frequency in a pair of instantaneous frequencies; Indicates The second instantaneous frequency in a pair of instantaneous frequencies; Indicates The bucket wheel speed corresponding to the first instantaneous frequency among the instantaneous frequencies; Indicates The bucket wheel speed corresponding to the second instantaneous frequency among the first instantaneous frequency; It represents the absolute value function; represents the linear normalization function.

[0030] Preferably, the obtaining of the natural noise variation of the target segment includes the following specific methods:

[0031] For any target segment, the natural noise change of the target segment is obtained according to the confidence of the sonar signal segments corresponding to all comparison segments, the time series distance between all comparison segments and the target segment, and the feature difference between all comparison segments and the target segment. The specific calculation formula is:

[0032]

[0033] In the formula, represents the natural noise variation of the target segment; Indicates the number of contrast segments; Indicates The confidence level of the sonar signal segment corresponding to the comparison segment; Indicates the maximum confidence in the sonar signal segment corresponding to all comparison segments; Indicates The temporal distance between the comparison segment and the target segment; Indicates the minimum distance between all comparison segments and the target segment in time series; Indicates The feature differences between the comparison segment and the target segment.

[0034] Preferably, the method of obtaining the natural noise content of the sonar signal component segment includes:

[0035] For any sonar signal component segment, the product of the noise factor of the sonar signal component segment and the natural noise change of the sonar signal component segment is normalized, and the normalized result is used as the natural noise content of the sonar signal component segment.

[0036] Preferably, the denoising of the sonar signal segment includes the following specific methods:

[0037] Preset an initial wavelet threshold For any sonar signal component segment, the wavelet threshold of the sonar signal component segment is obtained according to the natural noise content of the sonar signal component segment and the average value of the bucket wheel speed in the time period corresponding to the sonar signal component segment, combined with the initial wavelet threshold. The specific calculation formula is:

[0038]

[0039] In the formula, A wavelet threshold representing a component segment of the sonar signal; Represents the preset initial wavelet threshold; Indicates the natural noise content of the sonar signal component segment; It represents the average value of bucket wheel speed in the time period corresponding to the sonar signal component segment; represents the linear normalization function;

[0040] The wavelet threshold filtering algorithm is used to filter and denoise each sonar signal component segment according to the wavelet threshold of each sonar signal component segment, and the denoised sonar signal component segment is reconstructed to obtain the denoised sonar signal segment.

[0041] The beneficial effect of the technical solution of the present invention is as follows: the present application decomposes the sonar signal and divides the sonar signal component and the sonar signal into a plurality of sonar signal component segments and sonar signal segments; quantifies the sonar features in the sonar signal component segment according to the periodicity and energy in a single sonar signal component segment; and because when the sonar signal segment is less affected by noise, the EMD decomposition can more concentratedly divide the sonar features into one sonar signal component, based on which the influence of noise on the sonar signal segment is quantified, the confidence of the sonar signal segment is obtained, and the noise factor of the sonar signal component segment is further obtained by combining the sonar features of the sonar signal component segment.

[0042] Furthermore, since EMD decomposition is based on the decomposition of the entire signal, the greater the difference in noise between a certain sonar signal segment and the surrounding sonar signal segments, the more difficult it is to effectively decompose the sonar signal segment, and the noise will be more prevalent in each of its sonar signal component segments. Therefore, by comparing the differences between multiple sonar signal component segments in a local range, the natural noise changes of the sonar signal component segments can be obtained. Combined with the noise factor of the sonar signal component segment, the natural noise content of the sonar signal component segment can be obtained. Further combined with the corresponding rotation speed, the sonar signal component segment can be given an adaptive wavelet threshold for denoising.

