Multifunctional hardware intelligent management system

Abstract

The invention relates to the technical field of electric drill equipment management, in particular to a multifunctional hardware intelligent management system which comprises an intelligent control unit, a sensing detection unit and a driving execution unit. The dynamic prediction model is used for predicting a system delay advanced adjustment instruction, the sensing detection unit is used for collecting material hardness, torque and rotating speed data, the driving execution unit is used for driving the motor according to the instruction, and the speed regulation triggering module and the like work cooperatively. The drilling quality and efficiency are improved, and the drill bit damage risk is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of electric drill equipment management, in particular to a multifunctional hardware product intelligent management system. Background Art

[0002] Intelligent management is an important technology. In the field of hardware tools, electric drills are a widely used tool. Traditional electric drills have many limitations in speed and torque adjustment.

[0003] Traditional electric drills usually use simple mechanical speed regulation methods, such as adjusting the speed by changing different gear ratios. This method has a limited adjustment range and is cumbersome to operate. It is difficult to accurately adjust according to material properties in real time. Torque adjustment is also often rough and is generally achieved by manually adjusting the mechanical device. It cannot accurately adapt to the torque requirements of different materials, which can easily lead to poor drilling results. For example, when drilling on materials with higher hardness, the drilling progress may be slow or even the drill bit may be damaged due to insufficient torque; on soft materials, the material may be excessively deformed or damaged due to excessive torque. When faced with complex and changeable work scenes and materials, the speed and torque adjustment capabilities of traditional electric drills are difficult to meet actual needs, affecting work efficiency and quality. In order to solve this technical problem, we provide a multifunctional hardware product intelligent management system. Summary of the invention

[0004] The purpose of the present invention is to provide a multifunctional hardware product intelligent management system to solve the problems raised in the above background technology.

[0005] To achieve the above-mentioned purpose, a multifunctional hardware product intelligent management system is provided, which includes an intelligent control unit, a sensor detection unit, a drive execution unit, a speed regulation trigger module and a feedback regulation module;

[0006] The intelligent control unit is used to manage the operation of the electric drill, receive and process data information from multiple sensors, and judge the material hardness based on deep learning material hardness recognition. According to the judgment result, an adaptive speed torque matching algorithm is introduced to calculate the output control amount of the speed and torque, and finally the speed and torque are self-adjusted according to the output control amount, wherein:

[0007] When self-regulating the speed and torque, a dynamic prediction model is used to predict the system delay, and control instructions are issued in advance according to the predicted delay time;

[0008] The sensing detection unit includes a variety of sensors for real-time acquisition of material hardness information, torque magnitude and rotation speed during the operation of the electric drill;

[0009] The speed control trigger module is connected to the sensor detection unit and the intelligent control unit. When the electric drill starts to work or the hardness of the material changes during the work, the speed control operation is triggered, and the data signal transmitted by the sensor detection unit is monitored in real time. When the material hardness changes are detected, the speed control trigger signal is sent to the intelligent control unit in real time;

[0010] The drive execution unit drives the motor to execute corresponding actions and adjusts the speed and torque output of the electric drill according to the instructions of the intelligent control unit using the motor drive control technology;

[0011] The feedback regulation module is connected to the drive execution unit and the sensor detection unit to monitor the actual speed and torque of the electric drill in real time and feed it back to the intelligent control unit. If the actual speed and torque deviate from the expected speed and torque, the intelligent control unit will adjust the control instructions again through the feedback regulation module until the actual speed and torque of the electric drill reach the set value.

[0012] As a further improvement of the technical solution, the intelligent control unit includes a parameter calculation module and an instruction generation module:

[0013] The parameter calculation module introduces an adaptive speed-torque matching algorithm based on the received speed control trigger signal and the data from the material hardness sensor to calculate the output control amount of speed and torque;

[0014] The instruction generation module generates corresponding control instructions according to the output control quantity and sends them to the drive execution unit.

