Digital control method and system for underfloor wheel lathe

Abstract

The invention discloses a digital control method and system for an underfloor wheel lathe, and the method comprises the steps: collecting the working data of lathe equipment through a sensor and a data collector, and carrying out the archiving of the cutting data of a corresponding wheel in the lathe equipment, so as to obtain the parameter information of the wheel, analyzing the wheel parameter information according to a preset wheel cutting standard to obtain a wheel state data set, recording the working operation time of the lathe equipment and historical alarm data of the lathe equipment, and carrying out classified statistics on the historical alarm data to obtain historical fault statistical information after classified statistics; and an equipment health management model is constructed according to the wheel state data set, the working operation time and the historical fault statistical information, and the equipment health management model is used for performing fault prediction on the lathe equipment. Therefore, by implementing the method, the precision of production data of the lathe equipment in the digital control process and the control efficiency and accuracy of the lathe equipment can be improved, and faults of the lathe equipment can be checked in time.

Description

Technical Field

[0001] The present invention relates to the technical field of rail transit equipment manufacturing and maintenance, and in particular to a digital control method and system for an underfloor wheel lathe. Background Art

[0002] In the current rail transit equipment manufacturing and maintenance industry, wheelless lathe equipment (or: wheelless turning machine) is used to repair subway vehicle wheels. It can use CNC technology to perform high-precision turning and measurement of vehicle wheel pairs, while the wheel measurement and cutting data generated in the production process are generally recorded manually, or printed data reports are entered into the information system; secondly, equipment problems are generally discovered only after the equipment fails, and most of the failures need to be handled on-site, and the software program needs to be checked to troubleshoot the problem; most of the equipment's sensors are used for equipment control, and there are fewer sensors for equipment status monitoring, and there is no record information of the equipment status. Therefore, in the current digital control process of lathe equipment, there are problems such as low data accuracy, low equipment control efficiency and accuracy, and difficulty in timely troubleshooting and repairing equipment failures.

[0003] Therefore, a digital control method and system for an underfloor wheeled lathe is currently provided, which can improve the intelligence of the digital control of the underfloor wheeled lathe, thereby facilitating the improvement of the accuracy of production data of the lathe equipment during the digital control process, the control efficiency and accuracy of the lathe equipment, and the timely troubleshooting of faults occurring in the lathe equipment. Summary of the invention

[0004] The present invention provides a method and system for digital control of an underfloor wheel lathe, which can be beneficial to improving the accuracy of production data of the lathe equipment during the digital control process, the control efficiency and accuracy of the lathe equipment, and timely troubleshooting of faults occurring in the lathe equipment.

[0005] In order to solve the above technical problems, the first aspect of the present invention discloses a digital control method for an underfloor wheel lathe, the method comprising:

[0006] Collecting working data of the lathe equipment through sensors and data collectors, wherein the working data includes at least one of: operating status data, energy consumption data, and cutting data required to be measured for the corresponding wheel;

[0007] Archiving the cutting data of the corresponding wheel in the lathe equipment to obtain wheel parameter information, and analyzing the wheel parameter information according to a preset wheel cutting standard to obtain a wheel status data set;

[0008] Recording the working time of the lathe equipment and the historical alarm data of the lathe equipment in the past;

[0009] The historical alarm data is classified and counted to obtain historical fault statistical information after classification and statistics, and an equipment health management model is constructed based on the wheel status data set, the working running time and the historical fault statistical information. The equipment health management model is used to perform fault prediction and cutting data evaluation on the lathe equipment.

[0010] As an optional embodiment, in the first aspect of the present invention, the sensor includes: at least one of a temperature sensor, a liquid level sensor, a pressure sensor, a current and voltage sensor, and a displacement sensor; the operating status data includes: at least one of position data, current data, voltage data, and load data of multiple components corresponding to the lathe equipment; the cutting data includes: at least one of wear data, cutting load data, cutting size data, cutting position data, and component pressure data.

[0011] As an optional implementation, in the first aspect of the present invention, archiving the cutting data corresponding to the wheel in the lathe device to obtain wheel parameter information includes:

[0012] Performing preprocessing operations of data cleaning, data filtering, and data normalization on the cutting data corresponding to the wheel in the lathe equipment to obtain processed cutting data;

[0013] Archiving the processed cutting data to obtain wheel parameter information, the wheel parameter information includes: wear degree information, cutting load information, cutting size information, cutting position information, and component pressure information of the corresponding wheel, and the wheel status data includes: wheel status data before processing and wheel status data after processing;

[0014] The step of analyzing the wheel parameter information according to a preset wheel cutting standard to obtain a wheel status data set includes:

[0015] Analyzing the wear degree information of the wheel according to a preset wheel cutting standard to obtain wheel status data before processing;

[0016] The cutting load information, cutting size information, cutting position information and component pressure information of the wheel are analyzed according to a preset wheel cutting standard to obtain the wheel status data after processing.

[0017] As an optional embodiment, in the first aspect of the present invention, the method further comprises:

[0018] Recording the historical operation status data of the lathe equipment and the historical wheel status data after each wheel is processed, analyzing the historical operation status data and the historical wheel status data to obtain the cutting accuracy corresponding to each wheel in the past;

[0019] A precision relationship model between historical operating status data, historical wheel status data and cutting accuracy is constructed, and the cutting accuracy and cutting data corresponding to the wheels to be processed subsequently are optimized according to the precision relationship model.

[0020] As an optional implementation manner, in the first aspect of the present invention, the classifying and counting the historical alarm data to obtain the classified and counted historical fault statistical information includes:

[0021] Classify and count the historical alarm data according to preset time periods and preset alarm types to obtain historical fault statistical information corresponding to multiple alarm types in each preset time period;

[0022] Among them, the preset alarm types include: functional alarm type and fault alarm type. The functional types include: hydraulic unit alarm, lubrication unit alarm, servo system alarm, spindle system alarm. The fault types include: prompt alarm, main system fault alarm, auxiliary system fault alarm, and position pressure detection alarm.

