System and method for suppressing vibration at tail end of intelligent hoisting device

Abstract

The invention belongs to the technical field of mechanical control, and discloses an intelligent hoisting device tail end vibration suppression system and method.The intelligent hoisting device tail end vibration suppression system comprises an initialization module, an operating force measurement module, a data processing module and a speed calculation module, and the initialization module is used for obtaining the gravity of a heavy object before operation; the operating force measuring module is used for converting a digital signal sampled by the weighing sensor to obtain operating force containing noise; the data processing module is used for converting the noise-containing operating force signal into a pure operating force signal; the speed calculation module is used for obtaining the given speed of the motor. According to the method, the accurate weight gravity can be obtained, and errors of subsequent calculation are reduced; a digital signal obtained by sampling a sensor can be converted into a noisy operating force signal, and the intention of an operator is obtained; pure operation force signals without noise can be obtained, and the influence of vibration in the whole system is reduced; the given rotating speed of the motor is obtained through mathematical operation, and the running stability of the intelligent lifting device is guaranteed.

Description

Technical Field

[0001] The present invention belongs to the technical field of mechanical control, and particularly relates to a system and method for suppressing the end vibration of an intelligent lifting device. Background Technique

[0002] An intelligent lifting device is a key mechanical structure widely used in the fields of industrial automation, medical rehabilitation, aerospace, and precision manufacturing. Its main function is to change the lifting and lowering speeds of the device by measuring the operating force applied by the operator through an end sensor through reasonable mechanical design and control strategies, reducing the burden on the operator, and providing stable support or operating capabilities in specific environments. For example, in industrial production, an intelligent lifting device can be used to assist in handling heavy objects, reducing worker fatigue and improving production efficiency; in the medical field, an intelligent lifting device needs to maintain precise positioning to assist doctors in performing surgical operations; in the aerospace field, it is used for space operation tasks and needs to maintain high stability in a microgravity or complex stress environment to ensure the smooth execution of tasks.

[0003] However, when the intelligent lifting device is in operation, the weighing sensor will be affected by various factors such as external disturbances, friction of the transmission mechanism, and measurement errors, resulting in unstable output values, causing response fluctuations of the top motor, and thus leading to obvious vibrations in the end speed of the lifting device. This vibration is a composite vibration containing multiple frequencies. Among them, the vibration frequency of the low-frequency part is very close to the fluctuation frequency of the normal signal, and the amplitude is relatively large, having a greater impact on the system. In addition, as the motion state and the length of the steel wire rope change, the vibration frequency will also change. Traditional filtering methods such as low-pass filtering and average filtering will bring large delays or the filtering effect is not obvious, making it difficult to ensure the stability of the device end. Therefore, how to reduce the impact of vibration on the intelligent lifting device and improve the smooth operation ability of the device has become one of the key problems in current technical research. Summary of the Invention

[0004] The purpose of the present invention is to provide a system and method for suppressing the end vibration of an intelligent lifting device to solve the above technical problems.

[0005] To solve the above technical problems, the specific technical solutions of a system and method for suppressing the end vibration of an intelligent lifting device of the present invention are as follows:

[0006] An end vibration suppression system for an intelligent lifting device, comprising an initialization module, an operating force measurement module, a data processing module and a speed calculation module. The initialization module is used to obtain the gravity G of the heavy object before operation; the operating force measurement module is used to convert the digital signal D sampled by the weighing sensor to obtain the operating force F' containing noise; the data processing module is used to convert the noisy operating force signal F' into a pure operating force signal F; the speed calculation module is used to obtain the given speed of the motor to achieve the smooth operation of the intelligent lifting device.

[0007] Furthermore, it includes the following steps:

[0008] Step 1: The initialization module obtains the gravity G of the heavy object at the initial stage when the intelligent lifting device enters the operating state;

[0009] Step 2: The operating force measurement module converts the digital signal D obtained by sampling the weighing sensor into the operating force F' containing noise, which is used as the input of the data processing module;

[0010] Step 3: The data processing module obtains the pure operating force F through transformation operations based on the signal reconstruction principle;

[0011] Step 4: The speed calculation module converts the operating force F into the given speed V of the motor, so that the lifting device can smoothly complete the lifting and lowering movements.

