A PLC-based balancing machine control system and method for grinding tool processing

Abstract

The application discloses a kind of balancing machine control method and system based on PLC for grinding tool processing, for the dynamic balance correction of special grinding wheel with open pore structure inside, easy to adsorb and stay liquid.System includes PLC, vibration sensor, rotary encoder, auxiliary sensor and counterweight device.PLC determines the interference degree of liquid throw to vibration signal according to the state signal collected by auxiliary sensor, carries out adaptive filtering processing to original vibration signal according to interference degree to eliminate interference component, obtains the processed vibration signal reflecting the real mass distribution of special grinding wheel, then calculates the unbalance amount combined with main shaft rotation angle signal, generates one-time counterweight correction instruction when unbalance amount changes meet stable condition.The application realizes the fast, accurate and one-time convergence dynamic balance correction of special grinding wheel by real-time monitoring the liquid throw state and adaptive elimination of interference.

Description

Technical Field

[0001] This application relates to the field of control technology for balancing machines used in abrasive machining, and more specifically, to a PLC-based control system and method for a balancing machine used in abrasive machining. Background Technology

[0002] In the manufacturing process of precision grinding wheels, balancing machines are crucial equipment for ensuring product quality and processing efficiency. Their core function is to detect the imbalance of the grinding wheel during high-speed rotation and perform precise counterweight correction to eliminate vibration. Typically, the control core of a balancing machine is a programmable logic controller (PLC), which receives signals from vibration sensors and speed encoders, performs calculations, and issues commands to the counterweight device. This control method demonstrates stability and reliability when processing traditional dense grinding wheels.

[0003] However, existing technologies face significant challenges when performing dynamic balancing on special grinding wheels with open porous structures that easily absorb and retain liquids. These special grinding wheels absorb moisture or residual liquids during production, handling, and storage. When the spindle accelerates to the measuring speed, centrifugal force causes the liquid in the wheel's internal pores to be unevenly ejected. This ejection is a continuous dynamic process, with the total mass and center of mass of the grinding wheel constantly changing during measurement. The balancing machine records the vibration state at a given moment and calculates the counterweight scheme, but from the completion of the measurement to the actual installation of the counterweight, the liquid continues to be ejected, and the mass distribution has changed. After the operator installs the counterweight as instructed, the vibration often does not decrease or even increases, and the system detects that the imbalance is still out of tolerance, automatically entering a second measurement and correction cycle. This process repeats itself, with the balancing machine chasing a constantly moving target, and the control program iterating repeatedly without convergence. What should have been a balancing process in a few minutes may take more than half an hour, and may even fail to meet the acceptable standard. Existing PLC control logic based on fixed-state measurements cannot achieve fast, accurate, and one-time convergence dynamic balancing correction for this type of special grinding wheel.

[0004] Therefore, providing a PLC-based balancing machine control system and method for solving the above problems is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] This application discloses a PLC-based balancing machine control system and method for abrasive processing, aiming to solve the problem that in the prior art, when performing dynamic balancing correction on special grinding wheels with an open pore structure that easily adsorbs and retains liquid, the dynamic changes in mass distribution caused by liquid ejection result in a long balancing process, making it impossible to achieve fast, accurate and one-time convergence dynamic balancing correction.

[0006] The technical solution of this application is as follows:

[0007] In a first aspect, this application discloses a PLC-based balancing machine control system for grinding wheels, used for dynamic balancing correction of special grinding wheels with an open porous structure that easily adsorbs and retains liquids, including:

[0008] PLC;

[0009] Vibration sensors are installed on the spindle of the balancing machine to collect raw vibration signals and transmit them to the PLC;

[0010] A rotary encoder, installed at the end of the spindle, is used to collect spindle rotation angle signals and transmit them to the PLC;

[0011] Auxiliary sensors are used to collect state signals that characterize the physical state changes of a special grinding wheel caused by the ejection of internal liquid during rotation, and transmit the state signals to the PLC.

[0012] The counterweight device, connected to the PLC, is used to execute counterweight correction commands;

[0013] The PLC is used to determine the degree of interference of liquid ejection on the vibration signal based on the status signal; the original vibration signal is processed according to the degree of interference to eliminate the interference components caused by liquid ejection, and a processed vibration signal reflecting the true mass distribution of the special grinding wheel is obtained; the unbalance of the special grinding wheel is calculated using the influence coefficient method based on the amplitude and phase of the processed vibration signal and the rotor angle position corresponding to the spindle rotation angle signal; when the change of the unbalance meets the preset stability conditions, a one-time counterweight correction command is generated and sent to the counterweight device.

[0014] This technical solution introduces an auxiliary sensor to monitor the physical state changes caused by liquid ejection from the special grinding wheel in real time, and determines the degree of interference of the liquid ejection on the vibration signal based on the state signal. The PLC adaptively processes the original vibration signal according to the degree of interference, effectively eliminating the interference caused by liquid ejection, thereby obtaining a more realistic vibration signal and calculating the accurate imbalance. When the imbalance meets the stability condition, the system generates a one-time counterweight correction command, avoiding the problem of repeated measurement and correction caused by liquid ejection in traditional methods, significantly improving the efficiency and accuracy of dynamic balancing correction, and solving the technical problem of excessive time consumption and inability to converge in dynamic balancing correction of special grinding wheels.

[0015] Furthermore, in one embodiment, the auxiliary sensors include a laser displacement sensor and an ultrasonic sensor;

[0016] The laser displacement sensor is installed on the radial side of the special grinding wheel, and its measuring beam is perpendicular to the rotation axis of the special grinding wheel. It is used to collect the distance signal between the surface of the special grinding wheel and the laser displacement sensor.

[0017] An ultrasonic sensor is installed on the inner wall of the balancing machine's protective cover to collect signals characterizing the amount of liquid ejected from a special grinding wheel.

[0018] This technical solution, combining laser displacement sensors and ultrasonic sensors, can more comprehensively and accurately capture the physical state changes of special grinding wheels caused by liquid ejection during rotation from different dimensions (surface distance changes and the amount of ejected liquid). This provides a more reliable data basis for subsequent determination of the degree of interference, thereby further improving the system's ability to identify liquid ejection interference.

[0019] Based on this, this application also proposes that the PLC is used to: control the special grinding wheel to run according to a preset speed change curve before acquiring the original vibration signal and status signal, the speed change curve including a high speed stage and a low speed stage executed sequentially.

[0020] This technical solution, through operation on a preset speed curve, especially at high speeds, can accelerate the ejection of liquid from the special grinding wheel, allowing it to reach a relatively stable state before measurement. This reduces the dynamic changes in liquid ejection during measurement, creating a more favorable environment for subsequent vibration signal acquisition and processing, and further improving the accuracy and stability of the measurement results.

[0021] Based on the above, this application further proposes that the PLC is used to determine the level of interference based on the status signal, specifically as follows:

[0022] Acquire the signal from the ultrasonic sensor that characterizes the amount of liquid ejected from the special grinding wheel, and calculate its rate of change;

[0023] Acquire the distance signal between the surface of the special grinding wheel and the laser displacement sensor, which is collected by the laser displacement sensor, and calculate its fluctuation amplitude;

[0024] When the rate of change does not exceed the preset rate of change threshold and the fluctuation amplitude is less than the preset amplitude threshold, the interference level is determined to be low interference.

[0025] Otherwise, the interference level is determined to be high interference.

[0026] This technical solution, by comprehensively analyzing the rate of change of the ejected liquid volume and the fluctuation amplitude of the grinding wheel surface, can more precisely quantify the degree of interference of the ejected liquid on the vibration signal, classify the interference state into high interference and low interference, and provide a more targeted basis for subsequent adaptive filtering processing, thereby optimizing the interference elimination effect.

[0027] Furthermore, the PLC is specifically used to perform adaptive filtering processing on the original vibration signal based on the least mean square algorithm according to the degree of interference, so as to eliminate the interference components caused by liquid splashing.

[0028] When the interference level is high, the PLC increases the learning step size of the minimum mean square algorithm.

[0029] When the interference level is low, the PLC reduces the learning step size of the least mean square algorithm.

[0030] This technical solution allows the PLC to dynamically adjust the learning step size of the least mean square algorithm based on the real-time determined level of interference. Increasing the step size under high interference conditions accelerates algorithm convergence and quickly adapts to drastically changing interference; decreasing the step size under low interference conditions improves filtering accuracy and avoids over-correction. This adaptive filtering strategy enables the system to efficiently and accurately eliminate interference caused by liquid ejection under different interference intensities, significantly improving the realism of the processed vibration signal.

