TW202134622A - Predictive maintenance assessment device, predictive maintenance assessment method, and program - Google Patents

Abstract

A first differential value calculation unit (521) of this predictive maintenance assessment device (12a) acquires AE outputs (M(t)) of an AE sensor (20) installed on the surface of a metal casing (casing) of a gear box (30), and calculates a differential value ([delta]1) (first differential value) between the maximum value (Smax1) and the minimum value (Smin1) of the AE output in a prescribed temporal duration. An average value calculation unit (522) calculates an average value (Save) of the AE outputs in the prescribed temporal duration. A second differential value calculation unit (523) calculates a second differential value ([delta]2) (second differential value) between the minimum value (Smin1) and a maximum value (Smax2) of AE outputs that are less than the average value (Save), from among AE outputs in the prescribed temporal duration. A first ratio calculation unit (524) calculates the ratio (R1) (first ratio) of the first differential value to the second differential value. When the ratio (R1) is equal to or greater than a first prescribed value ([epsilon]1), a notification unit (54) issues a notification that there is a risk of an abnormality occurring in the gear box (30).

Description

Predictive maintenance judging device, predictive maintenance judging method and program

The invention relates to a predictive maintenance judging device, a predictive maintenance judging method and a program for predicting abnormalities in a machine.

It is known that when a solid material deforms, the strain energy accumulated up to that time is released as a sound wave (AE wave). Moreover, previously, there has been known a damage detection device that detects the AE wave by the AE sensor and analyzes the waveform to detect the damage of the gear.

For example, the gear damage detection device described in Patent Document 1 analyzes the output of the AE sensor and detects the signal strength in a specific frequency region to detect damage to the gear. [Prior Technical Literature] [Patent Literature]

[Patent Document 1] JP 2009-42151 A

[The problem to be solved by the invention]

However, in the damage detection device of Patent Document 1, there is a problem that if an abnormality such as damage or the like does not actually occur in the machine, the abnormality cannot be detected. Therefore, when an abnormality is detected, the machine must be stopped immediately, and inspection or repair of the abnormal part, replacement and cleaning of consumable parts (bearing or sealing parts, etc.) must be carried out. Therefore, the machine must be stopped at an unexpected timing, and it may be necessary to take measures such as not only stopping the machine but also stopping the production line. This may have a greater impact on the production process.

The present invention was completed in view of the above, and aims to provide a predictive maintenance judging device, a predictive maintenance judging method, and a program that can notify the occurrence of an abnormality that affects the operation of the machine before the abnormality actually occurs. [Technical means to solve the problem]

In order to solve the above-mentioned problems and achieve the objective, the predictive maintenance judging device of the present invention is characterized by: an AE sensor, which is arranged on the surface of the casing of the machine; and a first difference value calculation unit, which obtains the aforementioned AE sensor And calculate the first difference between the maximum value and the minimum value of the aforementioned output for a specific time share; an average value calculation unit that calculates the average value of the aforementioned output for the specific time share; a second difference value calculation unit, which Calculate the second difference between the maximum value and the minimum value of the output that does not reach the average value in the output of the specific time share; a first ratio calculation unit that calculates the ratio of the first difference value to the second difference value ; And the notification unit, which performs notification related to the predictive maintenance of the aforementioned machine when the ratio calculated by the aforementioned first ratio calculation unit is greater than the first specified value.

In addition, the predictive maintenance judging device of the present invention is characterized by having: a first difference value calculation unit that obtains the output of the AE sensor installed on the surface of the casing of the machine, and calculates the maximum value of the aforementioned output for a specific time share The first difference value with the minimum value; the third difference value calculation unit that calculates the maximum value and minimum value of the output remaining after removing the output for the maximum value greater than a specific ratio among the output of the specific time share The third difference value; the second ratio calculation unit that calculates the ratio of the first difference value to the third difference value, that is, the second ratio; and the notification unit that reports when the second ratio is greater than or equal to the second specific value There is a risk of abnormalities in the aforementioned machines.

In addition, the predictive maintenance judging device of the present invention is characterized by having: a first difference value calculation unit that obtains the output of the AE sensor installed on the surface of the casing of the machine, and calculates the maximum value of the aforementioned output for a specific time share The first difference value with the minimum value; the average value calculation unit, which calculates the average value of the output for the specific time share; the third ratio calculation unit, which calculates the ratio of the first difference value to the average value, that is, the third ratio ; And a notification unit, which is based on a two-dimensional graph of the first difference value and the third ratio taken on each axis, and reports that the machine is likely to be abnormal. [Effects of Invention]

The predictive maintenance judging device of the present invention can notify the occurrence of an abnormality that affects the operation of the machine before the actual occurrence of the abnormality, that is, when the signs of the abnormality are detected. Therefore, it is possible to preset the time sequence for machine inspection or maintenance, replacement of consumable parts, cleaning, etc. Therefore, during the machine stop period, by operating other machines, etc., the operating state of the production line can be maintained.

[Description of Acoustic Emission (AE: Acoustic Emission)] Before the description of the embodiment, the audio emission (hereinafter referred to as AE) used for the judgment of the predictive maintenance of the machine will be described. The so-called AE is a phenomenon in which when a solid material deforms, the strain energy accumulated up to that time is released as sound waves (elastic waves, AE waves). By detecting the AE wave, the abnormality of the solid material can be predicted. The frequency band of AE wave is said to be about several 10 kHz to several MHz, and it has a frequency band that cannot be detected by ordinary vibration sensors or acceleration sensors. Therefore, in order to detect the AE wave, a dedicated AE sensor is used. The AE sensor will be described in detail later.

Figure 1 is an explanatory diagram of the audio transmitter and AE sensor. As shown in Fig. 1(a), if the AE generation source P inside the solid material Q is deformed, touched, rubbed, etc., an AE wave W is generated. The AE wave W expands radially from the AE generating source P, and propagates inside the solid material Q at a speed corresponding to the solid material Q.

The AE wave W transmitted inside the solid material Q is detected by the AE sensor 20 provided on the surface of the solid material Q. Then, the AE sensor 20 outputs a detection signal D. Since the detection signal D is a signal representing vibration, it is an AC signal with positive and negative values. However, since it is difficult to directly perform various calculations on the detection signal D (AE wave W), generally the negative part of the detection signal D is treated as a half-wave rectified rectified waveform. Moreover, when analyzing the AE wave W, generally speaking, it is taken as the value obtained by averaging the square value of the rectified waveform at a specific time to obtain the square root value, that is, the RMS (Root Mean Square) value ) While processing.

Although the transmission speed of the AE wave W is different between the longitudinal wave and the transverse wave (the longitudinal wave is faster than the transverse wave), the difference can be ignored if the size (transmission distance) of the solid material Q is considered. Therefore, in this embodiment, the longitudinal wave is not performed. The difference with horizontal waves. That is, without distinguishing between longitudinal waves and transverse waves, the AE wave W detected within a specific time is used as the measurement signal and used as the object of analysis.

