Arc cutting method, device, equipment and medium based on intelligent numerical control

Abstract

The present application provides an arc cutting method, device, equipment and medium based on intelligent numerical control, which collects current data sets on the material being cut; extracts multiple local leakage currents in the stable arcing stage from the current data sets, determines the fault point according to all local leakage currents, determines the arc tracking resistance of the material being cut according to the time series characteristics of the current at the fault point, obtains the flow rate sequence of the protective gas, determines the diffusion of the slag at the fault point during the arc cutting process according to the flow rate sequence, determines the fault type fault judgment tree according to the diffusion and arc tracking resistance, judges the fault type of the arc cutting device leakage fault through the fault judgment tree, and adjusts the subsequent work flow of the arc cutting device based on the fault type. The above scheme can reduce the false operation of the arc cutting operation caused by transient faults when the slag hinders the insulating effect of the protective gas, thereby improving the efficiency of arc cutting production.

Description

Technical Field

[0001] The present application relates to the field of arc cutting technology, and more specifically, to an arc cutting method, device, equipment and medium based on intelligent numerical control. Background Art

[0002] Arc cutting device is a kind of equipment that uses electric arc as heat source to cut metal. The arc generated between carbon electrode and workpiece is used to melt the metal through carbon arc gouging, and the molten metal is blown away with compressed air. Usually, in order to protect the health of production personnel and product quality, the cutting operation is carried out under protective water, and the arc and protective water are insulated by protective gas.

[0003] During the arc cutting process, excess leakage current will be generated on the material being cut, and when the device for emitting shielding gas in the arc cutting device fails, a serious leakage fault will occur, resulting in damage to the material being cut and waste of energy, and even endangering production safety. In the prior art, the arc cutting device is usually stopped urgently when a large leakage current is detected to protect the material being cut and the production environment. However, in actual production, when the slag of the cut material is mixed into the airflow of the shielding gas, it will also briefly cause a large leakage current. The leakage fault in this case will disappear quickly. At this time, if the arc device is stopped urgently, it will affect production efficiency. Therefore, how to reduce the false operation of the arc cutting operation caused by transient faults when the slag hinders the insulating effect of the protective gas, and thereby improve the efficiency of arc cutting production has become a difficult problem faced by the industry. Summary of the invention

[0004] The present application provides an arc cutting method, device, equipment and medium based on intelligent numerical control, which can reduce the false operation of the arc cutting operation caused by a transient fault when the slag hinders the insulating effect of the protective gas, thereby improving the efficiency of the arc cutting production.

[0005] In a first aspect, the present application provides an arc cutting method based on intelligent numerical control, comprising:

[0006] Starting the arc cutting device, collecting current data at various locations on the material being cut in the target arc cutting device, and then obtaining a current data set;

[0007] Extracting multiple local leakage currents in the stable arcing stage from the current data set, performing current decay simulation based on all the local leakage currents and the cutting current of the arc cutting device at the current moment, and then obtaining the fault point where the leakage current occurs, and determining the arc tracking resistance of the cut material through the time sequence characteristics of the current at the fault point;

[0008] Obtain the flow velocity sequence of the shielding gas at the air outlet of the arc cutting device under various abnormal airflow conditions, and then determine the loss coefficient of the cutting efficiency of the target arc cutting device under the corresponding abnormal airflow condition according to each flow velocity sequence, and determine the diffusion degree of the slag in the shielding water at the fault point during the arc cutting process based on all the loss coefficients;

[0009] A fault judgment tree is constructed when leakage occurs in the target arc cutting device according to the diffusion degree and the arc tracking resistance of the cut material, and the fault type of the leakage fault of the arc cutting device is judged by the impact signal when the arc is struck at the fault point and the fault judgment tree;

[0010] The arc cutting operation of the target arc cutting device is adjusted in real time based on the fault type.

[0011] In some embodiments, extracting a plurality of local leakage currents in the stable arcing stage from the current data set specifically includes:

[0012] Selecting a current data from the current data set as selected current data;

[0013] determining an arc stabilization sequence during arc cutting according to the selected current data;

[0014] Determining a stable arcing stage according to the arc stable sequence;

[0015] Determine the local leakage current corresponding to the selected current data according to all current values ​​corresponding to the selected current data in the stable arcing stage;

[0016] Continue to determine the local leakage current corresponding to the remaining current data in the current data set.

[0017] In some embodiments, current decay simulation is performed based on all local leakage currents and the cutting current of the arc cutting device at the current moment, and then the fault point where the leakage current occurs is obtained, specifically including:

[0018] Obtain the cutting current of the arc cutting device at the current moment;

[0019] Determining a current decay rate sequence according to the cutting current and all local leakage currents;

[0020] The leakage current is simulated according to the current decay rate sequence to obtain the fault point where the leakage current occurs.

[0021] In some embodiments, determining the arc tracking resistance of the cut material by the timing characteristics of the current at the fault point specifically includes:

[0022] Obtain leakage fault samples;

[0023] Determining the timing characteristics of the current at the fault point;

[0024] According to the time series characteristics, the historical current data at the fault point is divided into continuous leakage current data, transient leakage current data and normal current data;

[0025] determining a current characteristic of the continuous leakage current data;

[0026] determining a current characteristic of the transient leakage current data;

[0027] determining a current characteristic of the normal current data;

[0028] The arc tracking resistance of the cut material is determined according to the current characteristics of the continuous leakage current data, the current characteristics of the transient leakage current data and the current characteristics of the normal current data.

[0029] In some embodiments, determining the loss coefficient of cutting efficiency of the target arc cutting device under the corresponding abnormal airflow state according to each flow rate sequence specifically includes:

[0030] Obtain leakage fault samples;

[0031] Selecting an abnormal airflow state as a selected airflow state;

[0032] Determine the fault type of each flow rate value in the flow rate sequence corresponding to the selected airflow state according to the leakage fault sample;

[0033] Determine the loss coefficient of cutting efficiency of the target arc cutting device under the selected airflow state according to all fault types;

[0034] Continue to determine the loss coefficient of cutting efficiency of the target arc cutting device under the abnormal residual airflow state.

[0035] In some embodiments, constructing a fault judgment tree when leakage occurs in the target arc cutting device according to the diffusion and the arc tracking resistance of the cut material specifically includes:

[0036] Determine a plurality of first-level judgment nodes according to the diffusion degree and the arc tracking resistance of the cut material;

[0037] Determine multiple secondary judgment nodes according to the node types of all the primary judgment nodes;

[0038] All the first-level judgment nodes and all the second-level judgment nodes form a fault judgment tree when leakage occurs in the target arc cutting device.

[0039] In some embodiments, adjusting the arc cutting operation of the target arc cutting device in real time based on the fault type specifically includes:

[0040] If the fault type is no fault, the subsequent arc cutting work of the arc cutting device is not adjusted;

[0041] If the fault type is a transient fault caused by slag, the flow rate of the shielding gas at the air outlet of the arc cutting device is temporarily increased, and the flow rate of the shielding gas is restored after the transient fault is eliminated;

[0042] If the fault type is a persistent fault caused by other factors, the power supply of the arc cutting device is immediately interrupted and an alarm is issued.

