An online monitoring and control system for arc additive manufacturing

Abstract

The present invention belongs to the field of arc additive manufacturing and relates to data analysis technology. It is used to solve the problem that the arc additive manufacturing online monitoring and control system in the prior art cannot optimize and analyze the processing parameters of the arc additive manufacturing by combining the operation monitoring parameters and the quality assessment results. Specifically, it is an arc additive manufacturing online monitoring and control system, including a manufacturing monitoring module, a quality assessment module and a control optimization module; the manufacturing monitoring module is used to perform operation monitoring of the arc additive manufacturing process; the quality assessment module is used to perform quality monitoring, assessment and analysis of the arc additive manufacturing workpiece; the control optimization module is used to perform control optimization analysis of the arc additive manufacturing process; the present invention can perform operation monitoring of the arc additive manufacturing process, obtain molten pool parameters by time-divided monitoring during the manufacturing process, and provide feedback and evaluation on the operation status of the arc additive manufacturing process through operation performance values ​​and operation stability values.

Description

Technical Field

[0001] The invention belongs to the field of arc additive manufacturing, relates to data analysis technology, and specifically is an online monitoring and control system for arc additive manufacturing. Background Art

[0002] Additive manufacturing is a manufacturing method that involves layering and slicing a three-dimensional digital model and then accumulating materials layer by layer along a pre-planned path. It has great advantages in the manufacturing of complex structural parts. Arc additive manufacturing is an additive manufacturing technology that uses electric arc as a heat source. It is a manufacturing method that melts metal wire or powder and accumulates metal parts layer by layer.

[0003] The arc additive manufacturing online monitoring and control system in the prior art can only control the processing parameters of the arc additive manufacturing during the manufacturing process, but cannot detect and evaluate the operating status of the manufacturing process and the processing quality of the produced workpieces after the manufacturing process is completed, resulting in the inability to guarantee the processing quality of the workpieces. At the same time, it is impossible to optimize and analyze the processing parameters of the arc additive manufacturing by combining the operating monitoring parameters and the quality evaluation results to improve the quality of the workpieces produced subsequently.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The object of the present invention is to provide an arc additive manufacturing online monitoring and control system, which is used to solve the problem that the arc additive manufacturing online monitoring and control system in the prior art cannot optimize and analyze the processing parameters of the arc additive manufacturing by combining the operation monitoring parameters with the quality assessment results;

[0006] The technical problem to be solved by the present invention is: how to provide an online monitoring and control system for arc additive manufacturing that can optimize and analyze the processing parameters of arc additive manufacturing by combining operation monitoring parameters and quality assessment results.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] An arc additive manufacturing online monitoring and control system comprises a manufacturing monitoring module, a quality assessment module and a control optimization module, wherein the manufacturing monitoring module, the quality assessment module and the control optimization module are sequentially connected in communication;

[0009] The manufacturing monitoring module is used to monitor the operation of the arc additive manufacturing process: mark the arc additive manufacturing process as a monitoring process, divide the monitoring process into a number of monitoring periods, obtain the melting temperature data RW and the melt gauge data RC of the monitoring period, and obtain the operation coefficient YX of the monitoring period by numerically calculating the melting temperature data RW and the melt gauge data RC; mark the monitoring process as a normal process or an abnormal process through the operation coefficient YX; and send the normal process to the quality assessment module;

[0010] The quality assessment module is used to perform quality monitoring, assessment and analysis on the workpiece manufactured by the arc additive manufacturing: marking the workpiece produced by the normal process as the analysis object, obtaining the quality coefficient ZL of the analysis object; marking the normal process corresponding to the analysis object as a qualified process or an abnormal process through the quality coefficient ZL; and sending the qualified process to the control optimization module;

[0011] The control optimization module is used to perform control optimization analysis on the arc additive manufacturing process.

