JPH06300619A - Diagnostic method and equipment for abnormal noise of machine - Google Patents

Abstract

PURPOSE:To detect a machine generating abnormal noise thoroughly. CONSTITUTION:The abnormal noise diagnostic equipment comprises a first AE sensor 2 for detecting an AE signal generated from a clutch 1 for washing machine during operation thereof, a second AE sensor 3 having detection frequency different from that of the first AE sensor 2, a spectral component extracting section 100 for extracting the spectral components of high and low frequency AE signals detected by respective sensors and the driving frequency of the machine, and a spectral component deciding section 200 for comparing the extracted spectral component with a preset reference value and discriminating between normal and abnormal sounds of the machine.

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 an abnormal sound of a machine which can detect an abnormal sound (a sound that is harsh to humans) generated from a machine such as a motor or a clutch with high accuracy. Regarding the device.

[0002]

2. Description of the Related Art For example, a part of a part of a motor, a clutch or the like provided in home electric appliances or automobiles is defective (a chip or a scratch of a gear, or an abnormal contact between a stationary body and a rotating body of rotating parts). If so, an abnormal sound that normally cannot occur will be generated. Therefore, manufacturers of motors, clutches, etc. carry out auditory inspections at the product shipping stage. Although not intended to detect an abnormal sound of a machine, an example of an apparatus configuration close to the present invention described below is described in JP-A-1-158345.

[0003]

DISCLOSURE OF THE INVENTION Problems to be Solved by the Invention
The one described in Japanese Patent No. 345 is not intended to detect an abnormal sound of a machine, but is intended to detect a minute foreign substance in the gas insulated switch. As for the device configuration, the elastic wave generated at the collision of minute foreign matter and noise such as water droplets are separated from the ratio of the high frequency component and the low frequency component of the elastic wave, and the minute foreign matter collision in the gas insulated switch is detected with high accuracy. Is what you are trying to do.

According to our experiments, it has been confirmed that low-frequency and high-frequency AE signals are simultaneously generated when an abnormal sound is generated from a washing machine clutch or an automobile gear motor, for example. Moreover, it was confirmed that only the low-frequency AE signal may be generated or only the high-frequency AE signal may be generated, depending on the part that causes the abnormal sound. That is, all low-frequency and high-frequency AE signals must be detected and evaluated separately to detect all abnormal sound products without omission. Therefore, JP-A-1-15
According to the method of taking the ratio of high frequency to low frequency disclosed in Japanese Patent No. 8345, it is difficult to detect abnormal sound products without omission.

Further, in Japanese Laid-Open Patent Publication No. 55-65052, an AE signal generated by cutting is detected by one sensor, and the detected signal is divided into a high frequency component and a low frequency component. Similar to the one described in Japanese Patent No. 158345, there is described an apparatus for detecting a tool damage by obtaining a ratio of a high frequency component and a low frequency component and comparing the value of this ratio with a reference value. Also in this case, it is difficult to detect the abnormal sound product without omission for the reasons described above.

Further, in Japanese Patent Laid-Open No. 62-116221, a signal output from an acoustic sensor or an acceleration sensor installed on the outer surface of a casing for accommodating a rotating body is amplified, and a high frequency component is extracted from the amplified signal. An apparatus is disclosed which outputs an envelope signal and a low-frequency component signal, analyzes the correlation between the output high-frequency component envelope signal and the low-frequency component signal, and detects whirling vibration of the rotating body. Also in this apparatus, it is premised that there is a correlation between the high frequency component envelope signal and the low frequency component signal, and it is not considered that the high frequency component envelope signal and the low frequency component signal exist independently.

A first object of the present invention is to provide a method for diagnosing an abnormal sound of a machine which can detect an abnormal sound product of the machine without omission.

A second object of the present invention is to provide a machine abnormal sound diagnosis apparatus suitable for carrying out the first machine abnormal sound diagnosis method.

A third object of the present invention is to provide a manufacturing facility of a machine capable of stopping the shipment of a machine product which emits an abnormal sound without omission.