[0043] In a second aspect, the present application provides an arc cutting device based on intelligent numerical control, wherein the arc cutting device based on intelligent numerical control includes a fault judgment unit, and the fault judgment unit includes:

[0044] A collection module is used to collect current data at various locations on the material being cut in the target arc cutting device after the arc cutting device is started, thereby obtaining a current data set;

[0045] a processing module, for extracting a plurality of local leakage currents in a stable arcing stage from the current data set, performing current decay simulation according to all the local leakage currents and the cutting current of the arc cutting device at the current moment, and then obtaining a fault point where the leakage current occurs, and determining the arc tracking resistance of the cut material through the time sequence characteristics of the current at the fault point;

[0046] The processing module is also used to obtain the flow rate sequence of the protective gas at the air outlet of the arc cutting device under various abnormal airflow conditions, and then determine the loss coefficient of the cutting efficiency of the target arc cutting device under the corresponding abnormal airflow condition according to each flow rate sequence, and determine the diffusion degree of the slag in the protective water at the fault point during the arc cutting process based on all the loss coefficients;

[0047] The processing module is also used to construct a fault judgment tree when leakage occurs in the target arc cutting device according to the diffusion degree and the arc tracking resistance of the cut material, and judge the fault type of the leakage fault of the arc cutting device through the impact signal when the arc is struck at the fault point and the fault judgment tree;

[0048] An execution module is used to adjust the arc cutting work of the target arc cutting device in real time based on the fault type.

[0049] In a third aspect, the present application provides a computer device, comprising a memory and a processor, wherein the memory stores codes, and the processor is configured to obtain the codes and execute the above-mentioned arc cutting method based on intelligent numerical control.

[0050] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned arc cutting method based on intelligent numerical control is implemented.

[0051] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects:

[0052] In the arc cutting method, device, equipment and medium based on intelligent numerical control provided by the present application, first, the arc cutting device is started, and the current data of various locations on the material to be cut in the target arc cutting device are collected, so as to obtain a current data set; multiple local leakage currents in the stable arc burning stage are extracted from the current data set, and current attenuation simulation is performed according to all local leakage currents and the cutting current of the arc cutting device at the current moment, so as to obtain the fault point where the leakage current occurs, and the arc tracking resistance of the material to be cut is determined by the time series characteristics of the current at the fault point; the protective gas at each outlet of the arc cutting device is obtained. A flow velocity sequence under abnormal airflow conditions is obtained, and then the loss coefficient of the cutting efficiency of the target arc cutting device under the corresponding abnormal airflow conditions is determined according to each flow velocity sequence; the diffusion degree of the slag in the protective water at the fault point during the arc cutting process is determined based on all the loss coefficients; a fault judgment tree is constructed when leakage occurs in the target arc cutting device according to the diffusion degree and the arc tracking resistance of the cut material, and the fault type of the leakage fault of the arc cutting device is judged by the impact signal when the arc is struck at the fault point and the fault judgment tree; the arc cutting work of the target arc cutting device is adjusted in real time based on the fault type.

[0053] It can be seen that the present application determines the fault point through multiple local leakage currents, and determines the arc tracking resistance of the cut material through the time series characteristics of the historical current at the fault point. On the other hand, the diffusion of slag in the protective water at the fault point during the arc cutting process is determined through the flow rate sequence of the protective gas at the air outlet in the arc cutting device (i.e., the diffusion degree), and a fault judgment tree is constructed in combination with the arc tracking resistance of the cut material and the diffusion of slag, so as to judge whether the leakage fault of the arc cutting device at the current moment is a transient fault caused by the slag hindering the insulating effect of the protective gas, and adjust the arc cutting work of the arc cutting device in real time according to the judgment result. In summary, the present application can reduce the false operation of the arc cutting operation caused by the transient fault caused by the slag hindering the insulating effect of the protective gas, thereby improving the efficiency of arc cutting production. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 is an exemplary flow chart of an arc cutting method based on intelligent numerical control according to some embodiments of the present application;

[0055] Figure 2is an exemplary flow chart of determining a local leakage current according to some embodiments of the present application;

[0056] Figure 3 is an exemplary flow chart of adjusting arc cutting work according to some embodiments of the present application;

[0057] Figure 4 is a schematic diagram of exemplary hardware and / or software of a fault judgment unit according to some embodiments of the present application;

[0058] Figure 5 It is a structural schematic diagram of a computer device for an arc cutting method based on intelligent numerical control as shown in some embodiments of the present application. DETAILED DESCRIPTION

[0059] The core of the present application is to start the arc cutting device, collect current data at various locations on the material being cut in the target arc cutting device, and then obtain a current data set; extract multiple local leakage currents in the stable arcing stage from the current data set, perform current attenuation simulation based on all local leakage currents and the cutting current of the arc cutting device at the current moment, and then obtain the fault point where the leakage current occurs, and determine the arc tracking resistance of the material being cut through the timing characteristics of the current at the fault point; obtain the flow rate sequence of the protective gas at the air outlet of the arc cutting device under various abnormal airflow conditions, and then determine the loss coefficient of the cutting efficiency of the target arc cutting device under the corresponding abnormal airflow condition based on each flow rate sequence, and determine the diffusion degree of the slag in the protective water at the fault point during the arc cutting process based on all the loss coefficients; construct a fault judgment tree when leakage occurs in the target arc cutting device based on the diffusion degree and the arc tracking resistance of the material being cut, and judge the fault type of the leakage fault of the arc cutting device through the impact signal when the arc is struck at the fault point and the fault judgment tree; and adjust the arc cutting work of the target arc cutting device in real time based on the fault type. The above scheme can reduce the false operation of the arc cutting operation emergency stop caused by transient faults when the slag hinders the insulating effect of the protective gas, thereby improving the efficiency of the arc cutting production.

[0060] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1 , which is an exemplary flow chart of an arc cutting method based on intelligent numerical control according to some embodiments of the present application. The arc cutting method 100 based on intelligent numerical control mainly includes the following steps:

[0061] In step 101, an arc cutting device is started, and current data at various locations on a material to be cut in a target arc cutting device are collected to obtain a current data set.

[0062] In specific implementation, the current data at various locations on the cut material are collected, and then the current data set is obtained by adopting the following steps, namely: first, a plurality of sampling points are preset on the cut material, and for each sampling point, the current value on the surface of the cut material is collected at the sampling point according to the preset sampling interval, and then all the collected current values ​​are sorted according to the order of collection, and then the obtained sequence is used as the current data at the sampling point, and then the current data at all sampling points are obtained, and finally the set consisting of all the current data is used as the current data set.

[0063] It should be noted that the sampling points in the present application can be preset according to the cutting path of the arc cutting device. For example, a straight line can be drawn through the arc striking point on the current material being cut in a direction perpendicular to the current cutting path, and multiple sampling points can be taken at equal intervals on the straight line. In particular, the arc striking point on the current material being cut is not used as a sampling point, wherein the equal interval can be preset according to actual needs. For example, in the present application, the equal interval is preset to 1 cm.