[0012] Furthermore, the specific steps of Step 1 are as follows:

[0013] Calibrate the ADC of the single-chip microcomputer, then perform sampling, and perform a three-time averaging operation on the sampled values to obtain the sampling average value. The calculation formula is:

[0014]

[0015] where D' is the average value of the sampled values, D is the value obtained by each ADC sampling, and i is the number of measurements.

[0016] Convert the average value of the sampled values to obtain the gravity of the heavy object. The calculation formula is:

[0017]

[0018] where G is the gravity of the heavy object, D' is the average value of the three samplings, V ref is the reference voltage of the ADC, n is the number of bits of the ADC, and K sen is the proportional coefficient between the gravity and voltage of the weighing sensor.

[0019] Furthermore, the specific steps of Step 2 are as follows:

[0020] The sampling interval time samples the operating force applied by the operator, and the time interval for each sampling remains consistent. Therefore, before each sampling, it is necessary to determine whether the set time of the timer has been reached. After reaching the timing time of the timer, ADC is used for sampling to obtain the resultant force on the sensor. The calculation formula is as follows:

[0021]

[0022] Among them, T is the resultant force on the sensor, D run is the sampling value during operation, V ref is the reference voltage of the ADC, n is the number of bits of the ADC, K sen is the proportionality coefficient between the gravity and voltage of the load cell;

[0023] The resultant force T measured by the sensor is judged through a threshold. If T exceeds the set threshold, it is determined that T contains gross error and the data is discarded. If T does not exceed the set threshold, it is determined that T does not contain gross error and enters the subsequent calculation, where the setting of the threshold is adjusted according to the actual measurement situation;

[0024] The difference between the resultant force and the gravity of the heavy object is calculated to obtain the operating force containing noise. The calculation formula is:

[0025] F' = T - G

[0026] Among them, F’ is the operating force containing noise, T is the resultant force on the sensor, and G is the gravity of the heavy object obtained by the initialization module. Further, the step 3 includes the following specific steps:

[0027] The data processing module includes four steps: data synthesis, noise reduction processing, data extraction, and threshold judgment;

[0028] In the data synthesis step, first, multiple operating forces containing noise stored previously are found in the memory of the single-chip microcomputer and arranged in chronological order. Then, the operating force containing noise obtained from this sampling is placed at the end of the sequence to form an original array, which serves as the input for the noise reduction processing step;

[0029] The noise reduction processing step uses three parts: forward transformation, coefficient processing, and inverse transformation. While ensuring a relatively small delay, the original array of noisy operating forces is processed to obtain the noise-reduced signal;

[0030] The signal obtained after noise reduction processing is an array rather than a single data. Therefore, the role of data extraction is to convert the array into a single data. The elements in the noise-reduced array are still arranged in chronological order. The last element of the array is extracted, and the obtained value is the data closest to the current moment;

[0031] It is judged whether signal distortion occurs after noise reduction processing by comparing whether the value of the extracted element exceeds the set threshold. If its value exceeds the set threshold, it is determined that signal distortion has occurred and the data is discarded. If its value does not exceed the set threshold, it is determined that no signal distortion has occurred, and the output data is the pure operating force F.

[0032] Furthermore, in the forward transform of the noise reduction processing, the original array is convolved with the selected filter to obtain the high-frequency coefficients and low-frequency coefficients of this layer. The low-frequency coefficients are then convolved with the filter to obtain the high-frequency coefficients and low-frequency coefficients of a new layer; the above operations are repeated until the specified decomposition level is reached. The calculation formula for single-layer forward transform is:

[0033]

[0034] where A(k) is the low-frequency coefficient, D(k) is the high-frequency coefficient, h(n) and g(n) are the low-pass filter and high-pass filter during forward transform respectively, n is the original signal index, k is the coefficient index, and k_max is the coefficient length of this layer.