[0012] As a preferred embodiment of the present invention, the process of acquiring the melt temperature data RW includes: acquiring the melt pool temperature value in real time during the monitoring period, retrieving the melt pool temperature range, marking the average value of the maximum value and the minimum value of the melt pool temperature range as the melt pool temperature scale value, marking the absolute value of the difference between the melt pool temperature value and the melt pool temperature scale value as the temperature deviation value, and marking the maximum value of the temperature deviation value during the monitoring period as the melt temperature data RW of the monitoring period; the process of acquiring the melt scale data RC includes: acquiring the melt pool size value in real time, retrieving the melt pool size range, marking the average value of the maximum value and the minimum value of the melt pool size range as the melt pool scale value, marking the absolute value of the difference between the melt pool size value and the melt pool scale value as the size deviation value, and marking the maximum value of the size deviation value during the monitoring period as the melt scale data RC of the monitoring period.

[0013] As a preferred embodiment of the present invention, the specific process of marking the monitoring process as a normal process or an abnormal process includes: summing and averaging the operating coefficient YX of all monitoring time periods in the monitoring process to obtain an operating performance value, calculating the variance of the operating coefficient YX of all monitoring time periods in the monitoring process to obtain an operating stability value, and comparing the operating performance value and the operating stability value with the preset operating performance threshold and operating stability threshold respectively: if the operating performance value is less than the operating performance threshold and the operating stability value is less than the operating stability threshold, it is determined that the manufacturing state of the monitoring process meets the requirements, and the monitoring process is marked as a normal process; otherwise, it is determined that the manufacturing state of the monitoring process does not meet the requirements, and the monitoring process is marked as an abnormal process.

[0014] As a preferred embodiment of the present invention, the process of obtaining the quality coefficient ZL of the analysis object includes: obtaining the pore data QK, crack data LW and shrinkage data SK of the analysis object, the pore data QK is the number of pores inside the analysis object, the crack data LW is the number of cracks in the analysis object, and the shrinkage data SK is the number of shrinkage pores inside the analysis object; the quality coefficient ZL of the analysis object is obtained by numerically calculating the pore data QK, crack data LW, shrinkage data SK and the volume value of the analysis object.

[0015] As a preferred embodiment of the present invention, the specific process of marking the normal process corresponding to the analysis object as a qualified process or an abnormal process includes: comparing the quality coefficient ZL of the analysis object with the preset quality threshold ZLmax: if the quality coefficient ZL is less than the quality threshold ZLmax, it is determined that the production quality of the analysis object meets the requirements, and the corresponding normal process is marked as a qualified process; if the quality coefficient ZL is greater than or equal to the quality threshold ZLmax, the corresponding normal process is marked as an abnormal process.

[0016] As a preferred embodiment of the present invention, the specific process of the control optimization module performing control optimization analysis on the arc additive manufacturing process includes: generating an optimization cycle, obtaining the metal wire diameter values ​​of all qualified processes during the operation within the optimization cycle, forming a wire diameter range by the maximum and minimum values ​​of the metal wire diameter values, dividing the wire diameter range into several wire diameter intervals, marking the operation performance value of the qualified process as YB, and obtaining the optimization coefficient YH of the qualified process through the formula YH=γ1*YB+γ2*ZL, and marking the optimization process within the wire diameter interval and the optimization range of the manufacturing parameters through the optimization coefficient YH.