[0023] As an optional implementation, in the first aspect of the present invention, after constructing the equipment health management model according to the wheel status data set, the working running time and the historical fault statistical information, the method further includes:

[0024] Collecting real-time operating status data of multiple components corresponding to the lathe equipment within a preset time period, performing preprocessing operations on the real-time operating status data, and obtaining a processed operating status data test set;

[0025] Inputting the operating status data test set into the equipment health management model for prediction calculation, and finally predicting the remaining service life of the lathe equipment and the corresponding probability of occurrence of each fault type;

[0026] Wherein, the real-time operation status data includes at least one of current data, voltage data, temperature data, pressure data, and load data.

[0027] As an optional embodiment, in the first aspect of the present invention, the method further comprises:

[0028] Establishing a communication link with the lathe equipment through a wireless network, and remotely monitoring the operating status data, energy consumption data and historical alarm data of the lathe equipment through the communication link, and determining whether abnormal data appears in the operating status data and / or energy consumption data, or whether new alarm data is added to the historical alarm data;

[0029] When it is determined that abnormal data appears in the operating status data and / or the energy consumption data, or when new alarm data is added to the historical alarm data, relevant control operations are performed on the lathe equipment through the communication link;

[0030] Wherein, the control operation includes: performing a fault detection operation, a fault troubleshooting operation and a fault repair operation on the lathe equipment according to the abnormal data and the newly added alarm data.

[0031] The second aspect of the present invention discloses a digital control system for an underfloor wheel lathe, the system comprising:

[0032] A collection module, used to collect working data of the lathe equipment through sensors and data collectors, wherein the working data includes at least one of: operating status data, energy consumption data, and cutting data required to be measured for the corresponding wheel;

[0033] An archiving module, used for archiving the cutting data of the corresponding wheel in the lathe equipment collected by the collecting module to obtain wheel parameter information;

[0034] An analysis module, configured to analyze the wheel parameter information archived by the archiving module according to a preset wheel cutting standard to obtain a wheel status data set;

[0035] A recording module, used to record the working operation time of the lathe equipment and the historical alarm data of the lathe equipment in the past;

[0036] A classification and statistics module, used for classifying and counting the historical alarm data recorded by the recording module to obtain historical fault statistics information after classification and statistics;

[0037] A construction module is used to construct an equipment health management model based on the wheel status data set obtained by the analysis module, the working operation time obtained by the recording module, and the historical fault statistical information obtained by the classification and statistics module. The equipment health management model is used to perform fault prediction and cutting data evaluation on the equipment.

[0038] As an optional embodiment, in the second aspect of the present invention, the sensor includes: at least one of a temperature sensor, a liquid level sensor, a pressure sensor, a current and voltage sensor, and a displacement sensor; the operating status data includes: at least one of position data, current data, voltage data, and load data of multiple components corresponding to the lathe equipment; the cutting data includes: at least one of wear data, cutting load data, cutting size data, cutting position data, and component pressure data.

[0039] As an optional implementation, in the second aspect of the present invention, the archiving module archives the cutting data corresponding to the wheel in the lathe equipment, and the specific method of obtaining the wheel parameter information is:

[0040] Performing preprocessing operations of data cleaning, data filtering, and data normalization on the cutting data corresponding to the wheel in the lathe equipment to obtain processed cutting data;

[0041] Archiving the processed cutting data to obtain wheel parameter information, the wheel parameter information includes: wear degree information, cutting load information, cutting size information, cutting position information, and component pressure information of the corresponding wheel, and the wheel status data includes: wheel status data before processing and wheel status data after processing;

[0042] The specific method in which the analysis module analyzes the wheel parameter information according to the preset wheel cutting standard to obtain the wheel status data set is:

[0043] Analyzing the wear degree information of the wheel according to a preset wheel cutting standard to obtain wheel status data before processing;

[0044] The cutting load information, cutting size information, cutting position information and component pressure information of the wheel are analyzed according to a preset wheel cutting standard to obtain the wheel status data after processing.

[0045] As an optional implementation, in the second aspect of the present invention, the recording module is further used to record the historical operation status data of the lathe equipment and the historical wheel status data after each wheel is processed;

[0046] The analysis module is further used to analyze the historical operation status data and the historical wheel status data recorded by the recording module to obtain the cutting accuracy corresponding to each wheel in the past;

[0047] The construction module is further used to construct a precision relationship model between the historical operating status data and historical wheel status data recorded by the recording module and the cutting precision analyzed by the analysis module;

[0048] The system further comprises:

[0049] The optimization module is used to optimize the cutting accuracy and cutting data corresponding to the wheels to be processed subsequently according to the accuracy relationship model constructed by the construction module.

[0050] As an optional implementation, in the second aspect of the present invention, the classification and statistics module performs classification and statistics on the historical alarm data, and obtains the historical fault statistical information after classification and statistics in a specific manner as follows:

[0051] Classify and count the historical alarm data according to preset time periods and preset alarm types to obtain historical fault statistical information corresponding to multiple alarm types in each preset time period;

[0052] Among them, the preset alarm types include: functional alarm type and fault alarm type. The functional types include: hydraulic unit alarm, lubrication unit alarm, servo system alarm, spindle system alarm. The fault types include: prompt alarm, main system fault alarm, auxiliary system fault alarm, and position pressure detection alarm.

[0053] As an optional implementation, in the second aspect of the present invention, the system further includes:

[0054] The acquisition module is further used to collect real-time operation status data of multiple components corresponding to the lathe equipment within a preset time period after the construction module constructs the equipment health management model according to the wheel status data set, the working operation time and the historical fault statistical information;

[0055] A preprocessing module, used for performing a preprocessing operation on the real-time running status data collected by the collecting module to obtain a processed running status data test set;

[0056] A calculation module, used for inputting the operating status data test set obtained by the preprocessing module into the equipment health management model for prediction calculation, and finally predicting the remaining service life of the lathe equipment and the corresponding probability of occurrence of each fault type;

[0057] Wherein, the real-time operation status data includes at least one of current data, voltage data, temperature data, pressure data, and load data.