[0031] In some preferred embodiments, the auxiliary sensor also includes an acoustic sensor;

[0032] Acoustic sensors are installed on the inner wall of the protective cover of the balancing machine or on the outer shell of the bearing housing of the balancing machine to collect acoustic signals generated by the rupture of the liquid inside the special grinding wheel;

[0033] Acoustic signals constitute a part of state signals;

[0034] PLCs are also used to identify the frequency and intensity of liquid rupture based on the spectral characteristics of acoustic signals.

[0035] When the detected liquid rupture frequency exceeds a preset frequency threshold, or the liquid rupture intensity exceeds a preset intensity threshold, and the current interference level is in a low interference state, the interference level is corrected from a low interference state to a high interference state, and the learning step size of the least mean square algorithm is controlled according to the corrected interference level: the learning step size is increased in the high interference state and decreased in the low interference state.

[0036] This technical solution, by introducing acoustic sensors, can capture the phenomenon of liquid breaking inside the grinding wheel at the acoustic characteristic level. This is a more direct and sensitive precursor or accompanying phenomenon of liquid ejection. When the acoustic signal indicates that the liquid breaking is intensifying, even if other indicators show low interference, the system can promptly correct the interference level to high interference and adjust the learning step size of the filtering algorithm accordingly. This allows for a faster and more accurate response to sudden liquid ejection interference, further improving the system's robustness and adaptability.

[0037] As a further improvement, the auxiliary sensor also includes a multispectral imaging camera;

[0038] A multispectral imaging camera is installed on the radial side of a special grinding wheel or on the inner wall of a protective cover to acquire multispectral images of the surface of the special grinding wheel or the inner wall of the protective cover.

[0039] Multispectral images constitute part of the state signal;

[0040] PLC is also used for image segmentation of multispectral images to identify the area and non-uniformity of liquid adhesion regions on the surface of special grinding wheels or the inner wall of protective covers.

[0041] When the area of ​​the liquid-attached region exceeds a preset area threshold, or the non-uniformity of the liquid-attached region exceeds a preset non-uniformity threshold, and the current interference level is in a low interference state, the interference level is corrected from a low interference state to a high interference state, and the learning step size of the least mean square algorithm is controlled according to the corrected interference level: the learning step size is increased in the high interference state, and the learning step size is decreased in the low interference state.

[0042] This technical solution enables multispectral imaging cameras to provide visual information about the area and non-uniformity of liquid adhesion regions, providing an intuitive and comprehensive characterization of liquid ejection. Through image analysis, the system can more accurately assess the spatial distribution and dynamic changes of liquid ejection. When abnormal liquid adhesion is detected, the system can promptly correct the level of interference and adjust the filtering strategy, further enhancing the system's ability to identify and respond to complex liquid ejection situations and improving the reliability of dynamic balance correction.

[0043] In one implementation, the PLC is also used to determine whether the change in the magnitude of the imbalance over a continuous period of time is less than a magnitude threshold, and to obtain a first determination result;

[0044] Determine whether the change in angular position is less than the angular threshold to obtain the second judgment result;

[0045] If both the first and second judgment results are yes, then the change in the unbalanced quantity is determined to satisfy the stability condition.

[0046] This technical solution, by simultaneously judging the changes in the magnitude and angle of the imbalance, enables a more comprehensive and accurate assessment of the stability of the imbalance. Only when both the magnitude and angle tend to stabilize is the stability condition deemed met. This avoids misjudgments due to fluctuations in a single indicator, ensuring that the counterweight correction command is issued only when the special grinding wheel reaches a truly stable state, thereby improving the final correction effect.

[0047] Preferably, the counterweight device is an automatic drilling device or an automatic counterweight block installation mechanism;

[0048] A one-time counterweight correction instruction includes the angle position to be corrected and the mass to be corrected.

[0049] Automatic drilling devices are used to drill the required quality at the required angle position on special grinding wheels;

[0050] The automatic counterweight installation mechanism is used to install counterweights of the mass to be corrected at the required angle position of a special grinding wheel.

[0051] This technical solution utilizes an automatic drilling device or an automatic counterweight installation mechanism as the counterweight device, achieving automation and precision in counterweight correction. The one-time counterweight correction command directly includes the correction angle and mass, avoiding errors and inefficiencies that may result from manual intervention. This significantly improves the automation level and correction accuracy of dynamic balancing, and shortens the entire correction cycle.

[0052] Secondly, this application also discloses a PLC-based balancing machine control method for abrasive machining, used to perform dynamic balancing correction on special grinding wheels with an open porous structure that easily adsorbs and retains liquids, including the following steps:

[0053] The original vibration signal, spindle rotation angle signal, and state signal characterizing the physical state change of the special grinding wheel caused by the ejection of internal liquid were collected during the rotation of the special grinding wheel.

[0054] The degree of interference of liquid ejection on the vibration signal is determined based on the state signal;

[0055] The original vibration signal is processed according to the degree of interference to eliminate the interference components caused by liquid splashing, and a processed vibration signal reflecting the true mass distribution of the special grinding wheel is obtained.

[0056] Based on the amplitude and phase of the processed vibration signal and the rotor angular position corresponding to the spindle rotation angle signal, the unbalance of the special grinding wheel is calculated using the influence coefficient method.

[0057] When the change in the unbalance meets the preset stability condition, a one-time counterweight correction command is generated and sent to the counterweight device for execution.

[0058] This technical solution utilizes a method that acquires state signals in real time and determines the degree of interference from liquid ejection on vibration signals. This allows for adaptive processing of the original vibration signals, effectively eliminating dynamic interference caused by liquid ejection. This method obtains a more accurate estimate of the imbalance and generates a correction command once the imbalance stabilizes. It fundamentally solves the problem of inaccurate measurements and repeated corrections caused by liquid ejection in the dynamic balancing of special grinding wheels, significantly improving calibration efficiency and accuracy.

[0059] Beneficial effects

[0060] This application discloses a PLC-based balancing machine control system for abrasive wheel machining. By introducing auxiliary sensors, it acquires real-time state signals characterizing the physical state changes of a special grinding wheel caused by internal liquid ejection during rotation. Based on these state signals, the PLC can accurately determine the degree of interference of the liquid ejection on the vibration signal. On this basis, the system adaptively processes the original vibration signal according to the determined interference level, effectively eliminating the interference components caused by liquid ejection, thus obtaining a processed vibration signal that more realistically and accurately reflects the mass distribution of the special grinding wheel. Subsequently, the system calculates the imbalance of the special grinding wheel using the influence coefficient method based on the processed vibration signal and the spindle rotation angle signal. When the change in imbalance meets the preset stability conditions, the system generates a one-time counterweight correction command and sends it to the counterweight device for execution.

[0061] Compared to existing technologies, the system in this application overcomes the problems of traditional balancing machines when handling special grinding wheels that easily absorb liquids, such as dynamic changes in mass distribution due to liquid ejection, inaccurate measurement results, repeated iterations of the balancing process, and excessive time consumption. By monitoring the liquid ejection status in real time and performing adaptive interference elimination, this application can obtain more stable unbalance data, thereby achieving the balancing standard with only one or very few corrections, significantly shortening the balancing time and improving production efficiency. This system effectively solves the problem of existing technologies being unable to perform rapid, accurate, and one-time convergent dynamic balancing correction for this type of special grinding wheel, demonstrating significant technological progress and practical value. Attached Figure Description

[0062] To more clearly illustrate the technical solutions in the embodiments of this application 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 only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0063] Figure 1 A structural block diagram of a PLC-based balancing machine control system for mold processing is provided in an embodiment of this application;

[0064] Figure 2 A flowchart illustrating a PLC-based balancing machine control method for mold processing, provided in an embodiment of this application. Detailed Implementation

[0065] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0066] The embodiments in this application are written in a progressive manner.

[0067] In response, this application proposes a PLC-based balancing machine control system for abrasive wheel machining, used for dynamic balancing correction of special grinding wheels with an open porous structure that easily adsorbs and retains liquids, including:

[0068] PLC;

[0069] Vibration sensors are installed on the spindle of the balancing machine to collect raw vibration signals and transmit them to the PLC;

[0070] A rotary encoder, installed at the end of the spindle, is used to collect spindle rotation angle signals and transmit them to the PLC;

[0071] Auxiliary sensors are used to collect state signals that characterize the physical state changes of a special grinding wheel caused by the ejection of internal liquid during rotation, and transmit the state signals to the PLC.