[0064] In addition, it should be noted that the sampling interval in the present application can be preset according to actual needs. For example, the sampling interval in the present application is preset to 0.1 second.

[0065] In step 102, multiple local leakage currents in the stable arcing stage are extracted from the current data set, and current attenuation simulation is performed based on all local leakage currents and the cutting current of the arc cutting device at the current moment, so as to obtain the fault point where the leakage current occurs, and the arc tracking resistance of the cut material is determined by the timing characteristics of the current at the fault point.

[0066] In some embodiments, reference Figure 2 , which is an exemplary flow chart of determining a local leakage current according to some embodiments of the present application. In the present application, extracting multiple local leakage currents in the stable arcing stage from the current data set can be achieved by using the following steps:

[0067] In step 1021, a current data is selected from the current data sets as selected current data;

[0068] In step 1022, an arc steady sequence during arc cutting is determined based on the selected current data;

[0069] In step 1023, a stable arcing stage is determined according to the arc stable sequence;

[0070] In step 1024, the local leakage current corresponding to the selected current data is determined according to all current values ​​corresponding to the selected current data in the stable arcing stage;

[0071] In step 1025, the local leakage current corresponding to the remaining current data in the current data set continues to be determined.

[0072] In a specific implementation, determining the arc stationary sequence in the arc cutting process according to the selected current data can be implemented in the following manner, namely: first, the selected current data is divided into multiple current components through a sampling window of a preset size (that is, the first to nth current values ​​in the selected current data are taken as the first current component, the second to n+1th current values ​​in the selected current data are taken as the second current component, and so on, until the last n current values ​​in the selected current data are classified into the current component, wherein n is the size of the sampling window), for each current component, the ADF (Augmented Derivatives) of the current component can be determined by a unit root test in the prior art. Dickey-Fuller) test statistic, and use the ADF test statistic as the arc smoothness of the corresponding current component, thereby obtaining the arc smoothness of each current component, and finally arranging all the arc smoothnesses according to the arrangement order of the corresponding current components in the selected current data, and using the obtained sequence as the arc smoothness sequence corresponding to the selected current data, wherein the size of the sampling window can be preset according to actual needs. For example, the present application can preset the size of the sampling window to 50 data lengths, that is, one sampling window includes 50 current values ​​in the selected current data.

[0073] It should be noted that the arc stabilization sequence in the present application is a sequence used to measure the stability of the arc between the electrode of the arc cutting device and the material being cut. The greater the arc stabilization in the arc stabilization sequence, the more stable the arc between the electrode of the arc cutting device and the material being cut at the corresponding moment. The smaller the arc stabilization in the arc stabilization sequence, the more unstable the arc between the electrode of the arc cutting device and the material being cut at the corresponding moment, and the closer it is to the arc striking stage or arc extinguishing stage of the arc cutting device.

[0074] In specific implementation, determining the stable arcing stage according to the arc stability sequence can be achieved in the following manner, namely: comparing all arc stability sequence values ​​in the arc stability sequence with a preset stability threshold, and taking the sampling time corresponding to the first current value in the current component corresponding to the arc stability that is greater than the stability threshold for the first time as the starting time of the stable arcing stage, and taking the sampling time corresponding to the last current value in the current component corresponding to the arc stability that is less than the stability threshold for the first time after the starting time as the end time of the stable arcing stage, thereby obtaining the stable arcing stage in the arc cutting process.

[0075] It should be noted that the stable arc burning stage in the present application refers to the stage in which the arc between the electrode of the arc cutting device and the material to be cut is completely stable. In this stable arc burning stage, the arc between the electrode of the arc cutting device and the material to be cut is completely stable, and the leakage current value at each location on the material to be cut is also completely stable.

[0076] In addition, it should be noted that the local leakage current in the present application refers to the current value of the leakage current at the corresponding sampling point on the cut material. As a preferred embodiment, the local leakage current corresponding to the selected current data can be determined based on all current values ​​corresponding to the selected current data in the stable arcing stage. The following steps can be adopted, namely: the average value of all current values ​​corresponding to the selected current data in the stable arcing stage can be used as the local leakage current corresponding to the selected current data.

[0077] In some embodiments, current decay simulation is performed based on all local leakage currents and the cutting current of the arc cutting device at the current moment, and then the fault point where the leakage current occurs is obtained, which can be achieved by the following steps:

[0078] Obtain the cutting current of the arc cutting device at the current moment;

[0079] Determining a current decay rate sequence according to the cutting current and all local leakage currents;

[0080] The leakage current is simulated according to the current decay rate sequence to obtain the fault point where the leakage current occurs.

[0081] In specific implementation, the cutting current of the arc cutting device at the current moment can be obtained in the following way, namely: the current value can be collected at the arc striking point on the current cutting material through a multimeter, and then the collected current value is used as the cutting current of the arc cutting device at the current moment.

[0082] It should be noted that the cutting current in the present application refers to the current value flowing through the arc striking point at the corresponding moment, and the cutting current is the current actually used to generate an arc on the arc cutting device.

[0083] In specific implementation, the current decay rate sequence determined according to the cutting current and all local leakage currents can be implemented in the following manner, namely: first, the cutting current is taken as the local leakage current at the arc striking point on the cut material, and then all the local leakage currents are arranged from small to large according to the distance between the corresponding sampling point and the arc striking point at the current moment, and the cutting current is added to the first value in the arranged sequence, and the second local leakage current in the sequence is subtracted from the first local leakage current, and the difference obtained is taken as the local leakage difference, and the distance between the sampling point corresponding to the second local leakage current and the arc striking point at the current moment is subtracted from the distance between the sampling point corresponding to the first local leakage current and the arc striking point at the current moment, and the opposite of the difference obtained is multiplied by the local leakage difference, and the value obtained is taken as the current decay rate between the first local leakage current and the second local leakage current, and so on, until the current decay rate between the last local leakage current and the second to last local leakage current is obtained, and all the current decay rates are arranged in the order obtained, and the obtained sequence is taken as the current decay rate sequence, wherein the local leakage difference in the above steps is only for the convenience of describing the process quantity used and has no specific meaning.

[0084] It should be noted that the current attenuation rate sequence in the present application is a sequence that represents the attenuation of the leakage current on the cut material as the distance from the arc striking point increases. The larger the current attenuation rate, the greater the degree of current attenuation between the corresponding two sampling points.

[0085] In specific implementation, the leakage current is simulated according to the current decay rate sequence, and the fault point where the leakage current occurs can be obtained in the following manner, namely: the current decay rate sequence is fitted into a curve by the Lagrange interpolation method in the prior art (the dependent variable is the current decay rate, and the independent variable is the square of the distance value corresponding to the local leakage current with the smallest distance between the corresponding sampling point and the arcing point at the current moment among all local leakage currents corresponding to the current decay rate), and the square root of the dependent variable value corresponding to the intersection of the straight line and the vertical axis is used as the height of the fault point, and finally the point at the height of the fault point directly above the arcing point at the current moment is used as the fault point.

