阅读说明：本技术 一种焊接气体智能控制方法 (Intelligent control method for welding gas ) 是由 马忠良 于 2021-10-27 设计创作，主要内容包括：本发明涉及焊接工艺技术领域,特别涉及一种焊接气体智能控制方法。本焊接气体智能控制方法实时获取焊接设备在焊接作业过程中的焊接状态参数、环境温度值以及气体输送管道横截面积变化率,根据实时获取的焊接状态参数、环境温度值以及气体输送管道横截面积变化率对送气系统进行调整,从而做到智能控制每一工位焊接设备的气体气压与气体输送流量,在保证了焊接质量的前提下,更为有效的降低气体成本。(The invention relates to the technical field of welding processes, in particular to an intelligent control method for welding gas. The intelligent control method for the welding gas obtains the welding state parameters, the environment temperature values and the change rate of the cross section area of the gas conveying pipeline of the welding equipment in the welding operation process in real time, and adjusts the gas supply system according to the welding state parameters, the environment temperature values and the change rate of the cross section area of the gas conveying pipeline which are obtained in real time, so that the gas pressure and the gas conveying flow of the welding equipment at each station are intelligently controlled, and the gas cost is effectively reduced on the premise of ensuring the welding quality.)

1. An intelligent control method for welding gas is characterized by comprising the following steps:

acquiring parameter information of a welding mode;

searching a first data module according to the acquired parameter information, and determining a welding mode matched with the parameter information, a welding process parameter corresponding to the welding mode and a gas control parameter corresponding to the welding mode;

sending the searched welding mode, the welding process parameters corresponding to the welding mode and the gas control parameters corresponding to the welding mode to a welding controller to control the welding execution process; meanwhile, the gas control parameters corresponding to the welding mode are issued to a gas controller to control the work of a gas supply system;

collecting welding state parameters, the cross-sectional area change rate of a gas conveying pipeline and an environment temperature value of welding equipment during working in real time;

acquiring the variable quantity of the welding state parameter in the current detection time period according to the welding state parameter acquired in real time when the welding equipment works;

searching a second data module according to the variation of the welding state parameter in the current detection time period, and calculating the first variation of the gas control parameter according to the matching result;

searching a third data module according to the environment temperature value acquired in real time when the welding equipment works, and calculating a second variable quantity of the gas control parameter according to the matching result;

searching a fourth data module according to the cross-sectional area change rate of the gas conveying pipeline when the collecting welding equipment works, and calculating a third change amount of the gas control parameter according to the matching result;

superposing the first variation, the second variation and the third variation to obtain the total variation of the corresponding gas control parameters;

respectively and correspondingly superposing the current values of the gas control parameters to obtain the total change amount of the corresponding gas control parameters, and obtaining the final gas control parameters;

and adjusting the gas delivery system according to the final gas control parameters.

2. The intelligent control method for the welding gas according to claim 1, characterized in that: the first data module stores a welding mode, welding mode corresponding parameters, welding process parameters and gas control parameters;

the second data module stores welding modes, welding state parameter variation and gas control parameter variation;

the third data module stores an environmental temperature value and a corresponding gas control parameter variable quantity;

the fourth data module stores the cross-sectional area change rate of the gas conveying pipeline and the corresponding gas control parameter variation.

3. The intelligent control method for the welding gas as recited in claim 2, wherein: the welding mode corresponding parameters include: at least one of a welding material thickness, a welding location, a welding material, a welding wire model.

4. The intelligent control method for the welding gas as recited in claim 2, wherein: the welding process parameters comprise: at least one of torch distance, wire feed speed, welding current, welding voltage, dry elongation, torch target angle, and torch carry angle.

5. The intelligent control method for the welding gas as recited in claim 2, wherein: the gas control parameters corresponding to the welding mode comprise: at least one of a supply pressure and a gas output flow rate.