[0072] The counterweight device, connected to the PLC, is used to execute counterweight correction commands;

[0073] The PLC is used to determine the degree of interference of liquid ejection on the vibration signal based on the status signal; the original vibration signal is processed according to the degree of interference to eliminate the interference components caused by liquid ejection, and a processed vibration signal reflecting the true mass distribution of the special grinding wheel is obtained; the unbalance of the special grinding wheel is calculated using the influence coefficient method based on the amplitude and phase of the processed vibration signal and the rotor angle position corresponding to the spindle rotation angle signal; when the change of the unbalance meets the preset stability conditions, a one-time counterweight correction command is generated and sent to the counterweight device.

[0074] The core of the PLC-based balancing machine control system for abrasive tool processing proposed in this application lies in the dynamic balancing correction of special grinding wheels. Special grinding wheels refer to grinding wheels with an open porous structure that easily attracts and retains liquids, such as certain ceramic or composite material grinding wheels. The purpose of dynamic balancing correction is to adjust the mass distribution of the grinding wheel to balance the centrifugal force generated during high-speed rotation, thereby reducing vibration, improving machining accuracy, and extending equipment life. The PLC (Programmable Logic Controller) is the core of the entire control system, responsible for receiving and processing various sensor signals and issuing control commands according to preset logic and algorithms.

[0075] In its implementation, the control system comprises the following main components:

[0076] First, the PLC, as the core of the control system, can be a commonly available industrial-grade PLC, such as the Siemens S7 series, Rockwell AB series, or Mitsubishi FX series. These PLCs have powerful data processing capabilities and real-time control performance, capable of meeting the complex calculations and rapid response requirements of dynamic balancing correction. The PLC is programmed to implement logic control, data acquisition, signal processing, imbalance calculation, and generation of counterweight correction instructions for the entire balancing process.

[0077] Secondly, vibration sensors are mounted on the spindle of the balancing machine to collect the raw vibration signals from the rotation of the special grinding wheel. These sensors can be piezoelectric accelerometers or eddy current displacement sensors. For example, a piezoelectric accelerometer can be selected and fixed on the spindle bearing housing. By measuring the vibration acceleration of the bearing housing, the vibration of the spindle and grinding wheel can be indirectly reflected. The vibration sensor converts the collected analog vibration signal into an electrical signal, which is then transmitted to the analog input module of the PLC for digital processing after passing through signal conditioning circuits (such as amplification and filtering).

[0078] Furthermore, a rotary encoder is installed at the end of the spindle to collect the spindle's rotation angle signal. The rotary encoder can be an incremental encoder or an absolute encoder. For example, an incremental photoelectric encoder can be selected; through its output A / B phase pulse signals and Z phase zero-position signal, the PLC can accurately calculate the spindle's rotational speed and real-time angular position. The rotation angle signal is crucial for determining the phase of the unbalance; combined with the phase of the vibration signal, it can accurately indicate the angular position of the unbalanced mass.

[0079] In addition, auxiliary sensors are used to collect state signals characterizing the physical state changes of the special grinding wheel caused by the ejection of internal liquid during rotation. These auxiliary sensors can be of various types. For example, an infrared thermal imager can be used to monitor changes in the surface temperature distribution of the grinding wheel, as liquid ejection is usually accompanied by evaporation heat absorption or frictional heat generation, leading to uneven surface temperature. Another approach is to use high-frequency acoustic sensors, installed on the inner wall of the balancing machine's protective cover, to capture the high-frequency sound waves generated when liquid breaks and ejects from the internal pores of the grinding wheel. These sensors transmit the collected state signals to the PLC, providing a basis for subsequent interference level assessment.

[0080] Finally, the counterweight device is connected to the PLC to execute counterweight correction commands. The counterweight device can be a manual counterweight installation mechanism, where the operator manually installs the counterweight according to the correction amount and angle displayed on the PLC; or it can be a semi-automatic or fully automatic counterweight system, such as an automatic drilling device or an automatic counterweight installation mechanism. For example, an automatic drilling device can be used, which includes a drill bit driven by a servo motor controlled by the PLC. This drill bit can precisely drill at a specified angular position on the grinding wheel according to commands issued by the PLC to remove a corresponding mass of material, thereby achieving dynamic balance correction.

[0081] The PLC plays a central role in the entire dynamic balancing process. When the special grinding wheel begins to rotate, vibration sensors continuously collect raw vibration signals, the rotary encoder provides the spindle angle signal, and auxiliary sensors also begin collecting status signals. The PLC first determines the degree of interference from liquid ejection on the vibration signals based on the status signals collected by the auxiliary sensors, such as the surface temperature distribution of the grinding wheel and high-frequency acoustic signals. For example, if a large unevenness in the surface temperature distribution of the grinding wheel or a high intensity of the high-frequency acoustic signal is detected, it indicates that the interference from liquid ejection is relatively severe.

[0082] Based on the determined level of interference, the PLC processes the original vibration signal to eliminate interference components caused by liquid ejection. For example, when the interference level is high, the PLC can employ a more aggressive filtering algorithm or adaptive algorithm, such as the Least Mean Square (LMS) algorithm, to track and suppress interference in real time. When the interference level is low, a more conservative filtering strategy can be used. Through this processing, a processed vibration signal reflecting the true mass distribution of the special grinding wheel can be obtained, thus avoiding false imbalances caused by liquid ejection.

[0083] Subsequently, the PLC calculates the unbalance of the special grinding wheel using the influence coefficient method based on the amplitude and phase of the processed vibration signal and the rotor angular position corresponding to the spindle rotation angle signal. The influence coefficient method is a mature dynamic balancing calculation method. By adding trial weights at known locations and measuring the resulting vibration changes, the relationship between the unbalance and the vibration response is established, and then the unbalance to be corrected is calculated.

[0084] After calculating the imbalance, the PLC continuously monitors its changes. When the imbalance meets preset stability conditions—for example, when the magnitude and angular position changes of several consecutive measurements are less than preset thresholds—it indicates that the liquid ejection from the grinding wheel has stabilized, and the measurement results at this point accurately reflect the mass distribution of the grinding wheel. Once the stability conditions are met, the PLC generates a one-time counterweight correction command and sends it to the counterweight device for execution. This command typically includes the angular position to be corrected and the magnitude of the mass to be corrected.

[0085] This application introduces auxiliary sensors to perceive the impact of liquid ejection on the physical state of the grinding wheel in real time, and dynamically adjusts the vibration signal processing strategy accordingly, thereby effectively filtering out interference and obtaining accurate vibration data. This closed-loop control mechanism of "perception-adaptation-correction" enables the balancing machine to accurately identify and correct the true imbalance of the special grinding wheel, avoiding ineffective correction of "outdated" data.

[0086] Compared with existing technologies, the advantages of this application are as follows: First, by using auxiliary sensors to monitor the liquid ejection state in real time, the system can intelligently determine the degree of interference and take targeted signal processing measures, significantly improving the accuracy of the vibration signal. Second, calculating the unbalance based on the processed real vibration signal ensures the effectiveness of the correction command. Finally, a one-time counterweight correction command is generated only when the change in unbalance meets the stability condition, avoiding repeated corrections, greatly shortening the balancing time, and improving production efficiency. This method not only solves the problem of dynamic balancing correction of special grinding wheels but also provides a new approach for balancing other workpieces with similar dynamic mass changes.

[0087] Specifically, the aforementioned auxiliary sensors can be configured in a specific way, including a laser displacement sensor and an ultrasonic sensor; the laser displacement sensor is installed on the radial side of the special grinding wheel, and its measuring beam is perpendicular to the rotation axis of the special grinding wheel, used to collect the distance signal between the surface of the special grinding wheel and the laser displacement sensor; the ultrasonic sensor is installed on the inner wall of the protective cover of the balancing machine, used to collect the signal characterizing the amount of liquid thrown out from the special grinding wheel.

[0088] A laser displacement sensor is a non-contact measuring device that accurately measures the distance between a target object and the sensor by emitting a laser beam and receiving reflected light. In this application, the laser displacement sensor is configured to be mounted radially to the side of a special grinding wheel, ensuring that its measuring beam is perpendicular to the rotation axis of the special grinding wheel, thereby enabling accurate acquisition of the distance signal between the surface of the special grinding wheel and the laser displacement sensor. This distance signal can reflect the minute deformation or surface condition changes that may occur on the surface of the special grinding wheel due to liquid ejection during high-speed rotation.

