JPH0631463A - Method for diagnosing welding machine - Google Patents

Abstract

PURPOSE:To quickly determine the propriety of equipment operation by making a diagnosis based on a guidance function to display the output in order of the incidence of various factors of an equipment abnormal phenomenon of the welding machine. CONSTITUTION:Abnormality of welding machine working numerical values of a welding current, the welding voltage, the welding speed, the pressurizing force of an electrode ring, etc., at the time of resistance-welding of steel materials and abnormality by trend value control based on a specified reference value are quickly detected as the alarm output and the various factors in relation to the equipment abnormal phenomenon of the welding machine detected at the time of this alarm output and the corresponding guide to these abnormal factors are diagnosed based on the guidance function to display the output in order of the incidence of each factor. Consequently, abnormality of the welding machine is quickly detected regardless of the change of welding conditions and a kind of steel and the propriety of equipment operation can be quickly determined.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for diagnosing a welding machine during resistance welding of a steel material, and in particular predicts an abnormality of the welding machine from fluctuations in measured values of welding current and welding voltage, and further measures each of these measured values. This is a proposal of a method for specifically diagnosing the condition of the equipment abnormality of the welding machine from the trend value management data accumulating the variations of the above.

[0002]

2. Description of the Related Art Generally, in resistance welding such as seam welding, as shown in FIG. 1, current is applied to a joint portion of materials to be welded (base material) 2 which are superposed via an electrode 1, and a resistance heating melting portion ( This is a technique in which both base materials are welded through the nugget 3 by forming the nugget) 3. Therefore, since the formation state of the nugget 3 is a factor that greatly affects the welded portion quality such as welding strength, the operating state of the resistance welding machine that affects the formation state of the nugget 3, that is, the welding current and the welding current. It is extremely important to control the welding machine operating values such as voltage.

As a conventional technique for diagnosing the welding state or the state of welding equipment by managing the operating values of the welding machine such as the welding current and the welding voltage, there is, for example, Japanese Patent Laid-Open No.
There is a method disclosed in Japanese Patent No. 32474. This disclosed technology calculates the amount of electric power input to the welding machine by inputting an output signal of a welding machine operation value such as welding current and welding voltage for each welding, and compares the amount of electric power with a preset reference value. By doing so, it is a method of detecting an abnormality in a welding machine operation value such as a welding current and a welding voltage, and by extension, an abnormality in a welding state.

[0004]

However, the above-mentioned prior art is a method of comparing the welding machine operation numerical values such as welding current and welding voltage with the reference value by an absolute value for each welding. For example, detection is effective for the occurrence of equipment abnormalities during one-time welding where the conditions do not change, but when the plate thickness or steel type of the material to be welded changes, the welding conditions also change,
The reference value has to be changed, and if this value is left as it is for diagnosis, a malfunction such as abnormal equipment may occur.

Therefore, conventionally, it is necessary to change the abnormality diagnosis reference value in accordance with changes in welding conditions. Therefore, not only is trend management based on a specific reference value impossible, but it is also necessary to operate the welding machine. However, there is a drawback that the tendency regarding the can not be grasped promptly.

Therefore, the present invention aims to overcome the drawbacks of the above-mentioned prior art, and in particular, regardless of changes in welding conditions and steel grades, abnormalities in welding machine operating values such as welding current and welding voltage, In other words, while quickly detecting a welder abnormality, by controlling the trend value of the abnormal state based on a specific reference value, it is possible to quickly determine whether the equipment should operate or not, and to take prompt and appropriate measures against the welder equipment abnormality. The purpose is to propose a welding machine diagnostic technique that can be used.

[0007]

As a result of earnest research for achieving the above-mentioned object, the inventors of the present invention have found that, when paying attention to variations in welding machine operating values such as welding current and welding voltage at each welding, According to the management by the variation, it is found that it is possible to manage the tendency value of the abnormal state by each detected value without the need to change the reference value for diagnosis as in the prior art, and in this tendency value management By displaying the concrete countermeasures based on the equipment abnormality on the CRT etc. as a guidance function, it is possible to promptly judge the propriety of equipment operation and take prompt and appropriate measures against the equipment abnormality of the welding machine. As a result, the inventors have come up with the method of the present invention as described below.

That is, according to the present invention, welding machine operation numerical values such as welding current, welding voltage, welding speed, and electrode wheel pressing force at the time of resistance welding of steel materials are output and compared and analyzed with a preset reference value. Detects the equipment abnormality of the welding machine as an alarm output, and calculates these variations from the maximum value, the minimum value and the average value of at least one or more of the above operating values, and compares them with a preset reference value. By managing trend values under comparison, when determining whether to operate the equipment, various factors related to the detected abnormalities in the equipment of the welding machine and a guide for dealing with these abnormal factors are generated. It is a welding machine diagnostic method characterized in that diagnosis is performed based on a display of a guidance function that outputs and displays in order of ratio.

