A cleaning method and system based on hydraulic engineering

Abstract

This invention relates to a cleaning method and system for hydraulic engineering projects, specifically concerning the control of a dredging cutter. The method includes: acquiring an agitation load in response to a preset dredging bottom-touching command; when the agitation load exceeds a preset contact threshold, determining the dredging location based on the agitation load and the engineering depth based on the dredging location; determining the bottom-touching duration based on the agitation load and the water depth based on the bottom-touching duration; determining the silt depth by comparing the engineering depth and the water depth, and matching the agitation force based on the silt depth; generating an agitation stroke curve by combining the silt depth and the agitation force, and sending a silt agitation command in response to the generation of the agitation stroke curve to facilitate the suction of silt by a mud pump and its transportation through pipelines. This invention improves the efficiency of hydraulic engineering cleaning and reduces the occurrence of cutter damage.

Description

Technical Field

[0001] This invention relates to the field of dredging cutter control, and in particular to a dredging method and system based on water conservancy projects. Background Technology

[0002] Hydraulic engineering cleanup refers to engineering operations that use mechanical equipment to remove silt from the bottom of water bodies in order to restore the flow capacity of rivers and the effective storage capacity of reservoirs.

[0003] In existing dredging operations, the water depth of the working area is usually measured first using a multibeam echo sounder or a single-beam echo sounder. Then, the engineering depth corresponding to the current designed dredging bottom elevation is obtained using a GPS or Beidou positioning system. The engineering depth is subtracted from the measured water depth to obtain the silt thickness at that location. Alternatively, a manual drill rod is inserted into the bottom mud until the hard bottom layer is reached. The silt thickness is determined by the depth of the drill rod penetration. The reamer is then rotated according to the silt thickness obtained from the measurement point to agitate the silt layer, and a mud pump is controlled to suck up the silt.

[0004] Different silt thicknesses require different reamer speeds. When there is a deviation between the actual silt thickness and the silt thickness at the measurement point, the reamer speed may not correspond to the silt condition, leading to reamer damage. Summary of the Invention

[0005] To improve the efficiency of water conservancy project cleaning and reduce the damage to the reamer, this invention provides a cleaning method and system based on water conservancy projects.

[0006] In a first aspect, the present invention provides a cleaning method based on water conservancy projects, employing the following technical solution: A cleaning method based on water conservancy projects, comprising: Step 100: Collect the agitation load in response to the preset dredging and bottom contact command; Step 101: When the agitation load is greater than the preset contact threshold, retrieve the dredging location based on the agitation load, and retrieve the engineering depth based on the dredging location; Step 102: Determine the bottom contact time based on the agitation load, and determine the water depth based on the bottom contact time; Step 103: Determine the silt depth by comparing the engineering depth and the water depth, and match the stirring force according to the silt depth; Step 104: Generate an agitation stroke curve by combining the sludge depth and agitation force, and in response to the generation of the agitation stroke curve, send a sludge agitation command to facilitate the suction of sludge by a sludge pump and its transportation through pipelines.

[0007] Optional, also includes: Step 105: Retrieve the cutter depth and cutter speed from the sludge agitation command, and compare the cutter depth with the water depth to determine the agitation depth; Step 106: Determine the mud concentration by combining the agitation depth and cutter rotation speed, and set the reference suction speed; Step 107: Compare the mud concentration with the reference suction rate to determine the concentration deviation, and determine the corrected suction rate based on the concentration deviation; Step 108: In response to the generation of the modified suction rate and the reference suction rate, a mud suction command is sent.

[0008] Optional, also includes: Step 109: Determine the reference load by combining the agitation depth and the reamer speed, and compare the agitation load with the reference load to determine the load deviation; Step 110: When the load deviation is greater than a preset error threshold, determine the deviation ratio based on the load deviation and the reference load; Step 111: Match the deceleration ratio by combining the aforementioned deviation ratio and load deviation; Step 112: Update the agitation stroke curve in response to the slowing ratio.

[0009] Optionally, it also includes a method for correcting the deceleration ratio, the method for correcting the deceleration ratio including: Step 200: When the load deviation is greater than a preset error threshold, compare the load deviation with the preset error threshold to determine the deviation time; Step 201: Determine the deviation frequency based on the deviation time, and determine the error coefficient based on the reamer depth; Step 202: Match the corresponding benchmark ratio according to the deviation ratio, and determine the error ratio by combining the benchmark ratio and the error coefficient; Step 203: Eliminate interference in the deviation frequency according to the error ratio to predict the particle density in the sludge, and count the load deviation as the total resistance. Step 204: Analyze the particle density and total resistance to determine the particle size, and combine the particle density and particle size to determine the particle coefficient; Step 205: Update the slow ratio in response to the particle coefficient.

[0010] By adopting the above technical solution, the deviation frequency is determined by the moment when the load deviation is too large, the error coefficient is determined by combining the cutter depth, the error ratio is calculated by the reference ratio and the error coefficient, the particle density is predicted after removing the interference components in the deviation frequency by using the error ratio, the particle size is determined by combining the load deviation statistics, and the particle coefficient is generated to correct the slowing ratio. Thus, the quantitative inversion from the load fluctuation frequency to the particle properties is realized, providing real-time data support for the physical properties of bottom sediment for the optimization of dredging parameters.

[0011] Optionally, the method for correcting the retarding ratio further includes: Step 206: When the error ratio is greater than a preset confidence threshold, retrieve multi-source data; Step 207: Extract interference factors from the multi-source data and determine interference weights based on the reamer depth; Step 208: Determine the interference coefficient by combining the interference factor and the interference weight; Step 209: Update the error ratio in response to the interference coefficient.

[0012] By adopting the above technical solution, multi-source data fusion is initiated when the error ratio is too large. Interference factors are extracted from multi-source data such as water pressure, vibration, and current. The interference weight of each factor is determined by combining the reamer depth. The interference coefficient is calculated by weighting to update the error ratio. In this way, the degree of external interference can be accurately quantified by cross-verification of multi-source sensor information, which is aimed at the complex interference characteristics of deep water areas, and the deficiency of the anti-interference capability of a single load signal can be made up for.

[0013] Optionally, the method for correcting the retarding ratio further includes: Step 210: When the error ratio is greater than a preset confidence threshold, calculate the density change rate based on the particle density and the particle size change rate based on the particle size. Step 211: Determine the consistency threshold based on the interference coefficient, and compare the density change rate, particle size change rate and consistency threshold to determine spatial consistency; Step 212: If the spatial consistency falls within the preset transition range, determine the idling time according to the error ratio, and generate and send an idling verification command in response to the idling time. Step 213: Retrieve the verification load according to the idle verification command, and extract the reference interference spectrum from the verification load; Step 214: Extract the actual load from the agitation load based on the reamer depth, and subtract the spectrum of the actual load from the reference interference spectrum to obtain the effective load spectrum; Step 215: Calculate the impedance values ​​from the payload spectrum and match the verification coefficients based on the impedance values; Step 216: Update the error ratio in response to the verification coefficient.

[0014] By adopting the above technical solution, when the error ratio is too large, the density change rate and particle size change rate of particle parameters are calculated, and the consistency threshold is determined by combining the interference coefficient to judge spatial consistency. When the consistency falls into the jump range, idle calibration is performed to update the error ratio. Thus, the effective payload signal is accurately extracted through the dual mechanism of spatial consistency verification and idle calibration, thereby improving the reliability of particle inversion under complex deep-water conditions.