[0058] As an optional implementation, in the second aspect of the present invention, the system further includes:

[0059] The construction module is also used to establish a communication link with the lathe equipment via a wireless network;

[0060] A monitoring module, used for remotely monitoring the operation status data, energy consumption data and historical alarm data of the lathe equipment through the communication link constructed by the construction module;

[0061] A judgment module, used to judge whether the operating status data and / or energy consumption data monitored by the monitoring module have abnormal data, or whether the historical alarm data have new alarm data;

[0062] A control module, configured to perform relevant control operations on the lathe equipment through the communication link when the judgment module judges that abnormal data appears in the operating status data and / or the energy consumption data, or new alarm data is added to the historical alarm data;

[0063] Wherein, the control operation includes: performing a fault detection operation, a fault troubleshooting operation and a fault repair operation on the lathe equipment according to the abnormal data and the newly added alarm data.

[0064] The third aspect of the present invention discloses another digital control system for an underfloor wheel lathe, the system comprising:

[0065] A memory storing executable program code;

[0066] a processor coupled to the memory;

[0067] The processor calls the executable program code stored in the memory to execute the digital control method for the underfloor wheels lathe disclosed in the first aspect of the present invention.

[0068] The fourth aspect of the present invention discloses a computer storage medium, wherein the computer storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the digital control method of the underfloor wheeled lathe disclosed in the first aspect of the present invention.

[0069] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0070] The present invention provides a digital control method and system for a wheelless lathe, the method comprising: collecting operating status data, energy consumption data, and cutting data required to be measured for a corresponding wheel of a lathe equipment through a sensor and a data collector, archiving and processing the cutting data of the corresponding wheel in the lathe equipment to obtain wheel parameter information, which can improve the accuracy and consistency of the cutting data; analyzing the wheel parameter information according to a preset wheel cutting standard to obtain a wheel status data set, which can optimize the cutting efficiency and cutting accuracy through analysis, optimize the equipment workflow, and try to eliminate operational errors and failures caused by human participation; recording the working operation time of the lathe equipment and the historical alarm data of the lathe equipment in the past, classifying and counting the historical alarm data, obtaining historical fault statistical information after classification and statistics, and constructing an equipment health management model based on the wheel status data set, the working operation time and the historical fault statistical information, the equipment health management model is used to perform fault prediction and cutting data evaluation on the lathe equipment, which can reduce equipment maintenance costs, reduce equipment failure rates, discover problems in advance, solve equipment failure points in advance, and improve equipment efficiency. It can be seen that the implementation of the present invention can improve the intelligence of the digital control of the underfloor wheel lathe, which is beneficial to improving the accuracy of the production data of the lathe equipment during the digital control process, the control efficiency and accuracy of the lathe equipment, and timely troubleshooting of faults occurring in the lathe equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0072] Figure 1 It is a flow chart of a digital control method of an underfloor wheel lathe disclosed in an embodiment of the present invention;

[0073] Figure 2 It is a flow chart of another digital control method of an underfloor wheel lathe disclosed in an embodiment of the present invention;

[0074] Figure 3 It is a structural schematic diagram of a digital control system of an underfloor wheel lathe disclosed in an embodiment of the present invention;

[0075] Figure 4 It is a structural schematic diagram of another digital control system of an underfloor wheel lathe disclosed in an embodiment of the present invention;

[0076] Figure 5 It is a structural schematic diagram of another digital control system of an underfloor wheel lathe disclosed in an embodiment of the present invention;

[0077] Figure 6 It is a structural schematic diagram of another digital control system of an underfloor wheel lathe disclosed in an embodiment of the present invention;

[0078] Figure 7 It is a schematic diagram of an equipment control interface of a digital control system of another underfloor wheeled lathe disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0079] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings 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.

[0080] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or terminal including a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units inherent to these processes, methods, products or terminals.

[0081] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0082] The present invention discloses a digital control method and system for a wheelless lathe. The method and system can collect operating status data, energy consumption data, and cutting data required to be measured for corresponding wheels of the lathe equipment through sensors and data collectors, archive and process the cutting data of corresponding wheels in the lathe equipment, and obtain wheel parameter information, which can improve the accuracy and consistency of the cutting data; analyze the wheel parameter information according to a preset wheel cutting standard to obtain a wheel status data set, and optimize the cutting efficiency and cutting accuracy through analysis, optimize the equipment workflow, and try to eliminate operational errors and failures caused by human participation; record the working operation time of the lathe equipment and the historical alarm data of the lathe equipment in the past, classify and count the historical alarm data, and obtain the classified and counted historical fault statistical information; and construct an equipment health management model based on the wheel status data set, the working operation time, and the historical fault statistical information. The equipment health management model is used to perform fault prediction and cutting data evaluation on the lathe equipment, which can reduce the equipment maintenance cost, reduce the equipment failure rate, discover problems in advance, solve equipment failure points in advance, and improve equipment efficiency. It can be seen that the implementation of the present invention can improve the intelligence of the digital control of the underfloor wheel lathe, thereby facilitating the improvement of the precision of the production data of the lathe equipment during the digital control process, the control efficiency and accuracy of the lathe equipment, and timely troubleshooting of the lathe equipment. The following are detailed descriptions.

[0083] Embodiment 1

[0084] See also Figure 1 , Figure 1 1 is a flow chart of a digital control method for a wheeled lathe disclosed in an embodiment of the present invention. Figure 1 The described digital control method of a floor-mounted wheel lathe can be applied to a digital control system of a floor-mounted wheel lathe, and the system can be applied to floor-mounted wheel lathe equipment (or floor-mounted wheel turning machine equipment), which is not limited in the embodiments of the present invention. Optionally, the floor-mounted wheel lathe equipment (or floor-mounted wheel turning machine) is used to repair subway vehicle wheels, and it can perform high-precision turning, repairing and measuring of vehicle wheelsets through numerical control technology, which is not limited in the embodiments of the present invention. Figure 1 As shown, the digital control method of the underfloor wheel lathe may include the following operations:

[0085] 101. Collect the working data of lathe equipment through sensors and data collectors.

