Electric drill control method, system, computer equipment and storage medium

Abstract

The present invention relates to the field of automation control technology, specifically to an electric drill control method, system, computer equipment and storage medium. The electric drill control method comprises the following steps: based on real-time electric drill operation data, collecting voltage and current data of the electric drill operation, combining torque and speed sensors, recording the torque and speed of the electric drill under various power inputs and analyzing the mutual relationship, and generating a speed torque output model. The beneficial effects of the present invention are that by calculating the relationship between torque speed and input power, combining the hardness information of the material, adjusting the torque parameters, matching various depths in the drilling process, improving the drilling efficiency, adjusting the operating parameters according to the vibration data, improving the accuracy and efficiency of drilling, analyzing the operating time and working mode of the electric drill, predicting the remaining life of the drill bit, reducing the maintenance cost and the risk of unexpected downtime, and optimizing the stability and efficiency of the motor operation through compensation parameter adjustment.

Description

Technical Field

[0001] The present invention relates to the field of automation control technology, and in particular to an electric drill control method, system, computer equipment and storage medium. Background Art

[0002] The field of automated control technology focuses on using a variety of control systems and information technologies to control machines and equipment, reduce human intervention and improve efficiency and accuracy, including sensor technology, actuators, automation software, feedback control systems and many other aspects. It is applied to manufacturing, robotics, transportation and various industrial processes, aiming to optimize production processes, improve product quality, reduce costs, reduce labor costs and operational errors, improve safety, and combine real-time data processing and the Internet of Things to improve the flexibility of control systems.

[0003] Among them, the electric drill control method focuses on implementing various control strategies for the electric drill to optimize operational performance, including adjusting and controlling the speed, torque and power of the electric drill through automation technology to match differentiated work requirements and material conditions, combining sensors to monitor the working status of the electric drill in real time, improving the efficiency and accuracy of drilling operations, reducing equipment loss and operational risks, enhancing the convenience and safety of user operations, reducing energy consumption and increasing tool life, and is applied to a variety of industries such as construction, manufacturing and mining.

[0004] Traditional electric drill control methods rely on preset programs and standard operating procedures. They are not adaptable enough to deal with rapidly changing operating environments and complex material conditions. For materials with different hardness, they cannot instantly adjust the torque and speed to match the material properties, resulting in low drilling efficiency and rapid wear of the drill bit. They are also insufficient in vibration control and cannot be adjusted in real time, which reduces drilling accuracy and efficiency. As a result, they cannot achieve optimal performance in high-demand industrial applications, affecting the optimization of production processes and cost efficiency. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an electric drill control method, system, computer equipment and storage medium.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: an electric drill control method, comprising the following steps:

[0007] S1: Based on the real-time electric drill operation data, the voltage and current data of the electric drill operation are collected, and combined with the torque and speed sensors, the torque and speed of the electric drill under various power inputs are recorded and the relationship is analyzed to generate a speed and torque output model;

[0008] S2: Based on the speed torque output model, considering the hardness information of the material type, analyzing the drilling efficiency of the electric drill with differentiated torques at various drilling depths, adjusting the torque to match the changes in the material and drilling depth, and generating a torque adjustment parameter;

[0009] S3: Based on the torque adjustment parameter, using a vibration sensor, real-time acquisition and analysis of vibration data during the operation of the electric drill, evaluating vibration change modes of the electric drill under various speeds and torques, and generating vibration mode analysis results;

[0010] S4: According to the vibration mode analysis result, the operating parameters of the electric drill are adjusted to optimize the vibration of the electric drill, and the parameters are iteratively optimized in combination with the real-time vibration information to generate a work configuration optimization record;

[0011] S5: Based on the work configuration optimization record, by analyzing the operation time and working mode of the electric drill and combining the type of the drill bit, evaluating and predicting the remaining life of the drill bit, and generating drill bit life prediction information;

[0012] S6: Based on the drill life prediction information, the current, voltage and temperature data during operation are collected in real time, the motor operation efficiency is analyzed and the downward trend is evaluated, the compensation parameters are calculated, and the electric drill operation compensation parameters are generated.

[0013] As a further solution of the present invention, the speed-torque output model includes speed-torque correlation data, electric drill power input data, and electric drill operation efficiency evaluation data; the torque adjustment parameters include material hardness impact analysis results, drilling efficiency data, and torque output adjustment parameters; the vibration mode analysis results include vibration frequency data, vibration amplitude analysis results, and information on the impact of vibration on drilling quality; the work configuration optimization record includes operation parameter adjustment results, vibration suppression effect evaluation information, and configuration change history records; the drill bit life prediction information includes drill bit usage statistics, estimated wear rate, and remaining effective working time; the electric drill operation compensation parameters include current and voltage adjustment parameters, temperature impact compensation parameters, and efficiency decline trend information.