[0015] Optionally, it also includes a soil remediation method, said soil remediation method comprising: Step 300: Match the soil type with the particle density and particle size, and retrieve the navigation route according to the dredging location; Step 301: Determine the excavation location by combining the navigation route and the cutter depth, and generate a soil distribution map by combining the soil type and the excavation location; Step 302: Read the particle size variation rate of the particle size coefficient from the soil distribution map, and expand the soil distribution map based on the particle size variation rate to form a predicted distribution map; Step 303: Determine the navigation area to be reached based on the navigation route, and read the regional coefficient of the navigation area from the predicted distribution map; Step 304: Calculate the mean value of the regional coefficients as the mean coefficient, and determine the prediction ratio based on the mean coefficient; Step 305: Generate a speed transition curve by combining the slowing ratio and the predicted ratio, and update the turbulence stroke curve in response to the speed transition curve.

[0016] By adopting the above technical solution, the inverted particle density and particle size are matched to the soil type. A soil distribution map is generated by combining the cutter depth and navigation route. A predicted distribution map is generated by using the particle change rate. The navigation area coefficient is read from the predicted distribution map to calculate the mean coefficient. Based on this, the predicted ratio is determined and fused with the deceleration ratio to generate a speed transition curve to update the travel curve. This realizes the inversion of the overall silt soil from a single point, enabling the cutter to adjust its rotation speed in advance according to the soil ahead, thus achieving predictive control.

[0017] Optionally, the soil remediation method further includes: Step 306: Read the sailing speed based on the sailing route, and analyze the sailing route to determine the extended route forward; Step 307: Read the extension coefficient from the predicted distribution map according to the extension route, and generate a coefficient fluctuation curve by combining the extension coefficient and the sailing speed; Step 308: Read the rate of change of navigation from the coefficient fluctuation curve; Step 309: When the rate of change of navigation is greater than the preset damage threshold, retrieve the damage location based on the rate of change of navigation, and read the altitude fluctuation curve from the predicted distribution map according to the damage location; Step 310: Determine the protection coefficient by combining the coefficient fluctuation curve and the preset damage threshold, and query the protection height from the height fluctuation curve according to the protection coefficient; Step 311: Generate the reamer extension stroke by combining the protection height and the extension path, and update the agitation stroke curve in response to the reamer extension stroke.

[0018] By adopting the above technical solution, the navigation speed and extension route are read based on the navigation route, and the extension coefficient generation coefficient fluctuation curve is read from the predicted distribution map. When the rate of change of navigation exceeds the damage threshold, the protection height is determined by combining the height fluctuation curve. Based on this, the reamer extension stroke is generated to update the stroke curve. Thus, the adaptive control of reamer extension is achieved by predicting the height fluctuation of the soil ahead. Under complex terrain conditions, the reamer height is adjusted in advance to reduce the situation of collision damage.

[0019] Optionally, the soil remediation method further includes: Step 312: If the spatial consistency falls within a preset jump range, determine the mutation type by combining the particle density and particle size; Step 313: Based on the dredging location, read the surrounding species from the predicted distribution map, and compare the mutated species with the surrounding species to determine the species difference; Step 314: When the difference between the types is less than a preset possible threshold, the jump load is extracted from the agitation load, and the spectral characteristics of the jump load are extracted to obtain the jump frequency; Step 315: Match the cutting frequency according to the reamer rotation speed, and compare the cutting frequency with the jump frequency to determine the frequency difference; Step 316: Update the idling time in response to the frequency difference.

[0020] By adopting the above technical solution, when the spatial consistency falls into the jump interval, the type of mutation is determined and compared with the surrounding types to determine the type difference. When the type difference is small, the jump load is extracted to extract the jump frequency, which is compared with the theoretical cutting frequency to determine the frequency difference. Based on this, the idling time is updated, thus constructing a dual jump diagnosis mechanism of spatial consistency verification and frequency domain conformity verification. This distinguishes between real soil mutation and sensor noise interference, reduces unnecessary idling calibration, and improves the intelligent decision-making accuracy of the system.

[0021] Secondly, the present invention provides a cleaning system based on water conservancy engineering, which adopts the following technical solution: A cleaning system based on water conservancy engineering, comprising: The acquisition module is used to acquire the agitation load; A memory for storing programs for any of the aforementioned cleaning methods based on water conservancy projects; The processor is the unit of memory that allows programs to be loaded and executed by the processor.

[0022] By adopting the above technical solution, the agitation load is collected in response to the dredging bottom-touching command. When the agitation load is too large, the dredging location and engineering depth are retrieved. The water depth is estimated using the bottom-touching time, and the silt depth is determined by combining the difference between the engineering depth and the water depth. Based on this, the agitation force is matched and an agitation stroke curve is generated. This enables automatic silt depth sensing and stroke planning based on load time sequence characteristics, without relying on dedicated depth sounding equipment, thus improving the adaptability of operations in shallow water areas.

[0023] In summary, the present invention has at least one of the following beneficial technical effects: By responding to the dredging bottom-reaching command and collecting the agitation load, and when the agitation load is too large, the dredging location and engineering depth are retrieved. The water depth is estimated using the bottom-reaching time, and the silt depth is determined by combining the difference between the engineering depth and the water depth. Based on this, the agitation force is matched and an agitation stroke curve is generated. This enables automatic silt depth sensing and stroke planning based on load time-series characteristics, without relying on dedicated depth sounding equipment, thus improving the adaptability of operations in shallow water areas. The reamer depth and reamer speed are retrieved from the sludge agitation command. The agitation depth is determined by combining the water depth. The sludge concentration is determined by the agitation depth and speed together. The concentration deviation is generated by comparing it with the benchmark suction speed. Then, the corrected suction speed is determined to adjust the sludge pump suction speed in a closed loop. This establishes a sludge concentration prediction and suction speed adaptive adjustment mechanism based on real-time operating conditions, reducing the situation where the sludge concentration is too high, causing pipe blockage, or the concentration is too low, reducing the conveying efficiency. The reference load is determined by combining the agitation depth and the cutter speed. The load deviation is calculated by comparing the actual agitation load with the reference load. When the load deviation is too large, the deviation ratio is determined and the deceleration ratio is matched. The agitation stroke curve is dynamically updated accordingly, thereby establishing a deceleration protection mechanism based on load feedback. When the actual load deviates from the theoretical expectation, the cutter speed is automatically adjusted to reduce the possibility of equipment overload damage. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of a cleaning method based on water conservancy engineering. Figure 2 This is a flowchart of a cleaning method based on water conservancy engineering. Figure 3 This is a flowchart of soil remediation methods. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0026] This invention discloses a cleaning method based on water conservancy projects.

[0027] Reference Figure 1 and Figure 2 A cleaning method based on water conservancy projects, comprising: Step 100: Collect the agitation load in response to the preset dredging and bottom contact command.

[0028] The dredging bottom contact command is a trigger signal that controls the shovel to begin sinking to start the dredging process. That is, the operator or automatic control system issues a command to start the shovel lifting mechanism, and the shovel begins to move downward from the water surface position. This command can be manually triggered by the operator through the control panel button, or it can be automatically generated by the system according to the preset operation plan after the dredging equipment reaches the starting point of the operation. The command is sent to the driver of the shovel lifting mechanism through the CAN bus or industrial Ethernet.

