Trench bottom rapid generation method fusing terrain trend and engineering constraint
By using wavelet transform and engineering constraints, channel topographic data is decomposed into low-frequency trend and high-frequency fluctuation terms, optimizing the channel bottom design and solving the problems of inaccuracy and insufficient adaptability of traditional channel design, thus achieving efficient and accurate channel bottom generation.
Patent Information
- Application Number
- CN202511424620.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-30
- Publication Date
- 2026-01-23
AI Technical Summary
Traditional channel design relies on human experience, resulting in redundant and inaccurate designs that are difficult to adapt to complex terrains and lack micro-control, thus affecting the accuracy and economy of channel design.
The terrain data is decomposed using wavelet transform. Combined with engineering constraints, the boundary effects are eliminated through standardization and mirror continuation. The data is decomposed into low-frequency trend terms and high-frequency fluctuation terms. The low-frequency terms are optimized and the high-frequency fluctuations are compressed to generate the final canal bottom elevation.
It enables adaptive analysis of complex terrain, improves the accuracy and efficiency of canal bottom design, overcomes the limitations of human experience, and enhances project quality.
Smart Images
Figure CN121389437A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of water conservancy and signal processing, in particular to a method for quickly generating a channel bottom by fusing terrain trends and engineering constraints. BACKGROUND
[0002] As the core water conservancy infrastructure connecting water sources and water use areas, the diversion channel is a key engineering carrier for realizing water resource allocation across regions, ensuring agricultural irrigation, industrial water use and urban and rural water supply. The effective functioning of the channel highly depends on scientific and reasonable design, especially the design of the channel bottom elevation, which directly determines the smoothness of water flow, water delivery efficiency and engineering construction cost, and also deeply affects the stability of the channel slope and the surrounding ecological environment. Under the background of increasingly prominent water resource supply and demand contradiction and continuously increasing requirements for ecological environment protection in engineering construction, the precision and economy of the channel bottom design have become the core indicators for measuring the quality of the diversion project.
[0003] The current channel bottom design mainly relies on the experience-based design of engineers according to industry specification manuals, which has three major defects: the distortion of simplified assumptions in the specification manual: the simplified formula in the design manual ignores the nonlinear change of the terrain, resulting in widespread design redundancy; strong subjectivity of manual interpretation: engineers need to visually divide the terrain paragraphs based on experience, and the consistency is poor; lack of quantitative control: the specification only provides slope range recommendations, but does not provide micro-relief control methods, resulting in excessive channel bottom slope fluctuations. Such methods can meet the basic needs in simple terrain and small-scale engineering scenarios, but their limitations are increasingly evident in long-distance water delivery and complex terrain conditions.
[0004] In view of the strong subjectivity and insufficient adaptability of the traditional experience-based design method and the efficiency bottleneck of the numerical simulation method, the present application proposes a method for quickly generating a channel bottom by fusing terrain trends and engineering constraints. The method performs multi-scale decomposition of the terrain data through wavelet transform, converts the traditional "experience-dominated segmented adjustment" mode into a systematic process of "signal processing (wavelet decomposition) → macro control (trend design) → micro optimization (fluctuation correction)", realizes adaptive analysis and efficient design of complex terrain, and especially in long-distance and complex terrain conditions, can significantly improve the precision and economy of the channel bottom design, and break through the technical bottleneck of relying on manual experience. SUMMARY
[0005] To achieve the above-mentioned purpose, the present application provides the following technical solutions: According to the first aspect of the present application, a method for quickly generating a channel bottom by fusing terrain trends and engineering constraints is claimed, comprising the following steps: S1, analyzing terrain data, standardizing channel stake number sequence data to obtain an original channel bottom elevation sequence of the channel; S2, the mirror image continuation method is used to expand the boundary of the original channel bottom height sequence, so as to eliminate the boundary effect of wavelet transform; S3, selecting a suitable wavelet base function and decomposition scale, the original channel bottom height sequence is decomposed into a low-frequency trend item and a high-frequency fluctuation item; S4, based on the low-frequency trend item obtained by decomposition, the engineering requirements of channel design are optimized to obtain a trend item; S5, the high-frequency fluctuation item is processed by using filter average value, and the high-frequency fluctuation item is compressed by soft threshold value; S6, the optimized trend item and the corrected fluctuation item are superimposed, and the final design channel bottom elevation is output.
