Implementation scheme of torque self-adaptive optimal clamping force based on oil stain thickness

Abstract

The invention relates to the technical field of machining and automatic control, and discloses a torque self-adaptive optimal clamping force implementation scheme based on oil stain thickness, which comprises the following steps: step S101, calculating to obtain a plurality of oil stain thicknesses, and converting the oil stain thicknesses into oil stain thickness signals; step S102, processing the oil contamination thickness signal to obtain an oil contamination thickness data sequence; s103, calculating according to the oil stain thickness data sequence to obtain a target clamping force; and S104, the clamping force is adjusted to the target clamping force through a clamping force executing mechanism. According to the method, the thickness of the oil stain on the surface of the workpiece is accurately measured in real time through the high-precision oil stain thickness detection sensor, and the corresponding target clamping force is rapidly and accurately calculated according to a nonlinear mapping model between the oil stain thickness and the optimal clamping force, so that the precision and quality of workpiece machining are greatly improved, and the working efficiency is improved. And the machining error and the rejection rate caused by oil stains are effectively reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of mechanical processing and automatic control, and more particularly to a solution for realizing a torque adaptive optimum clamping force based on oil stain thickness. Background Art

[0002] In the field of mechanical processing, stable clamping of workpieces is a key link to ensure processing quality and efficiency. However, in actual production environments, workpiece surfaces are often adhered to varying degrees of oil stains. These oil stains mainly come from coolants and lubricants used in the processing process, as well as various greases that the workpieces come into contact with during transportation and storage. The difference in the thickness of the oil stains has a significant impact on the workpiece clamping process, bringing many challenges to traditional clamping technology.

[0003] In traditional machining scenarios, the application of clamping force mainly depends on the operator's experience or a pre-set fixed value. However, this fixed clamping force method is difficult to cope with changes in oil thickness. For example, when the oil on the workpiece surface is thick, due to the lubricating effect of the oil, the actual friction coefficient between the workpiece and the fixture decreases. The originally set clamping force may not be sufficient to overcome the cutting force and other external forces generated during the machining process, causing the workpiece to shift or vibrate during the machining process, thereby generating machining errors, affecting the dimensional accuracy and surface quality of the workpiece, and in severe cases even causing the workpiece to be scrapped or the machining equipment to be damaged.

[0004] To address the above-mentioned issues, some solutions have emerged in the prior art that can adjust the clamping force according to the surface condition of the workpiece. For example, some clamping systems install pressure sensors between the fixture and the workpiece to monitor the clamping force in real time and adjust the clamping force appropriately through a feedback control system. However, most of these solutions do not fully consider the key factor of oil stain thickness, or can only perform rough and discontinuous clamping force adjustments. The change in oil stain thickness is a continuous process, which requires the clamping system to be able to perceive and respond in real time and accurately. Existing technologies often rely on complex optical detection equipment or high-cost chemical analysis methods. These methods are not only expensive and complex to operate, but also have slow detection speeds, making it difficult to meet the needs of high-speed and high-efficiency processing in actual production.

[0005] In addition, the existing adaptive clamping technology still has the problem of insufficient stability in practical applications. Due to the failure to accurately establish the precise mapping relationship between the oil stain thickness and the clamping force, these systems may over-adjust or under-adjust the clamping force when the oil stain thickness changes greatly. Excessive adjustment of the clamping force may cause the workpiece to deform and affect the workpiece's geometry, while insufficient adjustment cannot effectively ensure the stable clamping of the workpiece, posing a safety hazard. Summary of the Invention

[0006] The present invention provides a solution for realizing an optimal clamping force based on torque self-adaptation according to the thickness of oil stains, and solves the technical problems in the above-mentioned background technology.

[0007] The present invention provides a solution for realizing a torque adaptive optimal clamping force based on the thickness of the oil stain, comprising the following steps:

[0008] Step S101: At a preset acquisition frequency, a high-precision sensor transmits a light beam of a specific wavelength to the workpiece surface, receives the reflected light, analyzes its intensity, and calculates multiple oil stain thicknesses based on a pre-calibrated database of oil stain optical properties, converting them into oil stain thickness signals.