6. The intelligent control method for the welding gas as recited in claim 2, wherein: the specific process of searching the first data module and determining the welding mode matched with the parameter information, the welding process parameter corresponding to the welding mode and the gas control parameter corresponding to the welding mode comprises the following steps:

matching the parameter information with the corresponding parameter of each welding mode in the first data module;

and determining the welding mode, the corresponding welding process parameters and the corresponding gas control parameters according to the matching result.

7. The intelligent control method for the welding gas as recited in claim 2, wherein: the welding state parameters comprise: at least one of a sound spectrum, a light spectrum, a bath width, an arc start section, an arc end section, and a bath gray scale.

8. The intelligent control method for the welding gas as recited in claim 2, wherein: the gas control parameter variation of the second data module is as follows: the influence quantity of the variable quantity of each welding state parameter on each corresponding gas control parameter;

the gas control parameter variation of the third data module is as follows: the influence quantity of each ambient temperature value on each corresponding gas control parameter;

the gas control parameter variation of the fourth data module is as follows: the rate of change of the cross-sectional area of each gas delivery conduit contributes an amount to each gas control parameter associated therewith.

9. The intelligent control method for the welding gas as recited in claim 2, wherein:

the calculation formula of the first variation is as follows: q_i=∑C_jW_j，Wherein i =1,2, … l, l represents the number of gas control parameters, and is a positive integer; q_iRepresenting a first variation, C, of an ith gas control parameter_jRepresents the variation of the ith gas control parameter, W, corresponding to the variation of the jth welding state parameter_jRepresents a predetermined AND in the second data block_jThe weight of the corresponding gas control parameter; j =1,2, … … m, m being a positive integer and representing the number of welding state parameters;

the calculation formula of the second variation is as follows: u shape_i=T_iY_iWherein i represents the ith gas control parameter, U_iA second variation, T, representing the ith gas control parameter_iIndicating the variation of the ith gas control parameter, Y, corresponding to the ambient temperature value preset in the third data module_iRepresenting the weight value of the obtained environment temperature value to the ith gas control parameter;

the calculation formula of the third variation is as follows: zi = ∑ A_kB_kWherein Z is_iA third variation, A, of the ith gas control parameter_kRepresents the variation of the ith gas control parameter, B, corresponding to the variation of the cross-sectional area of the kth gas conveying pipeline preset in the fourth data module_kRepresenting the obtained cross-sectional area change rate of the kth gas conveying pipeline to the weight of the ith gas control parameter; k =1,2, … … n, n being a positive integer representing the number of gas delivery conduits.

10. The intelligent control method for the welding gas according to claim 1, characterized in that: the parameter information comprises at least one of the thickness of a welding material, the welding place, the welding material and the model of a welding wire; wherein the parameter information is acquired by any one of the following methods:

arranging a positioning module on a station, and acquiring the parameter information according to the position information provided by the positioning module;

or a label is arranged on the station, the parameter information corresponding to the label identification is obtained by scanning and reading the label.

Technical Field

The invention relates to the technical field of welding processes, in particular to an intelligent control method for welding gas.

Background

In the metal welding industry, when protective gas (argon, carbon dioxide, oxygen or argon + oxygen, argon + carbon dioxide and other ternary mixed gas) for welding is used, a pot type centralized gas storage is adopted in a factory with a certain scale at present, gas is supplied to a pipeline (a proportioner is added behind a gas storage tank for the mixed gas), the pipeline supplies gas to each station at the tail end, and a pressure reducing meter (or a flowmeter) is adopted to adjust the gas flow, so that gas supply is carried out on welding equipment.

At the air feed front end in the technical aspect in the industry at present, can only select suitable gas mixture ratio cabinet and the invariable pressure of supplying gas of adjustment according to end equipment quantity, can't realize real-time effectual management, the transportation process of pipeline can't realize controlling, only constantly increase the flow and compensate terminal "the air feed is not enough", the end is provided with the controller of some simple functions and only control terminal gas flow, do not study welding quality and effectively control gas to welding gas (argon gas, carbon dioxide or gas mixture etc.) essential attribute, can not accomplish the constant voltage stationary flow, the gaseous inefficiency of economizing on energy and effect are extremely poor, welding quality has been influenced even.