[0029] Agitation load refers to the resistance generated by the interaction between the auger and water, silt and hard bottom layer during the rotary cutting process. This resistance is collected in real time by a torque sensor installed on the auger drive shaft or a pressure sensor in the hydraulic system.

[0030] Step 101: When the agitation load is greater than the preset contact threshold, retrieve the dredging location based on the agitation load, and retrieve the engineering depth based on the dredging location.

[0031] The contact threshold is a preset load value used to distinguish between the cutter head being suspended and touching the bottom. When the cutter head is only idling in the water, the load is small, but once it touches the bottom sediment, the load will increase significantly. This threshold can be determined through experimental calibration or statistical analysis of historical operation data.

[0032] The dredging location refers to the current geographical coordinates of the shovel cutter, which are obtained in real time through the shipborne GPS or Beidou positioning system. When the agitation load is greater than the contact threshold, the system records the location coordinates at that moment as the dredging location.

[0033] Engineering depth refers to the depth value corresponding to the design dredging bottom elevation specified in the design documents at the dredging location. It represents the target depth that needs to be cleared at that location. The corresponding engineering depth can be obtained by retrieving the digital elevation model or dredging design cross-section diagram stored in the control system in advance and interpolating the coordinates of the dredging location.

[0034] Step 102: Determine the bottom contact time based on the agitation load, and determine the water depth based on the bottom contact time.

[0035] The bottoming time refers to the time interval between when the sluice begins to sink and when it contacts the surface of the silt. It can be timed from the moment the bottoming command is issued until the moment the stirring load first exceeds the contact threshold. The elapsed time is the bottoming time.

[0036] Water depth refers to the vertical distance from the water surface to the silt surface. After the sluice cutter is given the dredging bottom contact command, it continues to sink at a known constant speed until it contacts the silt surface. The sinking distance of the sluice cutter during this time period is equal to the product of the sluice cutter sinking speed and the bottom contact time. This sinking distance is the water depth. The sluice cutter sinking speed is obtained in real time by the differential value of the encoder of the lifting mechanism or determined by the sinking speed command preset by the control system.

[0037] Step 103: Determine the silt depth by comparing the engineering depth and the water depth, and match the stirring force according to the silt depth.

[0038] Silt depth refers to the total thickness of the silt layer at the dredging location, which is the vertical distance from the silt surface to the hard bottom layer. It is calculated by subtracting the water depth from the engineering depth. When the engineering depth is greater than the water depth, the silt depth is positive, indicating that there is a silt layer at that location that needs to be cleaned.

[0039] The agitation force refers to the maximum force required when cutting at the bottom layer of silt, i.e., the boundary between silt and the hard sublayer. The greater the silt depth, the greater the total thickness of the silt layer. The greater the overlying pressure on the bottom silt, the higher the density, and the greater the maximum agitation force required. The agitation force corresponding to the silt depth can be found in the agitation force correspondence table, which is a data table that records different silt depths and their corresponding agitation forces.

[0040] In this application, all correspondence tables and data tables are constructed using a three-pronged approach: scaled-down model calibration, real-ship operation verification, and discrete element numerical simulation. Specifically, based on actual dredging equipment (such as cutterheads and mud pumps), scaled-down experimental models are created according to the principle of full similarity in fluid mechanics. Systematic cutting experiments are conducted on an indoor excavation experimental platform for various standard soil types, including silt, silt, sand, and gravel. Parameters such as torque load, power, and mud density are collected simultaneously under different working conditions (cutterhead speed, lateral speed, cutting depth, reamer depth, etc.). Simultaneously, a discrete element numerical model of cutterhead cutting is established. The micro-parameters of the contact model are calibrated through virtual uniaxial compression tests and virtual Brazilian splitting tests. Dynamic cutting numerical simulations are then conducted to cover extreme working conditions that are difficult to achieve experimentally. Experimental results are cross-validated with numerical simulation results. After removing outliers, multidimensional statistical analysis is performed according to the combination of working condition parameters to fit quantitative mapping relationships between parameters and create correspondence tables. Each correspondence table is continuously updated and verified through data collection during real-ship operations to ensure its accuracy and reliability.

[0041] Step 104: Generate an agitation stroke curve by combining the sludge depth and agitation force, and in response to the generation of the agitation stroke curve, send a sludge agitation command to facilitate the suction of sludge by a sludge pump and its transportation through pipelines.

[0042] The agitation stroke curve refers to the complete sequence of process parameters that control the reamer to gradually penetrate from the surface of the silt to the bottom layer of the silt, while simultaneously controlling the actual agitation force to gradually approach the agitation force from the initial value at the surface. It includes the reamer's sinking depth command and the corresponding target agitation force command at each moment. The target force corresponding to each intermediate depth is determined by interpolation according to the mapping relationship between silt depth and agitation force, so that the reamer cuts with a force adapted to the density of that depth at each depth during the layer-by-layer penetration process.

[0043] The sludge agitation command is a device control signal generated based on the agitation stroke curve. It is used to drive the lifting mechanism and rotary drive mechanism of the reamer to cut the bottom sludge layer by layer according to the planned depth and force. This command is generated by the central controller and sent to the lifting drive and rotary drive via CAN bus or industrial Ethernet, so that the reamer gradually penetrates from the sludge surface to the designed depth according to the agitation stroke curve. The actual output torque at each depth changes with the target agitation force command, so that the mud pump can suck in the mud formed by the reamer layer by layer through the suction port and transport it to the designated location through the pipeline.

[0044] By responding to the dredging bottom-touching command and collecting the agitation load, and when the agitation load is too large, the dredging location and engineering depth are retrieved. The water depth is estimated using the bottom-touching time, and the silt depth is determined by combining the difference between the engineering depth and the water depth. Based on this, the agitation force is matched and an agitation stroke curve is generated. This enables automatic silt depth sensing and stroke planning based on load time-series characteristics, without relying on dedicated depth sounding equipment, thus improving the adaptability of operations in shallow water areas.

[0045] A cleaning method based on water conservancy projects also includes: Step 105: Retrieve the cutter depth and cutter speed from the sludge agitation command, and compare the cutter depth with the water depth to determine the agitation depth.

[0046] The reamer depth refers to the absolute depth position of the reamer, that is, the vertical distance from the water surface to the reamer. The reamer speed refers to the speed at which the reamer rotates around its drive shaft, which can be directly retrieved from the sludge stirring command.

[0047] The agitation depth refers to the depth to which the reamer cuts into the silt layer. It is equal to the reamer depth minus the water depth. A positive value indicates that the reamer has entered the silt layer, while a zero or negative value indicates that the reamer has not yet come into contact with the silt.

[0048] Step 106: Determine the mud concentration by combining the agitation depth and cutter rotation speed, and set the reference suction speed.

[0049] Mud concentration refers to the volume or mass percentage of solid particles in the mud-water mixture formed after the auger cuts the bottom mud and mixes with the water. The greater the agitation depth, the deeper the auger cuts into the silt layer, the more bottom mud is cut per unit time, and the higher the mud concentration. The higher the auger speed and the faster the cutting frequency, the higher the mud concentration will also be. The mud concentration corresponding to agitation depth and auger speed can be found in the mud concentration correspondence table. The mud concentration correspondence table is a data table that records different agitation depths and auger speeds and their corresponding mud concentrations.

[0050] The reference suction speed refers to the standard rotational speed of the mud pump at the current setting. It can be initially set by the operator and then retrieved directly from the system after the system executes steps 105 to 107 to obtain the dynamically adjusted suction speed.

