Method for formulating welding process characteristic curve of high-strength austenitic stainless steel

Abstract

The invention relates to the technical field of automatic welding, in particular to a high-strength austenitic stainless steel welding process characteristic curve making method which comprises the following specific steps: S1, selecting a welding process characteristic curve according to parameters corresponding to a common stainless steel weldment; s2, re-calibrating peak energy; s3, reformulating a pulse waveform; and S4, based on an arc length prediction formula of the pulse parameters and the wire feeding speed, calculating to obtain a base value current and a pulse frequency. According to the method, the pulse welding waveform is adjusted and optimized, the single pulse energy distribution in the welding process is modified, the pulse waveform special for the high-strength austenitic welding wire is formed, the special welding process characteristic curve customized for the high-strength austenitic stainless steel welding material is invented, and then the welding manufacturability and the molten pool spreadability of the high-strength austenitic stainless steel are optimized.

Description

Technical Field

[0001] The invention relates to the technical field of automated welding, and in particular to a method for formulating a high-strength austenitic stainless steel welding process characteristic curve. Background Art

[0002] With the in-depth implementation of the strategy of building a strong manufacturing country, the high-quality development of high-end equipment urgently requires new welding materials and welding technologies. Compared with conventional gas metal arc welding, the welding current of pulsed gas metal arc welding (P-GMAW) changes periodically: during the pulse peak, the peak current briefly exceeds the critical current of the jet transition, causing the welding wire to melt rapidly and form a droplet transition trend, and the current is reduced before the next droplet is formed, using a lower base current to maintain arc connectivity and continuously heat the welding wire. By periodically adjusting the current, P-GMAW can achieve autonomous and controllable droplet transition when the average welding current is lower than the critical current of the jet, and the energy input of the welding process can be accurately and effectively controlled by adjusting and matching multiple pulse parameters.

[0003] However, in order to achieve more accurate control of the heat input and droplet transfer process of the welding process, P-GMAW introduces a large number of pulse parameters. These complex and mutually coupled pulse parameters enhance the flexibility of current regulation on the one hand, but on the other hand, they also greatly increase the learning cost of P-GMAW. Constructing a dedicated unified welding process characteristic curve for the same type of welding wire is an effective way to achieve widespread application of P-GMAW.

[0004] High-strength austenitic stainless steel has high strength, excellent corrosion resistance and low magnetic properties, and has broad application prospects in the fields of shipbuilding, nuclear power and chemical industry. Compared with ordinary 316L stainless steel, the new high-strength austenitic stainless steel has a higher alloying element content and is more difficult to weld, mainly manifested in process problems such as large welding spatter, poor molten pool spread, and difficult droplet transition, which restricts its promotion and application.

[0005] The reason is that compared with ordinary austenitic stainless steel, the new high-strength austenitic stainless steel and its supporting welding materials have a higher alloy content, and the physical and chemical properties of the welding wire are quite different, which does not match the welding process characteristic curve built into the existing welding power supply. The existing welding process adjustment method is based on the existing welding process characteristic curve, which can only modify the average welding current and welding voltage. The essence of the pulse welding waveform is not touched, and the pulse energy cannot be controlled. There are process problems such as large welding spatter, poor molten pool spread, and difficulty in side fusion, which greatly hinder the promotion and application of high-strength austenitic stainless steel.

[0006] Publication No.: CN110369837A A welding process for super duplex stainless steel and super austenitic stainless steel adopts a combined welding method of TIG root welding and GMAW-P filling and capping welding, which optimizes the process parameters such as current, voltage, welding speed, heat input, etc. in each welding process, so as to ensure the weld metal requirements. However, the adjustment method of the process has a large parameter range, which is difficult to achieve precise control, and is prone to defects such as too large or too small heat-affected zone, molten pool splashing and pores.

[0007] Therefore, it is urgent to propose a new method for formulating high-strength austenitic stainless steel welding process characteristic curve to solve the above problems. Summary of the invention

[0008] In view of this, the present invention aims to propose a method for formulating a high-strength austenitic stainless steel welding process characteristic curve to solve the problems of large welding spatter, poor molten pool spread and difficult side fusion in the existing high-strength austenitic stainless steel welding.