[0043] The denoised sonar signal is obtained by filtering and denoising each sonar signal component segment and recombining the denoised sonar signal component segments. After obtaining the denoised sonar signal, the received sonar signal can be accurately identified, and then the reception time of the sonar signal can be accurately obtained. The distance between the dredging vessel and the riverbed can be obtained through the time difference between the transmission time and the reception time of the sonar signal combined with the speed of sound wave propagation in water. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0045] Figure 1 This is a structural block diagram of an integrated equipment for river channel dredging and sediment treatment of the present invention;

[0046] Figure 2 Schematic diagram of the target segment and the comparison segment. DETAILED DESCRIPTION

[0047] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, features and effects of a water conservancy river channel dredging and sediment treatment integrated equipment proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0048] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0049] The specific scheme of the integrated equipment for desilting and treating sediment in a water conservancy river provided by the present invention is described in detail below with reference to the accompanying drawings.

[0050] See also Figure 1 , which shows a structural block diagram of a water conservancy river channel dredging and sediment treatment integrated equipment provided by an embodiment of the present invention, the equipment includes the following modules:

[0051] The data acquisition module 101 is used to obtain the sonar signal and the bucket wheel rotation speed, and decompose the sonar signal to obtain a plurality of sonar signal components.

[0052] It should be noted that the specific process of clearing river silt is that the dredging ship first extends the bucket wheel into the bottom of the river channel and uses the bucket wheel to clear the silt. In order to prevent the bucket wheel from descending too deep and damaging the riverbed during the process of clearing river silt, the dredging ship needs to grasp the distance between the dredging ship and the riverbed in real time during the dredging process, that is, it is necessary to collect sonar signals through the sonar system.

[0053] It should be further explained that the sonar signal received by the sonar system will be interfered by noise, resulting in the sonar signal containing sonar components and noise components, making it impossible to accurately obtain the distance between the dredging ship and the river channel, so the sonar signal needs to be denoised; and the traditional EMD decomposition of the sonar signal is to only denoise the high-frequency component, but the noise component in the sonar signal includes the noise of the natural environment and the noise generated when the bucket wheel is working, which are recorded as natural noise and mechanical noise respectively, so that the EMD decomposition cannot effectively distinguish the sonar component from the noise component, resulting in a large amount of noise in each component of the sonar signal, that is, the traditional method of only denoising the high-frequency component cannot effectively remove the noise in the sonar signal. Therefore, this embodiment analyzes the noise content contained in each component and denoises each component, thereby improving the quality of the sonar signal.

[0054] Specifically, a sonar system installed in the dredging ship is used to collect sonar signals in the river channel in real time, and a speed sensor is installed on the driving shaft of the bucket wheel of the dredging ship to collect the bucket wheel speed in real time;

[0055] Furthermore, the sonar signal is subjected to EMD decomposition to obtain all sonar signal components of the sonar signal. Since EMD decomposition is a well-known prior art, it will not be described in detail in this embodiment.

[0056] The independent signal analysis module 102 is used to divide the sonar signal component and the sonar signal into a plurality of sonar signal component segments and sonar signal segments; obtain the sonar characteristics of the sonar signal component segment according to the periodicity and energy of the sonar signal component segment; obtain the confidence of the sonar signal segment according to the sonar characteristics of the sonar signal component segment corresponding to the sonar signal segment; obtain the noise factor of the sonar signal component segment according to the confidence of the sonar signal segment and the sonar characteristics of the corresponding sonar signal component segment.

[0057] It should be noted that the environment in the local range of the riverbed bottom is similar, so the sonar components in the sonar signal in the local range are similar, and this can be used as a basis for obtaining the sonar components in the sonar signal; therefore, this embodiment segments the sonar signal to facilitate the subsequent quantification of the sonar components in the sonar signal through the differences between different sonar signal segments. Since the noise component content in different sonar signal segments is different, in order to avoid inaccurate results caused by different noise component content when calculating the difference, the noise component content in the sonar signal segment, that is, the confidence of the sonar signal segment, is required.

[0058] It should be further explained that the less the noise component content in the sonar signal segment, the more the EMD decomposition can distinguish the noise component and the sonar component in the sonar signal segment; that is, the sonar signal features in the sonar signal component segment of the sonar signal segment will be more concentrated in one sonar signal component segment, and the sonar signal features have the characteristics of good periodicity and high energy, so this can be used as a basis to obtain the noise component content in the sonar signal segment, that is, the confidence of the sonar signal segment.

