Counterweight increasing method and system for dynamic balance of hub

Abstract

The invention belongs to the technical field of dynamic balance weight control and optimization of hubs, and particularly provides a balance weight increasing method and system for dynamic balance of a hub, and the method mainly comprises the steps: obtaining the current unbalance weight and angle information of the hub, and generating initial data; preprocessing the initial data to obtain an anti-vibration optimization coordinate; performing counterweight parameter collaborative calculation and dynamic optimization based on the anti-vibration optimization coordinates to obtain optimized counterweight parameters; generating an executable instruction for the optimized counterweight parameter; according to the executable instruction, counter weight adding and real-time state monitoring are carried out, and a hub balance index is generated; and feedback regulation and iterative control are executed according to the hub balance index, and a final balance confirmation signal is output. According to the method, high-precision automatic adjustment of the dynamic balance weight of the hub is realized, the human input and the operation time are reduced, the balance precision is stable and reaches the standard, meanwhile, the operation efficiency and the overall stability are improved through dynamic monitoring and iterative optimization, and the labor cost and the operation time consumption are reduced.

Description

Technical Field

[0001] This invention belongs to the field of wheel hub dynamic balancing counterweight control and optimization technology, and specifically relates to a method and system for increasing counterweights to achieve dynamic balancing of wheel hubs. Background Technology

[0002] In the production and maintenance of wheel hubs, dynamic balancing is a key step in ensuring their operational stability. After the dynamic balancing instrument detects the unbalanced weight and angle data of the wheel hub, the counterweight operation must be carried out with the equipment completely stopped. The operator must first disassemble the wheel hub, manually calculate the weight of the required counterweight based on the test data, fix the counterweight in the corresponding position by welding, and then reinstall the wheel hub and adjust it again. During the process, the integrity of the wheel hub structure must be taken into account, and the weight of the weld bead must be manually compensated.

[0003] In the above process, the counterweight operation is highly dependent on manual intervention. From data interpretation and counterweight calculation to welding and installation, everything is done manually. Manual calculation is prone to errors, and repeated disassembly and debugging steps increase the operation time. This not only makes it difficult to consistently achieve the standard requirements for balance accuracy, but also significantly increases labor costs and overall operation time due to the high repetition of the process. Summary of the Invention

[0004] This application provides a method and system for adding counterweights to achieve dynamic balancing of wheel hubs. It effectively solves the problems of large calculation errors, time-consuming repeated disassembly and assembly, and unstable balancing accuracy caused by manual operation of counterweights in the prior art. It realizes high-precision automated adjustment of wheel hub dynamic balancing counterweights, reduces manpower input and operation time, and ensures stable balancing accuracy. At the same time, it improves work efficiency and overall stability through dynamic monitoring and iterative optimization, and reduces labor costs and operation time.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: Firstly, this application provides a method for increasing the counterweight in dynamic balancing of a wheel hub, including: Obtain the current unbalanced weight and angle information of the wheel hub to generate initial data.

[0006] The initial data is preprocessed to obtain the vibration-optimized coordinates.

[0007] Based on the vibration-damping optimized coordinates, the counterweight parameters are calculated and dynamically optimized to obtain the optimized counterweight parameters.

[0008] Executable instructions are generated for the optimized counterweight parameters.

[0009] The system adds counterweights and monitors the real-time status according to the executable instructions, generating wheel hub balance indices.

[0010] Feedback adjustment and iterative control are performed based on the hub balance index, and a final balance confirmation signal is output.

[0011] Furthermore, the current unbalanced weight and angle information of the wheel hub are obtained to generate initial data, including: The system collects raw data on wheel hub weight and angle from the dynamic balancing instrument, performs noise filtering, and outputs purified weight and angle values.

[0012] By combining the wheel hub structure parameters with the purification weight angle value, a collaborative matching analysis is performed to generate the initial counterweight requirement parameters.

[0013] Furthermore, the initial data is preprocessed to obtain vibration-optimized coordinates, including: Based on the initial counterweight requirement parameters, environmental dynamic calibration is performed to obtain the calibrated counterweight reference.

[0014] Multi-source data cross-validation is performed on the calibrated counterweight reference to generate validation pass command data.

[0015] The axial vibration spectrum of the wheel hub is acquired in real time, and the dominant vibration characteristics are extracted from the verification pass command data.