The AE sensor 20 is enclosed by a protective cover 20a as shown in FIG. 1(b). Furthermore, on the bottom surface of the AE sensor 20, a wave receiving surface 20b for receiving the AE wave W is formed. The wave receiving surface 20b is formed of an insulator. In addition, a magnetic body 20c is provided near the bottom surface of the protective cover 20a, and the AE sensor 20 is fixed to the metal casing 30a of the machine 30 that is the object of predictive maintenance by the magnetic body 20c. At this time, the wave-receiving surface 20b is installed in a state in which it is in close contact with the surface of the metal casing 30a of the machine 30.

A vapor-deposited film 20d of copper or the like is formed on the upper portion of the wave-receiving surface 20b. In addition, a piezoelectric element 20e such as lead zirconate titanate (PZT) is provided on the upper portion of the vapor-deposited film 20d. The piezoelectric element 20e receives the AE wave W via the wave receiving surface 20b, and outputs an electric signal corresponding to the AE wave W. The electrical signal output by the piezoelectric element 20e is output as a detection signal D via the vapor-deposited film 20f and the connector 20g. In addition, since the detection signal D is relatively weak, in order to suppress the influence caused by the mixing of noise, a preamplifier (not shown in Figure 1(b)) is provided inside the AE sensor 20, which can be The detection signal D is output after pre-amplification.

AE is also generated due to minor damage or friction, so it is possible to detect signs of abnormalities in the machine at an early stage. In addition, the AE wave W expands radially from the AE generating source P. Therefore, if it is a metal casing, by installing the AE sensor 20, the AE wave W can be observed and detected at any position of the casing. Signal D. In addition, the specific analysis method of the detection signal D is described later. In addition, since the frequency bands of the signals that can be detected by the AE sensor 20 are different depending on the type, when selecting the AE sensor 20 to be used, it is preferable to consider the material of the equipment to be measured.

Hereinafter, based on the drawings, the implementation of the predictive maintenance judging device, the predictive maintenance judging method and the program of the present invention will be described in detail. In addition, the present invention is not limited by these embodiments. In addition, the constituent elements of the following embodiments include elements that can be replaced and easily conceived by those skilled in the art, or elements that are substantially the same.

[First Embodiment] The first embodiment of the present invention is an example of the predictive maintenance judging device 12a that detects and reports signs of abnormalities in the machine.

[Description of the outline composition of the predictive maintenance judging device] First, using FIG. 2, the overall configuration of the predictive maintenance determination system 10a using the predictive maintenance determination device 12a of the present embodiment will be described. Fig. 2 is an overall configuration diagram of a predictive maintenance judging system using the predictive maintenance judging device of the first embodiment. In addition, the predictive maintenance judging system 10a applies the predictive maintenance judging device 12a of the present invention to decelerate the rotational driving force of the motor 22 and drive the gear box 30 of the extruder 40 for predictive maintenance judgment. In addition, the gear box 30 is an example of the machine 30. The gear box 30 is formed by meshing a plurality of gears, and decelerates the rotational driving force of the motor 22 connected to the input side and transmits it to the output side. The predictive maintenance judging system 10a detects and reports abnormal signs such as cracks or wear occurring in the gear, and wear of the shaft supporting the gear. In addition, the device configuration described below is just an example, and the machine targeted for predictive maintenance is not limited to the gear box 30. In addition, the driving object of the gear box 30 is not limited to the extruder 40. In addition, the outline of the extruder 40 is mentioned later (refer FIG. 3).

The predictive maintenance judging device 12a obtains the output of the AE sensor 20 provided on the surface of the metal housing 30a of the gear box 30 connected to the extruder 40. Then, the predictive maintenance judging device 12a performs predictive maintenance of the gearbox 30 by analyzing the output of the AE sensor 20.

In addition, a sensor having a frequency band capable of detecting the AE wave W transmitted inside the metal casing 30a is used as the AE sensor 20. In particular, when the frequency band of the AE wave W to be detected is known, it is more desirable to use the AE sensor 20 with higher sensitivity to the frequency band. For example, in this embodiment, an AE sensor 20 having a high sensitivity to a frequency band including 150 kHz is used.

In addition, although the AE sensor 20 is not important to the installation position of the metal housing 30a of the gearbox 30, it is preferably installed near the part where the gearbox 30 is prone to abnormalities. For example, the AE sensor 20 is preferably installed near the output shaft of the gearbox 30.

The result of the judgment related to the predictive maintenance is that if it is determined that there is a sign of abnormality in the gearbox 30, the predictive maintenance judging device 12a reports the presence of an abnormality through a monitor or speaker not shown in FIG. 2 sign.

[Description of the structure of the extruder] Fig. 3 is a structural diagram of the extruder of the first embodiment. The extruder 40 rotates the screw 42 provided at the position where the output shaft 32 is extended by the rotation of the output shaft 32 that is rotationally driven corresponding to the output of the gear box 30, for example, to knead the resin raw material and the powder Shaped filler. In particular, the extruder 40 shown in FIG. 3 is a twin-screw extruder provided with two output shafts 32 arranged at a distance C between the shafts.

The two output shafts 32 are arranged in parallel while maintaining a certain inter-axial distance C inside the cylindrical portion 44. Furthermore, the bases of two screws 42 are connected to each output shaft 32, and the two screws 42 mesh with each other while rotating in the same direction. The output shaft 32 transmits the rotation of the motor 22 decelerated by the gear box 30 to the screw 42. The screw 42 rotates at a speed of 300 revolutions per minute or the like, for example.

Inside the barrel portion 44, two cylindrical insertion holes 46 are provided for each screw 42 to be inserted. The insertion hole 46 is a hole arranged along the length direction of the cylinder part 44, and a part of the cylinder overlaps so as to allow the two screws 42 to be engaged with each other to be inserted. A material supply port 47 for supplying the kneaded granular resin raw material and powdered filler material to the insertion hole 46 is provided on one end side in the longitudinal direction of the cylindrical portion 44. An ejection port 48 is provided on the other end side in the longitudinal direction of the cylinder portion 44 to eject the mixed material while passing through the insertion hole 46. A heater 49 that heats the material supplied to the insertion hole 46 by heating the cylindrical portion 44 is provided on the outer periphery of the cylindrical portion 44.

The screw 42 has a first screw portion 42a, a second screw portion 42b, and a third screw portion from one end side of the barrel portion 44 provided with the material supply port 47 toward the other end side of the barrel portion 44 provided with the ejection port 48 42c. Although detailed description is omitted, in order to uniformly knead materials, the first screw portion 42a, the second screw portion 42b, and the third screw portion 42c have different shapes from each other.

Similarly, the barrel portion 44 also extends from one end side where the material supply port 47 is provided toward the other end side where the ejection port 48 is provided, and corresponds to the first screw portion 42a, the second screw portion 42b, and the third screw portion 42c of the screw 42 It has a first cylindrical body portion 44a, a second cylindrical body portion 44b, and a third cylindrical body portion 44c. The gap between the screw 42 and the cylindrical portion 44 is formed to gradually decrease from the gear box 30 side toward the ejection port 48 side. Thereby, the material supplied from the material supply port 47 is further uniformly kneaded.

The length L of the barrel portion 44 in the longitudinal direction, the length L1 of the first barrel portion 44a and the first screw portion 42a, the length L1 of the second barrel portion 44b and the second screw portion 42b, the length L2 of the third barrel portion 44c and The length L3 of the third screw portion 42c is appropriately determined according to the kneaded material.