[0009] For P-GMAW, the energy input mainly comes from the peak stage. If you want the welding process to achieve a stable pulse-by-drop transition, you need to match the amount of molten metal formed by each pulse and its gravity, electromagnetic necking force and surface tension. The molten metal stably grows into a spherical droplet with a diameter of 1.2 times that of the welding wire and quickly detaches from the end of the welding wire and transitions downward under the action of the electromagnetic force, without excess molten metal following the droplet.

[0010] Due to the higher content of Cr, Ni and Mn, the thermal enthalpy and molten metal viscosity of high-strength austenitic stainless steel welding wire are higher than those of conventional welding wire. In addition, the higher Mn content also leads to higher surface tension of the molten metal. This is the reason why the droplet transfer of high-strength austenitic stainless steel welding wire is difficult.

[0011] In order to improve the processability and welding efficiency of high-strength austenitic stainless steel welding materials, the pulse waveform parameters are optimized for high-strength austenitic stainless steel welding wire based on its physical and chemical properties, and the arc pressure, droplet momentum, etc. in the welding process are refined and adjusted to form a special pulse welding current waveform, which is further promoted to become a special welding process characteristic curve, thereby optimizing the welding processability of high-strength austenitic stainless steel welding wire.

[0012] Conventional high-strength austenitic stainless steel welding process characteristic curve formulation methods mostly achieve high-strength austenitic stainless steel welding by adjusting welding current, voltage, wire feed speed, welding speed and other parameters. This method can directly observe the changes in welding effect by adjusting basic welding parameters, and the operation is simple and intuitive, but there is a large adjustment range of basic parameters, and it is difficult to achieve precise control. It is difficult to accurately control the heat input, which may cause the heat-affected zone to be too large or too small, affecting the mechanical properties of the weld, and it is difficult to accurately control the stability of the molten pool, which may cause defects such as spatter and pores.

[0013] In order to solve the above problems, this patent creatively adjusts and optimizes the pulse welding waveform, modifies the single pulse energy distribution of the welding process, forms a special pulse waveform for high-strength austenitic welding wire, and invents a special welding process characteristic curve customized for high-strength austenitic stainless steel welding materials, thereby optimizing the welding processability and molten pool spread of high-strength austenitic stainless steel.

[0014] The technical solution of the present invention is achieved in this way:

[0015] The present invention discloses a method for formulating a high-strength austenitic stainless steel welding process characteristic curve, comprising the following specific steps:

[0016] S1: Select the initial welding process characteristic curve; select the welding process characteristic curve according to the parameters corresponding to the ordinary stainless steel weldment as the initial reference;

[0017] S2: Recalibrate the peak energy; according to the characteristics of high-strength austenitic stainless steel, recalibrate the peak energy to ensure the reasonable distribution of energy during welding;

[0018] S3: Reformulate the pulse waveform; According to the material properties and welding requirements of high-strength austenitic stainless steel, the pulse waveform is reformulated to optimize the heat input and molten pool stability during welding;

[0019] S4: The base current and pulse frequency are calculated based on the arc length prediction formula of pulse parameters and wire feeding speed.

[0020] Further, in step S1 , the parameters of the weldment include thickness, geometry, joint type, weld position and wire diameter.

[0021] Furthermore, in step S2, calibrating the peak energy includes determining the optimal peak current and peak time. Based on the selected wire feeding speed and high-strength austenitic welding wire, a series of peak currents and peak times are selected within the welding current range, and the orthogonal test method is used for testing to determine the optimal peak current and peak time.

[0022] Furthermore, taking 11m / min as the base wire feeding speed, the peak current test range is 300A-500A, the adjustment step is 20A, the peak time range is 1.2ms-2.7ms, and the step is 0.1ms. Within the stable transition range, the peak current is 320-360A, and the peak time is 2.2-2.4ms, which is the optimal pulse parameter range.

[0023] Furthermore, in step S2, the best criteria for determining the peak current and peak time are that the molten droplets are separated one by one and cleanly.

[0024] Furthermore, in step S3, the pulse waveform is a rectangular wave, and the peak time is the peak time in step S2.

