JP6764369B2 - Join monitoring system and join equipment - Google Patents

Description

The present invention relates to a junction monitoring system and a junction device.

To perform welding, pressure is applied perpendicularly to the butt surface of the object to be welded, and the butt surface is heated by a method such as energization, laser irradiation, or friction stir welding. The applied pressure causes the gripping member of the welding machine to wear, and as a result, the contact state of the mating surfaces varies each time welding is performed. This affects the transient joining situation between the members during welding, which may lead to variations in welding quality.
In resistance welding, the objects to be welded are joined by utilizing Joule heat generated by passing a welding current between the objects to be welded in contact with each other while applying pressure. The load or pressing force applied to the object to be welded during pressurization in resistance welding is one of the factors that affect the quality of welding. As a method of controlling the welding quality, a method of estimating the inclination of the workpiece to be welded by measuring the strain of the electrode of the resistance welding machine and comparing it with a preset threshold value is disclosed (see, for example, Patent Document 1).

In Patent Document 1, the first and second welding electrodes arranged so as to sandwich the object to be welded and the distortion of the first welding electrode attached to the first welding electrode are non-electrically detected. A resistance welding device including a strain gauge to be welded and a control unit for detecting a load on the first welding electrode during welding of the object to be welded based on a signal from the strain gauge is described.

Japanese Unexamined Patent Publication No. 2015-155103

By the way, when the region to be joined by welding has a spread like a surface instead of a point, it is required to judge the welding quality from the information reflecting the joining condition in the entire joining region. For that purpose, it is necessary to monitor transient changes in the condition of the joint surface during welding. In the resistance welding apparatus described in Patent Document 1, since the judgment standard is a measured value at a certain time, the information on the transient change in the joining condition is not reflected in the quality judgment standard (considering the information). There is a problem (not done).

The present invention has been made in view of such circumstances, and an object of the present invention is to provide a joining monitoring system and a joining device capable of determining the joining quality of a product to be welded and the welding quality of the product to be welded.

In order to solve the above problems, the joint monitoring system of the present invention includes a plurality of load sensors that detect a load applied to a gripping member that abuts and fixes a plurality of products to be joined at the joint surface, and a plurality of load sensors of the products to be joined. A joint output sensor that measures the output of the joining means that heats the joint surface, a recording device that continuously records the output of the joint output sensor and the load data of the load sensor, and the recording device recorded in the recording device. Based on the load data, the load bias evaluation unit that calculates the bias of the load distribution due to the plurality of the objects to be joined not uniformly contacting each other on the joint surface as the load bias data, and the recording device recorded the data. By setting the reference time during joining based on the output of the joining output sensor and adding a time difference from the reference time to the load bias data at each time during joining, the time variation of the load bias Joining based on a load bias fluctuation data generator that generates load bias fluctuation data, which is data, a recording device that records the generated load bias fluctuation data, and the load bias fluctuation data recorded in the recording device. It is characterized by including a reference data storage unit for accumulating reference data that serves as a reference for quality determination.

According to the present invention, there is provided a joining monitoring system and a joining device capable of determining the joining quality of the product to be welded and the welding quality of the product to be welded.

It is a figure which shows the structure of the welding monitoring system which concerns on 1st Embodiment of this invention. It is a figure which shows the mounting position of the cylindrical or columnar welded object of the welding monitoring system which concerns on the 1st Embodiment, a gripping member, and a load sensor. It is a figure which shows the mounting position of the prismatic welded object, the gripping member, and the load sensor of the welding monitoring system which concerns on the 1st Embodiment. It is a figure which shows the plate-shaped object to be welded of the welding monitoring system which concerns on 1st Embodiment, the grip member, and the attachment position of a load sensor. It is a figure which shows the mounting position of the welded object of the welding monitoring system which concerns on the 1st Embodiment, a gripping member and a load sensor, and (a) is a figure in the case where the welded article is evenly in contact with each other on a mating surface. , (B) is a diagram when they are in contact with each other in a state of being tilted in one direction. It is the schematic which shows the positional relationship between the gripping member of the welding monitoring system which concerns on the 1st Embodiment and a load sensor. It is a figure which shows the plate-shaped welded object of the welding monitoring system which concerns on 1st Embodiment, and the attachment position of a gripping member and a load sensor, and (a) is a figure which the flat-plate-shaped object to be welded uniformly on the mating surface. The figure in the case of being in contact, (b) is a figure showing the case of being in contact in a state of being tilted in one direction. It is a flowchart which shows the process at the time of registration which accumulates the data (reference data) which becomes the reference in welding quality determination of the welding monitoring system which concerns on the 1st Embodiment. It is a flowchart which shows the process at the time of monitoring which determines the welding quality of the welded article of the welding monitoring system which concerns on the 1st Embodiment. It is a figure which shows the structure of the welding monitoring system which concerns on 2nd Embodiment of this invention. It is a figure which shows the structure of the welding monitoring system which concerns on 3rd Embodiment of this invention. It is a figure which shows the drawing on the 2D plane of the display data generated by the load bias fluctuation data generation part of the welding monitoring system which concerns on the 3rd Embodiment. It is a flowchart which shows the process at the time of monitoring which determines the welding quality of the welded article of the welding monitoring system which concerns on the 3rd Embodiment. It is a figure which shows the structure of the welding monitoring system which concerns on 4th Embodiment of this invention. It is a figure which shows the structure of the welding monitoring system which concerns on 5th Embodiment of this invention. It is a figure which shows the example of the welding apparatus which includes the welding monitoring system which concerns on embodiment.

Hereinafter, embodiments for carrying out the present invention (hereinafter referred to as “embodiments”) will be described in detail with reference to the drawings. In each figure, the same reference numerals are given to common parts, and duplicate description will be omitted.
(First Embodiment)
FIG. 1 is a diagram showing a configuration of a welding monitoring system (joint monitoring system) according to the first embodiment of the present invention.
As shown in FIG. 1, the welding monitoring system 100 includes a gripping member 110 for abutting and fixing a plurality of objects to be welded (articles to be welded) 1 at a joining surface (welding surface) and a load during the welding process (during welding). A data recording means 120 for recording data and a data evaluation means 130 for analyzing and evaluating load data recorded by the data recording means 120 are provided. The joining includes not only normal welding (Welding) but also friction stir welding (Friction Stir Welding) and the like.