Near the front end of the screw 42, the molten resin is kneaded in a uniform manner. Then, the molten resin passing through the screw 42 is ejected from the ejection port 48 in a uniformly kneaded state.

[Description of the hardware structure of the predictive maintenance judging device] Next, the hardware configuration of the predictive maintenance determination device 12a will be described using FIG. 4. Fig. 4 is a hardware configuration diagram of the predictive maintenance judging device of the first embodiment.

The predictive maintenance determination device 12 a includes a control unit 13, a storage unit 14, and a peripheral device controller 16.

The control unit 13 includes a CPU (Central Processing Unit) 13a, a ROM (Read Only Memory) 13b, and a RAM (Random Access Memory) 13c. The CPU 13a is connected to the ROM 13b and the RAM 13c via the bus line 15. The CPU 13a reads out the control program P1 stored in the memory unit 14, and expands it in the RAM 13c. The CPU 13a controls the operation of the control unit 13 by operating in accordance with the control program P1 developed in the RAM 13c. That is, the control unit 13 has the structure of a general computer that operates based on the control program P1.

The control unit 13 is further connected to the storage unit 14 and the peripheral device controller 16 via a bus line 15.

The memory unit 14 is a non-volatile memory such as a flash memory, or an HDD (Hard Disk Drive, hard disk drive), etc., which retains memory information even when the power is turned off. The memory unit 14 stores: the program including the control program P1, and the AE output M(t). The control program P1 is a program for enabling the functions of the control unit 13 to be performed. The AE output M(t) is a signal in which the A/D converter 17 converts the root mean square value of the detection signal D output by the AE sensor 20 into a digital signal.

In addition, the control program P1 can be pre-assembled into the ROM 13b and provided. In addition, the control program P1 can be configured as a file that can be installed in the control unit 13 or can be executed by the control unit 13, and is recorded on CD-ROM, floppy disk (FD), CD-R, DVD (Digital Versatile Disc, Digital versatile discs), etc., are provided as recording media that can be read by a computer. Furthermore, it can be configured to store the control program P1 on a computer connected to a network such as the Internet, and provide it by downloading it via the network. In addition, it can be configured to provide or distribute the control program P1 via a network such as the Internet.

The peripheral device controller 16 is connected to the A/D converter 17, the display device 18, and the operation device 19. The peripheral device controller 16 controls the actions of various connected hardware based on instructions from the control unit 13.

The A/D converter 17 converts the detection signal D output by the AE sensor 20 into a digital signal, and outputs an AE output M(t).

The display device 18 is, for example, a liquid crystal display. The display device 18 displays information related to the operation state of the predictive maintenance judging device 12a. In addition, the display device 18 informs when it predicts that the maintenance judging device 12a detects a sign of abnormality in the gear box 30 (machine).

The operation device 19 is a touch panel overlapping with, for example, the display device 18. The operating device 19 obtains operation information related to the setting or operation of the predictive maintenance judging device 12a.

[Description of the functional composition of the predictive maintenance judging device] Next, the functional configuration of the predictive maintenance determination device 12a will be described using FIG. 5. Fig. 5 is a diagram showing the functional structure of the predictive maintenance judging device of the first embodiment. The control unit 13 of the predictive maintenance determination device 12a expands and operates the control program P1 in the RAM 13c, so that the signal acquisition unit 51, the signal analysis unit 52a, the first determination unit 53a, and the notification unit 54 shown in FIG. 5 are realized For the function department.

The signal acquisition unit 51 acquires the detection signal D output by the AE sensor 20. The signal acquisition unit 51 includes an amplifier to amplify the detection signal D, and includes an A/D converter to convert the root mean square value of the detection signal D as an analog signal into an AE output M(t) as a digital signal.

The signal analysis unit 52a analyzes the AE output M(t), and calculates an evaluation value for determining whether a sign of abnormality is observed in the gear box 30.

The signal analysis unit 52 a further includes a first difference value calculation unit 521, an average value calculation unit 522, a second difference value calculation unit 523, and a first ratio calculation unit 524.

The first difference value calculation unit 521 calculates the difference value δ1 between the maximum value Smax1 and the minimum value Smin1 of the AE output M(t) for a specific time share (for example, 10 seconds) = Smax1-Smin1 (first difference value). In addition, the specific time may be determined to be an appropriate value based on the calculation ability of the predictive maintenance determination device 12a and the like.

The average value calculation unit 522 calculates the average value Save of the AE output M(t) for a specific time share.

The second difference value calculation unit 523 calculates the difference value δ2 between the maximum value Smax2 and the minimum value Smin1 of the AE output M(t) that has not reached the average value Save from the AE output M(t) of the specific time share = Smax2-Smin1( The second difference value).

The first ratio calculation unit 524 calculates the ratio R1 of the first difference value to the second difference value δ2 = δ1/δ2. The ratio R1 (first ratio) is calculated by the signal analysis unit 52a. The ratio R1 is the aforementioned evaluation value.

The first determination unit 53a determines whether the ratio R1 calculated by the first ratio calculation unit 524 is the first specific value ε1 or more.

When the first determining section 53a determines that the ratio R1 is equal to or greater than the first specific value ε1, the notification unit 54 performs notification related to predictive maintenance of the gear box 30 (machine). Specifically, the notification unit 54 notifies by displaying a sign that an abnormality is observed in the gear box 30 on the display device 18. In addition, the notification method of the notification unit 54 is not limited to this. The notification can be performed by lighting or flashing an indicator not shown in FIG. 4, or by using a speaker or a bee not shown in FIG. The buzzer outputs sound or sound to announce.

[Description of predictive maintenance judgment method] According to the evaluation experiment conducted by the inventors, the AE output M1(t) of the gearbox 30 that is the object of evaluation (for example, the gears built in the gearbox 30 is damaged, etc.), and the gearbox 30 is the normal situation of AE output M2(t) to compare, it can be seen that the ratio of the difference between the maximum and minimum values of AE output M1(t) to the difference between the maximum and minimum values of AE output M2(t) is About 5. Furthermore, it is known that the more the abnormality of the gear box 30 progresses, the larger the ratio becomes. Therefore, it is known that the ratio is preferably before the ratio reaches 5. For example, when the ratio becomes about 3, it is determined that there is a sign of abnormality in the gear box 30. .

Furthermore, according to the inventor’s evaluation, it can be known that the difference between the maximum and minimum values of the AE output M2(t) when the gearbox 30 is normal is compared to the AE output M1(t) when the gearbox 30 is abnormal. The ratio of the difference between the maximum value and the minimum value of the output of Save that does not reach the average value increases with the abnormal progress of the gear box 30.

Therefore, the inventors determined that in order to catch the signs of abnormality and report it, the following is appropriate, that is, the difference between the maximum and minimum values of the AE output M(t) is less than the average of the AE output M(t) When the ratio of the difference between the maximum value and the minimum value of the output of the value Save reaches the aforementioned first specific value ε1, it is determined that there is a sign of abnormality. In addition, the value of the first specific value ε1 only needs to be evaluated in advance and set to a value corresponding to the gear box 30 to be evaluated.