Disclosure of Invention

The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention provides an intelligent welding gas control method, which can accurately control the gas outlet condition of each port through global analysis, realize supply and intelligent regulation according to requirements, reduce the gas cost for welding and improve the welding quality.

The invention discloses an intelligent control method of welding gas, which comprises the following steps:

acquiring parameter information of a welding mode;

searching a first data module according to the acquired parameter information, and determining a welding mode matched with the parameter information, a welding process parameter corresponding to the welding mode and a gas control parameter corresponding to the welding mode;

sending the searched welding mode, the welding process parameters corresponding to the welding mode and the gas control parameters corresponding to the welding mode to a welding controller to control the welding execution process; meanwhile, the gas control parameters corresponding to the welding mode are issued to a gas controller to control the work of a gas supply system;

collecting welding state parameters, the change rate of the cross-sectional area of the gas conveying pipeline and an environment temperature value of the welding equipment during working in real time;

acquiring the variable quantity of the welding state parameter in the current detection time period according to the welding state parameter acquired in real time when the welding equipment works;

searching a second data module according to the variation of the welding state parameter in the current detection time period, and calculating the first variation of the gas control parameter according to the matching result;

searching a third data module according to the environment temperature value acquired in real time when the welding equipment works, and calculating a second variable quantity of the gas control parameter according to the matching result;

searching a fourth data module according to the change rate of the cross-sectional area of the gas conveying pipeline during the operation of the collecting welding equipment, and calculating a third change amount of the gas control parameter according to the matching result;

superposing the first variation, the second variation and the third variation to obtain the total variation of the corresponding gas control parameters;

respectively and correspondingly superposing the current values of the gas control parameters to obtain the total change amount of the corresponding gas control parameters, and obtaining the final gas control parameters;

and adjusting the gas delivery system according to the final gas control parameters.

Further, the first data module, the second data module, the third data module and the fourth data module are located on a cloud server; wherein the content of the first and second substances,

the first data module comprises a welding mode, welding mode corresponding parameters, welding process parameters and gas control parameters;

the second data module comprises a welding mode, a welding state parameter variable quantity and a gas control parameter variable quantity;

the third data module comprises an environmental temperature value and a corresponding gas control parameter variable quantity;

the fourth data module includes a rate of change of a cross-sectional area of the gas delivery conduit and a corresponding amount of change in a gas control parameter.

Further, the welding mode corresponding parameters include: one or more of a welding material thickness, a welding location, a welding material, a welding wire model.

Further, the welding process parameters include: one or more of torch distance, wire feed speed, welding current, welding voltage, dry elongation, torch target angle, and torch carry angle.

Further, the gas control parameters corresponding to the welding mode include: one or more of a feed gas pressure, a gas output flow rate.

Further, the specific process of searching for the first data module and determining the welding mode matched with the parameter information, the welding process parameter corresponding to the welding mode, and the gas control parameter corresponding to the welding mode includes:

matching the parameter information with the corresponding parameter of each welding mode in the first data module;

and determining the welding mode, the corresponding welding process parameters and the corresponding gas control parameters according to the matching result.

Further, the specific process of searching for the first data module and determining the welding mode matched with the parameter information, the welding process parameter corresponding to the welding mode, and the gas control parameter corresponding to the welding mode includes:

matching the parameter information with the corresponding parameter of each welding mode in the first data module;

and determining welding process parameters and gas control parameters according to the matching result.

Further, the welding state parameters include: one or more of a sound spectrum, a light spectrum, a bath width, an arc start section, an arc end section, and a bath gray scale.