[0086] In the embodiment of the present invention, optionally, Figure 6 As shown, the system may include: a sensor module, a data acquisition module, a control system, an interface display module and multiple functional components. Figure 7 As shown, Figure 7The device control interface represented by the interface display module, the operating user can view the real-time status information of the device through the interface display module, and can also retrieve historical measurement data, cutting data, alarm data and other information. In addition, multiple functional components may include: hydraulic system, lubrication system, driving wheel module, external support module, side pressure wheel module, side pressure wheel support module, measurement module, down-pressing module, active track module, servo system module, spindle module, sensor may include: at least one of temperature sensor, liquid level sensor, pressure sensor, current voltage sensor, displacement sensor, etc., working data may include: at least one of running status data, energy consumption data, cutting data required to be measured for the corresponding wheel, etc., wherein the running status data includes: at least one of the position data, current data, voltage data, load data, etc. of multiple components corresponding to the lathe equipment, and the cutting data includes: at least one of wear data, cutting load data, cutting position data, component pressure data, etc., which is not limited in the embodiment of the present invention.

[0087] In the embodiment of the present invention, it is optional to increase the type and quantity of sensors based on the original traditional sensors such as oil temperature, liquid level, pressure, displacement, etc. For example, current detection sensors, smart meters, lubrication point pressure sensors, etc. can be added to the motor, and pressure sensors can also be added to key parts to obtain component status data.

[0088] In this way, by collecting a large amount of equipment status and operation data, it is possible to analyze and optimize equipment functions and cutting efficiency, cutting accuracy, optimize equipment workflow, and try to eliminate operational errors and failures caused by human participation, which is beneficial to improving the accuracy of lathe equipment's production data during the digital control process, and the control efficiency and accuracy of lathe equipment.

[0089] 102. Archiving and processing the cutting data of the corresponding wheel in the lathe equipment to obtain wheel parameter information, and analyzing the wheel parameter information according to the preset wheel cutting standard to obtain the wheel status data set.

[0090] In an embodiment of the present invention, archiving the cutting data corresponding to the wheel in the lathe equipment to obtain wheel parameter information may include:

[0091] The cutting data of the corresponding wheel in the lathe equipment is preprocessed by data cleaning, data filtering and data normalization to obtain the processed cutting data.

[0092] The processed cutting data is archived to obtain wheel parameter information.

[0093] Among them, the wheel parameter information includes: wear degree information, cutting load information, cutting size information, cutting position information, and component pressure information of the corresponding wheel, and the wheel status data includes: wheel status data before processing and wheel status data after processing.

[0094] In an embodiment of the present invention, analyzing wheel parameter information according to a preset wheel cutting standard to obtain a wheel status data set may include:

[0095] The wheel wear degree information is analyzed according to the preset wheel cutting standard to obtain the wheel status data before processing.

[0096] The wheel cutting load information, cutting size information, cutting position information and component pressure information are analyzed according to the preset wheel cutting standard to obtain the wheel status data after processing.

[0097] In this way, the cutting data of the corresponding wheels in the lathe equipment are archived to obtain the wheel parameter information, and the wheel parameter information is analyzed according to the preset wheel cutting standard to obtain the wheel status data set, which reduces the manual repeated data entry link, avoids data errors and inconsistencies caused by human factors, ensures the accuracy and reliability of the data, and is conducive to improving the accuracy of the production data of the lathe equipment in the digital control process, and the control efficiency and accuracy of the lathe equipment.

[0098] 103. Record the working operation time of the lathe equipment and the historical alarm data of the lathe equipment in the past, and classify and count the historical alarm data to obtain the historical fault statistical information after classification and statistics.

[0099] In the embodiment of the present invention, historical alarm data is classified and counted to obtain historical fault statistical information after classification and counting, which may include:

[0100] The historical alarm data is classified and counted according to the preset time period and the preset alarm type, so as to obtain the historical fault statistical information corresponding to multiple alarm types in each preset time period.

[0101] Among them, the preset alarm types may include: functional alarm type, fault alarm type, further, the functional type may include: hydraulic unit alarm, lubrication unit alarm, servo system alarm, spindle system alarm, the fault type may include: prompt alarm, main system fault alarm, auxiliary system fault alarm, position pressure detection alarm, etc., which is not limited to the embodiments of the present invention.

[0102] In this way, equipment failures can be classified and counted, the frequency of different types of failures can be counted, the possible failure points of the equipment can be analyzed, and an equipment failure analysis report can be formed. When problems occur, fault diagnosis, analysis and processing can be carried out quickly, which can minimize the downtime of equipment failures and thus improve the utilization efficiency of equipment.

[0103] 104. Build an equipment health management model based on the wheel status data set, working operation time and historical fault statistics.

[0104] In the embodiment of the present invention, the model algorithm used to construct the equipment health management model can be optionally included in one of a deep neural network model algorithm, a clustering algorithm, and an association analysis algorithm, which is not limited in the embodiment of the present invention. Among them, the equipment health management model can be used for fault prediction and cutting data evaluation of lathe equipment.

[0105] In this way, the risk of failure can be predicted through the equipment health management model, and maintenance can be performed before the equipment fails, avoiding the impact of sudden failures on production and reducing maintenance costs.

[0106] In an optional embodiment, after executing step 104, the method further includes the following operations:

[0107] Real-time operation status data of multiple components corresponding to the lathe equipment are collected within a preset time period, and preprocessing operations are performed on the real-time operation status data to obtain a processed operation status data test set.

[0108] The operating status data test set is input into the equipment health management model for predictive calculation, and finally the remaining service life of the lathe equipment and the corresponding probability of occurrence of each fault type are predicted.

[0109] In this optional embodiment, optionally, the real-time operating status data may include: at least one of current data, voltage data, temperature data, pressure data, load data, etc., which is not limited in the embodiment of the present invention.