[0059] Preferably, in one embodiment of the present invention, a sonar signal segment length is preset , The specific value of can be set according to the actual situation, and this embodiment does not limit it. seconds to describe; the sonar signal and the sonar signal component are divided into several lengths of The sonar signal segment and sonar signal component segment; in particular, if the length of the last segment of the sonar signal (sonar signal component) is less than , then the actual signal segment is used to obtain the sonar signal segment (sonar signal component segment).

[0060] Further, the Hilbert transform is used to obtain the period in each sonar signal component segment and the instantaneous frequency of each data point in all sonar signal component segments;

[0061] For any sonar signal component segment, the maximum sonar feature of the sonar signal component segment is obtained according to the amplitude of the period in the sonar signal component segment and the amplitude of all maximum points in the sonar signal component segment. The specific calculation formula is:

[0062]

[0063] In the formula, Indicates the maximum sonar feature of the sonar signal component segment; Indicates the first component of the sonar signal The amplitude of the maximum point; Represents the mean value of the amplitude of all maximum points in the sonar signal component segment; Indicates the number of maximum points in the sonar signal component segment; Indicates the first component of the sonar signal The mean of the amplitude difference (absolute value of the difference) between a maximum point and the adjacent maximum points; Indicates the number of cycles in the sonar signal component segment; Indicates the first component of the sonar signal The amplitude of the cycle; represents an exponential function with a natural constant as the base. In this embodiment, Model to present inverse proportional relationship and normalization, As the input of the model, the implementer can set the inverse proportional function and normalization function according to the actual situation; Represents a linear normalization function, and the normalized object is all sonar signal component segments .

[0064] It should be noted that It represents the standard deviation of the amplitude of the maximum point in the sonar signal component segment, which can only show the degree of disorder of the overall distribution of the maximum point in the sonar signal component segment, but ignores the degree of local disorder; It represents the local disorder degree of the maximum value itself. When the difference between a certain maximum value and the adjacent maximum value is extremely large, it means that the maximum value is more disordered locally. Therefore, when calculating the disorder degree of the overall distribution of the maximum value points in the sonar signal component segment, the local disorder degree of the maximum value itself is used as the weight, and the formula is expressed as ,therefore The larger the value of , the more chaotic the distribution of the maximum values ​​in the sonar signal component segment, and the lower the degree of chaos, the better the periodicity. It indicates the periodicity of the sonar signal component segment obtained through the maximum value; and It represents the first The energy of a cycle. The better the periodicity of the sonar signal component segment and the higher the energy, the less noise components there are in the sonar signal component segment and the more sonar features it contains.

[0065] Similarly, the minimum sonar feature of the sonar signal component segment is obtained, and the average of the maximum sonar feature of the sonar signal component segment and the minimum sonar feature of the sonar signal component segment is used as the sonar feature of the sonar signal component segment.

[0066] It should be noted that, when the sonar signal segment is more seriously interfered by noise, the EMD decomposition is more difficult to separate the sonar component and the noise component in the sonar signal segment, that is, in the sonar signal component segment corresponding to the sonar signal segment, its sonar characteristics will not be concentrated in one sonar signal component segment, but will be concentrated in one sonar signal component segment. Therefore, the confidence of the sonar signal segment can be obtained based on this. The greater the confidence of the sonar signal segment, the less the noise component in the sonar signal segment.

[0067] Preferably, in one embodiment of the present invention, for any sonar signal segment, among the sonar signal component segments corresponding to the sonar signal segment, the sonar signal component segment with the largest sonar feature is recorded as the reference component segment; the average of the differences in sonar features between the reference component segment and all the sonar signal component segments corresponding to the sonar signal segment is taken as the confidence of the sonar signal segment, and the specific calculation formula is:

[0068]

[0069] In the formula, Indicates the confidence level of the sonar signal segment; Indicates the number of sonar signal component segments corresponding to the sonar signal segment; A sonar signal component segment representing a reference component segment; Indicates the sonar signal segment corresponding to Sonar characteristics of each sonar signal component segment.

[0070] It should be noted that The larger the value of , the more the sonar feature in the sonar signal component segment corresponding to the sonar signal segment appears in a sonar signal component segment, that is, the less the sonar signal segment is affected by noise, and the more credible the sonar signal segment is.