Further, the gas control parameter variation of the second data module is: the influence quantity of the variable quantity of each welding state parameter on each corresponding gas control parameter;

the gas control parameter variation of the third data module is as follows: the influence quantity of each ambient temperature value on each corresponding gas control parameter;

the gas control parameter variation of the fourth data module is as follows: the rate of change of the cross-sectional area of each gas delivery conduit contributes an amount to each gas control parameter associated therewith.

Further, the calculation formula of the first variation is as follows: q_i=∑C_jW_j，Wherein i =1,2, … l, l represents the number of gas control parameters, and is a positive integer; q_iRepresenting a first variation, C, of an ith gas control parameter_jRepresents the jth weldVariation of ith gas control parameter, W, corresponding to variation of state parameter_jRepresents a predetermined AND in the second data block_jThe weight of the corresponding gas control parameter; j =1,2, … … m, m being a positive integer and representing the number of welding state parameters;

the calculation formula of the second variation is as follows: u shape_i=T_iY_iWherein i represents the ith gas control parameter, U_iA second variation, T, representing the ith gas control parameter_iIndicating the variation of the ith gas control parameter, Y, corresponding to the ambient temperature value preset in the third data module_iRepresenting the weight value of the obtained environment temperature value to the ith gas control parameter;

the calculation formula of the third variation is as follows: z_i=∑A_kB_kWherein Z is_iA third variation, A, of the ith gas control parameter_kRepresents the variation of the ith gas control parameter, B, corresponding to the variation of the cross-sectional area of the kth gas conveying pipeline preset in the fourth data module_kAnd representing the obtained cross-sectional area change rate of the kth gas conveying pipeline to the weight of the ith gas control parameter.

Further, the parameter information includes factors affecting welding process parameters, such as welding material thickness, welding location, welding material, welding wire model and the like; wherein the parameter information is acquired by:

manually inputting the parameter information by field personnel;

or acquiring the parameter information in an automatic acquisition mode;

or a positioning module is arranged on the station, and the parameter information is obtained according to the position information provided by the positioning module;

or a label is arranged on the station, the parameter information corresponding to the label identification is obtained by scanning and reading the label.

The intelligent control method for the welding gas, provided by the invention, has the following beneficial effects: the intelligent welding gas control method calculates the total change amount of gas control parameters by calling data information in each data module, and adjusts the gas supply system by using the total change amount, so that the gas control is protected more accurately and timely, a better welding effect is achieved, and the gas supply cost is reduced.

Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.

FIG. 1 is a flow chart of a method for intelligent control of welding gas in accordance with an embodiment of the present invention;

fig. 2 is a schematic structural view of a gas supply system according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

An embodiment of the present invention is described below with reference to fig. 1 and 2.

The implementation of the intelligent control method for welding gas of the invention relates to the following data storage module.

A memory or a server, configured to store a plurality of data modules, where each data module stores various parameters and data of influence thereof on a gas control parameter, and the data modules include: the device comprises a first data module, a second data module, a third data module and a fourth data module, wherein the first data module comprises a welding mode, welding mode corresponding parameters, welding process parameters and gas control parameters. The second data module comprises a welding mode, a welding state parameter variable quantity and a gas control parameter variable quantity. The third data module comprises an ambient temperature value and a corresponding gas control parameter variation. The fourth data module includes a rate of change of a cross-sectional area of the gas delivery conduit and a corresponding amount of change in a gas control parameter. The gas conveying pipeline may be a terminal gas conveying pipeline of the gas supply system, a gas conveying pipeline at a gas inlet port of the gas supply system, or any gas conveying pipeline in the gas supply system. In addition, whether the gas conveying pipeline leaks gas or not can be monitored in real time according to the fact that the change rate of the cross section area of each position of the gas conveying pipeline is collected in real time, and by combining with the gas supply pressure parameter collected in the gas supply system, when the gas supply pressure is increased or decreased and the change rate of the cross section area of the gas conveying pipeline is not changed, the gas conveying pipeline may leak gas, and therefore whether the gas conveying pipeline leaks gas or not can be effectively detected in real time. The detection process of whether gas leakage occurs or not may be set to be performed before welding is started, thereby ensuring smooth progress of the welding process. In the actual application process, new parameter information can be added to each data module according to the requirement.