[0025] Further, in step S4, the arc length prediction formula based on pulse parameters and wire feeding speed is:

[0026] R 2 =0.9857

[0027] L=-12.22596+0.01552*I B +0.0354*I P +5.21194*t p -0.02577*f-

[0028] 0.97645*V

[0029] Where: L is the arc length;

[0030] I B is the base current, unit: A;

[0031] I P is the peak current, unit: A;

[0032] t p is the peak time, unit: ms;

[0033] f is the pulse frequency, unit: Hz;

[0034] V is the wire feeding speed, unit: m / min.

[0035] Furthermore, in step S4, the base current and pulse frequency are calculated as follows:

[0036] S41: Determine the welding wire diameter and wire feeding speed range;

[0037] S42: uniformly selecting multiple feature points within the wire feeding speed range;

[0038] S43: setting the welding arc length, peak current and peak time of each characteristic point;

[0039] S44: The base current and pulse frequency of each characteristic point are matched with the P-GMAW arc length prediction formula to obtain the overall welding process characteristic curve.

[0040] Furthermore, a 1.0mm diameter solid welding wire was selected, and the working range of the wire feeding speed was 5-15m / min. Six characteristic points were evenly selected within this range, and the welding arc length of each characteristic point was set to 7mm, the peak current was fixed to 340A, and the peak time was 2.3ms. The base current and pulse frequency of each characteristic point were matched with the help of the P-GMAW arc length prediction formula, and the overall welding process characteristic curve was obtained.

[0041] Furthermore, the method further includes step S5: verifying and optimizing the welding process characteristic curve, verifying the applicability of the characteristic curve and the welding quality through actual welding tests, and further optimizing the welding parameters according to the test results.

[0042] Compared with the prior art, the method for formulating a high-strength austenitic stainless steel welding process characteristic curve of the present invention has the following advantages:

[0043] 1. The present invention adjusts and optimizes the pulse welding waveform, modifies the single pulse energy distribution of the welding process, and forms a pulse waveform specifically for high-strength austenitic welding wire, thereby solving the problem that the adjustment range of basic parameters in the conventional formulation method is large and it is difficult to achieve precise control, and avoids process problems such as large welding spatter, poor molten pool spread, and difficulty in side fusion during the welding of high-strength austenitic stainless steel.

[0044] 2. The present invention invents a special welding process characteristic curve customized for high-strength austenitic stainless steel welding materials through creative experiments, thereby optimizing the welding processability and molten pool spread of high-strength austenitic stainless steel, reducing the learning cost of welding operators, and contributing to the promotion and application of high-strength austenitic stainless steel. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings:

[0046] Figure 1 It is the peak energy calibration record of the present invention;

[0047] Figure 2 This is a comparison diagram of the original pulse waveform of the present invention;

[0048] Figure 3 This is a rectangular waveform droplet transition state diagram of the present invention;

[0049] Figure 4 It is the exponential waveform droplet transition state diagram of the present invention;

[0050] Figure 5 This is a typical pulse waveform diagram after optimization of the present invention;

[0051] Figure 6 This is a diagram of the droplet transfer process after optimization of the present invention;

[0052] Figure 7 Comparison diagram of weld cross-section before and after adjustment of the present invention, (a) using the original pulse waveform and (b) using the optimized waveform;

[0053] Figure 8 It is a comparison diagram of the arc length prediction value and the measured value of the present invention;

[0054] Fig. 9 It is the molten droplet transition state diagram of each characteristic point of the present invention;

[0055] Fig.10 This is a diagram of the welding spatter collection method of the present invention;

[0056] Fig.11 This is a comparison diagram of welding spatter of the present invention;

[0057] Fig.12 This is a comparison chart of the splash weight of the present invention;

[0058] Fig.13 It is the electric signal recording diagram of the original characteristic curve welding process of the present invention;

[0059] Fig.14 The electrical signal recording diagram of the welding process of the optimized characteristic curve of the present invention;

[0060] Fig.15 The UI phase diagram of the present invention is compared, (a) is the characteristic curve using G3Si1, and (b) is the characteristic curve using the optimized process;