[0086] It should be noted that in the present application, current decay simulation is performed based on all local leakage currents and the cutting current of the arc cutting device at the current moment, and then the fault point where the leakage current occurs is obtained, namely: a current decay rate sequence is determined based on the cutting current and all local leakage currents; the leakage current is simulated based on the current decay rate sequence to obtain the fault point where the leakage current occurs.

[0087] It should be noted that the fault point in the present application refers to the point where leakage current is most obvious on the arc during arc cutting. The reason for the leakage current is usually due to the interruption of the flow of the insulating shielding gas. The interruption may be a continuous fault caused by a fault in the arc cutting device, or it may be a transient fault caused by a large volume of slag drifting into the flow of the shielding gas during the cutting process.

[0088] In some embodiments, determining the arc tracking resistance of the cut material by the timing characteristics of the current at all fault points can be achieved by the following steps:

[0089] Obtain leakage fault samples;

[0090] Determining the timing characteristics of the current at the fault point;

[0091] According to the time series characteristics, the historical current data at the fault point is divided into continuous leakage current data, transient leakage current data and normal current data;

[0092] determining a current characteristic of the continuous leakage current data;

[0093] determining a current characteristic of the transient leakage current data;

[0094] determining a current characteristic of the normal current data;

[0095] The arc tracking resistance of the cut material is determined according to the current characteristics of the continuous leakage current data, the current characteristics of the transient leakage current data and the current characteristics of the normal current data.

[0096] It should be noted that the leakage fault sample in the present application refers to a set of time, fault type and timing characteristics of the current at the fault point when the leakage current fault occurred in the historical working process of the arc cutting device. As a preferred embodiment, the leakage fault sample of the arc cutting device in the historical working process can be obtained from a database connected to the arc cutting device.

[0097] In specific implementation, determining the time series characteristics of the current at the fault point can be achieved in the following manner, namely: first, obtaining historical data of the current at the fault point, and arranging the autocorrelation coefficients of the historical data at different lag times from small to large according to the size of the lag time, and using the obtained sequence as the time series characteristics of the current at the fault point.

[0098] It should be noted that the timing characteristics in the present application are parameter sequences that represent the changes in the current at the corresponding fault point as the arc cutting device works over time.

[0099] In addition, it should be noted that the length of the sequence corresponding to the time series characteristics of the current at the fault point in the present application is equal to the historical data of the current at the fault point, and each autocorrelation coefficient in the sequence corresponding to the time series characteristics of the current at the fault point corresponds one-to-one to each current value in the historical data of the current at the fault point.

[0100] In specific implementation, the historical data of the current at the fault point is divided into continuous leakage current data, transient leakage current data and normal current data according to the time series characteristics, which can be implemented in the following manner, namely: firstly, a first characteristic threshold and a second characteristic threshold are preset, and then a set consisting of all current values ​​corresponding to all autocorrelation coefficients greater than the first characteristic threshold in the time series characteristics is taken as leakage current data, a set consisting of all current values ​​corresponding to autocorrelation coefficients less than or equal to the first characteristic threshold and greater than the second characteristic threshold is taken as transient leakage current data, and a set consisting of all current values ​​corresponding to autocorrelation coefficients less than or equal to the second characteristic threshold is taken as normal current data, wherein the first characteristic threshold and the second characteristic threshold can be determined according to experiments. For example, when a leakage fault occurs in the arc cutting device, multiple current values ​​at the fault point can be collected, all current values ​​can be arranged in the order of collection, and all autocorrelation coefficients of the arranged sequence can be obtained, and the sum of the mean of all autocorrelation coefficients and three times the standard deviation of all autocorrelation coefficients is taken as the first characteristic threshold, and the difference between the mean of all autocorrelation coefficients and three times the standard deviation of all autocorrelation coefficients is taken as the second characteristic threshold.

[0101] It should be noted that in the present application, normal current data refers to the set of current values ​​when no leakage fault occurs at the corresponding fault point, continuous leakage current data refers to the set of current values ​​when a continuous leakage fault occurs at the corresponding fault point, and transient leakage current data refers to the set of current values ​​when a transient leakage fault occurs at the corresponding fault point.

[0102] In specific implementation, determining the current characteristics of the continuous leakage current data can be achieved in the following manner, namely: first, determining the fault type corresponding to each current value in the continuous leakage current data in the leakage fault sample, for each fault type, taking the square of the ratio of the total number of fault types to the length of the continuous leakage current data as the process quantity of the fault type, and then obtaining the process quantity of each fault type, and finally taking the sum of the process quantities of all fault types as the current characteristics of the continuous leakage current data.

[0103] In specific implementation, determining the current characteristics of the transient leakage current data can be achieved in the following manner, namely: first, determining the fault type corresponding to each current value in the transient leakage current data in the leakage fault sample, for each fault type, taking the square of the ratio of the total number of fault types to the length of the transient leakage current data as the process quantity of the fault type, and then obtaining the process quantity of each fault type, and finally taking the sum of the process quantities of all fault types as the current characteristics of the transient leakage current data;

[0104] In specific implementation, determining the current characteristics of the normal current data can be achieved in the following manner, namely: first, determining the fault type corresponding to each current value in the normal current data in the leakage fault sample, for each fault type, taking the square of the ratio of the total number of fault types to the length of the normal current data as the process quantity of the fault type, and then obtaining the process quantity of each fault type, and finally taking the sum of the process quantities of all fault types as the current characteristics of the normal current data.

[0105] It should be noted that the current characteristic in the present application is a parameter indicating the degree of correlation between the corresponding current type and the fault type. The current characteristic is a value between zero and one. The larger the current characteristic, the smaller the correlation between the corresponding current type and the fault type.

[0106] In specific implementation, determining the arc tracking resistance of the cut material based on the current characteristics of the continuous leakage current data, the current characteristics of the transient leakage current data and the current characteristics of the normal current data can be achieved in the following manner, namely: first, multiplying the difference between the current characteristics of the normal current data and one by the length of the normal current data, then multiplying the difference between the current characteristics of the continuous leakage current data and one by the length of the continuous leakage current data, and multiplying the difference between the current characteristics of the transient leakage current data and one by the length of the transient leakage current data, and then dividing the sum of the three products obtained above by the total length of the historical data of the current at the corresponding fault point, and using the quotient obtained as the arc tracking resistance of the cut material.

[0107] It should be noted that, in the present application, arc tracking resistance refers to the ability of the surface of the cut material to prevent the formation of arc tracks under the action of electric arc. Arc tracks refer to the conductive path formed on the surface of the cut material under the action of electric arc. The arc tracks will cause leakage current to appear on the cut material other than the arc initiation point. The greater the arc tracking resistance, the stronger the ability of the cut material to resist the formation of continuous conductive tracks under the action of electric arc. At this time, the connection between the leakage current on the cut material and the fault type is stronger, that is, the fault type judged according to the current value at the fault point is more credible.