Optionally, the gas control parameter variation of the second data module is: the influence quantity of the variable quantity of each welding state parameter on each corresponding gas control parameter; for example, the amount of influence of the amount of change in the acoustic spectrum on the supply air pressure, the amount of influence of the amount of change in the spectrum on the supply air pressure; the amount of influence of the amount of change in the acoustic spectrum on the gas delivery flow rate and the amount of influence of the amount of change in the spectrum on the gas delivery flow rate.

The gas control parameter variation of the third data module is as follows: the ambient temperature value of each brings influence quantity to each gas control parameter; for example, the amount of influence of 20 ℃ on the feed gas pressure, the amount of influence of 20 ℃ on the gas delivery flow rate, the amount of influence of 25 ℃ on the feed gas pressure, and the amount of influence of 25 ℃ on the gas delivery flow rate.

The gas control parameter variation of the fourth data module is as follows: the rate of change of the cross-sectional area of each gas delivery conduit contributes an amount to each gas control parameter associated therewith. For example, the rate of change of the cross-sectional area of the gas delivery conduit at the end of the gas delivery system has an effect on the delivery pressure, the rate of change of the cross-sectional area of the gas delivery conduit at the end of the gas delivery system has an effect on the delivery flow rate, and the rate of change of the cross-sectional area of the gas delivery conduit at the gas inlet end of the gas delivery system has an effect on the delivery flow rate.

Fig. 1 shows a flow chart of a welding gas intelligent control method according to an embodiment of the invention. As shown in fig. 1, the intelligent control method for welding gas provided by this embodiment includes:

step 101: parameter information of a welding mode is acquired. In this step, the parameter information includes one or more of the welding material thickness, the welding location, the welding material, the welding wire model, and other factors that affect the welding process parameters. In the actual application process, new parameter information can be added according to the requirement.

Step 102: and searching a first data module according to the parameter information, and determining a welding mode matched with the parameter information, welding process parameters corresponding to the welding mode and gas control parameters corresponding to the welding mode.

In this step, the welding process parameters corresponding to the welding mode include: one or more of torch distance, wire feed speed, welding current, welding voltage, dry elongation, torch target angle, and torch carry angle. In the actual application process, new welding process parameters can be added according to the needs. The gas control parameters corresponding to the welding mode include, but are not limited to: one or more of a feed gas pressure, a gas output flow rate. In the practical application process, new gas control parameters can be added according to the needs.

Wherein, each welding mode respectively corresponds to a group of welding process parameters and a group of gas control parameters. And matching the parameter information of the real-time welding mode with corresponding parameters of the welding mode preset in the first data module, and determining the welding mode, welding process parameters and gas control parameters according to the successful matching result.

Step 103: and sending the searched welding mode, the welding process parameter corresponding to the welding mode and the gas control parameter corresponding to the welding mode to a welding controller, and controlling the welding execution process. And meanwhile, the gas control parameters corresponding to the welding mode are issued to a gas controller to control the work of the gas supply system.

Step 104: and collecting welding state parameters, the change rate of the cross-sectional area of the gas conveying pipeline and an environment temperature value of the welding equipment during working in real time. Wherein the welding state parameters include: one or more of a sound spectrum, a light spectrum, a bath width, an arc start section, an arc end section, and a bath gray scale. In the practical application process, new welding state parameters can be added according to the needs. For example, the width and length of the molten pool are acquired in real time when the welding equipment is working.

Step 105: and acquiring the variable quantity of the welding state parameter in the current detection time period according to the welding state parameter acquired in real time when the welding equipment works. For example, the amount of change in the molten pool width occurring in the current detection time and the amount of change in the molten pool length occurring in the current detection time are acquired.