Next, using FIG. 6, the method for the predictive maintenance determination device 12a to perform the determination for predictive maintenance, that is, to determine whether an abnormal sign is observed in the gear box 30 is described. Fig. 6 is an explanatory diagram of the predictive maintenance judgment method of the first embodiment.

Fig. 60a shown in Fig. 6 is an example of the AE output M(t) from the AE sensor 20 obtained by the signal obtaining unit 51 of the predictive maintenance judging device 12a. The horizontal axis of FIG. 6 represents time t, and the vertical axis represents the root mean square value (RMS value) of the AE output M(t) of the AE sensor 20. In addition, although the AE output from the AE sensor 20 is output as a continuous waveform, FIG. 60a is a scatter diagram that samples the continuous waveform at a specific time interval. In addition, the signal acquisition unit 51 acquires the AE output M(t) from the AE sensor 20 in a state where the motor 22, the gear box 30, and the extruder 40 are all operating.

The signal analysis unit 52a performs the following signal processing on the AE output M(t). First, the first difference value calculation unit 521 calculates the specific time share of the AE output M(t), for example, the difference value δ1 between the maximum value Smax1 and the minimum value Smin1 for 10 seconds shown in FIG. 6 = Smax1-Smin1 (first difference value).

Next, the average value calculation unit 522 calculates the average value Save of the AE output M(t) for a specific time share (for example, a 10 second share).

Furthermore, the second difference value calculation unit 523 calculates the maximum value Smax2 and the minimum value of the remaining AE output M(t) after excluding the AE output M(t) exceeding the average value Save from the output AE(t) at a specific time. The difference value of Smin1 δ2=Smax2-Smin1 (the second difference value).

Then, the first ratio calculation unit 524 calculates the ratio R1 (first ratio) of the first difference value δ1 to the second difference value δ2. That is, the first ratio calculation unit 524 calculates the ratio R1 by R1=δ1/δ2.

The first determination unit 53a determines whether the ratio R1 calculated by the first ratio calculation unit 524 is the first specific value ε1 or more. Then, when it is determined that the ratio R1 is greater than or equal to the first specific value ε1, the notification unit 54 reports to the display device 18 (refer to FIG. 4) that the abnormality of the gear box 30 is detected.

It is predicted that the maintenance judging device 12a will always perform the above-mentioned processing during the operation of the gear box 30 and the extruder 40. Then, the judgment by the first judgment unit 53a and the notification by the notification unit 54 are performed every specific time, for example, 10 seconds.

In addition, the timing of determination and notification is not limited to this. That is, based on the determination result of the AE output M(t) at a specific time in the past, the notification can be performed at a specific time interval. For example, it is possible to report the judgment result based on the AE output M(t) over a specific time (for example, 10 seconds) in the past in a time sequence such as once a second.

[Description of the processing flow of the predictive maintenance judging device] Next, the flow of processing performed by the predictive maintenance judging device 12a of the first embodiment will be explained with reference to Fig. 7. Fig. 7 is a flowchart showing an example of the flow of processing performed by the predictive maintenance judging device of the first embodiment.

The signal acquisition unit 51 acquires the AE output M(t) for a specific time share from the storage unit 14 (step S11).

The first difference value calculation unit 521 calculates the first difference value δ1 between the maximum value Smax1 and the minimum value Smin1 of the AE output M(t) for the specific time share (step S12).

The average value calculation unit 522 calculates the average value Save of the AE output M(t) for a specific time share (step S13).

The second difference value calculation unit 523 calculates the second difference value δ2 between the maximum value Smax2 and the minimum value Smin1 of the AE output M(t) that does not reach the average value Save from the AE output M(t) of the specific time share (step S14 ).

The first ratio calculation unit 524 calculates the ratio R1 (first ratio) of the first difference value δ1 to the second difference value δ2 (step S15).

The first determination unit 53a determines whether the first ratio R1 is equal to or greater than the first specific value ε1 (step S16). If it is determined that the first ratio R1 is greater than or equal to the first specific value ε1 (step S16: Yes), the process proceeds to step S17. On the other hand, if it is not determined that the first ratio R1 is greater than or equal to the first specific value ε1 (step S16: No), the process returns to step S11.

If it is determined to be YES in step S16, the notification unit 54 performs notification indicating that the predictive maintenance of the gear box 30 is related, that is, a notification indicating that an abnormality is observed. After that, the predictive maintenance judging device 12a ends the processing of FIG. 7.

As described above, in the predictive maintenance judging device 12a of the first embodiment, the first difference value calculation unit 521 obtains the AE sensing provided on the surface of the metal casing 30a (housing) of the gear box 30 (machine) The AE output M(t) of the device 20 is used to calculate the difference value δ1 (the first difference value) between the maximum value Smax1 and the minimum value Smin1 of the AE output M(t) for a specific time share. The average value calculation unit 522 calculates the average value Save of the AE output M(t) for a specific time share. Then, the second difference value calculation unit 523 calculates the difference value δ2 between the maximum value Smax2 and the minimum value Smin1 of the AE output M(t) that does not reach the average value Save from the AE output M(t) of the specific time share (the second Difference value). The first ratio calculation unit 524 calculates the ratio R1 (first ratio) of the difference value δ1 to the difference value δ2. Then, when the ratio R1 is greater than or equal to the first specific value ε1, the notification unit 54 notifies the gear box 30 that an abnormality may occur. Thereby, it is predicted that the maintenance judging device 12a will report when it detects that the AE output M(t) is smaller than the AE output M(t) generated when an obvious abnormality is caused in the gear box 30, so that it can cause a problem. Report before the action of the gear box 30 affects.

In addition, the predictive maintenance determining device 12a of the first embodiment performs predictive maintenance determination of the gear box 30 (machine) that drives the extruder 40. Therefore, since it is possible to report an abnormality that affects the operation of the gear box 30 or the extruder 40, it is possible to plan in advance to stop the extruder 40 and perform inspection or repair of the gear box 30, replacement of consumable parts, Timing of cleanup, etc. In this way, it is possible to prevent the production line from stopping at an unexpected timing.

In addition, in the predictive maintenance determination device 12a of the first embodiment, the frequency analysis performed when the AE wave W is analyzed is generally not performed. Therefore, it is possible to reduce the processing load when analyzing the AE output M(t).

[Second Embodiment] The second embodiment of the present invention is an example of the predictive maintenance determination device 12b that is provided in the predictive maintenance determination system 10b (not shown) and detects and reports signs of abnormalities in the equipment. The predictive maintenance judging device 12b is provided with a predictive maintenance judging method different from the aforementioned predictive maintenance judging device 12a.

[Description of the functional composition of the predictive maintenance judging device] With reference to Fig. 8, the functional configuration of the predictive maintenance judging device 12b will be described. Fig. 8 is a diagram showing the functional structure of the predictive maintenance judging device of the second embodiment. The control unit 13 of the predictive maintenance judging device 12b expands and operates the control program P2 (not shown) in the RAM 13c, so that the signal acquisition unit 51, the signal analysis unit 52b, and the second judgment unit 53b shown in FIG. And the notification unit 54 is realized as a functional unit.

The functions of the signal acquisition unit 51 and the notification unit 54 are the same as the aforementioned predictive maintenance determination device 12a.

