JP2002323355A - Abnormality detection device for painting gun and its method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an abnormality detection device for painting gun capable of detecting an abnormality of a painting gun automatically and easily. SOLUTION: Frequency analysis of vibration detected by a vibration sensor for detecting vibration of the painting gun is executed, and the value of a function acquired by multiplying an inner product function between a frequency at the normal time and a frequency during painting by the ratio between the magnitude of the frequency at the normal time and the magnitude of the frequency during painting is calculated, and the abnormality of the painting gun is judged based on the calculation result.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an apparatus and a method for detecting an abnormality of a paint gun for spraying paint.

[0002]

2. Description of the Related Art A coating gun sprays paint on an object to be coated by spraying. In such a coating gun, abnormalities such as clogging may occur during coating, which may cause uneven coating.

Conventionally, in order to detect such an abnormality,
For example, in Japanese Patent Application Laid-Open No. Hei 8-29211, vibration of a coating gun during a painting operation is detected, the vibration is analyzed, and a frequency distribution pattern at that time is compared with a frequency distribution pattern in a normal state. It is disclosed to detect a clogging abnormality.

[0004]

As compared with the prior art, when comparing the frequency distribution patterns during normal operation and during the painting operation, when an operator looks at the patterns and compares them, an abnormality is determined from the difference between the two patterns. Can be.

However, when it is considered that this is automatically determined by a personal computer or the like, both patterns are compared as figures. The comparative study of figures requires a certain amount of time even with recent advances in computer technology, and thus has a problem in that the judgment is delayed. There is also a problem that it is difficult to compare the figures in the first place and to determine how much difference between the two patterns is determined to be abnormal. This is because, in order to automate the process of human judgment by looking at a figure on a personal computer, it is necessary to create a program to execute such a judgment process, and creating such a program is difficult unlike numerical comparison That's why.

In particular, it is very difficult to determine the state of semi-clogging of the spray nozzle of the coating gun by humans only by comparing the patterns of the frequency analysis results, and such a semi-clogged state is also reliably determined. There is a need for an analysis method that can do this.

SUMMARY OF THE INVENTION An object of the present invention is to provide an apparatus and a method for automatically and easily detecting an abnormality of a coating gun, particularly a half-clogged state. .

[0008]

The above object is achieved by the following means.

(1) Vibration detecting means for detecting the vibration of the coating gun, frequency analyzing means for analyzing the frequency of the vibration detected by the vibration detecting means, and a normal frequency analyzed by the frequency analyzing means. Calculation means for calculating a value of a function obtained by multiplying the inner product function obtained from the frequency during painting analyzed by the frequency analysis means by the ratio of the magnitude of the normal frequency to the magnitude of the frequency during painting, Determining means for determining an abnormality of the coating gun based on a result of the calculation of the function.

(2) Vibration detecting means for detecting the vibration of the coating gun, frequency analyzing means for analyzing the frequency of the vibration detected by the vibration detecting means, and a normal frequency analyzed by the frequency analyzing means. Calculation means for calculating a value of a function obtained by multiplying a correlation function obtained from the frequency during painting analyzed by the frequency analysis means by a ratio of the magnitude of the normal frequency to the magnitude of the frequency during painting, Determining means for determining an abnormality of the coating gun based on a result of the calculation of the function.

(3) The frequency is in the range of 5 to 22 kHz.

(4) The frequency range of 5 to 22 kHz is extracted from the vibration detected by the vibration detecting means before being sent to the frequency analyzing means.

(5) The normal frequency is a result of analysis by the frequency analyzing means from vibration detected by the vibration detecting means in a normal state for 0.75 seconds to less than 12.5 seconds. I do.

(6) detecting the vibration of the coating gun in a normal state, performing a frequency analysis of the detected vibration in the normal state, and detecting the vibration of the coating gun during coating. Performing a frequency analysis of the vibration during the painting, and an inner product function obtained from the analyzed normal frequency and the analyzed frequency during the painting, the magnitude of the normal frequency and the frequency during the painting. Calculating a value of a function multiplied by a magnitude ratio; and determining an abnormality of the coating gun based on a calculation result of the correlation evaluation function. .