[0110] It can be seen that this optional embodiment can perform predictive calculations in the equipment health management model, and ultimately predict the remaining service life of the lathe equipment and the corresponding probability of occurrence of each type of fault, thereby avoiding the impact of sudden failures on production and reducing maintenance costs, which is beneficial to improving the control efficiency and accuracy of the lathe equipment in the digital control process.

[0111] In another optional embodiment, after executing step 104, the method further includes the following operations:

[0112] A communication link is established with the lathe equipment through a wireless network, and the operating status data, energy consumption data and historical alarm data of the lathe equipment are remotely monitored through the communication link to determine whether abnormal data appears in the operating status data and / or energy consumption data, or whether new alarm data is added to the historical alarm data.

[0113] When it is determined that abnormal data appears in the operating status data and / or energy consumption data, or when new alarm data is added to the historical alarm data, relevant control operations are performed on the lathe equipment through the communication link.

[0114] In this optional embodiment, the control operation may optionally include: performing fault detection operations, fault troubleshooting operations and fault repair operations on the lathe equipment according to the abnormal data and the newly added alarm data.

[0115] It can be seen that this optional embodiment can remotely monitor the operating status data, energy consumption data and historical alarm data of the lathe equipment through a communication link before the equipment failure occurs, and maintain the abnormal data in the operating status data and / or energy consumption data and new equipment failures. Equipment failures can be discovered and handled in a timely manner without going to the site, thereby shortening downtime, reducing maintenance costs, improving equipment reliability and stability, and enhancing production continuity.

[0116] Embodiment 2

[0117] See also Figure 2 , Figure 2 1 is a flow chart of a digital control method for a wheeled lathe disclosed in an embodiment of the present invention. Figure 2 The described digital control method of a floor-mounted wheel lathe can be applied to a digital control system of a floor-mounted wheel lathe, and the system can be applied to floor-mounted wheel lathe equipment (or floor-mounted wheel turning machine equipment), which is not limited in the embodiments of the present invention. Optionally, the floor-mounted wheel lathe equipment (or floor-mounted wheel turning machine) is used to repair subway vehicle wheels, and it can perform high-precision turning, repairing and measuring of vehicle wheelsets through numerical control technology, which is not limited in the embodiments of the present invention. Figure 2 As shown, the digital control method of the underfloor wheel lathe may include the following operations:

[0118] 201. Collect working data of lathe equipment through sensors and data collectors. The working data includes: operating status data, energy consumption data, and cutting data required to be measured for the corresponding wheels.

[0119] 202. Archiving and processing the cutting data of the corresponding wheel in the lathe equipment to obtain wheel parameter information, and analyzing the wheel parameter information according to the preset wheel cutting standard to obtain the wheel status data set.

[0120] 203. Record the working operation time of the lathe equipment and the historical alarm data of the lathe equipment in the past, and classify and count the historical alarm data to obtain the historical fault statistical information after classification and statistics.

[0121] 204. Build an equipment health management model based on the wheel status data set, working operation time and historical fault statistics.

[0122] 205. Record the historical operation status data of the lathe equipment and the historical wheel status data after each wheel is processed, analyze the historical operation status data and the historical wheel status data, and obtain the cutting accuracy corresponding to each wheel in the past.

[0123] 206. Construct a precision relationship model between historical operating status data, historical wheel status data and cutting accuracy, and optimize the cutting accuracy and cutting data corresponding to the wheels to be processed subsequently according to the precision relationship model.

[0124] In an embodiment of the present invention, optionally, the model algorithm used to construct the accuracy relationship model between historical operating status data, historical wheel status data and cutting accuracy can be a clustering algorithm or an association analysis algorithm, and the accuracy relationship model can be a linear model or a nonlinear model, which is not limited in the embodiment of the present invention.

[0125] In the embodiment of the present invention, for other descriptions of step 201 to step 204, please refer to the detailed description of step 101 to step 104 in the first embodiment, and the embodiment of the present invention will not be repeated.

[0126] It can be seen that the implementation of the embodiment of the present invention can analyze the historical operating status data and the historical wheel status data, obtain the cutting accuracy corresponding to each wheel in the past, and construct an accuracy relationship model between the historical operating status data, the historical wheel status data and the cutting accuracy, and optimize the cutting accuracy and cutting data corresponding to the wheels that need to be processed subsequently according to the accuracy relationship model, which can improve the management capabilities of the measurement data and cutting data, as well as improve the accuracy and consistency of the data. Through a large amount of equipment status and operation data, the cutting efficiency, cutting accuracy and equipment workflow are analyzed and optimized, reducing operational errors and failures caused by human participation.

[0127] It can be seen that the implementation Figure 2The described digital control method for the wheelless lathe can collect the working data of the lathe equipment through sensors and data collectors, and the working data includes: at least one of operating status data, energy consumption data, and cutting data required to be measured for the corresponding wheel. The cutting data of the corresponding wheel in the lathe equipment is archived and processed to obtain wheel parameter information, which can improve the accuracy and consistency of the cutting data; the wheel parameter information is analyzed according to the preset wheel cutting standard to obtain the wheel status data set, which can optimize the cutting efficiency and cutting accuracy through analysis, optimize the equipment workflow, and try to eliminate operational errors and failures caused by human participation; the working operation time of the lathe equipment and the historical alarm data of the lathe equipment in the past are recorded, the historical alarm data are classified and counted, and the historical fault statistical information after classification and statistics is obtained, and based on Based on the wheel status data set, working operation time and historical fault statistics, an equipment health management model is constructed to reduce equipment maintenance costs, reduce equipment failure rates, discover problems in advance, solve equipment failure points in advance, and improve equipment efficiency; and historical operating status data and historical wheel status data can be analyzed to obtain the cutting accuracy corresponding to each wheel in the past, and a precision relationship model between historical operating status data, historical wheel status data and cutting accuracy can be constructed, and the cutting accuracy and cutting data corresponding to the wheels that need to be processed later can be optimized according to the precision relationship model, which can improve the management capabilities of measurement data and cutting data, as well as improve the accuracy and consistency of data, which is beneficial to improve the accuracy of production data, control efficiency and accuracy of lathe equipment in the digital control process.