The signal analysis unit 52b analyzes the output of the AE sensor 20 acquired by the signal acquisition unit 51, and calculates an evaluation value used to determine whether a sign of abnormality is observed in the gear box 30.

The signal analysis unit 52b further includes a first difference value calculation unit 521, an abnormal value removal unit 525, a third difference value calculation unit 526, and a second ratio calculation unit 527.

The function of the first difference value calculation unit 521 is the same as the aforementioned predictive maintenance determination device 12a.

The abnormal value removing unit 525 removes the output whose maximum value Smax1 for the output is greater than the specific ratio U from the AE output M(t) of the specific time share. The specific ratio U is determined based on a preliminary evaluation experiment, etc., and is set to, for example, 30%. In addition, the specific ratio U is evaluated in advance, and is set to a value corresponding to the gear box 30 that is the object of evaluation. The details are described later.

The third difference value calculation unit 526 calculates the difference value δ3 between the maximum value Smax3 and the minimum value Smin1 of the output of the abnormal value removal unit 525 = Smax3-Smin1 (third difference value).

The second ratio calculation unit 527 calculates the ratio R2 of the first difference value δ1 to the third difference value δ3 = δ1/δ3. The ratio R2 (the second ratio) is the aforementioned evaluation value calculated by the signal analysis unit 52b.

The second determination unit 53b determines whether the ratio R2 calculated by the second ratio calculation unit 527 is a second specific value (for example, 3) or more.

[Description of predictive maintenance judgment method] Next, using FIG. 9, the method for the predictive maintenance determination device 12b to perform the determination for predictive maintenance, that is, to determine whether an abnormal sign is observed in the gear box 30 will be described. Fig. 9 is an explanatory diagram of the predictive maintenance judgment method of the second embodiment.

Fig. 60b shown in Fig. 9 is an example of the AE output M(t) from the AE sensor 20 obtained by the signal obtaining unit 51 of the predictive maintenance judging device 12a. The horizontal axis of FIG. 9 represents time t, and the vertical axis represents the root mean square value (RMS value) of the AE output M(t) of the AE sensor 20. In addition, although the AE output from the AE sensor 20 is output as a continuous waveform, FIG. 60b is a scatter diagram that samples the continuous waveform at a specific time interval.

The first difference value calculation unit 521 calculates the specific time share of the AE output M(t), for example, the difference value δ1 between the maximum value Smax1 and the minimum value Smin1 for 10 seconds as shown in FIG. 9 = Smax1-Smin1 (first difference value) .

Next, the abnormal value removing unit 525 removes the output whose maximum value Smax1 of the AE output M(t) is greater than the specific ratio U from the AE output M(t) of the specific time share.

Then, the third difference value calculation unit 526 calculates that the abnormal value removal unit 525 removes the maximum value Smax1 of the AE output M(t) from the AE output M(t) of the specific time share after the output of the specific ratio U or more is left. The difference between the maximum value Smax3 and the minimum value Smin1 of the output δ3=Smax3-Smin1 (the third difference value).

The second ratio calculation unit 527 calculates the ratio R2 (second ratio) of the first difference value δ1 to the third difference value δ3. That is, the second ratio calculation unit 527 calculates the ratio R2 by R2=δ1/δ3.

The first determination unit 53a determines whether the ratio R2 calculated by the second ratio calculation unit 527 is equal to or greater than the second specific value ε2. Then, when it is determined that the ratio R2 is greater than or equal to the second specific value ε2, the notification unit 54 reports to the display device 18 (refer to FIG. 4) that the abnormality of the gear box 30 is detected.

It is predicted that the maintenance judging device 12b always performs the above-mentioned processing during the operation of the gear box 30 and the extruder 40. Then, the judgment by the second judgment unit 53b and the notification by the notification unit 54 are performed every specific time, for example, every 10 seconds.

In addition, the timing of determination and notification is not limited to this. That is, based on the determination result of the AE output M(t) at a specific time in the past, the notification can be made at a specific time interval. For example, it is possible to report the judgment result of the AE output M(t) based on the past specific time (for example, 10 seconds) in a time sequence such as once a second.

In addition, in the second embodiment, the values of the specific ratio U and the second specific value ε2 are evaluated in advance, and are set to values corresponding to the gear box 30 to be evaluated.

According to the evaluation experiment conducted by the inventors, as mentioned above, it can be known that the difference between the maximum value and the minimum value of the AE output M1(t) when the gearbox 30 is obviously abnormal is normal for the gearbox 30 as the evaluation object. In this case, the ratio of the difference between the maximum value and the minimum value of the AE output M2(t) is about 5. Furthermore, it is known that the more the abnormality of the gear box 30 progresses, the larger the ratio becomes. Therefore, it is known that the ratio is preferably before the ratio reaches 5. For example, when the ratio becomes about 3, it is determined that there is a sign of abnormality in the gear box 30. .

Furthermore, according to the inventor’s evaluation, it can be known that the difference between the maximum and minimum values of the AE output M2(t) when the gearbox 30 is in a normal state, and the AE output M1( when the free gearbox 30 is abnormal) t) The difference between the maximum value and the minimum value of the output after removing about 30% of the data above the AE output M1(t) is approximately equal.

Therefore, the inventors determined that in order to catch the signs of abnormality and report it, the following is appropriate, that is, the difference between the maximum value and the minimum value of the AE output M(t) is subtracted from the AE output M(t). When the ratio of the difference between the maximum value and the minimum value in the case of 30% of the data reaches approximately 3 (corresponding to the aforementioned second specific value ε2), it is judged as a sign of abnormality.

Also, comparing the evaluation method described in the first embodiment with the evaluation method described in the second embodiment, the AE output M(t) is obtained by subtracting higher data from the AE output M(t) At the point of comparison of the data, it can be regarded as a roughly equivalent analysis method. Therefore, any method can be used for judgment, but the method described in the second embodiment, that is, the calculation of the method of judgment based on the data obtained by removing the data of the specific ratio above the AE output M(t) The amount can reduce the calculation of the average value as an unnecessary share.

[Description of the processing flow of the predictive maintenance judging device] Next, the flow of processing performed by the predictive maintenance judging device 12b of the second embodiment will be explained using FIG. 10. Fig. 10 is a flowchart showing an example of the flow of processing performed by the predictive maintenance judging device of the second embodiment.

The signal acquisition unit 51 acquires the AE output M(t) for a specific time share from the storage unit 14 (step S21).

The first difference value calculation unit 521 calculates the first difference value δ1 between the maximum value Smax1 and the minimum value Smin1 of the AE output M(t) for a specific time share (step S22).

The abnormal value removing unit 525 removes the AE output M(t) whose maximum value Smax1 of the AE output M(t) for a specific time share is greater than the specific ratio U (step S23).

The third difference value calculation unit 526 calculates the third difference value δ3 of the maximum value Smax3 after the abnormal value removal unit 525 removes the specific AE output M(t) and the minimum value Smin1 of the AE output M(t) (step S24).

The second ratio calculation unit 527 calculates the ratio R2 (second ratio) of the first difference value δ1 to the third difference value δ3 (step S25).