[0071] It should be further explained that, when the confidence of the sonar signal segment is greater, the sonar signal segment can more easily distinguish the sonar component from the noise component through EMD decomposition, that is, the sonar features in the sonar signal component segment of the sonar signal segment are more credible, so the noise factor of the sonar signal component segment can be obtained based on this.

[0072] Preferably, in one embodiment of the present invention, the difference between 1 and the sonar feature of the sonar signal component segment is multiplied by the confidence of the sonar signal segment corresponding to the sonar signal component segment, and the obtained product is used as the noise factor of the sonar signal component segment, and the specific calculation formula is:

[0073]

[0074] In the formula, Represents the noise factor of the sonar signal component segment; Represents the sonar characteristics of the sonar signal component segment; Indicates the confidence level of the sonar signal segment corresponding to the sonar signal component segment.

[0075] It should be noted that the greater the confidence of the sonar signal segment corresponding to the sonar signal component segment, the more credible the sonar feature of the sonar signal component segment is, and the lower the sonar feature of the sonar signal component segment, the more noise components are contained in the sonar signal component segment, that is, The larger the value is, the more noise components are contained in the sonar signal component segment.

[0076] So far, the noise factor of the sonar signal component segment is obtained through the above method.

[0077] The local signal analysis module 103 is used to obtain a comparison segment and a target segment, where the target segment and the comparison segment are sonar signal component segments; obtain a characteristic difference between the comparison segment and the target segment based on the difference between the comparison segment and the target segment in instantaneous frequency and bucket wheel speed; and obtain a natural noise change of the target segment based on the characteristic difference between the comparison segment and the target segment, the time series distance, and the confidence of the sonar signal segment corresponding to the comparison segment.

[0078] It should be noted that since the dredging process of the dredging ship is continuous, that is, the river channel positions cleared by the dredging ship in adjacent time periods are adjacent, and the environmental conditions at adjacent positions in the river channel are similar, therefore, within a certain time range, a certain sonar signal segment is similar to the other sonar signal segments. If the similarity is low, it means that the difference between the noise received by the sonar signal segment and the noise received by the other sonar signal segments is large, and since the EMD decomposition is based on the overall signal, the greater the difference in noise between a certain sonar signal segment and the surrounding sonar signal segments, the more difficult it is for the sonar signal segment to be effectively decomposed, and the noise will be more prevalent in each of its sonar signal component segments. Therefore, it is also necessary to denoise each sonar signal component segment according to the difference between each sonar signal component segment and the surrounding sonar signal component segments to improve the theoretical basis.

[0079] It should be further explained that, since the instantaneous frequency at each moment in the sonar signal component segment can accurately reflect the frequency change of the signal at each moment, and further reflect the characteristics of the sonar signal fluctuation over time, the same instantaneous frequency can more accurately obtain the difference between the sonar signal component segments. Therefore, this embodiment quantifies the difference between the sonar signal component segments by the difference in the instantaneous frequency of each sonar signal segment and the surrounding sonar signal segments corresponding to the sonar signal component segment.

[0080] Preferably, in one embodiment of the present invention, a local segment number is preset , The specific value of can be set according to the actual situation. This embodiment does not make a hard requirement. =4 to narrate;

[0081] For any sonar signal segment, sonar signal segments are recorded as local signal segments; all sonar signal component segments corresponding to the sonar signal segments are recorded as target segments, and all sonar signal component segments corresponding to all local signal segments are recorded as local signal component segments; it is particularly noted that if there is no sonar signal segment before sonar signal segment, then the closest Sonar signal segments are recorded as local signal segments.

[0082] For any target segment, the local signal component segment with the same IMF component number as the target segment is recorded as the comparison segment; Figure 2 As shown, Figure 2 Schematic diagram of the target segment and the comparison segment.

[0083] For any target segment, the instantaneous frequency of each data point in the comparison segment and the target segment is obtained by using Hilbert transform, and the instantaneous frequency sequence of each comparison segment and the instantaneous frequency sequence of the target segment are obtained. Since Hilbert transform is a well-known prior art, it will not be described in detail in this embodiment.

