ADCP-based cableway flow measurement data processing method, system and equipment and medium

Abstract

The invention discloses an ADCP-based cableway flow measurement data processing method, system and device and a medium, and relates to the technical field of data processing, and the method comprises the steps: obtaining a depth unit, obtaining equidistant measurement points, and collecting the echo intensity data of the depth unit; obtaining the relative sand content index of the depth unit; combining the depth units into a flow measurement area with equidistant measurement points according to the relative sand content indexes of the depth units; and if a plurality of flow measurement areas of three sequentially adjacent equidistant measurement points are overlapped with each other, taking the three equidistant measurement points as target measurement points, collecting flow data of the plurality of flow measurement areas at the three target measurement points through a cableway carrying ADCP, and obtaining a flow measurement result according to the flow data of the plurality of flow measurement areas of the three target measurement points. The method has the advantages of self-adaption, strong anti-interference capability and data collaborative verification.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and specifically to a cableway current measurement data processing method, system, device, and medium based on ADCP. Background Technology

[0002] In river hydrological monitoring, the ADCP (Acoustic Doppler Current Profiler) system utilizes the Doppler effect of sound waves to measure water velocity and flow rate. The ADCP system emits sound waves and measures their propagation speed and frequency changes in water to calculate these parameters. However, existing cable-mounted ADCP technologies suffer from complex stratification in sediment-laden water bodies due to uneven vertical sediment concentration distribution, and transient fluctuations in the flow structure between adjacent horizontal measuring points. Furthermore, current ADCP cable-mounted flow measurements typically employ fixed depth layers or pre-defined measurement zones, which presents inherent limitations.

[0003] Specifically, using ADCP echo intensity directly to calculate absolute sediment concentration requires complex calibration and is easily affected by transient changes in water characteristics (such as particle size variations and bubble interference), leading to a mismatch between the vertical velocity layer and the actual sediment concentration distribution. When the sediment concentration differs significantly between adjacent depth units, the representativeness of the velocity within the same measurement zone decreases. Furthermore, existing methods struggle to adaptively capture abrupt changes in sediment stratification (such as suspended sediment transition layers). Mechanically dividing depth units may fragment the same water layer or merge units with excessively large sediment concentration differences, causing a misalignment between the measurement zone and the actual homogeneous water layer. Finally, if only single-point instantaneous data is used to divide the measurement zone and collect flow rates, local disturbances in the horizontal flow structure (such as eddies and localized sand inrushes) will directly transmit to the results, leading to inaccurate velocity fusion results. Moreover, in the three-dimensional spatial detection network formed by cableway mobile scanning, existing methods cannot simultaneously reconcile the contradiction between vertical stratification and horizontal continuity; directly fusing multi-point flow rates will introduce noise. Summary of the Invention

[0004] To address the technical problems in existing technologies, such as the difficulty in dynamically identifying the true flow layer boundary and the inability to ensure the consistency of flow data from multiple measurement points, resulting in significant systematic errors in the final fused cross-sectional flow, this invention provides a cableway flow measurement data processing method, system, device, and medium based on ADCP.

[0005] A cableway flow measurement data processing method based on ADCP includes: acquiring the flow channel region corresponding to the vertical direction of the cableway, dividing the flow channel region into multiple depth units of equal thickness along the vertical direction, acquiring multiple equidistant measurement points located on the cableway, and collecting echo intensity data of multiple depth units at each equidistant measurement point using an ADCP mounted on the cableway; acquiring the i-th relative sediment concentration index of each depth unit based on the echo intensity data of each depth unit collected at the i-th equidistant measurement point; combining each depth unit into multiple flow measurement zones at the i-th equidistant measurement point based on the i-th relative sediment concentration index of each depth unit, wherein the flow measurement zone includes a single depth unit, two or more adjacent depth units, and the maximum difference of the i-th relative sediment concentration index of multiple depth units within the same flow measurement zone does not exceed a preset threshold; if multiple flow measurement zones of three consecutively adjacent equidistant measurement points overlap, then the three equidistant measurement points are taken as target measurement points, and flow data of multiple flow measurement zones are collected at the three target measurement points using an ADCP mounted on the cableway, and flow measurement results are obtained based on the flow data of multiple flow measurement zones at the three target measurement points.

[0006] Optionally, obtaining the i-th relative sediment concentration index of each depth unit based on the echo intensity data of each depth unit collected from the i-th equidistant measuring point includes: obtaining the maximum reference difference of the i-th equidistant measuring point based on the echo intensity data of each depth unit collected from the i-th equidistant measuring point; obtaining the mapping ratio of each depth unit based on the echo intensity data of each depth unit collected from the i-th equidistant measuring point and the maximum reference difference, and using the mapping ratio of each depth unit as the i-th relative sediment concentration index of each depth unit.

[0007] Optionally, obtaining the mapping ratio of each depth unit based on the echo intensity data of each depth unit collected from the i-th equidistant measuring point and the maximum reference difference includes: subtracting the minimum echo intensity data among all the echo intensity data of the i-th equidistant measuring point from the echo intensity data of the j-th depth unit collected from the i-th equidistant measuring point, and obtaining the relative difference of the j-th depth unit; dividing the relative difference of the j-th depth unit by the maximum reference difference to obtain the mapping ratio of the j-th depth unit.

[0008] Optionally, combining the depth units into multiple flow measurement zones for the i-th equidistant measuring point based on the i-th relative sediment concentration index of each depth unit includes: arranging all depth units sequentially in a vertical direction from the water surface downwards to form a depth sequence; taking the first depth unit of the depth sequence as the starting unit of the first flow measurement zone and starting the expansion operation; after terminating the expansion of the flow measurement zone, taking the depth unit at the location where the previous flow measurement zone terminated its expansion as the starting unit of the next flow measurement zone and repeating the expansion operation until the entire depth sequence is traversed, thereby forming multiple flow measurement zones for the i-th equidistant measuring point.