[0006] Further, in the step S1, the standardization processing is performed on the stake number sequence, the channel stake number sequence data is rearranged according to the preset fixed step length by linear interpolation, and a continuous and uniform original channel bottom height sequence is formed.
[0007] Further, the mirror image continuation method of the step S2 is a boundary expansion method, the first and last boundaries of the original channel bottom height sequence are regularly expanded, the sequence length is lengthened, the signal change at the boundary is smooth, the local characteristics of the "infinite sequence" are simulated, and the distortion of wavelet transform in the boundary area is reduced.
[0008] Further, the mirror image continuation method of the step S2 further comprises: S21, obtaining the original channel bottom height sequence to be processed, denoted as sequence X, and the length is L; S22, determining the expansion length n, based on the characteristics of the channel height sequence, adjusting n to L / 2 and taking the integer part downward; S23, expanding the boundary, taking the first or last endpoint of the sequence X as the symmetry axis, extracting n data after the first or last endpoint from the sequence X, arranging the n data in reverse order to form a front or rear end expansion subsequence, and splicing the subsequence to the front or rear end of the sequence X; S24, outputting the complete expansion sequence formed after the front end expansion and the rear end expansion, and the complete expansion sequence is used for subsequent wavelet transform.
[0009] Further, the step S3 further comprises: S31, the wavelet base function is selected as Db4 or Sym5; S32, the number of decomposition layers n is calculated according to the formula:
[0010] Wherein, is the length of the expanded sequence. The step S3 low frequency trend item, reflecting the overall change trend of the channel along the terrain, including the overall slope, regional terrain trend, is the basic framework of the design of the channel bottom; Further, the step S3 high frequency fluctuation item, reflecting the local terrain of the fine fluctuations, including small range of concave-convex, local obstacles caused by elevation change of terrain details characteristics; The step S4, further comprising: S41, constraint slope, according to the channel's water carrying capacity, anti-scour requirements, set the maximum allowable slope and minimum slope range; S42, reference along the soil bearing capacity, rock distribution geological data, the trend of the elevation of the item involved in the poor geological section is corrected.
[0011] Further, the step S5, further comprising: S51, the absolute average value of the fluctuation item sequence The calculation formula is as follows:
[0012] Wherein, The absolute average value of the high frequency fluctuation item; The length of the high frequency fluctuation sequence; The original high frequency fluctuation item data; S52, the fluctuation item is compressed by soft threshold, the calculation formula is as follows:
[0013] Wherein, The processed high frequency fluctuation item; The step S6 synthesis process, the final design of the channel bottom elevation calculation formula is as follows:
[0014] Wherein, The final design of the channel bottom elevation at k stake number; The optimized low frequency trend item at k stake number; The processed high frequency fluctuation item at k stake number; Further, the standardization processing, using linear difference method to process the stake number, the calculation formula is as follows:
[0015] Wherein, The original channel bottom elevation at j stake number, , The original channel bottom elevation of the first and last of the monotonic region respectively, a, b is the first and last stake number of the monotonic region; Further, the wavelet transform, the calculation formula is as follows:
[0016] wherein: is a scale factor, controlling the width and position of the wavelet function. By changing the scale factor , the wavelet window can analyze the signal at different scales (frequencies) respectively; is a translation factor, determining the time position of the analysis, and the double-parameter control mechanism gives the wavelet transform unique time-frequency analysis characteristics; The corresponding scaling and translation wavelet basis function is as follows:
[0017] Further, the optimization of the low-frequency trend item should refer to the following influencing factors: Water level requirement, geological condition, sediment content of water source, size of channel design flow, and combined with local irrigation management experience, select appropriate channel gradient.