[0017] As a preferred embodiment of the present invention, the specific process of marking the optimization process and the manufacturing parameter optimization range within the wire diameter interval includes: marking the qualified process whose metal wire diameter value is within the wire diameter interval as the matching process of the wire diameter interval, marking the L1 matching processes with the smallest optimization coefficient YH value within the wire diameter interval as the optimization process of the wire diameter interval, forming the wire feeding speed optimization range of the wire diameter interval by the minimum wire feeding speed and the maximum wire feeding speed in the optimization process, forming the printing speed optimization range of the wire diameter interval by the maximum printing speed and the minimum printing speed in the optimization process, forming the current optimization range of the wire diameter interval by the maximum current and the minimum current in the optimization process, forming the voltage optimization range of the wire diameter interval by the maximum voltage and the minimum voltage in the optimization process, marking the wire feeding speed optimization range, the printing speed optimization range, the current optimization range and the voltage optimization range of the wire diameter interval as the manufacturing parameter optimization range of the wire diameter interval; when the arc additive manufacturing is performed next time, first obtain the wire diameter value of the metal wire, call the manufacturing parameter optimization range of the wire diameter interval corresponding to the wire diameter value, and set the processing parameters of the arc additive manufacturing within the corresponding optimization ranges.

[0018] As a preferred embodiment of the present invention, the working method of the arc additive manufacturing online monitoring and control system comprises the following steps:

[0019] Step 1: Monitor the operation of the arc additive manufacturing process: mark the arc additive manufacturing process as a monitoring process, divide the monitoring process into several monitoring periods, obtain the melting temperature data RW and the melting ruler data RC of the monitoring period, and perform numerical calculations to obtain the operation performance value and the operation stability value, and mark the monitoring process as a normal process or an abnormal process according to the operation performance value and the operation stability value;

[0020] Step 2: Perform quality monitoring, evaluation and analysis on the arc additive manufacturing workpiece: mark the workpiece produced by the normal process as the analysis object, obtain the pore data QK, crack data LW and shrinkage data SK of the analysis object, and perform numerical calculations to obtain the quality coefficient ZL. The normal process is marked as a qualified process or an abnormal process by the quality coefficient ZL;

[0021] Step 3: Control optimization analysis of the arc additive manufacturing process: Generate an optimization cycle, obtain the wire diameter values ​​of all qualified processes in the optimization cycle during operation, and divide the wire diameter range into several wire diameter intervals by the maximum and minimum values ​​of the wire diameter. Mark the optimization process and manufacturing parameter optimization range within the wire diameter interval.

[0022] The present invention has the following beneficial effects:

[0023] 1. The manufacturing monitoring module can monitor the operation of the arc additive manufacturing process. During the manufacturing process, the molten pool parameters can be obtained by monitoring in different time periods, so as to analyze and calculate the operation performance value and operation stability value according to the molten pool parameters. The operation status of the arc additive manufacturing process can be fed back and evaluated through the operation performance value and operation stability value, and the monitoring process can be marked differently;

[0024] 2. The quality assessment module can be used to monitor and evaluate the quality of arc additive manufacturing workpieces. The quality coefficient is obtained by collecting and analyzing multiple quality parameters of the workpiece. The overall manufacturing quality of the workpiece is fed back based on the quality coefficient, so as to further differentiate the normal process. The manufacturing parameters of the qualified process provide data support for the parameter optimization analysis process.

[0025] 3. The control optimization module can be used to perform control optimization analysis on the arc additive manufacturing process, calculate the operating performance value and quality coefficient of the qualified process to obtain the optimization coefficient, and then divide the wire diameter range according to the metal wire diameter value, mark the optimization process of each wire diameter range and the manufacturing parameter optimization range, and optimize the arc additive manufacturing processing parameters according to the manufacturing parameter optimization range in the subsequent manufacturing process. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 paying creative work.

[0027] Figure 1 is a system block diagram of Embodiment 1 of the present invention;

[0028] Figure 2 This is a flow chart of the method of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0029] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than 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.

[0030] Embodiment 1

[0031] like Figure 1 As shown, an arc additive manufacturing online monitoring and control system includes a manufacturing monitoring module, a quality assessment module and a control optimization module, and the manufacturing monitoring module, the quality assessment module and the control optimization module are communicatively connected in sequence.