[0084] For any comparison segment, the DTW algorithm is used to match the instantaneous frequency sequence of the comparison segment with the instantaneous frequency sequence of the target segment to obtain a number of instantaneous frequency pairs. Since the DTW algorithm is a well-known prior art, it will not be described in detail in this embodiment. According to the instantaneous frequency in the instantaneous frequency pair and the bucket wheel speed corresponding to each instantaneous frequency in the instantaneous frequency pair, the characteristic difference between the comparison segment and the target segment is obtained. The specific calculation formula is:

[0085]

[0086] In the formula, Indicates the feature difference between the comparison segment and the target segment; represents the number of instantaneous frequency pairs; Indicates The first instantaneous frequency in a pair of instantaneous frequencies; Indicates The second instantaneous frequency in a pair of instantaneous frequencies; Indicates The bucket wheel speed corresponding to the first instantaneous frequency among the instantaneous frequencies; Indicates The bucket wheel speed corresponding to the second instantaneous frequency among the first instantaneous frequency; It represents the absolute value function; Represents a linear normalization function, whose normalization object is the relationship between all comparison segments of all target segments and their corresponding target segments. It is particularly noted that if the two sequences in the instantaneous frequency pair match a one-to-many instantaneous frequency match, the mean of the multiple instantaneous frequencies is calculated in the above calculation for processing.

[0087] It should be noted that the characteristic difference between the comparison segment and the target segment is the difference between different sonar signal component segments after eliminating the interference of mechanical noise; The smaller the value of is, the more similar the mechanical noise generated by the bucket wheel at the two moments is, that is, the less likely the signal difference at the two moments is caused by mechanical noise. The larger the value of , the greater the difference between different sonar signal component segments after eliminating the interference of mechanical noise.

[0088] It should be further explained that, since the closer the time distances of different sonar signal segments are, the more similar the sonar components in the corresponding sonar signal component segments are, after excluding the interference of mechanical noise, the greater the difference between the sonar signal component segment and the surrounding sonar signal component segments, the greater the difference in natural noise between the sonar signal component segment and the surrounding sonar signal component segments. Further combined with the confidence of the sonar signal segment corresponding to the sonar signal component segment, the natural noise change between the sonar signal component segment and the surrounding sonar signal component segments can be obtained.

[0089] Preferably, in one embodiment of the present invention, the natural noise variation of the target segment is obtained according to the confidence of the sonar signal segments corresponding to all the comparison segments, the time sequence distance between all the comparison segments and the target segment, and the characteristic difference between all the comparison segments and the target segment. The specific calculation formula is:

[0090]

[0091] In the formula, represents the natural noise variation of the target segment; Indicates the number of contrast segments; Indicates The confidence level of the sonar signal segment corresponding to the comparison segment; Indicates the maximum confidence in the sonar signal segment corresponding to all comparison segments; Indicates The temporal distance between the comparison segment and the target segment; Indicates the minimum distance between all comparison segments and the target segment in time series; Indicates The feature differences between the comparison segment and the target segment.

[0092] It should be noted that the natural noise change between the target segment and all the comparison segments represents the natural noise change between the target segment and all the comparison segments after excluding mechanical interference; The larger the value is, the more The greater the difference between the comparison segment and the target segment; The larger the value, the The closer the temporal distance between the comparison segment and the target segment is, the The more similar the sonar components are between the comparison segment and the target segment; The larger the value, the The less the noise component in the sonar signal segment corresponding to the first comparison segment, The more credible the comparison segment is, the more The bigger and The larger the value of , the greater the natural noise variation of the target segment.

[0093] The signal denoising module 104 is used to obtain the natural noise content of the sonar signal component segment according to the natural noise change and noise factor of the sonar signal component segment, and denoise the sonar signal segment in combination with the corresponding bucket wheel speed to obtain a denoised sonar signal; the riverbed position is determined through the denoised sonar signal, and the descent depth of the bucket wheel of the dredging ship is set to clean the silt at the bottom of the river.