[0035] Furthermore, the coefficient processing adopts the soft threshold processing method: when the absolute value of the coefficient is less than the threshold, the coefficient is set to zero; when the absolute value of the coefficient is greater than the threshold, the output is the coefficient minus the threshold; finally, the calculated coefficient is multiplied by the sign function to ensure that the positive and negative of the coefficient remain unchanged before and after processing and avoid signal distortion. The calculation formula for soft threshold processing is:

[0036] C new =sign(C old )max(|C old |-λ,0)

[0037] where C new is the coefficient after soft threshold processing, C old is the coefficient before soft threshold processing, λ is the threshold, and sign is the sign function, and the expression is:

[0038]

[0039] After processing the coefficients, the high-frequency coefficients and low-frequency coefficients are convolved and recursively operated with the filter through inverse transform to reconstruct the noise-reduced signal.

[0040] Furthermore, the calculation formula for single-layer inverse transform is:

[0041]

[0042] Among them, A(k) is the low-frequency coefficient, D(k) is the high-frequency coefficient, h(n) and g(n) are the low-pass filter and high-pass filter during the inverse transform respectively, n is the original signal index, k is the coefficient index, k_max is the length of the coefficients at this layer, f(n) is the denoised signal after reconstruction at the last layer, and is the low-frequency coefficient for the next inverse transform at other layers.

[0043] Further, the speed calculation module in step 4 includes three parts: operating force detection, compliance strategy, and touchdown detection. The operating force detection part determines whether the device needs to move. When the operating force is greater than the set threshold, it outputs the value of the current operating force and makes the device move through subsequent calculations and driving; when the operating force is less than the set threshold, it sets the operating force to zero and prohibits the device from moving. The calculation formula is:

[0044]

[0045] where F is the operating force and c is the set threshold.

[0046] The compliance strategy part calculates the given speed of the motor using the operating force and the actual speed of the motor at the previous moment, and realizes the compliant change of the end speed of the device when the operating force changes by controlling the given speed of the motor. The calculation formula is:

[0047]

[0048] where V is the given speed of the motor, F is the operating force, V real is the actual speed of the motor at the previous moment, B and M are the damping parameter and inertia parameter respectively, and t is the time interval for each calculation, which should be consistent with the sampling time of the operating force detection module;

[0049] The role of the touchdown detection part is to judge whether a touchdown occurs by calculating the difference between two operating forces, and avoid the phenomenon of the heavy object bouncing up after touchdown; when the difference between the two operating forces obtained by continuous two samplings is greater than the set threshold, it is determined that a touchdown has occurred, and the given speed of the motor will be set to zero until manually released; when the difference is less than the set threshold, it is determined that no touchdown has occurred, and the given speed of the motor calculated by the admittance control is output, and the calculation formula is:

[0050] where V is the given speed of the motor, F(n) and F(n - 1) are the two operating forces, and C

[0051]

[0052] is the set threshold. touch is the set threshold.

[0053] The intelligent hoisting device end vibration suppression system and method of the present invention have the following advantages: The initialization module designed by the present invention can obtain a relatively accurate weight of the heavy object, reducing the error in subsequent calculations; the operating force measurement module can convert the digital signal sampled by the sensor into a noisy operating force signal to obtain the operator's intention; the data processing module can obtain a pure operating force signal without noise, reducing the impact of vibration on the entire system; the speed calculation module can obtain the given motor speed through mathematical operations to ensure the smooth operation of the intelligent hoisting device. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 FIG. is a structural block diagram of the end vibration suppression system provided by an embodiment of the present invention;

[0055] Figure 2 FIG. is a structural block diagram of the initialization module provided by an embodiment of the present invention;

[0056] Figure 3 FIG. is a structural block diagram of the operating force measurement module provided by an embodiment of the present invention;

[0057] Figure 4 FIG. is a structural block diagram of the data processing module provided by an embodiment of the present invention;

[0058] Figure 5 FIG. is a structural block diagram of the noise reduction processing steps provided by an embodiment of the present invention;

[0059] Figure 6 FIG. is an experimental effect diagram of the data processing module provided by an example of the present invention;

[0060] Figure 7 FIG. is a structural block diagram of the speed calculation module provided by an example of the present invention; DETAILED DESCRIPTION OF THE INVENTION

[0061] In order to better understand the purpose, structure and function of the present invention, the intelligent hoisting device end vibration suppression system and method of the present invention will be further described in detail below with reference to the accompanying drawings.

