A paper feeding process path control method and system

Abstract

The application relates to the technical field of paper feeding process control, and provides a paper feeding process path control method and system, which comprises the following steps: acquiring current data of a servo motor of a paper picking mechanical arm, shaking data of a suction cup of the paper picking mechanical arm and a current total working time length of the servo motor; determining the friction characteristic of the servo motor according to the current data and the shaking data; the friction characteristic is used for indicating that the friction force of the servo motor is normal or the friction force of the servo motor is abnormal; in the case that the friction characteristic indicates that the friction force of the servo motor is abnormal, the driving force of the servo motor is adjusted based on the current data, the shaking data and the current total working time length of the servo motor, so as to inhibit path trajectory deviation. The accuracy of paper feeding process path control can be improved.

Description

Technical Field

[0001] This application relates to the field of paper feeding process control technology, and in particular to a paper feeding process path control method and system. Background Technology

[0002] In automated production lines, precise control of the paper feeding process is crucial for ensuring product quality and production efficiency. Typically, robotic arms, driven by servo motors, accurately pick up and deliver paper. However, as the equipment runs for extended periods, the frictional characteristics within the servo motor undergo subtle changes, which can cause slight vibrations in the end effector's suction cup when the robotic arm performs high-speed movements.

[0003] When handling certain types of paper, such as smooth, thin, and low-stiffness paper, these minute vibrations can affect the contact between the suction cup and the paper, leading to unstable adhesion, or even multiple sheets of paper sticking together or the paper shifting when lifted. Existing detection methods often struggle to capture these subtle anomalies, thus affecting the smooth operation of subsequent processes and resulting in low precision in the path control of the paper feeding process. Summary of the Invention

[0004] This application provides a method and system for path control in the paper feeding process, which can improve the accuracy of path control in the paper feeding process.

[0005] To achieve the above objectives, this application adopts the following technical solution:

[0006] In a first aspect, this application discloses a path control method for a paper feeding process. The method includes: acquiring current data of a servo motor of a paper picking robot arm, jitter data of the suction cup of the paper picking robot arm, and the current total working time of the servo motor; determining the friction characteristics of the servo motor based on the current data and jitter data; the friction characteristics are used to indicate whether the friction force of the servo motor is normal or abnormal; when the friction characteristics indicate that the friction force of the servo motor is abnormal, adjusting the driving force of the servo motor based on the current data, jitter data, and the current total working time of the servo motor to suppress path trajectory deviation.

[0007] Furthermore, the friction characteristics of the servo motor are determined based on the current data and jitter data, including: performing FFT processing on the current data to obtain the current parameter value of the target parameter of the target harmonic of the current data; the target parameter includes amplitude or phase; and determining the friction characteristics of the servo motor based on the current parameter value of the target parameter and the jitter data.

[0008] Based on this, the friction characteristics of the servo motor are determined according to the current parameter value of the target parameter and the jitter data, including: obtaining the normal parameter value of the target parameter when the friction force of the servo motor is normal; determining the target difference; the target difference is the difference between the current parameter value and the normal parameter value; when the absolute value of the target difference is greater than the preset difference threshold, the friction characteristics of the servo motor are determined according to the jitter data and the friction characteristics of the servo motor to indicate that the friction force of the servo motor is abnormal.

[0009] Furthermore, when the absolute value of the target difference is greater than a preset difference threshold, the friction characteristics of the servo motor are determined based on the jitter data and the friction characteristics of the servo motor to indicate abnormal friction force of the servo motor. This includes: performing FFT processing on the jitter data to obtain the parameter value of the target jitter parameter at the target frequency; and determining the friction characteristics of the servo motor to indicate abnormal friction force of the servo motor when the parameter value of the target jitter parameter is greater than a preset jitter parameter threshold.

[0010] In another implementation, adjusting the driving force of the servo motor based on current data, jitter data, and the current total operating time of the servo motor includes: determining a target driving force adjustment value for the servo motor based on current data, jitter data, and the current total operating time of the servo motor; and using the sum of the current driving force of the servo motor and the target driving force adjustment value as the adjusted driving force of the servo motor.

[0011] As a technical improvement, the target driving force adjustment value of the servo motor is determined based on current data, jitter data, and the current total working time of the servo motor. This includes: determining the current driving force adjustment value based on the current data; determining the jitter driving force adjustment value based on the jitter data; and determining the target driving force adjustment value based on the current driving force adjustment value, the jitter driving force adjustment value, and the current total working time of the servo motor.

[0012] To improve the solution, the current driving force adjustment value is determined based on the current data, including: obtaining a first correspondence; the first correspondence includes a one-to-one correspondence between multiple difference ranges and multiple current adjustment coefficients; taking the current adjustment coefficient corresponding to the difference range where the target difference is located in the first correspondence as the target current adjustment coefficient; the target difference is the difference between the current parameter value of the target parameter of the target harmonic of the current data and the normal parameter value of the target parameter when the friction force of the servo motor is normal; and taking the product of the current driving force of the servo motor and the target current adjustment coefficient as the current driving force adjustment value.

[0013] To enhance functionality, a jitter driving force adjustment value is determined based on jitter data, including: obtaining a second correspondence; the second correspondence includes a one-to-one correspondence between multiple jitter parameter value ranges and multiple jitter adjustment coefficients; using the jitter adjustment coefficient corresponding to the jitter parameter value range of the jitter data at the target frequency in the second correspondence as the target jitter adjustment coefficient; and using the product of the current driving force and the target jitter adjustment coefficient as the jitter driving force adjustment value.

[0014] To optimize the structure, a target drive force adjustment value is determined based on the current drive force adjustment value, the jitter drive force adjustment value, and the current total working time of the servo motor. This includes: using the sum of the current drive force adjustment value and the jitter drive force adjustment value as the initial drive force adjustment value; obtaining a third correspondence; this third correspondence includes a one-to-one correspondence between multiple total working time ranges and multiple working time correction coefficients; using the working time correction coefficient corresponding to the total working time range in the third correspondence as the target working time correction coefficient; and using the product of the target working time correction coefficient and the initial drive force adjustment value as the target drive force adjustment value.

[0015] Secondly, this application also discloses a paper feeding process path control system, which includes: an acquisition device and a processing device; the acquisition device is used to acquire current data of the servo motor of the paper picking robot arm, jitter data of the suction cup of the paper picking robot arm, and the current total working time of the servo motor; the processing device is used to determine the friction characteristics of the servo motor based on the current data and jitter data; the friction characteristics are used to indicate whether the friction force of the servo motor is normal or abnormal; the processing device is used to adjust the driving force of the servo motor based on the current data, jitter data, and the current total working time of the servo motor when the friction characteristics indicate that the friction force of the servo motor is abnormal, so as to suppress path trajectory deviation.

[0016] Beneficial effects

[0017] This application provides a path control method for a paper feeding process. It acquires current data of the servo motor of a paper-picking robotic arm, jitter data of the suction cup, and the current total working time of the servo motor, and determines the friction characteristics of the servo motor based on the current and jitter data. These friction characteristics indicate whether the friction force of the servo motor is normal or abnormal. When the friction characteristics indicate abnormal friction force, this application adjusts the driving force of the servo motor based on the current data, jitter data, and the current total working time of the servo motor to suppress path trajectory deviation.