<Welded product 1 and grip member 110>
The gripping member 110 abuts and fixes a plurality of products to be welded (for example, products 1a and 1b to be welded in FIG. 2) at the surfaces to be joined. Therefore, the gripping member 110 is composed of, for example, a plurality of gripping members 110 (see the upper gripping member 110a and the lower gripping member 110b in FIG. 2) for gripping and gripping a plurality of objects to be welded from above and below. At least one of the plurality of gripping members 110 is movable. A movable grip member (see the upper grip member 110a in FIG. 2) sandwiches the workpiece 1 together with another grip member (see the lower grip member 110b in FIG. 2) and is perpendicular to the mating surface 11 (joint surface). The product 1 to be welded is fixed by applying pressure to. Details of the gripping member 110 will be described later. In the present embodiment, the gripping member 110 will also be described as being included in the components of the welding monitoring system 100.

<Data recording means 120>
The data recording means 120 is a welding machine that heats a plurality of load sensors 121 that detect a load applied to the gripping member 110 and a mating surface 11 of the workpiece 1 (for example, the workpieces 1a and 1b in FIG. 2). It includes a welding output sensor 122 that measures the output of (not shown), and a recording device 123 that continuously records the output of the welding output sensor 122 and the load data of the load sensor 121. That is, the time change of the output of the welding output sensor 122 during welding and the time change of the load data during welding of the load sensor 121 are recorded (measured).

The load sensor 121 (four are provided in the examples of FIGS. 2 and 3) measures the load experienced by the gripping member 110 as the welding progresses as the pressure is applied. Specifically, the load sensor 121 measures the load (load data) in the vicinity of the contact surface between the gripping member 110 and the workpiece 1. The load sensor 121 is composed of, for example, a strain gauge that converts a force or mass such as tension or compression into an electric signal. A strain gauge is attached to the surface of the shape gripping member 110 as a load sensor element, but the present invention is not limited to this.
The load sensor 121 is installed in the gripping member 110 near the contact surface with the object to be welded 1 to be gripped. It is desirable to install four or more load sensors 121 at substantially equal intervals along a line parallel to the boundary line of the contact surface between the gripping member 110 and the product 1 to be welded.
By installing a plurality of load sensors 121 on the gripping member 110, if the workpieces 1 to be welded do not come into uniform contact with each other on the mating surface 11 and tilt occurs, the load sensor 121 installed in the tilted direction can be used. A large load is measured. In this way, it is possible to obtain information on the contact state of the workpiece 1 on the butt surface 11 from the difference in signals between the load sensor elements.

<Data evaluation means 130>
The data evaluation means 130 includes a load bias evaluation unit 131, a load bias fluctuation data generation unit 132, a recording device 133, a reference data storage unit 134, and a difference extraction unit 135.
The load bias evaluation unit 131 makes a plurality of objects to be welded 1 (for example, the objects to be welded 1a and 1b in FIG. 2) uniformly contact each other on the mating surface 11 based on the load data recorded in the recording device 123. The bias of the load distribution due to not doing so is calculated as the load bias data.

The load bias fluctuation data generation unit 132 sets a reference time during welding (for example, a time when energization of the welding output starts) based on the output of the welding output sensor 122 recorded in the recording device 123, and during welding. By adding a time difference from the reference time to the load bias data at each time of the above, load bias variation data which is time variation data of load bias is generated.
The above reference time is commonly set for each product to be welded so that the welding quality of each product to be welded is determined under the same conditions when the welding quality of the plurality of products 1 to be welded is to be determined in sequence. This is the reference time. Further, by setting this reference time, the time difference from this reference time can be set.
For example, when heating by an electric current is used as the welding means, the load bias fluctuation data generation unit 132 uses the time of the rise of the welding output (start of energization) as the reference time.

The recording device 133 records the load bias fluctuation data generated by the load bias fluctuation data generation unit 132.

The reference data storage unit 134 stores data (reference data) that serves as a reference for welding quality determination based on the load bias fluctuation data recorded in the recording device 133. That is, by using the product 1 to be welded with good quality as the product 1 to be welded, it is possible to accumulate data (reference data) that serves as a reference for determining the welding quality (see FIG. 8: "Registration process"). .. The data (reference data) that serves as a reference for determining the welding quality is accumulated in the reference data storage unit 134, and the difference extraction unit 135 reads it out as comparison data.
Instead of using the product 1 to be welded with good quality, analyze the load bias fluctuation data of each product to be welded, and accumulate the data with good judgment results as reference data by a statistical method. Is also possible.

The difference extraction unit 135 compares the load bias fluctuation data recorded in the recording device 133 with the reference data stored in the reference data storage unit 134 to extract the difference.

The data evaluation means 130 is composed of, for example, a general-purpose or dedicated processing server. The data evaluation means 130 is realized by a CPU (Central Processing Unit) expanding a program stored in a storage unit (not shown) of the processing server into a RAM and executing the program.

2 to 4 are views showing mounting positions of the product to be welded, the gripping member, and the load sensor. FIG. 2 shows a case where the shape of the product to be welded and the gripping member is cylindrical or columnar, FIG. 3 shows the case where the shape of the product to be welded and the gripping member is prismatic, and FIG. The case where the shape of the member is a flat plate shape is shown respectively.
As shown in FIG. 2, the gripping member 110 includes an upper gripping member 110a and a lower gripping member 110b that grip the cylindrical or columnar workpieces 1a and 1b to be welded from above and below. At least one grip member 110 (for example, the upper grip member 110a) is movable. A movable gripping member (upper gripping member 110a) sandwiches the products to be welded 1a and 1b together with other gripping members (lower gripping member 110b) and applies pressure perpendicularly to the mating surface 11 to produce the product to be welded. Fix 1a and 1b. When the upper gripping member 110a and the lower gripping member 110b are generically referred to without distinction, they are referred to as the gripping member 110 (the same notation method is adopted below).