[0051] Step 107: Compare the mud concentration with the reference suction rate to determine the concentration deviation, and determine the corrected suction rate based on the concentration deviation.

[0052] Concentration deviation refers to the residual mud concentration value after mud is extracted according to the reference suction rate. The higher the mud concentration and the lower the reference suction rate, the more residual mud there is, and the greater the concentration deviation. The concentration deviation corresponding to the mud concentration and the reference suction rate can be found in the concentration deviation table. The concentration deviation table is a data table that records different mud concentrations and reference suction rates and their corresponding concentration deviations.

[0053] Corrected suction speed refers to the amount of mud pump speed adjustment based on the magnitude and direction of the concentration deviation, on the basis of the reference suction speed. When the concentration deviation is positive, the suction speed is increased; when the deviation is negative, the suction speed is decreased. The corrected suction speed corresponding to the concentration deviation can be found in the corrected suction speed correspondence table, which is a data table that records different concentration deviations and their corresponding corrected suction speeds.

[0054] Step 108: In response to the generation of the modified suction rate and the reference suction rate, a mud suction command is sent.

[0055] The mud suction command is a device control signal generated based on the corrected suction speed. It is used to drive the variable frequency speed control device of the mud pump to adjust the speed of the mud pump to the target suction speed value. The target suction speed value can be calculated as the sum of the corrected suction speed and the reference suction speed. This command is generated by the central controller and sent to the mud pump frequency converter through CAN bus or industrial Ethernet, so that the conveying capacity of the mud pump matches the digging speed of the cutter head, ensuring that the mud is continuously and stably conveyed in the pipeline without pipe blockage or energy waste.

[0056] The reamer depth and reamer speed are retrieved from the sludge agitation command. The agitation depth is determined by combining the water depth and the sludge concentration. The concentration deviation is generated by comparing the agitation depth and the speed with the reference suction speed. The corrected suction speed is then determined to adjust the sludge pump suction speed in a closed loop. This establishes a sludge concentration prediction and suction speed adaptive adjustment mechanism based on real-time operating conditions, reducing the situation where excessively high sludge concentration leads to pipe blockage or excessively low concentration reduces the conveying efficiency.

[0057] A cleaning method based on water conservancy projects also includes: Step 109: Determine the reference load by combining the agitation depth and the cutter speed, and compare the agitation load with the reference load to determine the load deviation.

[0058] The reference load refers to the theoretical cutting resistance that a reamer should generate when cutting standard soil under the current stirring depth and reamer speed conditions. The greater the stirring depth and reamer speed, the greater the reference load. The reference load corresponding to the stirring depth and reamer speed can be found in the reference load correspondence table. The reference load correspondence table is a data table that records different stirring depths and reamer speeds and their corresponding reference loads.

[0059] Load deviation refers to the difference between the measured agitation load and the reference load. A positive value indicates that the actual resistance is greater than the theoretical expectation, indicating that the soil is relatively hard; a negative value indicates that the actual resistance is less than the theoretical expectation, indicating that the soil is relatively soft.

[0060] Step 110: When the load deviation is greater than the preset error threshold, determine the deviation ratio based on the load deviation and the reference load.

[0061] The error threshold is a preset allowable range of load deviation. When the load deviation exceeds this threshold, it indicates that the current soil is too hard and the speed of the cutter needs to be adjusted to avoid damage to the cutter. The error threshold can be determined by experimental calibration, that is, by testing the fluctuation range of load deviation when the cutter cuts in standard soil and taking the boundary value of this range as the error threshold.

[0062] The deviation ratio is the ratio of the load deviation to the reference load. The calculation formula is Deviation ratio = Load deviation / Reference load, which reflects the degree of deviation of the actual soil hardness from the standard soil hardness.

[0063] Step 111: Combine the aforementioned deviation ratio and load deviation to determine the deceleration ratio.

[0064] The retarding ratio refers to the proportion by which the reamer speed needs to be reduced relative to the current speed. It is used to reduce the speed when the reamer encounters hard soil to reduce cutting resistance, protect the equipment, and ensure cutting quality. The larger the deviation ratio and load deviation, the harder the soil, and the greater the speed reduction required, resulting in a larger retarding ratio. The retarding ratio corresponding to the deviation ratio and load deviation can be found in the retarding ratio correspondence table, which is a data table that records different deviation ratios and load deviations and their corresponding retarding ratios.

[0065] Step 112: Update the agitation stroke curve in response to the slowing ratio.

[0066] The cutter speed at each moment in the agitation stroke curve is multiplied by (1 - deceleration ratio) to reduce the cutter speed from the current value to the target speed. The cutter speed is reduced overall in the updated agitation stroke curve. The cutter operates at a lower speed when cutting hard soil to avoid overload and excessive wear. The updated agitation stroke curve replaces the original curve as the control basis for subsequent cutter movement. It is stored and executed by the central controller. At the same time, the updated cutter speed is output to step 105 to recalculate the mud concentration prediction value.

[0067] The reference load is determined by combining the agitation depth and the cutter speed. The load deviation is calculated by comparing the actual agitation load with the reference load. When the load deviation is too large, the deviation ratio is determined and the deceleration ratio is matched. The agitation stroke curve is dynamically updated accordingly, thereby establishing a deceleration protection mechanism based on load feedback. When the actual load deviates from the theoretical expectation, the cutter speed is automatically adjusted to reduce the possibility of equipment overload damage.

[0068] Reference Figure 3 Methods for correcting the slowdown ratio include: Step 200: When the load deviation is greater than a preset error threshold, the deviation time is determined by comparing the load deviation with the preset error threshold.

[0069] The deviation moment refers to the moment when the absolute value of the load deviation first exceeds the error threshold, and the moment when the absolute value of the load deviation jumps from below the threshold to above the threshold each time thereafter. By comparing the load deviation time series data with the threshold in real time, all the jump moments are recorded as deviation moments.

[0070] Step 201: Determine the deviation frequency based on the deviation time, and determine the error coefficient based on the reamer depth.

[0071] Deviation frequency refers to the number of deviation moments per unit time. The number of deviation moments can be counted within a sliding time window, and the deviation frequency is obtained by dividing the number by the window duration. Deviation frequency reflects the frequency of soil fluctuations encountered by the reamer during the cutting process. The higher the frequency, the more hard particles are encountered per unit time.

[0072] The error coefficient is used to characterize the degree of contamination of load measurement values ​​by external interference. The deeper the reamer, the greater the water pressure and the more complex the mechanical vibration, resulting in a larger error coefficient. The error coefficient corresponding to the reamer depth can be found in the error coefficient correspondence table. The error coefficient correspondence table is a data table that records different reamer depths and their corresponding error coefficients. This data table was calibrated through no-load calibration experiments at different depths.

[0073] Step 202: Match the corresponding benchmark ratio according to the deviation ratio, and determine the error ratio by combining the benchmark ratio and the error coefficient.

[0074] The reference ratio refers to the proportion of the load deviation actually caused by the difference in soil particle properties under ideal conditions without external interference. The reference ratio corresponding to the deviation ratio can be found in the reference ratio correspondence table. The reference ratio correspondence table is a data table that records different deviation ratios and their corresponding reference ratios. This data table is obtained by combining cutting experiments in standard soil with statistical analysis of load deviations.