[0016] Based on the dominant vibration characteristics, an anti-phase cancellation operation of the vibration waveform is performed, and vibration-resistant optimized coordinates are output.

[0017] Furthermore, based on the vibration-optimized coordinates, collaborative calculation and dynamic optimization of the counterweight parameters are performed to obtain optimized counterweight parameters, including: Based on the vibration-optimized coordinates, the weight and angle are calculated to generate a counterweight combination scheme.

[0018] The weight distribution of the weight combination scheme is optimized and adjusted, and the optimized weight allocation value is output.

[0019] The optimized weight distribution value is adjusted by combining the bolt constraint conditions to generate the adjusted angular coordinates.

[0020] Based on the adjusted angular coordinates, real-time error compensation calculations are performed, and precise counterweight parameters are output as optimized counterweight parameters.

[0021] Furthermore, executable instructions are generated for the optimized counterweight parameters, including: Based on the precise counterweight parameters, bolt fixing control commands are generated, and primary execution signals are output.

[0022] The primary execution signal is verified based on the dynamic balancing instrument status data, and a verification pass instruction is generated.

[0023] Based on the verification pass command, the hub angle is automatically positioned and the target angle coordinates are output.

[0024] Based on the target angle coordinates, the installation path of the counterweight is planned, and the final execution path is generated.

[0025] Calculate the preload gradient for the final execution path based on the bolt group distribution coordinates, and output the anti-deformation pressure threshold.

[0026] By coordinating the adjustment of bolt installation sequence and torque parameters, the anti-deformation pressure threshold is converted into an anti-deformation execution command.

[0027] Furthermore, based on the executable instructions, counterweights are added and real-time status monitoring is performed to generate wheel hub balance indicators, including: The trigger bolt fixing device executes the anti-deformation execution command, and the generating device provides real-time feedback.

[0028] The device provides real-time feedback to monitor the installation progress of the counterweight and outputs real-time position data.

[0029] The weight distribution status is verified based on the real-time location data, and an installation consistency report is generated.

[0030] The balance status in the installation consistency report is evaluated, and the wheel hub balance index is output as the balance status index.

[0031] Furthermore, feedback adjustment and iterative control are performed based on the hub balance index to output a final balance confirmation signal, including: Analyze the residual imbalance in the wheel hub balance index to generate a residual error dataset.

[0032] Based on the residual error dataset, the iteration requirement is determined, and a test repetition flag is output.

[0033] Based on the test repetition flag, the system parameters are dynamically reconfigured to generate update test instructions.

[0034] According to the dynamic balancing instrument restart test procedure, the updated test command is converted into the final balance signal.

[0035] Furthermore, by coordinating and adjusting the bolt installation sequence and torque parameters, the anti-deformation pressure threshold is converted into an anti-deformation execution command, including: Based on the stress distribution analysis of the anti-deformation pressure threshold, a stress spectrum of the bolt group is generated.

[0036] Based on the force diagram of the bolt group, a diagonal cross installation strategy is formulated to obtain the installation sequence strategy.

[0037] The torque gradient value is calculated based on the installation sequence strategy, and an anti-deformation execution command is generated.

[0038] Furthermore, based on the dominant vibration characteristics, a vibration waveform anti-phase cancellation operation is performed to output vibration-damping optimized coordinates, including: Phase data of vibration waveforms are extracted based on the dominant vibration characteristics to generate inverse phase waveform data.

[0039] An amplitude matching calculation is performed on the inverted waveform data, and the inverted cancellation result is output.

[0040] The offset of the counterweight position is adjusted based on the anti-phase cancellation result to generate vibration-optimized coordinates.

[0041] Secondly, this application provides a system for increasing counterweights to achieve dynamic balancing of a wheel hub, comprising: Initial data acquisition module: Acquires the current unbalanced weight and angle information of the wheel hub and generates initial data.

[0042] Data preprocessing module: preprocesses the initial data to obtain vibration-optimized coordinates; Parameter calculation and optimization module: Based on the vibration optimization coordinates, perform collaborative calculation and dynamic optimization of counterweight parameters to obtain optimized counterweight parameters.

[0043] Counterweight instruction generation module: Generates executable instructions for the optimized counterweight parameters.

[0044] Monitoring module: Implements counterweight addition and real-time status monitoring based on the executable instructions, and generates wheel hub balance index.