[0108] In step 103, the flow velocity sequence of the shielding gas at the air outlet of the arc cutting device under various abnormal airflow conditions is obtained, and then the loss coefficient of the cutting efficiency of the target arc cutting device under the corresponding abnormal airflow condition is determined according to each flow velocity sequence, and the diffusion degree of the slag in the shielding water at the fault point during the arc cutting process is determined based on all the loss coefficients.

[0109] In some embodiments, obtaining the flow rate sequence of the shielding gas at the air outlet of the arc cutting device under various abnormal airflow conditions can be achieved by using the following steps:

[0110] Obtaining flow rate data of shielding gas at the air outlet of the arc cutting device;

[0111] The flow velocity data is divided into flow velocity sequences under various abnormal airflow states.

[0112] In specific implementation, the flow rate data of the shielding gas at the air outlet of the arc cutting device can be obtained in the following manner, namely: the flow rate sensor at the air outlet of the arc cutting device can be used to collect the flow rate value of the shielding gas at a preset interval, and all the collected flow rate values ​​are arranged in the order of collection, and the obtained sequence is used as the flow rate data of the shielding gas at the air outlet of the arc cutting device.

[0113] In some embodiments, dividing the flow velocity data into flow velocity sequences under various abnormal airflow states may be achieved by using the following steps:

[0114] Each abnormal state of air flow is preset as a normal flow rate, a slag obstruction flow rate and an equipment failure flow rate;

[0115] Preset a first flow rate threshold and a second flow rate threshold;

[0116] extracting a flow velocity sequence at a normal flow velocity from the flow velocity data according to the first flow velocity threshold;

[0117] extracting a flow velocity sequence at a slag-impeded flow velocity from the flow velocity data according to the first flow velocity threshold and the second flow velocity threshold;

[0118] A flow rate sequence at a device failure flow rate is extracted from the flow rate data according to the second flow rate threshold.

[0119] It should be noted that the first flow rate threshold and the second flow rate threshold in the present application are boundary values ​​for distinguishing different abnormal airflow states. As a preferred embodiment, the determination of the first flow rate threshold and the second flow rate threshold in the present application can be implemented in the following manner, namely: when a continuous leakage fault occurs in the arc cutting device, the flow rate values ​​of multiple protective gases can be collected, and the sum of the mean of all flow rate values ​​and three times the standard deviation of all flow rate values ​​is taken as the first flow rate threshold, and the difference between the mean of all flow rate values ​​and three times the standard deviation of all flow rate values ​​is taken as the second flow rate threshold.

[0120] In addition, it should be noted that the normal flow rate in the present application refers to the flow rate of the shielding gas when the arc can theoretically be completely insulated, the equipment fault flow rate refers to the flow rate of the shielding gas when the arc insulation may be incomplete, the equipment fault flow rate is usually caused by a fault in the arc cutting device, and the equipment fault flow rate is usually smaller than the normal flow rate, the slag obstruction flow rate refers to the slag of the cut material appearing in the airflow of the shielding gas, which temporarily obstructs the flow of the shielding gas and causes a transient leakage current fault in the arc, and the slag obstruction flow rate is usually between the normal flow rate and the equipment fault flow rate. As a preferred embodiment, all flow rate values ​​greater than the first flow rate threshold in the flow rate sequence can be used as normal flow rates, all flow rate values ​​less than or equal to the first flow rate threshold and greater than the second flow rate threshold can be used as slag obstruction flow rates, and all flow rate values ​​less than or equal to the second flow rate threshold can be used as equipment fault flow rates.

[0121] It should be noted that the abnormal airflow state in the present application refers to a gas flow rate state of a protective gas that may cause a failure of the arc cutting device. For example, the gas flow rate state in the present application includes three types of airflow rate abnormalities: normal flow rate, equipment failure flow rate, and slag obstruction flow rate. In other embodiments, the abnormal airflow state can also be determined by other methods, which are not limited here.

[0122] In some embodiments, determining the loss coefficient of cutting efficiency of the target arc cutting device under the corresponding abnormal airflow state according to each flow rate sequence can be achieved by using the following steps:

[0123] Obtain leakage fault samples;

[0124] Selecting an abnormal airflow state as a selected airflow state;

[0125] Determine the fault type of each flow rate value in the flow rate sequence corresponding to the selected airflow state according to the leakage fault sample;

[0126] Determine the loss coefficient of cutting efficiency of the target arc cutting device under the selected airflow state according to all fault types;

[0127] Continue to determine the loss coefficient of cutting efficiency of the target arc cutting device under the abnormal residual airflow state.

[0128] It should be noted that the leakage fault sample in the present application refers to a set consisting of the time when the leakage current fault occurred during the historical operation of the arc cutting device, the fault type and the time sequence characteristics of the current at the fault point.

[0129] In specific implementation, determining the fault type of each flow rate value in the flow rate sequence corresponding to the selected airflow state based on the leakage fault sample can be achieved in the following manner, namely: for each flow rate value in the flow rate sequence corresponding to the selected airflow state, the sampling moment of the flow rate value is matched with the moment when the leakage current fault occurs in the leakage fault sample, and then the fault type corresponding to the moment when the leakage current fault occurs in the leakage fault sample is used as the fault type of the flow rate value.

[0130] In specific implementation, determining the loss coefficient of the cutting efficiency of the target arc cutting device under the selected airflow state based on all fault types can be achieved in the following manner, namely: for each fault type, the square of the ratio of the total number of occurrences of this fault type to the length of the flow rate sequence under the selected airflow state is used as the characteristic value of the fault type, and then the characteristic value of each fault type is obtained, and finally the sum of the characteristic values ​​of all fault types is used as the loss coefficient of the cutting efficiency of the target arc cutting device under the selected airflow state, wherein the characteristic value in the above steps is only a process quantity used for the convenience of description when determining the loss coefficient and has no specific meaning.

[0131] It should be noted that the loss coefficient in the present application is used to indicate the degree of loss in cutting efficiency of the arc cutting production process caused by the fault type caused under the corresponding gas flow rate state. The larger the loss coefficient, the more serious the loss in cutting efficiency of the arc cutting production process caused by the fault type caused under the corresponding gas flow rate state, that is, the lower the cutting efficiency of the arc cutting production process at this time.

[0132] In some embodiments, determining the diffusion degree of slag in the protective water at the fault point during arc cutting based on all fault loss coefficients can be achieved by the following steps:

[0133] Determine the diffusion component of the slag at the fault point at the normal flow rate according to the loss coefficient of the normal flow rate;

[0134] Determine the diffusion component of the slag at the fault point when the equipment fails according to the loss coefficient of the equipment failure flow rate;

[0135] Determine the diffusion component of the slag at the fault point when the airflow of the protective gas is obstructed by the slag according to the loss coefficient of the slag obstructing the flow velocity;

[0136] The diffusion degree of the slag at the fault point in the protective water is determined based on the diffusion component of the slag at the fault point at normal flow rate, the diffusion component of the slag at the fault point when the equipment fails, and the diffusion component of the slag at the fault point when the airflow of the protective gas is blocked by the slag.