[0009] Optionally, the expansion operation includes: sequentially adding depth units along the depth sequence starting from the initial unit, and calculating the difference between the maximum and minimum values ​​of the i-th relative sediment content index of all depth units in the current flow measurement area after adding a new depth unit; when the addition of a new depth unit causes the difference to exceed a preset threshold, the expansion of the current flow measurement area is terminated and the last newly added depth unit is removed.

[0010] Optionally, obtaining flow measurement results based on flow data from multiple flow measurement zones at three target measurement points includes: obtaining the average value of flow data from the kth flow measurement zone at the three target measurement points, and using this average value as the flow measurement result for the kth flow measurement zone, thereby obtaining the flow measurement results for each flow measurement zone.

[0011] A cableway current measurement data processing system based on ADCP is also provided. The system includes: an acquisition module, used to acquire the flow channel region corresponding to the vertical direction of the cableway, divide the flow channel region into multiple depth units of equal thickness along the vertical direction, acquire multiple equidistant measurement points located on the cableway, and collect echo intensity data of multiple depth units at each equidistant measurement point using an ADCP mounted on the cableway; a first data processing module, used to acquire the i-th relative sediment concentration index of each depth unit based on the echo intensity data of each depth unit collected at the i-th equidistant measurement point; and a second data processing module, used to acquire the i-th relative sediment concentration index of each depth unit based on the echo intensity data of each depth unit. The sediment concentration index combines various depth units into multiple flow measurement zones at the i-th equidistant measurement point. Each flow measurement zone includes a single depth unit, two or more adjacent depth units, and the maximum difference in the i-th relative sediment concentration index of multiple depth units within the same flow measurement zone does not exceed a preset threshold. The flow measurement data processing module is used to take the three equidistant measurement points as target measurement points when the multiple flow measurement zones of three sequentially adjacent equidistant measurement points overlap. The module collects flow data of multiple flow measurement zones at the three target measurement points using an ADCP mounted on the cableway, and obtains the flow measurement result based on the flow data of multiple flow measurement zones at the three target measurement points.

[0012] Optionally, the first data processing module is further configured to: obtain the maximum reference difference of the i-th equidistant measuring point based on the echo intensity data of each depth unit collected from the i-th equidistant measuring point; obtain the mapping ratio of each depth unit based on the echo intensity data of each depth unit collected from the i-th equidistant measuring point and the maximum reference difference, and use the mapping ratio of each depth unit as the i-th relative sand content index of each depth unit.

[0013] An electronic device is also provided, comprising: a memory storing a computer program thereon; and a processor for executing the computer program in the memory to implement a cableway current measurement data processing method based on ADCP.

[0014] A non-transitory computer-readable storage medium is also provided, on which a computer program is stored, which, when executed by a processor, implements a cableway current measurement data processing method based on ADCP.

[0015] The beneficial effects of this invention are reflected in: In the entire ADCP-based cableway flow measurement data processing method, firstly, by normalizing the relative sediment concentration index, the calibration dependence and environmental disturbance sensitivity of existing absolute sediment concentration conversions are avoided, ensuring that the sediment concentration gradient characterization is not affected by the transient characteristics of the water body. Furthermore, based on the continuous dynamic aggregation of the flow measurement zone, a preset threshold is used to control the uniformity of sediment concentration within the same layer, automatically adapting to the differences between thin interfaces (such as suspended sediment layers) and thick homogeneous layers, ensuring that the velocity measurements within each flow measurement zone have physical representativeness (avoiding mixing errors from heterogeneous water bodies). Simultaneously, through anti-disturbance design (such as anomaly...), Value isolation) eliminates the interference of local turbulence on the stratified structure; further, a three-point flow measurement zone coincidence verification mechanism is introduced, which forces the stratified structure to remain stable in adjacent horizontal positions, screens out the distorted profile caused by instantaneous pulsations (such as vortices and sand inrush), and ensures that only reliable strata dominated by water flow inertia participate in flow acquisition; based on the multi-point flow average fusion with strict partition alignment, the influence of single-point instantaneous disturbance is weakened by spatial redundancy, and the unity of vertical stratification and horizontal continuity is maintained (flow in the same measurement zone is collected from the same physical water layer), ultimately improving the accuracy of cross-sectional flow fusion. Attached Figure Description

[0016] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0017] Figure 1 This is a partial flowchart of S1 to S3 in the ADCP-based cableway current measurement data processing method of the present invention. Figure 2 This is a partial flowchart of S3 in the ADCP-based cableway current measurement data processing method of the present invention. Figure 3 This is a partial flowchart of S4 in the ADCP-based cableway current measurement data processing method of the present invention. Figure 4 This is a schematic diagram illustrating the steps of the cableway current measurement data processing method based on ADCP of the present invention. Figure 5 This is a schematic diagram of a portion of step S2 in the ADCP-based cableway current measurement data processing method of the present invention; Figure 6This is a schematic diagram of a portion of step S22 in the ADCP-based cableway current measurement data processing method of the present invention; Figure 7 This is a schematic diagram of a portion of step S3 in the ADCP-based cableway current measurement data processing method of the present invention. Figure 8 This is a schematic diagram of a portion of step S32 in the ADCP-based cableway current measurement data processing method of the present invention. Figure 9 This is a block diagram illustrating an electronic device according to an embodiment of the present invention.

[0018] Figure label: 700 - Electronic device; 701 - Processor; 702 - Memory; 703 - Multimedia component; 704 - I / O interface; 705 - Communication component. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0020] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0021] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0022] like Figures 1 to 4 As shown, a cableway current measurement data processing method based on ADCP is provided. In one embodiment, the method includes: S1. Obtain the flow channel region corresponding to the vertical direction of the cableway, divide the flow channel region into multiple depth units of the same thickness along the vertical direction, obtain multiple equidistant measurement points on the cableway, and collect echo intensity data of multiple depth units at each equidistant measurement point by using ADCP mounted on the cableway. S2. Obtain the i-th relative sediment concentration index of each depth unit based on the echo intensity data of each depth unit collected from the i-th equidistant measuring point. S3. Based on the i-th relative sediment concentration index of each depth unit, combine each depth unit into multiple flow measurement zones with i-th equidistant measurement points. The flow measurement zone includes a single depth unit, two or more adjacent depth units, and the maximum difference of the i-th relative sediment concentration index of multiple depth units in the same flow measurement zone does not exceed a preset threshold. S4. If the multiple flow measurement zones of three consecutively adjacent equidistant measuring points overlap, then these three equidistant measuring points are taken as target measuring points. The ADCP mounted on the cableway is used to collect flow data of multiple flow measurement zones at the three target measuring points, and the flow measurement result is obtained based on the flow data of multiple flow measurement zones at the three target measuring points.