Four or more load sensors 121 are installed at substantially equal intervals along a line parallel to the boundary line between the gripping member 110 (upper gripping member 110a, lower gripping member 110b) and the contact surfaces of the objects to be welded 1a and 1b. To do. In the example of FIG. 2, in the load sensor 121, four load sensors 121a to 121d are installed at equal intervals on the outer peripheral surface of the lower gripping member 110b. The load sensors 121a and 121c and the load sensors 121b and 121d are installed at positions facing each other in pairs. The load sensors 121a to 121d have the same configuration. When the load sensors 121a to 121d are generically referred to without distinction, they are referred to as load sensors 121.

As shown in FIG. 3, the gripping member 110 includes an upper gripping member 110c and a lower gripping member 110d that grip the workpieces 1c and 1d in the shape of a prism (here, a square pillar) by sandwiching them from above and below. At least one grip member 110 (for example, the upper grip member 110c) is movable. A movable gripping member (upper gripping member 110c) sandwiches the products to be welded 1c and 1d together with other gripping members (lower gripping member 110d) and applies pressure perpendicularly to the mating surface 12 to produce the product to be welded. Fix 1c and 1d.

Four or more load sensors 121 are installed at substantially equal intervals along a line parallel to the boundary line between the gripping member 110 (upper gripping member 110c, lower gripping member 110d) and the contact surfaces of the objects to be welded 1c and 1d. To do. In the example of FIG. 3, in the load sensor 121, four load sensors 121a to 121d are installed at equal intervals on the outer peripheral surface of the lower gripping member 110b. The load sensors 121a and 121c and the load sensors 121b and 121d are installed at positions facing each other in pairs.

As shown in FIG. 4, the gripping member 110 includes a gripping member 110e and a gripping member 110f that grip the flat plate-shaped workpieces 1e and 1f to be welded by sandwiching them from the x direction. At least one grip member 110 (for example, the grip member 110e) is movable. A movable gripping member (grasping member 110e) sandwiches the products 1e and 1f to be welded together with other gripping members (grasping members 110f), and applies pressure perpendicularly to the mating surface 13 to form the product 1e to be welded. 1f and fixed.

As shown in FIG. 4, when the shapes of the products to be welded 1e and 1f and the shapes of the gripping members 110e and 110f are flat plates, in order to detect the inclination of the products to be welded 1e and 1f, it is parallel to the flat plates. It is desirable to obtain the load bias in the direction perpendicular to the butt surface 13 (x direction) and in the direction parallel to the flat plate and parallel to the butt surface (y direction). For that purpose, a set of an x-direction load sensor 131 that measures the load in the x-direction and a y-direction load sensor 141 that measures the load in the y-direction is used. In the example of FIG. 4, four sets of the x-direction load sensors 131a to 131d and the y-direction load sensors 141a to 141d are installed. That is, the set of the x-direction load sensor 131a and the y-direction load sensor 141a of the grip member 110e is installed facing the set of the x-direction load sensor 131d and the y-direction load sensor 141d of the grip member 110f. Further, the pair of the x-direction load sensor 131b and the y-direction load sensor 141b of the grip member 110e is installed facing the pair of the x-direction load sensor 131c and the y-direction load sensor 141c of the grip member 110f.

Hereinafter, the welding monitoring method of the welding monitoring system 100 configured as described above will be described.
<Operation of each part during welding>
First, the operation of each part during welding will be described.
Take the case where the workpiece 110 to be welded and the gripping member 1 shown in FIG. 2 have a cylindrical shape or a cylindrical shape as an example.
By the operation of the gripping member 110, a plurality of objects to be welded 1a and 1b are abutted and fixed by a surface (welding surface 11) to be joined (welded). Here, a movable gripping member (upper gripping member 110a) sandwiches the workpieces 1a and 1b together with another gripping member (lower gripping member 110b) and applies pressure perpendicularly to the mating surface 11. The products 1a and 1b to be welded are fixed.

Four or more load sensors 121 are installed at substantially equal intervals along a line parallel to the boundary line between the gripping member 110 (upper gripping member 110a, lower gripping member 110b) and the contact surfaces of the objects to be welded 1a and 1b. Has been done.
When the products 1a and 1b to be welded do not come into uniform contact with each other on the mating surface 11 and tilted, a larger load is measured by the load sensor installed in the tilted direction. In this way, it is possible to obtain information on the contact state of the objects to be welded 1a and 1b on the abutting surface 11 from the difference in signals between the load sensor elements.

<Data recording>
Next, the operation of each part when the butt surface 11 of the product to be welded is heated and welded will be described.
Specific examples of the heating method include current application (resistance welding method), laser irradiation (laser welding method), and stirring with a rotary tool (friction stirring welding method). The butt surface 11 is melted or softened by heating, and the products to be welded are joined (welded) to each other. The welding output sensor 122 (see FIG. 1) measures the output for heating. Further, the load sensor 121 measures the load (load data) in the vicinity of the contact surface between the gripping member 110 and the product 1 to be welded, and continuously records the load (load data) in the recording device 123 (see FIG. 1). Based on the output (output signal) of the welding output sensor 122, the recording device 123 continuously records the load data of the load sensor 121 in the time from the welding start time to the welding start time in a required measurement cycle. It is recorded in 123.

<Analysis / evaluation of load data>
Next, the method of analyzing and evaluating the load data in the data evaluation means 130 will be described.
FIG. 5 is a diagram showing the mounting positions of the product to be welded, the gripping member, and the load sensor. FIG. 5 (a) shows the product to be welded, and FIG. 5 (b) shows one when the product to be welded is in uniform contact with the mating surface. The case where the contact is made while tilted in the direction is shown. The same components as those in FIG. 2 are designated by the same reference numerals.