[0045] Feedback Iteration Module: Performs feedback adjustment and iterative control based on the hub balance index, and outputs a final balance confirmation signal.

[0046] Thirdly, this application provides a device for adding counterweights to dynamically balance a wheel hub, which includes a memory and a processor; the memory is used to store a computer program; the processor is used to execute the computer program to implement the steps of the method for adding counterweights to dynamically balance a wheel hub as described in the first aspect.

[0047] Fourthly, this application provides a storage medium storing computer program instructions, which, when read and executed by a processor, perform the steps of the method for increasing counterweight for dynamic balancing of the wheel hub as described in the first aspect.

[0048] The beneficial effects of this invention are: This application employs a scheme that automatically acquires wheel hub imbalance data, preprocesses it to generate optimized coordinates, calculates counterweight parameters through collaborative calculations to generate execution commands, and simultaneously implements counterweight addition and status monitoring. It also incorporates feedback iterative control based on balance indicators to achieve fully automated operation. This effectively solves the problems of large calculation errors, time-consuming repetitive disassembly and assembly, and unstable balance accuracy caused by manual counterweight operation in existing technologies. It eliminates the uncertainty brought about by manual intervention, breaks through the limitations of traditional manual operation with machine stoppage, and achieves high-precision automated adjustment of wheel hub dynamic balancing counterweights. This reduces manpower input and operation time, ensuring stable balance accuracy. Simultaneously, dynamic monitoring and iterative optimization improve operational efficiency and overall stability, reducing labor costs and operation time.

[0049] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description and the drawings. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1 A schematic flowchart of a method for adding counterweights to achieve dynamic balancing of a wheel hub according to the present invention is shown. Figure 2 A schematic diagram of a wheel hub dynamic balancing system with added counterweights is shown. Detailed Implementation

[0052] To address the problems raised in the background technology, this application adopts a scheme that automatically acquires wheel hub imbalance data, preprocesses it to generate optimized coordinates, obtains counterweight parameters through collaborative calculation, generates execution instructions, synchronously implements counterweight addition and status monitoring, and combines balance indicators for feedback iterative control, thereby achieving fully automated operation.

[0053] 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, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] In some embodiments, such as Figure 1 As shown, this application provides a method for increasing the counterweight for dynamic balancing of a wheel hub, including: S1. Obtain the current unbalanced weight and angle information of the wheel hub and generate initial data.

[0055] S2. Preprocess the initial data to obtain the vibration-optimized coordinates.

[0056] S3. Based on the vibration-damping optimization coordinates, perform collaborative calculation and dynamic optimization of the counterweight parameters to obtain the optimized counterweight parameters.

[0057] S4. Generate executable instructions for optimizing counterweight parameters.

[0058] S5. Implement counterweight addition and real-time status monitoring based on executable instructions, and generate wheel hub balance index.

[0059] S6. Perform feedback adjustment and iterative control based on the wheel hub balance index, and output the final balance confirmation signal.

[0060] In some embodiments, obtaining the current unbalanced weight and angle information of the wheel hub in S1 and generating initial data includes: S11. Collect the raw data of wheel hub weight and angle output by the dynamic balancing instrument, perform noise filtering processing, and output the purified weight and angle values.

[0061] A dynamic balancing instrument is used to detect the balance of mass distribution in a rotating wheel hub. The raw wheel hub weight data output by the dynamic balancing instrument represents the mass value of the counterweight required at a specific position of the wheel hub. It is measured by a centrifugal force sensor and generated by analog-to-digital conversion. The raw angle data represents the azimuth angle of the counterweight position relative to the zero degree reference of the wheel hub. It is recorded in real time by an angle encoder.

[0062] The raw data of wheel hub weight and angle are subject to mechanical vibration noise and electromagnetic interference during the acquisition process. The raw data can be processed by a windowed finite-length unit impulse response filtering algorithm to obtain the filtered purified weight and angle values.

[0063] S12. Perform a collaborative matching analysis on the purification weight angle value based on the wheel hub structure parameters to generate the initial counterweight requirement parameters.

[0064] Wheel hub structural parameters are a key dataset describing the physical properties and geometric characteristics of the wheel hub, used to ensure compatibility between the weight distribution scheme and the actual wheel hub structure. These parameters mainly include bolt hole coordinates, wheel hub radius, and material density; among them, bolt hole coordinates represent the two-dimensional position coordinates of the bolt holes on the wheel hub surface, denoted as (…). ).