[0014] As a further solution of the present invention, based on the real-time electric drill operation data, the voltage and current data of the electric drill operation are collected, and the torque and speed of the electric drill under various power inputs are recorded and analyzed in combination with torque and speed sensors. The steps of generating a speed and torque output model are specifically as follows:

[0015] S101: Based on the real-time operation data of the electric drill, the voltage and current data of the electric drill during operation are collected, the power information of the electric drill under various operation modes is analyzed, and the operation power information is generated;

[0016] S102: Based on the operating power information, using torque and speed sensors, real-time monitoring of torque and speed data of the electric drill under various operating powers, and generating power response data;

[0017] S103: Based on the power response data, the relationship between torque, rotational speed and input power is analyzed, the influence of power change on the operating efficiency of the electric drill is analyzed, and a rotational speed torque output model is generated.

[0018] As a further solution of the present invention, based on the speed torque output model, considering the hardness information of the material type, analyzing the drilling efficiency of the electric drill with differentiated torque at various drilling depths, adjusting the torque to match the changes in the material and drilling depth, and generating the torque adjustment parameter are specifically as follows:

[0019] S201: Based on the speed torque output model, analyzing the drilling efficiency of the electric drill on materials with various hardnesses, evaluating the requirements of the hardnesses of various materials on the electric drill torque, and generating material impact information;

[0020] S202: Based on the material impact information, considering the depth change of the drilling hole, analyzing the impact of various depths on the torque demand, constructing a torque demand change model, and generating a depth impact analysis result;

[0021] S203: Based on the depth impact analysis result, calculate and adjust the torque adjustment parameters required for various materials and differentiated drilling depths, optimize the drilling efficiency, and generate the torque adjustment parameters.

[0022] As a further solution of the present invention, based on the torque adjustment parameter, a vibration sensor is used to collect and analyze the vibration data of the electric drill in real time during operation, and the vibration change mode of the electric drill under various speeds and torques is evaluated. The steps of generating the vibration mode analysis result are specifically as follows:

[0023] S301: Based on the torque adjustment parameter, the vibration data of the electric drill during operation is collected in real time through a vibration sensor, the vibration characteristics under various speed and torque configurations are recorded, and operation vibration data is generated;

[0024] S302: Based on the operation vibration data, frequency analysis is performed on the vibration data under various speeds and torques, vibration frequencies and vibration amplitudes of various speed and torque combinations are identified, and key vibration modes are generated;

[0025] S303: Based on the key vibration modes, evaluate the influence of various vibration modes on the drilling of the electric drill, including drilling efficiency and equipment stability, and generate vibration mode analysis results.

[0026] As a further solution of the present invention, according to the vibration mode analysis result, the operating parameters of the electric drill are adjusted to optimize the vibration of the electric drill, and the parameters are iteratively optimized in combination with the real-time vibration information to generate the working configuration optimization record. Specifically, the steps are as follows:

[0027] S401: Based on the vibration mode analysis result, analyzing the influence of the torque, rotation speed and propulsion force setting of the electric drill on the vibration, identifying key influencing parameters, and generating vibration cause analysis data;

[0028] S402: Based on the vibration cause analysis data, adjusting the torque, rotation speed and propulsion force parameters of the electric drill to optimize the vibration performance, and recording the adjusted vibration data to generate parameter adjustment test results;

[0029] S403: Based on the parameter adjustment test results and in combination with the real-time vibration monitoring data, the operating parameters of the electric drill are iteratively optimized to optimize the vibration performance and drilling efficiency, and a work configuration optimization record is generated.

[0030] As a further solution of the present invention, based on the work configuration optimization record, by analyzing the running time and working mode of the electric drill and combining the type of the drill bit, the remaining life of the drill bit is evaluated and predicted, and the steps of generating drill bit life prediction information are specifically as follows:

[0031] S501: Based on the work configuration optimization record, collect and analyze the data of the electric drill operation time and work mode, evaluate the operation efficiency under various drill types, and generate drill type operation data;

[0032] S502: Based on the drill bit type operation data, analyzing the wear speed and efficiency of multiple types of drill bits, evaluating the performance of the drill bits in differentiated working modes, and generating drill bit performance evaluation results;

[0033] S503: Based on the drill bit performance evaluation result, combined with the usage time and operation intensity, the wear trends of multiple drill bits are analyzed and the remaining life is predicted, and the drill bit life prediction information is generated.

[0034] As a further solution of the present invention, based on the drill life prediction information, the current, voltage and temperature data in operation are collected in real time, the motor operation efficiency is analyzed and the downward trend is evaluated, and the compensation parameters are calculated. The steps of generating the electric drill operation compensation parameters are specifically as follows:

[0035] S601: Based on the drill life prediction information, monitor the current, voltage and temperature of the electric drill in real time, record key operating parameters, and generate motor monitoring data;

[0036] S602: Analyze the motor efficiency based on the motor monitoring data, identify key factors that affect the efficiency decline, evaluate the motor performance change, and generate motor operation efficiency data;

[0037] S603: Based on the motor operation efficiency data, a fuzzy logic control algorithm is used to calculate the motor operation compensation parameters that need to be adjusted, optimize the motor operation efficiency, and generate the electric drill operation compensation parameters.