[0137] In specific implementation, determining the diffusion component of the slag at the fault point at normal flow rate based on the loss coefficient of the normal flow rate can be achieved in the following way, namely: first multiplying the difference between the loss coefficient of the normal flow rate and one by the total number of normal flow rates, and using the obtained value as the diffusion component of the slag at the fault point at normal flow rate.

[0138] In specific implementation, determining the diffusion component of the slag at the fault point when the equipment fails based on the loss coefficient of the equipment failure flow velocity can be achieved in the following manner, namely: first multiplying the difference between the loss coefficient of the equipment failure flow velocity and one by the total number of equipment failure flow velocities, and using the obtained value as the diffusion component of the slag at the fault point when the equipment fails.

[0139] In specific implementation, determining the diffusion component of slag at the fault point when the airflow of the shielding gas is obstructed by slag based on the loss coefficient of the slag obstruction flow velocity can be achieved in the following manner, namely: first, multiplying the difference between the loss coefficient of the slag obstruction flow velocity and one by the total number of slag obstruction flow velocities, and using the obtained value as the diffusion component of the slag at the fault point when the airflow of the shielding gas is obstructed by slag.

[0140] It should be noted that the diffusion component in this application is a parameter that indicates the diffusion of the slag of the cut material in the protective water under the corresponding gas flow rate state. The larger the diffusion component, the larger the diffusion range of the slag of the cut material in the protective water under the corresponding gas flow rate state.

[0141] In specific implementation, the diffusion degree of slag at the fault point in the protective water can be determined according to the diffusion component of the slag at the fault point at normal flow rate, the diffusion component of the slag at the fault point at equipment failure, and the diffusion component of the slag at the fault point when the airflow of the protective gas is blocked by the slag. The following method can be used, namely: the diffusion component of the slag at the fault point at normal flow rate, the diffusion component of the slag at the fault point at equipment failure, and the diffusion component of the slag at the fault point when the airflow of the protective gas is blocked by the slag are added together, the sum is divided by the sum of the lengths of the flow rate sequences under all abnormal airflow conditions, and the quotient is used as the diffusion degree of the fault point in the protective water during arc cutting.

[0142] It should be noted that the diffusion degree in the present application is a parameter indicating the diffusion of the slag of the cut material in the protective water. The larger the diffusion degree, the more serious the diffusion of the slag of the cut material in the protective water, that is, the greater the damage caused by the slag of the cut material to the arc cutting operation. At this time, the connection between the diffusion of the slag of the cut material and the fault type is stronger, and the fault type judged according to the flow rate of the protective gas at the outlet of the arc cutting device is more credible.

[0143] In step 104, a fault judgment tree is constructed when leakage occurs in the target arc cutting device based on the diffusion and the arc tracking resistance of the cut material, and the fault type of the leakage fault of the arc cutting device is judged by the impact signal when the arc is struck at the fault point and the fault judgment tree.

[0144] In some embodiments, constructing a fault judgment tree when leakage occurs in the target arc cutting device according to the diffusion and the arc tracking resistance of the cut material can be implemented by the following steps:

[0145] Determine a plurality of first-level judgment nodes according to the diffusion degree and the arc tracking resistance of the cut material;

[0146] Determine multiple secondary judgment nodes according to the node types of all the primary judgment nodes;

[0147] All the first-level judgment nodes and all the second-level judgment nodes form a fault judgment tree when leakage occurs in the target arc cutting device.

[0148] In specific implementation, determining multiple first-level judgment nodes according to the diffusion and the arc tracking resistance can be achieved in the following manner, namely: comparing the diffusion and the arc tracking resistance, when the diffusion is greater than or equal to the arc tracking resistance, all abnormal airflow states, namely normal flow rate, equipment failure flow rate and slag obstruction flow rate are taken as first-level judgment nodes, and when the diffusion is less than the arc tracking resistance, continuous leakage current, transient leakage current and normal current are taken as first-level judgment nodes.

[0149] It should be noted that the first-level judgment node in the present application is used as a basis for making the first judgment on the fault type at the fault point.

[0150] In specific implementation, the following steps can be used to determine multiple secondary judgment nodes based on the node types of all the first-level judgment nodes, namely: if the node type of the first-level judgment node is different airflow abnormal states, namely normal flow rate, equipment fault flow rate and slag obstruction flow rate, then the continuous leakage current, transient leakage current and normal current are used as the secondary judgment nodes of the normal flow rate, and the continuous leakage current, transient leakage current and normal current are used as the secondary judgment nodes of the equipment fault flow rate, and then the continuous leakage current, transient leakage current and normal current are used as the secondary judgment nodes of the slag obstruction flow rate, if the first-level judgment node is continuous leakage current, transient leakage current and normal current, then the normal flow rate, equipment fault flow rate and slag obstruction flow rate are used as the secondary judgment nodes of the continuous leakage current, and the normal flow rate, equipment fault flow rate and slag obstruction flow rate are used as the secondary judgment nodes of the transient leakage current, and then the normal flow rate, equipment fault flow rate and slag obstruction flow rate are used as the secondary judgment nodes of the normal current.

[0151] It should be noted that the secondary judgment node in the present application is used as a basis for making a second judgment on the fault type at the fault point.

[0152] In specific implementation, all the first-level judgment nodes and all the second-level judgment nodes are composed of a fault judgment tree to determine the fault type, which can be implemented in the following way, namely: select a first-level judgment node and a second-level judgment node under the first-level judgment node, and use the fault type with the largest number of occurrences among all the fault types corresponding to the selected first-level judgment node and the selected second-level judgment node in the leakage fault sample as the judgment result corresponding to the selected first-level judgment node and the selected second-level judgment node, repeat the above steps to obtain the judgment result of each second-level judgment node under all the first-level judgment nodes, and then obtain the fault judgment tree.

[0153] In some embodiments, judging the fault type of the leakage fault of the arc cutting device by using the impact signal when the arc is struck at the fault point and the fault judgment tree can be achieved by using the following steps:

[0154] Determine the primary fault classification according to all the primary judgment nodes in the fault judgment tree, the impact signal when the arc is struck at the fault point, and the flow rate value of the protective gas at the current moment;

[0155] The fault type of the arc cutting device leakage fault is determined according to all the second-level judgment nodes under the first-level fault classification.

[0156] In specific implementation, the first-level fault classification can be determined based on all the first-level judgment nodes in the fault judgment tree, the impact signals when arcing at all fault points and the flow rate value of the protective gas at the current moment. That is: the fault judgment tree can be used as a decision tree, the impact signal when arcing at the fault point can be used as the input parameter corresponding to the current value in the fault judgment tree, the flow rate value of the protective gas at the current moment can be used as the input parameter corresponding to the flow rate value in the fault judgment tree, and the output judgment result can be used as the fault type of the leakage fault of the arc cutting device at the current moment.

[0157] It should be noted that the fault types in this application include no fault, transient fault caused by slag and continuous fault caused by equipment.