[0018] Through the above technical solution, this application effectively solves the problem in the prior art where subtle changes in the internal friction characteristics of the servo motor are difficult to detect, leading to vibration of the robotic arm's suction cup, which in turn causes unstable paper adsorption, multiple sheets sticking together, or path deviation. Specifically, this application, by monitoring current and vibration data in real time, can capture early signs of changes in the friction characteristics of the servo motor, avoiding the problems caused by the lag of traditional fault alarm thresholds. Simultaneously, by combining the total working time of the servo motor, the aging degree and potential risks of the motor can be more comprehensively assessed. When abnormal friction is detected, the system can intelligently adjust the driving force of the servo motor to compensate for the path trajectory deviation caused by friction changes, ensuring that the robotic arm maintains high precision and stability even at high speeds. This not only improves the accuracy of paper feeding and effectively avoids the occurrence of "hidden double sheets" or "unstable single sheets," but also reduces the risk of defective products entering subsequent processes, significantly improving production efficiency and product quality. Accordingly, this application overcomes the shortcomings of insufficient detection of hidden anomalies and the lack of effective compensation mechanisms in the prior art, achieving refined and adaptive control of the paper feeding process path. Attached Figure Description

[0019] Figure 1 A flowchart illustrating a paper feeding process path control method provided in this application;

[0020] Figure 2 A flowchart illustrating a paper feeding process path control method provided in this application;

[0021] Figure 3 A flowchart illustrating a paper feeding process path control method provided in this application;

[0022] Figure 4 This is a schematic diagram of the architecture of a paper feeding process path control system provided in this application. Detailed Implementation

[0023] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0024] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0025] In automated production lines, precise control of the paper feeding process is crucial for ensuring product quality and production efficiency. Typically, robotic arms, driven by servo motors, accurately pick up and deliver paper. However, as the equipment runs for extended periods, the frictional characteristics within the servo motor undergo subtle changes, which can cause slight vibrations in the end effector's suction cup when the robotic arm performs high-speed movements.

[0026] When handling certain types of paper, such as smooth, thin, and low-stiffness paper, these minute vibrations can affect the contact between the suction cup and the paper, leading to unstable adhesion, or even multiple sheets of paper sticking together or the paper shifting when lifted. Existing detection methods often struggle to capture these subtle anomalies, thus affecting the smooth operation of subsequent processes and resulting in low precision in the path control of the paper feeding process.

[0027] In this regard, such as Figure 1 As shown, this application proposes a path control method for a paper feeding process, the method comprising:

[0028] S101. Obtain the current data of the servo motor of the paper picking robot arm, the vibration data of the suction cup of the paper picking robot arm, and the current total working time of the servo motor.

[0029] S102. Determine the friction characteristics of the servo motor based on the current data and jitter data.

[0030] Friction characteristics are used to indicate whether the friction force of a servo motor is normal or abnormal.

[0031] S103. When the friction characteristics indicate that the friction force of the servo motor is abnormal, adjust the driving force of the servo motor based on the current data, jitter data and the current total working time of the servo motor to suppress the path trajectory deviation.

[0032] This application, by real-time monitoring of servo motor current data and suction cup vibration data, combined with the servo motor's current total working time, can accurately identify abnormal friction states of the servo motor. Once an abnormality is detected, the system will intelligently adjust the servo motor's driving force, thereby effectively suppressing deviation of the robotic arm's path trajectory, significantly improving the stability and accuracy of paper feeding, and solving the problem of difficulty in detecting and correcting hidden faults in existing technologies.

[0033] To better understand the technical solution proposed in this application, some key terms and implementation environments are first explained. In this application, "paper-picking robotic arm" refers to an industrial robotic arm used to grasp and transport paper on an automated production line. It is typically driven by multiple joints and servo motors, with a suction cup at its end for adsorbing paper. A "servo motor" is a motor that precisely controls motion; its "current data" reflects the load and internal state of the motor during operation, while "jitter data" quantifies the minute vibrations or offsets of the suction cup at the end of the robotic arm during movement. "Friction characteristics" describe the internal friction state of the servo motor, indicating whether the friction is within the normal range or abnormal. "Driving force" refers to the torque output by the servo motor, directly affecting the movement of the robotic arm. "Path trajectory deviation" refers to the deviation between the actual trajectory and the ideal trajectory when the robotic arm executes a preset motion path. This method is typically implemented in an industrial control system or embedded system that can acquire sensor data in real time, perform data processing and algorithm calculations, and send instructions to the servo motor controller to adjust its driving force.

[0034] The core of the paper feeding process path control method proposed in this application lies in the effective suppression of the robotic arm's path trajectory deviation through comprehensive perception and intelligent analysis of the servo motor's operating status.

[0035] Firstly, acquiring the current data of the servo motor of the paper-picking robotic arm, the jitter data of the suction cup of the paper-picking robotic arm, and the current total working time of the servo motor can be achieved in several ways. For example, current data can be acquired in real time by integrating a current sensor into the servo motor driver. This sensor converts the phase current or total current of the motor into an electrical signal, which is then converted into a digital signal by an analog-to-digital converter (ADC) for processing by the control system. Jitter data can be acquired by installing a high-precision accelerometer or laser displacement sensor near the suction cup at the end of the robotic arm. These sensors can capture minute vibrations or positional deviations of the suction cup during movement and convert these physical quantities into electrical signals for digital processing. The current total working time of the servo motor can be recorded using an internal timer or accumulator. The timer starts each time the motor starts and pauses when it stops, accumulating the time into the total duration.

[0036] Secondly, the frictional characteristics of the servo motor are determined based on current and jitter data. These characteristics indicate whether the servo motor's friction is normal or abnormal. In one implementation, this can be determined by analyzing the time-domain or frequency-domain characteristics of the current data. For example, a current threshold can be set; if the current value of the servo motor consistently exceeds this threshold when operating under no-load or light-load conditions, it may indicate an abnormal increase in friction. Alternatively, by analyzing specific harmonic components in the current signal, significant changes in the amplitude or phase of these harmonic components may also indicate a change in frictional characteristics. Simultaneously, jitter data can also serve as an auxiliary basis for judgment. For instance, when the suction cup exhibits jitter exceeding a preset range during a specific movement phase, combining this data with current data can more accurately determine whether the friction is abnormal.

[0037] Finally, when the friction characteristics indicate abnormal friction in the servo motor, the driving force of the servo motor is adjusted based on current data, jitter data, and the servo motor's current total operating time to suppress path trajectory deviation. When the system determines that the servo motor's friction is abnormal, the driving force needs to be adjusted. For example, based on the degree of abnormality in the current data, the driving current or voltage of the servo motor can be appropriately increased to compensate for the increased friction. Simultaneously, considering the jitter data, if the jitter amplitude is large, a larger adjustment of the driving force may be needed, or the frequency response characteristics of the driving force may be adjusted to suppress resonance. Furthermore, the current total operating time of the servo motor can also be used as a reference factor for adjusting the driving force, because after prolonged operation, internal mechanical wear and aging of the motor may cause friction to gradually increase. Therefore, for motors with a longer total operating time, a more aggressive driving force adjustment strategy can be adopted when abnormal friction is detected. In this way, it can be ensured that the robotic arm can still maintain its preset motion path and avoid path trajectory deviation even when abnormal friction is detected.