[0089] An ultrasonic sensor is a sensor that uses ultrasonic waves for detection. It detects the presence, distance, or quantity of a target by emitting and receiving ultrasonic waves. In this application, an ultrasonic sensor is installed on the inner wall of the protective cover of a balancing machine to monitor the amount of liquid ejected from inside a special grinding wheel. When the special grinding wheel rotates at high speed, the liquid adsorbed inside may be ejected due to centrifugal force. The ultrasonic sensor can detect this ejected liquid and collect signals characterizing the liquid quantity. These signals can indirectly reflect the retention and ejection of liquid inside the special grinding wheel, providing a basis for subsequently judging the degree of interference of liquid ejection on the vibration signal.

[0090] By employing the aforementioned technical solution and using laser displacement sensors and ultrasonic sensors as auxiliary sensors, precise monitoring of the liquid ejection state inside special grinding wheels can be achieved. The laser displacement sensor can capture minute deformations or surface state changes on the surface of the special grinding wheel caused by liquid ejection, while the ultrasonic sensor can effectively quantify the amount of liquid ejected. This multi-sensor fusion monitoring method significantly improves the accuracy and comprehensiveness of the status signals, enabling the PLC to more accurately assess the degree of interference of liquid ejection on vibration signals. This, in turn, improves the accuracy and reliability of dynamic balancing correction, effectively avoiding misjudgments and over-corrections caused by liquid interference, thereby extending the service life of the special grinding wheel and improving machining quality.

[0091] This application further proposes that the PLC is also used to: control a special grinding wheel to run according to a preset speed change curve before acquiring the original vibration signal and status signal, the speed change curve including a high speed stage and a low speed stage executed sequentially.

[0092] Specifically, the preset speed change curve refers to a series of stages in which the rotational speed of the special grinding wheel is pre-set and controlled by the PLC before formal dynamic balancing data acquisition. The purpose of the high-speed stage is to use greater centrifugal force to expel as much liquid as possible from inside the special grinding wheel that might be ejected during subsequent measurements and cause interference. For example, this high speed can be set to or close to the maximum safe operating speed of the special grinding wheel and maintained for a certain period to ensure sufficient liquid expulsion. Subsequently, the purpose of the low-speed stage is to stabilize the distribution of the remaining liquid inside the special grinding wheel after most of the liquid has been expelled, and to ensure a smooth transition in the operating state of the entire system (including the special grinding wheel, spindle, etc.), creating a more stable environment for subsequent precise vibration and status signal acquisition. This low speed can be set to a speed lower than the high speed but sufficient to maintain stable wheel rotation and maintained for a period to achieve a stabilizing effect.

[0093] Through the above technical solution, this application can effectively preprocess the internal liquid state of the special grinding wheel before dynamic balancing measurements, significantly reducing the initial interference of liquid ejection on the vibration signal. This allows the PLC to process the original vibration signal based on more stable and purer input data, thereby improving the accuracy and efficiency of interference elimination. Ultimately, this application can obtain a more accurate processed vibration signal reflecting the true mass distribution of the special grinding wheel, thereby improving the accuracy of unbalance calculation and ensuring the precision and reliability of dynamic balancing correction. The effect is particularly significant for special grinding wheels with an open porous structure that easily absorbs and retains liquid.

[0094] In some preferred embodiments, it is assumed that a special grinding wheel, after being installed on a balancing machine, may have absorbed coolant inside. When starting the dynamic balancing correction program, the PLC first controls the balancing machine spindle to drive the special grinding wheel according to a preset speed change curve. Specifically, this speed change curve can be set as follows: First, the special grinding wheel runs at a high speed of 3000 RPM for 30 seconds. At this high speed, most of the coolant absorbed inside the special grinding wheel will be thrown out due to centrifugal force. Subsequently, the speed of the special grinding wheel is reduced to a low speed of 800 RPM and continues to run for 15 seconds to allow the remaining small amount of coolant inside the special grinding wheel to reach a relatively stable distribution state and to ensure smooth operation of the entire system. After completing this pre-running stage, the PLC begins to formally collect the raw vibration signal collected by the vibration sensor, the spindle angle signal collected by the rotary encoder, and the status signal collected by the auxiliary sensors. This preprocessing method ensures that the liquid state inside the special grinding wheel is relatively stable at the time of data acquisition, thereby providing high-quality input data for subsequent interference elimination and imbalance calculation.

[0095] This application further proposes a specific method for the PLC to determine the level of interference based on the aforementioned status signal, including:

[0096] Acquire the signal from the ultrasonic sensor that represents the amount of liquid ejected from the special grinding wheel, and calculate its rate of change.

[0097] The distance signal between the surface of the special grinding wheel and the laser displacement sensor, collected by the laser displacement sensor, is obtained, and its fluctuation amplitude is calculated.

[0098] When the aforementioned rate of change does not exceed a preset rate of change threshold and the aforementioned fluctuation amplitude is less than a preset amplitude threshold, the aforementioned level of interference is determined to be a low interference state.

[0099] Otherwise, the above level of interference is determined to be a high level of interference.

[0100] Specifically, the aforementioned ultrasonic sensor is configured to be installed on the inner wall of the balancing machine's protective cover to collect real-time signals of the liquid volume ejected from the special grinding wheel. By processing this liquid volume signal, its rate of change can be calculated. This rate of change characterizes the trend and speed of change in the amount of liquid ejected per unit time, and is an important indicator for measuring the dynamic intensity of liquid ejection. The rate of change can be calculated using various mathematical methods such as differential and moving average, with the aim of quantifying the instantaneous or short-term intensity of liquid ejection.

[0101] Simultaneously, the aforementioned laser displacement sensor is installed radially to the side of the special grinding wheel, with its measuring beam perpendicular to the wheel's rotation axis. This sensor is used to acquire the distance signal between the grinding wheel surface and the laser displacement sensor. The fluctuation amplitude of this distance signal reflects the instantaneous influence of liquid adhesion, flow, or ejection on the grinding wheel's geometry or surface condition. A larger fluctuation amplitude generally indicates a more significant physical disturbance caused by the liquid on the grinding wheel surface or during ejection. The fluctuation amplitude can be calculated based on statistical measures such as the difference between the maximum and minimum values ​​of the signal and the standard deviation, aiming to assess the degree of disturbance the liquid causes to the grinding wheel's surface condition.

[0102] Furthermore, this application sets preset change rate thresholds and preset amplitude thresholds. These thresholds are predetermined based on a large amount of experimental data, empirical values, or theoretical analysis, and are used to distinguish different degrees of liquid ejection interference. When the change rate of the liquid volume does not exceed the preset change rate threshold, and the fluctuation amplitude of the distance signal is less than the preset amplitude threshold, it indicates that the interference of liquid ejection on the vibration signal is relatively small and stable, and this is judged as a low interference state. Conversely, if any condition is not met, i.e., the intensity of liquid ejection or the disturbance to the surface condition of the grinding wheel reaches a certain level, it is judged as a high interference state.

[0103] Through the above technical solution, this application enables precise and dynamic quantitative assessment of the vibration interference caused by internal liquid ejection during the machining of special grinding wheels. Compared to methods that rely solely on a single state signal or experience to judge the interference level, this application, by comprehensively analyzing the rate of change of ejected liquid volume and the fluctuation amplitude of the distance signal from the grinding wheel surface, can more sensitively and accurately capture the impact of liquid ejection on the dynamic balance state of the grinding wheel. This refined interference level determination allows subsequent processing of the original vibration signal to be adaptively adjusted according to the actual interference intensity. For example, a more aggressive filtering strategy can be used when the interference is strong, while a gentler strategy can be used when the interference is weak, thereby more effectively eliminating the interference components caused by liquid ejection and obtaining a vibration signal that more accurately reflects the mass distribution of the special grinding wheel. This significantly improves the accuracy and reliability of dynamic balance correction, avoids over- or under-correction caused by inaccurate assessment of liquid ejection interference, and thus improves the machining accuracy and service life of the special grinding wheel.

[0104] In some preferred embodiments, a specific example is given below. Suppose a balancing machine is performing dynamic balancing on a special grinding wheel with internal coolant adsorbed. During the balancing process, the PLC continuously receives signals from ultrasonic sensors and laser displacement sensors.