[0023] In this embodiment, it should be noted that in S1, a high-resolution three-dimensional detection grid covering the waterway profile is constructed. During cableway ADCP operations, the flow channel region is first divided vertically: the entire water depth range from the water surface to the riverbed is divided into depth units of equal thickness (e.g., each unit represents a 0.5-meter water layer). This division is based on the physical characteristics of the ADCP acoustic beam—the volume of water penetrated by the acoustic pulse within a fixed sampling period is constant; therefore, the depth unit is essentially a slice of water column of equal thickness covered by acoustic energy. Simultaneously, equidistant measurement points are defined horizontally: based on the positioning accuracy of the cableway traction mechanism, sampling positions are marked on the cableway at fixed intervals (e.g., 2 meters) to ensure that the ADCP probe is aligned with the preset measurement point each time it stops. When the cableway moves to a measurement point, the ADCP emits high-frequency acoustic pulses underwater and receives echo signals from different depth units. The echo intensity data for each depth unit is essentially the energy attenuation value (unit: dB) of the acoustic wave after scattering by suspended sediment, air bubbles, and other particles within that water layer. By scanning point by point along the cableway and collecting the echo intensity matrix on the vertical profile, a three-dimensional spatial dataset is finally formed, consisting of the X-axis (horizontal measurement point spacing), the Z-axis (depth unit sequence), and the Y-axis (acoustic parameters). This grid structure provides a spatial basis for subsequent dynamic segmentation of sediment-bearing layers—each "grid unit" represents the acoustic characteristic sampling value of a specific water layer at a specific location, and its thickness consistency ensures the comparability of the vertical sediment-bearing gradient.

[0024] Furthermore, the grid design of S1 directly serves the dynamic identification needs of the flow layer. Existing methods use fixed water layer divisions, but sediment in natural rivers is often non-uniformly distributed due to factors such as gravity settling and turbulent mixing. S1 improves resolution by setting depth cells, making the water body within each cell approximately homogeneous. When ADCP scans all depth cells at a single measuring point, its echo intensity data sequence directly maps the vertical sediment concentration variation trend: strong acoustic scattering in high sediment concentration areas leads to high echo intensity, while the opposite is true in low sediment concentration areas. At this time, the difference in echo intensity between cells implicitly contains the physical boundary information of sediment concentration stratification (which S2 will use to extract the "relative sediment concentration index"). For example, when the echo intensity of a cell is significantly higher than that of adjacent cells, it suggests that there is a sudden change in sediment concentration at this location; and the operation of dynamically merging cells into flow measurement areas based on this in S3 is essentially an adaptive clustering of physical boundaries—by setting a preset echo intensity difference threshold (reflecting the tolerable range of sediment concentration fluctuation), cells with continuous acoustic characteristics are grouped into the same water layer group. Therefore, the high-resolution grid constructed by S1 provides the conditions for measuring the gradient, while the equidistant layout of measurement points lays the foundation for verifying the consistency of adjacent profiles in the horizontal direction.

[0025] In S2, it's important to note that while ADCP echo intensity is positively correlated with sediment concentration in sediment-laden water, its absolute value is affected by multiple factors such as sound wave frequency, particle size distribution, and temperature gradient. Directly converting echo intensity to sediment concentration (e.g., using laboratory calibration formulas) requires frequent on-site calibration and has poor adaptability to transiently changing water conditions. S2 innovatively proposes a relative sediment concentration index, which is essentially a normalized representation of the relative differences in sediment concentration across all depth units within a single vertical line (the i-th measuring point). In its implementation, firstly, key benchmarks are extracted using the echo intensity dataset (from the high-resolution grid in S1) of each depth unit at the same measuring point: the maximum benchmark difference represents the maximum span of echo intensity within that vertical line (i.e., the extreme range of sediment concentration variation). Subsequently, each depth unit undergoes a two-stage processing: the first stage calculates the relative difference between the unit's echo intensity and the minimum value across the entire vertical line, reflecting the degree to which the unit deviates from the lowest sediment concentration benchmark; the second stage divides the relative difference by the maximum benchmark difference to generate a mapping ratio between 0 and 1 (i.e., the relative sediment concentration index). The core advantage of this design lies in avoiding reliance on absolute physical quantities—the mapping ratio only expresses the ranking relationship of the sand content of each unit within the same vertical line (e.g., the sand content of a unit with an index of 0.8 is much higher than that of a unit with an index of 0.2), without the need to precisely calibrate the actual sand content value. For example, at the suspended sediment abrupt change in sand content at the interface of the suspended sediment abrupt change, the index of the upper unit approaches 0, while the index of the lower unit jumps to above 0.9. This relative difference is sufficient to identify the layer boundary (providing a reliable basis for the dynamic merging of units in S3).