[0038] The overall working principle of this application lies in constructing an intelligent friction characteristic assessment and driving force adjustment mechanism by real-time, multi-dimensional monitoring and analysis of the servo motor's operating status of the paper-picking robotic arm. After acquiring the servo motor's current data, suction cup vibration data, and the servo motor's current total operating time, the system first uses the current and vibration data to comprehensively judge the servo motor's friction characteristics. This judgment is not a simple threshold comparison, but rather involves in-depth data analysis, such as frequency domain analysis, to identify whether the friction force is in an abnormal state. Once an abnormal friction force is detected, the system does not immediately trigger a shutdown alarm. Instead, based on the currently collected current data, vibration data, and the servo motor's cumulative operating time, it intelligently calculates an optimal driving force adjustment value. This adjustment value is applied to the servo motor in real time, thereby compensating for insufficient or excessive driving force caused by abnormal friction force, allowing the robotic arm to continue moving precisely along the preset path trajectory, effectively suppressing path trajectory deviation. The entire process forms a closed-loop control system, realizing early warning and adaptive compensation for potential servo motor faults, ensuring the stability and accuracy of the paper feeding process.

[0039] This application offers significant advantages and innovations compared to existing technologies. Traditional methods often rely on simple fault threshold alarms or periodic maintenance, making it difficult to capture subtle and gradual changes in the internal frictional characteristics of servo motors, thus hindering effective intervention before faults occur. For example, existing systems may only alarm when motor current or jitter reaches a severe level, by which time the robotic arm's path may have already deviated significantly, potentially leading to paper pickup failure or double-sheet issues. The core innovation of this application lies in its incorporation of these data into the servo motor's "frictional characteristics," along with the "total current working time" as a measure of aging. This allows for earlier and more accurate identification of potential frictional anomalies. By adjusting the driving force at the early stages of frictional anomalies, this application proactively suppresses path deviations, preventing the problem from worsening. This preventative and adaptive control strategy significantly improves the stability and reliability of the paper feeding process, substantially reducing production efficiency losses and product quality issues caused by latent faults, demonstrating the advancement and practicality of this application in the field of automation control.

[0040] Specifically, in the above-mentioned paper feeding process path control method, the friction characteristics of the servo motor can be determined based on the current data and jitter data in the following manner.

[0041] like Figure 2 As shown, the frictional characteristics of the servo motor are determined based on the aforementioned current and jitter data, specifically including:

[0042] S201. Perform FFT processing on the current data to obtain the current parameter values ​​of the target harmonic of the current data.

[0043] The target parameters include amplitude or phase.

[0044] S201. Determine the friction characteristics of the servo motor based on the current parameter values ​​of the target parameters and the jitter data.

[0045] FFT (Fast Fourier Transform) is an algorithm that converts time-domain signals into frequency-domain signals. By performing FFT processing on the current data of a servo motor, the amplitude and phase information of different frequency components in the current signal can be analyzed. During operation, changes in the internal friction of the servo motor cause changes in specific harmonic components in the current signal. The target harmonic refers to a specific frequency component closely related to the changes in the friction characteristics of the servo motor. Target parameters, such as amplitude or phase, are indicators used to quantify the characteristics of these harmonic components. The current parameter value is the real-time value of the target parameter of the target harmonic obtained after FFT processing.

[0046] Furthermore, after obtaining the current parameter values ​​of the target harmonics of the current data, and combining this with the jitter data of the suction cup of the paper-picking robotic arm, the friction characteristics of the servo motor can be comprehensively assessed. The jitter data reflects the vibration of the robotic arm during movement, and abnormal friction often leads to increased mechanical vibration or a change in its pattern. Therefore, combining the frequency domain characteristics of the current signal with the mechanical jitter data allows for a more comprehensive and accurate evaluation of the servo motor's friction state.

[0047] This application's solution, through FFT processing of servo motor current data, effectively extracts the amplitude or phase information of specific harmonic components related to frictional changes from complex current signals. Internal frictional anomalies in the servo motor, such as bearing wear or poor lubrication, typically generate specific vibration frequencies during motor operation. These vibrations couple into the motor's current signal, manifesting as abnormalities in the amplitude or phase of specific harmonics. FFT processing amplifies and identifies these weak anomalous signals. Simultaneously, by combining the vibration data of the suction cup of the paper-picking robotic arm, the frictional state reflected in the current data can be verified and supplemented from a mechanical motion perspective. When friction is abnormal, the robotic arm's vibration increases or exhibits a specific pattern, which corroborates the harmonic anomalies in the current signal, thereby improving the accuracy and reliability of frictional characteristic assessment.

[0048] By employing the aforementioned technical solution, FFT processing of current data combined with jitter data is used to determine the frictional characteristics of the servo motor, enabling early and accurate diagnosis of the servo motor's frictional state. Compared to methods relying solely on a single data source or simple threshold judgments, this solution, by analyzing the frequency domain characteristics of the current signal, can more sensitively capture subtle signs of frictional force changes, effectively identifying even the initial stages of frictional anomalies. Simultaneously, the introduction of jitter data for auxiliary judgment further enhances the reliability and anti-interference capability of the diagnosis, avoiding misjudgments. This provides an accurate basis for timely adjustment of the servo motor's driving force, effectively suppressing path trajectory deviation and ensuring the stability and accuracy of the paper feeding process.

[0049] like Figure 3 As shown, this application further proposes the above-mentioned method for determining the frictional characteristics of a servo motor based on the current parameter values ​​of the target parameters, including:

[0050] S301. Obtain the normal parameter value of the target parameter when the friction force of the servo motor is normal.

[0051] S302. Determine the target difference; the target difference is the difference between the current parameter value and the normal parameter value.

[0052] S303. When the absolute value of the target difference is greater than the preset difference threshold, the friction characteristics of the servo motor are determined based on the jitter data and the friction characteristics of the servo motor to indicate that the friction force of the servo motor is abnormal.

[0053] Specifically, the normal parameter value of the target parameter when the friction of the servo motor is normal refers to the reference value of the target parameter (such as amplitude or phase) of the target harmonic obtained by performing FFT processing on the current data when the servo motor is in normal working condition and the friction is not abnormal. This normal parameter value can be measured and recorded before the servo motor is put into use or during regular maintenance, and can serve as a reference for subsequent judgment on whether the friction is abnormal.

[0054] The target difference can be understood as the degree of deviation between the currently measured target parameter value and the preset normal parameter value. By calculating the difference between the two, the difference between the current operating state of the servo motor and the normal state can be quantified.

[0055] In practical applications, when the absolute value of the target difference exceeds the preset difference threshold, it indicates that the servo motor's operating state has significantly deviated from the normal state. In this case, further judgment is needed based on jitter data. The preset difference threshold is an empirical value or a critical value determined through experiments, used to distinguish between normal fluctuations and potential abnormalities. Based on this, and according to the jitter data and the servo motor's friction characteristics, it can be ultimately determined whether the servo motor's friction characteristics indicate an abnormal frictional force.