[0061] Fig.16 Comparison of welding morphologies of butt weld test plates of the present invention (a) (c) are butt weld morphologies using the G3Si1 characteristic curve, and (b) (d) are butt weld morphologies using the optimized characteristic curve;

[0062] Fig.17 Comparison of fillet weld morphology of the present invention: (a) is the fillet weld morphology using the G3Si1 characteristic curve, and (b) is the fillet weld morphology using the optimized characteristic curve;

[0063] Fig.18 Comparison of fillet weld morphology of the present invention: (a) is the fillet weld morphology using the G3Si1 characteristic curve, and (b) is the fillet weld morphology using the optimized characteristic curve. DETAILED DESCRIPTION

[0064] In order to make the technical means, objectives and effects of the present invention easy to understand, the embodiments of the present invention are described in detail below with reference to specific drawings.

[0065] It should be noted that all the terms used in the present invention to indicate directionality and position, such as "upper", "lower", "left", "right", "front", "back", "vertical", "horizontal", "inside", "outside", "top", "lower", "lateral", "longitudinal", "center", etc., are only used to explain the relative positional relationship and connection status between the components in a certain state, and are only for the convenience of describing the present invention, rather than requiring the present invention to be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the descriptions of "first", "second", etc. in the present invention are only used for descriptive purposes, and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features.

[0066] In the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0067] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" 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 may be combined in any one or more embodiments or examples in a suitable manner.

[0068] The welding process characteristic curve is a chart drawn through experimental data, which shows the relationship between various parameters in the welding process and the welding results.

[0069] In pulse welding, the welding current is calculated as the average current.

[0070] The present invention discloses a method for formulating a high-strength austenitic stainless steel welding process characteristic curve, comprising the following specific steps:

[0071] S1: Select the initial welding process characteristic curve; select the welding process characteristic curve according to the parameters corresponding to the ordinary stainless steel weldment as the initial reference;

[0072] S2: Recalibrate the peak energy; according to the characteristics of high-strength austenitic stainless steel, recalibrate the peak energy to ensure the reasonable distribution of energy during welding;

[0073] S3: Reformulate the pulse waveform; According to the material properties and welding requirements of high-strength austenitic stainless steel, the pulse waveform is reformulated to optimize the heat input and molten pool stability during welding;

[0074] S4: The base current and pulse frequency are calculated based on the arc length prediction formula of pulse parameters and wire feeding speed.

[0075] According to the parameters of the corresponding ordinary stainless steel weldment, the welding process characteristic curve is selected as an initial welding process characteristic curve as the starting point to provide a reference for subsequent optimization and adjustment; by recalibrating the peak energy and formulating the pulse waveform, better weld formation can be achieved, the unevenness and undercut of the weld can be reduced, sufficient penetration of the weld can be ensured, welding defects such as incomplete penetration and slag inclusion can be reduced, better molten pool control and weld formation can be achieved, and welding defects such as spatter and porosity can be reduced; using the arc length prediction formula, according to the pulse parameters and wire feeding speed, the appropriate base current and pulse frequency are calculated to ensure the stability of the arc and the controllability of the welding process.

[0076] This setting optimizes welding parameters by recalibrating peak energy, formulating pulse waveform, and calculating base current and pulse frequency. It can improve welding quality, production efficiency, and reduce welding defects. It is highly targeted, systematic, and scientific. It solves the process problems of difficult molten droplet transition of high-strength austenitic stainless steel wire when pulse metal electrode gas shielded welding of high-strength austenitic stainless steel, inability to control pulse energy, large welding spatter, poor molten pool spread, and difficulty in side fusion.

[0077] Specifically, in step S1 , the parameters of the weldment include thickness, geometry, joint type, weld position and welding wire diameter.

[0078] By comprehensively considering the thickness, geometry, joint type, weld position and wire diameter of the weldment, the welding parameters of ordinary stainless steel weldments with the same structure can be selected to ensure that the selection of welding parameters is more reasonable, ensure welding quality, production efficiency and reduce welding defects, provide a basic welding parameter setting for subsequent tests, and facilitate optimization and adjustment.

[0079] This setting can effectively reduce the number of subsequent tests and help reduce test costs.