[0015] As a further improvement of the technical solution, the method for the intelligent control unit to self-regulate the speed and torque of the motor is as follows:

[0016] S1. When the electric drill starts working, the material hardness sensor detects the hardness information of the drilling material in real time and transmits it to the intelligent control unit. The intelligent control unit calculates the initial speed and torque setting values ​​according to the pre-stored database of the correspondence between the material hardness, speed and torque, and the received real-time material hardness data;

[0017] S2. During the drilling process, the speed sensor and torque sensor continuously monitor the actual speed and torque of the electric drill. If the deviation between the actual speed and the set speed value exceeds the deviation range, or the deviation between the actual torque and the set torque exceeds the deviation range, the intelligent control unit generates an adjustment instruction according to the adaptive speed torque matching algorithm and sends it to the drive execution unit;

[0018] S3. The drive execution unit adjusts the motor speed and torque in real time by adjusting the power supply voltage and current parameters of the motor according to the adjustment instruction.

[0019] As a further improvement of the technical solution, the expressions of the initial speed and torque setting values ​​in S1 are as follows:

[0020] Initial speed setting value N set :

[0021]

[0022] Among them, N i and N i+1 The material hardness is H i and H i+1 The corresponding speed value when

[0023] Torque setting value T set :

[0024]

[0025] Among them, T j and T j+1 The material hardness is H i and H i+1 The corresponding torque value.

[0026] As a further improvement of the technical solution, the method for generating corresponding adjustment instructions according to the adaptive speed torque matching algorithm in S2 is as follows:

[0027] Calculate the deviation between the actual speed and torque and the set speed and torque, and set the proportional coefficient, integral coefficient and differential coefficient according to historical experience values, and calculate the proportional control item, integral control item and differential control item according to the mathematical relationship between the proportional coefficient, integral coefficient, differential coefficient and the deviation;

[0028] The output control quantity of the adaptive speed torque matching algorithm is obtained by integrating the proportional, integral and differential control items, and the output control quantity is sent to the drive execution unit.

[0029] As a further improvement of the technical solution, the method of adjusting the speed and torque of the electric drill in real time by adjusting the power supply voltage and current of the motor in S3 specifically includes:

[0030] During the drilling process, the intelligent control unit receives feedback data from the speed sensor and torque sensor in real time and compares it with the set value. If the actual speed is lower than the set speed and the difference exceeds the deviation range, the intelligent control unit outputs the control amount to the drive execution unit. The drive execution unit increases the output voltage of the driver according to the output control amount to increase the motor speed. Conversely, if the actual speed is higher than the set speed, the output voltage of the driver is reduced. For torque regulation, the same control strategy is adopted. When the actual torque is lower than the set torque, the current output of the driver is increased according to the output control amount. When the actual torque is higher than the set torque, the current output is reduced.

[0031] As a further improvement of the technical solution, the intelligent control unit uses a dynamic prediction model to estimate the delay of the system, which is specifically as follows:

[0032] The current voltage V t 、Current I t And the control instruction sequence, speed sequence and torque sequence at several previous moments are used as the input data of the model. The expression of the input data is Where m is the number of selected historical data time steps, indicating that the impact of the data of the past m time steps on the current state is considered;

[0033] Will The input is sent to the dynamic prediction model, and the model performs forward propagation calculations to output the predicted speed and torque sequence at several moments in the future. and According to the predicted speed and torque sequence, its changing trend is analyzed to determine the time required to reach the set value, that is, the predicted response time of the speed and torque, and a threshold is set. When the difference between the predicted speed or torque and the set value is less than the threshold, it is considered that the set value is reached.

[0034] As a further improvement of the technical solution, the calculation method of the speed and torque response time is specifically as follows:

[0035] calculate The minimum value at , as the predicted speed response time step, where ε N is the speed threshold, and then converts it into actual time. Assuming that the actual time interval corresponding to each time step is Δt, then t N =i×Δt, where t N is the speed response time;

[0036] calculate The minimum value at , as the predicted torque response time step, where ε T is the torque threshold, which is then converted into actual torque. Assuming that the torque time interval corresponding to each time step is Δt, then t T=i×Δt, where t T is the torque response time.