[0009] Step S102, filtering, amplifying and analog-to-digital conversion are performed on the oil stain thickness signal to obtain an oil stain thickness data sequence;

[0010] Step S103: Calculate the target clamping force using a pre-stored quadratic polynomial mapping model based on the oil stain thickness data sequence, obtain the actual clamping force fed back by the clamping force sensor, and generate a motor drive control signal using a PID control algorithm;

[0011] Step S104 , adjusting the rotation angle and speed of the motor according to the motor drive control signal, and adjusting the clamping force to the target clamping force through the clamping force actuator.

[0012] Furthermore, the calculation formula for the oil stain thickness h is as follows:

[0013] Where k represents the sensor calibration coefficient, I0 represents the reflected light intensity when there is no oil pollution, and the measured reflected light intensity.

[0014] Furthermore, a Butterworth low-pass filter is used to remove high-frequency noise interference in the oil thickness signal. The transfer function H(s) of the Butterworth low-pass filter is calculated as follows:

[0015] Where s represents the complex frequency variable, n represents the filter order, ω c represents the filter cutoff frequency, ω c =2πf c , f c Indicates the filter cutoff frequency.

[0016] Furthermore, the filtered oil stain thickness signal is amplified to obtain a preliminary processed signal of the oil stain thickness, wherein the amplification factor is a custom parameter.

[0017] Furthermore, the amplified oil stain thickness signal is subjected to analog-to-digital conversion to obtain an oil stain thickness data sequence, wherein the resolution is a custom parameter.

[0018] Furthermore, the calculation formula of the quadratic polynomial mapping model is as follows:

[0019] F target =p1×h 2 +p1×h+p3, where F target represents the target clamping force, h represents the oil thickness, and p1, p2, and p3 represent the first, second, and third weight coefficients, respectively.

[0020] Furthermore, the calculation formula for generating the motor drive control signal through the PID control algorithm is as follows:

[0021] Where ΔF(t) represents the difference between the actual clamping force and the target clamping force, ΔF(τ) represents the difference between the actual clamping force and the target clamping force at the τth integration moment, and K p Indicates the proportional control coefficient, K i Indicates the integral control coefficient, K d represents the differential control coefficient.

[0022] Furthermore, the clamping force actuator includes: a motor drive system, a screw-nut transmission device, and a clamping head in contact with the workpiece. The screw-nut transmission device converts the rotational motion into linear motion, pushing the clamping head to apply or reduce the clamping force to the workpiece.

[0023] Furthermore, the relationship between the linear displacement Δx of the screw-nut transmission and the motor rotation angle θ is as follows:

[0024] where d p It represents the screw pitch and L represents the effective length of the screw.

[0025] Furthermore, the relationship between the clamping force F and the motor torque T is as follows:

[0026] Where η represents the motor transmission efficiency and r is the screw radius.

[0027] The beneficial effects of the present invention are: 1. Accurate adaptation to changes in oil stains: Through a high-precision oil stain thickness detection sensor, the oil stain thickness on the workpiece surface is measured in real time and accurately, and based on the nonlinear mapping model between the oil stain thickness and the optimal clamping force, the corresponding target clamping force is quickly and accurately calculated, thereby greatly improving the accuracy and quality of workpiece processing, and effectively reducing the processing error and scrap rate caused by oil stains; 2. High-precision clamping force control: Using signal processing technology and PID error feedback control algorithm, the oil stain thickness signal is accurately processed and analyzed to generate an accurate motor drive control signal to achieve high-precision, continuously adjustable control of the clamping force; 3. Fast response and dynamic adjustment: The oil stain thickness is continuously executed at a high frequency The cyclic process of detection, signal processing, control decision-making and clamping force execution has the ability to quickly respond to changes in oil thickness, and can correct clamping force deviations in time during the processing process, thereby ensuring the continuity and efficiency of the entire processing process and improving production efficiency; 4. Improved stability and reliability: By accurately establishing a mapping relationship between oil thickness and clamping force, the problem of excessive or insufficient clamping force adjustment is avoided, and the risks of workpiece deformation, processing errors and equipment damage caused by improper clamping force are effectively prevented, thereby improving the stability and reliability of the processing process; 5. Advantages of non-contact measurement: The oil thickness detection sensor adopts a non-contact measurement method, which will not cause scratches or pollution to the workpiece surface, thereby ensuring the surface quality of the workpiece. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a flow chart of a solution for implementing a torque adaptive optimal clamping force based on oil stain thickness according to the present invention;

[0029] Figure 2 Schematic diagram of the clamping force actuator of the present invention. DETAILED DESCRIPTION

[0030] The subject matter described herein will now be discussed with reference to exemplary embodiments. It should be understood that these embodiments are discussed solely to enable those skilled in the art to better understand and implement the subject matter described herein, and that the functions and arrangements of the elements discussed may be varied without departing from the scope of this specification. Various examples may omit, substitute, or add various processes or components as needed. In addition, features described with respect to some examples may also be combined in other examples.