Step 106: searching the second data module according to the variation of the welding state parameter in the current detection time period, and calculating the first variation of the gas control parameter according to the matching result; for example, if the variation of the width of the molten pool in the current detection time and the variation of the length of the molten pool in the current detection time are obtained in real time, the second data module is searched, the variation of the gas control parameter corresponding to the width of the molten pool and the variation of the gas control parameter corresponding to the length of the molten pool are determined, and the first variation caused by the width of the molten pool and the length of the molten pool to the gas control parameter is calculated according to the matching result.

Step 107: and searching the third data module according to the ambient temperature value acquired in real time when the welding equipment works, and calculating a second variable quantity of the gas control parameter according to a matching result. The welding environment temperature also has great influence on the diffusivity of the protective gas, the welding environment temperature is collected in real time, and the gas control parameters are corrected by utilizing the environment temperature value. At this time, the welding mode is not distinguished. For example, the third data module is searched according to the real-time collection of the ambient temperature value of the welding equipment during working, the corresponding gas control parameter variation and the weight of the gas control parameter are determined, and the second variation of the gas control parameter is calculated according to the corresponding gas control parameter variation and the weight of the gas control parameter.

Step 108: searching a fourth data module according to the cross-sectional area change rate of the gas conveying pipeline during the working of the collecting welding equipment, and calculating a third variable quantity of the gas control parameter according to a matching result;

step 109: and superposing the first variable quantity, the second variable quantity and the third variable quantity to obtain the total change quantity of the corresponding gas control parameters. And (4) correspondingly superposing the current values of the gas control parameters respectively to obtain the total change amount of the corresponding gas control parameters, and obtaining the final gas control parameters.

Step 110: and adjusting the gas supply system according to the acquired gas control parameter variation. For example, the final gas control parameters are sent to a gas controller to control the operation of the gas delivery system, and each device in the gas delivery system changes the gas delivery pressure or gas output flow rate in the gas delivery system in response to the adjusted gas control parameters.

According to the technical scheme, the welding state parameters, the environmental temperature values and the change rate of the cross-sectional area of the gas conveying pipeline of the welding equipment in the welding operation process are obtained in real time, and the gas supply system is adjusted according to the welding state parameters, the environmental temperature values and the change rate of the cross-sectional area of the gas conveying pipeline which are obtained in real time, so that the gas pressure and the gas conveying flow of the welding equipment at each station are intelligently controlled, and the gas cost is effectively reduced on the premise of ensuring the welding quality.

Based on the foregoing description of the embodiments, in an alternative implementation, a gas control parameterThe calculation formula of the first variation of the number variation is as follows: q_i=∑C_jW_j，Wherein i =1,2, … l, l represents the number of gas control parameters, and is a positive integer; q_iRepresenting a first variation, C, of an ith gas control parameter_jRepresents the variation of the ith gas control parameter, W, corresponding to the variation of the jth welding state parameter_jRepresents a predetermined AND in the second data block_jThe weight of the corresponding gas control parameter; j =1,2, … … m, m being a positive integer and representing the number of welding state parameters. And the variable quantity of the gas control parameter is different under different welding modes. E.g. C₁Representing the variation of the supply gas pressure corresponding to the variation of the bath width, C₂Representing the amount of change in supply air pressure corresponding to the amount of change in the arcing section. The corresponding first variation calculation formula of the supply air pressure is: q₁=W₁C₁+W₂C₂。

The calculation formula of the second variable quantity of the gas control parameter is U_i=T_iY_iWherein, T_iRepresenting the variation of gas control parameter, Y, corresponding to the ambient temperature value preset in the third data module_iAnd representing the weight of the obtained ambient temperature value to the ith gas control parameter, for example, when the collected ambient temperature is 20 ℃, the second variation of the gas pressure is: u shape₁=T₁Y₁Wherein, T₁Is the amount of change in gas pressure, Y₁Is a weight of 20 ℃ versus gas pressure.