[0009]

FIG. 2 is a system configuration diagram showing an embodiment of a welding machine diagnosing method according to the present invention. The welding machine operating values such as welding current, welding voltage, and welding speed are shown for each welding. Is compared with a preset reference value to detect an abnormality in the welding machine, and the variation (variation) of the measured value is evaluated under trend value management to detect an abnormality in the welding machine,
Output and display various factors related to this abnormal phenomenon and a guide for dealing with these abnormal factors in the order of occurrence rate of each factor,
It is a system that promptly judges whether the equipment is operating or not based on the display of the guidance function.

In this figure, at each welding,
Output signals of welding machine operation numerical values such as welding current and welding voltage having waveforms as shown in FIG. 3 measured at high speed are input to the storage device 4, respectively. Next, from the data signal accumulated in the storage device 4, the variation calculating circuit 5 calculates the variation σ = (maximum value−minimum value) / average value, and inputs it to the abnormality detection circuit 6 and the tendency value management determination circuit 7. Then, the abnormality of the welding machine is always detected online.

That is, the abnormality detection circuit 6 detects the facility abnormality of the welding machine at each welding time by comparing the input value with the reference value in absolute value, and outputs an alarm. On the other hand, in the tendency value management judgment circuit 7, based on the output signal of the equipment abnormality, as shown in FIG. 4, data in which the variation σ accumulated at each welding is managed as a tendency value and a specific reference value are set. By comparing and determining the above, the abnormal phenomenon of the equipment of the welding machine is detected over time and an alarm is output.

[0012] Here, the abnormal phenomena of the equipment of the welding machine and various factors that cause these abnormal phenomena are associated in advance, and the occurrence rate of each of the above factors and the factors thereof are eliminated from past failure records. A correspondence guide for doing so is set in advance in the abnormality correspondence determination circuit 11 having a guidance function (see Tables 1 and 2).

[0013]

[Table 1]

[0014]

[Table 2]

Then, in response to the above-mentioned alarm output, the abnormality handling determination circuit 11 diagnoses the detected abnormalities of the welding machine facility based on the guidance function, and various factors related to the abnormal phenomena and these abnormalities. Corresponding guides for factors are output and displayed on the CRT 13 or the like in the order of occurrence rates of each factor set in advance.

Therefore, according to the present invention, the worker can grasp the cause of the facility abnormality of the welding machine and the corresponding guide for eliminating the cause at an early stage, and promptly know whether the facility is in operation or not. It is possible to judge and take prompt measures against abnormalities. As a result, the work stoppage for adjusting the equipment of the welding machine is minimized, welding breakage of steel can be significantly reduced, welding accuracy and product yield can be improved, and line operation rate can be greatly improved. It

[0017]

EXAMPLES An example in which the welding machine diagnostic method according to the present invention is applied to a seam welding machine installed on the inlet side of a continuous processing line for steel strips will be described with reference to FIGS. 2 to 4 and Tables 1 and 2. . In addition, as shown in FIG. 1, welding using this seam welder is performed by superposing the tail end portion of the preceding steel strip and the tip end portion of the trailing steel strip, and by superposing the superposed portion on a pair of upper and lower electrode wheels. While pressing, move in the width direction of the steel strip.

In the welding machine diagnosing method of the present invention, first, a signal obtained by measuring a welding current, a welding voltage, a welding speed (a peripheral speed of an electrode wheel), a pressing force of the electrode wheel, etc. during seam welding is stored as each signal. Input to the device 4. In FIG. 3, for example, the welding current is measured at a cycle of 3 msec, and the horizontal axis indicates time or the position in the width direction of the steel strip.

Next, each data signal thus accumulated in the storage device 4 is input to the variation calculation circuit 5, and the variation calculation circuit 5 calculates the variation σ of each data signal for each welding and The result is input to the abnormality detection circuit 6 and the tendency value management determination circuit 7.

Then, in the abnormality detecting circuit 6, similarly to the prior art, the abnormality of the welding machine is detected by comparing the input value with the reference value in absolute value. That is, when the input value exceeds the reference value, it is detected that there is an abnormality in the welding machine, and it serves as a trigger signal to display an alarm and the like, and the variation stored in the trend value management determination circuit 7 is The trend value management data obtained by comparing σ with a specific reference value is detected and displayed on a CRT or the like.