[0037] As a further improvement of the technical solution, the method of issuing a control instruction in advance according to the predicted delay time specifically includes:

[0038] According to the predicted speed and torque response time, as well as the deviation between the current and set values, the control command amount that needs to be adjusted in advance is calculated. According to the calculated adjustment amount, the control command sent to the drive execution unit is adjusted in advance. The new voltage command is V new =V t +ΔV, the new current command is I new =I t +ΔI.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] In a multifunctional intelligent management system for hardware products, an intelligent control unit is used to use deep learning to identify material hardness, an adaptive algorithm is introduced to calculate the control quantity, and a dynamic prediction model is used to predict delays and adjust instructions in advance. It can collect data in real time, accurately adjust the speed and torque, overcome the shortcomings of traditional electric drills, and keep the electric drills in the best condition for different materials and scenarios, improve drilling quality and efficiency, and reduce the risk of drill bit damage, providing users with a more intelligent, efficient, and reliable operating experience, and improving the level of intelligent management of hardware products. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is an overall block diagram of the present invention.

[0042] The meaning of each number in the figure is:

[0043] 1. Intelligent control unit; 11. Parameter calculation module; 12. Instruction generation module;

[0044] 2. Sensing detection unit; 3. Driving execution unit. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] Example 1

[0047] The present invention provides a multifunctional hardware product intelligent management system. Figure 1As shown, it includes an intelligent control unit 1, a sensor detection unit 2, a drive execution unit 3, a speed regulation trigger module and a feedback regulation module;

[0048] The intelligent control unit 1 is used to manage the operation of the electric drill, receive and process data information from multiple sensors, and judge the material hardness based on deep learning material hardness recognition. According to the judgment result, an adaptive speed torque matching algorithm is introduced to calculate the output control amount of the speed and torque. Finally, the speed and torque are self-adjusted according to the output control amount, wherein:

[0049] When self-regulating the speed and torque, a dynamic prediction model is used to predict the system delay, and control instructions are issued in advance according to the predicted delay time.

[0050] The speed regulation trigger module is connected to the sensor detection unit 2 and the intelligent control unit 1. When the electric drill starts to work or the hardness of the material changes during the work, the speed regulation operation is triggered, and the data signal transmitted by the sensor detection unit 2 is monitored in real time. When the material hardness changes are detected, the speed regulation trigger signal is sent to the intelligent control unit 1 in real time;

[0051] The feedback regulation module is connected to the drive execution unit 3 and the sensor detection unit 2, monitors the actual speed and torque of the electric drill in real time, and feeds it back to the intelligent control unit 1. If the actual speed and torque deviate from the expected speed and torque, the intelligent control unit 1 adjusts the control command again through the feedback regulation module until the actual speed and torque of the electric drill reach the set value.

[0052] The intelligent control unit includes a parameter calculation module and an instruction generation module:

[0053] The parameter calculation module 11 introduces an adaptive speed-torque matching algorithm according to the received speed control trigger signal and the data transmitted by the material hardness sensor to calculate the output control amount of the speed and torque;

[0054] The instruction generation module 12 generates corresponding control instructions according to the output control amount and sends them to the drive execution unit 3;

[0055] The method for the intelligent control unit 1 to self-regulate the speed and torque of the motor is as follows:

[0056] S1. When the electric drill starts working, the material hardness is the key factor in determining the appropriate rotation speed and torque. The material hardness sensor detects the hardness information of the drilling material in real time and transmits it to the intelligent control unit 1. The intelligent control unit 1 calculates the initial rotation speed and torque setting value according to the pre-stored database of the correspondence between the material hardness, the rotation speed and the torque, and the received real-time material hardness data, so as to provide a reasonable starting parameter setting for the subsequent drilling work, thereby improving the versatility and applicability of the electric drill and reducing problems such as drill bit wear or poor drilling effect caused by inappropriate initial parameters;