As shown in FIG. 5A, when the cylindrical or columnar workpieces to be welded are uniformly in contact with each other on the mating surface 11, the load sensors 121a to 121c measure substantially the same load. The load bias evaluation unit 131 (see FIG. 1) of the data evaluation means 130 evaluates that the contact state of the mating surface 11 is uniform.

On the other hand, as shown in FIG. 5B, when the cylindrical or columnar workpiece to be welded is in contact with the mating surface 11 in a state of being tilted in one direction, the load sensor 121a installed in the tilted direction is A larger load is measured as compared with the load sensor 121c installed at the opposite location. The load bias evaluation unit 131 (see FIG. 1) of the data evaluation means 130 evaluates the direction and magnitude of the load bias on the mating surface 11 based on the difference in the measured values, and calculates the load bias data.

<Generation of load bias data>
The load bias evaluation unit 131 (see FIG. 1) of the data evaluation means 130 combines the load data of the plurality of load sensors 121 at a certain time, and calculates the load bias data indicating the direction and magnitude of the load bias (see FIG. 1). See FIG. 6 below).

An example of the calculation method of the load bias data will be described.
FIG. 6 is a schematic view showing the positional relationship between the gripping member and the load sensor. FIG. 6 shows a method of calculating load bias data when a strain gauge is attached as a load sensor 121 to the cylindrical or columnar gripping member 110 shown in FIG.
As shown in FIG. 6, the x-axis is taken in an arbitrary direction in the plane in contact with the workpiece, and the y-axis is taken in the direction orthogonal to the x-axis. A load sensor 121a is installed in the first quadrant of the x-axis and the y-axis, a load sensor 121b is installed in the second quadrant, a load sensor 121c is installed in the third quadrant, and a load sensor 121d is installed in the fourth quadrant. The angles of the load sensors 121a to 121d in the installation position direction are set to θ ₁ , θ ₂ , ..., θ _n , and the signals of the respective load sensors are set to ε ₁ , ε ₂ , ..., Ε _n ( _{n in} FIG. 6). = 4).
load imbalance epsilon _y to load bias epsilon _x and y-axis directions of the x-axis direction is represented by the following formula (1).

Load imbalance evaluation unit 131 of the data evaluation unit 130 (see FIG. 1), according to equation (1), to generate a load bias data, a load imbalance epsilon _y to load bias epsilon _x and y-axis directions of the x-axis direction evaluate.
The method of calculating the load bias data when the load sensor 121 is installed on the cylindrical or columnar gripping member 110 has been described above.
In this evaluation method, load bias data can be similarly generated even when the prismatic gripping member 110 shown in FIG. 3 is used.

<Analysis / evaluation of load data of flat plate-shaped welded product and gripping member>
FIG. 7 is a diagram showing the mounting positions of the flat plate-shaped product to be welded, the gripping member, and the load sensor, and FIG. 7 (a) is a diagram when the flat plate-shaped product to be welded is in uniform contact with the mating surface. Reference numeral 7 (b) shows a case where the contact is in an inclined state in one direction. The same components as those in FIG. 4 are designated by the same reference numerals.
Further, the magnitude of the load applied to the product 1 to be welded in the x direction is shown as the magnitude of the white arrow (the larger the white arrow, the larger the load).
As shown in FIG. 7, the gripping member 110 includes a gripping member 110e and a gripping member 110f that grip the flat plate-shaped workpieces 1e and 1f to be welded by sandwiching them from the x direction. The gripping member 110e and the gripping member 110f sandwich the products 1e and 1f to be welded and apply pressure perpendicularly to the mating surface 13 to fix the products 1e and 1f to be welded. Further, four sets of the x-direction load sensors 131a to 131d and the y-direction load sensors 141a to 141d are installed.

As shown in FIG. 7A, when the flat plate-shaped workpieces 1e and 1f have no inclination and the load is applied almost evenly, the x-direction load sensor 131a and the x-direction load sensor 131d are both used. Measure approximately equal loads. Similarly, the x-direction load sensor 131b and the x-direction load sensor 131c both measure substantially the same load. Similarly, in the y direction, the y direction load sensor 134a and the y direction load sensor 141d measure the same load, and the y direction load sensor 134b and the y direction load sensor 141c measure the same load.
In this case, the load bias evaluation unit 131 (see FIG. 1) of the data evaluation means 130 evaluates that the contact state of the mating surface 13 is uniform.

On the other hand, as shown in FIG. 7B, if there is a difference between the measured values of the x-direction load sensors 131a and 131b and the measured values of the x-direction load sensors 131d and 131c, the difference causes the load in the x-axis direction. The bias ε _x can be obtained. From this load bias ε _{x in the} x direction, it is possible to obtain information on the inclination of the objects to be welded 1e and 1f and the condition of the butt surface. Similarly, when there is a difference between the measured values of the y-direction load sensors 141a and 141b and the measured values of the y-direction load sensors 141d and 141c in the y-direction, the load bias ε _y in the y-axis direction is obtained by the difference. be able to. From this load bias ε _{y in the} y direction, it is possible to obtain information on the inclination of the objects to be welded 1e and 1f and the condition of the abutting surface.
By installing a plurality of sets of four load sensors facing each other (two sets in FIG. 6) along the y direction in this way, load biases ε _x and ε _y at each installation position can be obtained.
The load bias evaluation unit 131 (see FIG. 1) of the data evaluation means 130 evaluates the direction and magnitude of the load bias on the mating surface 11 based on the difference in the measured values, and generates load bias data.