[0038] As a further solution of the present invention, the fuzzy logic control algorithm is according to the formula:

[0039]

[0040] Calculate the adjusted motor operating parameters, where: are the motor operating parameters after adjustment. is the proportional gain, is the error signal, is the integration time, represents the integral of the error signal over time, is the differential time, represents the rate of change of the error signal, is the weight coefficient of ambient temperature, is the ambient temperature, is the weight coefficient of the load change rate, is the load change rate, is the weight coefficient of the vibration level, is the vibration level, is the weight coefficient of the motor life prediction value, is the predicted value of motor life, For small time intervals, is the error signal of minor changes.

[0041] The electric drill control system is used to execute the electric drill control method, and the electric drill control system includes:

[0042] The operation data acquisition module collects the voltage and current data of the electric drill when it is running based on the real-time electric drill operation data. It combines the torque and speed sensors to analyze the torque and speed of the electric drill under various power states and generates the electric drill operation data.

[0043] The torque relationship analysis module analyzes and adjusts the torque requirements of the electric drill at various drilling depths based on the electric drill operation data and takes into account the material hardness information, optimizes the drilling efficiency, and generates drilling torque configuration parameters;

[0044] The operation vibration control module monitors the vibration condition of the electric drill in real time based on the drilling torque configuration parameters, analyzes the vibration change mode under various speeds and torques, adjusts the operation parameters to optimize the vibration performance, and generates a vibration optimization configuration;

[0045] Using the information analysis module, based on the vibration optimization configuration, evaluates the impact of the electric drill operation time and mode on the drill bit life, combines the drill bit type, predicts the drill bit life, and generates drill bit replacement prompt information;

[0046] The parameter compensation calculation module collects the current, voltage and temperature data of the electric drill in real time based on the drill bit replacement prompt information, calculates the compensation parameters to optimize the motor operation efficiency by analyzing the motor operation efficiency, and generates the electric drill operation compensation parameters.

[0047] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the electric drill control system as described above when executing the computer program.

[0048] A computer-readable storage medium stores a computer program, which implements the steps of the electric drill control method as described above when executed by a processor.

[0049] Compared with the prior art, the advantages and positive effects of the present invention are:

[0050] In the present invention, by calculating the relationship between torque speed and input power, combined with the hardness information of the material, the torque parameters are adjusted to match various depths in the drilling process, thereby improving the drilling efficiency. The operating parameters are adjusted according to the vibration data to improve the accuracy and efficiency of drilling. The operating time and working mode of the electric drill are analyzed to predict the remaining life of the drill bit, reduce maintenance costs and the risk of unexpected downtime, and optimize the stability and efficiency of the motor operation through compensation parameter adjustment. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a schematic diagram of the workflow of the present invention;

[0052] Figure 2 This is a detailed flow chart of S1 of the present invention;

[0053] Figure 3 This is a detailed flow chart of S2 of the present invention;

[0054] Figure 4 This is a detailed flow chart of S3 of the present invention;

[0055] Figure 5 This is a detailed flow chart of S4 of the present invention;

[0056] Figure 6 This is a detailed flow chart of S5 of the present invention;

[0057] Figure 7 This is a detailed flow chart of S6 of the present invention;

[0058] Figure 8 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0060] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0061] See also Figure 1 The present invention provides a technical solution, an electric drill control method, comprising the following steps:

[0062] S1: Based on the real-time electric drill operation data, the voltage and current data of the electric drill operation are collected, and combined with the torque and speed sensors, the torque and speed of the electric drill under various power inputs are recorded and the relationship is analyzed to generate a speed and torque output model;

[0063] S2: Based on the speed-torque output model, considering the hardness information of the material type, the drilling efficiency of the electric drill with differentiated torque at various drilling depths is analyzed, the torque is adjusted to match the changes in material and drilling depth, and the torque adjustment parameters are generated;

[0064] S3: Based on the torque adjustment parameter, the vibration sensor is used to collect and analyze the vibration data of the electric drill in real time during operation, evaluate the vibration change mode of the electric drill under various speeds and torques, and generate vibration mode analysis results;

[0065] S4: According to the vibration mode analysis results, the operating parameters of the electric drill are adjusted to optimize the vibration of the electric drill, and the parameters are iteratively optimized in combination with the real-time vibration information to generate a work configuration optimization record;

[0066] S5: Based on the work configuration optimization record, by analyzing the operation time and working mode of the electric drill and combining the type of drill bit, the remaining life of the drill bit is evaluated and predicted, and the drill bit life prediction information is generated;

[0067] S6: Based on the drill life prediction information, the current, voltage and temperature data during operation are collected in real time, the motor operation efficiency is analyzed and the downward trend is evaluated, the compensation parameters are calculated, and the electric drill operation compensation parameters are generated.