[0062] An intelligent hoisting device end vibration suppression system of the present invention includes an initialization module, an operating force measurement module, a data processing module and a speed calculation module. The initialization module is used to obtain the gravity G of the heavy object before operation; the operating force measurement module is used to convert the digital signal D sampled by the weighing sensor to obtain a noisy operating force F'; the data processing module is used to convert the noisy operating force signal F' into a pure operating force signal F, reducing the impact of the sensor signal fluctuation caused by the vibration of the transmission mechanism and measurement error on the entire intelligent hoisting device system; the speed calculation module is used to obtain the given speed of the motor to achieve the smooth operation of the intelligent hoisting device.

[0063] In the initial stage when the intelligent hoisting device enters the operating state, first, through the initialization module, the gravity G of the heavy object is obtained. Then, during the lifting and lowering processes, the weighing sensor at the wire rope is sampled to obtain a digital signal D. After passing through the operating force measurement module, an operating force F' containing noise is obtained. The noisy operating force signal F' is processed by the data processing module to obtain a pure operating force signal F without noise. Then, through the speed calculation module, the given speed V of the motor at the top end of the intelligent hoisting device is obtained.

[0064] As Figure 1 shown, a method for suppressing the vibration at the end of an intelligent hoisting device according to the present invention includes the following steps:

[0065] Step 1: In the initial stage when the intelligent hoisting device enters the operating state, the initialization module obtains the gravity G of the heavy object;

[0066] During the operation of the intelligent hoisting device, what the weighing sensor measures is the resultant force of the gravity of the heavy object and the operating force applied by the operator. Therefore, in order to better control the movement of the device, it is necessary to separate the gravity of the heavy object and the operating force. The initialization module of the present invention is as Figure 2 shown, and its main function is to obtain a relatively accurate gravity of the heavy object. Since the ADC of the single-chip microcomputer is used to sample the weighing sensor on the intelligent hoisting device, it is necessary to calibrate the ADC before sampling. In order to eliminate errors, it is necessary to perform a triple mean operation on the sampled values to obtain the sampling average value. The calculation formula is:

[0067]

[0068] where D' is the average value of the sampled values, D is the value obtained by each ADC sampling, and i is the number of measurements.

[0069] The average value of the sampled values is converted to obtain the gravity of the heavy object. The calculation formula is:

[0070]

[0071] where G is the gravity of the heavy object, D' is the average value of the three samplings, V ref is the reference voltage of the ADC, n is the number of bits of the ADC, and K sen is the proportional coefficient between the gravity and voltage of the weighing sensor.

[0072] Step 2: The operating force measurement module converts the digital signal D obtained by sampling the weighing sensor into an operating force F' containing noise and uses it as the input of the data processing module;

[0073] The operating force measurement module is used to measure and separate the operating force applied by the operator in real time when the intelligent hoisting device is operating, as Figure 3As shown in the figure. To ensure the accuracy of control and the synchronization of time, and improve the reliability of sampling, the time interval for each sampling should be kept consistent. Therefore, before each sampling, it is necessary to determine whether the time set by the timer has been reached. At the same time, the operating force applied by the operator changes slowly. To include as much change in the operating force as possible, the sampling time interval should not be too short. Setting it to 0.1 s can better meet the above requirements and can be adjusted according to the actual operating conditions in practice.

[0074] After reaching the timing time of the timer, use the ADC for sampling to obtain the resultant force on the sensor. The calculation formula is:

[0075]

[0076] where T is the resultant force on the sensor, D run is the sampling value during operation, V ref is the reference voltage of the ADC, n is the number of bits of the ADC, and K sen is the proportional coefficient between the gravity and voltage of the load cell.