[0057] During the drilling process, due to the unevenness of the material, the wear of the drill bit and other external factors, the actual speed and torque of the electric drill may deviate from the initial set values. In order to ensure that the drilling work is always carried out under appropriate parameters, it is necessary to monitor the actual speed and torque in real time and compare them with the set values. When the deviation exceeds a certain range, it means that the current speed and torque are no longer suitable for the current drilling situation and need to be adjusted in time. Therefore, the intelligent control unit generates adjustment instructions based on the adaptive speed torque matching algorithm.

[0058] S2. During the drilling process, the speed sensor and the torque sensor continuously monitor the actual speed and torque of the electric drill. If the deviation between the actual speed and the set speed value exceeds the deviation range, or the deviation between the actual torque and the set torque exceeds the deviation range, the intelligent control unit 1 generates an adjustment instruction according to the adaptive speed torque matching algorithm and sends it to the drive execution unit 3, thereby improving the timeliness and accuracy of the adjustment, ensuring that the electric drill can correct the deviation of the speed and torque in time during the drilling process and keep it within the appropriate working parameter range, thereby improving the drilling quality and efficiency and extending the service life of the drill bit;

[0059] S3, the driving execution unit 3 adjusts the speed and torque of the electric drill in real time according to the adjustment instruction by adjusting the power supply voltage and current parameters of the motor, so that the electric drill can respond to the adjustment instruction in real time and maintain working at a suitable speed and torque, thereby further improving the drilling quality and efficiency.

[0060] The expressions for the initial speed and torque setting values ​​in S1 are as follows:

[0061] In order to realize that the electric drill automatically adjusts the speed and torque according to the hardness of the material, it is necessary to establish a quantitative relationship between material hardness and speed and torque, and establish a three-dimensional mapping table of material hardness-speed-torque, which can better handle subtle changes in material hardness, where material hardness is used as the independent variable and speed and torque are used as dependent variables. For a given material hardness range, it is divided into several small intervals. In each small interval, a set of corresponding speed and torque values ​​are determined through experimental calculations, which can more accurately describe this relationship to meet the drilling needs of materials with different hardness;

[0062] After receiving the real-time hardness value from the material hardness sensor, first determine the small interval where the hardness value is located. Suppose the hardness value is H, the endpoint hardness values ​​of the small interval are H1 and H2, the corresponding speed values ​​are N1 and N2, and the torque values ​​are T1 and T2, then:

[0063] Initial speed setting value N set :

[0064]

[0065] Among them, N i and N i+1 The material hardness is H i and H i+1 The corresponding speed value when

[0066] Torque setting value T set :

[0067]

[0068] Among them, T j and T j+1 The material hardness is H i and H i+1 The corresponding torque value.

[0069] The method for generating corresponding adjustment instructions according to the adaptive speed torque matching algorithm in S2 is as follows:

[0070] Calculate the deviation between the actual speed and torque and the set speed and torque N (t) and e T (t), where

[0071] e N (t) = N set (t)-N real (t)

[0072] e T (t) = T set (t)-T real (t)

[0073] Among them, N set (t) and T set (t) are the actual speed and actual torque at time t, respectively. The proportional coefficient K is set according to historical experience. p , integral coefficient K I and the differential coefficient K D , and calculate the proportional control term u p (t),u p (t) = K p ×eN (t) and u p (t) = K p ×e T (t), the proportional control term is used to quickly respond to the deviation and reduce the error, but using it alone may cause a steady-state error in the system. Then the speed deviation and torque are integrated, and the integral expression is:

[0074]

[0075] Where τ is the integral variable, and the integral control term u is calculated according to the integral coefficient I (t),u I (t) = K I I N (t) and, the integral control term is used to eliminate the steady-state error so that the system can accurately track the set value in the steady state, but too strong an integral action may cause the system to respond slowly or produce overshoot. Finally, the differential control term of the speed and torque is calculated, that is:

[0076]

[0077] The differential control term is used to predict the change trend of the deviation, adjust the system in advance, suppress overshoot, and improve the stability and response speed of the system. Finally, the proportional, integral, and differential control terms are combined to obtain the output control quantity of the PID controller and the output control quantity of the adaptive speed torque matching algorithm.