The load bias fluctuation data generation unit 132 (see FIG. 1) of the data evaluation means 130 sets a reference time based on the output signal of the welding output sensor 122 (see FIG. 1) of the data recording means 120. For example, when heating by an electric current is used as the welding means, the time of the rise of the welding output (start of energization) is set as the reference time. Then, the load bias fluctuation data generation unit 132 generates the load bias fluctuation data by adding a time difference from the reference time to the load bias data output by the load bias evaluation unit 131 at each time. For the load bias fluctuation data, by setting the time of the rise of the welding output (start of energization) as the reference time, it is possible to evaluate the welding quality of each welded product 1 at the common reference time, and the load bias changes from moment to moment. The data can be compared between each product 1 to be welded. Thereby, the pattern of the change in the contact state on the butt surface of the product to be welded during welding can be compared between the welded products.

[When registering standard data storage]
FIG. 8 is a flowchart showing a process at the time of registration for accumulating data (reference data) that serves as a reference for welding quality determination. This flow is executed by a CPU such as a server that constitutes the data evaluation means 130, for example. As a reference product to be welded, a case where a cylindrical or cylindrical product to be welded and a gripping member shown in FIG. 2 are used is taken as an example.
First, in step S1, the gripping member 110 of the data recording means 120 (see FIG. 1) sandwiches the reference good quality welded product 1 (for example, the welded products 1a and 1b in FIG. 2), and the mating surface 11 By applying pressure perpendicular to (joint surface), the products 1 to be welded (articles 1a and 1b to be welded in FIG. 2) of good quality are fixed.
In step S2, the data recording means 120 melts the butt surface 11 by applying a current (resistance welding method), and joins the products to be welded 1 (articles 1a and 1b to be welded in FIG. 2) to each other.
In step S3, the welding output sensor 122 (see FIG. 1) of the data recording means 120 measures the output for heating.

In step S4, the load sensor 121 (see FIG. 1) of the data recording means 120 measures the load (load data) experienced by the gripping member 110 as the pressure is applied.
In step S5, the recording device 123 (see FIG. 1) of the data recording means 120 continuously records the output of the welding output sensor 122 and the load data of the load sensor 121.
In step S6, the load bias evaluation unit 131 (see FIG. 1) of the data evaluation means 130 generates load bias data of the product 1 to be welded of good quality based on the load data recorded in the recording device 123. ..

In step S7, the load bias fluctuation data generation unit 132 (see FIG. 1) of the data evaluation means 130 determines the welded product 1 of good quality based on the output of the welding output sensor 122 recorded in the recording device 123. Set the reference time. For example, the time of the rise of the welding output (start of energization) is set as the reference time.
In step S8, the load bias fluctuation data generation unit 132 assigns a time difference from the reference time to the load bias data at each time during welding to obtain the load bias fluctuation data which is the time fluctuation data of the load bias. calculate.

In step S9, the recording device 133 (see FIG. 1) of the data evaluation means 130 records the load bias fluctuation data.

In step S10, the reference data storage unit 134 (see FIG. 1) of the data evaluation means 130 uses data (reference) as a reference for welding quality determination based on load bias fluctuation data of the workpiece 1 of good quality. Data) is accumulated.
By executing the above flow, the reference data storage unit 134 of the data evaluation means 130 accumulates reference data for welding quality determination for the product 1 to be welded of good quality, that is, the reference product 1 to be welded. It was.

The main registration process is executed in advance prior to the process at the time of monitoring described later, and is stored in the reference data storage unit 134 as reference data.
In addition, standard data is accumulated for each product to be welded according to the shape and type of the product to be welded, the usage conditions of the welding machine (resistance welding, laser welding, friction stir welding), processing equipment (press machine), etc. ..

FIG. 9 is a flowchart showing a process during monitoring for determining the welding quality of the workpiece to be welded. This flow is executed by a CPU such as a server that constitutes the data evaluation means 130, for example. As a reference product to be welded, a case where a cylindrical or cylindrical product to be welded and a gripping member shown in FIG. 2 are used is taken as an example.
First, in step S11, the gripping member 110 of the data recording means 120 (see FIG. 1) sandwiches the welded product 1 (for example, the welded products 1a and 1b in FIG. 2) to be welded and monitored, and the mating surface 11 (joining). By applying pressure perpendicular to the surface), the welded products 1 (welded products 1a and 1b in FIG. 2) to be monitored for welding are fixed.
In step S12, the data recording means 120 melts the butt surface 11 by applying a current (resistance welding method), and connects the welded products 1 (welded products 1a and 1b in FIG. 2) to be welded and monitored. Join.

In step S13, the welding output sensor 122 (see FIG. 1) of the data recording means 120 measures the output for heating.
In step S14, the load sensor 121 (see FIG. 1) of the data recording means 120 measures the load (load data) experienced by the gripping member 110 as the pressure is applied.
In step S15, the recording device 123 (see FIG. 1) of the data recording means 120 continuously records the output of the welding output sensor 122 and the load data of the load sensor 121.

In step S16, the load bias evaluation unit 131 (see FIG. 1) of the data evaluation means 130 calculates the load bias data of the workpiece 1 to be welded and monitored based on the load data recorded in the recording device 123. To do.

In step S17, the load bias fluctuation data generation unit 132 (see FIG. 1) of the data evaluation means 130 is a welded product to be monitored for welding based on the output signal of the welding output sensor 122 recorded in the recording device 123. Set the reference time of 1. For example, the time of the rise of the welding output (start of energization) is set as the reference time.
In step S18, the load bias fluctuation data generation unit 132 calculates the load bias fluctuation data by adding a time difference from the reference time to the load bias data at each time during welding.

In step S19, the recording device 133 (see FIG. 1) of the data evaluation means 130 records the load bias fluctuation data.
In step S20, the reference data storage unit 134 (see FIG. 1) of the data evaluation means 130 uses data (reference) as a reference for welding quality determination based on load bias fluctuation data of the workpiece 1 of good quality. Data) is accumulated.

In step S21, the difference extraction unit 135 (see FIG. 1) of the data evaluation means 130 uses the load bias fluctuation data of the welded product to be monitored for welding as reference data (load bias fluctuation data of the welded product of good quality). If the difference is smaller than the predetermined value, it is judged that the welding quality of the product to be welded is good.