[0056] This application's solution introduces the normal parameter value of the target parameter when the servo motor's friction force is normal, and calculates the target difference between the current parameter value and this normal parameter value, thus providing a quantitative indicator to assess the deviation of the servo motor's operating state. When the absolute value of this target difference exceeds a preset difference threshold, it indicates that the servo motor's friction force may have become abnormal. Based on this, further judgment using jitter data can verify or refine the indication of abnormal friction force. This step-by-step judgment mechanism first provides an initial abnormal signal through current data analysis, and then confirms it through jitter data, effectively avoiding misjudgments that may arise from a single data source, and improving the accuracy and reliability of friction characteristic judgment. It is precisely because of this mechanism based on benchmark value comparison and multi-source data verification that abnormal friction force of the servo motor can be identified earlier and more accurately.

[0057] Through the above technical solution, this application provides a more accurate and reliable method for judging the friction characteristics of servo motors. Compared with a general judgment based solely on the current parameter values ​​and jitter data of the target parameters, this solution introduces normal parameter values ​​and preset difference thresholds to achieve quantitative detection of frictional anomalies, significantly improving the sensitivity and accuracy of anomaly detection. This precise judgment helps to promptly identify potential faults in the servo motor, thereby enabling earlier adjustment of the servo motor's driving force, effectively suppressing path deviations during paper feeding, and avoiding production efficiency decline and product quality problems caused by abnormal friction.

[0058] In some preferred embodiments, a specific example is given below. Assume that when the servo motor is operating normally, the normal parameter value of the target harmonic amplitude (as the target parameter) obtained through FFT processing of the current data is 10mA. During actual operation, at a certain moment, the current parameter value of the target harmonic amplitude is detected to be 15mA. At this time, the target difference is calculated to be 15mA - 10mA = 5mA. If the preset difference threshold is set to 3mA, then because the absolute value of the target difference, 5mA, is greater than the preset difference threshold of 3mA, the system will initially determine that the friction of the servo motor may be abnormal.

[0059] Furthermore, the system analyzes the jitter data acquired at this time. For example, if the jitter parameter value at the target frequency also shows an abnormally increasing trend (e.g., exceeding the preset jitter parameter threshold), then the friction characteristics of the servo motor indicate an abnormal friction force. Conversely, if the jitter data is normal, it may indicate that the deviation of the current parameter value is caused by other non-friction force abnormal factors, thus avoiding misjudgment. In this way, the solution of this application can achieve accurate identification of abnormal friction force in servo motors.

[0060] This application further proposes a more accurate and reliable method for judging friction characteristics, which improves the accuracy of judging friction anomalies by combining vibration data for secondary confirmation.

[0061] Specifically, when the absolute value of the aforementioned target difference is greater than a preset difference threshold, the friction characteristics of the servo motor are determined based on the jitter data and the friction characteristics of the servo motor to indicate abnormal friction force of the servo motor. This includes: performing FFT processing on the jitter data to obtain the parameter value of the target jitter parameter at the target frequency; and determining the friction characteristics of the servo motor to indicate abnormal friction force of the servo motor when the parameter value of the target jitter parameter is greater than a preset jitter parameter threshold.

[0062] The FFT processing of jitter data involves converting time-domain jitter data into frequency-domain data using a Fast Fourier Transform. The purpose is to decompose complex jitter signals into simple harmonic components of different frequencies, thereby identifying characteristic frequencies associated with specific mechanical faults (such as bearing wear, gear meshing defects, etc.). The target frequency can be understood as a specific vibration frequency closely related to abnormal friction in the servo motor. For example, when a component inside the servo motor wears down, it may produce significant vibration at a specific frequency. The target jitter parameter value refers to the amplitude, power spectral density, or other quantifiable indicators of jitter intensity at the target frequency. Furthermore, the preset jitter parameter threshold is a pre-defined benchmark value used to distinguish between normal and abnormal jitter. This threshold can be determined through long-term monitoring and data analysis of the servo motor under normal operating conditions, or through experimental testing and experience accumulation. When the target jitter parameter value exceeds the preset jitter parameter threshold, it indicates that the jitter intensity of the servo motor at a specific frequency has exceeded the normal range, thus strongly supporting the judgment of abnormal servo motor friction.

[0063] This application's solution addresses the potential for misjudgment or missed detection that may arise from relying solely on current data by introducing FFT processing and threshold judgment of jitter data. Friction anomalies are often accompanied by vibration or jitter of mechanical components, which exhibit specific characteristics in the frequency domain. By performing FFT processing on the jitter data, the intensity of jitter at these characteristic frequencies can be accurately captured. When current data indicates a possible friction anomaly, a secondary confirmation is made by combining the jitter data with the jitter parameter value at the target frequency to check if it exceeds a preset threshold. This allows for a more direct and accurate reflection of the actual mechanical friction state of the servo motor. It is precisely this multi-dimensional and complementary judgment mechanism that makes the identification of friction anomalies more reliable, avoiding the limitations that may arise from a single data source.

[0064] Through the above technical solution, this application can significantly improve the accuracy and reliability of servo motor friction characteristic judgment. By combining current data analysis with jitter data analysis, misjudgments or omissions caused by the limitations of a single data source can be effectively avoided, especially in the early stages of friction anomalies or when the manifestations are not obvious. This dual confirmation mechanism makes the diagnosis of servo motor friction status more comprehensive and accurate, thus providing a more solid and reliable basis for subsequent drive force adjustment, and ultimately helping to more effectively suppress the path trajectory deviation of the paper picking robot arm, ensuring the stability and accuracy of the paper feeding process.

[0065] In some preferred embodiments, a specific example is given below. Suppose that during operation of the servo motor of a paper-picking robotic arm, the absolute value of the target difference between the current value and the normal value of the target parameter of the target harmonic of its current data is detected to be greater than a preset difference threshold. This initially indicates that the servo motor may have abnormal friction. To further confirm this, the system immediately collects the jitter data of the servo motor. Subsequently, the collected jitter data is sent to the FFT processing module for frequency domain analysis to obtain the parameter value of the target jitter parameter at a specific target frequency (e.g., a frequency related to servo motor bearing wear). If the parameter value of this target jitter parameter is further detected to be greater than the preset jitter parameter threshold, then it is finally determined that the friction characteristics of the servo motor indicate an abnormal friction force. Conversely, if the current data shows an abnormality, but the jitter data does not exceed the preset jitter parameter threshold at the target frequency, it may indicate that the current abnormality is not caused by mechanical friction, thus avoiding unnecessary drive force adjustments.

[0066] This application further proposes a more specific and optimized method for adjusting the driving force, which aims to determine the amount of driving force adjustment in a structured manner, thereby improving the accuracy and effectiveness of the adjustment.

[0067] The driving force of the servo motor is adjusted based on the aforementioned current data, jitter data, and the current total working time of the servo motor. Specifically, this includes: determining the target driving force adjustment value of the servo motor based on the current data, jitter data, and the current total working time of the servo motor; and using the sum of the current driving force of the servo motor and the target driving force adjustment value as the adjusted driving force of the servo motor.