[0080] Specifically, in step S2, calibrating the peak energy includes determining the optimal peak current and peak time. Based on the selected wire feeding speed and high-strength austenitic welding wire diameter, a series of peak currents and peak times are selected within the welding current range, and the orthogonal test method is used for testing to determine the optimal peak current and peak time.

[0081] By determining the peak current and peak time through a variety of test combinations, the shape and fluidity of the molten pool can be better controlled, smooth formation of the weld can be achieved, welding defects such as unevenness, undercut, incomplete penetration, cracks and slag inclusions can be reduced, the uniformity and aesthetics of the weld can be ensured, and the problem of difficult molten droplet transition of high-strength austenitic stainless steel welding wire can be solved.

[0082] This setting ensures that the selected peak current and peak time have a scientific basis through welding tests and data recording, improves the rationality and accuracy of welding parameters, ensures the welding quality of high-strength austenitic stainless steel, and improves welding efficiency.

[0083] Specifically, taking 11m / min as the benchmark wire feeding speed, the peak current test range is 300A-500A, the adjustment step is 20A, the peak time is gradually tested from low to high, with a step size of 0.1ms, the best transition and upper and lower boundaries, and the peak current of 320-360A is comprehensively selected within the stable transition range. The peak time of 2.2-2.4ms is the optimal pulse parameter range.

[0084] This setting determines the optimal peak current and peak time of high-strength austenitic stainless steel with a base wire feeding speed of 11m / min, reduces the labor of recalibrating the peak energy of high-strength austenitic stainless steel at this wire feeding speed, and helps to form the subsequent welding process characteristic curve.

[0085] Specifically, in step S2, the best criteria for determining the peak current and peak time are that the molten droplets are separated one by one and cleanly.

[0086] The molten droplets are separated drop by drop, which can ensure the stable transfer of the molten droplets, reduce the generation of spatter and pores, make the weld evenly formed, and reduce the unevenness, undercut and cracks of the weld.

[0087] This setting can effectively improve the forming quality of the weld, reduce welding defects, ensure the mechanical properties of the weld, and at the same time shorten the welding time and improve production efficiency.

[0088] Specifically, in step S3, the pulse waveform is a rectangular wave, and the peak time is the peak time in step S2.

[0089] The steep rising and falling edges of the rectangular wave can achieve rapid droplet transfer, reduce the time the droplet stays in the air, and thus reduce spatter. The high peak current of the rectangular wave can provide sufficient energy to ensure full penetration of the weld, reduce welding defects such as incomplete penetration and slag inclusion, and the short peak time of the rectangular wave can effectively control welding heat input, reduce welding deformation and the hardness of the heat-affected zone.

[0090] This setting can ensure the stability of the arc and the controllability of the welding process, reduce fluctuations in the welding process, reduce welding defects, shorten welding time, improve welding speed and quality, and improve production efficiency.

[0091] Specifically, in step S3, for a typical wire feeding speed of 11 m / min, the peak time is increased to 2.3 ms, the peak current is adjusted to 350 A, and the average weld width is increased from 8.15 mm to 8.92 mm based on the original rectangular waveform.

[0092] For a typical wire feeding speed of 11m / min, the droplet transfer process of rectangular pulse waveform and exponential pulse waveform is compared. Due to the high viscosity of the liquid metal of high-strength austenitic welding wire, the rectangular wave can better promote the droplet shedding;

[0093] Therefore, based on the original rectangular waveform, the peak time is increased to 2.3ms, and the peak current is adjusted to 350A. The droplet transition state is greatly improved. Its waveform and transition state are as follows: Figure 5 and Figure 6 At the same time, the extension of the pulse time increases the arc's action time on the molten pool, promotes the spread of the molten pool, and the average molten width increases from 8.15mm to 8.92mm.

[0094] In step S3, for a typical wire feeding speed of 11 m / min, the peak time is increased to 2.3 ms, the peak current is adjusted to 350 A, and the average weld width is increased from 8.15 mm to 8.92 mm based on the original rectangular waveform. This can optimize the molten droplet transfer, improve the penetration quality, improve the weld formation, reduce welding defects and improve the welding stability, which can ensure that the selection of welding parameters is more reasonable and improve the welding quality and production efficiency.