(7) detecting the vibration of the coating gun in a normal state, performing a frequency analysis of the detected vibration in the normal state, and detecting the vibration of the coating gun during coating. Performing a frequency analysis of the vibration during the coating, and a correlation function obtained from the analyzed normal frequency and the analyzed frequency during the coating, the magnitude of the normal frequency and the magnitude of the frequency during the painting. Calculating a value of a function multiplied by an aspect ratio; and determining an abnormality of the coating gun based on a calculation result of the evaluation function.

(8) The frequency is in the range of 5 to 22 kHz.

(9) The frequency range of 5 to 22 kHz is extracted from the detected vibration before frequency analysis.

(10) In the step of performing the frequency analysis of the vibration in the normal state, the analysis is performed based on the vibration detected in the normal state for 0.75 seconds or more and less than 12.5 seconds.

[0019]

The present invention has the following effects for each claim.

According to the first aspect of the present invention, the vibration means detects the vibration of the coating gun during the painting operation, and the frequency analysis means decomposes the detected vibration for each frequency component. Calculate the value of a function obtained by further multiplying the inner product function obtained from the normal frequency and the frequency during painting by the ratio of the magnitude of the normal frequency to the magnitude of the frequency during painting. Since it was decided to determine the abnormality based on a predetermined threshold from the calculation result of the function,
An abnormality of the coating gun can be detected by numerical calculation. In particular, by using the value of the function multiplied by the ratio of the magnitude of the frequency during normal operation to the magnitude of the frequency during painting, abnormalities that were difficult to determine with the conventional frequency pattern analysis such as semi-clogging are also detected. It is possible to do. Therefore, the abnormality of the coating gun can be automatically and easily detected by using an arithmetic device such as a personal computer.

According to the second aspect of the present invention, the vibration means detects the vibration of the coating gun during the painting operation, and the frequency analysis means decomposes the detected vibration for each frequency component. Calculate the value of a function obtained by multiplying the correlation function obtained from the normal frequency and the frequency during painting by the ratio of the magnitude of the normal frequency to the magnitude of the frequency during painting. Since it was decided to determine the abnormality based on a predetermined threshold from the calculation result of the function,
An abnormality of the coating gun can be detected by numerical calculation. In particular, by using the value of the function multiplied by the ratio of the magnitude of the frequency during normal operation to the magnitude of the frequency during painting, abnormalities that were difficult to determine with the conventional frequency pattern analysis such as semi-clogging are also detected. It is possible to do. Therefore, the abnormality of the coating gun can be automatically and easily detected by using an arithmetic device such as a personal computer.

According to the third aspect of the present invention, since the frequency is in the range of 5 to 22 kHz, high frequency components caused by noise due to the power supply frequency and mechanical vibration are cut off.
An abnormality of the coating gun can be detected with higher accuracy.

According to the present invention as set forth in claim 4, the above-mentioned 5-
Since the frequency range of 22 kHz is extracted before the frequency analysis, it is possible to reduce the load on the frequency analysis and the arithmetic processing, and to quickly determine the presence or absence of an abnormality.

According to the fifth aspect of the present invention, when an abnormality occurs during the coating by performing the frequency analysis in the normal state from the vibration detected for 0.75 seconds or more and less than 12.5 seconds, The correlation between the normal frequency and the abnormal frequency is clarified, making it easier to determine the abnormality.

According to the present invention, the vibration of the coating gun during the coating operation is detected, and the detected vibration is decomposed for each frequency component to determine the frequency in the normal state and the frequency during the coating. Calculate the value of a function obtained by multiplying the obtained inner product function by the ratio of the magnitude of the frequency during normal operation to the magnitude of the frequency during painting, and use the calculated result to determine an abnormality based on a predetermined threshold. Is determined, the abnormality of the coating gun can be detected by numerical calculation. In particular,
By using the value of the function multiplied by the ratio of the magnitude of the frequency during normal operation to the magnitude of the frequency during painting, it is also possible to detect abnormalities such as semi-clogging that were difficult to determine with the conventional frequency pattern analysis. Becomes possible. Therefore,
By using an arithmetic device such as a personal computer, it is possible to automatically and easily detect an abnormality of the coating gun.