[0010]

According to the present invention, as a first method for achieving the above object, at least two kinds of AE sensors having different detection frequencies are mounted, and the AE signals detected by the respective sensors are detected. Frequency analysis is performed to extract the drive frequency of the machine to be diagnosed and the amplitude value of the frequency that matches the harmonic component thereof, and among the extracted amplitude values, 1
The abnormal sound diagnosis method for machines is adopted, in which even if the number exceeds the reference value set in advance corresponding to the drive frequency and its harmonic components, it is diagnosed as an abnormal sound product. It is a thing.

A second method for achieving the above object is to:
In the first method, a method for diagnosing abnormal sound of a machine is employed, in which an output signal of an AE sensor is detected by a detection circuit and then frequency analysis is performed.

The present invention also provides, as a first device for achieving the above object, a first AE sensor for detecting an AE signal generated from a machine, and the first AE sensor is an AE signal A second AE sensor having a different detection frequency, a signal processor for frequency-analyzing the outputs of the first and second AE sensors, and an amplitude value of a frequency component matching a preset drive frequency of the machine and its harmonic component Is extracted from the frequency analysis result, and the amplitude value extracted by the spectrum component extraction unit is compared with the reference values set corresponding to the drive frequency and its harmonic components, respectively. However, if it exceeds the reference value, a spectral component determination unit that determines that an abnormal sound is generated,
This is a configuration of a machine abnormality diagnosing device including a display for displaying a determination result.

A second device of the present invention for achieving the above object comprises, in addition to the first device, a detection circuit for detecting the outputs of the first and second AE sensor, and the output of the detection circuit. The signal is input to the signal processor.

The present invention also achieves the above-mentioned object,
A machine manufacturing line, a driving mechanism that is arranged close to the machine manufacturing line, and that operates the machine manufactured by the machine manufacturing line, and a sound of the machine that is driven by the driving mechanism are AE
9. An abnormal sound diagnostic apparatus for a machine according to claim 5, wherein the abnormal sound diagnostic apparatus for a machine is loaded through a sensor, and the machine that has been actuated is generated as a normal product and an abnormal product based on a diagnosis result of the abnormal sound diagnostic apparatus. A machine manufacturing facility is configured to include a product unloading mechanism for sorting products.

[0015]

[Operation] The operation of the machine is cyclic, and the contact between the boss and the shaft when the shaft rotates, the cycle of abnormal sound when the meshing of the teeth of the gear is abnormal, etc., are the number of rotations of the shaft (driving frequency) and its harmonics. It appears as the frequency of the wave component. If you confirm the amplitude at these frequencies in the normal state beforehand and set the reference value for each frequency by this, when the extracted amplitude exceeds the above-mentioned reference value that is preset in correspondence with the frequency. , Can be determined to be abnormal.

According to the knowledge of the inventors, an AE signal (hereinafter, referred to as a high frequency AE signal) that can be detected by a high frequency AE sensor (here, a sensor capable of detecting an elastic wave having a frequency of 30 kHz or more) is used. It has been found that there are some abnormal sound generation products that can be detected by evaluating (call), while some abnormal sound generation products cannot be detected only by evaluating the high frequency AE signal.

For these abnormal sound products, it is assumed that the AE signal with a frequency of 30 kHz or less (hereinafter, low frequency AE).
It has been revealed that an abnormal sound product can be detected by evaluation using an AE sensor capable of detecting a signal).

The following two factors can be considered as factors that cannot detect all abnormal phenomena in the high frequency AE signal.

Even if the high frequency AE signal is generated from the abnormal portion, it cannot be detected because it is attenuated because it does not propagate to the high frequency AE sensor mounting position due to the high frequency.

Further, when the material of the abnormal portion is a material having a low Young's modulus such as platox, the high frequency AE signal is less likely to be generated, and the low frequency AE signal is more likely to be generated.

Therefore, A generated over several Hz to several MHz
It is important to detect and evaluate the E signal in order to detect an abnormal sound product of the machine.