[0105] Specifically, ultrasonic sensors monitor the amount of coolant ejected from the special grinding wheel in real time. The PLC processes this data and calculates the rate of change in coolant volume. For example, if the coolant volume increases from 1 ml / s to 5 ml / s over a certain period, the rate of change is calculated. Simultaneously, a laser displacement sensor continuously measures the distance between the surface of the special grinding wheel and the sensor, and the PLC calculates the amplitude of the distance signal fluctuation. For example, within a certain rotation cycle, the maximum fluctuation range of the distance signal is 0.05 mm.

[0106] At this point, the PLC compares the calculated rate of change of coolant volume with a preset rate of change threshold (e.g., 2 ml / s) and compares the fluctuation amplitude of the distance signal with a preset amplitude threshold (e.g., 0.03 mm).

[0107] If the calculated coolant volume change rate is 1 ml / s (not exceeding 2 ml / s) and the distance signal fluctuation amplitude is 0.02 mm (less than 0.03 mm), then the PLC determines that the current liquid ejection's interference with the vibration signal is a low-interference state. This means that the liquid ejection is relatively stable and has a small impact.

[0108] However, if the coolant flow rate suddenly increases to 3 ml / s (exceeding 2 ml / s), or the distance signal fluctuation increases to 0.06 mm (exceeding 0.03 mm), the PLC will immediately determine that the current interference level is a high interference state. This indicates that the liquid ejection has a significant instantaneous impact on the dynamic balance of the grinding wheel.

[0109] Through this dynamic, quantitatively-based judgment mechanism, the PLC can adjust the processing strategy of subsequent vibration signals in real time to ensure that the most accurate balance data can be obtained under different interference intensities.

[0110] This application further proposes that the PLC is specifically used to perform adaptive filtering processing on the original vibration signal based on the least mean square algorithm according to the above-mentioned interference level, so as to eliminate the interference components caused by liquid splashing; wherein, when the interference level is high, the PLC increases the learning step size of the least mean square algorithm; when the interference level is low, the PLC decreases the learning step size of the least mean square algorithm.

[0111] Specifically, the Least Mean Square (LMS) algorithm is a widely used adaptive filtering algorithm. Its core idea is to minimize the mean square error between the output signal and the desired signal by iteratively adjusting the filter coefficients. The learning step size is a key parameter in the LMS algorithm, determining the magnitude of the filter coefficient adjustment in each iteration. A larger learning step size results in faster convergence but may lead to larger steady-state errors or unstable convergence; a smaller learning step size results in slower convergence but achieves smaller steady-state errors and better convergence stability. In practical applications, when the PLC determines the interference level to be high, it indicates that the interference component caused by the liquid splashing is strong or changes drastically. In this case, increasing the learning step size of the LMS algorithm allows the filter to adapt to this strong or rapidly changing interference more quickly, thus accelerating the elimination of interference components. Conversely, when the PLC determines the interference level to be low, it indicates that the interference component caused by the liquid splashing is weak or relatively stable. In this case, decreasing the learning step size of the LMS algorithm allows the filter to be finely adjusted within a smaller range, thus achieving a more accurate filtering effect and avoiding over-adjustment or the introduction of new errors.

[0112] Through the above technical solution, this application can significantly improve the elimination effect of liquid ejection interference during the dynamic balancing correction of special grinding wheels. Compared with the filtering method using fixed parameters, this adaptive filtering process can dynamically adjust the filtering strategy according to the degree of interference, thereby achieving fast and effective interference suppression in strong interference environments and high-precision interference elimination in weak interference environments. As a result, the processed vibration signal can more accurately reflect the true mass distribution of the special grinding wheel, thereby improving the accuracy of unbalance calculation and the reliability of dynamic balancing correction, effectively avoiding misjudgment or insufficient correction caused by liquid ejection interference, and improving the overall performance and applicability of the balancing machine control system.

[0113] In some preferred embodiments, a specific example is given below. Assume that during the dynamic balancing process of a special grinding wheel, the PLC first determines the level of interference caused by liquid ejection based on the state signals collected by the ultrasonic sensor and the laser displacement sensor. For example, at the initial stage of grinding wheel startup or when the rotational speed changes rapidly, the rate of change of the ultrasonic signal and the fluctuation amplitude of the laser displacement signal may be high, and the PLC determines this to be a high-interference state. At this time, the PLC sets the learning step size of the least mean square algorithm used for adaptive filtering to a relatively large value, such as 0.01, to ensure that the filter can converge quickly and effectively suppress strong liquid ejection interference. As the grinding wheel operation stabilizes, the amount of liquid ejection decreases, and the rate of change of the ultrasonic signal and the fluctuation amplitude of the laser displacement signal decrease, and the PLC determines this to be a low-interference state. At this time, the PLC adjusts the learning step size to a relatively small value, such as 0.001, to improve the accuracy and stability of the filtering, further refine the elimination of residual interference, and thus obtain a purer vibration signal, providing a more reliable data basis for subsequent unbalance calculations.

[0114] This application further proposes that the aforementioned auxiliary sensors also include acoustic sensors;

[0115] Acoustic sensors are installed on the inner wall of the protective cover of the balancing machine or on the outer shell of the bearing housing of the balancing machine to collect acoustic signals generated by the rupture of the liquid inside the special grinding wheel;

[0116] Acoustic signals constitute a part of state signals;

[0117] PLCs are also used to identify the frequency and intensity of liquid rupture based on the spectral characteristics of acoustic signals.

[0118] When the detected liquid rupture frequency exceeds a preset frequency threshold, or the liquid rupture intensity exceeds a preset intensity threshold, and the current interference level is in a low interference state, the interference level is corrected from a low interference state to a high interference state, and the learning step size of the least mean square algorithm is controlled according to the corrected interference level: the learning step size is increased in the high interference state and decreased in the low interference state.

[0119] Specifically, an acoustic sensor can be understood as a device that converts sound waves into electrical signals. Its installation location is chosen to maximize the capture of acoustic signals generated by the rupture of liquid inside a special grinding wheel. For example, installing it on the inner wall of a balancing machine's protective cover or on the outer shell of the balancing machine's bearing housing can effectively receive faint sounds generated by cavitation of the liquid inside the grinding wheel, bubble bursting, or the interaction between the liquid and the grinding wheel's porous structure. These acoustic signals, as part of the status signals, provide the PLC with additional information about the dynamic behavior of the liquid inside the special grinding wheel. The PLC's processing of the acoustic signals includes spectral analysis to identify the frequency and intensity of liquid rupture. Liquid rupture typically generates broadband noise or impact signals within a specific frequency range. By analyzing its spectral characteristics, the activity level of the liquid rupture can be quantified. For example, when the identified liquid rupture frequency or intensity exceeds a preset threshold, it indicates intense internal liquid dynamic activity, potentially generating significant transient interference. In practical applications, when the PLC determines that it is in a low-interference state based on the ultrasonic and laser displacement sensors, if the acoustic sensor detects that the frequency or intensity of liquid rupture exceeds a preset threshold, it indicates that although the surface phenomenon is not obvious, the internal liquid activity may cause potential strong interference. In this case, the PLC will correct the interference level from a low-interference state to a high-interference state. The corrected interference level will be used to control the learning step size of the least mean square algorithm. That is, in the high-interference state, the learning step size is increased to improve the filter's response speed and its ability to suppress transient interference; in the low-interference state, the learning step size is decreased to ensure the smoothness and accuracy of the filter.

[0120] Through the above technical solution, this application can significantly improve the accuracy of judging the degree of vibration interference caused by the ejection of internal liquid in special grinding wheels. Especially when the internal liquid exhibits complex dynamic behavior (such as rupture) while surface phenomena are not obvious, the introduction of acoustic sensors can provide crucial supplementary information, making the assessment of the interference level more comprehensive and accurate. Therefore, the learning step size of the adaptive filtering algorithm can be dynamically adjusted according to more realistic interference conditions, thereby enhancing the robustness of the filter and its ability to suppress transient interference. Ultimately, this improves the accuracy and efficiency of dynamic balancing correction, ensuring the stability of the special grinding wheel during processing and the quality of the product.