[0078] For speed control:

[0079] u N (t) = u p (t)+u I (t)+u D (t)

[0080] For torque control:

[0081] u T (t) = u p (t)+u I (t)+u D (t)

[0082] By continuously adjusting the parameter K of the adaptive speed torque matching algorithm p , K I and K D , so that the actual speed and torque of the electric drill can quickly and accurately track the set values, achieving good control effect.

[0083] In S3, the speed and torque of the electric drill are adjusted in real time by adjusting the power supply voltage and current of the motor, specifically including:

[0084] During the drilling process, the intelligent control unit 1 receives the feedback data from the speed sensor and the torque sensor in real time, realizing real-time monitoring of the working state of the electric drill. This closed-loop control method can timely detect the deviation between the actual speed and torque and the set value, so as to make precise adjustments and compare them with the set value. If the actual speed is lower than the set speed and the difference exceeds the deviation range, the intelligent control unit 1 outputs the control amount to the drive execution unit 3, and the drive execution unit 3 increases the output voltage of the driver according to the output control amount to increase the motor speed. On the contrary, if the actual speed is higher than the set speed, the output voltage of the driver is reduced. For the adjustment of torque, the same control strategy is adopted. When the actual torque is lower than the set torque, the current output of the driver is increased according to the output control amount. When the actual torque is higher than the set torque, the current output is reduced. It directly acts on the drive parameters of the motor, can quickly and effectively change the output characteristics of the motor, and realize flexible adjustment of the speed and torque.

[0085] The intelligent control unit 1 uses a dynamic prediction model to estimate the delay of the system, as follows:

[0086] The current voltage V t 、Current I t And the control instruction sequence, speed sequence and torque sequence at several previous moments are used as the input data of the model. The expression of the input data is Where m is the number of selected historical data time steps, indicating that the impact of the data of the past m time steps on the current state is considered;

[0087] Will The input is sent to the dynamic prediction model, and the model performs forward propagation calculations to output the predicted speed and torque sequence at several moments in the future. and According to the predicted speed and torque sequence, its changing trend is analyzed to determine the time required to reach the set value, that is, the response time of the speed and torque, and set a threshold. When the difference between the predicted speed or torque and the set value is less than the threshold, it is considered that the set value is reached.

[0088] The calculation method of the speed and torque response time is as follows:

[0089] calculate The minimum value at , as the predicted speed response time step, where ε N is the speed threshold, and then converts it into actual time. Assuming that the actual time interval corresponding to each time step is Δt, then t N =i×Δt, where t α is the speed response time;

[0090] calculate The minimum value at , as the predicted torque response time step, where εT is the torque threshold, which is then converted into actual torque. Assuming that the torque time interval corresponding to each time step is Δt, then t T =i×Δt, where t T is the torque response time.

[0091] The method of issuing control instructions in advance according to the predicted delay time specifically includes:

[0092] According to the predicted speed and torque response time, as well as the deviation between the current and set values, calculate the control command amount that needs to be adjusted in advance. Assume that the current speed deviation is ΔN = N set -N real (t), the torque deviation is ΔT = T set -T real (t), the predicted speed response time is t N , the predicted torque response time is t T , the idea of ​​proportional control can be used to calculate the adjustment amount, that is:

[0093]

[0094] According to the calculated adjustment amount, the control instruction sent to the drive execution unit 3 is adjusted in advance, and the new voltage instruction is V new =V t +ΔV, the new current command is I new =I t +ΔI.