The third variation of the gas control parameter is calculated by Z_i=∑A_kB_kWherein Z is_iA third variation, A, of the ith gas control parameter_kRepresents the variation of the ith gas control parameter, B, corresponding to the variation of the cross-sectional area of the kth gas conveying pipeline preset in the fourth data module_kRepresenting the obtained cross-sectional area change rate of the kth gas conveying pipeline to the weight of the ith gas control parameter; k =1,2, … … n, n being a positive integer representing the number of gas delivery conduits. E.g. to the end gas-conveying pipeThe change rate of the cross-sectional area of the gas conveying pipeline at the tail end is 0.1%, the change rate of the cross-sectional area of the gas conveying pipeline at the tail end of the gas inlet port is 0.2%, the fourth data module is searched, and the gas supply pressure change A matched with the 0.1% change rate of the gas conveying pipeline at the tail end is determined₁And the influence weight B on the air supply pressure₁A supply pressure variation A matching the 0.2% variation rate of the end gas delivery pipe₂And the influence weight B on the air supply pressure₂Calculating to obtain a third variable quantity: z₁=A₁B₁+A₂B₂. Because the change rate of the cross-sectional area of the gas conveying pipeline is the process parameter of the gas, the influence quantity of the process change of the pair of input conditions on the gas control parameter can be set to realize timely and rapid adjustment of the gas control parameter.

In the above-described embodiment, the first variation amount of the gas control parameter is correlated with the welding result (welding state parameter), i.e., is influenced by the result exhibited after welding. The second variation of the gas control parameter is related to the welding environment factor, i.e. the ambient environment during the welding operation, specifically, the ambient temperature in this embodiment. The third amount of change in the gas control parameter is related to an input condition in the welding process, specifically, in this embodiment, the rate of change of the cross-sectional area of the gas delivery conduit. In summary, in the embodiment, the gas control parameter variation is obtained from the sum of the welding result, the operating environment and the welding input condition, so that the gas control parameter can be effectively adjusted to ensure that the welding result is stably and timely adjusted. Compared with a scheme of singly adjusting the gas control parameters by taking the welding result (welding state parameter) as a consideration factor, the method has the advantages that the factors of operating environment and input condition change are considered simultaneously, so that the adjustment of the gas control parameters is more accurate and timely.

In the above embodiments, the data stored in each data module may be a discrete data set, for example, stored in a table manner. According to the first numerical value of the input condition, a second numerical value which is closest to the first numerical value of the input condition in the table can be found, so that other parameter information corresponding to the input condition corresponding to the second numerical value in the table is searched and used as determined parameter information, or the gas control parameter variation and the weight corresponding to the input condition are used as determined information after searching and using the determined parameter information.

The data stored in each data module can be in a function form, the independent variable of the function is an input condition, and the dependent variable of the function is a variable quantity and a weight value. The input conditions can be used as independent variables of the function and can be brought into the function to obtain the corresponding variable quantity and weight.

Based on the content of the foregoing embodiments, in an alternative implementation, the foregoing step 106 may be performed by:

searching the second data module according to the obtained variation of each welding state parameter in the current detection time period, determining the variation of each corresponding gas control parameter, and calculating the first variation of the gas control parameter: sigma C_jW_jConcretely, as follows, W₁C₁+W₂C₂+W₂C₂+...+W_jC_j。

For example, according to the acquired variation of the molten pool width in the current detection time period and the variation of the arc starting section in the current detection time period, the second data module is searched, and the air supply pressure variation C corresponding to the variation of the molten pool width in the current detection time period is determined₁And C₁Corresponding W₁Determining the air supply pressure variation C corresponding to the variation of the arc striking section in the current detection time period₂And C₂Corresponding W₂Based on the matching result, a first variation of the supply air pressure is calculated, specifically as follows, W₁C₁+W₂C₂。

Based on the content of the foregoing embodiments, in an alternative implementation, the foregoing step 108 may be performed by:

the first variation, the second variation and the third variation of the same gas control parameter are superposed to obtain the variation of the gas control parameter, such as the variation of the supply pressure