[0075] Error ratio refers to the proportion of load deviation affected by external interference. The calculation formula is: Error ratio = Reference ratio * Error coefficient. The larger the error ratio, the more serious the external interference is to the current load data, and the lower the reliability of the data.

[0076] Step 203: Eliminate interference in the deviation frequency according to the error ratio to predict the particle density in the sludge, and count the load deviation as the total resistance.

[0077] Particle density refers to the density of solid particles in silt, reflecting the compactness of the bottom mud. The higher the particle density, the more times the cutting teeth collide, and the higher the deviation frequency. Since the deviation frequency is mixed with false fluctuations caused by external interference, it is necessary to remove the interference part to obtain the effective frequency caused by particle collision. Effective frequency = deviation frequency * (1 - error ratio). The particle density corresponding to the effective frequency can be found in the particle density correspondence table. The particle density correspondence table is a data table that records different effective frequencies and their corresponding particle densities. This data table is calibrated by cutting experiments on standard bottom mud of different densities combined with load spectrum analysis.

[0078] The total resistance refers to the sum of all load deviations exceeding the error threshold within a unit of time, reflecting the total resistance encountered by the reamer during the cutting process within the sliding time window.

[0079] Step 204: Analyze the particle density and total resistance to determine the particle size, and combine the particle density and particle size to determine the particle coefficient.

[0080] Particle size refers to the equivalent diameter of solid particles in silt. The greater the total obstruction, the stronger the obstruction effect caused by hard particles in the silt. The smaller the particle density, the fewer hard particles there are in the silt. Therefore, the larger the particle size of the hard particles, the greater the obstruction effect. The particle size corresponding to particle density and total obstruction can be found in the particle size correspondence table. The particle size correspondence table is a data table that records different particle densities and total obstruction and their corresponding particle sizes. This data table is calibrated by cutting experiments of standard particles of different sizes combined with load measurement.

[0081] The particle coefficient is a comprehensive index used to characterize the physical properties of the current sediment and the ease of cutting with a reamer. The larger the particle density and the coarser the particle size, the larger the particle coefficient, indicating that the sediment is more difficult to cut. The particle coefficient corresponding to the particle density and particle size can be found in the particle coefficient correspondence table. The larger the particle coefficient, the harder and more difficult the sediment is to cut. It is necessary to further increase the retardation ratio to reduce the reamer speed. That is, calculate the product of the original retardation ratio and (1 + particle coefficient) as the new retardation ratio. The particle coefficient correspondence table is a data table that records different particle densities and particle sizes and their corresponding particle coefficients.

[0082] Step 205: Update the slow ratio in response to the particle coefficient.

[0083] Methods for correcting the slowdown ratio also include: Step 206: When the error ratio is greater than the preset confidence threshold, retrieve multi-source data.

[0084] The confidence threshold is a preset upper limit for the error ratio. When the error ratio exceeds this threshold, it indicates that the current payload data is severely affected by external interference. Relying solely on the error coefficient corresponding to the depth is insufficient to guarantee the inversion accuracy, and more independent data sources need to be introduced for cross-validation.

[0085] Multi-source data refers to a collection of data collected in real time from various types of sensors on dredging equipment, such as water pressure, vibration, and current. This data is then uniformly aggregated to the central controller through a data acquisition module, and the sampling frequency of each data source is synchronized with the time of the load signal.

[0086] Step 207: Extract interference factors from the multi-source data and determine interference weights based on the reamer depth.

[0087] Interference factor refers to the characteristic value extracted from the data of various sensors that can characterize the degree of external interference. For example, for a water pressure sensor, the variance of the water pressure signal per unit time is taken as the interference factor; for a vibration sensor, the energy of the vibration acceleration signal in the cutting frequency band of the reamer is taken as the interference factor; for a motor current sensor, the harmonic distortion rate of the current signal is taken as the interference factor.

[0088] Interference weights are weighting coefficients related to reamer depth, used to characterize the influence of each interference factor on load measurement at different depths. The interference weights of each interference factor corresponding to the reamer depth can be found in the interference weight correspondence table. The interference weight correspondence table is a data table that records different reamer depths and their corresponding interference factor weights. The deeper the reamer, the greater the weight of the water pressure interference factor. This data table was calibrated through sensitivity analysis of the influence of each interference source on load measurement at multiple different depths.

[0089] Step 208: Determine the interference coefficient by combining the interference factor and interference weight.

[0090] The interference coefficient is a comprehensive interference quantification index obtained by weighting and summing each interference factor according to its corresponding interference weight. Each interference factor needs to be normalized before summing to ensure the uniformity of dimensions, and the product of the original error ratio and (1 + interference coefficient) is calculated as the new error ratio.

[0091] Step 209: Update the error ratio in response to the interference coefficient.

[0092] Methods for correcting the slowdown ratio also include: Step 210: When the error ratio is greater than the preset confidence threshold, calculate the density change rate based on the particle density and the particle size change rate based on the particle size.

[0093] The density change rate is the ratio of the change in particle density between the current dredging location and the adjacent dredging location to the spatial distance. It can be obtained by taking the difference between the particle density at the current point and the particle density at the previous measured point along the navigation route, and then dividing by the spatial distance between the two points.

[0094] The particle size change rate refers to the ratio of the change in particle size between the current dredging location and the adjacent dredging location to the spatial distance. It can be obtained by taking the difference between the particle size at the current point and the particle size at the previous measured point along the navigation route, and then dividing it by the spatial distance between the two points.

[0095] Step 211: Determine the consistency threshold based on the interference coefficient, and compare the density change rate, particle size change rate and consistency threshold to determine spatial consistency.

[0096] The consistency threshold is a preset upper limit of spatial change rate, used to determine whether the sediment properties of adjacent locations are consistent. The larger the interference coefficient, the larger the consistency threshold. The judgment standard is more lenient to accommodate measurement fluctuations when the interference is large. The consistency threshold corresponding to the interference coefficient can be found in the consistency threshold correspondence table. The consistency threshold correspondence table is a data table that records different interference coefficients and their corresponding consistency thresholds. This data table is calibrated through statistical analysis of spatial change rate under different interference levels.

[0097] Spatial consistency refers to whether both the density change rate and the particle size change rate are less than the consistency threshold. If both are less than the threshold, the spatial consistency is consistent, indicating that the physical properties of the bottom sediment at adjacent locations are continuous and uniform. If either is greater than the threshold, the spatial consistency is abrupt, indicating that there is a sudden change in soil quality at that location.

[0098] Step 212: If the spatial consistency falls within the preset transition range, determine the idling time according to the error ratio, and generate and send an idling verification command in response to the idling time.

[0099] The jump interval refers to the numerical range of density change rate or particle size change rate. When the spatial consistency is jump, the jump interval judgment is automatically triggered.

[0100] Idle time refers to the duration during which the reamer idles at the target depth. The larger the error ratio, the more severe the interference, and the longer the idle time is required to collect sufficient reference interference signals. The idle time corresponding to the error ratio can be found in the idle time correspondence table. The idle time correspondence table is a data table that records different error ratios and their corresponding idle times. This data table was obtained through experimental calibration of the effectiveness of idle calibration under different interference levels.

[0101] The idle calibration command is a control signal that controls the reamer to stop lateral movement and advance at the target depth, and only maintain rotational movement. This command is generated by the central controller and sent to the reamer's lifting drive mechanism and lateral movement drive mechanism via the CAN bus, so that the reamer enters the idle state.

[0102] Step 213: Retrieve the verification load according to the idle verification command, and extract the reference interference spectrum from the verification load.