[0121] In some preferred embodiments, it is assumed that the special grinding wheel is undergoing dynamic balancing on a balancing machine. At a certain moment, the rate of change of liquid ejection detected by the ultrasonic sensor does not exceed a preset rate of change threshold, and the amplitude of the distance signal fluctuation between the grinding wheel surface and the sensor detected by the laser displacement sensor is also less than a preset amplitude threshold. At this time, the PLC initially determines that the interference level is low. However, the acoustic sensor simultaneously detects high-frequency, high-intensity acoustic signals generated inside the special grinding wheel. After spectrum analysis, the identified liquid rupture frequency exceeds a preset frequency threshold (e.g., 5kHz), and the liquid rupture intensity also exceeds a preset intensity threshold. In this case, although the surface phenomenon shows low interference, the internal liquid rupture activity indicates the presence of a significant transient interference source. The PLC will correct the current interference level from low interference to high interference based on the acoustic signal judgment. Subsequently, the PLC will increase the learning step size of the least mean square algorithm according to the corrected high interference state, so that the adaptive filter can respond faster and eliminate the transient vibration interference component caused by internal liquid rupture. In this way, even under complex internal fluid dynamics, the system can maintain accurate identification and effective suppression of disturbances, thereby ensuring the accuracy of dynamic balance correction.

[0122] This application further proposes a PLC-based balancing machine control system for mold processing, wherein the aforementioned auxiliary sensor also includes a multispectral imaging camera;

[0123] A multispectral imaging camera is installed on the radial side of a special grinding wheel or on the inner wall of a protective cover to acquire multispectral images of the surface of the special grinding wheel or the inner wall of the protective cover.

[0124] Multispectral images constitute part of the state signal;

[0125] PLC is also used for image segmentation of multispectral images to identify the area and non-uniformity of liquid adhesion regions on the surface of special grinding wheels or the inner wall of protective covers.

[0126] When the area of ​​the liquid-attached region exceeds a preset area threshold, or the non-uniformity of the liquid-attached region exceeds a preset non-uniformity threshold, and the current interference level is in a low interference state, the interference level is corrected from a low interference state to a high interference state, and the learning step size of the least mean square algorithm is controlled according to the corrected interference level: the learning step size is increased in the high interference state, and the learning step size is decreased in the low interference state.

[0127] Specifically, a multispectral imaging camera is a sensor capable of simultaneously capturing images across multiple narrow bands, acquiring spectral information on reflection, absorption, or emission at different wavelengths. By analyzing this spectral information, the presence, distribution, and characteristics of liquids on the surface of specialized grinding wheels or the inner wall of protective shields can be more accurately identified and quantified. For example, water has strong absorption characteristics in specific infrared bands, so the liquid adhesion area can be identified by observing the response of multispectral images in these bands.

[0128] A multispectral imaging camera can be mounted radially to the side of a special grinding wheel for direct observation of its rotating surface; or it can be mounted on the inner wall of a balancing machine's protective cover to monitor any liquid accumulation that may occur on the cover. The acquired multispectral images are transmitted to a PLC as part of a status signal.

[0129] In this context, PLC image segmentation for multispectral images refers to separating the pixel regions representing liquid from the background regions in an image using image processing algorithms. For example, thresholding, region growing, or machine learning-based segmentation methods can be employed. Image segmentation identifies liquid-attached areas and further calculates their area and non-uniformity. The liquid-attached area refers to the total area covered by liquid on the surface of the special grinding wheel or the inner wall of the protective cover, while non-uniformity characterizes the uniformity or concentration of the liquid distribution.

[0130] When the PLC detects that the area of ​​the liquid adhesion region exceeds a preset area threshold, or the non-uniformity of the liquid adhesion region exceeds a preset non-uniformity threshold, even if the judgment results based on the ultrasonic sensor and laser displacement sensor indicate a low interference state, the PLC will correct the interference level to a high interference state. This correction mechanism aims to more sensitively capture potential interference caused by localized liquid adhesion or non-uniform distribution that might be overlooked by traditional methods.

[0131] Depending on the level of interference after correction, the PLC adjusts the learning step size of the least mean square algorithm accordingly. In the case of high interference, the learning step size is increased to enable the adaptive filter to respond faster and eliminate interference components caused by the liquid; while in the case of low interference, the learning step size is decreased to improve the stability and accuracy of the filter.

[0132] By introducing a multispectral imaging camera and combining it with image segmentation technology, the system can identify and quantify the area and non-uniformity of liquid adhesion regions. This allows it to promptly correct the interference level to a high-interference state, even when traditional sensors might deem it low-interference. This correction mechanism enables more flexible and accurate adjustment of the adaptive filter's learning step size, ensuring efficient elimination of interference components under various liquid interference scenarios, especially when localized or non-uniform liquid adhesion exists. This results in a vibration signal that more accurately reflects the mass distribution of the special grinding wheel. Ultimately, this significantly improves the accuracy, stability, and robustness of dynamic balancing correction, making it particularly suitable for high-precision dynamic balancing correction of special grinding wheels with open porous structures that easily absorb and retain liquids.

[0133] In some preferred embodiments, it is assumed that during the high-speed rotation of the special grinding wheel, most of the internal liquid has been ejected due to centrifugal force. The rate of change in the amount of liquid ejected is low, as detected by the ultrasonic sensor, and the fluctuation amplitude of the distance on the surface of the special grinding wheel is also small, as detected by the laser displacement sensor. At this point, the system initially determines that it is in a low-interference state. However, due to the special properties of the special grinding wheel material or the effect of surface tension, a small amount of liquid may still adhere to the surface of the special grinding wheel or the inner wall of the balancing machine's protective cover in the form of uneven patches.

[0134] Meanwhile, a multispectral imaging camera continuously acquires multispectral images of the surface of the special grinding wheel or the inner wall of the protective cover. After receiving these images, the PLC performs image segmentation processing. By analyzing the spectral response of specific bands in the images, the PLC identifies multiple irregular liquid adhesion areas. Further calculations reveal that although the total area of ​​these liquid adhesion areas is not large, their distribution is extremely uneven, causing the non-uniformity of the liquid adhesion areas to exceed a preset non-uniformity threshold.

[0135] Based on this, the PLC adjusts the current interference level from low interference to high interference. Subsequently, the PLC increases the learning step size of the least mean square algorithm, enabling the adaptive filter to more quickly adapt to and eliminate vibration interference caused by these unevenly deposited liquids. In this way, even localized liquid deposits that are difficult to detect with the naked eye can be accurately identified and effectively handled by the system, ensuring the accuracy and reliability of the dynamic balance correction.

[0136] To more accurately determine whether the change in the unbalance quantity meets the preset stability condition, this application proposes a more detailed judgment method.

[0137] The PLC is also used to determine whether the change in the magnitude of the imbalance over a continuous period of time is less than a magnitude threshold, thus obtaining a first judgment result; to determine whether the change in angular position is less than an angular threshold, thus obtaining a second judgment result; if both the first and second judgment results are yes, then the change in the imbalance is determined to satisfy the stability condition.

[0138] Specifically, during dynamic balancing, the PLC continuously monitors the calculated imbalance. The first step, determining whether the magnitude change of the imbalance over a continuous period is less than a threshold, involves the PLC tracking the magnitude of the imbalance and evaluating its magnitude over a continuous time period. If this magnitude change is less than the preset threshold, the imbalance is considered to be stable, and the first judgment result is "yes." The second step, determining whether the angular position change is less than the angle threshold, involves the PLC simultaneously monitoring the angular position change of the imbalance. If this angular position change is less than the preset angle threshold, the angular position of the imbalance is also considered to be stable, and the second judgment result is "yes." Only when both judgment results are "yes," meaning the magnitude and angular position of the imbalance have stabilized within a certain range, will the PLC ultimately determine that the change in the imbalance meets the preset stability condition. The magnitude and angle thresholds can be set and adjusted according to the characteristics of the special grinding wheel, balancing accuracy requirements, and practical application experience.

[0139] Through the above technical solution, this application can significantly improve the accuracy and reliability of dynamic balancing correction. Traditional stability condition judgments may be based on only a single index or relatively lenient conditions, which are easily affected by transient factors such as environmental noise or liquid ejection from the special grinding wheel, resulting in an unstable calculated imbalance and affecting the accuracy of counterweight correction. This application, however, by simultaneously considering the magnitude and angular position changes of the imbalance and setting strict thresholds, can more comprehensively and accurately assess the dynamic balance state of the special grinding wheel. Therefore, it can effectively avoid correction before the imbalance has stabilized, reduce the number of repeated corrections due to inaccurate corrections, improve balancing efficiency, and ultimately ensure the processing quality and service life of the special grinding wheel.