[0065] The collaborative matching analysis specifically involves dynamically combining the purified weight angle value output by the dynamic balancing instrument with the wheel hub structural parameters, including the following steps: S121. Based on the bolt hole coordinates ( Calculate the effective radius of the counterweight position. : ;in, This represents the actual distance from the counterweight position to the center of the wheel hub.

[0066] Converting two-dimensional coordinates into one-dimensional radius values ​​can solve the problem of lever arm differences caused by the curved surface of the wheel hub.

[0067] S122. Based on effective radius Calculate the weighting coefficient with the hub radius r ;in, Used to adjust the weight of the counterweight to ensure centrifugal force balance.

[0068] This enables dynamic matching between structural parameters and dynamic balance data, avoiding counterweight errors caused by different radii.

[0069] S123. Combining the purified weight value W and the weighting coefficient Generate initial counterweight requirements parameters: ; ;in, Represents the required weight. From the perspective of demand, This represents the purification angle value.

[0070] In some embodiments, the preprocessing of the initial data in S2 to obtain vibration-optimized coordinates includes: S21. Perform environmental dynamic calibration based on the initial counterweight requirement parameters to obtain the calibrated counterweight reference.

[0071] In some scenarios, such as temperature and humidity changes in mines, the wheel hub material undergoes thermal expansion, which can cause the counterweight position to shift. The calibration formula is: ;in, From the perspective of demand, Represents the real-time ambient temperature. This represents the standard test temperature, such as 25℃. This represents the coefficient of thermal expansion of the wheel hub material. Represents the wheel hub radius. This represents the calibration angle in the calibrated counterweight reference.

[0072] Temperature change threshold Calibration is triggered periodically to avoid frequent fine-tuning.

[0073] S22. Perform multi-source data cross-validation on the calibrated counterweight reference and generate validation pass command data.

[0074] The system compares the wheel hub's historical balance data to verify the rationality of the current calibrated weight benchmark. If the error is less than a certain value, such as less than 2%, the system outputs a verification pass command.

[0075] S23. Real-time acquisition of the axial vibration spectrum of the wheel hub, and extraction of the dominant vibration characteristics from the verification pass command data.

[0076] Extracting the frequency component with the largest amplitude from the axial vibration spectrum, i.e. the dominant vibration characteristic, can solve the problem of vibration interference with the accuracy of counterweight in a specific frequency band.

[0077] Specifically, the frequency with the largest absolute value of the Fourier transform result of the wheel hub axial vibration spectrum is the core frequency of the dominant vibration characteristic.

[0078] S24. Perform vibration waveform anti-phase cancellation operation based on the dominant vibration characteristics, and output vibration-optimized coordinates.

[0079] Based on the principle of anti-phase wave interference to cancel vibration interference, the formula is: ;in, This represents the angle value of the calibrated counterweight reference. The core frequency, representing the dominant vibrational characteristic, The amplitude represents the angular fluctuation, i.e., the measured vibration amplitude, and t represents the time variable. Represents the initial phase of vibration. The angle value represents the vibration-resistant optimization coordinate.

[0080] In some embodiments, the vibration waveform anti-phase cancellation operation performed in S24 based on the dominant vibration characteristics, and the output of vibration-damping optimized coordinates, includes: S241. Extract vibration waveform phase data based on dominant vibration characteristics and generate inverse waveform data.

[0081] Based on the frequency in the dominant vibration characteristics and phase This generates waveform data that is out of phase with the original vibration wave. ;in, The frequency representing the dominant vibration characteristic, The initial phase represents the dominant vibration characteristic, and t represents the time variable. This represents the amplitude of the angular fluctuation caused by the vibration.

[0082] S242. Perform amplitude matching calculation on the inverted waveform data and output the inverted cancellation result.

[0083] While maintaining the reverse wave phase mechanism, the amplitude ratio is dynamically adjusted. This allows the energy of the antiphase wave to completely cancel out the original vibration wave.

[0084] Calculate the optimal amplitude amplification factor To make the amplitude of the antiphase wave match that of the original vibration wave: ;in, Real-time measurement via sensors That is .

[0085] Inverse cancellation result for: .