[0077] To eliminate gross errors, it is necessary to perform threshold judgment on the resultant force T measured by the sensor. If T exceeds the set threshold, it is determined that T contains gross errors and the data is discarded. If T does not exceed the set threshold, it is determined that T does not contain gross errors and enters the subsequent calculation. The setting of the threshold can be adjusted according to the actual measurement situation.

[0078] Subtract the resultant force from the gravity of the heavy object to obtain the operating force containing noise. The calculation formula is:

[0079] F' = T - G

[0080] where F’ is the operating force containing noise, T is the resultant force on the sensor, and G is the gravity of the heavy object obtained by the initialization module.

[0081] Step 3: The data processing module, based on the signal reconstruction principle, obtains the pure operating force F through transformation operations to reduce the impact of vibration on the entire system;

[0082] During the actual operation of the intelligent lifting device, due to the influence of transmission mechanisms such as wire ropes and gears and inaccurate measurement results, the operating force obtained by the operating force measurement module contains a lot of noise and cannot be directly used as the input of the speed calculation module, otherwise it will cause vibration and instability of the entire system. The noise frequency of the operating force is very close to the signal fluctuation frequency and will change with the change of the operating state. Common filtering methods will have problems such as difficult to set the cut-off frequency and large delay, resulting in poor filtering effects, which will further exacerbate the vibration at the end of the device. The data processing module of the present invention is based on the principle of signal reconstruction. Without setting a fixed cut-off frequency and on the premise of ensuring low latency, it converts the operating force signal containing noise into a relatively pure operating force signal, mainly including four steps: data synthesis, noise reduction processing, data extraction, and threshold judgment, as Figure 4 shown.

[0083] In the data synthesis step, first, multiple previously stored operating forces containing noise are found in the memory of the single-chip microcomputer and arranged in chronological order, and then the operating force containing noise obtained from the current sampling is placed at the end of the sequence to form an original array, which is used as the input of the noise reduction processing step.

[0084] The noise reduction processing step uses three parts: forward transformation, coefficient processing, and inverse transformation. Under the premise of ensuring a small delay, it processes the original array of noisy operating forces to obtain a noise-reduced signal.

[0085] The signal obtained after noise reduction processing is an array rather than a single data. Therefore, the role of data extraction is to convert the array into a single data for convenient application in subsequent calculations. Before and after noise reduction, the relative positions of the elements in the array do not change. Therefore, the elements in the noise-reduced array are still arranged in chronological order. By extracting the last element of the array, the obtained value is the data closest to the current moment.

[0086] Since problems such as signal distortion and distortion may occur during the noise reduction process, it is necessary to judge whether signal distortion occurs after noise reduction processing by comparing whether the value of the extracted element exceeds the set threshold. If its value exceeds the set threshold, it is determined that signal distortion has occurred and the data is discarded. If its value does not exceed the set threshold, it is determined that no signal distortion has occurred, and the output data is the pure operating force F.

[0087] The noise reduction processing step mainly includes three parts: forward transformation, coefficient processing, and inverse transformation, as Figure 5 shown. In the forward transformation, the original array is convolved with the selected filter to obtain the high-frequency coefficients and low-frequency coefficients of this layer. The low-frequency coefficients are then convolved with the filter to obtain the high-frequency coefficients and low-frequency coefficients of a new layer. Repeat the above operations until the specified decomposition level is reached. The calculation formula for a single-layer forward transformation is:

[0088]

[0089] Among them, A(k) is the low-frequency coefficient, D(k) is the high-frequency coefficient, h(n) and g(n) are the low-pass filter and high-pass filter during the forward transform respectively, n is the original signal index, k is the coefficient index, and k_max is the length of the coefficients at this layer.