[0068] Specifically, the target driving force adjustment value is a quantified value calculated based on the servo motor's operating status (reflected by current data, jitter data, and current total working time) to correct its current driving force. This value can be positive (increasing driving force) or negative (decreasing driving force), and its magnitude and direction depend on the degree and type of friction anomaly. The adjusted servo motor driving force is the new driving force obtained by adding the target driving force adjustment value to the servo motor's current driving force. In this way, the output torque of the servo motor can be dynamically and precisely adjusted to compensate for path trajectory deviation caused by friction anomalies. In practical applications, this adjustment process aims to adjust the actual driving force of the servo motor to a level that can effectively counteract the effects of abnormal friction, thereby ensuring that the movement trajectory of the paper-picking robotic arm conforms to the preset path as closely as possible.

[0069] The proposed solution refines the drive force adjustment process into two distinct steps: first, determining the target drive force adjustment value for the servo motor; and then, superimposing this adjustment value with the current drive force of the servo motor to form the adjusted drive force. This structured adjustment method ensures that drive force correction is no longer vague or empirical, but rather a quantitative and targeted adjustment calculated based on a comprehensive analysis of the servo motor's current data, jitter data, and total operating time. This ensures that when the servo motor experiences abnormal friction, its drive force can be precisely corrected to effectively counteract the impact of abnormal friction on the path trajectory, thereby suppressing path trajectory deviation. In this way, drive force adjustment becomes more controllable and precise, avoiding over-compensation or under-compensation problems that may result from improper adjustment.

[0070] Through the above technical solution, this application provides a more refined and quantifiable driving force adjustment mechanism. Compared to a basic solution that only indicates the need to adjust the driving force, this application clarifies the specific operation of calculating the target driving force adjustment value and superimposing it on the current driving force, thereby significantly improving the accuracy and responsiveness of the driving force adjustment. This precise adjustment helps to more effectively suppress path trajectory deviation caused by abnormal friction of the servo motor, ensuring the stability and accuracy of the paper feeding process, and thus improving the operating efficiency and reliability of the entire paper feeding system.

[0071] In some preferred embodiments, it is assumed that during the paper feeding process, by analyzing the current and jitter data of the servo motor, its frictional characteristics indicate abnormal friction. At this time, the system calculates a target driving force adjustment value based on the real-time acquired current and jitter data, as well as the current total operating time of the servo motor, using a preset algorithm or lookup table. For example, if abnormal friction is detected leading to insufficient driving force, the target driving force adjustment value may be positive, indicating that the driving force needs to be increased; conversely, if abnormal friction leads to driving force overload, the target driving force adjustment value may be negative.

[0072] Once the target driving force adjustment value is determined, the system adds the current driving force of the servo motor to this adjustment value to obtain a new, adjusted driving force. For example, if the current driving force is 10 N·m and the calculated target driving force adjustment value is +0.5 N·m, the adjusted driving force will become 10.5 N·m. This adjusted driving force is then applied to the servo motor to compensate for the effects of abnormal friction, thereby ensuring that the paper picking robot arm can run smoothly along the preset path and effectively suppressing path deviation.

[0073] This application further proposes a specific method for determining the target drive force adjustment value of the servo motor based on current data, jitter data, and the current total working time of the servo motor. By calculating step by step and taking comprehensive consideration, a more refined drive force adjustment can be achieved.

[0074] Specifically, the target drive force adjustment value of the servo motor is determined based on the aforementioned current data, jitter data, and the current total operating time of the servo motor, including:

[0075] The current driving force adjustment value is determined based on the current data; the jitter driving force adjustment value is determined based on the jitter data; and the target driving force adjustment value is determined based on the current driving force adjustment value, the jitter driving force adjustment value, and the current total working time of the servo motor.

[0076] Determining the current drive force adjustment value based on current data refers to assessing the impact of the internal friction state on the drive force by analyzing the current data generated by the servo motor during operation. Current data directly reflects the load changes and friction torque within the servo motor; when friction is abnormal, the current data will exhibit a specific change pattern. By processing and analyzing this current data, the amount of drive force adjustment required due to abnormal friction can be quantified. The purpose is to compensate for the impact of friction changes on the drive force demand from an electrical perspective.

[0077] Furthermore, determining the jitter drive force adjustment value based on jitter data refers to assessing the impact of the robotic arm's motion smoothness on the drive force by monitoring the jitter data of the suction cup of the paper-picking robotic arm. Jitter data directly reflects the stability of the robotic arm's motion trajectory. When abnormal friction of the servo motor causes path deviation, the jitter of the suction cup will intensify. By analyzing the jitter data, the amount of adjustment required to the drive force due to increased jitter can be quantified. The purpose is to compensate for the drive force demand caused by jitter at the mechanical motion level, thereby restoring the stability of the path trajectory.

[0078] In practical applications, determining the target drive force adjustment value based on the current drive force adjustment value, the jitter drive force adjustment value, and the current total operating time of the servo motor involves combining the two independently calculated adjustment values ​​and adjusting them according to the current total operating time of the servo motor to obtain the final target drive force adjustment value. The current drive force adjustment value and the jitter drive force adjustment value reflect the impact of abnormal servo motor friction on the drive force from different dimensions; their combination provides a more comprehensive basis for adjustment. Simultaneously, the current total operating time of the servo motor can serve as an indicator of the degree of equipment wear or aging status, correcting the drive force adjustment value to better reflect the actual operating conditions of the servo motor at different stages of its life cycle. The aim is to ensure the comprehensiveness, accuracy, and adaptability of the drive force adjustment.

[0079] This application's solution refines the determination process of the target drive force adjustment value into a step-by-step calculation and comprehensive consideration based on current data, jitter data, and the current total working time. This allows for a more accurate identification and quantification of the impact of servo motor friction anomalies on the drive force. Specifically, the current drive force adjustment value directly reflects changes in the electrical load inside the servo motor, while the jitter drive force adjustment value is directly related to the motion stability of the robotic arm. By calculating these two adjustment values ​​separately, the limitations of single-factor evaluation can be avoided, resulting in a more comprehensive response to friction anomalies. Furthermore, introducing the current total working time of the servo motor as a correction factor allows the drive force adjustment to adapt to potential performance degradation or wear during long-term operation of the servo motor, thereby ensuring optimal drive force compensation at different stages of use. This multi-dimensional, hierarchical adjustment strategy enables the target drive force adjustment value to more accurately reflect the actual operating state and requirements of the servo motor.

[0080] The above technical solution enables precise and intelligent adjustment of the servo motor drive force. By quantifying the impact of current and jitter data on the drive force, different types of friction anomalies can be more accurately identified and responded to. Simultaneously, by introducing the servo motor's current total operating time as a correction factor, the drive force adjustment can adapt to the long-term operating conditions and wear levels of the equipment, avoiding adjustment deviations that may be caused by single or simple combinations of factors. Therefore, the determined target drive force adjustment value is more accurate, thereby more effectively suppressing path trajectory deviation of the paper picking robotic arm and significantly improving the stability and reliability of the paper feeding process.