[0086] S243. Adjust the offset of the counterweight position based on the anti-phase cancellation result to generate vibration-resistant optimized coordinates.

[0087] Calculate the angle values ​​of the vibration-optimized coordinates: ;in, The angle value representing the vibration-damping optimization coordinates. This represents the angle value of the calibrated counterweight reference. This represents the amplitude of the angular fluctuation, i.e., the measured vibration amplitude. The frequency represents the dominant vibration characteristic, and t represents the time variable. This represents the initial phase of the vibration.

[0088] The vibration-resistant optimization coordinates are: { , }

[0089] In some embodiments, S3 performs collaborative calculation and dynamic optimization of counterweight parameters based on vibration-optimized coordinates to obtain optimized counterweight parameters, including: S31. Calculate the weight and angle based on the vibration optimization coordinates to generate a counterweight combination scheme.

[0090] Installation angle is: ,in, This represents the reference angle of the k-th bolt hole.

[0091] Using vector decomposition, the total load is distributed to various mounting points circumferentially around the wheel hub using trigonometric functions: Where n represents the total number of bolt holes.

[0092] The counterweight combination scheme is: {( , |k=1,2, ,n}.

[0093] S32. Perform weight distribution optimization adjustment on the counterweight combination scheme and output the optimized weight allocation value.

[0094] In the counterweight combination scheme, ensure that the weight difference between any two counterweights does not exceed the safety threshold to avoid wheel hub deformation. The safety threshold can be determined through wheel hub fatigue test.

[0095] Calculate the maximum weight difference between the two counterweights. ,like If the weight exceeds the safety threshold, adjust the weight proportionally to ensure all... Approaching average weight , .

[0096] The formula is adjusted as follows: ;in, The convergence coefficient can be determined by measuring the maximum allowable adjustment step size corresponding to the critical stress point through hub fatigue testing, and then verifying it in conjunction with numerical stability. This represents the adjusted weight.

[0097] The optimized weight distribution value is: { }

[0098] S33. Combine the bolt constraint conditions to perform positional collaborative correction on the optimized weight distribution value and generate the adjusted angular coordinates.

[0099] Check the actual spacing of the bolts. If the actual spacing is less than the preset minimum safety spacing, then make angle corrections.

[0100] The correction mechanism is as follows: calculate the deviation between the minimum safety clearance and the actual bolt spacing. According to the sensitivity coefficient Adjust the angle: ;in, Represents the adjusted angle coordinates. The deformation sensitivity is reflected by calibration using a finite element model.

[0101] The minimum safe clearance represents the minimum clearance at which safe operation is possible. The minimum safe clearance is determined by the outer diameter of the measuring tool and the diameter of the bolt head.

[0102] S34. Perform real-time error compensation calculation based on the adjusted angular coordinates, and output accurate counterweight parameters as optimized counterweight parameters.

[0103] Real-time acquisition of ambient temperature T, and calculation of temperature drift offset: ;in, Represents the temperature drift coefficient. Represents standard temperature.

[0104] Final angle for: .

[0105] The optimized counterweight parameters are: { , }

[0106] In some embodiments, generating executable instructions for optimizing counterweight parameters in S4 includes: S41. Generate bolt fixing control commands based on precise counterweight parameters and output primary execution signals.

[0107] The weight and angle are converted into control signals for the bolt motor, such as pulse frequency and duty cycle.

[0108] S42. Verify the primary execution signal based on the dynamic balancing instrument status data and generate a verification pass command.

[0109] The dynamic balancing instrument collects real-time status data, including rotational speed and vibration amplitude, and then performs verification and judgment. Specifically, the measured vibration velocity is compared with the reference vibration velocity. If the absolute value of the difference between the two does not exceed the vibration safety threshold, the verification is deemed to have passed; otherwise, the verification fails. The vibration safety threshold represents the minimum permissible deviation.

[0110] S43. Execute automatic hub angle positioning based on the verification pass command and output the target angle coordinates.

[0111] The servo motor is triggered according to the verification command, driving the wheel hub to rotate to the target angle. Target angle coordinates for: ;in, The angle deviation is obtained by subtracting the target value from the measured value. This represents the proportional coefficient, which is one of the parameters in PID control.

[0112] S44. Plan the counterweight installation path based on the target angle coordinates and generate the final execution path.