[0031] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in one or more embodiments of the present invention should have the usual meanings understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in one or more embodiments of the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprising" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0032] like Figures 1 and 2 As shown, the solution for realizing the torque adaptive optimal clamping force based on the oil stain thickness includes the following steps:

[0033] Step S101: At a preset acquisition frequency, a high-precision sensor transmits a light beam of a specific wavelength to the workpiece surface, receives the reflected light, analyzes its intensity, and calculates multiple oil stain thicknesses based on a pre-calibrated database of oil stain optical properties, converting them into oil stain thickness signals.

[0034] Step S102, filtering, amplifying and analog-to-digital conversion are performed on the oil stain thickness signal to obtain an oil stain thickness data sequence;

[0035] Step S103: Calculate the target clamping force using a pre-stored quadratic polynomial mapping model based on the oil stain thickness data sequence, obtain the actual clamping force fed back by the clamping force sensor, and generate a motor drive control signal using a PID control algorithm;

[0036] Step S104 , adjusting the rotation angle and speed of the motor according to the motor drive control signal, and adjusting the clamping force to the target clamping force through the clamping force actuator.

[0037] In one embodiment of the present invention, the calculation formula of the oil stain thickness h is as follows:

[0038] Where k represents the sensor calibration coefficient, I0 represents the reflected light intensity when there is no oil pollution, and the measured reflected light intensity.

[0039] It should be noted that the choice of a specific wavelength depends on the optical absorption and reflection characteristics of the oil, and is usually selected in the visible to near-infrared band (between approximately 400nm and 1100nm). For example, for most industrial lubricants, near-infrared wavelengths of 850nm or 940nm are often used for reflection measurements because the oil film is more sensitive to changes in reflectivity at these wavelengths and the sensor responds well.

[0040] It should be noted that the purpose of the pre-calibrated database of oil stain optical properties is to establish a mapping relationship between oil stain thickness and reflected light signals, including: oil stain type and its reflectivity curve at different wavelengths, reflected light intensity / phase changes corresponding to different oil stain thicknesses, etc.; the sensor calibration coefficient can be determined through experimental calibration, such as using coating technology to form multiple oil layers of known thickness on smooth glass or metal sheets, recording the reflected light intensity at each known thickness, calculating the ratio to the reflected light intensity under oil-free conditions, and finally fitting a logarithmic curve. The slope of the curve is the sensor calibration coefficient, which will not be elaborated here.

[0041] In one embodiment of the present invention, a Butterworth low-pass filter is used to remove high-frequency noise interference in the oil thickness signal. The transfer function H(s) of the Butterworth low-pass filter is calculated as follows:

[0042] Where s represents the complex frequency variable, n represents the filter order, ω c represents the filter cutoff frequency, ω c =2πf c , f c Indicates the filter cutoff frequency.

[0043] It should be noted that the complex frequency variable is used to represent the frequency characteristics, where the real and imaginary parts of the complex frequency variable represent the attenuation and frequency components of the signal respectively; the filter order determines the sharpness or attenuation speed of the filter. The higher the filter order, the steeper the transition band of the filter around the cutoff frequency, and the better the filtering effect, but the amount of calculation will also increase accordingly; the cutoff angular frequency indicates the frequency at which the filter begins to attenuate significantly; the filter cutoff frequency is used to control the frequency response of the filter, and the unit is Hertz.

[0044] In one embodiment of the present invention, the filtered oil stain thickness signal is amplified to obtain a preliminary processed signal of the oil stain thickness, wherein the amplification factor is a custom parameter.