As described above, the welding monitoring system 100 of the present embodiment includes a gripping member 110 that abuts and fixes a plurality of objects to be welded 1 at joint surfaces, and a plurality of load sensors that detect a load applied to the gripping member 110. A recording device that continuously records the output of the welding output sensor 122 that measures the output of the welding means that heats the mating surface 11 of the product 1 to be welded, the output of the welding output sensor 122, and the load data of the load sensor 121. 123 and. Further, based on the load data recorded in the recording device 123, the load bias evaluation unit 131 that generates load bias data due to the objects 1 to be welded not contacting each other uniformly on the mating surface 11 and the recording device 123. Based on the output signal of the welding output sensor 122 recorded in, the reference time during welding is set, and the time difference from the above reference time is added to the load bias data at each time during welding. The load bias fluctuation data generation unit 132 that generates the load bias fluctuation data which is the time fluctuation data of the load bias, the recording device 133 that records the generated load bias fluctuation data, and the load bias fluctuation data recorded in the recording device 133. Based on this, the reference data storage unit 134 that stores the data that serves as the reference for determining the welding quality and the load bias fluctuation data recorded in the recording device 133 are compared with the reference data stored in the reference data storage unit 134. The difference extraction unit 135 for extracting the difference is provided.

With this configuration, the load bias fluctuation data, which is the time fluctuation data of the load bias, is generated every time the welded product 1 is welded, and can be compared with the reference data of the product to be welded of good quality. The melting state of the butt surface 11 can be estimated based on the information reflecting the transient change in the joining state during welding. In addition, it is possible to determine the variation in welding quality in real time, which can be useful for quality control (improvement of quality) of welded products. In particular, when this welding monitoring system is used as a system for quality assurance of mass-produced welded products, it is possible to inspect without stopping the production line. Therefore, it is possible to inspect the entire amount.

In the present embodiment, the registration process (see FIG. 8) for accumulating the load bias fluctuation data of the product to be welded of good quality is executed, but instead of executing this registration process, each product to be welded The load bias fluctuation data may be accumulated, and the product corresponding to the standard set value may be used as a good quality welded product. In this case, statistical processing such as using the past value of the load bias fluctuation data of each welded product may be performed. There is an advantage that the registration process does not have to be executed.

(Second Embodiment)
FIG. 10 is a diagram showing a configuration of a welding monitoring system according to a second embodiment of the present invention. The same components as those in FIG. 1 are designated by the same reference numerals, and the description of overlapping portions will be omitted.
As shown in FIG. 10, the welding monitoring system 200 includes a gripping member 110 that abuts and fixes a plurality of objects to be welded 1 at joint surfaces, and a data recording means 120 that records load data during the welding process (during welding). The data evaluation means 230 is provided for analyzing and evaluating the load data recorded by the data recording means 120.
The data evaluation means 230 includes a load bias evaluation unit 231, a load bias fluctuation data generation unit 132, a recording device 133, a reference data storage unit 134, and a difference extraction unit 135.

The load bias evaluation unit 231 includes a vibration mode decomposition unit 232, an x-direction bias extraction unit 233, and a y-direction bias extraction unit 234.
The vibration mode decomposition unit 232 receives the measurement data of each load sensor 121 from the data recording means 120, and decomposes the data into vibration frequency components.
The x-direction bias extraction unit 233 receives the data processed by the vibration mode decomposition unit 232, calculates the load bias in the x-direction according to the above equation (1), and sends the data to the load bias fluctuation data generation unit 132.
The y-direction bias extraction unit 234 receives the data processed by the vibration mode decomposition unit 232, calculates the load bias in the y-direction according to the above equation (1), and sends the data to the load bias fluctuation data generation unit 132.

The vibration mode decomposition unit 232 extracts a vibration mode of a specific frequency from the load data by Fourier transform.
As a result, it is possible to extract the magnitude of vibration accompanying the sudden displacement of the product to be welded during welding and remove other frequency components unrelated to the vibration of the product to be welded. As a result, data that suppresses noise other than vibration on the joint surface can be obtained, and the accuracy of determining the welding quality can be improved.

As described above, according to the second embodiment, the load bias evaluation unit 231 of the data evaluation means 230 includes the vibration mode decomposition unit 232, so that the welding quality determination accuracy can be improved. For example, it is possible to investigate the degree of melting in each direction in which the time change (vibration) of the load distribution during welding is large. Therefore, according to the welding monitoring system 200 of the present embodiment, the welding quality of the product to be welded can be improved.

(Third Embodiment)
FIG. 11 is a diagram showing a configuration of a welding monitoring system according to a third embodiment of the present invention. The same components as those in FIG. 10 are designated by the same reference numerals, and the description of overlapping portions will be omitted.
As shown in FIG. 11, the welding monitoring system 300 includes a gripping member 110 that abuts and fixes a plurality of objects to be welded 1 at joint surfaces, and a data recording means 120 that records load data during the welding process (during welding). The data evaluation means 330 for analyzing and evaluating the load data recorded by the data recording means 120 is provided.
The data evaluation means 330 includes a load bias evaluation unit 231, a load bias fluctuation data generation unit 332, a recording device 133, a reference data storage unit 134, and a difference extraction unit 335.

The load bias fluctuation data generation unit 332 displays the load bias in the x direction and the load bias in the y direction calculated by the load bias evaluation unit 231 as one point on the two-dimensional plane as the x coordinate value and the y coordinate value. To generate. That is, the load bias fluctuation data generation unit 332 generates display data that visualizes and displays the time change (vibration) of the load distribution during welding on a two-dimensional plane of the load bias in the x direction and the load bias in the y direction. To do. Further, the load bias fluctuation data generation unit 332 connects the time changes (vibrations) with a line and generates a single image as a locus of the load bias fluctuation. The locus is drawn so that the difference between the time when the data corresponding to the point on the locus is obtained and the reference time can be read.