Further, since the abnormal sound detection target is a mechanical component, the rotational sliding sound (driving frequency) and the generation frequency of the high frequency AE signal, the gear sound (mesh engagement frequency) and the maximum amplitude of the low frequency AE signal are detected. Since the frequencies shown match, if you examine the spectral components that match the drive frequency of the machine,
It is possible to distinguish between normal products and products that generate abnormal noise.

The reason why it is difficult to detect an abnormal phenomenon of a machine without omission unless both the high frequency AE signal and the low frequency AE signal are evaluated is as follows. FIG. 5 is a summary of materials that can be detected by high frequency and low frequency AE. That is, it can be seen that a low frequency AE signal is generated from the plastics material and a high frequency AE signal is generated from the metal material. It is considered that the generation factors of high frequency and low frequency are due to the Young's modulus of the material shown in the figure.

Furthermore, the generation of high frequency and low frequency depends on the AE
It also depends on where the signal is generated. The result of our experiment,
It has been clarified that an AE signal of several Hz to several MHz may be generated from the abnormal part of the machine. For high frequency A
If an error occurs near the E sensor mounting position,
Although it is possible to detect the AE signal of the high frequency component with the high frequency AE sensor, when the position where the AE signal is generated is far from the sensor mounting position, the high frequency component included in the AE signal is attenuated, and therefore it can be detected. Disappear. On the other hand, since the low frequency component AE signal is not easily attenuated, it is possible to detect the low frequency component AE signal by mounting the low frequency component AE sensor.

[0025]

Embodiments of the present invention will be described below with reference to the drawings. As a machine to be diagnosed, a home washing machine will be described as an example here. FIG. 2 shows the structure of a clutch for a washing machine. The illustrated washing machine clutch includes a pulley 18 that is rotated by a belt, a G shaft 19 that rotates together with the pulley 18, and a G gear that is fixed to the G shaft 19.
12, a resin gear 13 meshing with the G gear 12, and the resin gear
It is configured to include a P gear 15 that meshes with the gear 13, and a P shaft 14 that is fixed to the P gear 15 and rotates together with the P gear 15. The G gear 12 and the P gear 15 are metallic.

This clutch decelerates the rotation of the pulley 18 and transmits it to the P shaft 14 to rotate the stirring rod of the washing tub provided above the P shaft 14 for washing. For example, if the resin gear 13 is damaged,
Alternatively, if the meshing state of the resin gear 13 and the G gear 12 is poor, an abnormal sound is generated at the same time as the AE signal is generated due to the collision of the gears. If the coil collar 16 is not properly attached, the coil collar 16 vibrates and collides with the G shaft 19, so that an AE signal is generated. At the same time, an abnormal sound is generated. Furthermore, when foreign matter is mixed into the boss 17 and the boss 17 is damaged, an AE signal and an abnormal sound are generated from the abnormal sliding portion between the G shaft 19 and the boss 17. That is, A
The abnormal sound can be detected by detecting the E signal. Also,
The above-described phenomenon of abnormal sound generation also causes damage to parts.

Therefore, by trial-driving the product on the factory shipment line, detecting the AE signal generated by the trial-driving product, and evaluating it, it is possible to detect the clutch generating an abnormal sound or the clutch that may cause damage. It is possible to prevent abnormal products from being shipped as products.

FIG. 1 shows a diagnostic algorithm for detecting an abnormal sound product according to the present invention, and FIG. 3 shows an example of a device configuration for carrying out the present invention.

The abnormality diagnosis apparatus shown in FIG. 3 includes a high frequency AE sensor 2 mounted on a machine to be diagnosed, a low frequency AE sensor 3 having a different detection frequency of the AE signal from the high frequency AE sensor 2, and a high frequency AE sensor. A connected to the AE sensor 2 for
E measurement amplifier 4, low frequency amplifier 5 connected to low frequency AE sensor 3, detection circuits 6 and 7 connected to AE measurement amplifier 4 and low frequency amplifier 5, respectively, and the detection circuit A / D converter 8 connected to the output side of 6, 7
A signal processor 9 connected to the output side of the A / D converter 8, an abnormality determination processing section 10 connected to the output side of the signal processor 9, and the abnormality determination processing section 1
And a display 11 connected to the output side of 0.