[0095] The sensing detection unit 2 includes a variety of sensors for real-time acquisition of material hardness information, torque size and rotation speed during the operation of the electric drill.

[0096] The driving execution unit 3 drives the motor to execute corresponding actions and adjusts the rotation speed and torque output of the electric drill according to the instructions of the intelligent control unit 1 using the motor driving control technology.

[0097] In the present invention, an intelligent control unit is used to identify material hardness based on deep learning, an adaptive algorithm is used to calculate the speed and torque control amount, and a dynamic prediction model is used to predict system delays and adjust instructions in advance. The sensor detection unit collects material hardness, torque and speed data, and the drive execution unit drives the motor according to the instructions. The present invention also includes modules such as speed regulation triggering to work together. The present invention overcomes the limitations of traditional electric drill speed and torque adjustment, can be accurately adjusted in real time, improves drilling quality and efficiency, and reduces the risk of drill bit damage.

[0098] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A multifunctional hardware product intelligent management system, characterized in that: It comprises an intelligent control unit (1), a sensor detection unit (2), a drive execution unit (3), a speed regulation trigger module and a feedback regulation module; The intelligent control unit (1) is used to manage the operation of the electric drill, receive and process data information from multiple sensors, and judge the material hardness based on deep learning material hardness recognition, introduce an adaptive speed torque matching algorithm based on the judgment result, calculate the output control amount of the speed and torque, and finally self-regulate the speed and torque based on the output control amount, wherein: When self-regulating the speed and torque, a dynamic prediction model is used to predict the system delay, and control instructions are issued in advance according to the predicted delay time; The sensing detection unit (2) comprises a plurality of sensors for collecting material hardness information, torque magnitude and rotation speed in real time during the operation of the electric drill; The speed regulation trigger module is connected to the sensing detection unit (2) and the intelligent control unit (1), and when the electric drill starts to work or the hardness of the material changes during operation, the speed regulation operation is triggered, and the data signal transmitted by the sensing detection unit (2) is monitored in real time. When a change in the hardness of the material is detected, a speed regulation trigger signal is sent to the intelligent control unit (1) in real time; The driving execution unit (3) drives the motor to execute corresponding actions and adjusts the rotation speed and torque output of the electric drill according to the instructions of the intelligent control unit (1) using motor driving control technology; The feedback adjustment module is connected to the driving execution unit (3) and the sensor detection unit (2), monitors the actual rotation speed and torque of the electric drill in real time, and feeds back the actual rotation speed and torque to the intelligent control unit (1); if there is a deviation between the actual rotation speed and torque and the expected rotation speed and torque, the intelligent control unit (1) adjusts the control instruction again through the feedback adjustment module until the actual rotation speed and torque of the electric drill reach the set value.

2. The multifunctional hardware product intelligent management system according to claim 1 is characterized in that: The intelligent control unit (1) comprises a parameter calculation module (11) and an instruction generation module (12): The parameter calculation module (11) introduces an adaptive speed torque matching algorithm according to the received speed control trigger signal and the data transmitted by the material hardness sensor to calculate the output control amount of the speed and torque; The instruction generation module (12) generates corresponding control instructions according to the output control quantity and sends the instructions to the driving execution unit (3).

3. The multifunctional hardware product intelligent management system according to claim 1 is characterized in that: The method for the intelligent control unit (1) to self-regulate the speed and torque of the motor is specifically as follows: S1. When the electric drill starts working, the material hardness sensor detects the hardness information of the drilling material in real time and transmits it to the intelligent control unit (1). The intelligent control unit (1) calculates the initial speed and torque setting values ​​according to the pre-stored database of the correspondence between the material hardness and the speed and torque, and the received real-time material hardness data; S2. During the drilling process, the speed sensor and the torque sensor continuously monitor the actual speed and torque of the electric drill. If the deviation between the actual speed and the set speed value exceeds the deviation range, or the deviation between the actual torque and the set torque exceeds the deviation range, the intelligent control unit (1) generates an adjustment instruction according to the adaptive speed torque matching algorithm and sends it to the drive execution unit (3); S3, the driving execution unit (3) adjusts the power supply voltage and current parameters of the motor according to the adjustment instruction, thereby adjusting the speed and torque of the electric drill in real time.