The difference extraction unit 335 compares the load bias fluctuation data of the welded product to be welded and compared with the reference data, and determines that the welding quality of the welded product is good when the time change (vibration) is smaller than the predetermined value. To do.

FIG. 12 is a diagram showing drawing of the display data generated by the load bias fluctuation data generation unit 332 on a two-dimensional plane. FIG. 12A shows a drawing of the generated display data on a two-dimensional plane based on a product to be welded of good quality. Further, FIGS. 12 (b)-(d) show drawing of the generated display data on a two-dimensional plane based on the object to be welded to be monitored for welding. In FIG. 12A, each point (p0-p4) is drawn (plotted) from the reference time as the base point (S; p0) to the end point (E; p5) at regular intervals (black circles (● marks). )reference). Further, the time change (vibration) is drawn as the locus 11 of the load bias fluctuation. It should be noted that the locus 11 of the load bias fluctuation may be drawn by changing the brightness and color with time to generate an image. The difference between the data of the time change becomes clearer, and the welding quality can be evaluated.

In the above, the vibration mode decomposition unit 232 of the load bias evaluation unit 231 decomposes the measurement data of each load sensor 121 into vibration frequency components from the data recording means 120, and the x-direction bias extraction unit 233 and the y-direction bias extraction unit 234. Is an example of calculating the load bias in the x-direction and the y-direction according to the above equation (1). As shown in FIGS. 4 and 7, when a plurality of sets of four opposing load sensors 131 and 141 are installed instead of the example using the formula (1), from each set, FIG. 12 (b) -A locus image of the load bias fluctuation illustrated in (d) can be obtained.

FIG. 13 is a flowchart showing a process at the time of monitoring for determining the welding quality of the workpiece to be welded. The same process as the flow shown in FIG. 9 is given the same step number, and the description of the overlapping portion is omitted.
When the load bias fluctuation data is generated in step S18, the load bias fluctuation data generation unit 332 generates display data for displaying the generated load bias fluctuation data on a two-dimensional plane in step S31. For example, as shown in FIG. 12A, strain bias is performed on a graph in the x / y direction parallel to the joint surface, with the reference time as the base point (S; p0) and at regular intervals up to the end point (E; p5). The locus 11 and each point (p0-p5) are drawn.
As a result, the load distribution and its vibration over time (that is, load bias fluctuation data) can be visualized and displayed.

In step S32, the difference extraction unit 335 of the data evaluation means 130 compares the load bias fluctuation data of the welded product to be welded with the reference data (load bias fluctuation data of the welded product of good quality), and time. When the change (vibration) is smaller than the predetermined value, it is judged that the welding quality of the workpiece is good.
As a result, the welding quality of the product to be welded can be evaluated by comparing the load distribution with the reference data of the time change of the vibration (that is, the load bias fluctuation data).

<Evaluation example>
An example of evaluating the welding quality of the workpiece to be welded will be described with reference to FIGS. 12 (b)-(d).
As a result of measuring the load data for a certain product to be welded, it is assumed that the display data shown in FIG. 12B is obtained. When the drawing of the display data shown in FIG. 12B and the drawing of the reference data shown in FIG. 12A are compared, from the base point (S; p0) to the end point (E; p5) of both reference times. Since the point (p0-p5) and the locus 11 are similar to each other, it is judged to be normal (good welding quality).
Further, when the drawing of the display data shown in FIG. 12 (c) and the drawing of the reference data shown in FIG. 12 (a) are compared, the vibration of the load distribution of the display data shown in FIG. 12 (c) is small. The product to be welded measured at this time is judged to be abnormal (poor welding quality).
Further, when the drawing of the display data shown in FIG. 12D is compared with the drawing of the reference data shown in FIG. 12A, the load distribution of the display data shown in FIG. 12D has a large vibration. The product to be welded measured at this time is judged to be abnormal (poor welding quality).

The similarity determination method is as follows.
(1) Compare the distances from the base point (S; p0) to each point (p0-p5), take the sum of them to obtain the deviation, and if the deviation falls within the predetermined range, it is normal and does not fit. If not, it is judged as abnormal.
(2) The area inside the locus 11 of both is calculated, the calculated areas are compared, and if the difference value of the area falls within a predetermined range, it is determined to be normal, and if it does not fall, it is determined to be abnormal.
(3) A plurality of loci 11 on the x / y direction graph of the reference data are registered as basic patterns, and the measured patterns of the workpiece to be welded are matched by pattern matching to compare with the plurality of basic patterns. If there is a pattern, it is judged as normal, and if it is not, it is judged as abnormal.

For example, when the similarity determination method (1) is adopted, the distance from the base point (p0) to the point (p1) in FIG. 12 (b) and the distance from the base point (0) to the point (p1) in FIG. 12 (a). Find the difference from the distance of. Similarly, the difference between the base point (0) and the distance to each point (p1-p5) is obtained, and the sum of these differences is compared with a predetermined value to determine normal / abnormal.

As described above, according to the third embodiment, the load bias fluctuation data generation unit 332 can classify the pattern of the large-capacity welding data by generating the load bias locus 11 image (see FIG. 12). It is possible to improve the classification accuracy of welding quality.

(Fourth Embodiment)
FIG. 14 is a diagram showing a configuration of a welding monitoring system according to a fourth embodiment of the present invention. The same components as those in FIG. 1 are designated by the same reference numerals, and the description of overlapping portions will be omitted.
As shown in FIG. 14, the welding monitoring system 400 includes a gripping member 110 that abuts and fixes a plurality of objects 1 to be welded at joint surfaces, and a data recording means 420 that records load data during the welding process (during welding). The data evaluation means 130 for analyzing and evaluating the load data recorded by the data recording means 420 is provided.
The data recording means 420 includes an individual identification unit 421 that obtains information (individual identification information) for identifying an individual to be welded, and a plurality of load sensors 121 that detect a load applied to the gripping member 110. , The welding output sensor 122 for measuring the output for heating the mating surface 11 of the welded product 1 (for example, the welded products 1a and 1b in FIG. 2), the output of the welding output sensor 122, and the load data of the load sensor 121. It includes a recording device 123 for continuously recording.
The individual identification unit 421 generates individual identification information by, for example, photographing or engraving the appearance. The individual identification information is transmitted to the data evaluation means 130, and is recorded in the recording device 133 in association with the load bias fluctuation data.