[0045] It should be noted that the choice of amplification factor depends on the actual strength of the signal, the noise level and the requirements of subsequent analog-to-digital conversion, ensuring that the signal does not exceed the input range of the analog-to-digital converter after amplification to avoid signal overload distortion. Or if the signal itself is weak and noisy, a larger amplification factor may be required to enhance the detectability of the signal, for example, the amplification factor is set between 1 and 100.

[0046] In one embodiment of the present invention, the amplified oil stain thickness signal is subjected to analog-to-digital conversion to obtain an oil stain thickness data sequence, wherein the resolution is a custom parameter.

[0047] It should be noted that the resolution of analog-to-digital conversion refers to the minimum signal change that the analog-to-digital converter (ADC) can distinguish, that is, the amount of analog signal change represented by each digital signal.

[0048] In one embodiment of the present invention, the calculation formula of the quadratic polynomial mapping model is as follows:

[0049] F target =p1×h 2 +p1×h+p3, where F target represents the target clamping force, h represents the oil thickness, and p1, p2, and p3 represent the first, second, and third weight coefficients, respectively.

[0050] It should be noted that coating technology is used to form multiple oil layers of known thickness on smooth glass or metal sheets, and the oil thickness of each sample is obtained by a high-precision sensor. The friction coefficient at each oil thickness can be obtained through a slip experiment. Then, different clamping forces are applied to each sample, and the standard processing process is performed. It is recorded whether slippage, vibration, or workpiece deformation occurs under each clamping force. The target clamping force is determined, and the least squares method can be used to complete the fitting of the quadratic polynomial mapping model to determine the first weight coefficient, the second weight coefficient, and the third weight coefficient. I will not go into details here.

[0051] In one embodiment of the present invention, the calculation formula for generating the motor drive control signal by the PID control algorithm is as follows:

[0052] Where ΔF(t) represents the difference between the actual clamping force and the target clamping force, ΔF(τ) represents the difference between the actual clamping force and the target clamping force at the τth integration moment, and K p Indicates the proportional control coefficient, K i Indicates the integral control coefficient, K d represents the differential control coefficient.

[0053] In one embodiment of the present invention, the clamping force actuator includes: a motor drive system, a screw-nut transmission device, and a clamping head in contact with the workpiece, wherein the screw-nut transmission device converts the rotational motion into linear motion, pushing the clamping head to apply or reduce the clamping force to the workpiece, wherein the motor drive system receives the motor drive control signal to drive the motor to operate, and then drives the clamping head through the screw-nut transmission device to achieve the application and adjustment of the clamping force.

[0054] In one embodiment of the present invention, the relationship between the linear displacement Δx of the screw-nut transmission and the motor rotation angle θ is as follows:

[0055] where d p It represents the screw pitch and L represents the effective length of the screw.

[0056] In one embodiment of the present invention, the relationship between the clamping force F and the motor torque T is as follows:

[0057] Where η represents the motor transmission efficiency and r is the screw radius.

[0058] It should be noted that the screw pitch refers to the axial distance between two adjacent threads on the screw shaft, which determines the linear displacement generated by each rotation of the motor (or unit angle); the effective length of the screw refers to the maximum stroke range on the screw shaft within which the nut can move, excluding the fixed structures or limit sections at both ends; the motor transmission efficiency refers to the proportion of the mechanical energy output by the motor that is actually effectively transmitted to the clamping structure, which can be provided by the motor manufacturer or obtained by experimental measurement and will not be elaborated here.

[0059] It should be noted that during the entire processing process, the cycle of oil stain thickness detection, signal processing, control decision-making and clamping force execution is continuously executed according to the preset acquisition frequency. Through real-time dynamic adaptive control, it is ensured that the clamping force always adapts to the changes in oil stain thickness and maintains it in the optimal state, providing a stable and reliable basic guarantee for mechanical processing. This real-time monitoring and dynamic adjustment mechanism enables the system to quickly respond to changes in oil stain thickness and promptly correct clamping force deviations, thereby improving processing accuracy and efficiency and reducing production costs.

[0060] It should be noted that the intervals and thresholds are set for ease of comparison. The threshold size depends on the amount of sample data and the cardinality set by those skilled in the art for each set of sample data, as long as it does not affect the proportional relationship between the parameter and the quantized value. Furthermore, the above formulas are all dimensionless numerical calculations. These formulas are derived from software simulations of the most recent real-world conditions using large amounts of data. The preset parameters in these formulas are set by those skilled in the art based on actual conditions.