[0032] The manufacturing monitoring module is used to monitor the operation of the arc additive manufacturing process: the arc additive manufacturing process is marked as a monitoring process, the monitoring process is divided into several monitoring periods, and the melting temperature data RW and the melting scale data RC of the monitoring period are obtained. The process of obtaining the melting temperature data RW includes: obtaining the molten pool temperature value in real time during the monitoring period, calling the molten pool temperature range, marking the average value of the maximum value and the minimum value of the molten pool temperature range as the molten pool temperature scale value, marking the absolute value of the difference between the molten pool temperature value and the molten pool temperature scale value as the temperature deviation value, and marking the maximum value of the temperature deviation value in the monitoring period as the melting temperature data RW of the monitoring period; the process of obtaining the melting scale data RC includes: obtaining the molten pool size value in real time, calling the molten pool size range, marking the average value of the maximum value and the minimum value of the molten pool size range as the molten pool scale value, marking the absolute value of the difference between the molten pool size value and the molten pool scale value as the size deviation value, and marking the maximum value of the size deviation value in the monitoring period as the melting scale data RC of the monitoring period; the operation coefficient Y of the monitoring period is obtained by the formula YX=α1*RW+α2*RC X, where α1 and α2 are both proportional coefficients, and α1>α2>1; the operation coefficients YX of all monitoring periods in the monitoring process are summed and averaged to obtain the operation performance value, the variance of the operation coefficients YX of all monitoring periods in the monitoring process is calculated to obtain the operation stability value, and the operation performance value and the operation stability value are compared with the preset operation performance threshold and the operation stability threshold respectively: if the operation performance value is less than the operation performance threshold and the operation stability value is less than the operation stability threshold, it is determined that the manufacturing state of the monitoring process meets the requirements, and the monitoring process is marked as a normal process; otherwise, it is determined that the manufacturing state of the monitoring process does not meet the requirements, and the monitoring process is marked as an abnormal process; the normal process is sent to the quality assessment module; the arc additive manufacturing process is operated and monitored, and the molten pool parameters are obtained by monitoring in time periods in the middle of the manufacturing process, so as to analyze and calculate the operation performance value and the operation stability value according to the molten pool parameters, and the operation state of the arc additive manufacturing process is fed back and evaluated through the operation performance value and the operation stability value, and the monitoring process is marked differentially.

[0033] The quality assessment module is used to perform quality monitoring, assessment and analysis on arc additive manufacturing workpieces: mark the workpieces obtained in the normal process as the analysis object, and obtain the pore data QK, crack data LW and shrinkage data SK of the analysis object through permanent magnetic disturbance detection technology and laser ultrasonic detection technology. The pore data QK is the number of pores inside the analysis object, the crack data LW is the number of cracks in the analysis object, and the shrinkage data SK is the number of shrinkage pores inside the analysis object; the quality coefficient ZL of the analysis object is obtained by the formula ZL=(β1*QK+β2*LW+β3*SK) / TJ, where β1, β2 and β3 are all proportional coefficients, and β1>β2>β3>1, and TJ is the volume value of the analysis object; the analysis object is The quality coefficient ZL of the object is compared with the preset quality threshold ZLmax: if the quality coefficient ZL is less than the quality threshold ZLmax, it is determined that the production quality of the analyzed object meets the requirements, and the corresponding normal process is marked as a qualified process; if the quality coefficient ZL is greater than or equal to the quality threshold ZLmax, the corresponding normal process is marked as an abnormal process; the qualified process is sent to the control optimization module; quality monitoring, evaluation and analysis are performed on the arc additive manufacturing workpiece, and the quality coefficient is obtained by collecting and analyzing multiple quality parameters of the workpiece. According to the quality coefficient, the overall manufacturing quality of the workpiece is fed back, so as to further differentiate the normal process, and provide data support for the parameter optimization analysis process through the manufacturing parameters of the qualified process.