[0081] In some preferred embodiments, the target drive force adjustment value of the servo motor can be determined as follows: First, by analyzing current data, such as through harmonic analysis, a current drive force adjustment value reflecting the degree of frictional abnormality is calculated. Second, by analyzing the vibration data of the suction cup, such as through frequency analysis, a vibration drive force adjustment value reflecting the smoothness of the robotic arm's movement is calculated. Then, these two adjustment values ​​are initially superimposed to obtain an initial drive force adjustment value. Finally, based on the current total working time of the servo motor, a preset correction coefficient table is consulted to correct the initial drive force adjustment value to obtain the final target drive force adjustment value. For example, when the total working time of the servo motor is long, the correction coefficient may be larger to compensate for the effects of long-term wear.

[0082] This application further proposes a more refined method for determining the current driving force adjustment value based on current data. By establishing a correspondence between the current parameter difference and the adjustment coefficient, the adaptive adjustment of the driving force is achieved.

[0083] According to the above method, the current driving force adjustment value is determined based on the current data, including:

[0084] Obtain the first correspondence; the first correspondence includes a one-to-one correspondence between multiple difference ranges and multiple current adjustment coefficients; take the current adjustment coefficient corresponding to the difference range where the target difference is located in the first correspondence as the target current adjustment coefficient; the target difference is the difference between the current parameter value of the target harmonic of the current data and the normal parameter value of the target parameter when the friction force of the servo motor is normal; take the product of the current driving force of the servo motor and the target current adjustment coefficient as the current driving force adjustment value.

[0085] Specifically, the first correspondence refers to a pre-established mapping rule used to guide drive force adjustment. This correspondence divides the target difference between the current and normal parameter values ​​of the target harmonic in the servo motor current data into multiple discrete difference ranges. Each difference range uniquely corresponds to a current adjustment coefficient. For example, a smaller target difference may correspond to a smaller current adjustment coefficient; a larger target difference may correspond to a larger current adjustment coefficient. This design aims to provide different levels of drive force adjustment based on the severity of friction anomalies.

[0086] The target difference can be understood as the degree of deviation in current characteristics between the current operating state and the normal operating state of the servo motor. This deviation can be quantified by comparing the current parameter values ​​(e.g., amplitude or phase) of the target harmonics of the current data with the normal parameter values ​​of the target parameters when the servo motor friction is normal.

[0087] In practical applications, the target current adjustment coefficient is obtained by looking up the corresponding value in the first correspondence based on the currently calculated target difference. Once the target current adjustment coefficient is determined, it is multiplied by the current driving force of the servo motor to obtain the current driving force adjustment value. This multiplication calculation method ensures that the adjustment value is correlated with the current driving force level, thus ensuring the rationality of the adjustment.

[0088] This application's solution introduces a first correspondence relationship, establishing a mapping between the target difference between the current and normal parameter values ​​of the target harmonic parameters of the current data and a preset current adjustment coefficient. When the servo motor experiences frictional anomalies, the target parameters of the target harmonics in its current data will deviate, generating a target difference. The larger this target difference, the more severe the frictional anomaly. By finding the target current adjustment coefficient corresponding to the range of this target difference in the first correspondence relationship, an appropriate adjustment coefficient can be dynamically selected based on the severity of the anomaly. Subsequently, this target current adjustment coefficient is multiplied by the current driving force of the servo motor to calculate the current driving force adjustment value. This refined adjustment mechanism based on the difference range and adjustment coefficient ensures that the driving force adjustment is no longer a simple fixed value or a coarse threshold judgment, but rather can adaptively adjust according to the actual degree of anomaly, guaranteeing the accuracy and effectiveness of the adjustment.

[0089] The above technical solution enables precise and adaptive adjustment of the servo motor's driving force. By establishing a primary correspondence between the target difference and the current adjustment coefficient, a suitable current driving force adjustment value can be dynamically determined based on the actual degree of frictional anomaly in the servo motor. This avoids the problems of under-adjustment or over-adjustment that may exist in traditional methods, making the driving force adjustment more accurate and efficient. Consequently, it can more effectively suppress path trajectory deviation of the paper-picking robotic arm, improve the stability and accuracy of the paper feeding process, and extend the service life of the servo motor.

[0090] This application further proposes a step for determining the jitter drive force adjustment value based on jitter data, including:

[0091] Obtain the second correspondence; the second correspondence includes a one-to-one correspondence between multiple jitter parameter value ranges and multiple jitter adjustment coefficients; take the jitter adjustment coefficient corresponding to the jitter parameter value range of the jitter data at the target frequency in the second correspondence as the target jitter adjustment coefficient; take the product of the current driving force and the target jitter adjustment coefficient as the jitter driving force adjustment value.

[0092] Specifically, the second correspondence can be understood as a pre-established mapping table or functional relationship, the purpose of which is to quantify jitter data of different degrees into corresponding drive force adjustment coefficients. Here, the jitter parameter value range refers to dividing the jitter data at the target frequency into several continuous or discrete intervals, each interval representing a degree of jitter. The jitter adjustment coefficient is the value corresponding to each jitter parameter value range, used to indicate the proportion or magnitude of drive force adjustment required under a specific jitter level. For example, when the jitter parameter value is large, the corresponding jitter adjustment coefficient may also be large, applying a greater drive force adjustment. The target jitter adjustment coefficient refers to the adjustment coefficient found in the second correspondence based on the currently detected jitter data, matching the current jitter parameter value range. Finally, the jitter drive force adjustment value is obtained by multiplying the current drive force of the servo motor by this target jitter adjustment coefficient, ensuring that the proportionality of the drive force adjustment is adapted to the current drive force level.

[0093] This application's solution introduces a second correspondence to systematically correlate the target jitter parameter value at the target frequency with the jitter adjustment coefficient. When the suction cup of the paper-picking robotic arm jitters, its jitter data is processed to obtain the target jitter parameter value. This parameter value is then used to find its corresponding jitter parameter value range in the second correspondence and obtain the corresponding target jitter adjustment coefficient. Therefore, the current driving force of the servo motor is multiplied by this target jitter adjustment coefficient to calculate the jitter driving force adjustment value. This adjustment mechanism based on quantifying the degree of jitter makes the driving force adjustment no longer a simple empirical judgment, but a precise calculation based on the actual jitter situation, thus more effectively compensating for path trajectory deviation caused by jitter.

[0094] The above technical solution enables precise adjustment of the servo motor's driving force. By introducing a second correspondence, the parameter values ​​of the target jitter parameters at the target frequency are correlated with the jitter adjustment coefficient, making the determination of the jitter driving force adjustment value more scientific and quantitative. This helps to more accurately reflect the degree of impact of jitter on path trajectory deviation, thereby providing more precise driving force compensation, effectively improving the path control accuracy and stability of the paper feeding process, and reducing the scrap rate caused by jitter.

[0095] This application further proposes a step for determining the target driving force adjustment value based on the aforementioned current driving force adjustment value, the aforementioned jitter driving force adjustment value, and the aforementioned current total operating time of the servo motor, including:

[0096] The sum of the above-mentioned current driving force adjustment value and the above-mentioned jitter driving force adjustment value is used as the initial driving force adjustment value; a third correspondence is obtained; the above-mentioned third correspondence includes a one-to-one correspondence between multiple total working time ranges and multiple working time correction coefficients; the working time correction coefficient corresponding to the current total working time range in the above-mentioned third correspondence is used as the target working time correction coefficient; the product of the above-mentioned target working time correction coefficient and the above-mentioned initial driving force adjustment value is used as the above-mentioned target driving force adjustment value.