Q₁+U₁+Z₁=W₁C₁+W₂C₂+W₂C₂+...+W_jC_j+T₁Y₁+A₁B₁+A₂B₂+...+A_kB_k。

Based on the content of the foregoing embodiment, in an alternative implementation, the foregoing step 101 may be implemented by one of the following ways:

manually inputting the parameter information by field personnel;

or automatically acquiring the parameter information through the memory or the server;

or a positioning module is arranged on a station, and the parameter information is obtained according to the position information provided by the positioning module;

or a label is arranged on a station, the parameter information corresponding to the label identification is obtained by scanning and reading the label.

Within the workshop, if the position of each welding station is fixed, that is to say the welding mode of a certain welding station is fixed. In this case, the parameter information required for the welding mode can be manually entered by field personnel before the device is first put into production. And the parameter information can be saved on the station equipment so as to be conveniently known.

The positioning module can be used for automatically acquiring the parameter information, so that errors are not easy to occur, and the condition that the welding equipment of the station possibly needs to be replaced is more convenient. For example, the welding mode at that station on the shop line is fixed, but the welding equipment can be moved. At this moment, positioning modules can be arranged on all welding equipment, when the welding equipment is in place at a certain station and is ready to start working, a request can be sent to a cloud server, the cloud server receives the request and acquires positioning information sent by the positioning modules, and the cloud server stores all the positioning information, corresponding welding modes and parameter information in the welding modes. And the cloud server determines a welding mode and parameter information in the welding mode according to the acquired positioning information and returns the parameter information to the welding controller. Meanwhile, the cloud server determines welding process parameters and gas control parameters according to the welding mode and feeds the information back to the welding controller. The gas control parameters are also simultaneously fed back to the gas controller.

To the workshop that needs nimble set up welding station, for example, welding equipment can remove in the workshop as required, and at this moment, it will be more convenient to adopt the mode of label discernment to obtain parameter information, and is difficult for makeing mistakes. A label is arranged on a certain welding device, and the welding device has a function of marking the welding device. The method comprises the steps that the label information is obtained through a scanning device and sent to a cloud server, and the cloud server determines a welding mode corresponding to the welding equipment and parameter information in the welding mode according to the obtained label information. And the cloud server returns the welding mode and the parameter information in the welding mode to the welding controller. Meanwhile, the cloud server determines welding process parameters and gas control parameters according to the welding mode and feeds the information back to the welding controller. The gas control parameters are also simultaneously fed back to the gas controller.

The acquisition method utilizing the cloud server can conveniently and quickly acquire the parameter information. And can be more convenient and reliable in the case of production line process or equipment adjustment.

Fig. 2 is a schematic view showing a structure of a gas supply system according to an embodiment of the present invention.

The gas supply system includes, but is not limited to, a gas supply device for supplying gas; the gas master control device is used for adjusting gas supply pressure and gas output flow; the branch pipe pressure stabilizing device is used for controlling the stability of air pressure; and the intelligent welding gas management device is used for automatically matching reasonable gas flow according to the requirement of the welding equipment. And the memory or the server is used for storing a plurality of data modules, wherein each data module stores various parameters and influence data of the parameters on the gas control parameters. The connection relation of each device is shown in fig. 2, one end of the gas master control device is connected with the gas supply device, the other end of the gas master control device is connected with one end of the branch pipe pressure stabilizing device, the other end of the branch pipe pressure stabilizing device is connected with one end of the welding gas intelligent management device, and the other end of the welding gas intelligent management device is connected with the welding equipment. The gas supply device can provide mixed gas, and can also provide pure gas such as single argon gas or single carbon dioxide gas. All be provided with PLC control panel or singlechip control panel in gaseous total controlling means, branch pipe voltage regulator device, the gaseous intelligent management device of welding, each device of real-time control.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element. It should be noted that the above-described device embodiments are merely illustrative, where the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.

Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.

Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.