On the other hand, the tendency value management judgment circuit 7 compares the variation σ with a specific reference value, and when the value of the variation σ exceeds the reference value, it is detected that the welding machine is abnormal,
It becomes a trigger signal and an alarm or the like is displayed.

Further, the trigger signal output from the abnormality detection circuit 6 and / or the tendency value management determination circuit 7 is converted into a related abnormality factor and an abnormality countermeasure guide for this abnormality factor in the abnormality countermeasure determination circuit 11. ,
It is a diagnostic system in which the occurrence rate of each factor is output and displayed on a CRT, etc., and the concreteness of the operation of the equipment is determined based on the display result of the guidance function.

Here, the guidance function of the abnormality handling determination circuit 11 will be described. In this abnormality correspondence determination circuit 11,
Abnormal factors for each device constituent element, which are considered for each abnormal phenomenon and correspond to the welding abnormal phenomenon as shown in Table 1 and the apparatus constituent elements of the welding machine, are input together with the past occurrence rate.
Further, the abnormality handling determination circuit 11 is inputted with an abnormality handling guide as shown in Table 2 which is preset in association with the abnormality factors in Table 1.

Therefore, the abnormality handling determination circuit 11 uses the trigger signal input for each specific abnormality phenomenon as the cause of abnormality of the device components corresponding to these signals, and an abnormality handling guide for eliminating this cause. It has a guidance function of converting to and, based on the occurrence rate set in advance for each abnormality factor as shown in Table 1, the output is displayed on the CRT or the like in descending order of the occurrence rate.

As a result, the worker can promptly take appropriate measures against the abnormality such as performing inspection and repair offline without being confused by the plurality of abnormality factors displayed on the CRT and the abnormality countermeasure guide. You can

The occurrence rate set for each of the above-mentioned abnormal factors changes according to the number of years that the welding machine has been operating, failure countermeasure activities, etc. Therefore, the rate of occurrence is regularly, for example, about once a year. It is necessary to review and set again in. Regarding this, it is performed by re-inputting the occurrence rate of the abnormality factor using the data input device 12 connected to the abnormality correspondence determination circuit 11, and as a result, the correspondence guide for the abnormality is always output normally, and the welding machine It is possible to take prompt and appropriate measures against equipment abnormalities.

[0027]

As described above, according to the welding machine diagnosis method of the present invention, regardless of changes in welding conditions and steel types,
Abnormalities in welding machine operating values such as welding current and welding voltage, that is, abnormalities in the welding machine, and abnormalities due to trend value management based on specific reference values can be quickly detected as an alarm output, and at the time of the above-mentioned alarm output. , The various factors related to the detected abnormalities in the welding machine and the guides for dealing with these abnormal factors are output and displayed on the CRT13 etc. in the order of occurrence rate of each factor, so the operator can display the guidance function. Based on this, it is possible to grasp the cause of the equipment abnormality of the welding machine and the correspondence guide for eliminating the cause at an early stage, to promptly judge the propriety of the equipment operation, and to promptly respond to the equipment abnormality of the welding machine. Appropriate measures can be taken. In addition, this makes it possible to prevent welding breakage of the steel material during welding and to significantly improve the line operating rate.

[Brief description of drawings]

FIG. 1 is an explanatory diagram showing the principle of seam resistance welding.

FIG. 2 is a system configuration diagram showing an embodiment of a welding machine diagnosis method according to the present invention.

FIG. 3 is a diagram showing an example of an input signal obtained by measuring a welding current at a cycle of 3 msec.

FIG. 4 is a diagram showing an output example of trend value management data of variation σ.

[Explanation of symbols]

 1 electrode 2 welded material 3 nugget 4 storage device 5 variation calculation circuit 6 abnormality detection circuit 7 trend value management determination circuit 8 raw signal 9 measurement point 10 abnormality determination reference value 11 abnormality response determination circuit 12 data input device 13 CRT

Claims (1)

[Claims] 1. A welding machine operating numerical value such as a welding current, a welding voltage, a welding speed, a welding force of an electrode wheel, etc., during resistance welding of a steel material is output and compared with a preset reference value to analyze the welding machine. The equipment abnormality is detected as an alarm output, and these variations are calculated from the maximum value, the minimum value and the average value of at least one or more of the above-mentioned output values, and compared with a preset reference value. By managing trend values, when determining whether to operate the equipment, various factors related to the detected abnormalities of the welding machine equipment and a guide for dealing with these abnormality factors are output in order of occurrence rate of each factor. A method for diagnosing a welding machine, characterized by diagnosing based on the display of a guidance function.