[0128] Embodiment 3

[0129] See also Figure 3 , Figure 3 1 is a schematic diagram of a digital control system for a wheeled lathe disclosed in an embodiment of the present invention. Figure 3 The described digital control system of the underfloor wheel lathe can execute the digital control method of the underfloor wheel lathe, and the system can be applied to underfloor wheel lathe equipment (or: underfloor wheel turning machine equipment), which is not limited in the embodiments of the present invention. Optionally, the underfloor wheel lathe equipment (or: underfloor wheel turning machine) is used to repair the wheels of subway vehicles, and it can perform high-precision turning, repairing and measuring of vehicle wheelsets through numerical control technology, which is not limited in the embodiments of the present invention. Figure 3 As shown, the digital control system of the underfloor wheel lathe may include an acquisition module, an archiving module, an analysis module, a recording module, a classification and statistics module, and a construction module, wherein:

[0130] The acquisition module 301 is used to acquire the working data of the lathe equipment through sensors and data collectors. The working data includes: at least one of running status data, energy consumption data, and cutting data required to be measured for the corresponding wheel.

[0131] The archiving module 302 is used to archive the cutting data of the corresponding wheel in the lathe equipment collected by the collecting module 301 to obtain wheel parameter information.

[0132] The analysis module 303 is used to analyze the wheel parameter information archived by the archiving module 302 according to a preset wheel cutting standard to obtain a wheel status data set.

[0133] The recording module 304 is used to record the working operation time of the lathe equipment and the historical alarm data of the lathe equipment in the past.

[0134] The classification and statistics module 305 is used to perform classification and statistics on the historical alarm data recorded by the recording module 304 to obtain historical fault statistical information after classification and statistics.

[0135] The construction module 306 is used to construct an equipment health management model based on the wheel status data set analyzed by the analysis module 303, the working operation time recorded by the recording module 304, and the historical fault statistics information obtained by the classification statistics module 305. The equipment health management model is used to predict faults and evaluate cutting data of the equipment.

[0136] It can be seen that implementation Figure 3 The described digital control system of the wheelless lathe can collect the working data of the lathe equipment through sensors and data collectors. The working data includes: at least one of operating status data, energy consumption data, and cutting data required to be measured for the corresponding wheel. The cutting data of the corresponding wheel in the lathe equipment is archived and processed to obtain wheel parameter information, which can improve the accuracy and consistency of the cutting data; the wheel parameter information is analyzed according to the preset wheel cutting standard to obtain the wheel status data set, which can optimize the cutting efficiency and cutting accuracy through analysis, optimize the equipment workflow, and try to eliminate operational errors and failures caused by human participation; the working operation time of the lathe equipment and the historical alarm data of the lathe equipment in the past are recorded, the historical alarm data are classified and counted, and the historical fault statistical information after classification is obtained; and an equipment health management model is constructed based on the wheel status data set, the working operation time and the historical fault statistical information, which can reduce the equipment maintenance cost, reduce the equipment failure rate, discover problems in advance, solve equipment failure points in advance, and improve equipment efficiency. It can be seen that the implementation of the present invention can improve the intelligence of the digital control of the underfloor wheel lathe, which is beneficial to improving the accuracy of the production data of the lathe equipment during the digital control process, the control efficiency and accuracy of the lathe equipment, and timely troubleshooting of faults occurring in the lathe equipment.

[0137] In an optional embodiment, the sensor includes: at least one of a temperature sensor, a liquid level sensor, a pressure sensor, a current and voltage sensor, and a displacement sensor; the operating status data includes: at least one of position data, current data, voltage data, and load data of multiple components corresponding to the lathe equipment; the cutting data includes: at least one of wear data, cutting load data, cutting size data, cutting position data, and component pressure data.

[0138] It can be seen that the implementation Figure 4 The digital control system of the underfloor wheel lathe described can collect a large amount of equipment status and operation data, analyze and optimize equipment functions and cutting efficiency, thereby helping to improve the accuracy of production data, control efficiency and accuracy of the lathe equipment during the digital control process.

[0139] In another optional embodiment, Figure 4 As shown, the archiving module 302 archives the cutting data corresponding to the wheel in the lathe equipment, and the specific method of obtaining the wheel parameter information is as follows:

[0140] The cutting data of the corresponding wheel in the lathe equipment is preprocessed by data cleaning, data filtering, and data normalization to obtain the processed cutting data.

[0141] The processed cutting data is archived to obtain wheel parameter information, which includes: wear degree information of the corresponding wheel, cutting load information, cutting size information, cutting position information, and component pressure information. The wheel status data includes: wheel status data before processing and wheel status data after processing.

[0142] The specific method in which the analysis module 303 analyzes the wheel parameter information according to the preset wheel cutting standard and obtains the wheel status data set is as follows:

[0143] The wheel wear degree information is analyzed according to the preset wheel cutting standard to obtain the wheel status data before processing.

[0144] The wheel cutting load information, cutting size information, cutting position information and component pressure information are analyzed according to the preset wheel cutting standard to obtain the wheel status data after processing.

[0145] It can be seen that the implementation Figure 4The digital control system of the described wheelless lathe is capable of archiving the cutting data of the corresponding wheels in the lathe equipment to obtain wheel parameter information, and analyze the wheel parameter information according to the preset wheel cutting standard to obtain the wheel status data set, thereby reducing the manual repeated data entry process, avoiding data errors and inconsistencies caused by human factors, ensuring the accuracy and reliability of the data, and thus facilitating improving the accuracy of the production data of the lathe equipment during the digital control process, and the control efficiency and accuracy of the lathe equipment.

[0146] In yet another optional embodiment, Figure 4 As shown, the recording module 304 is also used to record the historical operation status data of the lathe equipment and the historical wheel status data after each wheel is processed.

[0147] The analysis module 303 is further used to analyze the historical operation status data and historical wheel status data recorded by the recording module 304 to obtain the cutting accuracy corresponding to each wheel in the past.