[0018] The application belongs to the technical field of water conservancy engineering and signal processing, and discloses a channel bottom rapid generation method fusing terrain trend and engineering constraint. The method aims to solve the problems that the traditional channel design relies on artificial experience and is difficult to accurately adapt to complex terrain changes; the original channel bottom elevation data is standardized pretreated; the mirror extension method is adopted to expand the boundary to suppress the boundary effect of wavelet transform; appropriate wavelet basis function and decomposition scale are selected, and the channel bottom elevation sequence is decomposed into low-frequency component reflecting overall terrain trend and high-frequency component reflecting local fluctuation; then, the low-frequency trend is optimized according to engineering requirements, and the high-frequency fluctuation is compressed by a soft threshold to smooth the slight fluctuation; finally, the processed trend item and fluctuation item are reconstructed to generate the final channel bottom elevation design result meeting the engineering practice. The application realizes multi-scale adaptive analysis of terrain data, and significantly improves the precision and efficiency of channel bottom design. BRIEF DESCRIPTION OF DRAWINGS
[0019] Figure 1 The workflow diagram of the channel bottom rapid generation method fusing terrain trend and engineering constraint which is claimed by the embodiments of the application; Figure 2 The second workflow diagram of the channel bottom rapid generation method fusing terrain trend and engineering constraint which is claimed by the embodiments of the application; Figure 3 The effect schematic diagram before and after the boundary extension processing of the channel bottom rapid generation method fusing terrain trend and engineering constraint which is claimed by the embodiments of the application; Figure 4 The multi-scale decomposition schematic diagram of the elevation data of the channel bottom rapid generation method fusing terrain trend and engineering constraint which is claimed by the embodiments of the application; Figure 5 A channel design channel bottom calculation result schematic diagram of a method for quickly generating a channel bottom by fusing terrain trends and engineering constraints. DETAILED DESCRIPTION
[0020] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the scope of protection of the present application.
[0021] The terms "first", "second", "third" in the present application are only for descriptive purpose, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second", "third" can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "a plurality of" is at least two, for example, two, three, etc., unless otherwise explicitly and specifically limited. All directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present application are only used to explain the relative position relationship, movement condition, etc. between components in a certain posture (as shown in the drawings), and if the certain posture changes, the directional indications also change accordingly. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units is not limited to the listed steps or units, but can optionally include steps or units not listed, or can optionally include other steps or units inherent to the process, method, product or device.
[0022] In this document, reference to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are they necessarily mutually exclusive of one another. A person of ordinary skill in the art will understand that the embodiments described herein can be combined with other embodiments.
[0023] According to a first embodiment of the present application, the present application claims a method for quickly generating a channel bottom by fusing terrain trends and engineering constraints, referring to Figure 1 , comprising the following steps: S1, analyzing terrain data, standardizing channel stake number sequence data, and obtaining an original channel bottom height sequence of the channel; S2, the mirror image continuation method is used to expand the boundary of the original channel bottom height sequence, so as to eliminate the boundary effect of wavelet transform; S3, selecting a suitable wavelet base function and decomposition scale, the original channel bottom height sequence is decomposed into a low-frequency trend item and a high-frequency fluctuation item; S4, based on the low-frequency trend item obtained by decomposition, the engineering requirements of channel design are optimized to obtain a trend item; S5, the high-frequency fluctuation item is processed by using filter average value, and the high-frequency fluctuation item is compressed by soft threshold value; S6, the optimized trend item and the corrected fluctuation item are superimposed, and the final design channel bottom elevation is output.
[0024] Further, in the step S1, the standardization processing is performed on the stake number sequence, the channel stake number sequence data is rearranged according to a preset fixed step length by linear interpolation, and a continuous and uniform original channel bottom height sequence is formed.
[0025] Further, the mirror image continuation method of the step S2 is a boundary expansion method, the first and last boundaries of the original channel bottom height sequence are regularly expanded, the sequence length is lengthened, the signal change at the boundary is smooth, the local characteristics of the "infinite sequence" are simulated, and the distortion of wavelet transform in the boundary area is reduced.
[0026] Further, with reference to Figure 2 , the mirror image continuation method of the step S2 further includes: S21, obtaining an original channel bottom height sequence to be processed, denoted as sequence X, and the length is L; S22, determining the expansion length n, based on the characteristics of the channel height sequence, adjusting n to L / 2 and taking the integer part downward; S23, expanding the boundary, taking the first or last endpoint of the sequence X as the symmetry axis, extracting n data after the first or last endpoint from the sequence X, arranging the n data in reverse order to form a front or rear end expansion subsequence, and splicing the subsequence to the front or rear end of the sequence X; S24, outputting the complete expansion sequence formed after the front end expansion and the rear end expansion, and the complete expansion sequence is used for subsequent wavelet transform.
[0027] Further, the step S3 further includes: S31, the wavelet base function is selected as Db4 or Sym5; S32, the decomposition layer number n is calculated according to the formula:
[0028] Wherein, is the length of the expanded sequence; The step S3 low frequency trend item, reflecting the overall trend of the channel along the terrain, including the overall slope, regional terrain trend, is the basic framework of the design of the channel bottom; Further, the step S3 high frequency fluctuation item, reflecting the local terrain of the subtle ups and downs, including small range of concave-convex, local obstacles caused by elevation change of terrain details characteristics; The step S4, further comprising: S41, constraint slope, according to the channel's water carrying capacity, anti-scour requirements, set the maximum slope and minimum slope range allowed; S42, reference along the soil bearing capacity, rock distribution geological data, the trend of the elevation of the item involved in the poor geological section is corrected.