[0097] Specifically, the initial drive force adjustment value refers to the preliminary superposition of the drive force adjustment calculated based on real-time current data and jitter data. Its purpose is to compensate for the friction anomalies of the servo motor in the current instant or short period of time. The third correspondence can be understood as a preset mapping table or function, which is used to associate the cumulative running time of the servo motor (i.e., the current total working time) with the corresponding correction factor (i.e., the working time correction coefficient).

[0098] In practical applications, multiple total operating time ranges can divide the entire expected lifespan of a servo motor into several stages, such as the break-in period, stable operation period, and aging period, each corresponding to different degrees of wear and aging. Multiple operating time correction coefficients are predetermined based on empirical data, experimental tests, or predictive models, used to quantify the additional correction amount for drive force adjustment at different operating time stages. For example, as the total operating time of the motor increases, its internal friction may gradually increase; in this case, the corresponding correction coefficient can be set to a value greater than 1 to appropriately increase the drive force adjustment.

[0099] The target working time correction factor refers to the correction factor found in the third correspondence based on the current actual total working time of the servo motor, corresponding to the range of total working time it falls within. Ultimately, the target drive force adjustment value is obtained by multiplying the target working time correction factor by the initial drive force adjustment value. This allows the drive force adjustment to consider both real-time anomalies and the cumulative correction under long-term motor operation.

[0100] This application's solution effectively addresses the limitations of adjusting drive force solely based on real-time current and jitter data by introducing a correction mechanism related to the servo motor's current total operating time. Specifically, the initial drive force adjustment value can quickly respond to friction anomalies occurring in the servo motor within a short period, providing immediate compensation. Furthermore, by obtaining a third correspondence and determining a target operating time correction coefficient based on the servo motor's current total operating time, the initial drive force adjustment value can be further corrected.

[0101] Because servo motors experience wear and aging of their internal mechanical components after prolonged operation, leading to cumulative changes in their frictional characteristics, these changes cannot be fully reflected by instantaneous data. By multiplying the target operating time correction factor by the initial drive force adjustment value, the final target drive force adjustment value not only considers the current abnormal state but also incorporates the cumulative effects of long-term motor operation, resulting in more accurate and comprehensive drive force adjustment. For example, when the total operating time of the servo motor is long, even if the abnormality indicated by real-time current and jitter data is the same as initially, the increased overall wear of the motor may necessitate a larger drive force adjustment to effectively suppress path trajectory deviation. In this case, the target operating time correction factor can play a role in amplifying and correcting the initial adjustment value.

[0102] Through the above technical solution, this application can more comprehensively and accurately evaluate the actual operating status of the servo motor, especially taking into full account the cumulative wear and aging effects caused by long-term motor operation. This allows the drive force adjustment to be based not only on instantaneous data, but also on the motor's "historical health status," thereby significantly improving the accuracy and adaptability of the drive force adjustment. Ultimately, it can more effectively suppress path trajectory deviation of the paper picking robot arm, reduce the risk of failure due to motor aging, extend the service life of the servo motor, and improve the stability and reliability of the paper feeding process.

[0103] In some preferred embodiments, assuming that the servo motor of the paper-picking robotic arm detects an abnormal friction force at a certain moment, the initial drive force adjustment value calculated from current data and jitter data is 5N. Simultaneously, the system records the current total operating time of this servo motor as 6500 hours. The preset third correspondence is as follows:

[0104] The total working hours range from 0 to 2000 hours, with a corresponding working hours correction factor of 1.0.

[0105] The total working hours range from 2001 to 5000 hours, with a corresponding working hours correction factor of 1.1.

[0106] The total working hours range from 5001 to 8000 hours, with a corresponding working hours correction factor of 1.2.

[0107] The total working hours are over 8001 hours, and the corresponding working hours correction factor is 1.3.

[0108] Based on the third correspondence mentioned above, since the current total working time is 6500 hours, falling within the range of 5001-8000 hours, the corresponding target working time correction factor is determined to be 1.2. Therefore, the final target driving force adjustment value is calculated as the initial driving force adjustment value of 5N multiplied by the target working time correction factor of 1.2, which is 6N. In this way, in addition to considering real-time anomalies, the cumulative wear of the motor over long-term operation is also taken into account, resulting in a more precise correction of the driving force and thus more effectively suppressing path trajectory deviation.

[0109] This application also discloses a paper feeding process path control system, comprising: an acquisition device and a processing device; the acquisition device is used to acquire current data of the servo motor of the paper picking robot arm, jitter data of the suction cup of the paper picking robot arm, and the current total working time of the servo motor; the processing device is used to determine the friction characteristics of the servo motor based on the current data and jitter data; the friction characteristics are used to indicate whether the friction force of the servo motor is normal or abnormal; the processing device is used to adjust the driving force of the servo motor based on the current data, jitter data, and the current total working time of the servo motor when the friction characteristics indicate that the friction force of the servo motor is abnormal, so as to suppress path trajectory deviation.

[0110] This system integrates acquisition and processing devices to achieve real-time, multi-dimensional monitoring and intelligent intervention of the servo motor's operating status during paper feeding. The acquisition device comprehensively collects current data from the servo motor, vibration data from the suction cup, and the motor's cumulative operating time, providing foundational data for subsequent analysis. Based on this data, the processing device intelligently determines whether the servo motor's frictional characteristics are abnormal and adaptively adjusts the servo motor's driving force in abnormal situations. This collaborative mechanism effectively compensates for path trajectory deviations caused by changes in motor friction, significantly improving the accuracy and stability of paper feeding. It solves the problem of traditional methods failing to identify and correct hidden faults, ensuring the smooth operation of the automated production line.

[0111] In some embodiments of this application, the methods for obtaining the current data of the servo motor of the paper-picking robotic arm, the vibration data of the suction cup of the paper-picking robotic arm, and the current total working time of the servo motor, as well as the specific methods for determining the friction characteristics of the servo motor and adjusting the driving force of the servo motor based on these data, have already been described in the above embodiments, and will not be repeated here. It should be emphasized that the paper feeding process path control system proposed in this application achieves effective management and execution of the entire control process by modularizing these functions into specific hardware or software entities.

[0112] Specifically, the acquisition device can be understood as a collection of sensors and data acquisition modules. For example, current data can be acquired using Hall current sensors or shunt resistors integrated into the servo motor driver. These sensors convert current signals into voltage signals, which are then digitized by an analog-to-digital converter (ADC). Jitter data can be acquired using miniature accelerometers, gyroscopes, or laser displacement sensors mounted on the suction cup at the end of the paper-picking robotic arm. These sensors can monitor the minute vibrations or displacements of the suction cup in three-dimensional space in real time and transmit the data to the control system. The current total operating time of the servo motor can be realized using a real-time clock (RTC) module combined with non-volatile memory (NVM) within the system. The times of each motor start and stop are recorded and accumulated to calculate the total operating time. These sensors and modules can communicate with the processing device via wired or wireless means.