[0068] The speed-torque output model includes speed-torque correlation data, electric drill power input data, and electric drill operation efficiency evaluation data. The torque adjustment parameters include material hardness impact analysis results, drilling efficiency data, torque output adjustment parameters, vibration mode analysis results, vibration frequency data, vibration amplitude analysis results, and information on the impact of vibration on drilling quality. The work configuration optimization record includes operation parameter adjustment results, vibration suppression effect evaluation information, and configuration change history. The drill life prediction information includes drill bit usage statistics, estimated wear rate, and remaining effective working time. The electric drill operation compensation parameters include current and voltage adjustment parameters, temperature impact compensation parameters, and efficiency decline trend information.

[0069] See also Figure 2 Based on the real-time electric drill operation data, the voltage and current data of the electric drill operation are collected. Combined with the torque and speed sensors, the torque and speed of the electric drill under various power inputs are recorded and the relationship between them is analyzed. The steps to generate the speed and torque output model are as follows:

[0070] S101: Based on the real-time electric drill operation data, the voltage and current data of the electric drill during operation are collected, and the power information of the electric drill under various operation modes is analyzed. The specific process of generating the operation power information is as follows;

[0071] In sub-step S101, based on the real-time electric drill operation data, the current and voltage sensors are used to collect the current of the electric drill in real time during operation. and voltage Data, through the instantaneous measurement of current and voltage, calculate the power at each time point , the formula is: ,in, Represents at time The power, For in time The voltage, For in time , analyze the impact of different operating modes of the electric drill on current and voltage, evaluate the average power under multiple modes, predict the operating efficiency of the electric drill, perform periodic analysis on the operating data, identify multiple mode consumption patterns, and generate operating power information.

[0072] S102: Based on the operating power information, using torque and speed sensors, real-time monitoring of the torque and speed data of the electric drill under various operating powers, and generating power response data specifically includes:

[0073] In sub-step S102, based on the operating power information, the torque and speed sensor are used to monitor the torque of the electric drill at different operating powers in real time. and speed , the torque sensor and speed sensor continuously record data and track the performance output of the electric drill in real time. The formula is: ,in, is the conversion factor used to convert from power to torque, For time The torque, For time The power, For time The speed is used to generate power response data.

[0074] S103: Based on the power response data, the relationship between torque, speed and input power is analyzed, and the influence of power change on the operating efficiency of the electric drill is analyzed. The process of generating a speed torque output model is specifically as follows;

[0075] In sub-step S103, based on the power response data, the torque , speed and input power The relationship between them is analyzed, and the relationship model between torque, speed and power is established using the multiple linear regression model. The formula is: ,in, Power Torque The influence coefficient of Speed Torque The influence coefficient of is the intercept of the regression model, which represents the basic torque value under the conditions of zero power and zero speed. The coefficient is estimated through actual measurement data, the impact of power changes on the operating efficiency of the electric drill is analyzed, and the speed-torque output model is generated.

[0076] See also Figure 3 Based on the speed torque output model, considering the hardness information of the material type, the drilling efficiency of the electric drill with differentiated torque at various drilling depths is analyzed, and the torque is adjusted to match the changes in material and drilling depth. The steps to generate the torque adjustment parameters are as follows:

[0077] S201: Based on the speed torque output model, the drilling efficiency of the electric drill on various hardness materials is analyzed, the demand for the electric drill torque of various material hardnesses is evaluated, and the process of generating material impact information is as follows;

[0078] In sub-step S201, based on the speed torque output model, the drilling efficiency of the electric drill on various hardness materials is analyzed, and a multivariate regression analysis method is used, including collecting the drilling torque and speed data from materials with different hardnesses, taking the material hardness as the independent variable and the electric drill torque as the dependent variable, and constructing a data model. According to the data model, the regression analysis formula is used to calculate the influence of various hardness materials on the electric drill torque, and the formula is: ,in, is the required torque, is the material hardness, is the intercept term, representing the basic torque demand, is the coefficient of hardness, indicating how the torque requirement changes for every unit increase in hardness. is the error term, representing the influence of other unobserved variables, and is used to evaluate the demand for electric drill torque for various material hardnesses and generate material impact information.

[0079] S202: Based on the material impact information, considering the change in the depth of the drilling hole, analyzing the impact of various depths on the torque demand, building a torque demand change model, and generating the depth impact analysis result. The specific process is as follows;

[0080] In sub-step S202, based on the material influence information, the depth change of drilling is considered, the influence of various depths on torque demand is analyzed, and the torque data of drilling at different depths is collected. The depth and material hardness information are used as independent variables, and the torque is used as the dependent variable to construct a torque demand model. Linear regression analysis is applied, and the formula is: ,in, is the torque requirement, is the drilling depth, is the material hardness, is the intercept, representing the torque demand at zero depth and base hardness, and are the influence coefficients of depth and hardness, As the error term, a torque demand variation model is constructed to generate deep impact analysis results.

[0081] S203: Based on the depth impact analysis result, the torque adjustment parameters required for various materials and differentiated drilling depths are calculated and adjusted to optimize the drilling efficiency. The specific process of generating the torque adjustment parameters is as follows;

[0082] In sub-step S203, based on the depth impact analysis results, the torque adjustment parameters required for various materials and differentiated drilling depths are calculated and adjusted. The torque adjustment parameters are set as a set of weight coefficients using a linear regression model. The coefficients are adjusted through an optimization algorithm to maximize drilling efficiency. The formula is: ,in, is the adjusted torque, To predict the torque, is the adjusted baseline value, To adjust the coefficient, it is dynamically adjusted according to the actual drilling efficiency feedback, the drilling efficiency is optimized, and the torque adjustment parameters are generated.