[0029] In this embodiment, as shown in the accompanying Figure 3 The boundary effect of the step 2 wavelet transform, when using wavelet decomposition to extract the trend component, the data at both ends appear similar to the distortion of the sine wave, because the wavelet transform has limitations in processing data boundaries; As shown in the accompanying Figure 4 , table 1, the step S3 wavelet transform is used to decompose the elevation data.
[0030] Table 1 wavelet transform decomposition data table
[0031] Further, the step S5, further comprising: S51, calculate the absolute average value of the fluctuation item sequence The calculation formula is as follows:
[0032] Wherein, The absolute average value of the high frequency fluctuation item; The length of the high frequency fluctuation sequence; The original high frequency fluctuation item data; S52, soft threshold compression of the fluctuation item, the calculation formula is as follows:
[0033] Wherein, The processed high frequency fluctuation item; As shown in the accompanying Figure 5 The step S6 synthesis process, the final design of the channel bottom elevation calculation formula is as follows:
[0034] Wherein, The final design of the channel bottom elevation at k stake number; The optimized low-frequency trend item at the k stake number; The processed high-frequency fluctuation item at the k stake number; Further, the standardization processing adopts a linear difference method to process the stake number, and the calculation formula is as follows:
[0035] Wherein, is the original canal bottom elevation at the j stake number, , are the original canal bottom elevations at the beginning and end of the monotonic region respectively, and a and b are the beginning and end stake numbers of the monotonic region; Further, the wavelet transform has the calculation formula as follows:
[0036] In the formula, is a scale factor, which controls the width and position of the wavelet function. By changing the scale factor , the wavelet window can analyze the signal at different scales (frequencies) respectively; is a translation factor, which determines the time position of the analysis, and the double-parameter control mechanism gives the wavelet transform unique time-frequency analysis characteristics; The corresponding scaling and translation wavelet basis function is as follows:
[0037] Further, the optimization of the low-frequency trend item should refer to the following influencing factors: Water level requirement, geological condition, sediment content of water source, size of channel design flow, and appropriate channel gradient are selected in combination with local irrigation management and operation experience.
[0038] In the several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented by other ways. For example, the device embodiments described above are only schematic, and the division of units is only a logical function division, and other division manners can be adopted during actual implementation, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interfaces, devices or units, and can be electrical, mechanical or other forms.
[0039] In addition, the various functional units in the embodiments of the present application can be integrated in one processing unit, or each can exist as an independent physical unit, or two or more than two of them can be integrated in one physical unit. The above-mentioned integrated unit can be implemented in the form of hardware, or in the form of a software functional unit. The above is only an embodiment of the present application, and does not limit the patent scope of the present application, and any equivalent structure or equivalent process transformation using the content of the present application specification and drawings, or direct or indirect application in other related technical fields, are also included in the patent protection scope of the present application.
[0040] The specific embodiments of the application are described in detail above, but they are only examples, and the present application is not limited to the above-described specific embodiments. Any equivalent modification or replacement of the present application made by those skilled in the art is also within the scope of the present application, and therefore, equivalent transformation and modification, improvement, etc. made without departing from the spirit and principle range of the present application should be covered within the scope of the present application.
Claims
1. A method for rapid generation of channel bottoms that integrates topographic trends and engineering constraints, characterized in that, Includes the following steps: S1, Analyze the terrain data, standardize the channel station sequence data, and obtain the original channel bottom elevation sequence; S2, The original channel bottom elevation sequence is extended by mirror continuation method to eliminate the boundary effect of wavelet transform; S3. Select appropriate wavelet basis functions and decomposition scales to decompose the original channel bottom height sequence into low-frequency trend terms and high-frequency fluctuation terms. S4. Based on the low-frequency trend terms obtained from the decomposition, the engineering requirements of the channel design are optimized to obtain trend terms; S5, the high-frequency fluctuation term is processed by using the filtered average value, and the high-frequency fluctuation term is compressed by soft threshold; S6. The optimized trend term and the corrected fluctuation term are superimposed to output the final design channel bottom elevation.