[0103] The verification load refers to the load signal of the reamer in an idle state. At this time, the reamer only overcomes water resistance and mechanical friction resistance. The verification load does not contain any effective signals related to particle cutting, but only external interference components such as water pressure and mechanical vibration.

[0104] The reference interference spectrum is the spectrum obtained by converting the verification load to the frequency domain through a fast Fourier transform. The timing signal of the verification load can be windowed and then subjected to a fast Fourier transform to obtain the amplitude values ​​of each frequency component as the reference interference spectrum. The reference interference spectrum reflects the energy distribution of each frequency component under pure interference conditions.

[0105] Step 214: Extract the actual load from the agitation load based on the reamer depth, and subtract the spectrum of the actual load from the reference interference spectrum to obtain the effective load spectrum.

[0106] Actual load refers to the noisy load signal collected during normal cutting operations of the reamer at the current reamer depth, which can be obtained from the continuously collected agitation load based on the current timestamp.

[0107] The effective load spectrum is the spectrum obtained by subtracting the reference interference spectrum from the actual load in the frequency domain. The actual load spectrum can be obtained by adding a Hanning window to the actual load time signal and then performing a fast Fourier transform. The effective load spectrum is obtained by subtracting the amplitude spectrum of the reference interference spectrum from the amplitude spectrum of the actual load spectrum at each frequency point. The effective load spectrum reflects the frequency distribution of the pure load signal generated only by particle cutting after removing external interference components.

[0108] Step 215: Calculate the impedance values ​​from the payload spectrum and match the verification coefficients based on the impedance values.

[0109] The obstacle value refers to the statistical characteristic quantity extracted from the effective load spectrum. It can be used to calculate the total energy of the effective load spectrum by integration. The larger the total energy, the larger the actual cutting load after removing interference.

[0110] The check coefficient is a numerical value that characterizes the accuracy of the load signal. The larger the impedance value, the stronger the effective signal and the higher the data quality. The larger the check coefficient, the higher the quality of the load signal. The error ratio should be further reduced. The check coefficient corresponding to the impedance value can be found in the check coefficient correspondence table. Then, the product of the original error ratio and (1 - check coefficient) is calculated as the new error ratio. The check coefficient correspondence table is a data table that records different impedance values ​​and their corresponding check coefficients. This data table is calibrated through correlation analysis of the inversion accuracy under different signal quality.

[0111] Step 216: Update the error ratio in response to the verification coefficient.

[0112] Soil remediation methods include: Step 300: Match the soil type with the particle density and particle size, and retrieve the navigation route according to the dredging location.

[0113] Soil type refers to the type of sediment classified according to the combination of particle density and particle size. The soil type correspondence table can be used to look up the soil type corresponding to the particle density and particle size. The soil type correspondence table is a data table that records different particle densities and particle sizes and their corresponding soil types. The soil types in the soil type correspondence table are arranged in ascending order of hardness and assigned a corresponding sequence number. For example, the sequence number of silt is 1, the sequence number of silt is 2, the sequence number of sand is 3, and the sequence number of gravel is 4. This data table was obtained by comparing and calibrating the results of laboratory sieve analysis and load inversion of a large number of sediment samples.

[0114] The navigation route refers to the trajectory formed by connecting the dredging locations in sequence. That is, the path formed by connecting all the determined dredging locations in chronological order. It is retrieved from the route recording module of the control system. Each time a dredging location is determined, the coordinates of that location are stored in the route data table in sequence to form a continuous navigation route.

[0115] Step 301: Determine the excavation location by combining the navigation route and the cutter depth, and generate a soil distribution map by combining the soil type and the excavation location.

[0116] The excavation location refers to the three-dimensional spatial position of the reamer during its current operation. It is determined by the geographical coordinates of the dredging location and the reamer depth. The excavation location represents the spatial point corresponding to the bottom mud cut by the reamer at different depths at the same dredging location.

[0117] The soil distribution map is a spatial distribution map generated by marking all excavated locations and their corresponding depths within the work area using three-dimensional spatial coordinates. Specifically, it is a three-dimensional grid map with the dredging location as the horizontal and vertical axes and the reamer depth as the vertical axis. Each three-dimensional grid cell stores the soil type label at that location and depth. Different depths at the same dredging location can correspond to different soil types. Excavated three-dimensional grids are filled with the measured soil types, while unexcavated three-dimensional grids are left blank or filled with default values.

[0118] Step 302: Read the particle change rate of the particle coefficient from the soil distribution map, and expand the soil distribution map based on the particle change rate to form a predicted distribution map.

[0119] The particle change rate refers to the ratio of the variation of the particle coefficient at the same depth between adjacent locations along the navigation route on a soil distribution map to the spatial distance. The particle coefficient at the same depth at each location point can be extracted from the soil distribution map, and the difference in particle coefficient between adjacent points can be calculated and divided by the distance to obtain the particle change rate.

[0120] The predicted distribution map is a predictive soil distribution map of the entire working area obtained by extrapolating the soil distribution map in three dimensions based on the particle change rate. It can be used to extend along the navigation route to the entire working area by utilizing the statistical trend of the particle change rate at each depth in the soil distribution map. The Kriging interpolation method or the inverse distance weighting method is used to infer the soil type at each depth in the unexcavated area, forming a three-dimensional predicted distribution map covering the entire working area. Each three-dimensional grid cell in the predicted distribution map stores the predicted soil type at that location and depth.

[0121] Step 303: Determine the navigation area to be reached based on the navigation route, and read the regional coefficient of the navigation area from the predicted distribution map.

[0122] The navigation area refers to the three-dimensional space that the reamer is about to reach but has not yet excavated along the navigation route. The horizontal area covered by a certain distance extended forward from the end of the navigation route along the navigation direction can be used as the navigation area. The extension distance is determined by the prediction time window, which is 10 to 30 seconds.

[0123] The regional coefficient refers to the comprehensive value of soil characteristics of each three-dimensional grid cell within the navigation area read from the predicted distribution map, and the particle density of each grid cell at the current reamer depth is taken as the regional coefficient.

[0124] Step 304: Calculate the mean of the regional coefficients as the mean coefficient, and determine the prediction ratio based on the mean coefficient.

[0125] The mean coefficient refers to the arithmetic mean of the regional coefficients within the navigation area, reflecting the average soil characteristics of that area at the current cutter depth.

[0126] The predicted ratio refers to the required deceleration ratio under soil conditions with a mean coefficient. The predicted ratio can be calculated by multiplying the deceleration ratio by (1 + mean coefficient). The larger the mean coefficient, the harder the soil ahead, and the larger the predicted ratio, the greater the amount of deceleration needs to be reduced in advance.

[0127] Step 305: Generate a speed transition curve by combining the slowing ratio and the predicted ratio, and update the turbulence stroke curve in response to the speed transition curve.

[0128] The speed transition curve is a speed change curve that smoothly transitions from the current speed to the target speed. Current speed = current speed * (1 - deceleration ratio), target speed = current speed * (1 - prediction ratio). The deceleration ratio represents the deceleration required under the current soil conditions, and the prediction ratio represents the additional deceleration required under the predicted soil conditions ahead. The speed transition curve adopts an S-shaped acceleration and deceleration curve to ensure smooth speed changes without impact.

[0129] Soil remediation methods also include: Step 306: Read the sailing speed based on the sailing route, and analyze the sailing route to determine the extended route forward.