[0158] In step 105, the arc cutting operation of the arc cutting device is adjusted in real time based on the fault type.

[0159] In some embodiments, reference Figure 3 , which is an exemplary flow chart of adjusting the arc cutting work according to some embodiments of the present application. In the present application, the real-time adjustment of the arc cutting work of the target arc cutting device based on the fault type can be implemented by the following steps:

[0160] In step 1051, if the fault type is no fault, the subsequent arc cutting work of the arc cutting device is not adjusted;

[0161] In step 1052, if the fault type is a transient fault caused by slag, the flow rate of the shielding gas at the air outlet of the arc cutting device is temporarily increased, and the flow rate of the shielding gas is restored after the transient fault is eliminated;

[0162] In step 1053, if the fault type is a persistent fault caused by the equipment, the power supply of the arc cutting device is immediately interrupted and an alarm is issued.

[0163] In addition, in another aspect of the present application, in some embodiments, the present application provides an arc cutting device based on intelligent numerical control, the arc cutting device based on intelligent numerical control includes a fault judgment unit, referring to Figure 4 , which is a schematic diagram of exemplary hardware and / or software of a fault judgment unit according to some embodiments of the present application, the fault judgment unit 400 includes: a collection module 401, a processing module 402 and an execution module 403, which are described as follows:

[0164] The acquisition module 401 in the present application is mainly used to start the arc cutting device, collect current data at various locations on the material being cut in the target arc cutting device, and then obtain a current data set;

[0165] Processing module 402, in the present application, is mainly used to extract multiple local leakage currents in the stable arcing stage from the current data set, perform current decay simulation according to all local leakage currents and the cutting current of the arc cutting device at the current moment, and then obtain the fault point where the leakage current occurs, and determine the arc tracking resistance of the cut material through the time sequence characteristics of the current at the fault point;

[0166] It should be noted that the processing module 402 in the present application is also used to obtain the flow rate sequence of the protective gas at the air outlet of the arc cutting device under various abnormal airflow conditions, and then determine the loss coefficient of the cutting efficiency of the target arc cutting device under the corresponding abnormal airflow condition according to each flow rate sequence, and determine the diffusion degree of the slag in the protective water at the fault point during the arc cutting process based on all the loss coefficients;

[0167] It should be noted that the processing module 402 in the present application is also used to construct a fault judgment tree when leakage occurs in the target arc cutting device according to the diffusion degree and the arc tracking resistance of the cut material, and judge the fault type of the leakage fault of the arc cutting device through the impact signal when the arc is struck at the fault point and the fault judgment tree;

[0168] The execution module 403 in the present application is mainly used to adjust the arc cutting work of the target arc cutting device in real time based on the fault type.

[0169] In addition, the present application also provides a computer device, which includes a memory and a processor, wherein the memory stores codes, and the processor is configured to obtain the codes and execute the above-mentioned arc cutting method based on intelligent numerical control.

[0170] In some embodiments, reference Figure 5 , which is a schematic diagram of the structure of a computer device for an arc cutting method based on intelligent numerical control according to some embodiments of the present application. The arc cutting method based on intelligent numerical control in the above embodiments can be Figure 5 The computer device 500 shown in the figure is implemented, and the computer device 500 includes at least one processor 501, a communication bus 502, a memory 503 and at least one communication interface 504.

[0171] The processor 501 may be a general-purpose central processing unit (CPU) or an application-specific integrated circuit (ASIC).

[0172] The communication bus 502 may be used to transmit information between the above-mentioned components.

[0173] The memory 503 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, an optical disc storage (including a compressed optical disc, a laser disc, an optical disc, a digital versatile disc, a Blu-ray disc, etc.), a magnetic disk or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer, but is not limited thereto. The memory 503 may exist independently and be connected to the processor 501 via the communication bus 502. The memory 503 may also be integrated with the processor 501.

[0174] The memory 503 is used to store the program code for executing the solution of the present application, and the execution is controlled by the processor 501. The processor 501 is used to execute the program code stored in the memory 503. The program code may include one or more software modules. The arc cutting method based on intelligent numerical control in the above embodiment can be implemented by the processor 501 and one or more software modules in the program code in the memory 503.

[0175] The communication interface 504 uses any transceiver or other device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0176] In a specific implementation, as an embodiment, a computer device may include multiple processors, each of which may be a single-CPU processor or a multi-CPU processor. The processor here may refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0177] The above-mentioned computer device may be a general-purpose computer device or a special-purpose computer device. In a specific implementation, the computer device may be a desktop computer, a portable computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device or an embedded device. The embodiment of the present application does not limit the type of computer device.

[0178] In addition, the present application also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned arc cutting method based on intelligent numerical control is implemented.

[0179] In summary, in the arc cutting method, device, equipment, medium and arc cutting device based on intelligent numerical control disclosed in the embodiments of the present application, first, the arc cutting device is started to collect current data at various locations on the material to be cut in the target arc cutting device, and then a current data set is obtained; multiple local leakage currents in the stable arcing stage are extracted from the current data set, and current attenuation simulation is performed based on all local leakage currents and the cutting current of the arc cutting device at the current moment, and then the fault point where the leakage current occurs is obtained, and the arc tracking resistance of the material to be cut is determined by the time series characteristics of the current at the fault point; the air outlet of the arc cutting device is obtained to maintain the arc tracking resistance of the material to be cut. The flow velocity sequence of the shielding gas under each abnormal airflow state is determined, and then the loss coefficient of the cutting efficiency of the target arc cutting device under the corresponding abnormal airflow state is determined according to each flow velocity sequence, and the diffusion degree of the slag in the shielding water at the fault point during the arc cutting process is determined based on all the loss coefficients; a fault judgment tree is constructed when leakage occurs in the target arc cutting device according to the diffusion degree and the arc tracking resistance of the cut material, and the fault type of the leakage fault of the arc cutting device is judged by the impact signal when the arc is struck at the fault point and the fault judgment tree; the arc cutting work of the target arc cutting device is adjusted in real time based on the fault type.

[0180] It can be seen that the present application determines the fault point through multiple local leakage currents, and determines the arc tracking resistance of the cut material through the time series characteristics of the historical current at the fault point. On the other hand, the diffusion of slag in the protective water at the fault point during the arc cutting process is determined through the flow rate sequence of the protective gas at the air outlet in the arc cutting device (i.e., the diffusion degree), and a fault judgment tree is constructed in combination with the arc tracking resistance of the cut material and the diffusion of slag, so as to determine whether the leakage fault of the arc cutting device at the current moment is a transient fault caused by the slag hindering the insulating effect of the protective gas, and adjust the arc cutting work of the arc cutting device in real time based on the judgment result. In summary, the present application can reduce the false operation of the arc cutting operation caused by transient faults when the slag hinders the insulating effect of the protective gas, thereby improving the efficiency of arc cutting production.