[0083] See also Figure 4 Based on the torque adjustment parameters, the vibration sensor is used to collect and analyze the vibration data of the electric drill in real time during operation, and the vibration change mode of the electric drill under various speeds and torques is evaluated. The specific steps for generating the vibration mode analysis results are as follows:

[0084] S301: Based on the torque adjustment parameter, the vibration data of the electric drill during operation is collected in real time through the vibration sensor, and the vibration characteristics under various speed and torque configurations are recorded. The specific process of generating the operation vibration data is as follows;

[0085] In sub-step S301, based on the torque adjustment parameters, the vibration data of the electric drill during operation is collected in real time through a vibration sensor, including configuring different speed and torque settings of the electric drill, and using the vibration sensor to record the vibration characteristics under each configuration, and comparing the sensor data with the torque adjustment parameters of the electric drill. To associate, mark the torque and speed values ​​corresponding to each data point when collecting data, and use the data collection formula: ,in, Represents vibration data, is the rotation speed, is the adjusted torque, represents the baseline vibration level, is the influence coefficient of speed on vibration, It is the influence coefficient of torque on vibration, generating operating vibration data.

[0086] S302: Based on the running vibration data, frequency analysis is performed on the vibration data under various speeds and torques, and the vibration frequencies and vibration amplitudes of various speed and torque combinations are identified to generate the key vibration modes. Specifically, the process is as follows;

[0087] In sub-step S302, based on the running vibration data, frequency analysis is performed on the vibration data at various speeds and torques, including using Fourier transform to analyze the frequency components of the vibration data. It will be converted into the form of frequency and amplitude in order to identify the vibration frequency and amplitude under various speed and torque combinations. The frequency analysis formula applied is: ,in, represents the vibration frequency, is the baseline frequency, It is the coefficient of logarithmic transformation of vibration data, which is used to map vibration data into frequency domain and generate key vibration mode information.

[0088] S303: Based on the key vibration modes, the influence of various vibration modes on the drilling of the electric drill is evaluated, including the drilling efficiency and the stability of the equipment, and the process of generating the vibration mode analysis result is specifically as follows;

[0089] In sub-step S303, based on the key vibration modes, the effects of various vibration modes on electric drill drilling, including drilling efficiency and equipment stability, are evaluated. The drilling efficiency and equipment stability are predicted based on the vibration amplitude data. The formula is: ,in, represents the drilling efficiency, is the key vibration frequency, is the vibration amplitude, is the baseline efficiency level, is the influence coefficient of frequency on efficiency, The influence coefficient of amplitude on efficiency is used to analyze the influence of vibration mode on the performance of the electric drill and generate vibration mode analysis results.

[0090] See also Figure 5 According to the vibration mode analysis results, the operating parameters of the electric drill are adjusted to optimize the vibration of the electric drill. The parameters are iteratively optimized in combination with real-time vibration information. The specific steps to generate the work configuration optimization record are as follows:

[0091] S401: Based on the vibration mode analysis results, the process of analyzing the influence of the torque, speed and propulsion force settings of the electric drill on the vibration, identifying key influencing parameters, and generating vibration cause analysis data is as follows;

[0092] In sub-step S401, based on the vibration mode analysis results, the torque, speed and propulsion settings of the electric drill are analyzed to identify the influence of various parameters on the vibration performance, including establishing a regression model between the vibration level and each parameter, using the regression analysis formula: ,in, is the vibration level, is the coefficient of torque influence on vibration, is the coefficient of the influence of speed on vibration, is the coefficient of the propulsion force on vibration, represents torque, represents the rotation speed, Representing the propulsion force, by calculating the influence of each parameter, the key influencing parameters of vibration are determined and vibration cause analysis data is generated.

[0093] S402: Based on the vibration cause analysis data, the torque, speed and propulsion force parameters of the electric drill are adjusted to optimize the vibration performance, and the adjusted vibration data is recorded. The process of generating parameter adjustment test results is specifically as follows;

[0094] In sub-step S402, based on the vibration cause analysis data, the torque, speed and propulsion force of the electric drill are adjusted to optimize the vibration performance. The formula is: ,in, is the adjusted vibration level, is the torque adjustment factor, is the speed adjustment factor, is the propulsion adjustment coefficient, is the vibration attenuation factor, represents torque, represents the rotation speed, Represents propulsion, Represent the environmental noise and vibration levels, record the adjusted vibration data, analyze the adjustment effect, verify the optimization effect and provide data support for iterative optimization, and generate parameter adjustment test results.