[0026] Furthermore, the relativization process in S2 significantly improves the robustness of water flow stratification identification. Since the maximum reference difference originates from instantaneous data at the same measuring point, it automatically cancels out the negative impact of environmental noise on acoustic energy (such as short-term bubble interference causing synchronous attenuation of echo intensity across the entire vertical line). Simultaneously, the normalization characteristic of the mapping ratio ensures the index's comparability across measuring points—even if the absolute sediment concentration differs across vertical lines, the index level consistently reflects the local sediment concentration gradient (e.g., an index of 0.6 at measuring point A and an index of 0.6 at measuring point B represent similar sediment concentration positions within their respective vertical lines). This characteristic lays the foundation for the subsequent multi-point consistency check in S4. It should be emphasized that the index generation process relies solely on data calculations within a single vertical line, without introducing external parameters, thus resulting in high computational efficiency and no accumulated errors. In engineering scenarios, after the ADCP acquires data at a measuring point (S1), it can immediately calculate and temporarily store the relative sediment concentration index for each depth unit (typically taking only milliseconds), ensuring the real-time dynamic partitioning in S3. More importantly, this index implicitly reveals the continuity of the sediment-bearing structure—a small difference in the index between adjacent units indicates uniform sediment content, while a sharp increase in the difference indicates a layer boundary. For example, if the index of the vertical sequence is [0.1, 0.2, 0.3, 0.85, 0.87], then there is a natural abrupt change in stratification between 0.3 and 0.85, while 0.85 and 0.87 can be classified as the same water layer. This quantitative description of continuity is the direct basis for the adaptive merging of units using the "maximum difference threshold" in S3 (the preset threshold essentially controls the tolerance for sediment fluctuation within the same layer), thereby avoiding layer fragmentation or erroneous merging caused by mechanical division.

[0027] In S3, adaptive flow layer aggregation is performed based on sediment distribution. After calculating the relative sediment concentration index of each depth unit along a single vertical line (i-th measuring point) (S2), the discrete units of the vertical sequence need to be dynamically combined into a flow measurement area with consistent physical properties. The technical necessity lies in the fact that the sediment-laden water layer of a natural river is not of fixed thickness; it may be as thin as tens of centimeters (such as the interface between clear and turbid water) or as thick as several meters (homogeneous high sediment concentration layer). S3 scans adjacent units sequentially along the water depth direction to determine whether they meet the "sediment homogeneity" by using a preset maximum difference threshold (i.e., the allowable fluctuation range of the sediment concentration index within the same layer). The specific execution is divided into three stages: First, the depth units are sorted from the water surface to the riverbed to form a vertical chain; starting from the shallowest unit, the flow measurement area is expanded layer by layer downwards; each time the expansion occurs, it is determined whether the addition of a new unit disrupts the homogeneity of the current partition—by calculating in real time the difference between the maximum and minimum values ​​of the sediment concentration index of all units in the current flow measurement area (i.e., the interval span). If the interval span exceeds the preset threshold after adding a new unit, the expansion is terminated and the process reverts to the previous state. For example, if the sediment concentration index sequence at a certain measuring point is [0.1, 0.15, 0.18, 0.8, 0.82], and the threshold is set to 0.2: starting from the water surface unit 0.1, after adding 0.15, the span becomes 0.05 < 0.2; after adding 0.18, the span becomes 0.08 < 0.2; continuing to add 0.8, the span jumps to 0.7 > 0.2, at which point it reverts to [0.1, 0.15, 0.18] to form the first measuring zone. The remaining unit [0.8, 0.82] is classified as the second zone because the difference is 0.02 < 0.2. This process is essentially the identification of "continuous homogeneous segments" of the sediment concentration gradient: when the difference between adjacent indices is gradual, they are included in the same zone; when a sudden change occurs (a sharp increase in gradient), the zone boundary is triggered, thus accurately matching the actual water layer thickness.

[0028] The preset threshold corresponds to the maximum allowable fluctuation range of the sediment concentration index within the same layer (i.e., the "maximum difference"), used to determine whether multiple depth units belong to the same flow layer. For example, a threshold of 0.1 means that the sediment concentration index of all units within the flow measurement area must fall within the range of ±0.1 (e.g., index values ​​between 0.3 and 0.4). Exceeding this range triggers stratification. The preset threshold value is determined directly by obtaining typical sediment concentration gradients in the flow channel through historical hydrological data or a limited number of field tests. For example, the sediment concentration in the clear-water-turbid-water interface layer can increase by more than 10 times (corresponding to an index difference > 0.8), while the sediment concentration fluctuation in the homogeneous layer is usually less than 5% (index difference < 0.05). When the sediment concentration difference exceeds 30%, the velocity profile is significantly distorted. Therefore, the index difference threshold is usually set to within 0.3 (0.1-0.2 for conservative scenarios). For example, under typical working conditions with a sediment concentration of 10-50 kg / m³ during the flood season, a limited number of measured vertical sediment concentration profiles revealed that the sediment concentration jumped from 8 kg / m³ to 40 kg / m³ at a vertical distance of 1.2 meters (the abrupt change point). The exponential difference between the units above and below the abrupt change point was calculated (example: upper layer exponent 0.2 → lower layer exponent 0.9, the difference is 0.7). Finally, the minimum gradient difference near the abrupt change point (such as an exponential difference of 0.05 within a homogeneous layer) was set as the safe baseline value, and a 20% margin was added to determine the preset threshold as 0.06.

[0029] Furthermore, S3's zoning strategy directly improves the representativeness of velocity measurements. Existing fixed stratification may force units with significant differences in sediment content into the same layer (e.g., units with indices of 0.2 and 0.8 belong to the same 1-meter-thick water layer), resulting in velocity measurements in that layer being a mixture of heterogeneous water bodies, thus losing physical meaning. S3 avoids this problem through two mechanisms: First, the dynamic zoning depth is not preset but is entirely determined by the sediment gradient—low ​​gradient areas are automatically merged into thick layers (e.g., [0.1, 0.15, 0.18] are merged into a 0.3-meter layer), while high gradient areas retain thin or single layers (e.g., [0.8, 0.82] is a 0.1-meter layer), ensuring that the sediment homogeneity within each measurement zone meets engineering tolerance (threshold controllable); Second, the zoning boundaries are strictly aligned with sediment-bearing abrupt change surfaces to avoid disrupting the homogeneous layer. For example, at suspended sediment strata, if the exponential sequence is [0.25, 0.26, 0.85, 0.86], even if the threshold is set to 0.6, adding 0.85 after expanding to 0.26 will still trigger the threshold (span 0.61 > 0.6). Therefore, it automatically partitions between 0.26 and 0.85 to ensure that the low / high sediment-bearing layers above and below the strata are independent zones. More importantly, this design can distinguish between real sediment-bearing layers and transient disturbances: when local turbulence causes an anomalous exponential value in a single unit (such as 0.6 being an anomalous value in the sequence [0.3, 0.32, 0.35, 0.6, 0.33]), expanding to 0.6 will trigger the threshold (span 0.3 > 0.25), but after retreating, the first zone terminates at 0.35; subsequently, when the second zone is restarted from the anomalous unit 0.6, its span with the subsequent 0.33 has reached 0.27 > 0.25, so 0.6 becomes a separate zone—isolating the disturbance point as an independent thin layer. This disturbance resistance capability ensures that the final diffraction zone accurately reflects the dominant flow structure, providing a reliable vertical reference framework for multi-point flow fusion in S4.