[0181] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0182] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. An arc cutting method based on intelligent numerical control, characterized in that: include: Starting the arc cutting device, collecting current data at various locations on the material being cut in the target arc cutting device, and then obtaining a current data set; Extracting multiple local leakage currents in the stable arcing stage from the current data set, performing current decay simulation based on all the local leakage currents and the cutting current of the arc cutting device at the current moment, and then obtaining the fault point where the leakage current occurs, and determining the arc tracking resistance of the cut material through the time sequence characteristics of the current at the fault point; Obtain the flow velocity sequence of the shielding gas at the air outlet of the arc cutting device under various abnormal airflow conditions, and then determine the loss coefficient of the cutting efficiency of the target arc cutting device under the corresponding abnormal airflow condition according to each flow velocity sequence, and determine the diffusion degree of the slag in the shielding water at the fault point during the arc cutting process based on all the loss coefficients; A fault judgment tree is constructed when leakage occurs in the target arc cutting device according to the diffusion degree and the arc tracking resistance of the cut material, and the fault type of the leakage fault of the arc cutting device is judged by the impact signal when the arc is struck at the fault point and the fault judgment tree; adjusting the arc cutting operation of the target arc cutting device in real time based on the fault type; Among them, collecting current data at various locations on the cut material in the target arc cutting device to obtain a current data set specifically includes: first presetting multiple sampling points on the cut material, collecting the current value on the surface of the cut material at each sampling point according to a preset sampling interval, and then sorting all the current values ​​collected at each sampling point according to the order of collection, and then using all the obtained sequences as the current data of each sampling point respectively, and finally using the set of all the current data as the current data set.

2. The method according to claim 1, characterized in that Extracting a plurality of local leakage currents in the stable arcing stage from the current data set specifically comprises: Selecting a current data from the current data set as selected current data; determining an arc stabilization sequence during arc cutting according to the selected current data; Determining a stable arcing stage according to the arc stable sequence; Determine the local leakage current corresponding to the selected current data according to all current values ​​corresponding to the selected current data in the stable arcing stage; Continuing to determine the local leakage current corresponding to the residual current data in the current data set; Among them, determining the arc stability sequence in the arc cutting process according to the selected current data specifically includes: dividing the selected current data into multiple current components through a sampling window of a preset size, for each current component, determining the enhanced Dickey-Fuller test statistic of each current component, and using the enhanced Dickey-Fuller test statistic of each current component as the arc stability of each current component, and finally arranging all the arc stability according to the arrangement order of the corresponding current components in the selected current data, and using the obtained sequence as the arc stability sequence in the arc cutting process.

3. The method according to claim 1, characterized in that According to all the local leakage currents and the cutting current of the arc cutting device at the current moment, the current decay simulation is performed to obtain the fault points where the leakage current occurs, including: Obtain the cutting current of the arc cutting device at the current moment; Determining a current decay rate sequence according to the cutting current and all local leakage currents; Simulating the leakage current according to the current decay rate sequence to obtain the fault point where the leakage current occurs; Among them, simulating the leakage current according to the current decay rate sequence to obtain the fault point where the leakage current occurs specifically includes: fitting the current decay rate sequence into a curve through the Lagrange interpolation method, and taking the square root of the dependent variable value at the intersection of the curve and the vertical axis as the height of the fault point, and finally taking the point at the height directly above the arcing point at the current moment as the fault point where the leakage current occurs.

4. The method according to claim 1, characterized in that Determining the arc tracking resistance of the cut material by the time sequence characteristics of the current at the fault point specifically includes: Obtain leakage fault samples; Determining the timing characteristics of the current at the fault point; According to the time series characteristics, the historical current data at the fault point is divided into continuous leakage current data, transient leakage current data and normal current data; determining a current characteristic of the continuous leakage current data; determining a current characteristic of the transient leakage current data; determining a current characteristic of the normal current data; The arc tracking resistance of the cut material is determined according to the current characteristics of the continuous leakage current data, the current characteristics of the transient leakage current data and the current characteristics of the normal current data.

5. The method according to claim 1, characterized in that The loss coefficient of cutting efficiency of the target arc cutting device under the corresponding abnormal airflow state is determined according to each flow rate sequence, specifically including: Obtain leakage fault samples; Selecting an abnormal airflow state as a selected airflow state; Determine the fault type of each flow rate value in the flow rate sequence corresponding to the selected airflow state according to the leakage fault sample; Determine the loss coefficient of cutting efficiency of the target arc cutting device under the selected airflow state according to all fault types; Continue to determine the loss coefficient of cutting efficiency of the target arc cutting device under the abnormal residual airflow state.

6. The method according to claim 1, characterized in that The fault judgment tree when leakage occurs in the target arc cutting device is constructed according to the diffusion and the arc tracking resistance of the cut material, specifically including: Determine a plurality of first-level judgment nodes according to the diffusion degree and the arc tracking resistance of the cut material; Determine multiple secondary judgment nodes according to the node types of all the primary judgment nodes; All the first-level judgment nodes and all the second-level judgment nodes form a fault judgment tree when leakage occurs in the target arc cutting device.

7. The method according to claim 1, characterized in that The real-time adjustment of the arc cutting operation of the target arc cutting device based on the fault type specifically includes: If the fault type is no fault, the subsequent arc cutting work of the arc cutting device is not adjusted; If the fault type is a transient fault caused by slag, the flow rate of the shielding gas at the air outlet of the arc cutting device is temporarily increased, and the flow rate of the shielding gas is restored after the transient fault is eliminated; If the fault type is a persistent fault caused by other factors, the power supply of the arc cutting device is immediately interrupted and an alarm is issued.

8. An arc cutting device based on intelligent numerical control, which uses the method described in any one of claims 1 to 7 to perform arc cutting, and the arc cutting device based on intelligent numerical control includes a fault judgment unit, characterized in that: The fault judgment unit comprises: A collection module is used to collect current data at various locations on the material being cut in the target arc cutting device after the arc cutting device is started, thereby obtaining a current data set; a processing module, for extracting a plurality of local leakage currents in a stable arcing stage from the current data set, performing current decay simulation according to all the local leakage currents and the cutting current of the arc cutting device at the current moment, and then obtaining a fault point where the leakage current occurs, and determining the arc tracking resistance of the cut material through the time sequence characteristics of the current at the fault point; The processing module is also used to obtain the flow rate sequence of the protective gas at the air outlet of the arc cutting device under various abnormal airflow conditions, and then determine the loss coefficient of the cutting efficiency of the target arc cutting device under the corresponding abnormal airflow condition according to each flow rate sequence, and determine the diffusion degree of the slag in the protective water at the fault point during the arc cutting process based on all the loss coefficients; The processing module is also used to construct a fault judgment tree when leakage occurs in the target arc cutting device according to the diffusion degree and the arc tracking resistance of the cut material, and judge the fault type of the leakage fault of the arc cutting device through the impact signal when the arc is struck at the fault point and the fault judgment tree; An execution module is used to adjust the arc cutting work of the target arc cutting device in real time based on the fault type.

9. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores codes, and the processor is configured to obtain the codes and execute the arc cutting method based on intelligent numerical control as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the arc cutting method based on intelligent numerical control as described in any one of claims 1 to 7 is implemented.

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