[0095] S403: Based on the parameter adjustment test results, combined with the real-time vibration monitoring data, iteratively optimize the operating parameters of the electric drill, optimize the vibration performance and drilling efficiency, and generate the work configuration optimization record. The specific process is as follows;

[0096] In sub-step S403, based on the parameter adjustment test results and combined with the real-time vibration monitoring data, the operating parameters of the electric drill are iteratively optimized, and the parameter iterative optimization formula is: ,in, For the optimized parameter configuration, is the expected vibration level, is the current vibration level, To adjust the reaction coefficient, is the parameter preservation factor, Set the original parameters, adjust and optimize the operating parameters of the electric drill, and generate work configuration optimization records.

[0097] See also Figure 6 Based on the work configuration optimization record, by analyzing the operation time and working mode of the electric drill and combining the type of drill bit, the remaining life of the drill bit is evaluated and predicted. The steps for generating drill bit life prediction information are as follows:

[0098] S501: Based on the work configuration optimization record, collect and analyze the data of the electric drill operation time and work mode, evaluate the operation efficiency under various drill types, and generate the drill type operation data. The specific process is as follows;

[0099] In sub-step S501, based on the work configuration optimization record, the data of the electric drill operation time and the working mode are collected to evaluate the operation efficiency of various drill types under different working modes. By measuring the operation time of each drill under various load and speed settings and recording the corresponding work efficiency, the operation efficiency of the drill is calculated and compared. The formula is: ,in, Indicates the operating efficiency of the drill bit, Indicates the running time, represents the efficiency coefficient of the working mode, Indicates the number of data points collected to evaluate and compare the performance of different drill bit types and generate drill bit type operating data.

[0100] S502: Based on the drill bit type operation data, the wear rate and efficiency of various types of drill bits are analyzed, the performance of the drill bits under differentiated working modes is evaluated, and the process of generating the drill bit performance evaluation result is specifically as follows;

[0101] In sub-step S502, based on the drill bit type operation data, the wear rate and efficiency of various drill bits are analyzed, including recording the wear amount and usage time of each drill bit under different operating conditions, evaluating the performance of the drill bit in different working modes, and quantitatively analyzing the wear rate. The formula is: ,in, Indicates the wear rate, represents the amount of wear during the observation period, Indicates the cumulative usage time of the drill bit and generates the drill bit performance evaluation result.

[0102] S503: Based on the drill bit performance evaluation results, combined with the use time and operation intensity, the wear trends of multiple drill bits are analyzed and the remaining life is predicted. The specific process of generating drill bit life prediction information is as follows;

[0103] In sub-step S503, based on the drill performance evaluation results, combined with the data of usage time and operation intensity, the wear trends of multiple drill bits are analyzed to predict the remaining life. By analyzing the known wear rate and current wear state, the remaining service life of each drill bit is predicted. The formula is: ,in, Remaining life, Indicates the initial wear state of the drill bit. Indicates the current wear status, Indicates the calculated wear rate, and predicts the life of the drill bit through actual usage data and performance history to generate drill life prediction information.

[0104] See also Figure 7 Based on the drill life prediction information, the current, voltage and temperature data in operation are collected in real time, the motor operation efficiency is analyzed and the downward trend is evaluated, and the compensation parameters are calculated. The specific steps for generating the electric drill operation compensation parameters are as follows:

[0105] S601: Based on the drill life prediction information, the current, voltage and temperature of the electric drill are monitored in real time, key operating parameters are recorded, and the specific process of generating motor monitoring data is as follows;

[0106] In sub-step S601, based on the drill life prediction information, the real-time monitoring of the electric drill is implemented, including the measurement of current, voltage and temperature, using sensors to regularly record key operating parameters, and collating and storing information through a data acquisition system to evaluate the stability of key parameters. The formula is: ,in, Indicates comprehensive monitoring parameters, are the weight coefficients of current, voltage and temperature respectively, Indicates the current value, Indicates the voltage value, Indicates temperature, tracks the operating status of the electric drill in real time, and generates motor monitoring data.

[0107] S602: Based on the motor monitoring data, the motor efficiency is analyzed, key factors affecting the efficiency reduction are identified, the motor performance change is evaluated, and the specific process of generating the motor operation efficiency data is as follows;

[0108] In sub-step S602, based on the motor monitoring data, the motor efficiency is analyzed and the key factors leading to the decline in efficiency are identified, including comparing the relationship between the operating parameters and the efficiency at different time points, and performing efficiency analysis. The formula is: ,in, represents the motor efficiency, is the power generated by the motor, Indicates the energy consumed by the motor. By analyzing the current, voltage and temperature data, the changes in motor performance are evaluated and the motor operating efficiency data is generated.

[0109] S603: Based on the motor operation efficiency data, the fuzzy logic control algorithm is used to calculate the motor operation compensation parameters that need to be adjusted, optimize the motor operation efficiency, and generate the electric drill operation compensation parameters. The specific process is as follows;

[0110] In sub-step S603, based on the motor operating efficiency data, a fuzzy logic control algorithm is used to calculate the motor operating compensation parameters that need to be adjusted, the fuzzy set of the input data is processed, and the optimal adjustment strategy is determined. By adjusting the input parameters of the motor, including current and voltage, the operating efficiency of the motor is optimized to ensure that the electric drill maintains optimal performance under differentiated working conditions, and the electric drill operating compensation parameters are generated.