4. The multifunctional hardware product intelligent management system according to claim 3 is characterized in that: The expressions of the initial speed and torque setting values ​​in S1 are as follows: Initial speed setting value N set : Among them, N i and N i+1 The material hardness is H i and H i+1 The corresponding speed value when Torque setting value T set : Among them, T j and T j+1 The material hardness is H i and H i+1 The corresponding torque value.

5. The multifunctional hardware product intelligent management system according to claim 3 is characterized by: The method for generating corresponding adjustment instructions according to the adaptive speed torque matching algorithm in S2 is specifically as follows: Calculate the deviation between the actual speed and torque and the set speed and torque, and set the proportional coefficient, integral coefficient and differential coefficient according to historical experience values, and calculate the proportional control item, integral control item and differential control item according to the mathematical relationship between the proportional coefficient, integral coefficient, differential coefficient and the deviation; The proportional, integral and differential control items are integrated to obtain the output control quantity of the adaptive speed torque matching algorithm, and the output control quantity is sent to the drive execution unit (3).

6. The multifunctional hardware product intelligent management system according to claim 3 is characterized by: The method of adjusting the motor speed and torque in real time by adjusting the power supply voltage and current of the motor in S3 specifically includes: During the drilling process, the intelligent control unit (1) receives feedback data from the speed sensor and the torque sensor in real time and compares the data with the set value. If the actual speed is lower than the set speed and the difference exceeds the deviation range, the intelligent control unit (1) outputs a control amount to the drive execution unit (3). The drive execution unit (3) increases the output voltage of the driver according to the output control amount to increase the motor speed. On the contrary, if the actual speed is higher than the set speed, the output voltage of the driver is reduced. For the adjustment of the torque, the same control strategy is adopted. When the actual torque is lower than the set torque, the current output of the driver is increased according to the output control amount. When the actual torque is higher than the set torque, the current output is reduced.

7. The multifunctional hardware product intelligent management system according to claim 1 is characterized in that: The intelligent control unit (1) uses a dynamic prediction model to estimate the delay of the system, specifically as follows: The current voltage V t 、Current I t And the control instruction sequence, speed sequence and torque sequence at several previous moments are used as the input data of the model. The expression of the input data is Where m is the number of selected historical data time steps, indicating that the impact of the data of the past m time steps on the current state is considered; Will Input into the dynamic prediction model and output the predicted speed and torque sequence at several moments in the future and According to the predicted speed and torque sequence, its changing trend is analyzed, the predicted response time of speed and torque is determined, and a threshold is set. When the difference between the predicted speed or torque and the set value is less than the threshold, it is considered that the set value is reached.

8. The multifunctional hardware product intelligent management system according to claim 7 is characterized in that: The calculation method of the speed and torque response time is specifically as follows: calculate The minimum value at , as the predicted speed response time step, where ε N is the speed threshold, and then converts it into actual time. Assuming that the actual time interval corresponding to each time step is Δt, then t N =i×Δt, where t N is the speed response time; calculate The minimum value at , as the predicted torque response time step, where ε T is the torque threshold, which is then converted into actual torque. Assuming that the torque time interval corresponding to each time step is Δt, then t T =i×Δt, where t T is the torque response time.

9. The multifunctional hardware product intelligent management system according to claim 1 is characterized in that: The method of issuing the control instruction in advance according to the predicted delay time specifically includes: According to the predicted speed and torque response time, as well as the deviation between the current and set values, the control instruction amount that needs to be adjusted in advance is calculated. According to the calculated adjustment amount, the control instruction sent to the drive execution unit (3) is adjusted in advance. Then, the new voltage instruction is V new =V t +ΔV, the new current command is I new =I t +ΔI.

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