[0130] Sailing speed refers to the current speed of the dredging equipment along the navigation route, which is obtained by calculating the change in displacement in the direction of the navigation route per unit time through the ship's GPS positioning system.

[0131] The extended route refers to a predicted path that extends forward from the current position along the direction of the navigation route. That is, it continues forward from the current end of the navigation route along its tangent direction. The extension distance = navigation speed * prediction time window.

[0132] Step 307: Read the extension coefficient from the predicted distribution map according to the extension route, and generate a coefficient fluctuation curve by combining the extension coefficient and the sailing speed.

[0133] The extension coefficient refers to the comprehensive value of soil characteristics at the current cutter depth at each location point on the extension route read from the predicted distribution map. In other words, the particle coefficient corresponding to the current cutter depth is read point by point along the extension route from the predicted distribution map as the extension coefficient.

[0134] The coefficient fluctuation curve is a curve formed by arranging the extension coefficients of each point on the extension route in spatial order. The horizontal axis is the cumulative distance along the extension route, and the vertical axis is the extension coefficient value. The coefficient fluctuation curve is drawn by connecting each sampling point to form a continuous curve using a linear interpolation method.

[0135] Step 308: Read the rate of change of navigation from the coefficient fluctuation curve.

[0136] The rate of change of the navigation curve refers to the slope of the coefficient fluctuation curve along the extended route. The first derivative of the coefficient fluctuation curve along the distance direction can be obtained. The larger the absolute value of the derivative, the more drastic the change of soil characteristics in a short distance, and there may be steep slopes or abrupt terrain changes.

[0137] Step 309: When the rate of change of navigation is greater than the preset damage threshold, retrieve the damage location based on the rate of change of navigation, and read the altitude fluctuation curve from the predicted distribution map according to the damage location.

[0138] The damage threshold is a preset upper limit for the rate of change of navigation. When the rate of change of navigation exceeds this threshold, it indicates that there is a drastic change in soil or terrain ahead. If the operation continues at the current reamer height, a collision may occur, resulting in equipment damage. The damage threshold is determined by checking the mechanical structural strength of the equipment.

[0139] Damage location refers to the location point on the extended route corresponding to the rate of change of navigation exceeding the damage threshold, which is determined by finding the point in the coefficient fluctuation curve where the slope exceeds the threshold.

[0140] The height fluctuation curve refers to the curve showing the change of particle coefficient at different depths at the damaged location from the predicted distribution map. The horizontal axis represents the reamer depth, i.e., the vertical position, and the vertical axis represents the particle coefficient value. This curve reflects the soil distribution characteristics at the damaged location in the vertical direction.

[0141] Step 310: Determine the protection coefficient by combining the coefficient fluctuation curve and the preset damage threshold, and query the protection height from the height fluctuation curve according to the protection coefficient.

[0142] The protection coefficient refers to the critical particle coefficient at which the reamer is just undamaged at the damage location. That is, the actual particle coefficient at the damage location under the drastic soil quality change corresponding to the damage threshold. The particle coefficient of the previous sampling point before the damage location can be read from the coefficient fluctuation curve as the reference coefficient. The location of the previous sampling point can be read as the reference position. The distance between the reference position and the damage location can be calculated as the damage distance. Then, the product of the damage distance and the damage threshold can be calculated as the coefficient increment. Finally, the sum of the reference coefficient and the coefficient increment can be calculated as the protection coefficient.

[0143] The protection height refers to the safe depth to which the reamer needs to be raised to avoid collisions with hard interlayers or abrupt soil changes. The protection height can be found in the height fluctuation curve at the depth where the particle coefficient is equal to the protection coefficient. In other words, in the height fluctuation curve, the depth range where the particle coefficient is less than or equal to the protection coefficient is the safe operating depth range for the reamer, while the depth range where the particle coefficient is greater than the protection coefficient carries the risk of reamer damage.

[0144] Step 311: Generate the reamer extension stroke by combining the protection height and the extension path, and update the agitation stroke curve in response to the reamer extension stroke.

[0145] The reamer extension stroke refers to the sequence of vertical displacement trajectory parameters of the reamer at various points along the extension route, from the current depth to the protection height. The updated agitation stroke curve incorporates the reamer extension stroke into the reamer's motion trajectory planning, so that the equipment automatically raises the reamer to the protection height before reaching the damaged position along the navigation route to avoid hard interlayers or soil abrupt change layers, and then returns to the normal working depth after passing the damaged position.

[0146] Soil remediation methods also include: Step 312: If the spatial consistency falls within the preset jump range, determine the mutation type by combining the particle density and particle size.

[0147] Mutation type refers to the abnormal soil type that appears at the current excavation location based on the combination characteristics of particle density and particle size. The soil type corresponding to the particle density and particle size at the current point can be found in the soil type correspondence table as the mutation type.

[0148] Step 313: Based on the dredging location, read the surrounding species from the predicted distribution map and compare the mutated species with the surrounding species to determine the species difference.

[0149] Surrounding types refer to the set of soil types of each three-dimensional grid cell in the vicinity of the current dredging location, read from the predicted distribution map. The vicinity is defined as a range with a radius of 1 meter centered on the current dredging location.

[0150] The species difference refers to the degree of difference between the mutation species and the surrounding species. It can be obtained by reading the corresponding sequence number of the mutation species and the surrounding species from the soil type correspondence table, and calculating the absolute value of the difference between the sequence numbers as the species difference. The smaller the species difference, the closer the mutation species is to the surrounding species, and the more likely the jump is to be noise or measurement error.

[0151] Step 314: When the difference between the types is less than a preset possible threshold, the jump load is extracted from the agitation load, and the spectral characteristics of the jump load are extracted to obtain the jump frequency.

[0152] The threshold may be a preset upper limit for the species difference. When the species difference is less than the threshold, it indicates that there may be a mutation in the species in the surrounding soil. The jump may be a real change in soil quality, which needs to be further verified by frequency domain analysis to eliminate noise interference.

[0153] A jump load refers to a segment of agitated load signal collected within a sampling window before and after the jump occurs. The sampling window length is set to 5 seconds before and 5 seconds after the jump.

[0154] The jump frequency refers to the main peak frequency extracted after the jump load is converted to the frequency domain by Fast Fourier Transform. The jump load signal can be windowed by Hanning and then subjected to Fast Fourier Transform to obtain the spectrum. The frequency corresponding to the maximum amplitude in the spectrum is read as the jump frequency.

[0155] Step 315: Match the cutting frequency according to the reamer rotation speed, and compare the cutting frequency and the jump frequency to determine the frequency difference.

[0156] Cutting frequency refers to the load fluctuation frequency generated by the periodic cutting of the bottom mud by the cutting teeth during normal cutting process of the reamer. The calculation formula is: cutting frequency = reamer speed * number of cutting teeth / 60, where the number of cutting teeth is preset by the operator.

[0157] Frequency difference refers to the ratio of the difference between the switching frequency and the cutting frequency. When the frequency difference is less than 10%, it indicates that the switching frequency matches the cutting frequency, the fluctuation of the switching load is synchronized with the periodic cutting action of the reamer, and the switching is caused by the actual soil changes. When the frequency difference is greater than 30%, it indicates that the switching frequency does not match the cutting frequency, and the switching may be caused by external random interference or sensor noise.

[0158] Step 316: Update the idling time in response to the frequency difference.