[0030] In S4, the reliability defects of instantaneous stratification results at single points are addressed. In natural rivers, although the flow structure at horizontally adjacent locations is macroscopically continuous (e.g., the sediment-laden layer extends gently in the main flow zone), local disturbances (e.g., eddies, sand inrush) can cause vertical stratification distortion at single points. For example, if a false thin sediment-laden layer is formed at a certain measuring point due to instantaneous turbulence, directly measuring the flow velocity based on this will introduce significant deviations. S4 verifies the stability of the flow structure by the spatial overlap of the measuring zones of adjacent measuring points: only when the measuring zones of three consecutive equidistant measuring points (derived from the adaptive stratification in S3) are completely consistent on the vertical boundary is the flow structure in that region considered to have spatiotemporal continuity. This design is based on the fundamental principle of fluid mechanics—that real flow stratification has inertia in the horizontal direction, and the probability of three adjacent measuring points (with a span of typically 4-6 meters) simultaneously exhibiting the same stratification structure is much higher than that of random disturbances. In the specific verification, "overlap" means that the number, order, and depth range of the flow measurement zones divided by the three measuring points all match (e.g., measuring points A, B, and C each contain three flow measurement zones: zone 1 from the water surface to 1.5m, zone 2 from 1.5m to 3.0m, and zone 3 from 3.0m to the riverbed). If a point has an additional thin layer due to localized sand inrush (e.g., an abnormal zone is added at measuring point B between 2.0m and 2.2m), the overlap is disrupted and the point is filtered out. Through this mechanism, only the profile of the stable flow region is retained as the target measuring point.

[0031] Furthermore, S4 collects flow data in the same flow measurement zone (e.g., zone k) for the target measuring points that have passed the overlap verification (e.g., measuring points A, B, and C), and then averages the three independent measurements as the final flow rate of zone k. This operation implicitly incorporates two layers of fault tolerance design: First, horizontal multi-point cross-verification suppresses instantaneous fluctuations. For example, if the flow rate of zone k at measuring point A is temporarily low due to local eddies, while the data at measuring points B and C are normal, the average value automatically weakens the impact of outliers. Second, strict alignment of vertical zones ensures data comparability. Because the boundaries of the flow measurement zones at each point completely overlap (a prerequisite for S4 verification), zone k represents the same physical water layer (consistent sediment content and water depth range) at the three measuring points. In this case, the average flow rate has hydrodynamic significance—equivalent to spatial smoothing of sampling at horizontally adjacent points of the same water layer. In particular, for thin layers in non-overlapping areas (e.g., the 2.0-2.2m anomalous layer at the aforementioned measuring point B), S4 directly discards its flow data (because it cannot pass verification), avoiding the transmission of non-universal disturbances to the final result. For example, during the flood season, a localized tumbling of bottom sand occurs at a certain cross section, causing a surge in sediment concentration in the near-bed area of ​​a single point. S3 isolates this as an independent thin layer, while S4 excludes this point because there is no similar layer in the adjacent points. Finally, the flow data of only the stable layers are merged.

[0032] In summary, the entire ADCP-based cableway flow measurement data processing method firstly avoids the calibration dependence and environmental disturbance sensitivity of existing absolute sediment concentration conversions through relative sediment concentration index normalization, ensuring that the sediment concentration gradient characterization is unaffected by the transient characteristics of the water body. Furthermore, based on the continuous dynamic aggregation of the flow measurement zone, a preset threshold is used to control the uniformity of sediment concentration within the same layer, automatically adapting to the differences between thin interfaces (such as suspended sediment layers) and thick homogeneous layers, ensuring that the velocity measurements within each flow measurement zone have physical representativeness (avoiding mixing errors from heterogeneous water bodies). Simultaneously, through anti-disturbance design… (For example, outlier isolation) eliminates the interference of local turbulence on the stratified structure; further, a three-point flow measurement zone overlap verification mechanism is introduced, which forces the stratified structure to remain stable in adjacent horizontal positions, filtering out distorted profiles caused by instantaneous pulsations (such as vortices and sand inrush), ensuring that only reliable strata dominated by water flow inertia participate in flow acquisition; based on multi-point flow averaging fusion with strict partition alignment, the influence of single-point instantaneous disturbances is weakened by spatial redundancy, while maintaining the unity of vertical stratification and horizontal continuity (flow in the same measurement zone is collected from the same physical water layer), ultimately improving the accuracy of cross-sectional flow fusion. In summary, a complete closed loop of accurate sediment layer matching, outlier disturbance decoupling, and homogeneous fusion of multi-source data is achieved, improving the error of cross-sectional flow detection in natural rivers with non-uniform spatiotemporal distribution of sediment content.

[0033] like Figure 5 As shown, in one embodiment, obtaining the i-th relative sediment concentration index of each depth unit in S2 based on the echo intensity data of each depth unit collected from the i-th equidistant measuring point includes: S21. Obtain the maximum reference difference of the i-th equidistant measuring point based on the echo intensity data of each depth unit collected from the i-th equidistant measuring point. S22. Based on the echo intensity data and maximum reference difference of each depth unit collected from the i-th equidistant measuring point, obtain the mapping ratio of each depth unit, and use the mapping ratio of each depth unit as the i-th relative sand content index of each depth unit.