According to the present invention, the vibration of the coating gun during the coating operation is detected, and the detected vibration is decomposed for each frequency component to determine the frequency at the time of normal operation and the frequency during coating. Calculate a value of a function obtained by further multiplying the obtained correlation function by the ratio of the magnitude of the frequency during normal operation to the magnitude of the frequency during painting, and use the calculated result to determine an abnormal value based on a predetermined threshold. Is determined, the abnormality of the coating gun can be detected by numerical calculation. In particular,
By using the value of the function multiplied by the ratio of the magnitude of the frequency during normal operation to the magnitude of the frequency during painting, it is also possible to detect abnormalities such as semi-clogging that were difficult to determine with the conventional frequency pattern analysis. Becomes possible. Therefore,
By using an arithmetic device such as a personal computer, it is possible to automatically and easily detect an abnormality of the coating gun.

According to the present invention, since the frequency is in the range of 5 to 22 kHz, high-frequency components caused by noise or mechanical vibration due to the power supply frequency are cut off.
An abnormality of the coating gun can be detected with higher accuracy.

According to the ninth aspect of the present invention, the above-mentioned 5-
Since the frequency range of 22 kHz is extracted before the frequency analysis, it is possible to reduce the load on the frequency analysis and the arithmetic processing, and to quickly determine the presence or absence of an abnormality.

According to the tenth aspect of the present invention, when an abnormality occurs during the coating by performing the frequency analysis in the normal state from the vibration detected for 0.75 seconds or more and less than 12.5 seconds, The correlation between the normal frequency and the abnormal frequency is clarified, making it easier to determine the abnormality.

[0030]

BRIEF DESCRIPTION OF THE DRAWINGS FIG.
An embodiment of the present invention will be described.

Embodiment 1 FIG. 1 is a diagram showing a schematic configuration of a coating apparatus and an abnormality detection apparatus according to Embodiment 1 of the present invention.

The coating apparatus comprises a coating gun 11 attached to the end of the arm of the robot 10, a pump 13 for supplying coating to the coating gun 11, and a coating tank 14. The coating gun 11 is provided with a spray nozzle 12 for injecting a coating material at its tip.

The abnormality detecting device comprises a vibration sensor 21 attached to the spray nozzle 12, an arithmetic unit 22, and an output unit 23 for outputting a result. Here, the arithmetic unit 22 is a so-called personal computer or the like, and executes a program created in accordance with a processing procedure described later to perform frequency analysis by fast Fourier transform (FFT) to determine whether there is an abnormality. The output device 23 is a display or a printer connected to a personal computer.

The vibration sensor 21 is an acceleration sensor,
The vibration when the paint is sprayed from the spray nozzle 12 is detected.

The painting operation is performed by the robot 10 operating the painting gun 11 according to a predetermined program so that a predetermined range is painted on the surface to be painted of the work (not shown). At this time, the pump 13 sends the paint in the paint tank 14 to the painting gun 11 at a predetermined pressure in conjunction with the operation of the robot 10. Thereby, the paint is sprayed from the spray nozzle 12 provided at the tip of the paint gun 11 to perform the painting.

Next, a procedure for detecting an abnormality of the coating gun during the coating operation will be described.

FIG. 2 is a flowchart showing an abnormality detection procedure.

First, prior to actual abnormality detection, vibrations in a normal paint state are detected (S1).

Here, as shown in FIG. 3, in the normal vibration detection, as shown in FIG. 3, when one unit of cut-out time for detecting vibration and performing frequency analysis is set to n, in the present embodiment, the first cut-out time n0 is determined. Sections are used.

The detected normal vibration is subjected to FFT (Fast Fourier Transform) analysis as frequency analysis (S2).
Subsequently, a specific frequency band is cut out, and a normal-time spectrum X0 is calculated (S3).