The reason why the low frequency amplifier 5 is necessary is as follows. Since the electrostatic capacity of the AE sensor is about 500 pF, the output impedance of the sensor is 32 MΩ for an AE signal of 10 Hz, for example. Therefore, the input impedance of the amplifier should be about 100 MΩ. Normal AE
Since the input impedance of the measuring amplifier is about 10 kΩ, it is difficult to amplify the low frequency AE signal. Therefore, here is a charge amplifier type amplifier,
Alternatively, a high input impedance amplifier using a FET in the input stage is used.

First, the clutch for the washing machine to be inspected
1, a high frequency AE sensor 2 and a low frequency AE sensor 3 are mounted at different positions. Next, the washing machine clutch 1 is operated (the pulley 18 is rotated, and the G gear 1
2, the P shaft 14 is rotated via the resin gear 13 and the P gear 15), the output of the high frequency AE sensor 2 is supplied to the AE measurement amplifier 4, and the output of the low frequency AE sensor 3 is supplied to the low frequency amplifier 5 , Respectively. The signals amplified by the AE measurement amplifier 4 and the low-frequency amplifier 5 are detected by the detection circuits 6 and 7, and the detected signals are A / D converter 8
Is converted into a digital signal by.

The high-frequency and low-frequency AE detection signals converted into digital signals by the A / D converter 8 are input to the signal processor 9 and subjected to frequency analysis processing.
By this frequency analysis, vibration of each frequency is extracted and output to the abnormality determination processing unit 10. The abnormality determination processing unit 10 extracts the amplitude at the drive frequency and its harmonics, and sets the amplitude corresponding to the drive frequency and its harmonics.
Is compared with a reference value of amplitude for detecting an abnormal sound generating product stored in.

The drive frequency is the basic number of revolutions between machine parts, such as the number of revolutions if the machine to be inspected is a rotary machine, the number of teeth x the number of revolutions if it is a gear, and the number of reciprocations if it is a reciprocating machine. The motion frequency of motion. Further, for example, if there are abnormalities at a plurality of places around the rotation axis, abnormalities appear in the frequencies of the harmonic components of the drive frequency.

As a result of the comparison, when there is a measured value exceeding the reference value, a signal indicating the occurrence of abnormal sound is output to the display unit 11. When a signal indicating the occurrence of abnormal sound is input to the display unit 11,
The screen display or voice display externally indicates that the machine under inspection, the clutch for the washing machine in this embodiment, is abnormal.

FIG. 4 shows examples of high-frequency and low-frequency AE signal waveforms detected from the normal product and the abnormal phenomenon product of the above washing machine clutch. As is clear from the figure, the abnormal sound generation of the machine can be detected without omission only by evaluating both the high frequency and low frequency AE signals.

The reason why it is difficult to detect an abnormal phenomenon of a machine without omission unless both the high frequency AE signal and the low frequency AE signal are evaluated is as follows. FIG. 5 is a summary of materials that can be detected by high frequency and low frequency AE. The resin gear 13 and the coil collar 16 are made of plastics, and the G shaft 19 and the boss 17 are made of metal. That is, it can be seen that a low frequency AE signal is generated from the plastics material and a high frequency AE signal is generated from the metal material. At the contact portion between the plastics material and the metal, a low frequency AE signal is generated on the plastics material side. The difference between high frequency and low frequency is considered to be due to the Young's modulus of the material shown in FIG.

Furthermore, the high frequency and low frequency are generated by the AE
It also depends on where the signal is generated. As a result of experiments conducted by the inventors, it has been clarified that an AE signal of several Hz to several MHz may be generated from the abnormal part of the machine. When an abnormality occurs at a position near the mounting position of the high frequency AE sensor, the high frequency AE sensor can detect the high frequency component AE signal, but the position where the AE signal is generated is far from the sensor mounting position. In this case, the high frequency component contained in the AE signal is attenuated and cannot be detected. On the other hand, the low frequency AE signal is not easily attenuated, so the low frequency AE signal
If the sensor is attached, the AE signal of low frequency component can be detected.