[0094] It should be noted that this embodiment is an integrated equipment for dredging and sediment treatment of water conservancy rivers. Specifically, by removing the noise in the sonar signal, the dredging ship can accurately obtain the information of the river bottom, thereby avoiding the dredging ship from damaging the riverbed during dredging. After obtaining the noise factor of the sonar signal component segment and the difference in natural noise between the sonar signal component segments through the independent signal analysis module 102 and the local signal analysis module 103, the natural noise content of the sonar signal component segment can be obtained; further combined with the bucket wheel speed in the corresponding time period of the sonar signal component segment, that is, mechanical noise, the noise level in the sonar signal component segment is obtained, and denoising is performed on the sonar signal component segment, and finally all sonar signal segments are reorganized to obtain the denoised sonar signal.

[0095] Preferably, in one embodiment of the present invention, for any sonar signal component segment, the product of the noise factor of the sonar signal component segment and the natural noise change of the sonar signal component segment is normalized, and the normalized result is used as the natural noise content of the sonar signal component segment, and the specific calculation formula is:

[0096]

[0097] In the formula, Indicates the natural noise content of the sonar signal component segment, Represents the noise factor of the sonar signal component segment; Indicates the natural noise variation of the sonar signal component segment; Represents a linear normalization function, whose normalization object is all sonar signal component segments .

[0098] It should be further explained that the sonar signal component segment contains not only natural noise but also mechanical noise, and the mechanical noise is generated by the rotation of the bucket wheel. Therefore, the mechanical noise in the sonar signal component segment can be quantified by the bucket wheel speed in the time period corresponding to the sonar signal component segment. The wavelet threshold of the sonar signal component segment can be set in combination with the natural noise in the sonar signal component segment to denoise the sonar signal component segment.

[0099] Preferably, in one embodiment of the present invention, an initial wavelet threshold is preset , The specific value of can be set according to the actual situation. This embodiment does not make a hard requirement. to give a narrative;

[0100] For any sonar signal component segment, the wavelet threshold of the sonar signal component segment is obtained according to the natural noise content of the sonar signal component segment, the average value of the bucket wheel speed in the time period corresponding to the sonar signal component segment, and the initial wavelet threshold. The specific calculation formula is:

[0101]

[0102] In the formula, A wavelet threshold representing a component segment of the sonar signal; Represents the preset initial wavelet threshold; Indicates the natural noise content of the sonar signal component segment; It represents the average value of bucket wheel speed in the time period corresponding to the sonar signal component segment; Represents a linear normalization function, and its normalization object is the mean value of the bucket wheel speed in the corresponding time period of all sonar signal component segments.

[0103] It should be noted that when the natural noise and mechanical noise in the sonar signal component segment are larger, a larger wavelet threshold should be assigned to the sonar signal component segment for denoising to remove the noise component in the sonar signal component segment. After the wavelet thresholds of all sonar signal component segments are obtained, denoising can be performed for all sonar signal component segments.

[0104] Preferably, in one embodiment of the present invention, a wavelet threshold filtering algorithm is used to filter and denoise each sonar signal component segment according to the wavelet threshold of each sonar signal component segment, and the denoised sonar signal component segment is reconstructed to obtain a denoised sonar signal segment; and all denoised sonar signal segments are recombined to obtain a denoised sonar signal.

[0105] It should be further explained that after obtaining the denoised sonar signal, the received sonar signal can be accurately identified, and then the reception time of the sonar signal can be accurately obtained. The distance between the dredging ship and the riverbed can be obtained by the time difference between the transmission time and the reception time of the sonar signal, combined with the speed of sound wave propagation in water.

[0106] Furthermore, when the dredging ship is clearing the silt in the river channel, the maximum descending depth of the bucket wheel of the dredging ship shall not be greater than the distance between the dredging ship and the riverbed, so as to avoid the dredging ship from damaging the riverbed.

[0107] It should be noted that the distance between the dredging vessel and the riverbed is obtained by using the time difference between the emission time and the reception time of the sonar signal combined with the speed of sound waves propagating in water. This is a well-known prior art and will not be described in detail in this embodiment.

[0108] At this point, this embodiment is completed.