Here, the specific frequency band is, for example, 5
A range of ２２22 kHz is preferred. This means that by cutting the frequency below 5 kHz, it is possible to remove the power supply frequency and other low frequency vibration components from outside (for example, vibration when a person or a machine moves), while cutting the frequency exceeding 22 kHz. Accordingly, high-frequency components such as machine oscillation can be removed, and the occurrence of an abnormality in the coating gun can be accurately detected without being affected by external noise.

The calculation of the normal spectrum in step S3 is performed as follows.

Here, for the time-series time signal x (n), its frequency spectrum x (m, L) is expressed by the following (1).
Defined as shown in the equation.

[0044]

(Equation 1)

Where N is the block size, M is the overlap size, and ω (k) = when −K ≦ k ≦ K.
(1−cos (2πk / K)) / 2, where k is otherwise, ω (k) = 0, K = N / 2, m is an integer that increases in the time direction, and L increases in the frequency direction. (Hereinafter the same in each formula). Note that both time and frequency are discrete data.

From the equation (1), the spectrum X at normal time is obtained.
0 is defined as in the following equation (2).

[0047]

(Equation 2)

In the expression, “the number of N included in n”
Is a number indicating how many analysis numbers are included in one cutout time n with the block size N for FFT analysis as one unit. Specifically, for example, if the block size N is 512 (the number of blocks), it is a number indicating how many times the FFT analysis is performed with 512 units as one unit during n hours (hereinafter, in each formula, Similar).

After the normal-time spectrum is calculated, the abnormality in the actual painting operation is detected.

First, vibration during the painting operation is detected (S
4). The detected vibration is subjected to FFT analysis at regular time intervals (S5), and a specific frequency band is cut out, and the above-mentioned (1)
The operating spectrum Xi is calculated by the following equation (3) using the equation (S6). Here, the specific frequency band is preferably 5 to 22 kHz as described above.

[0051]

(Equation 3)

After calculating the operating spectrum Xi, the correlation value ρ between the normal time and the painting time is calculated from the normal time spectrum X0 and the operating spectrum Xi using a function (hereinafter referred to as an evaluation function) shown in the following equation (4). (I) is calculated (S
7).

[0053]

(Equation 4)

In equation (4), fU is the lower limit frequency (here, 5 Hz), and fL is the upper limit frequency (here, 2 Hz).
2 Hz).

The evaluation function shown in the equation (4) is obtained by calculating the ratio between the magnitude of the normal frequency and the magnitude of the frequency during painting to the inner product function of the frequency during painting and the frequency obtained during the FFT analysis. It is a multiplication. In the above equation (4), the inner product function part is as shown in the following equation (5), and the ratio of the magnitude of each frequency during normal operation and during painting is as shown in the following equation (6).

[0056]

(Equation 5)

[0057]

(Equation 6)

As is well known, the inner product function is one of the functions for obtaining the correlation, and obtains each frequency spectrum component obtained as a result of the FFT analysis as a multidimensional vector as in the above equation (5). is there. Further, the ratio between the magnitude of the frequency in the normal state and the magnitude of the frequency during the painting is the ratio of the magnitude of the vector of each frequency spectrum as in the above equation (6).

As described above, by multiplying the inner product function by the ratio of the magnitude of the normal frequency to the magnitude of the frequency during painting,
The evaluation can be performed in consideration of the intensity of the detected vibration. This is because, for example, when only the vibration intensity changes with little change in the frequency distribution, when the correlation between the normal state and during painting is evaluated using only the inner product function, the value (calculated result of the inner product function) is almost “1”. However, as shown in the above equation (4), by multiplying the inner product function by the ratio of the magnitude of the normal frequency to the magnitude of the frequency during painting, the vibration intensity can be reduced even if the frequency distribution does not change significantly. Even if it changes,
The value of the calculation result (the calculation result of the above equation (4)) is
An abnormality can be detected without becoming "1".

Thus, the calculation result ρ of the evaluation function
After obtaining (i), it is determined whether the value is abnormal based on a predetermined threshold (S8), and if an abnormality is detected, an abnormal signal is output to the output device 23. (S
9), end the processing. On the other hand, if there is no abnormality, the process returns to step S4, and the abnormality detection is continued until the painting operation ends.