2. The method for rapid generation of channel bottoms integrating terrain trends and engineering constraints according to claim 1, characterized in that, In the standardization process of step S1, the station number sequence is standardized by using linear interpolation to rearrange the channel station number sequence data according to a preset fixed step size, forming a continuous and uniform original channel bottom elevation sequence.
3. The method for rapid generation of channel bottoms integrating topographic trends and engineering constraints according to claim 1, characterized in that, The mirror extension method in step S2 is a boundary extension method. By regularly extending the data at the beginning and end boundaries of the original channel bottom high sequence, the sequence length is extended, making the signal change at the boundary smooth, simulating the local characteristics of an "infinitely long sequence", and reducing the distortion of wavelet transform in the boundary region.
4. The method for rapid generation of channel bottoms integrating topographic trends and engineering constraints according to claim 1, characterized in that, The mirror continuation method in step S2 further includes: S21, Obtain the original channel bottom height sequence to be processed, denoted as sequence X, with a length of L; S22, determine the extension length n, based on the channel high program sequence characteristics, adjust n to L / 2 and round down; S23, Extend the boundary: Using the first or last endpoint of sequence X as the axis of symmetry, extract n data points after the first or last endpoint of sequence X, arrange them in reverse order to form a front or back extended subsequence, and splice the subsequence to the front or back of sequence X. S24, output the complete extended sequence formed by front-end expansion and back-end expansion, the complete extended sequence is used for subsequent wavelet transform.
5. The method for rapid generation of channel bottoms integrating terrain trends and engineering constraints according to claim 1, characterized in that, Step S3 further includes: S31, the wavelet basis function is selected as Db4 or Sym5; S32, the number of decomposition layers n is calculated using the formula: in, The length of the extended sequence; The low-frequency trend item in step S3 reflects the overall change trend of the terrain along the channel, including the overall slope and the orientation of the regional terrain, and is the basic framework for the channel bottom design.
6. The method for rapid generation of channel bottoms integrating terrain trends and engineering constraints according to claim 1, characterized in that, The high-frequency fluctuation term in step S3 reflects the subtle undulations of the local terrain, including small-scale bumps and depressions, and terrain details such as elevation changes caused by local obstacles. Step S4 further includes: S41, Constraint Slope: Based on the channel's water conveyance capacity and erosion prevention requirements, the maximum and minimum allowable slope ranges are set. S42, referencing geological data on soil bearing capacity and rock strata distribution along the route, the elevations of sections with unfavorable geological conditions in the trend item are corrected.
7. The method for rapid generation of channel bottoms integrating topographic trends and engineering constraints according to claim 1, characterized in that, Step S5 further includes: S51, Calculate the fluctuation term sequence The absolute average value is calculated using the following formula: in, This represents the absolute average value of the high-frequency fluctuation term; The length of the high-frequency fluctuation sequence; This is the original high-frequency fluctuation data; S52, soft threshold compression is applied to the fluctuation term, and the calculation formula is as follows: in, This refers to the processed high-frequency fluctuation term; The final formula for calculating the channel bottom elevation in step S6 of the synthesis process is as follows: in, This represents the final design elevation of the canal bottom at station k. The optimized low-frequency trend term at station k; This refers to the processed high-frequency fluctuation term at station k.
8. The method for rapid generation of channel bottoms integrating terrain trends and engineering constraints according to claim 2, characterized in that, The standardization process uses a linear interpolation method to process the station number, and the calculation formula is as follows: in, The original canal bottom elevation at station j. , , respectively, are the original channel bottom elevations at the beginning and end of the monotonic field, and a and b are the station numbers at the beginning and end of the monotonic field.
9. The method for rapid generation of channel bottoms integrating terrain trends and engineering constraints according to claim 6, characterized in that, The wavelet transform is calculated using the following formula: In the formula: The scaling factor controls the width and position of the wavelet function; by changing the scaling factor... Wavelet windows can analyze signals at different scales (frequencys); The translation factor determines the time position of the analysis, and the dual-parameter control mechanism endows wavelet transform with unique time-frequency analysis characteristics; The corresponding scaling and translation wavelet basis functions are as follows: 。 10. The method for rapid generation of channel bottoms integrating terrain trends and engineering constraints according to claim 9, characterized in that, The optimization of low-frequency trend terms should take into account the following influencing factors: The appropriate channel gradient should be selected based on water level requirements, geological conditions, sediment content of the water source, design flow rate of the channel, and local irrigation district management and operation experience.