[0111] Fuzzy logic control algorithm, according to the formula:

[0112]

[0113] Calculate the adjusted motor operating parameters, where: is the adjusted motor operating parameter, which is used to represent the output of the motor control system. is the proportional gain, which is used to adjust the influence of the error signal. is the error signal, which is used to measure the deviation between the current state and the target state. is the integral time, which is used to adjust the influence of integral control. It represents the integral of the error signal over time and is used for integral control to provide the accumulated deviation value. is the differential time, which is used to adjust the sensitivity of the differential control. Indicates the rate of change of the error signal, which is used for differential control to provide instant deviation change speed. is the weight coefficient of ambient temperature, is the ambient temperature, an external factor that affects the motor's operating status. is the weight coefficient of the load change rate, is the load change rate, which indicates the speed of change of the motor load. is the weight coefficient of the vibration level, The vibration level is a measure of the intensity of vibration generated when the electric drill is operated. is the weight coefficient of the motor life prediction value, is the motor life prediction value, which is used to predict the remaining effective working time of the motor. A small time interval used to represent time increments in integral and differential calculations in mathematics. is the error signal The small changes in the error signal are used to calculate the rate of change of the error signal.

[0114] The specific execution process of the formula is as follows:

[0115] The sensors installed on the electric drill monitor and record the motor current, voltage and ambient temperature in real time. , Load change rate , vibration level , and motor life prediction value , using fuzzy logic algorithm to process the error signal , dynamically evaluate the error through integration and differentiation calculation, combine the weight coefficients of various parameters, and calculate the integral Handling past accumulated errors, differentials Respond to the instantaneous change speed of the error and output the adjusted operating parameters , optimize motor performance, cope with changing operating conditions and environmental factors, and ensure the efficiency and safety of electric drill operation.

[0116] See also Figure 8 The electric drill control system is used to execute the electric drill control method. The electric drill control system includes:

[0117] The operation data acquisition module collects the voltage and current data of the electric drill when it is running based on the real-time electric drill operation data. It combines the torque and speed sensors to analyze the torque and speed of the electric drill under various power states and generates the electric drill operation data.

[0118] The torque relationship analysis module is based on the electric drill operation data and considers the material hardness information to analyze and adjust the torque requirements of the electric drill at various drilling depths, optimize the drilling efficiency, and generate drilling torque configuration parameters;

[0119] The operating vibration control module monitors the vibration condition of the electric drill in real time based on the drilling torque configuration parameters, analyzes the vibration change mode under various speeds and torques, adjusts the operating parameters to optimize the vibration performance, and generates the vibration optimization configuration;

[0120] Use the information analysis module to evaluate the impact of the drill operation time and mode on the drill bit life based on the vibration optimization configuration, and predict the drill bit life based on the drill bit type to generate drill bit replacement prompt information;

[0121] The parameter compensation calculation module collects the current, voltage and temperature data of the electric drill in real time based on the drill bit replacement prompt information, calculates the compensation parameters to optimize the motor operating efficiency by analyzing the motor operating efficiency, and generates the electric drill operating compensation parameters.