[0095] Specifically, in step S4, the arc length prediction formula based on pulse parameters and wire feeding speed is:

[0096] R 2 =0.9857

[0097] L=-12.22596+0.01552*I B +0.0354*I P +5.21194*t p -0.02577*f-

[0098] 0.97645*V

[0099] Where: L is the arc length;

[0100] I B is the base current, unit: A;

[0101] I P is the peak current, unit: A;

[0102] t p is the peak time, unit: ms;

[0103] f is the pulse frequency, unit: Hz;

[0104] V is the wire feeding speed, unit: m / min.

[0105] R 2 =0.9857 represents the coefficient of determination, which is used to measure the degree of fit of the model, that is, the proportion of the variation explained by the model to the total variation, R 2 The value range is between 0 and 1. The closer the value is to 1, the better the model fit is. 2 = 0.9857 means that the model is able to explain about 98.57% of the data variation, which is a very high value, indicating that the model fits the data very well.

[0106] This setting can accurately control the base current and pulse frequency through the arc length prediction formula, ensure the stability of the arc and the controllability of the welding process, reduce fluctuations in the welding process, ensure the consistency and repeatability of the welding process, and improve welding quality and production efficiency.

[0107] Specifically, in step S4, the calculation steps of the base current and the pulse frequency are:

[0108] S41: Determine the welding wire diameter and wire feeding speed range;

[0109] S42: uniformly selecting multiple feature points within the wire feeding speed range;

[0110] S43: Setting the welding arc length, peak current and peak time of each characteristic point;

[0111] S44: The base current and pulse frequency of each characteristic point are matched with the P-GMAW arc length prediction formula to obtain the overall welding process characteristic curve.

[0112] In step S4, by determining the wire diameter and wire feeding speed range, multiple feature points are evenly selected, the welding arc length, peak current, and peak time of each feature point are set, and the base current and pulse frequency of each feature point are matched with the P-GMAW arc length prediction formula to obtain the overall welding process characteristic curve, which can better optimize welding parameters, improve welding quality, reduce welding defects, and ensure the stability of the welding process and the quality of the weld.

[0113] This setting uses the arc length formula to calculate the base current and pulse frequency, avoiding a large number of experiments, reducing experimental costs, helping to form a proprietary welding process characteristic curve, facilitating subsequent welding use, ensuring the consistency of the welding process and welding quality, and reducing learning costs.

[0114] Preferably, a 1.0 mm diameter solid welding wire is selected, the working range of the wire feeding speed is 5-15 m / min, 6 characteristic points are uniformly selected within this range, the welding arc length of each characteristic point is set to 7 mm, the peak current is fixed to 340 A, and the peak time is 2.3 ms. The base current and pulse frequency of each characteristic point are matched with the P-GMAW arc length prediction formula, and the overall welding process characteristic curve is shown in Table 1. The base current and pulse frequency increase linearly with the increase of the wire feeding speed, and the peak parameters remain unchanged. The droplet transition state under this set of parameters is as follows Fig. 9 As shown, a stable and clean pulse-to-drop transition is achieved within the working range of the welding wire, which basically eliminates the overheating explosion and short circuit of the molten droplet and greatly reduces the welding spatter rate.

[0115] Table 1 Process characteristic point parameters

[0116]

[0117]

[0118] When the wire feeding speed changes, the most direct impact of the mismatch between the melting speed of the welding wire and the wire feeding speed is the change in the welding arc length. The welding arc length is closely related to the welding quality. For the same liquid bridge length, under a shorter arc length, the molten droplet will contact the molten pool before it is separated, thus causing a short circuit. Under an excessively long arc length, sidewall arcing and arc drift will occur in the groove. For flat plate surfacing, the ideal arc length is about 7mm.

[0119] This setting forms a characteristic curve for the welding process of high-strength austenitic stainless steel with 1.0mm diameter welding wire, which helps to ensure welding quality, facilitates direct reference in subsequent processing, improves the consistency of welding process, and reduces welding quality differences.