[0090] The role of coefficient processing is to modify the high-frequency coefficients by setting a threshold to achieve the purpose of noise reduction. The soft-threshold processing method can make the denoised signal obtained by the final output have better continuity and smoothness, and takes into account both the fidelity and denoising performance of the signal. Therefore, it is one of the most widely used coefficient processing methods. The principle of soft-threshold processing is as follows: when the absolute value of the coefficient is less than the threshold, the coefficient is set to zero, which helps to remove low-amplitude noise; when the absolute value of the coefficient is greater than the threshold, the output is the coefficient minus the threshold, which not only retains the strong signal components but also reduces the noise; finally, the calculated coefficient is multiplied by the sign function to ensure that the positive and negative of the coefficient remain unchanged before and after processing, avoiding signal distortion. The calculation formula of soft-threshold processing is:

[0091] C new =sign(C old )max(|C old |-λ,0)

[0092] Among them, C new is the coefficient after soft-threshold processing, C old is the coefficient before soft-threshold processing, λ is the threshold, sign is the sign function, and the expression is:

[0093]

[0094] After processing the coefficients, through the inverse transform, the high-frequency coefficients and low-frequency coefficients are convolved and recursively operated with the filters to reconstruct the denoised signal. The calculation formula of the single-layer inverse transform is:

[0095]

[0096] Among them, A(k) is the low-frequency coefficient, D(k) is the high-frequency coefficient, h(n) and g(n) are the low-pass filter and high-pass filter during the inverse transform respectively, n is the original signal index, k is the coefficient index, k_max is the length of the coefficients at this layer, f(n) is the reconstructed denoised signal at the last layer, and is the low-frequency coefficient of the next inverse transform at other layers.

[0097] To better illustrate the effect of the data processing module, the present invention provides experimental results as Figure 6As shown. By comparing the curves in the figure, it can be seen that the data processing module provided by the present invention can convert the noisy operating force into a relatively pure operating force, and at the same time, compared with the traditional average filtering, it can ensure a lower latency.

[0098] Step 4: The speed calculation module converts the operating force F into the motor's given speed V, so that the hoisting device can smoothly complete the lifting and lowering movements.

[0099] The speed calculation module includes three parts: operating force detection, compliance strategy, and ground contact detection, as Figure 7 shown. The operating force detection part mainly judges whether the device needs to move. When the operating force is greater than the set threshold, it outputs the value of the current operating force and makes the device move through subsequent calculations and driving; when the operating force is less than the set threshold, the operating force is set to zero and the device is prohibited from moving. The calculation formula is:

[0100]

[0101] where F is the operating force and c is the set threshold.

[0102] The compliance strategy part uses the operating force and the actual speed of the motor at the previous moment to calculate the given speed of the motor. Since the response ability of the motor is strong, the given speed of the motor is the same as the end speed of the device. Therefore, by controlling the given speed of the motor, the compliant change of the end speed of the device when the operating force changes can be realized. The calculation formula is:

[0103]

[0104] where V is the given speed of the motor, F is the operating force, V real is the actual speed of the motor at the previous moment, B and M are the damping parameter and the inertia parameter respectively, and t is the time interval for each calculation, which should be consistent with the sampling time of the operating force detection module.

[0105] The role of the ground contact detection part is to judge whether the ground contact situation occurs by calculating the difference between two operating forces, and avoid the phenomenon of the heavy object bouncing up after touching the ground. Since at the moment when the heavy object touches the ground, the ground will give the heavy object an upward supporting force instantaneously, causing the value of the weighing sensor to change suddenly, and this change is much larger than the change of the operating force applied by the operator. Therefore, when the difference between the operating forces obtained by two consecutive samplings is greater than the set threshold, it is determined that the ground contact situation has occurred, and the given speed of the motor will be set to zero until manually released; when the difference is less than the set threshold, it is determined that the ground contact situation has not occurred, and the given speed of the motor calculated by the admittance control is output. The calculation formula is:

[0106]

[0107] Among them, V is the given speed of the motor, F(n) and F(n - 1) are the operation forces for two times, and C touch is the set threshold value.

[0108] The terms used in one or more embodiments of this specification are for the purpose of describing specific embodiments only and are not intended to limit one or more embodiments of this specification. The singular forms "a", "the", and "said" used in one or more embodiments of this specification and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" as used herein refers to and includes any and all possible combinations of one or more of the associated listed items.