Next, the operation of the abnormality determination processing unit 10 shown in FIG. 3 will be specifically described with reference to FIG. Abnormality determination processing unit 10
Is configured to include a spectrum component extraction unit 100 and a spectrum component determination unit 200.

In the spectral component extraction unit 100, the amplitude values F1v to F1 of a plurality of driving frequencies of the machine, which have been input in advance, are obtained from the frequency analysis results of the low frequency and high frequency AE signals.
nv is extracted. FIG. 6 shows an example of the first peak frequency in the frequency analysis result of the high frequency and low frequency AE detection signals detected from the abnormal product of the washing machine clutch.
In the case of a gear abnormality, the same frequency component as the machine abnormality occurrence frequency due to the number of gear teeth is detected as the first peak frequency. When the high-frequency and low-frequency AE signals are checked for the boss sliding noise and the coil color hit noise, the 14.5 Hz component which is the rotation frequency of the G shaft 19 becomes the first peak frequency. This is because the G shaft 19 and the coil collar 16 collide once per rotation, so a 14.5 Hz component is detected, and the boss sliding sound is that the boss 17 and the G shaft 19 rotate once per rotation. This is because they come into contact with each other. Therefore, the spectral component extraction unit 100 extracts the amplitude values of the various frequencies described above and sends them to the spectral component determination unit 200.

The spectrum component determination unit 200 stores the reference values K1 to Kn of the amplitudes of the drive frequency and its harmonics, and each spectrum component (drive frequency and its harmonics) input from the spectrum component extraction unit 100 is stored. Wave amplitude) F1v
~ Fnv and the reference values K1 to Kn are compared, and if even one of F1v to Fnv exceeds the reference value, it is determined to be an abnormal sound product. The determination result including the frequency of the amplitude exceeding the reference value is displayed on the outside through the display unit 11.

In the above-described embodiment, the embodiment using the detection signal is described, but the same effect may be obtained in some cases by using each AE sensor output itself instead of the detection signal.

If the amplitudes of the detected high frequency and low frequency AE signals are below a certain value, the drive frequencies and their harmonic amplitudes F1v to Fnv obtained by frequency analysis are obtained.
It is possible to set the reference value of the amplitude of the detection signal so that the value does not exceed the reference values K1 to Kn. Usually, when the inspection result of a product is divided into three, that is, it is obvious that there is an abnormality, that needs to be investigated in detail, and there is clearly no abnormality, the majority are those with no obvious abnormality.
If the process after the frequency analysis is omitted for those that can be clearly determined to be normal, the inspection process time can be shortened. In this case, before performing frequency analysis, the amplitudes of the detected high-frequency and low-frequency AE signals are compared with preset reference values for the amplitudes of the respective detected signals, and if either exceeds the reference value. Then, the process after the frequency analysis is performed to determine the presence / absence of an abnormality. If none of them exceeds the reference value, it may be determined that there is no abnormality without performing the process after the frequency analysis. In this case, it is desirable to set the reference value of the amplitude of the detection signal to a sufficient value on the safe side.

Finally, with reference to FIG. 7, an embodiment of a machine manufacturing facility according to the present invention will be described. In the illustrated embodiment, a manufacturing line 50 for a washing machine clutch, a driving mechanism 70 for driving a machine (clutch for a washing machine) 60 manufactured by the manufacturing line 50, and a driving mechanism 70 are operated. It is configured to include an abnormal sound diagnostic device 80 for diagnosing an abnormal sound of a machine, and a product unloading mechanism 90 that operates by using the output of the abnormal sound diagnostic device 80 as one input. Although the operating mechanism 70 is arranged beside the production line 50 in FIG. 7, it may be arranged in the production line 50 so as to interrupt the line. Although not shown, the driving mechanism 70 has means for gripping and fixing a machine (washing machine clutch) to be driven, and the gripping and fixing means has a high-frequency AE sensor and a low-frequency AE sensor.
A sensor is incorporated so that the high frequency AE sensor and the low frequency AE sensor are mounted at predetermined positions on the machine at the same time when the machine is gripped and fixed. Production line 50
Is an intermittent flow method, in which the product unloading mechanism 90 sequentially stores the input determination results in a temporary memory, and considers the time during which the machine moves between the operating mechanism 70 and the product unloading mechanism 90 to determine the determination results. It is designed to be read out. The abnormal sound diagnostic device 80 has the configuration shown in FIG. 3, and is configured to output the determination result to the product unloading mechanism 90 in addition to the output to the display.