[0061] The above describes the embodiments of this embodiment, but this embodiment is not limited to the above specific implementation methods. The above specific implementation methods are merely illustrative and not restrictive. Ordinary technicians in this field can also make many forms based on the inspiration of this embodiment, all of which are protected by this embodiment.

Claims

1. The solution for realizing the optimal clamping force based on torque self-adaptation and oil stain thickness is characterized by: The following steps are involved: Step S101: At a preset acquisition frequency, a high-precision sensor transmits a light beam of a specific wavelength to the workpiece surface, receives the reflected light, analyzes its intensity, and calculates multiple oil stain thicknesses based on a pre-calibrated database of oil stain optical properties, converting them into oil stain thickness signals. Step S102, filtering, amplifying and analog-to-digital conversion are performed on the oil stain thickness signal to obtain an oil stain thickness data sequence; Step S103: Calculate the target clamping force using a pre-stored quadratic polynomial mapping model based on the oil stain thickness data sequence, obtain the actual clamping force fed back by the clamping force sensor, and generate a motor drive control signal using a PID control algorithm; Step S104 , adjusting the rotation angle and speed of the motor according to the motor drive control signal, and adjusting the clamping force to the target clamping force through the clamping force actuator.

2. The solution for realizing torque adaptive optimal clamping force based on oil stain thickness according to claim 1, characterized in that: The calculation formula for oil stain thickness h is as follows: Where k represents the sensor calibration coefficient, I0 represents the reflected light intensity when there is no oil pollution, and the measured reflected light intensity.

3. The solution for realizing torque adaptive optimal clamping force based on oil stain thickness according to claim 1, characterized in that: The Butterworth low-pass filter is used to remove high-frequency noise interference in the oil thickness signal. The transfer function H(s) of the Butterworth low-pass filter is calculated as follows: Where s represents the complex frequency variable, n represents the filter order, ω c represents the filter cutoff frequency, ω c =2πf c , f c Indicates the filter cutoff frequency.

4. The solution for realizing torque adaptive optimal clamping force based on oil stain thickness according to claim 1, characterized in that: The filtered oil stain thickness signal is amplified to obtain a preliminary processed signal of the oil stain thickness, where the amplification factor is a custom parameter.

5. The solution for realizing torque adaptive optimal clamping force based on oil stain thickness according to claim 1, characterized in that: The amplified oil pollution thickness signal is converted into digital form to obtain the oil pollution thickness data sequence, where the resolution is a custom parameter.

6. The solution for realizing torque adaptive optimal clamping force based on oil stain thickness according to claim 1, characterized in that: The calculation formula of the quadratic polynomial mapping model is as follows: F target =p1×h 2 +p1×h+p3, where F target represents the target clamping force, h represents the oil thickness, and p1, p2, and p3 represent the first, second, and third weight coefficients, respectively.

7. The solution for realizing torque adaptive optimal clamping force based on oil stain thickness according to claim 1, characterized in that: The calculation formula for generating the motor drive control signal through the PID control algorithm is as follows: Where ΔF(t) represents the difference between the actual clamping force and the target clamping force, ΔF(τ) represents the difference between the actual clamping force and the target clamping force at the τth integration moment, and K p Indicates the proportional control coefficient, K i Indicates the integral control coefficient, K d represents the differential control coefficient.

8. The solution for realizing torque adaptive optimal clamping force based on oil stain thickness according to claim 1, characterized in that: The clamping force actuator includes: a motor drive system, a screw-nut transmission device, and a clamping head in contact with the workpiece. The screw-nut transmission device converts the rotational motion into linear motion, pushing the clamping head to apply or reduce the clamping force to the workpiece.

9. The solution for realizing torque adaptive optimal clamping force based on oil stain thickness according to claim 8, characterized in that: The relationship between the linear displacement Δx of the screw nut transmission and the motor rotation angle θ is as follows: where d p It represents the screw pitch and L represents the effective length of the screw.

10. The solution for realizing torque adaptive optimal clamping force based on oil stain thickness according to claim 1, characterized in that: The relationship between the clamping force F and the motor torque T is as follows: Where η represents the motor transmission efficiency and r is the screw radius.

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