[0120] Specifically, the method further includes step S5: verifying and optimizing the welding process characteristic curve, verifying the applicability of the characteristic curve and the welding quality through actual welding tests, and further optimizing the welding parameters according to the test results.

[0121] This setting ensures that the final welding process characteristic curve can meet the needs of actual applications and helps to improve welding quality and production efficiency.

[0122] Example 1

[0123] A 1.0 mm high-strength austenitic stainless steel welding wire is selected, the wire feeding speed is 11 m / min, the peak current is 320-360 A, the peak time is 2.2-2.4 ms, and the pulse waveform is a square wave.

[0124] For 1.0mm diameter solid wire, the working range of wire feeding speed is 5-15m / min. Six characteristic points are evenly selected within this range. The welding arc length of each characteristic point is set to 7mm, the peak current is fixed to 340A, and the peak time is 2.3ms. The base current and pulse frequency of each characteristic point are matched with the P-GMAW arc length prediction formula. The overall welding process characteristic curve is shown in Table 1. The base current and pulse frequency increase linearly with the increase of wire feeding speed, and the peak parameters remain unchanged. The droplet transition state under this set of parameters is as follows Fig. 9 As shown, a stable and clean pulse-to-drop transition is achieved within the working range of the welding wire, which basically eliminates the overheating explosion and short circuit of the molten droplet and greatly reduces the welding spatter rate.

[0125] Example 2

[0126] The obtained special process characteristic curve was used to carry out welding experiments with the process curve of the welding machine, and the performance of the special process characteristic curve of high-strength austenitic welding wire was compared from three aspects: welding spatter rate, welding stability and weld bead morphology.

[0127] (1) Comparison of welding spatter rate

[0128] First, the welding spatter of the single-pass welding of the flat plate is collected, weighed and compared. The collection method is as follows: Fig.10 As shown, two copper plates are placed on both sides of the weld, with a bottom spacing of 16 mm and a top spacing of 100 mm. The weld length is controlled to be 250 mm, and the welding speed is 30 cm / min. After welding, the spatter particles on the copper plates are scraped off and weighed. Fig.10 Welding spatter collection method

[0129] The G3Si1 characteristic curve built into the welding machine and the optimized process characteristic curve were used for welding three times, and the spatter weight was compared. Fig.11 and Fig.12 As shown, the splash weight was reduced by 83.04%, Fig.11Weld spatter comparison, Fig.12 Splash Weight Comparison

[0130] (2) Comparison of welding stability

[0131] During the welding process, the arc welding quality analyzer was used to collect the current and voltage data of the welding process. The standard deviation of the current in the welding process using the original characteristic curve was 214.53, and the coefficient of variation was 1.14422; the standard deviation of the current in the welding process using the high-strength austenitic welding wire process characteristic curve was 106.97, and the coefficient of variation was 0.70781. The obtained data was used to draw a UI phase diagram;

[0132] Figures 13 to 15 As shown, it can be seen that the welding process using the optimized process characteristic curve is more stable, and there is no short circuit, arc breaking and other phenomena. Fig.13 Original characteristic curve welding process electrical signal record; Fig.14 Optimize the characteristic curve welding process electrical signal recording; Fig.15 Comparison of UI phase diagrams, (a) is the characteristic curve using G3Si1, and (b) is the characteristic curve using the optimized process.

[0133] (3) Comparison of weld bead morphology

[0134] The weld bead morphology using the G3Si1 characteristic curve is compared with the weld bead morphology using the high-strength austenitic welding wire characteristic curve. Figures 16 to 18 As shown, it can be seen that the customized process characteristic curve significantly improves the molten pool spread of A700 welding wire, and significantly improves the problem of side wall unfusion in V-groove welding, forming a uniform and full weld. Fig.16 Comparison of welding morphologies of butt test plates, (a) (c) are butt weld morphologies using G3Si1 characteristic curve, (b) (d) are butt weld morphologies using optimized characteristic curve; Fig.17 Comparison of fillet weld morphology. (a) is the fillet weld morphology using the G3Si1 characteristic curve, and (b) is the fillet weld morphology using the optimized characteristic curve. Fig.18 Comparison of fillet weld morphology, (a) is the fillet weld morphology using the G3Si1 characteristic curve, and (b) is the fillet weld morphology using the optimized characteristic curve.