[0148] The construction module 306 is further used to construct a precision relationship model between the historical operating status data and historical wheel status data recorded by the recording module 304 and the cutting precision analyzed by the analysis module 303 .

[0149] The system also includes:

[0150] The optimization module 307 is used to optimize the cutting accuracy and cutting data corresponding to the wheels to be processed subsequently according to the accuracy relationship model constructed by the construction module 306.

[0151] It can be seen that implementation Figure 4 The digital control system of the described wheelless lathe can analyze the historical operating status data and the historical wheel status data to obtain the cutting accuracy corresponding to each wheel in the past, and construct an accuracy relationship model between the historical operating status data, the historical wheel status data and the cutting accuracy, and optimize the cutting accuracy and cutting data corresponding to the wheels to be processed subsequently according to the accuracy relationship model, which can improve the management capabilities of measurement data and cutting data, as well as improve the accuracy and consistency of the data. Through a large amount of equipment status and operation data, it can analyze and optimize the cutting efficiency, cutting accuracy and equipment workflow, and reduce operational errors and failures caused by human participation.

[0152] In yet another optional embodiment, Figure 4 As shown, the classification statistics module 305 performs classification statistics on the historical alarm data, and the specific method of obtaining the historical fault statistics information after classification statistics is:

[0153] The historical alarm data is classified and counted according to the preset time period and the preset alarm type, so as to obtain the historical fault statistical information corresponding to multiple alarm types in each preset time period.

[0154] Among them, the preset alarm types include: functional alarm type and fault alarm type. The functional types include: hydraulic unit alarm, lubrication unit alarm, servo system alarm, spindle system alarm. The fault types include: prompt alarm, main system fault alarm, auxiliary system fault alarm, and position pressure detection alarm.

[0155] It can be seen that implementation Figure 4 The digital control system of the underfloor wheel lathe described is capable of classifying and counting equipment failures, counting the frequency of occurrence of different types of failures, analyzing possible failure points of the equipment, and forming an equipment failure analysis report. When a problem occurs, the fault diagnosis, analysis and processing can be performed quickly, which can minimize the equipment failure downtime and thus improve the equipment utilization efficiency.

[0156] In yet another optional embodiment, Figure 4 As shown, the acquisition module 301 is also used to collect real-time operating status data of multiple components corresponding to the lathe equipment within a preset time period after the construction module 306 builds the equipment health management model according to the wheel status data set, working operation time and historical fault statistics information.

[0157] The system also includes:

[0158] The preprocessing module 308 is used to perform preprocessing operations on the real-time running status data collected by the collecting module 301 to obtain a processed running status data test set.

[0159] The calculation module 309 is used to input the operating status data test set processed by the preprocessing module 308 into the equipment health management model for predictive calculation, and finally predict the remaining service life of the lathe equipment and the corresponding probability of occurrence of each type of fault.

[0160] The real-time operation status data includes at least one of current data, voltage data, temperature data, pressure data and load data.

[0161] It can be seen that implementation Figure 4 The digital control system of the described wheelless lathe can perform predictive calculations through the equipment health management model, and ultimately predict the remaining service life of the lathe equipment and the corresponding probability of occurrence of each type of fault, thereby avoiding the impact of sudden failures on production and reducing maintenance costs, which is beneficial to improving the control efficiency and accuracy of the lathe equipment in the digital control process.

[0162] In yet another optional embodiment, the system further comprises:

[0163] The construction module 306 is further used to establish a communication link with the lathe equipment through a wireless network.

[0164] The monitoring module 310 is used to remotely monitor the operating status data, energy consumption data and historical alarm data of the lathe equipment through the communication link constructed by the construction module 306.

[0165] The judgment module 311 is used to judge whether abnormal data appears in the operation status data and / or energy consumption data monitored by the monitoring module 310, or whether new alarm data is added to the historical alarm data.

[0166] The control module 312 is used to perform relevant control operations on the lathe equipment through a communication link when the judgment module 311 judges that abnormal data appears in the operating status data and / or energy consumption data, or new alarm data is added to the historical alarm data.

[0167] Among them, the control operation includes: fault detection operation, fault troubleshooting operation and fault repair operation performed on the lathe equipment according to abnormal data and newly added alarm data.

[0168] It can be seen that implementation Figure 4 The described 145 can remotely monitor the operating status data, energy consumption data and historical alarm data of the lathe equipment through a communication link before an equipment failure occurs, and maintain abnormal data in the operating status data and / or energy consumption data and new equipment failures. Equipment failures can be discovered and handled in a timely manner without going to the site, thereby shortening downtime, reducing maintenance costs, improving equipment reliability and stability, and enhancing production continuity.

[0169] Embodiment 4

[0170] See also Figure 5 , Figure 5 FIG. 1 is a schematic diagram of the structure of a digital control system of another underfloor wheel lathe disclosed in an embodiment of the present invention. Figure 5 As shown, the digital control system of the underfloor wheel lathe may include:

[0171] A memory 401 storing executable program codes;

[0172] a processor 402 coupled to the memory 401;

[0173] The processor 402 calls the executable program code stored in the memory 401 to execute the steps in the digital control method of the underfloor wheeled lathe described in the first embodiment of the present invention or the second embodiment of the present invention.

[0174] Embodiment 5

[0175] An embodiment of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute the steps in the digital control method of the underfloor wheel lathe described in Embodiment 1 or Embodiment 2 of the present invention.

[0176] Embodiment 6

[0177] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps in the digital control method of a wheelless lathe described in Embodiment 1 or Embodiment 2.

[0178] The system embodiment described above is only illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, that is, they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without paying creative labor.