[0122] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. An electric drill control method, characterized in that: The following steps are involved: Based on the real-time electric drill operation data, the voltage and current data of the electric drill operation are collected. Combined with the torque and speed sensors, the torque and speed of the electric drill under various power inputs are recorded and the relationship is analyzed to generate a speed torque output model. The specific steps are as follows: Based on the real-time electric drill operation data, the voltage and current data of the electric drill during operation are collected, the power information of the electric drill under various operation modes is analyzed, and the operation power information is generated; Based on the operating power information, using torque and speed sensors, real-time monitoring of the torque and speed data of the electric drill under various operating powers is performed to generate power response data; Based on the power response data, the relationship between torque, speed and input power is analyzed, the influence of power change on the operating efficiency of the electric drill is analyzed, and a speed torque output model is generated; Based on the speed torque output model, considering the hardness information of the material type, the drilling efficiency of the electric drill with differentiated torque at various drilling depths is analyzed, the torque is adjusted to match the changes in the material and drilling depth, and the torque adjustment parameter is generated. The specific steps are as follows: Based on the speed torque output model, the drilling efficiency of the electric drill on materials with various hardnesses is analyzed, the requirements of the hardness of various materials on the electric drill torque are evaluated, and the material impact information is generated; Based on the material impact information, considering the depth change of the drilling hole, analyzing the impact of various depths on the torque demand, building a torque demand change model, and generating depth impact analysis results; Based on the depth impact analysis results, calculate and adjust torque adjustment parameters required for various materials and differentiated drilling depths, optimize drilling efficiency, and generate torque adjustment parameters; Based on the torque adjustment parameter, using a vibration sensor, real-time collection and analysis of vibration data during the operation of the electric drill, evaluation of vibration change modes of the electric drill under various speeds and torques, and generation of vibration mode analysis results; According to the vibration mode analysis result, the operating parameters of the electric drill are adjusted to optimize the vibration of the electric drill, and the parameters are iteratively optimized in combination with the real-time vibration information to generate the specific steps of the work configuration optimization record are as follows: Based on the vibration mode analysis results, analyzing the influence of the torque, speed and propulsion force settings of the electric drill on the vibration, identifying key influencing parameters, and generating vibration cause analysis data; Based on the vibration cause analysis data, adjusting the torque, speed and propulsion force parameters of the electric drill to optimize the vibration performance, and recording the adjusted vibration data to generate parameter adjustment test results; Based on the parameter adjustment test results, combined with real-time vibration monitoring data, iteratively optimize the operating parameters of the electric drill, optimize vibration performance and drilling efficiency, and generate a work configuration optimization record; Based on the work configuration optimization record, by analyzing the operation time and working mode of the electric drill and combining the type of drill bit, the remaining life of the drill bit is evaluated and predicted, and the specific steps of generating drill bit life prediction information are as follows: Based on the work configuration optimization record, collect and analyze the data of the electric drill operation time and working mode, evaluate the operation efficiency under various drill bit types, and generate drill bit type operation data; Based on the drill bit type operation data, the wear rate and efficiency of various types of drill bits are analyzed, the performance of the drill bits under differentiated working modes is evaluated, and a drill bit performance evaluation result is generated; Based on the drill bit performance evaluation results, combined with usage time and operation intensity, the wear trends of multiple drill bits are analyzed and the remaining life is predicted to generate drill bit life prediction information; Based on the drill life prediction information, the current, voltage and temperature data in operation are collected in real time, the motor operation efficiency is analyzed and the downward trend is evaluated, and the compensation parameters are calculated. The specific steps of generating the electric drill operation compensation parameters are as follows: Based on the drill life prediction information, the current, voltage and temperature of the electric drill are monitored in real time, key operating parameters are recorded, and motor monitoring data is generated; Based on the motor monitoring data, analyze the motor efficiency, identify key factors affecting the efficiency decline, evaluate the motor performance changes, and generate motor operation efficiency data; Based on the motor operation efficiency data, a fuzzy logic control algorithm is used to calculate the motor operation compensation parameters that need to be adjusted, optimize the motor operation efficiency, and generate the electric drill operation compensation parameters; The fuzzy logic control algorithm is based on the formula: Calculate the adjusted motor operating parameters, where: are the motor operating parameters after adjustment. is the proportional gain, is the error signal, is the integration time, represents the integral of the error signal over time, is the differential time, represents the rate of change of the error signal, is the weight coefficient of ambient temperature, is the ambient temperature, is the weight coefficient of the load change rate, is the load change rate, is the weight coefficient of the vibration level, is the vibration level, is the weight coefficient of the motor life prediction value, is the predicted value of motor life, For small time intervals, is the error signal Small changes in The speed-torque output model includes speed-torque correlation data, electric drill power input data, and electric drill operation efficiency evaluation data; the torque adjustment parameters include material hardness impact analysis results, drilling efficiency data, and torque output adjustment parameters; the vibration mode analysis results include vibration frequency data, vibration amplitude analysis results, and information on the impact of vibration on drilling quality; the work configuration optimization record includes operation parameter adjustment results, vibration suppression effect evaluation information, and configuration change history records; the drill bit life prediction information includes drill bit usage statistics, estimated wear speed, and remaining effective working time; the electric drill operation compensation parameters include current and voltage adjustment parameters, temperature impact compensation parameters, and efficiency decline trend information.

2. Electric drill control system, characterized in that: The electric drill control system is used to execute the electric drill control method according to claim 1, and the electric drill control system comprises: The operation data acquisition module collects the voltage and current data of the electric drill when it is running based on the real-time electric drill operation data. It combines the torque and speed sensors to analyze the torque and speed of the electric drill under various power states and generates the electric drill operation data. The torque relationship analysis module analyzes and adjusts the torque requirements of the electric drill at various drilling depths based on the electric drill operation data and takes into account the material hardness information, optimizes the drilling efficiency, and generates drilling torque configuration parameters; The operation vibration control module monitors the vibration condition of the electric drill in real time based on the drilling torque configuration parameters, analyzes the vibration change mode under various speeds and torques, adjusts the operation parameters to optimize the vibration performance, and generates a vibration optimization configuration; Using the information analysis module, based on the vibration optimization configuration, evaluates the impact of the electric drill operation time and mode on the drill bit life, combines the drill bit type, predicts the drill bit life, and generates drill bit replacement prompt information; The parameter compensation calculation module collects the current, voltage and temperature data of the electric drill in real time based on the drill bit replacement prompt information, calculates the compensation parameters to optimize the motor operation efficiency by analyzing the motor operation efficiency, and generates the electric drill operation compensation parameters.

3. A computer device comprising a memory and a processor, characterized in that: The memory stores a computer program, and the processor implements the electric drill control system of claim 2 when executing the computer program.

4. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the electric drill control method according to claim 1 are implemented.

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