[0109] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An integrated equipment for dredging and treating sediment in a water conservancy river, characterized in that: The device includes the following modules: A data acquisition module is used to obtain the sonar signal and the bucket wheel speed, decompose the sonar signal, and obtain several sonar signal components; The independent signal analysis module is used to divide the sonar signal component and the sonar signal into a plurality of sonar signal component segments and sonar signal segments; obtain the sonar characteristics of the sonar signal component segment according to the periodicity and energy of the sonar signal component segment; obtain the confidence of the sonar signal segment according to the sonar characteristics of the sonar signal component segment corresponding to the sonar signal segment; obtain the noise factor of the sonar signal component segment according to the confidence of the sonar signal segment and the sonar characteristics of the corresponding sonar signal component segment; The method for obtaining the sonar feature of the sonar signal component segment is as follows: for any sonar signal component segment, according to the amplitude of the period in the sonar signal component segment and the amplitude of all the maximum points in the sonar signal component segment, obtain the maximum sonar feature of the sonar signal component segment; obtain the minimum sonar feature of the sonar signal component segment, and take the average of the maximum sonar feature of the sonar signal component segment and the minimum sonar feature of the sonar signal component segment as the sonar feature of the sonar signal component segment; The local signal analysis module is used to obtain the comparison segment and the target segment, wherein the target segment and the comparison segment are sonar signal component segments; obtain the characteristic difference between the comparison segment and the target segment according to the difference between the comparison segment and the target segment in instantaneous frequency and bucket wheel speed; obtain the natural noise change of the target segment according to the characteristic difference between the comparison segment and the target segment, the time sequence distance and the confidence of the sonar signal segment corresponding to the comparison segment; The signal denoising module is used to obtain the natural noise content of the sonar signal component segment according to the natural noise change and noise factor of the sonar signal component segment, and denoise the sonar signal segment in combination with the corresponding bucket wheel speed to obtain a denoised sonar signal; the riverbed position is determined through the denoised sonar signal, and the descent depth of the dredging ship bucket wheel is set to clean the silt at the bottom of the river.

2. The integrated equipment for river channel dredging and sediment treatment according to claim 1, characterized in that: The specific method of dividing the sonar signal components and the sonar signal into a plurality of sonar signal component segments and sonar signal segments includes: Preset a sonar signal segment length , split the sonar signal and the sonar signal component into several lengths Sonar signal segments and sonar signal component segments.

3. The integrated equipment for river channel dredging and sediment treatment according to claim 1, characterized in that: The specific method of obtaining the sonar features of the sonar signal component segments includes: The Hilbert transform is used to obtain the period in each sonar signal component segment and the instantaneous frequency of each data point in all sonar signal component segments; The specific calculation formula of the maximum sonar feature of the sonar signal component segment is: In the formula, Indicates the maximum sonar feature of the sonar signal component segment; Indicates the first component of the sonar signal The amplitude of the maximum point; Represents the mean value of the amplitude of all maximum points in the sonar signal component segment; Indicates the number of maximum points in the sonar signal component segment; Indicates the first component of the sonar signal The mean of the amplitude difference between a maximum point and its adjacent maximum points; Indicates the number of cycles in the sonar signal component segment; Indicates the first component of the sonar signal The amplitude of the cycle; represents an exponential function with a natural constant as base; represents the linear normalization function.

4. The integrated equipment for desilting and treating sediment in a water conservancy river according to claim 1, characterized in that: The specific method of obtaining the confidence of the sonar signal segment includes: For any sonar signal segment, the sonar signal component segment with the largest sonar feature among the sonar signal component segments corresponding to the sonar signal segment is recorded as the reference component segment; the average of the differences in sonar features between the reference component segment and all the sonar signal component segments corresponding to the sonar signal segment is taken as the confidence of the sonar signal segment.

5. The integrated equipment for river channel dredging and sediment treatment according to claim 1, characterized in that: The specific method of obtaining the noise factor of the sonar signal component segment includes: For any sonar signal component segment, the difference between 1 and the sonar feature of the sonar signal component segment is multiplied by the confidence of the sonar signal segment corresponding to the sonar signal component segment, and the obtained product is used as the noise factor of the sonar signal component segment.