[0034] In this embodiment, it should be noted that in S21, this step extracts the range (maximum value minus minimum value) of the echo intensity of all depth units within the vertical line of the current measuring point (the i-th equidistant measuring point). This value characterizes the global span of sediment concentration variation along the vertical line (e.g., the acoustic response difference scale between clear water layers and high sediment concentration layers), serving as the reference denominator for subsequent normalization. Its physical significance lies in the fact that the range originates from single-point instantaneous data, which can automatically cancel out synchronous noise across the entire vertical line (such as acoustic energy attenuation caused by short-term bubble clusters), preventing environmental interference from being transmitted to the sediment concentration index calculation.

[0035] In S22, the input is the raw echo intensity of a single measurement point, and the output is a dimensionless sediment concentration index. The entire process does not rely on external parameters or complex calibration, ensuring real-time calculation (millisecond-level response), and the index is comparable across measurement points (e.g., an index of 0.6 on different verticals represents similar sediment concentration positions).

[0036] like Figure 6 As shown, in one embodiment, S22, obtaining the mapping ratio of each depth unit based on the echo intensity data of each depth unit collected from the i-th equidistant measuring point and the maximum reference difference includes: S221. Subtract the minimum echo intensity data among all the echo intensity data of the depth cells collected by the i-th equidistant measuring point from the echo intensity data of the j-th depth cell collected by the i-th equidistant measuring point, and obtain the relative difference value of the j-th depth cell. S222. Divide the relative difference of the j-th depth cell by the maximum reference difference to obtain the mapping ratio of the j-th depth cell.

[0037] In this embodiment, it should be noted that in S221, the acoustic response increment of the j-th unit relative to the cleanest water layer is obtained by subtracting the minimum value along the entire vertical line from the echo intensity of the j-th unit. This operation eliminates the bias of absolute values ​​(such as differences in instrument gain), so that the result only reflects the relative difference in sediment content between units (example: if the relative difference of a unit is 30 dB, it indicates that its sediment content is significantly higher than that of the reference unit). This difference implicitly contains the vertical sediment gradient distribution, providing an unbiased input for exponential generation.

[0038] In S222, the relative difference is divided by the maximum benchmark difference in S21, forcibly mapping the sand content to the 0-1 range. The generated value is essentially the sand content ranking position of the current cell within the vertical line (e.g., an index of 0.6 indicates the range where the sand content of the cell is higher than 60%), decoupled from the absolute physical quantity. For example, with an index of 0.1 for the cell above the mezzanine and 0.9 for the cell below, even if environmental interference causes the absolute value of the echo intensity to drift, the relative order can still accurately identify the layer boundary (directly serving the S3 partition threshold determination).

[0039] like Figure 7 As shown, in one embodiment, S3, which combines the depth units into multiple flow measurement zones with the i-th equidistant measurement point based on the i-th relative sediment concentration index of each depth unit, includes: S31. Arrange all depth units in sequence according to their vertical position from the water surface downwards to form a depth sequence; S32. Take the first depth unit of the depth sequence as the starting unit of the first current measurement zone and start the expansion operation; S33. After terminating the expansion of the current measurement zone, take the depth cell at the location where the previous current measurement zone terminates its expansion as the starting cell of the next current measurement zone, and repeat the expansion operation until the entire depth sequence is traversed, thereby forming multiple current measurement zones for the i-th equidistant measurement point.

[0040] In this embodiment, it should be noted that in S31, all depth units of a single measuring point (i) are arranged in a vertical physical order from the water surface to the riverbed, forming an ordered sequence. The core of this is to establish a spatial continuity benchmark, ensuring that subsequent zoning operations strictly follow the natural laws of water flow stratification (sediment gradient changes with depth). For example, the vertical positional relationship between adjacent units directly affects the judgment of "sediment uniformity," ensuring that the zoning boundary does not cross physically adjacent layers (e.g., avoiding skipping layer merging). This operation forms the basic topological framework for dynamic zoning.

[0041] In S32, the first flow measurement zone is initialized starting from the topmost unit of the sequence, marking the start of the dynamic expansion process. This technique is essential to ensure the spatial continuity of the zones—each flow measurement zone consists of physically adjacent units, preventing the forced merging of non-adjacent units (such as splitting the water layer). For example, starting from the surface unit, the flow measurement process gradually detects sediment load changes downwards. When a sudden change in sediment load is encountered (such as the clear-turbidity water interface), the current zone is terminated, and the point of change automatically becomes the starting point of the next zone.

[0042] S33. After terminating the expansion in the current flow measurement zone, use the cell at the termination point (e.g., the removed 0.8 cell) as the starting cell for the next partition, and repeat the expansion operation in S32. Repeat this process until the entire depth sequence is covered, forming a partition group covering the entire vertical line. This mechanism ensures no cells are missed (e.g., riverbed cells must be included in the final zone), and partitioning strictly follows the depth gradient, avoiding jumps or overlaps (example output: [water surface - 1.5m], [1.5m - riverbed]).

[0043] like Figure 8 As shown, in one embodiment, the extended operation in S32 includes: S321. Starting from the initial unit, add depth units sequentially along the depth sequence, and after adding a new depth unit, calculate the difference between the maximum and minimum values ​​of the i-th relative sediment concentration index of all depth units in the current flow measurement area. S322. When the addition of a new depth unit causes the difference to exceed a preset threshold, the expansion of the current flow measurement area is terminated and the last newly added depth unit is removed.

[0044] In this embodiment, it should be noted that in S321, starting from the current starting unit, downstream units are temporarily included in the candidate flow measurement area in sequence. After each addition, the range (maximum minus minimum value) of the i-th relative sediment concentration index of all units in the area (ultimately forming multiple flow measurement areas with i-th equidistant measurement points) is calculated in real time. This range reflects the sediment concentration fluctuation amplitude in the current partition (e.g., the range of [0.1, 0.15, 0.18] is 0.08), which is a direct indicator for judging whether the added unit destroys the "sand concentration uniformity". The essence of the expansion is to tentatively search for the maximum homogeneous range.