The second determination unit 53b determines whether or not the second ratio R2 is greater than or equal to the second specific value ε2 (step S26). If it is determined that the second ratio R2 is greater than or equal to the second specific value ε2 (step S26: YES), the process proceeds to step S27. On the other hand, if it is determined that the second ratio R2 is greater than or equal to the second specific value ε2 (step S26: No), the process returns to step S21.

If it is determined to be YES in step S26, the notification unit 54 performs notification indicating that the predictive maintenance of the gear box 30 is related, that is, a notification indicating that an abnormality is observed. After that, the predictive maintenance judging device 12b ends the process of FIG. 10.

As described above, in the predictive maintenance judging device 12b of the second embodiment, the first difference value calculating unit 521 obtains the AE sensing provided on the surface of the metal casing 30a (housing) of the gear box 30 (machine) The AE output M(t) of the device 20 is used to calculate the difference value δ1 (the first difference value) between the maximum value Smax1 and the minimum value Smin1 of the AE output M(t) for a specific time share. The third difference value calculation unit 526 calculates the maximum value Smax3 and minimum value Smin1 of the AE output M(t) remaining after the output of the maximum value Smax1 is greater than the specific ratio U from the AE output M(t) of the specific time share. The difference value δ3 (the third difference value). Then, the second ratio calculation unit 527 calculates the ratio R2 of the difference value δ1 to the difference value δ3 (the second ratio). When the ratio R2 is greater than or equal to the second specific value ε2, the second determining unit 53b reports the sign that the gear box 30 has observed abnormality. Thereby, it is predicted that the maintenance judging device 12b will report when it detects that the AE output M(t) is smaller than the AE output M(t) generated when the gearbox 30 causes an obvious abnormality, so that it can cause a problem. Report before the action of the gear box 30 affects.

In addition, the predictive maintenance determining device 12b of the second embodiment performs predictive maintenance determination of the gear box 30 (machine) driving the extruder 40. Therefore, since it is possible to report an abnormality that affects the operation of the gear box 30 or the extruder 40, it is possible to plan in advance to stop the extruder 40 and perform inspection or repair of the gear box 30, replacement of consumable parts, Timing of cleanup, etc. In this way, it is possible to prevent the production line from stopping at an unexpected timing.

[Third Embodiment] Next, as a third embodiment of the present invention, the predictive maintenance determination device 12c shown in FIG. 11 will be described. Fig. 11 is an overall configuration diagram of a predictive maintenance judging system using the predictive maintenance judging device of the third embodiment.

The predictive maintenance judging system 10c detects and reports abnormal signs such as cracking or abrasion that occurs in the gear box 30 that decelerates the rotation driving force of the motor 22 and drives the extruder 40, and the abrasion of the shaft supporting the gear. The predictive maintenance judging device 12c is equipped with the predictive maintenance judging system 10c, and detects and reports signs of abnormalities in the machine. The predictive maintenance judging device 12c is equipped with a predictive maintenance judging method different from the aforementioned predictive maintenance judging devices 12a and 12b.

[Description of the functional composition of the predictive maintenance judging device] Next, the functional configuration of the predictive maintenance determination device 12c will be described using FIG. 12. Fig. 12 is a diagram showing the functional structure of the predictive maintenance judging device of the third embodiment. The control unit 13 of the predictive maintenance judging device 12c expands and operates the control program P3 (not shown) in the RAM 13c, so that the signal acquisition unit 51, the signal analysis unit 52b, and the third judgment unit 53c shown in FIG. And the notification unit 54 is realized as a functional unit.

The function of the signal acquisition unit 51 is the same as the aforementioned predictive maintenance judging device 12a, 12b. In addition, the function of the notification unit 54 is as explained in the first embodiment. That is, in the case of this embodiment, the notification unit 54 performs notification corresponding to the judgment result of the third judgment unit 53c.

The signal analysis unit 52c analyzes the AE output M(t) acquired by the signal acquisition unit 51, and calculates an evaluation value used to determine whether a sign of abnormality is observed in the gear box 30.

The signal analysis unit 52c further includes a first difference value calculation unit 521, an average value calculation unit 522, and a third ratio calculation unit 528.

The functions of the first difference value calculation unit 521 and the average value calculation unit 522 are the same as the aforementioned predictive maintenance determination device 12a. Furthermore, the third ratio calculation unit 528 calculates the difference value δ1 (the first difference value) between the maximum value Smax1 and the minimum value Smin1 of the AE output M(t) calculated by the first difference value calculation unit 521 for the specific time share with respect to the average value The ratio R3 (=δ1/Save: the third ratio) of the average Save ratio of the AE output M(t) calculated by the calculation unit 522 for the specific time share.

The third determination unit 53c determines the state of the gear box 30 based on the difference value δ1 calculated by the first difference value calculation unit 521 of the signal analysis unit 52c and the ratio R3 calculated by the third ratio calculation unit 528. The specific determination method will be described below.

[Description of the judgment method of the predictive maintenance judgment device] Next, the determination method performed by the third determination unit 53c of the predictive maintenance determination device 12c will be explained using FIG. 13. The inventor is equivalent to multiple gearboxes 30 in various states with AE sensors 20, and analyzed multiple data (the number of data is about 2000 (the sampling frequency is about 100 Hz)) obtained by each of them in 20 seconds. As a result of the analysis, a judgment method suitable for judging the state of the gearbox 30 is proposed. Fig. 13 is a diagram showing an example of the judgment criterion of the third embodiment.

Take the difference value δ1 (first difference value) on the vertical axis of FIG. 13, and take the third ratio R3 (=δ1/Save) on the horizontal axis. Then, the third determining unit 53c determines whether there is a possibility of abnormality in the gear box 30 based on the two-dimensional graph 80a formed by the difference value δ1 and the third ratio R3.

Specifically, when the difference value δ1 is smaller than the difference value first threshold value Td1, and the third ratio R3 is smaller than the ratio first threshold value Tr1, that is, when the difference value δ1 and the third ratio R3 are located in the area W1 of FIG. 13 When it is inside, the third determining unit 53c determines that the gear box 30 is normal. In addition, at this time, the notification unit 54 does not perform any notification. In addition, the notification unit 54 can notify that the gear box 30 is normal at this time.

Furthermore, when the difference value δ1 is smaller than the difference value first threshold value Td1, and the third ratio R3 is greater than the ratio first threshold value Tr1 and smaller than the ratio second threshold value which is larger than the ratio first threshold value Tr1 At Tr2, that is, when the difference value δ1 and the third ratio R3 are located inside the area W2 of FIG. 13, the third determining unit 53c determines that the gear box 30 is in an observation state that requires a low frequency (for example, about once a year) The state of observation). Then, the notification unit 54 performs notification indicating that it is in a required low frequency (for example, about once a year).

In addition, when the difference value δ1 is greater than or equal to the first threshold value Td1 of the difference value and smaller than the second threshold value Td2 of the difference value which is greater than the first threshold value Td1 of the difference value, and the third ratio R3 is smaller than the aforementioned ratio No. 2 When the threshold value Tr2, that is, when the difference value δ1 and the third ratio R3 are located inside the area W3 of FIG. 13, the third determining unit 53c determines that the gear box 30 is in the observing state where the intermediate frequency is required. Then, the notification unit 54 performs notification indicating that it is in a state of observation that requires a moderate frequency (for example, about once every six months).