[0159] When the frequency difference is small, it indicates that although the jump is not much different from the surrounding soil, the fluctuation frequency is synchronized with the cutting frequency, which may still be a real soil change. Idle calibration needs to be performed for further confirmation. When the frequency difference is large, the jump is determined to be sensor noise, and the idle time is set to zero to skip the idle calibration.

[0160] Based on the same inventive concept, embodiments of the present invention provide a cleaning system based on water conservancy projects, comprising: The acquisition module is used to acquire the agitation load; A memory for storing programs for any of the aforementioned cleaning methods based on water conservancy projects; The processor is the unit of memory that allows programs to be loaded and executed by the processor.

[0161] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0162] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A cleaning method based on water conservancy projects, characterized in that, include: Step 100: Collect the agitation load in response to the preset dredging and bottom contact command; Step 101: When the agitation load is greater than the preset contact threshold, retrieve the dredging location based on the agitation load, and retrieve the engineering depth based on the dredging location; Step 102: Determine the bottom contact time based on the agitation load, and determine the water depth based on the bottom contact time; Step 103: Determine the silt depth by comparing the engineering depth and the water depth, and match the stirring force according to the silt depth; Step 104: Generate an agitation stroke curve by combining the sludge depth and agitation force, and in response to the generation of the agitation stroke curve, send a sludge agitation command to facilitate the suction of sludge by a sludge pump and its transportation through pipelines.

2. The cleaning method based on water conservancy engineering according to claim 1, characterized in that, Also includes: Step 105: Retrieve the cutter depth and cutter speed from the sludge agitation command, and compare the cutter depth with the water depth to determine the agitation depth; Step 106: Determine the mud concentration by combining the agitation depth and cutter rotation speed, and set the reference suction speed; Step 107: Compare the mud concentration with the reference suction rate to determine the concentration deviation, and determine the corrected suction rate based on the concentration deviation; Step 108: In response to the generation of the modified suction rate and the reference suction rate, a mud suction command is sent.

3. A method of cleaning based on hydraulic engineering according to claim 2, characterized in that, Also includes: Step 109: Determine the reference load by combining the agitation depth and the reamer speed, and compare the agitation load with the reference load to determine the load deviation; Step 110: When the load deviation is greater than a preset error threshold, determine the deviation ratio based on the load deviation and the reference load; Step 111: Match the deceleration ratio by combining the aforementioned deviation ratio and load deviation; Step 112: Update the agitation stroke curve in response to the slowing ratio.

4. A method of cleaning based on hydraulic engineering according to claim 3, characterized in that, It also includes a method for correcting the retardation ratio, the method comprising: Step 200: When the load deviation is greater than a preset error threshold, compare the load deviation with the preset error threshold to determine the deviation time; Step 201: Determine the deviation frequency based on the deviation time, and determine the error coefficient based on the reamer depth; Step 202: Match the corresponding benchmark ratio according to the deviation ratio, and determine the error ratio by combining the benchmark ratio and the error coefficient; Step 203: Eliminate interference in the deviation frequency according to the error ratio to predict the particle density in the sludge, and count the load deviation as the total resistance. Step 204: Analyze the particle density and total resistance to determine the particle size, and combine the particle density and particle size to determine the particle coefficient; Step 205: Update the slow ratio in response to the particle coefficient.

5. A method of cleaning based on hydraulic engineering according to claim 4, characterized in that, The method for correcting the retarding ratio also includes: Step 206: When the error ratio is greater than the preset confidence threshold, retrieve multi-source data; Step 207: Extract interference factors from the multi-source data and determine interference weights based on the reamer depth; Step 208: Determine the interference coefficient by combining the interference factor and the interference weight; Step 209: Update the error ratio in response to the interference coefficient.

6. A method of cleaning based on hydraulic engineering according to claim 5, characterized in that, The method for correcting the retarding ratio also includes: Step 210: When the error ratio is greater than a preset confidence threshold, calculate the density change rate based on the particle density and the particle size change rate based on the particle size. Step 211: Determine the consistency threshold based on the interference coefficient, and compare the density change rate, particle size change rate and consistency threshold to determine spatial consistency; Step 212: If the spatial consistency falls within the preset transition range, determine the idling time according to the error ratio, and generate and send an idling verification command in response to the idling time. Step 213: Retrieve the verification load according to the idle verification command, and extract the reference interference spectrum from the verification load; Step 214: Extract the actual load from the agitation load based on the reamer depth, and subtract the spectrum of the actual load from the reference interference spectrum to obtain the effective load spectrum; Step 215: Calculate the impedance values ​​from the payload spectrum and match the verification coefficients based on the impedance values; Step 216: Update the error ratio in response to the verification coefficient.

7. A method of cleaning based on hydraulic engineering according to claim 6, characterized in that, It also includes soil remediation methods, which include: Step 300: Match the soil type with the particle density and particle size, and retrieve the navigation route according to the dredging location; Step 301: Determine the excavation location by combining the navigation route and the cutter depth, and generate a soil distribution map by combining the soil type and the excavation location; Step 302: Read the particle size variation rate of the particle size coefficient from the soil distribution map, and expand the soil distribution map based on the particle size variation rate to form a predicted distribution map; Step 303: Determine the navigation area to be reached based on the navigation route, and read the regional coefficient of the navigation area from the predicted distribution map; Step 304: Calculate the mean value of the regional coefficients as the mean coefficient, and determine the prediction ratio based on the mean coefficient; Step 305: Generate a speed transition curve by combining the slowing ratio and the predicted ratio, and update the turbulence stroke curve in response to the speed transition curve.

8. A method of cleaning based on hydraulic engineering according to claim 7, characterized in that, The soil remediation method also includes: Step 306: Read the sailing speed based on the sailing route, and analyze the sailing route to determine the extended route forward; Step 307: Read the extension coefficient from the predicted distribution map according to the extension route, and generate a coefficient fluctuation curve by combining the extension coefficient and the sailing speed; Step 308: Read the rate of change of navigation from the coefficient fluctuation curve; Step 309: When the rate of change of navigation is greater than the preset damage threshold, retrieve the damage location based on the rate of change of navigation, and read the altitude fluctuation curve from the predicted distribution map according to the damage location; Step 310: Determine the protection coefficient by combining the coefficient fluctuation curve and the preset damage threshold, and query the protection height from the height fluctuation curve according to the protection coefficient; Step 311: Generate the reamer extension stroke by combining the protection height and the extension path, and update the agitation stroke curve in response to the reamer extension stroke.

9. A cleaning method based on water conservancy engineering according to claim 8, characterized in that, The soil remediation method also includes: Step 312: If the spatial consistency falls within a preset jump range, determine the mutation type by combining the particle density and particle size; Step 313: Based on the dredging location, read the surrounding species from the predicted distribution map, and compare the mutated species with the surrounding species to determine the species difference; Step 314: When the difference between the types is less than a preset possible threshold, the jump load is extracted from the agitation load, and the spectral characteristics of the jump load are extracted to obtain the jump frequency; Step 315: Match the cutting frequency according to the reamer rotation speed, and compare the cutting frequency with the jump frequency to determine the frequency difference; Step 316: Update the idling time in response to the frequency difference.

10. A cleaning system based on water conservancy engineering, characterized in that, include: The acquisition module is used to acquire the agitation load; A memory for storing a program of a cleaning method based on a water conservancy project as described in any one of claims 1 to 9; The processor is the unit of memory that allows programs to be loaded and executed by the processor.

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