In the equipment having the above structure, the manufacturing line 50
The machine 60 manufactured in 1. is sent to the operation mechanism 70, is fixed by gripping, and is operated for a predetermined time. The sound generated by the machine due to this operation is taken out to the abnormal sound diagnostic device 80 through the high frequency AE sensor and the low frequency AE sensor, and normality / abnormality is determined. The determination result of the abnormal sound diagnostic device 80 is output to the product unloading mechanism 90. Then, the product unloading mechanism 90 sequentially stores the input determination results, sequentially reads from the previously stored determination results, and when the corresponding machine arrives at the product unloading mechanism 90, based on the read determination result. We classify normal products and abnormal products, do not ship abnormal products, and ship only normal products. FIG. 8 shows a series of operation flows performed by the apparatus of FIG.

When a machine is manufactured by the above-described manufacturing equipment, a machine producing an abnormal sound or a machine having a defect is detected on the production line, so that it is not necessary to ship an abnormal product. . The machine diagnosed as abnormal is disassembled and the cause of the abnormality is investigated. Once the cause of the abnormality is clarified, it is possible to provide feedback to the design and manufacturing departments so that the abnormality will not occur again. Therefore, it becomes possible to finally manufacture a highly reliable machine.

[0046]

As described above, according to the present invention,
It is possible to detect a machine that emits an abnormal sound without omission. Furthermore, if the diagnostic device according to the present invention is provided in a machine manufacturing line, shipment of abnormal products can be prevented.

[Brief description of drawings]

FIG. 1 is a flowchart showing an abnormal sound diagnosis algorithm for a machine according to the present invention.

FIG. 2 is a perspective view showing a structural example of a washing machine clutch which is an example of a machine.

FIG. 3 is a block diagram showing a main configuration of an embodiment of an abnormal sound diagnostic device for a machine according to the present invention.

FIG. 4 is an example of specific data for explaining the present invention.

FIG. 5 is an example of specific data for explaining the present invention.

FIG. 6 is an example of specific data for explaining the present invention.

FIG. 7 is a perspective view showing a main configuration of an embodiment of a machine manufacturing facility of the present invention.

8 is a flowchart showing an operation procedure of the embodiment shown in FIG.

[Explanation of symbols]

 1 Washing machine clutch 2 High frequency AE sensor 3 Low frequency AE sensor 4 AE measurement amplifier 5 Low frequency amplifier 6,7 Detection circuit 8 A / D converter 9 Signal processor 10 Abnormality judgment processing unit 11 Indicator 12 G gear 13 Resin Gear 14 P Shaft 15 P Gear 16 Coil Color 17 Boss 18 Pulley 19 G Shaft 50 Machine Manufacturing Line 60 Machine Manufactured 70 Operating Mechanism 80 Machine Abnormal Sound Diagnosis Device 90 Product Export Mechanism 100 Spectral Component Extraction Unit 200 Spectrum Component determination part

 ─────────────────────────────────────────────────── ─── Continuation of the front page (72) Yuichi Yamaki 1-1-1, Higashi-Taga-cho, Hitachi, Ibaraki Prefecture Living Company Division, Hitachi Ltd. (72) Inventor Kazuo Kikuchi 1-chome, Higashi-Taga-cho, Hitachi No. 1-1 Living Company Division, Hitachi, Ltd. (72) Inventor Yoshiyuki Sato 3-2-2 Sachimachi, Hitachi City, Ibaraki Prefecture Hitachi Engineering Services Co., Ltd.