[0135] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for formulating a high-strength austenitic stainless steel welding process characteristic curve, characterized in that: The specific steps include: S1: Select the initial welding process characteristic curve; select the welding process characteristic curve according to the parameters corresponding to the ordinary stainless steel weldment as the initial reference; S2: Recalibrate the peak energy; according to the characteristics of high-strength austenitic stainless steel, recalibrate the peak energy to ensure the reasonable distribution of energy during welding; S3: reformulate the pulse waveform; According to the material properties and welding requirements of high-strength austenitic stainless steel, the pulse waveform is reformulated to optimize the heat input and molten pool stability during welding; S4: The base current and pulse frequency are calculated based on the arc length prediction formula of pulse parameters and wire feeding speed.

2. The method for formulating a high-strength austenitic stainless steel welding process characteristic curve according to claim 1, characterized in that: In step S1 , the parameters of the weldment include thickness, geometry, joint type, weld position and wire diameter.

3. The method for formulating a high-strength austenitic stainless steel welding process characteristic curve according to claim 1, characterized in that: In step S2, calibrating the peak energy includes determining the optimal peak current and peak time. Based on the selected wire feeding speed and high-strength austenitic welding wire, a series of peak currents and peak times are selected within the welding current range, and the orthogonal test method is used for testing to determine the optimal peak current and peak time.

4. The method for formulating a high-strength austenitic stainless steel welding process characteristic curve according to claim 3, characterized in that: Taking 11m / min as the base wire feeding speed, the peak current test range is 300A-500A, the adjustment step is 20A, the peak time range is 1.2ms-2.7ms, and the step is 0.1ms. Within the stable transition range, the peak current is 320-360A, and the peak time is 2.2-2.4ms, which is the optimal pulse parameter range.

5. The method for formulating a high-strength austenitic stainless steel welding process characteristic curve according to claim 3, characterized in that: In step S2, the best criteria for determining the peak current and peak time are that the molten droplets are separated one by one and cleanly.

6. The method for formulating a high-strength austenitic stainless steel welding process characteristic curve according to claim 1, characterized in that: In step S3, a rectangular wave is selected as the pulse waveform, and the peak time is the peak time in step S2.

7. The method for formulating a high-strength austenitic stainless steel welding process characteristic curve according to claim 1, characterized in that: In step S4, the arc length prediction formula based on pulse parameters and wire feeding speed is: R 2 ＝0.9857 L=-12.22596+0.01552*I B +0.0354*I P +5.21194*t p -0.02577*f- 0.97645*V Where: L is the arc length; I B is the base current, unit: A; I P is the peak current, unit: A; t p is the peak time, unit: ms; f is the pulse frequency, unit: Hz; V is the wire feeding speed, unit: m / min.

8. The method for formulating a high-strength austenitic stainless steel welding process characteristic curve according to claim 7, characterized in that: In step S4, the base current and pulse frequency are calculated as follows: S41: Determine the welding wire diameter and wire feeding speed range; S42: uniformly selecting multiple feature points within the wire feeding speed range; S43: setting the welding arc length, peak current and peak time of each characteristic point; S44: The base current and pulse frequency of each characteristic point are matched with the P-GMAW arc length prediction formula to obtain the overall welding process characteristic curve.

9. The method for formulating a high-strength austenitic stainless steel welding process characteristic curve according to claim 8, characterized in that: When a 1.0mm diameter solid welding wire is selected, the working range of the wire feeding speed is 5-15m / min. Six characteristic points are evenly selected within this range, and the welding arc length of each characteristic point is set to 7mm, the fixed peak current is 340A, and the peak time is 2.3ms. The base current and pulse frequency of each characteristic point are matched with the P-GMAW arc length prediction formula to obtain the overall welding process characteristic curve.

10. The method for formulating a high-strength austenitic stainless steel welding process characteristic curve according to any one of claims 1 to 9, characterized in that: The method further includes step S5: verifying and optimizing the welding process characteristic curve, verifying the applicability of the characteristic curve and the welding quality through actual welding tests, and further optimizing the welding parameters according to the test results.

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