[0045] In S322, when the range of a newly added cell exceeds a preset threshold (e.g., 0.1), it is determined that the sand-containing characteristics of that cell are incompatible with the previous region (e.g., after adding 0.8 to [0.1, 0.15, 0.18], the range jumps to 0.7 > 0.1), and the process immediately reverts: the newly added cell is removed and the current expansion is terminated. This operation ensures that the partition boundary is always located at the critical point of sand-containing abrupt change (e.g., the boundary between 0.18 and 0.8), so that the sand-containing fluctuation within each flow measurement zone is strictly controlled (≤ threshold).

[0046] In one implementation, obtaining the flow measurement result based on the flow data of multiple flow measurement zones at three target measurement points in step S4 includes: The average value of the flow data of the kth flow measurement zone of the three target measurement points is obtained, and this average value is used as the flow measurement result of the kth flow measurement zone. In this way, the flow measurement results of each flow measurement zone are obtained.

[0047] In this embodiment, it should be noted that the flow fusion operation of S4 focuses on multi-point spatial smoothing of reliable vertical partitions: for the k-th flow zone that passes the three-point flow zone overlap test, its flow data comes from three horizontally adjacent target points (the vertical partition boundaries are strictly aligned to ensure data homogeneity); by averaging the three-point flow values, it suppresses instantaneous disturbances at single points (such as flow abnormalities caused by local vortices at point B) and maintains the physical consistency of the vertical stratification structure—the flow of the k-th flow zone after fusion represents the spatial average state of the water layer in the stable flow region, thereby weakening the impact of pulsating noise (such as sand inrush interference) on the final cross-sectional flow, while retaining the true stratified flow velocity characteristics.

[0048] A cableway current measurement data processing system based on ADCP is also provided, the system comprising: The acquisition module is used to acquire the flow channel area corresponding to the vertical direction of the cableway, divide the flow channel area into multiple depth units of the same thickness along the vertical direction, acquire multiple equidistant measurement points on the cableway, and collect echo intensity data of multiple depth units at each equidistant measurement point by using ADCP mounted on the cableway. The first data processing module is used to obtain the i-th relative sediment concentration index of each depth unit based on the echo intensity data of each depth unit collected from the i-th equidistant measuring point. The second data processing module is used to combine each depth unit into multiple flow measurement zones with an equidistant measuring point i based on the i-th relative sediment concentration index of each depth unit. The flow measurement zone includes a single depth unit, two or more adjacent depth units, and the maximum difference of the i-th relative sediment concentration index of multiple depth units in the same flow measurement zone does not exceed a preset threshold. The flow measurement data processing module is used to take the three equidistant measurement points as target measurement points when multiple flow measurement zones of three sequentially adjacent equidistant measurement points overlap with each other. The module collects flow data of multiple flow measurement zones at the three target measurement points through an ADCP mounted on the cableway, and obtains the flow measurement result based on the flow data of multiple flow measurement zones at the three target measurement points.

[0049] In one embodiment, the first data processing module is further configured to: obtain the maximum reference difference of the i-th equidistant measuring point based on the echo intensity data of each depth unit collected from the i-th equidistant measuring point; obtain the mapping ratio of each depth unit based on the echo intensity data of each depth unit collected from the i-th equidistant measuring point and the maximum reference difference; and use the mapping ratio of each depth unit as the i-th relative sand content index of each depth unit.

[0050] In this embodiment, it should be noted that the specific method of performing the above-mentioned ADCP-based cableway current measurement data processing system has been described in detail in the embodiments of the ADCP-based cableway current measurement data processing method, and will not be elaborated here.

[0051] Figure 9 This is a block diagram of an electronic device illustrating an ADCP-based cableway current measurement data processing method according to an exemplary embodiment. Figure 9 As shown, the electronic device 700 may include: a processor 701 and a memory 702. The electronic device 700 may also include one or more of a multimedia component 703, an I / O interface 704 (input / output interface), and a communication component 705.

[0052] The processor 701 controls the overall operation of the electronic device 700 to complete all or part of the steps in the ADCP-based cableway current measurement data processing method described above. The memory 702 stores various types of data to support the operation of the electronic device 700. This data may include, for example, instructions for any application or method operating on the electronic device 700, and application-related data such as contact data, sent and received messages, pictures, audio, video, etc. The memory 702 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. Multimedia component 703 may include a screen and an audio component. The screen may be, for example, a touchscreen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in memory 702 or transmitted via communication component 705. The audio component also includes at least one speaker for outputting audio signals. I / O interface 704 provides an interface between processor 701 and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual or physical buttons. Communication component 705 is used for wired or wireless communication between the electronic device 700 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IoT, eMTC, or other 5G technologies, or combinations thereof, is not limited here. Therefore, the corresponding communication component 705 may include: a Wi-Fi module, a Bluetooth module, an NFC module, etc.

[0053] In an exemplary embodiment, the electronic device 700 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described ADCP-based cableway current measurement data processing method.

[0054] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, which, when executed by a processor, implement the steps of the ADCP-based cableway current measurement data processing method described above. For example, the computer-readable storage medium may be the memory 702 including program instructions described above, which may be executed by the processor 701 of the electronic device 700 to complete the ADCP-based cableway current measurement data processing method described above.

[0055] In another exemplary embodiment, a computer program product is also provided, comprising a computer program executable by a programmable device, the computer program having a code portion for performing the above-described ADCP-based cableway current measurement data processing method when executed by the programmable device.

[0056] The preferred embodiments of the present disclosure have been described in detail above with reference to the accompanying drawings. However, the present disclosure is not limited to the specific details of the above embodiments. Within the scope of the technical concept of the present disclosure, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0057] It should also be noted that the various specific technical features described in the above embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, this disclosure will not describe the various possible combinations separately.