[0109] The above description is only the preferred embodiment of one or more embodiments of this specification and is not intended to limit one or more embodiments of this specification. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of one or more embodiments of this specification shall be included within the scope of protection of one or more embodiments of this specification.

Claims

1. An end vibration suppression system for an intelligent lifting device, characterized in that, It includes an initialization module, an operating force measurement module, a data processing module and a speed calculation module. The initialization module is used to obtain the gravity G of the heavy object before operation; the operating force measurement module is used to convert the digital signal D sampled by the weighing sensor to obtain the operating force F' containing noise; the data processing module is used to convert the noisy operating force signal F' into a pure operating force signal F; the speed calculation module is used to obtain the given speed of the motor to achieve the stable operation of the intelligent lifting device.

2. An intelligent lifting device end vibration suppression method for the intelligent lifting device end vibration suppression system as described in claim 1, characterized in that, It includes the following steps: Step 1: The initialization module obtains the gravity G of the heavy object at the initial stage when the intelligent lifting device enters the operating state. Step 2: The operating force measurement module converts the digital signal D obtained by sampling the weighing sensor into the operating force F' containing noise as the input of the data processing module. Step 3: The data processing module obtains the pure operating force F through transformation operations based on the signal reconstruction principle. Step 4: The speed calculation module converts the operating force F into the given speed V of the motor, so that the lifting device can smoothly complete the lifting and lowering movements.

3. The method for suppressing the end vibration of the intelligent hoisting device according to claim 1, wherein The specific steps of Step 1 include: Calibrate the ADC of the single-chip microcomputer, then perform sampling, and perform a three-time mean operation on the sampled values to obtain the sampling average value. The calculation formula is: Among them, D' is the average value of the sampling values, D is the value obtained by each ADC sampling, and i is the number of measurements. Convert the average value of the sampling values to obtain the gravity of the heavy object. The calculation formula is: Among them, G is the gravity of the heavy object, D’ is the average value of three samplings, V ref is the reference voltage of the ADC, n is the number of bits of the ADC, K sen is the proportionality coefficient between the gravity and voltage of the weighing sensor.

4. The method for suppressing the vibration at the end of the intelligent hoisting device according to claim 1, characterized in that, The specific steps of Step 2 include: Sample the operating force applied by the operator at intervals. The time interval for each sampling is kept consistent. Therefore, before each sampling, it is necessary to judge whether the time set by the timer has been reached. After reaching the timing time of the timer, use the ADC to sample to obtain the resultant force on the sensor. The calculation formula is: Among them, T is the resultant force on the sensor, D run is the sampling value during operation, V ref is the reference voltage of the ADC, n is the number of bits of the ADC, K sen is the proportionality coefficient between the gravity and voltage of the load cell; Perform a threshold judgment on the resultant force T measured by the sensor. If T exceeds the set threshold, it is determined that T contains gross errors and the data is discarded. If T does not exceed the set threshold, it is determined that T does not contain gross errors and enters the subsequent calculation. The setting of the threshold is adjusted according to the actual measurement situation. Subtract the resultant force from the gravity of the heavy object to obtain the operating force containing noise. The calculation formula is: F' = T - G Among them, F' is the operating force containing noise, T is the resultant force on the sensor, and G is the gravity of the heavy object obtained by the initialization module.

5. The method for suppressing the end vibration of the intelligent hoisting device according to claim 1, characterized in that, The specific steps of Step 3 include: The data processing module includes four steps: data synthesis, noise reduction processing, data extraction and threshold judgment; In the data synthesis step, first find multiple operating forces containing noise stored previously in the memory of the single-chip microcomputer and arrange them in chronological order, and then place the operating force containing noise obtained by this sampling at the end of the sequence to form an original array as the input of the noise reduction processing step; The noise reduction processing step uses three parts: forward transformation, coefficient processing and inverse transformation to process the original array of noisy operating forces to obtain the noise-reduced signal while ensuring a small delay. The signal obtained after noise reduction processing is an array rather than a single data. Therefore, the role of data extraction is to convert the array into a single data. The elements in the array after noise reduction are still arranged in chronological order. By extracting the last element of the array, the obtained value is the data closest to the current moment; By comparing whether the value of the extracted element exceeds the set threshold, it is judged whether signal distortion occurs after noise reduction processing. If its value exceeds the set threshold, it is determined that signal distortion has occurred, and the data is discarded. If its value does not exceed the set threshold, it is determined that no signal distortion has occurred, and the output data is the pure operating force F.