[0034] The control optimization module is used to perform control optimization analysis on the arc additive manufacturing process: generate an optimization cycle, obtain the wire diameter values ​​of all qualified processes in the optimization cycle during operation, form the wire diameter range by the maximum and minimum values ​​of the wire diameter value, divide the wire diameter range into several wire diameter intervals, mark the operation performance value of the qualified process as YB, and obtain the optimization coefficient YH of the qualified process through the formula YH=γ1*YB+γ2*ZL, where γ1 and γ2 are both proportional coefficients, and γ1>γ2>1; mark the qualified process whose wire diameter value is within the wire diameter interval as the matching process of the wire diameter interval, mark the L1 matching processes with the smallest optimization coefficient YH value within the wire diameter interval as the optimization process of the wire diameter interval, form the wire feeding speed optimization range of the wire diameter interval by the minimum wire feeding speed and the maximum wire feeding speed in the optimization process, form the printing speed optimization range of the wire diameter interval by the maximum printing speed and the minimum printing speed in the optimization process, and The maximum and minimum current values ​​in the optimization process constitute the current optimization range of the wire diameter interval, the maximum and minimum voltage values ​​in the optimization process constitute the voltage optimization range of the wire diameter interval, and the wire feeding speed optimization range, printing speed optimization range, current optimization range and voltage optimization range in the wire diameter interval are marked as the manufacturing parameter optimization range of the wire diameter interval; when the arc additive manufacturing is performed next time, the wire diameter value of the metal wire is first obtained, and the manufacturing parameter optimization range of the wire diameter interval corresponding to the wire diameter value is called, and the processing parameters of the arc additive manufacturing are set within the corresponding optimization ranges; the arc additive manufacturing process is controlled and optimized, and the operation performance value and quality coefficient of the qualified process are calculated to obtain the optimization coefficient, and then the wire diameter interval is divided according to the metal wire diameter value, and the optimization process and manufacturing parameter optimization range of each wire diameter interval are marked, and the arc additive manufacturing processing parameters are optimized and controlled according to the manufacturing parameter optimization range in the subsequent manufacturing process.

[0035] Embodiment 2

[0036] like Figure 2 As shown, an arc additive manufacturing online monitoring and control method comprises the following steps:

[0037] Step 1: Monitor the operation of the arc additive manufacturing process: mark the arc additive manufacturing process as a monitoring process, divide the monitoring process into several monitoring periods, obtain the melting temperature data RW and the melting ruler data RC of the monitoring period, and perform numerical calculations to obtain the operation performance value and the operation stability value, and mark the monitoring process as a normal process or an abnormal process according to the operation performance value and the operation stability value;

[0038] Step 2: Perform quality monitoring, evaluation and analysis on the arc additive manufacturing workpiece: mark the workpiece produced by the normal process as the analysis object, obtain the pore data QK, crack data LW and shrinkage data SK of the analysis object, and perform numerical calculations to obtain the quality coefficient ZL. The normal process is marked as a qualified process or an abnormal process by the quality coefficient ZL;

[0039] Step 3: Control optimization analysis of the arc additive manufacturing process: Generate an optimization cycle, obtain the wire diameter values ​​of all qualified processes in the optimization cycle during operation, and divide the wire diameter range into several wire diameter intervals by the maximum and minimum values ​​of the wire diameter. Mark the optimization process and manufacturing parameter optimization range within the wire diameter interval.

[0040] An arc additive manufacturing online monitoring and control system, when working, marks the arc additive manufacturing process as a monitoring process, divides the monitoring process into several monitoring time periods, obtains melting temperature data RW and melt gauge data RC in the monitoring time period, performs numerical calculation to obtain operation performance value and operation stability value, and marks the monitoring process as a normal process or an abnormal process through the operation performance value and operation stability value; marks the workpiece produced by the normal process as an analysis object, obtains pore data QK, crack data LW and shrinkage data SK of the analysis object, performs numerical calculation to obtain quality coefficient ZL, and marks the normal process as a qualified process or an abnormal process through the quality coefficient ZL; generates an optimization cycle, obtains metal wire diameter values ​​of all qualified processes in the optimization cycle during operation, forms a wire diameter range by the maximum and minimum values ​​of the metal wire diameter value, divides the wire diameter range into several wire diameter intervals, and marks the optimization process and manufacturing parameter optimization range within the wire diameter interval.