[0113] Angle Convert to 3D installation coordinates ( The starting point coordinates and the target point set can be calculated using standard robot motion planning methods. The execution path of ) yields the spatiotemporal trajectory sequence Path: ;in, Represents a timestamp. represents the coordinates of the path points at the end of the robotic arm, and m represents the total number of path points.

[0114] S45. Calculate the preload gradient for the final execution path based on the bolt group distribution coordinates, and output the anti-deformation pressure threshold.

[0115] Calculate the bolt lever arm : .

[0116] Preload gradient for: ;in, This represents the rated preload of the bolt. This represents the cross-sectional area of ​​the bolt hole.

[0117] Deformation pressure threshold for: That is, find all The minimum value within is used as the anti-deformation pressure threshold; where, This represents the yield strength of the wheel hub material.

[0118] S46. Coordinate the adjustment of bolt installation sequence and torque parameters, and convert the anti-deformation pressure threshold into anti-deformation execution command.

[0119] In some embodiments, the coordinated adjustment of the bolt installation sequence and torque parameters in S46 converts the anti-deformation pressure threshold into an anti-deformation execution command, including: S461. Based on the stress distribution analysis of the bolt group under anti-deformation pressure threshold, generate the stress spectrum of the bolt group.

[0120] Calculate the theoretical forces on each bolt: .

[0121] Draw a thermal diagram of the stress distribution on the bolts, and identify high-stress areas, such as... The area where life .

[0122] S462. Based on the bolt group force diagram, formulate a diagonal cross installation strategy to obtain the installation sequence strategy.

[0123] Prioritize installing bolts diagonally opposite the bolts bearing the greatest stress to disperse stress concentration.

[0124] If the force diagram shows an asymmetrical distribution, then install the components in descending order of force values ​​to obtain the installation sequence strategy.

[0125] S463. Calculate the torque gradient value based on the installation sequence strategy and generate anti-deformation execution command.

[0126] The torque formula is: ;in, This represents the dynamic torque of the k-th bolt. Represents the bolt base torque. This represents the real-time pressure of the bolt.

[0127] By integrating the installation sequence and dynamic torque, anti-deformation execution commands are generated.

[0128] In some embodiments, S5 includes adding counterweights and monitoring real-time status according to executable instructions, and generating wheel hub balance indicators, including: S51. Trigger the bolt fixing device to execute the anti-deformation execution command and generate real-time feedback from the device.

[0129] The drive bolt motor tightens the counterweight according to the installation sequence and torque parameters in the instructions, and outputs the motor status in real time, such as current, speed, position, etc., forming a feedback data stream, that is, the device provides real-time feedback.

[0130] S52. Based on the real-time feedback from the device, monitor the installation progress of the counterweight and output real-time position data.

[0131] Count the number of bolts that have been installed and calculate the installation completion rate; use a laser ranging system to scan the actual position of the counterweight and calculate the deviation from the target position.

[0132] Real-time position data includes real-time progress percentage and position deviation values ​​of each counterweight.

[0133] S53. Verify the weight distribution status based on real-time location data and generate an installation consistency report.

[0134] Check the positional deviation of each counterweight one by one, use the judgment rules to determine whether the installation is qualified, and calculate the installation qualification rate.

[0135] Specifically, a deviation threshold can be set, such as 0.1mm. If the positional deviation of the counterweight is less than or equal to the deviation threshold, it is considered qualified; otherwise, it is considered unqualified.

[0136] The generated installation consistency report includes the deviation values ​​of each bolt position, the pass / fail judgment results, and the overall installation pass rate.

[0137] S54. Evaluate the balance status in the installation consistency report and output the wheel hub balance index as the balance status index.

[0138] The balance assessment formula is: ;in, Represents an indicator of equilibrium state. This represents the installation qualification rate. The average position deviation is represented by K, which represents the deviation penalty coefficient and can be determined by calibration using experimental data from mine pneumatic balancing.

[0139] In some embodiments, S6 performs feedback adjustment and iterative control based on the wheel hub balance index, and outputs a final balance confirmation signal, including: S61. Analyze the residual imbalance in the wheel hub balance index and generate a residual error dataset.

[0140] Set a passing threshold and calculate the deviation from the passing threshold: Taking a passing threshold of 95% as an example, when... When, deviation ;when When, deviation ;in, This represents the j-th type of error component. When j=1, it is the angle deviation component, and when j=2, it is the weight deviation component.