As described above, according to the fourth embodiment, the welding monitoring system 400 includes the individual identification unit 421, so that the accuracy of determining the welding quality can be improved.
For example, when a feature of a certain product to be welded that could not be identified in the manufacturing process is later grasped, the load bias fluctuation data recorded in the recording device 133 based on the individual identification information can be reviewed to perform the following. It can be fed back to the welding quality judgment in the manufacturing process. By repeating this feedback process, the welding quality determination accuracy can be improved.

(Fifth Embodiment)
The welding monitoring system according to the fifth embodiment of the present invention will be described.
The welding monitoring system according to the present embodiment shows an example of a notification process that notifies the related equipment of the production line and the site supervisor of the occurrence of an abnormality when an abnormality is detected in the welding quality.
FIG. 15 is a diagram showing a configuration of a welding monitoring system according to a fifth embodiment of the present invention. The same components as those in FIG. 1 are designated by the same reference numerals, and the description of overlapping portions will be omitted.
As shown in FIG. 15, the welding monitoring system 500 further controls the abnormality notification means 501, PLCs (Programmable Logic Controllers) 502 and 504, and the entire production system in addition to the welding monitoring system 100 of FIG. The MES (Manufacturing Execution System) 503 is provided. PLC502, 504 and MES503 are related equipment on the production line.

When an abnormality is detected in the welding quality by the difference extraction unit 135, the abnormality notification means 501 notifies the related equipment of the production line and the site supervisor 10 of the occurrence of the abnormality.
The welding monitoring system 500 notifies the detected abnormality to the MES503 and the mobile terminal 20 that control the entire production system via the PLCs 502 and 504. As a result, necessary control can be executed when the MES503 abnormality is detected.

As described above, according to the fifth embodiment, when an abnormality in welding quality is detected by the difference extraction unit 135, the detected abnormality can be notified to the MES 503 or the mobile terminal 20 via the PLCs 502 and 504. It is possible to control the operating status of the production line.

The present invention is not limited to the above embodiments, and includes other modifications and applications as long as it does not deviate from the gist of the present invention described in the claims. For example, as shown in FIG. 16, the welding device W including the welding monitoring system of the embodiment (for example, the welding monitoring system 100 of FIG. 1) can be used.
Further, for example, a part of the configuration of one embodiment can be replaced with the configuration of another embodiment, and the configuration of another embodiment can be added to the configuration of one embodiment. Is. Further, it is possible to add / delete / replace a part of the configuration of each embodiment with another configuration.

In addition, the control lines and information lines are shown as necessary for explanation, and not all control lines and information lines are shown in the product. In practice, it can be considered that almost all configurations are interconnected.

100,200,300,400,500 Welding monitoring system (joint monitoring system)
1,1a, 1b Welded product (welded product)
11 Mating surface (joint surface)
110 Gripping member 110a Upper gripping member 110b Lower gripping member 120, 420 Data recording means 121, 121a to 121d Load sensor 122 Welding output sensor (joint output sensor)
123 Recording device 130, 230, 330 Data evaluation means 131,231 Load bias evaluation unit 131a to 131d x direction load sensor 141a to 141dy direction load sensor 132,332 Load bias fluctuation data generation unit 133 Recording device 134 Reference data storage unit 135 Difference extraction unit 231 Load bias evaluation unit 232 Vibration mode decomposition unit 233 x-direction bias extraction unit 234 y-direction bias extraction unit 421 Individual identification unit 501 Abnormality notification means 502,504 PLC
503 MES
W Welding equipment (joining equipment)

Claims (8)

Multiple load sensors that detect the load applied to the gripping member that abuts and fixes multiple objects to be joined at the joint surface,
A bonding output sensor that measures the output of the bonding means that heats the bonding surface of the product to be bonded, and
A recording device that continuously records the output of the junction output sensor and the load data of the load sensor, and
Based on the load data recorded in the recording device, the load bias evaluation unit calculates the bias of the load distribution due to the plurality of the objects to be joined not uniformly contacting each other on the joint surface as the load bias data. ,
Based on the output of the junction output sensor recorded in the recording device, the reference time during the junction is set, and the time difference from the reference time is given to the load bias data at each time during the junction. Then, the load bias fluctuation data generator that generates the load bias fluctuation data, which is the time fluctuation data of the load bias,
A recording device that records the generated load bias fluctuation data, and
A joint monitoring system including a reference data storage unit that stores reference data that serves as a reference for determining joint quality based on the load bias fluctuation data recorded in the recording device. The joint monitoring system according to claim 1, further comprising a difference extraction unit that compares load bias fluctuation data with reference data to extract differences. The difference extraction unit
The joint monitoring system according to claim 2, further comprising notifying when an abnormality in the joint quality of the product to be joined is detected. The junction monitoring system according to claim 1, wherein the load bias evaluation unit extracts a vibration mode of a specific vibration frequency and / or decomposes the load bias into the x-axis direction and the y-axis direction. .. It is provided with an individual identification unit that identifies the individual of the material to be joined.
The reference data storage unit
The joint monitoring system according to claim 1, wherein the identified individual identification information and the load bias fluctuation data are accumulated as a set. The load bias fluctuation data generation unit
The joint monitoring system according to claim 1, wherein display data for visualizing the calculated load bias data is generated. The load bias fluctuation data generation unit
The first or sixth aspect of claim 1 or 6, wherein the calculated load bias data is made to correspond to a two-dimensional plane, and the time change is connected by a line to generate display data for displaying the trajectory of the load bias change. The described junction monitoring system. A joining device comprising the joining monitoring system according to any one of claims 1 to 7.

Images