In addition, when the difference value δ1 is greater than or equal to the second threshold value Td2 of the difference value and smaller than the third threshold value Td3 of the difference value which is larger than the second threshold value Td2 of the difference value, and the third ratio R3 is smaller than the aforementioned ratio second At the threshold Tr2, that is, when the difference value δ1 and the third ratio R3 are located inside the area W4 of FIG. 13, the third determining unit 53c determines that the gear box 30 is in a state of undergoing observation at a required high frequency. Then, the notification unit 54 performs notification indicating that it is in a state of observation that requires a high frequency (for example, about once every three months).

In addition, when the difference value δ1 is smaller than the difference value second threshold value Td2, and the third ratio R3 is greater than the ratio second threshold value Tr2, that is, when the difference value δ1 and the third ratio R3 are located between the area W5 of FIG. 13 When it is inside, the third determination unit 53c determines that the gear box 30 is in a low-urgency state requiring maintenance. Then, the notification unit 54 reports that it is in a low-urgency state requiring maintenance (for example, a state where maintenance within 2 to 3 years is recommended).

Furthermore, when the difference value δ1 is greater than or equal to the difference value second threshold value Td2 and smaller than the difference value third threshold value Td3 which is greater than the difference value second threshold value Td2, and the third ratio R3 is the ratio second When the threshold value Tr2 or more, that is, when the difference value δ1 and the third ratio R3 are located inside the area W6 of FIG. 13, the third determination unit 53c determines that the gear box 30 is in a state of maintenance requiring maintenance with a moderate degree of urgency. Then, the notification unit 54 performs notification indicating that the state of urgency is moderate and requires maintenance (for example, a state where maintenance within 1 to 2 years is recommended).

In addition, when the difference value δ1 is greater than or equal to the third threshold value Td3 of the difference value, that is, when the difference value δ1 and the third ratio R3 are located inside the area W7 of FIG. 13, the third determining unit 53c determines that the gear box 30 is in A state of high urgency that requires maintenance. Then, the notification unit 54 reports that it is in a state of need for maintenance with a high degree of urgency (for example, a state where maintenance within one year is recommended).

In addition, it can be made on the horizontal axis to take the ratio R1 (=δ1/δ2) used in the first embodiment or the ratio R2 (=δ1/δ3) used in the second embodiment, and take the difference value δ1 on the vertical axis. The dimension map 80a evaluates the state of the gear box 30 based on the position of the evaluation value plotted on the two-dimensional map 80a. That is, as described in the third embodiment, a plurality of threshold values corresponding to the evaluation functions of the vertical axis and the horizontal axis can be set, and the relationship between the measured evaluation value and the threshold value can be used to evaluate the gearbox 30 state.

In addition, in this embodiment, the number of AE sensors 20 provided in the gear box 30 is not limited to one. That is, a plurality of AE sensors 20 can be arranged on the surface of the gear box 30 corresponding to each axial direction, and the output of each AE sensor 20 can be evaluated with the two-dimensional graph 80a shown in FIG. 13 respectively. In this way, by performing simultaneous measurement of a plurality of channels, the state of each axial direction of the gear box 30 can be evaluated, so that the position where the gear box 30 is abnormal can be more accurately specified.

In addition, the location where the AE sensor 20 is installed can have variations on the input shaft side (the motor 22 side), the output shaft side (extruder 40 side), the intermediate shaft side (the central part of the gear box 30) of the gear box 30, etc. .

[Explanation of the data processing flow of the predictive maintenance judging device] Next, the flow of the determination processing performed by the signal analysis unit 52c and the third determination unit 53c will be described with reference to FIG. 14. 14 is a flowchart illustrating an example of the flow of processing performed by the signal analysis unit and the third determination unit in the third embodiment.

The signal acquisition unit 51 acquires the AE output M(t) for a specific time share from the storage unit 14 (step S31).

The signal analysis unit 52c sorts the AE output M(t) of the specific time share acquired in step S31 in descending order from the larger value (step S32).

The signal analysis unit 52c removes the burst value from the AE output M(t) sorted in descending order in step S32 (step S33). Specifically, the AE output M(t) sorted in descending order is classified according to, for example, 100 scales (0≦M(t)<100, 101≦M(t)<200,...), and only in the classified 100 scales When there are 2 data, delete the data below the 2 data.

The first difference value calculation unit 521 specifies the maximum value Smax1 and the minimum value Smin1 of the AE output M(t) (step S34).

The average value calculation unit 522 calculates the average value Save of the AE output M(t) for a specific time share (step S35).

The first difference value calculation unit 521 calculates the first difference value δ1 between the maximum value Smax1 and the minimum value Smin1. Then, the third ratio calculation unit 528 calculates the third ratio R3 (=δ1/Save) (step S36).

The third judging unit 53c judges the state of the gear box 30 in accordance with the criteria explained in FIG. 13 (step S37).

As described above, in the predictive maintenance judging device 12c of the third embodiment, the first difference value calculation unit 521 obtains the AE sensing provided on the surface of the metal housing 30a (housing) of the gear box 30 (machine) The AE output M(t) of the device 20 is used to calculate the difference value δ1 (the first difference value) between the maximum value Smax1 and the minimum value Smin1 of the AE output M(t) for a specific time share. The average value calculation unit 522 calculates the average value Save of the AE output M(t) for a specific time share. Then, the third ratio calculation unit 528 calculates a third ratio R3 that is the ratio of the difference value δ1 (first difference value) to the average value Save. Then, based on the difference value δ1 and the third ratio R3, that is, based on the two-dimensional graph 80a, the notification unit 54 notifies the gear box 30 that there is a possibility of abnormality. Thereby, it is predicted that the maintenance judging device 12c can notify the gear when it detects that the AE output M(t) is smaller than the AE output M(t) generated when the gearbox 30 causes a significant abnormality. Report the abnormality caused by the action of the box 30 before the occurrence.

In addition, the determination method described in the third embodiment, that is, the determination method based on the two-dimensional graph 80a of FIG. 13 can be applied to the first embodiment and the second embodiment. By making the determination based on a plurality of determination criteria as described above, the state of the gear box 30 can be determined in more detail.

[Fourth Embodiment] The fourth embodiment of the present invention is an example of the predictive maintenance determination device 12d that is provided in the predictive maintenance determination system 10d that detects and reports signs of abnormalities in the equipment.

First, using FIG. 15, the overall configuration of the predictive maintenance determination system 10d using the predictive maintenance determination device 12d of the present embodiment will be described. Fig. 15 is an overall configuration diagram of a predictive maintenance judging system using the predictive maintenance judging device of the fourth embodiment.

The predictive maintenance determination system 10d has a structure in which a vibration sensor 70 is added to the structure of the predictive maintenance determination system 2a described in FIG. 2. The vibration sensor 70 is arranged on the surface of the metal shell 30 a of the gear box 30 to measure the magnitude of the vibration acceleration generated in the gear box 30. Specifically, the magnitude of the vibration acceleration in the range of several Hz to several 10 Hz lower than the frequency range measured by the AE sensor 20 is detected. In addition, the vibration sensor 70 is an example of the acceleration sensor of the present invention, for example, a piezoelectric acceleration sensor is used.