[0141] Residual error dataset = { }

[0142] S62. Determine the iteration requirements based on the residual error dataset and output a test repetition flag.

[0143] Figure it out first and The larger of the absolute values ​​is denoted as . .

[0144] use To determine the test repeatability, compare it with 5%. If the test is repeated, the test duplication flag is true, indicating that the test needs to be restarted; otherwise, the test duplication flag is false, indicating that the test does not need to be restarted.

[0145] S63. Dynamically reconfigure system parameters based on the test repeat flag and generate update test instructions.

[0146] Triggered when the test repeat flag is true: like for Then adjust the temperature drift coefficient K in S54 using the following formula: ;in, represent The sign, i.e., the positive and negative sign function. The step size for adjusting the temperature drift coefficient can be calibrated through field experiments.

[0147] like for Adjust the security threshold in S32: ;in, Represents the original safety threshold. This represents the adjusted safety threshold. The weight threshold adjustment coefficient can be calibrated through mine field experiments.

[0148] Update test command = { , }

[0149] S64. Restart the test procedure according to the dynamic balancing instrument and convert the update test command into the final balance signal.

[0150] Load the update test command and restart the test process (starting from S1). If the new balance index is greater than or equal to the qualified threshold, output the "balance meets the standard" signal; otherwise, output the "manual intervention required" signal.

[0151] In some embodiments, such as Figure 2 As shown, this application provides a system for adding counterweights to achieve dynamic balancing of a wheel hub, comprising: Initial data acquisition module: Acquires the current unbalanced weight and angle information of the wheel hub and generates initial data.

[0152] Data preprocessing module: preprocesses the initial data to obtain vibration-optimized coordinates.

[0153] Parameter calculation and optimization module: Based on the vibration optimization coordinates, the module performs collaborative calculation and dynamic optimization of the counterweight parameters to obtain the optimized counterweight parameters.

[0154] Counterweight instruction generation module: Generates executable instructions for optimizing counterweight parameters.

[0155] Monitoring module: Implements counterweight addition and real-time status monitoring based on executable commands, and generates wheel hub balance index.

[0156] Feedback Iteration Module: Performs feedback adjustment and iterative control based on the wheel hub balance index, and outputs a final balance confirmation signal.

[0157] In some embodiments, this application provides a device for adding counterweights to dynamically balance a wheel hub, which includes a memory and a processor; the memory is used to store a computer program; the processor is used to execute the computer program to implement the steps of the method for adding counterweights to dynamically balance a wheel hub.

[0158] In some embodiments, this application provides a storage medium storing computer program instructions, which are read and executed by a processor to perform the step of adding counterweights to dynamically balance the wheel hub.

[0159] Any references to memory, storage, database, or other media used in the embodiments provided in this invention may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory.

[0160] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0161] 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 of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method of adding weight to a wheel hub dynamic balancing process, comprising: The method comprises the following steps: Obtaining the current unbalanced weight and angle information of the hub to generate initial data; Preprocessing the initial data to obtain anti-vibration optimization coordinates; Performing collaborative calculation and dynamic optimization of the counterweight parameters based on the anti-vibration optimization coordinates to obtain optimized counterweight parameters; Generating executable instructions for the optimized counterweight parameters; Implementing counterweight addition and real-time state monitoring according to the executable instructions to generate hub balancing indicators; Performing feedback adjustment and iterative control according to the hub balancing indicators to output a final balancing confirmation signal.

2. The hub balancing add-on weight method of claim 1, wherein, Obtaining the current unbalanced weight and angle information of the hub to generate initial data, comprising: Collecting the hub weight and angle raw data output by the dynamic balancing instrument, performing noise filtering processing, and outputting purified weight and angle values; Performing collaborative matching analysis on the purified weight and angle values combined with the hub structure parameters to generate initial counterweight demand parameters.

3. The hub balancing add-on weight method of claim 2, wherein, Preprocessing the initial data to obtain anti-vibration optimization coordinates, comprising: Performing environmental dynamic calibration based on the initial counterweight demand parameters to obtain calibrated counterweight references; Performing multi-source data cross-validation on the calibrated counterweight references to generate verification pass instruction data; Real-time acquisition of hub axial vibration spectrum, extraction of dominant vibration characteristics from the verification pass instruction data; Performing vibration waveform inverse offset operation based on the dominant vibration characteristics to output anti-vibration optimization coordinates.