[0058] Furthermore, various different embodiments of this disclosure can be combined in any way, as long as they do not violate the spirit of this disclosure, they should also be regarded as the content disclosed in this disclosure.

[0059] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A cableway current measurement data processing method based on ADCP, characterized in that, include: The flow channel region corresponding to the vertical direction of the cableway is obtained, and the flow channel region is divided into multiple depth units of the same thickness along the vertical direction. Multiple equidistant measurement points are obtained on the cableway, and echo intensity data of multiple depth units are collected at each equidistant measurement point by using an ADCP mounted on the cableway. The i-th relative sediment concentration index of each depth unit is obtained based on the echo intensity data of each depth unit collected from the i-th equidistant measuring point. Based on the i-th relative sediment concentration index of each depth unit, the depth units are combined into multiple flow measurement zones with i-th equidistant measurement points. The flow measurement zone includes a single depth unit, two or more adjacent depth units, and the maximum difference of the i-th relative sediment concentration index of multiple depth units in the same flow measurement zone does not exceed a preset threshold. If multiple flow measurement zones of three consecutively adjacent equidistant measurement points overlap, then these three equidistant measurement points are taken as target measurement points. The ADCP mounted on the cableway is used to collect flow data of multiple flow measurement zones at the three target measurement points, and the flow measurement result is obtained based on the flow data of multiple flow measurement zones at the three target measurement points.

2. The cableway current measurement data processing method based on ADCP according to claim 1, characterized in that, The process of obtaining the i-th relative sediment concentration index of each depth unit based on the echo intensity data collected from the i-th equidistant measuring point includes: The maximum reference difference of the i-th equidistant measuring point is obtained based on the echo intensity data of each depth unit collected from the i-th equidistant measuring point. The mapping ratio of each depth unit is obtained based on the echo intensity data and maximum reference difference collected from the i-th equidistant measuring point, and the mapping ratio of each depth unit is used as the i-th relative sand content index of each depth unit.

3. The cableway current measurement data processing method based on ADCP according to claim 2, characterized in that, The process of obtaining the mapping ratio of each depth unit based on the echo intensity data of each depth unit collected from the i-th equidistant measuring point and the maximum reference difference includes: Subtract the minimum echo intensity data among all the echo intensity data of the j-th depth cell collected by the i-th equidistant measuring point from the echo intensity data of the j-th depth cell, and obtain the relative difference value of the j-th depth cell. Divide the relative difference of the j-th depth cell by the maximum reference difference to obtain the mapping ratio of the j-th depth cell.

4. The cableway current measurement data processing method based on ADCP according to claim 1, characterized in that, The multiple flow measurement zones that combine the depth units into i-th equidistant measurement points based on the i-th relative sediment concentration index of each depth unit include: All depth units are arranged sequentially from the water surface downwards according to their vertical position to form a depth sequence; The first depth unit of the depth sequence is used as the starting unit of the first current measurement zone, and the expansion operation begins. After the expansion of the current measurement zone is terminated, the depth cell at the location where the previous current measurement zone was terminated is taken as the starting cell of the next current measurement zone, and the expansion operation is repeated until the entire depth sequence is traversed, thereby forming multiple current measurement zones for the i-th equidistant measurement point.

5. The cableway current measurement data processing method based on ADCP according to claim 4, characterized in that, The extended operations include: Starting from the initial unit, depth units are added sequentially along the depth sequence. After adding a new depth unit, the difference between the maximum and minimum values ​​of the i-th relative sediment concentration index of all depth units in the current flow measurement area is calculated. If the addition of a new depth unit causes the difference to exceed a preset threshold, the expansion of the current flow measurement zone is terminated and the last newly added depth unit is removed.

6. The cableway current measurement data processing method based on ADCP according to claim 1, characterized in that, The process of obtaining flow measurement results based on flow data from multiple flow measurement zones at three target measurement points includes: The average value of the flow data of the kth flow measurement zone of the three target measurement points is obtained, and this average value is used as the flow measurement result of the kth flow measurement zone. In this way, the flow measurement results of each flow measurement zone are obtained.

7. A cableway current measurement data processing system based on ADCP, characterized in that, The system includes: The acquisition module is used to acquire the flow channel area corresponding to the vertical direction of the cableway, divide the flow channel area into multiple depth units of the same thickness along the vertical direction, acquire multiple equidistant measurement points on the cableway, and collect echo intensity data of multiple depth units at each equidistant measurement point by using ADCP mounted on the cableway. The first data processing module is used to obtain the i-th relative sediment concentration index of each depth unit based on the echo intensity data of each depth unit collected from the i-th equidistant measuring point. The second data processing module is used to combine each depth unit into multiple flow measurement zones with an equidistant measuring point i based on the i-th relative sediment concentration index of each depth unit. The flow measurement zone includes a single depth unit, two or more adjacent depth units, and the maximum difference of the i-th relative sediment concentration index of multiple depth units in the same flow measurement zone does not exceed a preset threshold. The flow measurement data processing module is used to take the three equidistant measurement points as target measurement points when multiple flow measurement zones of three sequentially adjacent equidistant measurement points overlap with each other. The module collects flow data of multiple flow measurement zones at the three target measurement points through an ADCP mounted on the cableway, and obtains the flow measurement result based on the flow data of multiple flow measurement zones at the three target measurement points.

8. The cableway current measurement data processing system based on ADCP according to claim 7, characterized in that, The first data processing module is also used for: The maximum reference difference of the i-th equidistant measuring point is obtained based on the echo intensity data of each depth unit collected from the i-th equidistant measuring point. The mapping ratio of each depth unit is obtained based on the echo intensity data and maximum reference difference collected from the i-th equidistant measuring point, and the mapping ratio of each depth unit is used as the i-th relative sand content index of each depth unit.

9. An electronic device, characterized in that, include: A memory on which computer programs are stored; A processor is configured to execute the computer program in the memory to implement the cableway current measurement data processing method based on any one of claims 1 to 6.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the cableway current measurement data processing method based on any one of claims 1 to 6.

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