Claims (9)

[Claims] 1. At least two machines having different detection frequencies.
A single AE sensor is mounted, the machine is operated, the frequency of the AE signal detected by each sensor during operation is analyzed, and the drive frequency of the machine to be diagnosed and the amplitude value of the frequency that matches its harmonics Respectively, comparing the extracted amplitude value with a reference value set in advance corresponding to the drive frequency and its harmonics, respectively, and the amplitude of the value exceeding the reference value among the extracted amplitude values. A method for diagnosing abnormal sound in a machine, comprising a procedure for diagnosing an abnormal sound product when there is a value. 2. The method for diagnosing abnormal sound of a machine according to claim 1, further comprising a step of detecting the output of the AE sensor before frequency analysis. 3. Amplitudes of outputs of the first and second AE sensors are compared with reference amplitude values preset respectively for the first and second AE sensors, and when both reference amplitude values are small, The machine to be inspected is determined to be a normal product without performing the process after the frequency analysis, and the process after the frequency analysis is performed when either one or both of the reference amplitude values are large. 1. The method for diagnosing abnormal sound of machine according to 1. 4. The amplitudes of the outputs of the detection circuits for detecting the outputs of the first and second AE sensors are compared with the reference amplitude values preset for the first and second AE sensors, respectively. When the reference amplitude value is small, the machine to be inspected is judged to be a normal product without performing the processing after the frequency analysis, and when one or both of the reference amplitude values are large, the processing after the frequency analysis is performed. The method for diagnosing abnormal sound of a machine according to claim 2, wherein: 5. A first AE sensor for detecting an AE signal generated from a machine, and the first AE sensor is an AE.
A second AE sensor having a different detection frequency of the signal;
A signal processor for frequency-analyzing the output of the second AE sensor, a spectrum component extraction unit for extracting an amplitude value of a frequency component that matches a preset machine drive frequency and its harmonics from a frequency analysis result, and the spectrum component. The amplitude value extracted by the extraction unit is compared with the reference values set in advance corresponding to the drive frequency and its harmonics, and if there is an amplitude value exceeding the reference value, it is determined as an abnormal sound product. A spectrum component determination unit for determination,
An abnormal sound diagnostic device for a machine, comprising a display for displaying a judgment result. 6. The abnormal sound diagnostic device for a machine according to claim 5, wherein a detection circuit is provided at a stage subsequent to the first and second AE sensors, and each detection signal is used for processing after frequency analysis. . 7. A signal is output when the reference amplitude value is large by comparing the amplitude of the output of each AE sensor and the reference amplitude value set in advance after the first and second AE sensors. Each one comparison circuit, an AND circuit and an OR circuit that receive the output of the comparison circuit, and an output signal indicating that the product is a normal product are input to the display unit when there is no output from the AND circuit. 6. The abnormal sound diagnostic apparatus for a machine according to claim 5, further comprising a control circuit for inputting the outputs of the first and second AE sensors to the signal processor when the output of the above is output. 8. A comparator circuit provided in the subsequent stage of the detection circuit, which compares the amplitude of the output of each detection circuit with a preset reference amplitude value and outputs a signal when the reference amplitude value is large. And an AND circuit and an OR circuit that receive the output of the comparison circuit, and an output signal indicating that the product is a normal product when there is no output from the AND circuit, and when there is an output from the OR circuit. 7. The abnormal sound diagnostic device for a machine according to claim 6, further comprising a control circuit for inputting the output of the detection circuit to the signal processor. 9. A manufacturing line of a machine, a driving mechanism which is arranged in the vicinity of the manufacturing line of the machine and operates the machine manufactured by the manufacturing line of the machine, and elasticity generated by the machine operated by the driving mechanism. An abnormal sound diagnostic apparatus for a machine according to any one of claims 5 to 8 which captures a wave via an AE sensor and processes it, and based on a diagnostic result of the abnormal sound diagnostic apparatus,
A manufacturing facility of a machine comprising a product unloading mechanism for separating the operated machine into a normal product and an abnormal product.