6. The method for suppressing the end vibration of the intelligent hoisting device according to claim 5, characterized in that, In the forward transform of the noise reduction processing, the original array is convolved with the selected filter to obtain the high-frequency coefficients and low-frequency coefficients of this layer. The low-frequency coefficients are then convolved with the filter to obtain the high-frequency coefficients and low-frequency coefficients of a new layer; repeat the above operations until the specified decomposition level is reached. The calculation formula for a single-layer forward transform is: Among them, A(k) is the low-frequency coefficient, D(k) is the high-frequency coefficient, h(n) and g(n) are the low-pass filter and high-pass filter during the forward transform respectively, n is the original signal index, k is the coefficient index, and k_max is the coefficient length of this layer.

7. The method for suppressing the end vibration of the intelligent hoisting device according to claim 5, characterized in that, The coefficient processing adopts the soft threshold processing method: when the absolute value of the coefficient is less than the threshold, the coefficient is set to zero; when the absolute value of the coefficient is greater than the threshold, the output is the coefficient minus the threshold; finally, the calculated coefficient is multiplied by the sign function to ensure that the positive and negative nature of the coefficient remains unchanged before and after processing, avoiding signal distortion. The calculation formula for soft threshold processing is: C new = sign(C old ) max(|C old | - λ, 0) Among them, C new is the coefficient after soft threshold processing, C old is the coefficient before soft threshold processing, λ is the threshold, sign is the sign function, and the expression is: After processing the coefficients, through the inverse transform, the high-frequency coefficients and low-frequency coefficients are convolved and recursively operated with the filter to reconstruct the noise-reduced signal.

8. The method for suppressing the end vibration of the intelligent hoisting device according to claim 5, characterized in that, The calculation formula for a single-layer inverse transform is: Among them, A(k) is the low-frequency coefficient, D(k) is the high-frequency coefficient, h(n) and g(n) are the low-pass filter and high-pass filter during the inverse transform respectively, n is the original signal index, k is the coefficient index, k_max is the coefficient length of this layer, f(n) is the noise-reduced signal reconstructed at the last layer, and is the low-frequency coefficient of the next inverse transform at other layers.

9. The method for suppressing the end vibration of the intelligent lifting device according to claim 1, wherein The speed calculation module in step 4 includes three parts: operating force detection, compliance strategy, and touchdown detection. The operating force detection part judges whether the device needs to move. When the operating force is greater than the set threshold, the value of the current operating force is output, and the device is driven to move through subsequent calculations; when the operating force is less than the set threshold, the operating force is set to zero, and the device is prohibited from moving. The calculation formula is: Among them, F is the operating force, and c is the set threshold, The compliance strategy part uses the operating force and the actual speed of the motor at the previous moment to calculate the given speed of the motor. By controlling the given speed of the motor, the compliant change of the end speed of the device when the operating force changes is realized. The calculation formula is: where V is the given speed of the motor, F is the operating force, V real is the actual speed of the motor at the previous moment, B and M are the damping parameter and the inertia parameter respectively, and t is the time interval for each calculation, which should be consistent with the sampling time of the operating force detection module; The function of the ground contact detection part is to judge whether the ground contact occurs by calculating the difference between two operating forces, so as to avoid the phenomenon of the heavy object bouncing up after touching the ground; when the difference between the operating forces obtained by two consecutive samplings is greater than the set threshold, it is determined that the ground contact has occurred, and the given speed of the motor will be set to zero until manually released; when the difference is less than the set threshold, it is determined that the ground contact has not occurred, and the given speed of the motor calculated by the admittance control is output. The calculation formula is: Among them, V is the given speed of the motor, F(n) and F(n - 1) are the operating forces of two operations, and C touch is the set threshold value.

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