Here, the threshold value varies depending on the block size of FFT analysis, how to take various constants, and the like.
12, when the observation time is 0.75 seconds and the overlap is 0, the threshold value of the total blockage abnormality is set to 0.85. As described later, the half-clogging abnormality is determined to be half-clogged when the threshold value is set to 1.1 since the correlation value rapidly increases in a half-clogged portion as described later.

FIG. 4 is a drawing showing correlation values when a full clogging abnormality has occurred, and FIG. 5 is a drawing showing correlation values when a half clogging abnormality has occurred. In each figure, the vertical axis represents the correlation value (calculation result of the evaluation function), and the horizontal axis represents time (second).

As can be seen from FIG. 4, when a full clogging abnormality occurs, the correlation value gradually decreases and eventually becomes zero.

On the other hand, as shown in FIG. 5, when a semi-clogging abnormality occurs, the correlation value rises sharply and then falls. This indicates that when half-clogging is found as a value calculated by the equation (4), the vibration intensity has changed, and the upper limit (1.2 in this embodiment) is set as the threshold. If both lower limits (0.8 in this embodiment) are set, such a half-clogged state can be accurately grasped in this embodiment.

As described above, in the first embodiment, both the full clogging abnormality and the semi-clogging abnormality can be evaluated as numerical values, so that these abnormal states can be easily detected.

In the first embodiment, as shown in the equation (4), the product of the inner product function multiplied by the ratio of the magnitude of each frequency during normal operation and during coating is used as the evaluation function. Instead of this, as shown in the following equation (7), instead of the inner product function, a correlation function using a value obtained by subtracting the average value from the spectrum for obtaining each inner product is added to the normal function and during painting, respectively. May be used as the evaluation function.

[0067]

(Equation 7)

The “number between (fU−fL)” is
When FFT analysis is performed with a lower limit of 5 kHz and an upper limit of 22 kHz, the actually obtained data is discrete data, so (Δ
f = (sampling frequency / block size), which means the number of data existing between the upper limit and the adjustment.

As described above, in the case where the equation (7) is used, similarly to the case where the above-described equation (4) is used, it is possible to reliably detect both the full clogging abnormality and the semi-clogging abnormality.

Embodiment 2 FIG. 6 is a drawing showing a schematic configuration of a coating apparatus and an abnormality detection apparatus according to Embodiment 2 of the present invention. Note that members having the same functions as those of the first embodiment are given the same reference numerals, and descriptions thereof will be omitted.

The configuration of the coating apparatus is the same as that of the first embodiment, and the robot 10, the coating gun 11, the pump 13,
And a paint tank 14.
A spray nozzle 12 is provided at the tip. The coating operation by this coating apparatus is the same as that of the first embodiment, and the description is omitted.

The abnormality detecting device includes a vibration sensor 21 attached to the spray nozzle 12, and a low-pass filter (LP) for directly cutting off a high frequency component in an analog manner in order to extract a specific frequency component from a signal from the vibration sensor.
F) 31, a high-pass filter (HPF) 32 for cutting low-frequency components, an arithmetic unit 22, and an output unit 23.

Next, a procedure for detecting an abnormality of the coating gun during the coating operation will be described.

FIG. 7 is a flowchart showing an abnormality detection procedure.

First, normal vibration is detected (S1).
1). Then, unnecessary frequency components are cut from the signal from the vibration sensor by the low-pass filter 31 and the high-pass filter 32 to extract only specific frequency components (S12). Here, as described above, only signals in the range of 5 to 22 kHz are passed.

Thereafter, the FFT is performed in the same manner as in the first embodiment.
The analysis is performed (S13), and the normal spectrum X0 is calculated (S14).

After the normal spectrum calculation, an abnormality in the actual painting operation is detected.

First, vibration during the painting operation is detected (S1).
5) As described above, unnecessary frequency components are cut from the signal from the vibration sensor using the low-pass filter 31 and the high-pass filter 32 (S16).