[0041] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0042] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the real value. The coefficients in the formula are set by technicians in this field according to the actual situation; for example: formula ZL = (β1*QK+β2*LW+β3*SK) / TJ; technicians in this field collect multiple groups of sample data and set corresponding quality coefficients for each group of sample data; substitute the set quality coefficients and the collected sample data into the formula, any three formulas constitute a three-variable linear equation group, screen the calculated coefficients and take the average, and obtain the values ​​of β1, β2 and β3 as 3.25, 2.63 and 2.12 respectively;

[0043] The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding quality coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the quality coefficient is proportional to the value of the pore data.

[0044] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0045] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An arc additive manufacturing online monitoring and control system, characterized in that: It includes a manufacturing monitoring module, a quality assessment module and a control optimization module, wherein the manufacturing monitoring module, the quality assessment module and the control optimization module are sequentially connected in communication; The manufacturing monitoring module is used to monitor the operation of the arc additive manufacturing process: marking the arc additive manufacturing process as a monitoring process, dividing the monitoring process into a plurality of monitoring periods, obtaining the melting temperature data RW and the melt gauge data RC of the monitoring period, and obtaining the operation coefficient YX of the monitoring period by numerically calculating the melting temperature data RW and the melt gauge data RC; The monitoring process is marked as a normal process or an abnormal process through the operation coefficient YX; Send the normal process to the quality assessment module; The quality assessment module is used to perform quality monitoring, assessment and analysis on the arc additive manufacturing workpiece: marking the workpiece produced by the normal process as the analysis object, obtaining the quality coefficient ZL of the analysis object; marking the normal process corresponding to the analysis object as a qualified process or an abnormal process according to the quality coefficient ZL; Send qualified processes to the control optimization module; The control optimization module is used to perform control optimization analysis on the arc additive manufacturing process; The process of acquiring the melt temperature data RW includes: acquiring the melt pool temperature value in real time during the monitoring period, calling the melt pool temperature range, marking the average value of the maximum value and the minimum value of the melt pool temperature range as the melt pool temperature scale value, marking the absolute value of the difference between the melt pool temperature value and the melt pool temperature scale value as the temperature deviation value, and marking the maximum value of the temperature deviation value during the monitoring period as the melt temperature data RW of the monitoring period; the process of acquiring the melt scale data RC includes: acquiring the melt pool size value in real time, calling the melt pool size range, marking the average value of the maximum value and the minimum value of the melt pool size range as the melt pool scale value, marking the absolute value of the difference between the melt pool size value and the melt pool scale value as the size deviation value, and marking the maximum value of the size deviation value during the monitoring period as the melt scale data RC of the monitoring period; The specific process of marking the monitoring process as a normal process or an abnormal process includes: summing and averaging the operation coefficients YX of all monitoring periods in the monitoring process to obtain an operation performance value, performing variance calculation on the operation coefficients YX of all monitoring periods in the monitoring process to obtain an operation stability value, and comparing the operation performance value and the operation stability value with the preset operation performance threshold and the operation stability threshold respectively: if the operation performance value is less than the operation performance threshold and the operation stability value is less than the operation stability threshold, it is determined that the manufacturing state of the monitoring process meets the requirements, and the monitoring process is marked as a normal process; otherwise, it is determined that the manufacturing state of the monitoring process does not meet the requirements, and the monitoring process is marked as an abnormal process; The process of obtaining the quality coefficient ZL of the analysis object includes: obtaining pore data QK, crack data LW and shrinkage data SK of the analysis object, where the pore data QK is the number of pores inside the analysis object, the crack data LW is the number of cracks in the analysis object, and the