4. The hub balancing add-on weight method of claim 1, wherein, Performing collaborative calculation and dynamic optimization of the counterweight parameters based on the anti-vibration optimization coordinates to obtain optimized counterweight parameters, comprising: Solving the weight and angle according to the anti-vibration optimization coordinates to generate a counterweight combination scheme; Performing weight distribution optimization adjustment on the counterweight combination scheme to output optimized weight distribution values; Performing position collaborative correction on the optimized weight distribution values combined with the bolt constraint conditions to generate adjusted angle coordinates; Performing real-time error compensation calculation based on the adjusted angle coordinates to output accurate counterweight parameters as optimized counterweight parameters.

5. The hub balancing add-on weight method of claim 1, wherein, Generating executable instructions for the optimized counterweight parameters, comprising: Generating bolt fixing control instructions according to the accurate counterweight parameters to output primary execution signals; Performing verification on the primary execution signals according to the dynamic balancing instrument state data to generate verification pass instructions; Performing hub angle automatic positioning according to the verification pass instructions to output target angle coordinates; Planning counterweight block installation path based on the target angle coordinates to generate final execution path; Calculating pre-tightening force gradient for the final execution path according to the bolt group distribution coordinates to output anti-deformation pressure threshold; Collaboratively adjusting the bolt installation sequence and torque parameters to convert the anti-deformation pressure threshold into anti-deformation execution instructions.

6. The hub balancing add-on weight method of claim 1, wherein, Implementing counterweight addition and real-time state monitoring according to the executable instructions to generate hub balancing indicators, comprising: Triggering the bolt fixing device to execute the anti-deformation execution instructions to generate device real-time feedback; Monitoring the counterweight block installation progress based on the device real-time feedback to output real-time position data; Verifying the weight distribution state according to the real-time position data to generate installation consistency report; Evaluating the balancing state in the installation consistency report to output hub balancing indicators as balancing state indicators.

7. The hub balancing add-on weight method of claim 1, wherein, According to the wheel hub balance index, feedback adjustment and iterative control are performed, and a final balance confirmation signal is output, including: Analyzing the residual imbalance in the wheel hub balance index, a residual error data set is generated; Based on the residual error data set, determine the iteration requirement, output test repeat flag; According to the test repeat flag, dynamically reconfigure the system parameters, and generate an updated test instruction; According to the dynamic balancing machine restart test process, the updated test instruction is converted into a final balance signal.

8. The hub balancing add-on weight method of claim 5, wherein, Coordinately adjust the bolt installation sequence and torque parameters, and convert the anti-deformation pressure threshold into an anti-deformation execution instruction, including: Based on the anti-deformation pressure threshold, analyze the stress distribution of the bolt group, and generate a bolt group stress map; According to the bolt group stress map, develop a diagonal cross installation strategy to obtain an installation sequence strategy; According to the installation sequence strategy, calculate the torque gradient value, and generate an anti-deformation execution instruction.

9. The hub balancing add-on weight method of claim 3, wherein, Based on the dominant vibration characteristics, perform vibration waveform anti-phase cancellation operation, and output anti-vibration optimization coordinates, including: Based on the dominant vibration characteristics, extract the vibration waveform phase data, and generate the anti-phase waveform data; Perform amplitude matching calculation on the anti-phase waveform data, and output the anti-phase cancellation result; According to the anti-phase cancellation result, adjust the position offset of the counterweight, and generate the anti-vibration optimization coordinates.

10. A hub balancing weight addition system, comprising: It includes: Initial data acquisition module: obtain the current unbalanced weight and angle information of the wheel hub, and generate initial data; Data preprocessing module: pre-process the initial data to obtain anti-vibration optimization coordinates; Parameter calculation and optimization module: based on the anti-vibration optimization coordinates, perform counterweight parameter collaborative calculation and dynamic optimization to obtain optimized counterweight parameters; Counterweight instruction generation module: generate executable instructions for the optimized counterweight parameters; Monitoring module: according to the executable instructions, implement counterweight addition and real-time state monitoring, and generate wheel hub balance index; Feedback iteration module: according to the wheel hub balance index, feedback adjustment and iterative control are performed, and a final balance confirmation signal is output.

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