[0140] This application further proposes to optimize the specific implementation of the counterweight device in order to improve the automation level and correction accuracy of dynamic balance correction.

[0141] The aforementioned counterweight device is an automatic drilling device or an automatic counterweight block installation mechanism;

[0142] A one-time counterweight correction instruction includes the angle position to be corrected and the mass to be corrected.

[0143] The automatic drilling device is used to drill the mass that needs to be corrected at the angle position that needs to be corrected at the special grinding wheel.

[0144] The automatic counterweight installation mechanism is used to install the counterweight of the mass to be corrected at the angle position of the special grinding wheel.

[0145] Specifically, a counterweight device can be understood as a mechanical actuator capable of automatically correcting the mass of a special grinding wheel according to correction instructions generated by a PLC. As a preferred embodiment, this counterweight device can be implemented as an automatic drilling device or an automatic counterweight installation mechanism. The automatic drilling device refers to an automated device integrating drilling tools and a control unit, capable of precisely removing material at a specific angular position on the special grinding wheel according to received instructions, i.e., drilling out the required mass of material to achieve mass balance. Its purpose is to eliminate imbalance by reducing weight. On the other hand, the automatic counterweight installation mechanism refers to an automated device capable of automatically grabbing, positioning, and installing a pre-set mass of counterweight to a specific angular position on the special grinding wheel. Its purpose is to eliminate imbalance by increasing weight.

[0146] The one-time counterweight correction command is a control command generated by the PLC and sent to the counterweight device after determining that the imbalance of the special grinding wheel meets the stability condition. This command specifically includes two key parameters: the angle position to be corrected and the mass to be corrected. The angle position to be corrected refers to the precise circumferential position on the special grinding wheel where mass adjustment is required, usually expressed as an angle value. The mass to be corrected refers to the amount of mass that needs to be added or removed at that angle position.

[0147] When the counterweight device is an automatic drilling device, it receives and parses the one-time counterweight correction command. Based on the specified angle position to be corrected in the command, the automatic drilling device precisely positions the drill bit at that position on the special grinding wheel and performs drilling to the corresponding depth according to the mass parameters to be corrected, thereby removing the corresponding mass of material. When the counterweight device is an automatic counterweight block installation mechanism, it automatically selects a suitable counterweight block based on the specified angle position and mass to be corrected in the command and precisely installs it at that angle position on the special grinding wheel.

[0148] Through the above technical solution, this application can significantly improve the automation level and dynamic balancing accuracy of the control system for balancing machines used in abrasive machining. Because the counterweight device can automatically perform mass correction, it avoids errors and time consumption that may be introduced by manual operation, thereby shortening the correction cycle and improving production efficiency. Furthermore, the precision of the one-time counterweight correction command ensures the accuracy of the correction operation, enabling the dynamic balance state of the special grinding wheel to reach the required level faster and more stably, thus improving the machining quality and service life of the special grinding wheel.

[0149] In some preferred embodiments, assuming the PLC calculates and determines that the imbalance is stable, it generates a one-time counterweight correction command indicating that 0.5 grams of mass needs to be removed at the 180-degree position of the special grinding wheel. If the balancing machine is equipped with an automatic drilling device, this device will receive this command. Subsequently, the control system of the automatic drilling device will drive the drill bit to precisely move to the 180-degree circumferential position of the special grinding wheel, and automatically adjust the drilling depth and time according to the 0.5-gram mass requirement to perform precise material removal. After drilling is completed, the imbalance of the special grinding wheel is effectively corrected.

[0150] As another specific implementation, if the balancing machine is equipped with an automatic counterweight installation mechanism, and the instruction indicates that 1.2 grams of mass needs to be added at the 90-degree position of the special grinding wheel, then the automatic counterweight installation mechanism will select a 1.2-gram counterweight from its storage unit and, using its robotic arm or clamp, precisely install or adhere the counterweight to the 90-degree position of the special grinding wheel. In this way, the mass distribution of the special grinding wheel is adjusted, thereby achieving dynamic balance correction.

[0151] This application also discloses a PLC-based balancing machine control method for abrasive wheel processing, used for dynamic balancing correction of special grinding wheels with an open porous structure that easily adsorbs and retains liquid, including the following steps:

[0152] S1. Collect the original vibration signal, spindle rotation angle signal, and state signal characterizing the physical state change of the special grinding wheel caused by the ejection of internal liquid during its rotation;

[0153] S2. Determine the degree of interference of liquid ejection on vibration signals based on state signals;

[0154] S3. The original vibration signal is processed according to the degree of interference to eliminate the interference components caused by liquid splashing, and the processed vibration signal that reflects the true mass distribution of the special grinding wheel is obtained.

[0155] S4. Based on the amplitude and phase of the processed vibration signal and the rotor angular position corresponding to the spindle rotation angle signal, the unbalance of the special grinding wheel is calculated using the influence coefficient method.

[0156] S5. When the change in the unbalance meets the preset stability condition, a one-time counterweight correction command is generated and sent to the counterweight device for execution.

[0157] In some embodiments of this application, the above-mentioned PLC-based balancing machine control method for mold processing is proposed.

[0158] Specifically, in the steps of collecting the original vibration signal of the special grinding wheel during rotation, the spindle rotation angle signal, and the state signal characterizing the physical state change of the special grinding wheel caused by the ejection of internal liquid, the above embodiments have already described how the vibration sensor, rotary encoder, and auxiliary sensors collect these signals, and will not be repeated here. It is important to emphasize that the collection of these signals is the foundation of the entire dynamic balancing correction process, providing the necessary data input for subsequent interference judgment and imbalance calculation.

[0159] The step of determining the degree of interference of liquid ejection on the vibration signal based on the state signal can be understood as analyzing the state signal collected by the auxiliary sensor to assess the impact of liquid ejection on vibration measurement. Specifically, this step may include: threshold judgment on the signal of a single auxiliary sensor, for example, when the temperature of a certain area on the surface of the grinding wheel exceeds a preset temperature threshold, it is judged as a high interference state; or, by manually observing the liquid ejection on the surface of the grinding wheel or inside the protective cover, the operator manually inputs the judgment result of the interference level. The purpose is to provide a dynamic reference for subsequent vibration signal processing.

[0160] The step of processing the original vibration signal according to the degree of interference to eliminate interference components caused by liquid ejection and obtain a processed vibration signal reflecting the true mass distribution of the special grinding wheel can be understood as selecting an appropriate signal processing algorithm to filter or compensate the original vibration signal based on the aforementioned determined interference level. Specifically, when the interference is determined to be high, a digital filter with fixed parameters, such as a high-order Butterworth filter, can be used to suppress broadband noise with strong attenuation characteristics; when the interference is determined to be low, a milder low-pass filter can be used to retain more original signal information. The purpose is to extract effective vibration information reflecting the true mass distribution of the special grinding wheel from the original vibration signal affected by liquid ejection.

[0161] In practical applications, the steps for calculating the unbalance of special grinding wheels using the influence coefficient method are based on the amplitude and phase of the processed vibration signal and the rotor angular position corresponding to the spindle rotation angle signal. The basic principles and applications of the influence coefficient method have already been described in the above embodiments and will not be repeated here. It should be emphasized that this step is based on the vibration signal with interference eliminated, ensuring the accuracy of the unbalance calculation.

[0162] Furthermore, the step of generating a one-time counterweight correction command and sending it to the counterweight device for execution when the change in imbalance meets a preset stability condition can be understood as determining when to perform the final counterweight correction based on continuous monitoring of the imbalance change. Specifically, this stability condition can be set as follows: in three consecutive measurements, the amplitude of the imbalance is less than a certain fixed threshold, or the angular position of the imbalance fluctuates within a certain fixed angular range. The purpose is to ensure that the final counterweight correction is performed only when the liquid ejection process tends to stabilize and the imbalance truly reflects the mass distribution of the grinding wheel, thus avoiding ineffective correction of dynamically changing "false" imbalances.

[0163] Compared with existing control methods based on fixed-state measurement and single vibration signal processing, the core innovation of this application lies in introducing real-time sensing of physical state changes caused by liquid ejection and dynamically adjusting the vibration signal processing strategy according to the perceived level of interference. Traditional methods, when faced with dynamically changing mass distributions, cannot distinguish between the actual imbalance and the interference caused by liquid ejection, resulting in calculated counterweight schemes based on outdated or inaccurate data, leading to repeated corrections. This application, by explicitly adding the steps of "determining the degree of interference of liquid ejection on the vibration signal based on the state signal" and "processing the original vibration signal according to the degree of interference" to the method steps, enables the system to intelligently adapt to the dynamic process of liquid ejection inside the grinding wheel, effectively filtering out interference components, thereby obtaining a vibration signal reflecting the true mass distribution of the special grinding wheel.