[0179] Through the specific description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the above technical solution can be essentially or partly contributed to the prior art in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0180] Finally, it should be noted that the digital control method and system for a wheelless lathe disclosed in the embodiment of the present invention only discloses the preferred embodiments of the present invention, which are only used to illustrate the technical solution of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, it should be understood by those skilled in the art that the technical solutions described in the aforementioned embodiments can still be modified, or some of the technical features therein can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A digital control method for an underfloor wheel lathe, characterized in that: The method comprises: Collecting working data of the lathe equipment through sensors and data collectors, wherein the working data includes at least one of: operating status data, energy consumption data, and cutting data required to be measured for the corresponding wheel; Archiving the cutting data of the corresponding wheel in the lathe equipment to obtain wheel parameter information, and analyzing the wheel parameter information according to a preset wheel cutting standard to obtain a wheel status data set; Recording the working time of the lathe equipment and the historical alarm data of the lathe equipment in the past; The historical alarm data is classified and counted to obtain historical fault statistical information after classification and statistics, and an equipment health management model is constructed based on the wheel status data set, the working running time and the historical fault statistical information. The equipment health management model is used to perform fault prediction and cutting data evaluation on the lathe equipment.

2. The digital control method of an underfloor wheel lathe according to claim 1, characterized in that: The sensor includes: at least one of a temperature sensor, a liquid level sensor, a pressure sensor, a current and voltage sensor, and a displacement sensor; the operating status data includes: at least one of position data, current data, voltage data, and load data of multiple components corresponding to the lathe equipment; the cutting data includes: wear data, cutting load data, cutting size data, cutting position data, and at least one of component pressure data.

3. The digital control method of an underfloor wheel lathe according to claim 2, characterized in that: The step of archiving the cutting data corresponding to the wheel in the lathe equipment to obtain wheel parameter information includes: Performing preprocessing operations of data cleaning, data filtering, and data normalization on the cutting data corresponding to the wheel in the lathe equipment to obtain processed cutting data; Archiving the processed cutting data to obtain wheel parameter information, the wheel parameter information includes: wear degree information, cutting load information, cutting size information, cutting position information, and component pressure information of the corresponding wheel, and the wheel status data includes: wheel status data before processing and wheel status data after processing; The step of analyzing the wheel parameter information according to a preset wheel cutting standard to obtain a wheel status data set includes: Analyzing the wear degree information of the wheel according to a preset wheel cutting standard to obtain wheel status data before processing; The cutting load information, cutting size information, cutting position information and component pressure information of the wheel are analyzed according to a preset wheel cutting standard to obtain the wheel status data after processing.

4. The digital control method for an underfloor wheel lathe according to claim 3, characterized in that: The method further comprises: Recording the historical operation status data of the lathe equipment and the historical wheel status data after each wheel is processed, analyzing the historical operation status data and the historical wheel status data to obtain the cutting accuracy corresponding to each wheel in the past; A precision relationship model between historical operating status data, historical wheel status data and cutting accuracy is constructed, and the cutting accuracy and cutting data corresponding to the wheels to be processed subsequently are optimized according to the precision relationship model.

5. The digital control method for an underfloor wheel lathe according to claim 1, characterized in that: The classifying and counting the historical alarm data to obtain the classified and counted historical fault statistical information includes: Classify and count the historical alarm data according to preset time periods and preset alarm types to obtain historical fault statistical information corresponding to multiple alarm types in each preset time period; Among them, the preset alarm types include: functional alarm type and fault alarm type. The functional types include: hydraulic unit alarm, lubrication unit alarm, servo system alarm, spindle system alarm. The fault types include: prompt alarm, main system fault alarm, auxiliary system fault alarm, and position pressure detection alarm.

6. The digital control method for an underfloor wheel lathe according to claim 1 or 5, characterized in that: After constructing the equipment health management model according to the wheel status data set, the working running time and the historical fault statistical information, the method further includes: Collecting real-time operating status data of multiple components corresponding to the lathe equipment within a preset time period, performing preprocessing operations on the real-time operating status data, and obtaining a processed operating status data test set; Inputting the operating status data test set into the equipment health management model for prediction calculation, and finally predicting the remaining service life of the lathe equipment and the corresponding probability of occurrence of each fault type; Wherein, the real-time operation status data includes at least one of current data, voltage data, temperature data, pressure data, and load data.

7. The digital control method for an underfloor wheel lathe according to claim 1, characterized in that: The method further comprises: Establishing a communication link with the lathe equipment through a wireless network, and remotely monitoring the operating status data, energy consumption data and historical alarm data of the lathe equipment through the communication link, and determining whether abnormal data appears in the operating status data and / or energy consumption data, or whether new alarm data is added to the historical alarm data; When it is determined that abnormal data appears in the operating status data and / or the energy consumption data, or when new alarm data is added to the historical alarm data, relevant control operations are performed on the lathe equipment through the communication link; Wherein, the control operation includes: performing fault detection, troubleshooting and repair on the lathe equipment according to the abnormal data and the newly added alarm data.

8. A digital control system for an underfloor wheel lathe, characterized in that: The system comprises: A collection module, used to collect working data of the lathe equipment through sensors and data collectors, wherein the working data includes at least one of: operating status data, energy consumption data, and cutting data required to be measured for the corresponding wheel; An archiving module, used for archiving the cutting data of the corresponding wheel in the lathe equipment collected by the collecting module to obtain wheel parameter information; An analysis module, configured to analyze the wheel parameter information archived by the archiving module according to a preset wheel cutting standard to obtain a wheel status data set; A recording module, used to record the working operation time of the lathe equipment and the historical alarm data of the lathe equipment in the past; A classification and statistics module, used for classifying and counting the historical alarm data recorded by the recording module to obtain historical fault statistics information after classification and statistics; A construction module is used to construct an equipment health management model based on the wheel status data set obtained by the analysis module, the working operation time obtained by the recording module, and the historical fault statistical information obtained by the classification and statistics module. The equipment health management model is used to perform fault prediction and cutting data evaluation on the equipment.

9. A digital control system for an underfloor wheel lathe, characterized in that: The system comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the digital control method for the underfloor wheels lathe as described in any one of claims 1-7.

10. A computer storage medium, characterized in that: The computer storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the digital control method of the underfloor wheeled lathe as described in any one of claims 1-7.

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