shrinkage data SK is the number of shrinkage pores inside the analysis object; and obtaining the quality coefficient ZL of the analysis object by numerically calculating the pore data QK, the crack data LW, the shrinkage data SK and the volume value of the analysis object; The specific process of marking the normal process corresponding to the analysis object as a qualified process or an abnormal process includes: comparing the quality coefficient ZL of the analysis object with the preset quality threshold ZLmax: if the quality coefficient ZL is less than the quality threshold ZLmax, it is determined that the production quality of the analysis object meets the requirements, and the corresponding normal process is marked as a qualified process; if the quality coefficient ZL is greater than or equal to the quality threshold ZLmax, the corresponding normal process is marked as an abnormal process; The specific process of the control optimization module for control optimization analysis of the arc additive manufacturing process includes: generating an optimization cycle, obtaining the metal wire diameter values ​​of all qualified processes in the optimization cycle during operation, forming a wire diameter range by the maximum and minimum values ​​of the metal wire diameter values, dividing the wire diameter range into several wire diameter intervals, marking the operation performance value of the qualified process as YB, and obtaining the optimization coefficient YH of the qualified process through the formula YH=γ1*YB+γ2*ZL, wherein γ1 and γ2 are both proportional coefficients, and γ1>γ2>1, and marking the optimization process in the wire diameter interval and the optimization range of the manufacturing parameters through the optimization coefficient YH; The specific process of marking the optimization process and the manufacturing parameter optimization range within the wire diameter interval includes: marking the qualified process whose metal wire diameter value is within the wire diameter interval as the matching process of the wire diameter interval, marking the L1 matching processes with the smallest optimization coefficient YH value within the wire diameter interval as the optimization process of the wire diameter interval, forming the wire feeding speed optimization range of the wire diameter interval by the minimum wire feeding speed and the maximum wire feeding speed in the optimization process, forming the printing speed optimization range of the wire diameter interval by the maximum printing speed and the minimum printing speed in the optimization process, forming the current optimization range of the wire diameter interval by the maximum current and the minimum current in the optimization process, forming the voltage optimization range of the wire diameter interval by the maximum voltage and the minimum voltage in the optimization process, marking the wire feeding speed optimization range, the printing speed optimization range, the current optimization range and the voltage optimization range of the wire diameter interval as the manufacturing parameter optimization range of the wire diameter interval; when the arc additive manufacturing is performed next time, first obtain the wire diameter value of the metal wire, call the manufacturing parameter optimization range of the wire diameter interval corresponding to the wire diameter value, and set the processing parameters of the arc additive manufacturing within the corresponding optimization ranges.

2. The arc additive manufacturing online monitoring and control system according to claim 1, characterized in that: The working method of the arc additive manufacturing online monitoring and control system comprises the following steps: Step 1: Monitor the operation of the arc additive manufacturing process: mark the arc additive manufacturing process as a monitoring process, divide the monitoring process into several monitoring periods, obtain the melting temperature data RW and the melting ruler data RC of the monitoring period, and perform numerical calculations to obtain the operation performance value and the operation stability value, and mark the monitoring process as a normal process or an abnormal process according to the operation performance value and the operation stability value; Step 2: Perform quality monitoring, evaluation and analysis on the arc additive manufacturing workpiece: mark the workpiece produced by the normal process as the analysis object, obtain the pore data QK, crack data LW and shrinkage data SK of the analysis object, and perform numerical calculations to obtain the quality coefficient ZL. The normal process is marked as a qualified process or an abnormal process by the quality coefficient ZL; Step 3: Control optimization analysis of the arc additive manufacturing process: Generate an optimization cycle, obtain the wire diameter values ​​of all qualified processes in the optimization cycle during operation, and divide the wire diameter range into several wire diameter intervals by the maximum and minimum values ​​of the wire diameter. Mark the optimization process and manufacturing parameter optimization range within the wire diameter interval.

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