Thereafter, as in the first embodiment, an FFT analysis is performed (S17), and an operating spectrum Xi is calculated (S18). Subsequently, the above equation (4) or (7)
A correlation value is calculated using the evaluation function shown in the equation (S1
9). Subsequently, it is determined whether or not there is an abnormality based on the correlation calculation result based on the correlation value and a predetermined threshold value (S2).
0), if there is an abnormality, an abnormality signal is output to the output device 23 (S21), and the process ends. On the other hand, if there is no abnormality, the process returns to step S15, and the abnormality detection is continued until the painting operation ends.

Thus, also in the second embodiment, similarly to the first embodiment, it is possible to detect a full clogging abnormality or a semi-clogging abnormality of the coating gun.

In the second embodiment, unnecessary frequency components are cut off from the signal from the vibration sensor using the low-pass filter 31 and the high-pass filter 32 in an analog manner. Since only the frequency components necessary for the processing need to be processed, the load on the arithmetic unit is reduced.

Embodiment 3 In Embodiments 1 and 2 described above, the spectrum in a normal state is calculated by using only one initial cutout time n. In Embodiment 3, instead of this, the calculation is performed in the following manner. The spectrum in a normal state is calculated using a plurality of cutout times.

If this is conceptually illustrated, as shown in FIG. 8, a normal-time spectrum is calculated from a plurality of cut-out times n01 to n0i as a reference interval t0, and then vibrations in the observation intervals n1 to ni are detected. Then, the abnormality is determined.

Therefore, the device configuration in the third embodiment may be the same as that in the first or second embodiment, and the entire operation procedure may be the same as that in the first or second embodiment. Therefore, in the description of the third embodiment, the description of the device configuration and the operation procedure will be omitted, and only the calculation of the normal-time spectrum unique to the third embodiment and the abnormality determination using the same will be described.

First, when calculating the normal-time spectrum, the spectrum at one cut-out time n is calculated by the following equation (8).

[0086]

(Equation 8)

Then, one calculated cut-out time n
At a plurality of cut-out times (n01 to
A normal spectrum X0 (m) is calculated by averaging n0i) according to the following equation (9).

[0088]

(Equation 9)

Subsequently, for this normal spectrum, the correlation evaluation value ρ0 (i) of each spectrum X0i in the reference section is calculated by the following equation (10).

[0090]

(Equation 10)

The average of the correlation evaluation value ρ0 (i) is obtained by the following equation (11), and this is set as a variation function ρ0 in the reference section t0.

[0092]

[Equation 11]

[0093] In the equation, the "reference spectrum number" is the number of spectrums when the paint is normally sprayed from the spray nozzle when the paint is applied.

Then, the evaluation function ρ (i) in the normal state and during the actual painting operation is calculated from the vibration detected at each cutting time n in the observation section by the following equation (12).

[0095]

(Equation 12)

Here, as described in the first embodiment, the evaluation function expressed by the equation (12) is:
It is based on the inner product function obtained from the multi-dimensional vector of the frequency during normal operation and during painting, multiplied by the ratio of the magnitude of each frequency during normal operation and during painting.

Thus, it is possible to detect an abnormality of the coating gun in consideration of various vibration components generated during normal operation. The analysis time for calculating the normal time spectrum is arbitrarily determined according to the actual painting site and the state of the painting gun.
About 5 seconds are preferable. This is because if the analysis time for calculating the normal spectrum is too short, it is not possible to capture various vibration components that occur during normal operation.
Even if it is too long, an abnormality may occur during that time, so the above range is preferable.

The calculation of the normal-time spectrum may be performed in advance before the painting operation starts, or may be performed immediately before the painting operation starts and the painting operation may be shifted to the painting operation.

In the third embodiment, (12)
Instead of the expression, the evaluation may be performed by the following expression (13) using a correlation function.

[0100]

(Equation 13)

[Brief description of the drawings]

FIG. 1 is a schematic diagram for explaining a configuration of an abnormality detection device according to a first embodiment to which the present invention has been applied.

FIG. 2 is a flowchart illustrating an abnormality detection procedure according to the first embodiment.