[0164] Therefore, the method of this application can calculate a more accurate imbalance and generate and execute a counterweight correction command in one go when the imbalance change meets the stability condition. This "sensing-adapting-correcting" closed-loop control method significantly improves the accuracy and efficiency of dynamic balancing correction of special grinding wheels, avoids the problems of low production efficiency and excessively long balancing time caused by ineffective correction in traditional methods, and achieves fast, accurate and one-time convergent dynamic balancing correction.

[0165] In the embodiments provided in this application, it should be understood that the disclosed methods and systems can be implemented in other ways. The system embodiments described above are merely illustrative. For example, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple modules or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, and can be electrical, mechanical, or other forms.

[0166] In addition, each functional module in the various embodiments of this application can be fully integrated into a processor, or each module can be a separate device, or two or more modules can be integrated into a device; each functional module in the various embodiments of this application can be implemented in hardware or in the form of hardware plus software functional units.

[0167] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by program instructions and related hardware. The aforementioned program instructions can be stored in a computer-readable storage medium. When the program instructions are executed, they perform the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0168] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature.

[0169] If a flowchart is used in this application, it is used to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, the steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0170] The foregoing provides a detailed description of a PLC-based balancing machine control system and method for mold processing provided in this application. The above description of the disclosed embodiments enables those skilled in the art to implement or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A PLC-based balancing machine control system for abrasive tool processing, used for dynamic balancing of special grinding wheels with an open porous structure that easily adsorbs and retains liquid, characterized in that... include: PLC; A vibration sensor, installed on the spindle of the balancing machine, is used to collect raw vibration signals and transmit them to the PLC; A rotary encoder, installed at the end of the spindle, is used to collect spindle rotation angle signals and transmit them to the PLC; An auxiliary sensor is used to collect state signals characterizing the physical state changes of the special grinding wheel caused by the ejection of internal liquid during rotation, and to transmit the state signals to the PLC. A counterweight device, connected to the PLC, is used to execute counterweight correction commands; The PLC is used to determine the degree of interference of the liquid ejection on the vibration signal based on the status signal; to process the original vibration signal according to the degree of interference to eliminate the interference components caused by the liquid ejection, and to obtain a processed vibration signal that reflects the true mass distribution of the special grinding wheel; to calculate the unbalance of the special grinding wheel using the influence coefficient method based on the amplitude and phase of the processed vibration signal and the rotor angle position corresponding to the spindle rotation angle signal; and to generate a one-time counterweight correction command and send it to the counterweight device when the change of the unbalance meets the preset stability conditions.

2. The PLC-based balancing machine control system for mold processing according to claim 1, characterized in that, The auxiliary sensors include a laser displacement sensor and an ultrasonic sensor; The laser displacement sensor is installed on the radial side of the special grinding wheel, and its measuring beam is perpendicular to the rotation axis of the special grinding wheel. It is used to collect the distance signal between the surface of the special grinding wheel and the laser displacement sensor. The ultrasonic sensor is installed on the inner wall of the balancing machine's protective cover and is used to collect signals characterizing the amount of liquid ejected from the special grinding wheel.

3. The PLC-based balancing machine control system for mold processing according to claim 1, characterized in that, The PLC is also used to: control the special grinding wheel to run according to a preset speed change curve before acquiring the original vibration signal and the status signal, the speed change curve including a high speed stage and a low speed stage executed sequentially.

4. The PLC-based balancing machine control system for mold processing according to claim 2, characterized in that, The PLC is used to determine the level of interference based on the status signal, specifically as follows: Acquire the signal from the ultrasonic sensor that represents the amount of liquid ejected from the special grinding wheel, and calculate its rate of change; The distance signal between the surface of the special grinding wheel and the laser displacement sensor, collected by the laser displacement sensor, is obtained, and its fluctuation amplitude is calculated. When the rate of change does not exceed a preset rate of change threshold and the fluctuation amplitude is less than a preset amplitude threshold, the interference level is determined to be a low interference state. Otherwise, the interference level is determined to be a high interference state.

5. The PLC-based balancing machine control system for mold processing according to claim 4, characterized in that, The PLC is specifically used to perform adaptive filtering processing on the original vibration signal based on the least mean square algorithm according to the degree of interference, so as to eliminate the interference components caused by the liquid splashing out. When the interference level is at the high interference state, the PLC increases the learning step size of the minimum mean square algorithm; When the interference level is in the low interference state, the PLC reduces the learning step size of the least mean square algorithm.

6. The PLC-based balancing machine control system for mold processing according to claim 5, characterized in that, The auxiliary sensor also includes an acoustic sensor; The acoustic sensor is installed on the inner wall of the protective cover of the balancing machine or on the outer shell of the bearing seat of the balancing machine, and is used to collect the acoustic signal generated by the rupture of the liquid inside the special grinding wheel; The acoustic signal constitutes a part of the state signal; The PLC is also used to identify the liquid rupture frequency and liquid rupture intensity based on the spectral characteristics of the acoustic signal; When the detected liquid rupture frequency exceeds a preset frequency threshold, or the liquid rupture intensity exceeds a preset intensity threshold, and the current interference level is in the low interference state, the interference level is corrected from the low interference state to the high interference state, and the learning step size of the least mean square algorithm is controlled according to the corrected interference level: the learning step size is increased in the high interference state, and the learning step size is decreased in the low interference state.

7. The PLC-based balancing machine control system for mold processing according to claim 5, characterized in that, The auxiliary sensor also includes a multispectral imaging camera; The multispectral imaging camera is installed on the radial side of the special grinding wheel or on the inner wall of the protective cover, and is used to acquire multispectral images of the surface of the special grinding wheel or the inner wall of the protective cover. The multispectral image constitutes part of the state signal; The PLC is also used to perform image segmentation on the multispectral image and identify the area and non-uniformity of the liquid adhesion region on the surface of the special grinding wheel or the inner wall of the protective cover. When the area of ​​the liquid-attached region exceeds a preset area threshold, or the non-uniformity of the liquid-attached region exceeds a preset non-uniformity threshold, and the current interference level is in the low interference state, the interference level is corrected from the low interference state to the high interference state, and the learning step size of the least mean square algorithm is controlled according to the corrected interference level: the learning step size is increased in the high interference state, and the learning step size is decreased in the low interference state.

8. The PLC-based balancing machine control system for mold processing according to claim 1, characterized in that, The PLC is also used to determine whether the change in the magnitude of the imbalance over a continuous period of time is less than a magnitude threshold, and to obtain a first determination result; Determine whether the change in angular position is less than an angular threshold to obtain a second judgment result; If both the first and second judgment results are yes, then the change in the unbalance quantity is determined to satisfy the stability condition.

9. The PLC-based balancing machine control system for mold processing according to claim 1, characterized in that, The counterweight device is an automatic drilling device or an automatic counterweight block installation mechanism; The one-time counterweight correction instruction includes the angle position to be corrected and the mass to be corrected; The automatic drilling device is used to drill the mass to be corrected at the angle position to be corrected on the special grinding wheel; The automatic counterweight installation mechanism is used to install the counterweight of the mass to be corrected at the angle position to be corrected on the special grinding wheel.

10. A PLC-based control method for a balancing machine in abrasive machining, used for dynamic balancing of special grinding wheels with an open porous structure that easily adsorbs and retains liquid, characterized in that... Includes the following steps: The original vibration signal, spindle rotation angle signal, and state signal characterizing the physical state change of the special grinding wheel caused by the ejection of internal liquid were collected during the rotation of the special grinding wheel. The degree of interference of the liquid ejection on the vibration signal is determined based on the state signal. The original vibration signal is processed according to the degree of interference to eliminate the interference components caused by the liquid splashing out, so as to obtain a processed vibration signal that reflects the true mass distribution of the special grinding wheel. Based on the amplitude and phase of the processed vibration signal and the rotor angle position corresponding to the spindle rotation angle signal, the unbalance of the special grinding wheel is calculated using the influence coefficient method. When the change in the imbalance meets the preset stability condition, a one-time counterweight correction command is generated and sent to the counterweight device for execution.

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