6. The integrated equipment for desilting and treating sediment in a water conservancy river according to claim 1, characterized in that: The specific method of obtaining the comparison segment and the target segment includes: Preset a local segment number For any sonar signal segment, replace the sonar signal segments, recorded as local signal segments; all sonar signal component segments corresponding to the sonar signal segments are recorded as target segments, and all sonar signal component segments corresponding to all local signal segments are recorded as local signal component segments; For any target segment, the local signal component segment with the same IMF component sequence number as the target segment is recorded as the comparison segment.

7. The integrated equipment for desilting and treating sediment in a water conservancy river according to claim 1, characterized in that: The specific method of obtaining the feature difference between the comparison segment and the target segment includes: For any target segment, the instantaneous frequency of each data point in the comparison segment and the target segment is obtained by using Hilbert transform, and the instantaneous frequency sequence of each comparison segment and the instantaneous frequency sequence of the target segment are obtained; For any comparison segment, the DTW algorithm is used to match the instantaneous frequency sequence of the comparison segment with the instantaneous frequency sequence of the target segment to obtain several instantaneous frequency pairs; according to the instantaneous frequency in the instantaneous frequency pair and the bucket wheel speed corresponding to each instantaneous frequency in the instantaneous frequency pair, the characteristic difference between the comparison segment and the target segment is obtained. The specific calculation formula is: In the formula, Indicates the feature difference between the comparison segment and the target segment; represents the number of instantaneous frequency pairs; Indicates The first instantaneous frequency in a pair of instantaneous frequencies; Indicates The second instantaneous frequency in a pair of instantaneous frequencies; Indicates The bucket wheel speed corresponding to the first instantaneous frequency among the instantaneous frequencies; Indicates The bucket wheel speed corresponding to the second instantaneous frequency among the first instantaneous frequency; It represents the absolute value function; represents the linear normalization function.

8. The integrated equipment for desilting and treating sediment in a water conservancy river according to claim 1, characterized in that: The specific method of obtaining the natural noise variation of the target segment includes: For any target segment, the natural noise change of the target segment is obtained according to the confidence of the sonar signal segments corresponding to all comparison segments, the time series distance between all comparison segments and the target segment, and the feature difference between all comparison segments and the target segment. The specific calculation formula is: In the formula, represents the natural noise variation of the target segment; Indicates the number of contrast segments; Indicates The confidence level of the sonar signal segment corresponding to the comparison segment; Indicates the maximum confidence in the sonar signal segment corresponding to all comparison segments; Indicates The temporal distance between the comparison segment and the target segment; Indicates the minimum distance between all comparison segments and the target segment in time series; Indicates The feature differences between the comparison segment and the target segment.

9. The integrated equipment for river channel dredging and sediment treatment according to claim 1, characterized in that: The specific method of obtaining the natural noise content of the sonar signal component segment includes: For any sonar signal component segment, the product of the noise factor of the sonar signal component segment and the natural noise change of the sonar signal component segment is normalized, and the normalized result is used as the natural noise content of the sonar signal component segment.

10. The integrated equipment for desilting and treating sediment in a water conservancy river according to claim 1, characterized in that: The denoising of the sonar signal segment includes the following specific methods: Preset an initial wavelet threshold For any sonar signal component segment, the wavelet threshold of the sonar signal component segment is obtained according to the natural noise content of the sonar signal component segment and the average value of the bucket wheel speed in the time period corresponding to the sonar signal component segment, combined with the initial wavelet threshold. The specific calculation formula is: In the formula, A wavelet threshold representing a component segment of the sonar signal; Represents the preset initial wavelet threshold; Indicates the natural noise content of the sonar signal component segment; It represents the average value of bucket wheel speed in the time period corresponding to the sonar signal component segment; represents the linear normalization function; The wavelet threshold filtering algorithm is used to filter and denoise each sonar signal component segment according to the wavelet threshold of each sonar signal component segment, and the denoised sonar signal component segment is reconstructed to obtain the denoised sonar signal segment.

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