[0113] The processing device can be one or more hardware platforms such as microcontrollers (MCUs), digital signal processors (DSPs), field-programmable gate arrays (FPGAs), or industrial personal computers (IPCs). The processing device integrates software modules for performing data analysis, friction characteristic determination, and drive force adjustment algorithms. For example, the processing device may include an FFT (Fast Fourier Transform) module for frequency domain analysis of current and jitter data, a state machine or expert system module for determining friction characteristics based on the analysis results, and a PID (Proportional-Integral-Derivative) controller or adaptive control algorithm module for calculating and outputting adjusted servo motor drive commands. The processing device connects to the servo motor driver via a communication interface (such as CAN bus, EtherCAT, or Modbus) to send adjusted drive force commands in real time. In some embodiments, the acquisition and processing devices can be integrated into the same physical unit, such as a smart sensor module or a controller integrating data acquisition and processing functions. In other embodiments, they can be independent units communicating via a network to achieve distributed control.

[0114] The paper feeding process path control system proposed in this application has significant advantages and innovations compared to existing technologies. Traditional paper feeding systems often lack the ability to perceive and adaptively adjust subtle changes in the internal friction characteristics of servo motors in real time. This leads to deviations in the robotic arm's path trajectory as motor performance gradually degrades, resulting in problems such as unstable adsorption, double sheets, or lateral drift of the paper. For example, existing systems may only trigger an alarm when the motor current or vibration reaches a severe fault threshold, by which time the problem has already manifested and affected production.

[0115] The innovation of this application lies in achieving comprehensive and refined monitoring and intelligent decision-making of the servo motor's operating status through specialized acquisition and processing devices. The acquisition device can collect multi-dimensional data on current, jitter, and operating time, providing rich information to the processing device. Based on this information, the processing device can accurately determine the cause of frictional anomalies in their early stages and proactively adjust the servo motor's driving force. This system-level preventative and adaptive control strategy allows the robotic arm to maintain its preset motion path even when faced with changes in the motor's internal friction, effectively suppressing path deviation. Therefore, this application significantly improves the stability and reliability of the paper feeding process, reduces production losses and product quality issues caused by latent faults, and demonstrates its advancement and practicality in the field of automation control.

[0116] The above are merely embodiments of this application and are not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A paper feeding process path control method characterized by, The method includes: Acquire the current data of the servo motor of the paper picking robot arm, the vibration data of the suction cup of the paper picking robot arm, and the current total working time of the servo motor; The friction characteristics of the servo motor are determined based on the current data and the jitter data; the friction characteristics are used to indicate whether the friction force of the servo motor is normal or abnormal. When the friction characteristics indicate that the friction force of the servo motor is abnormal, the driving force of the servo motor is adjusted based on the current data, the jitter data, and the current total working time of the servo motor to suppress path trajectory deviation.

2. The paper feeding process path control method according to claim 1, characterized in that, The frictional characteristics of the servo motor are determined based on the current data and the jitter data, including: The current data is processed by FFT to obtain the current parameter values ​​of the target parameters of the target harmonic of the current data; the target parameters include amplitude or phase. The friction characteristics of the servo motor are determined based on the current parameter value of the target parameter and the jitter data.

3. The paper feeding process path control method according to claim 2, characterized in that, Determining the friction characteristics of the servo motor based on the current parameter value of the target parameter and the jitter data includes: Obtain the normal parameter value of the target parameter when the friction force of the servo motor is normal; Determine the target difference; the target difference is the difference between the current parameter value and the normal parameter value; When the absolute value of the target difference is greater than a preset difference threshold, the friction characteristics of the servo motor are determined based on the jitter data and the friction characteristics of the servo motor to indicate that the friction force of the servo motor is abnormal.

4. The paper feeding process path control method according to claim 3, characterized in that, When the absolute value of the target difference is greater than a preset difference threshold, the friction characteristics of the servo motor are determined based on the jitter data and the friction characteristics of the servo motor to indicate abnormal friction force of the servo motor, including: Perform FFT processing on the jitter data to obtain the parameter values ​​of the target jitter parameters of the jitter data at the target frequency; When the value of the target jitter parameter is greater than the preset jitter parameter threshold, the friction characteristics of the servo motor are determined to indicate that the friction force of the servo motor is abnormal.

5. The paper feeding process path control method according to claim 1, characterized in that, Adjusting the driving force of the servo motor based on the current data, the jitter data, and the current total operating time of the servo motor includes: The target driving force adjustment value of the servo motor is determined based on the current data, the jitter data, and the current total working time of the servo motor. The sum of the current driving force of the servo motor and the target driving force adjustment value is used as the adjusted driving force of the servo motor.

6. The paper feeding process path control method according to claim 5, characterized in that, Determining the target drive force adjustment value of the servo motor based on the current data, the jitter data, and the current total operating time of the servo motor includes: Determine the current driving force adjustment value based on the current data; The jitter driving force adjustment value is determined based on the jitter data; The target driving force adjustment value is determined based on the current driving force adjustment value, the jitter driving force adjustment value, and the current total working time of the servo motor.

7. The paper feeding process path control method according to claim 6, characterized in that, Determining the current driving force adjustment value based on the current data includes: Obtain the first correspondence; the first correspondence includes a one-to-one correspondence between multiple difference ranges and multiple current adjustment coefficients; The current adjustment coefficient corresponding to the difference range in the first correspondence is taken as the target current adjustment coefficient; the target difference is the difference between the current parameter value of the target harmonic of the current data and the normal parameter value of the target parameter when the friction of the servo motor is normal. The product of the current driving force of the servo motor and the target current adjustment coefficient is used as the current driving force adjustment value.

8. The paper feeding process path control method according to claim 6, characterized in that, Determining the jitter drive force adjustment value based on the jitter data includes: Obtain the second correspondence; the second correspondence includes a one-to-one correspondence between multiple jitter parameter value ranges and multiple jitter adjustment coefficients; The jitter adjustment coefficient corresponding to the jitter parameter value range of the jitter data at the target frequency in the second correspondence is taken as the target jitter adjustment coefficient; The product of the current driving force and the target jitter adjustment coefficient is used as the jitter driving force adjustment value.

9. The paper feeding process path control method according to claim 6, characterized in that, The target drive force adjustment value is determined based on the current drive force adjustment value, the jitter drive force adjustment value, and the current total operating time of the servo motor, including: The sum of the current driving force adjustment value and the jitter driving force adjustment value is used as the initial driving force adjustment value; Obtain the third correspondence; the third correspondence includes a one-to-one correspondence between multiple total working time ranges and multiple working time correction coefficients; The working time correction coefficient corresponding to the working time range in the third correspondence relationship is taken as the target working time correction coefficient. The target driving force adjustment value is obtained by multiplying the target working time correction coefficient by the initial driving force adjustment value.

10. A paper feeding process path control system, characterized in that, The system includes: an acquisition device and a processing device; The acquisition device is used to acquire the current data of the servo motor of the paper picking robot arm, the vibration data of the suction cup of the paper picking robot arm, and the current total working time of the servo motor. The processing device is used to determine the friction characteristics of the servo motor based on the current data and the jitter data; the friction characteristics are used to indicate whether the friction force of the servo motor is normal or abnormal. The processing device is used to adjust the driving force of the servo motor based on the current data, the jitter data, and the current total working time of the servo motor when the friction characteristics indicate that the friction force of the servo motor is abnormal, so as to suppress path trajectory deviation.

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