FIG. 3 is a drawing for explaining a cut-out time of frequency analysis according to the first embodiment.

FIG. 4 is a diagram showing a correlation value when a full clogging abnormality occurs.

FIG. 5 is a diagram showing a correlation value when a semi-clogging abnormality occurs.

FIG. 6 is a schematic diagram for explaining a configuration of an abnormality detection device according to a second embodiment to which the present invention has been applied.

FIG. 7 is a flowchart illustrating an abnormality detection procedure according to the second embodiment.

FIG. 8 is a diagram for explaining a cut-out time of frequency analysis according to the third embodiment.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 11 Painting gun 12 Spray nozzle 21 Vibration sensor 22 Operation device 23 Output device 31 Low pass filter (LPF) 32 High pass filter (HPF)

 ──────────────────────────────────────────────────続 き Continued on the front page F term (reference) 2F076 BA19 BD12 BE08 2G064 AA11 AB01 BA15 CC41 CC53 4F035 AA03 BB04 BB05 BB31

Claims (10)

[Claims] 1. A vibration detecting means for detecting a vibration of a coating gun, a frequency analyzing means for analyzing a frequency of the vibration detected by the vibration detecting means, a normal frequency analyzed by the frequency analyzing means and the frequency Calculating means for calculating a value of a function obtained by multiplying the inner product function obtained from the frequency during painting analyzed by the analyzing means by the ratio of the magnitude of the normal frequency to the magnitude of the frequency during painting, Determining means for determining an abnormality of the coating gun based on a calculation result of the function. 2. A vibration detecting means for detecting the vibration of the coating gun, a frequency analyzing means for performing a frequency analysis of the vibration detected by the vibration detecting means, a normal frequency analyzed by the frequency analyzing means and the frequency Calculation means for calculating a value of a function obtained by multiplying the correlation function obtained from the frequency during painting analyzed by the analysis means by the ratio of the magnitude of the frequency during normal operation to the magnitude of the frequency during painting, Determining means for determining an abnormality of the coating gun based on a calculation result of the function. 3. The apparatus according to claim 1, wherein the frequency is in a range of 5 to 22 kHz. 4. The abnormality detection for a paint gun according to claim 3, wherein the frequency range of 5 to 22 kHz is extracted from the vibration detected by the vibration detecting means before being sent to the frequency analyzing means. apparatus. 5. The normal frequency is a result of analysis by the frequency analyzing means from vibration detected by the vibration detecting means in a normal state for 0.75 seconds or more and less than 12.5 seconds. The coating gun abnormality detecting device according to claim 1. 6. A step of detecting a vibration of the coating gun in a normal state, a step of performing a frequency analysis of the detected vibration in a normal state, and a step of detecting the vibration of the coating gun during coating. Performing a frequency analysis of the vibration during painting, and an inner product function obtained from the analyzed normal frequency and the analyzed frequency during painting, the magnitude of the normal frequency and the magnitude of the frequency during painting. Calculating a value of a function multiplied by the ratio of the height and a step of determining an abnormality of the coating gun based on a calculation result of the correlation evaluation function. 7. A step of detecting a vibration of the coating gun in a normal state, a step of performing frequency analysis of the detected vibration in a normal state, a step of detecting the vibration of the coating gun during coating, and Performing a frequency analysis of the vibration during painting, and a correlation function obtained from the analyzed normal frequency and the analyzed frequency during painting, the magnitude of the normal frequency and the magnitude of the painting frequency. Calculating a value of a function multiplied by the ratio of: and determining an abnormality of the coating gun based on the calculation result of the evaluation function. 8. The method according to claim 6, wherein the frequency is in a range of 5 to 22 kHz. 9. The method according to claim 8, wherein the frequency range of 5 to 22 kHz is extracted from the detected vibration before frequency analysis. 10. The apparatus according to claim 6, wherein the step of performing the frequency analysis of the vibration in the normal state includes analyzing the vibration detected in the normal state for a time of 0.75 seconds or more and less than 12.5 seconds. The method for detecting an abnormality of a coating gun according to any one of the first to third aspects.