The predictive maintenance judging system 10d measures the magnitude of the vibration acceleration generated in the gearbox 30, and when the vibration acceleration is greater than a specific acceleration, it switches the method of judging the state of the gearbox 30 described in the third embodiment to another judging method. That is, the predictive maintenance judging system 10d judges the state of the gearbox 30 based on a judgment criterion different from that in FIG. 13 when the magnitude of the vibration acceleration generated in the gearbox 30 is greater than a specific acceleration, that is, the third specific value ε3. On the other hand, when the magnitude of the vibration acceleration generated in the gear box 30 is less than the third specific value ε3, the state of the gear box 30 is determined based on the determination criterion shown in FIG. 13. In addition, the third specific value ε3 is preferably set to about 10 m/s ² based on evaluation experiments conducted by the inventors.

Fig. 16 is a diagram showing the functional structure of the predictive maintenance judging device of the fourth embodiment. The control unit 13 of the predictive maintenance judging device 12d expands and operates the control program P3 (not shown) in the RAM 13c, so that the signal acquisition unit 55, the signal analysis unit 52d, and the fourth judgment unit 53d shown in FIG. And the notification unit 54 is realized as a functional unit.

The signal acquisition unit 55 acquires the AE output M(t) for a specific time share from the storage unit 14. In addition, the signal acquisition unit 55 acquires the vibration acceleration from the vibration sensor 70.

The signal analysis unit 52d includes a vibration acceleration determination unit 520 in addition to the functions described in the third embodiment. The vibration acceleration determination unit 520 determines whether the vibration acceleration acquired by the vibration sensor 70 is greater than the third specific value ε3.

The function of the notification unit 54 is as explained in the first embodiment. That is, in the case of the present embodiment, the notification unit 54 performs notification corresponding to the judgment result of the fourth judgment unit 53d.

The fourth judging unit 53d judges the state of the gear box 30 based on the judging method corresponding to the magnitude of the vibration acceleration obtained by the vibration sensor 70. The specific determination method is described later.

When the magnitude of the vibration acceleration generated by the gearbox 30 is greater than the third specific value ε3, the predictive maintenance judging device 12d judges the state of the gearbox 30 based on the judgment criterion (two-dimensional graph 80b) shown in FIG. 17, for example. Fig. 17 is a diagram showing an example of the judgment criterion when the vibration acceleration is greater than the third specific value ε3.

Take the difference value δ1 (the first difference value) on the vertical axis of Fig. 17, and take the minimum value Smin1 of the AE output M(t) or the average value Save of the AE output M(t) on the horizontal axis. Furthermore, the fourth determination unit 53d determines whether there is a risk of abnormality in the gear box 30 based on the two-dimensional graph 80b formed by the difference value δ1 and the minimum value Smin1 (or the average value Save).

Specifically, when the difference value δ1 is less than the first threshold value Td1 of the difference value, and the minimum value Smin1 (or average Save) is less than the signal output threshold value Ts1, that is, when the difference value δ1 and the minimum value Smin1 (or average When the value Save) is located inside the region W11 in FIG. 17, the fourth determining unit 53d determines that the gear box 30 is in an observed state (for example, an observed state that requires approximately once a year) at a low frequency. Then, the notification unit 54 performs notification indicating that it is in a required low frequency (for example, about once a year).

In addition, when the difference value δ1 is greater than or equal to the first threshold value Td1 of the difference value and smaller than the second threshold value Td2 of the difference value which is greater than the first threshold value Td1 of the difference value, and the minimum value Smin1 (or the average value Save ) Is less than the signal output threshold value Ts1, that is, when the difference value δ1 and the minimum value Smin1 (or the average value Save) are located inside the area W12 of FIG. 17, the fourth determination unit 53d determines that the gearbox 30 is in the necessary intermediate frequency Under the state of observation. Then, the notification unit 54 performs notification indicating that it is in a state of observation that requires a moderate frequency (for example, about once every six months).

Also, when the difference value δ1 is greater than the difference value second threshold value Td2 and less than the difference value third threshold value Td3, and the minimum value Smin1 (or average Save) is less than the signal output threshold value Ts1, that is, When the difference value δ1 and the minimum value Smin1 (or the average value Save) are located inside the area W13 of FIG. 17, the fourth determining unit 53d determines that the gear box 30 is in the state of undergoing observation at a required high frequency. Then, the notification unit 54 performs notification indicating that it is in a state of observation that requires a high frequency (for example, about once every three months).

Also, when the difference value δ1 is less than the difference value second threshold value Td2, and the minimum value Smin1 (or average Save) is greater than the signal output threshold value Ts1, that is, when the difference value δ1 and the minimum value Smin1 (or average value Save) When it is located inside the area W14 in FIG. 17, the fourth determination unit 53d determines that the gear box 30 is in a low-urgency state requiring maintenance. Then, the notification unit 54 reports that it is in a low-urgency state requiring maintenance (for example, a state where maintenance within 2 to 3 years is recommended).

Also, when the difference value δ1 is greater than or equal to the second threshold value Td2 of the difference value and less than the third threshold value Td3 of the difference value, and the minimum value Smin1 (or average Save) is greater than or equal to the signal output threshold value Ts1, that is When the difference value δ1 and the minimum value Smin1 (or the average value Save) are located inside the area W15 in FIG. 17, the fourth determining unit 53d determines that the gear box 30 is in a state of need for maintenance with a moderate degree of urgency. Then, the notification unit 54 performs notification indicating that the state of urgency is moderate and requires maintenance (for example, a state where maintenance within 1 to 2 years is recommended).

Furthermore, when the difference value δ1 is greater than or equal to the third threshold value Td3 of the difference value, that is, when the difference value δ1 and the minimum value Smin1 (or the average value Save) are located inside the area W16 of FIG. 17, the fourth determination unit 53d determines This is because the gear box 30 is in a state of high emergency and requires maintenance. Then, the notification unit 54 reports that it is in a state of need for maintenance with a high degree of urgency (for example, a state where maintenance within one year is recommended).

Next, referring to FIG. 18, the flow of the determination processing performed by the signal analysis unit 52c and the fourth determination unit 53d will be described. FIG. 18 is a flowchart illustrating an example of the flow of processing performed by the signal analysis unit and the fourth determination unit in the fourth embodiment.

The signal acquisition unit 55 acquires the vibration acceleration from the vibration sensor 70. (Step S41).

The signal acquisition unit 55 acquires the AE output M(t) for a specific time share from the storage unit 14 (step S42).

The vibration acceleration determination unit 520 determines whether the vibration acceleration is greater than the third specific value ε3 (step S43). If it is determined that the vibration acceleration is greater than the third specific value ε3 (step S43: Yes), the process proceeds to step S44. On the other hand, if it is not determined that the vibration acceleration is greater than the third specific value ε3 (step S43: No), the process proceeds to step S45.

The fourth determination unit 53d determines the state of the gear box 30 based on the two-dimensional map 80b (step S44). After that, the processing of FIG. 18 is ended.

The fourth determination unit 53d determines the state of the gear box 30 based on the two-dimensional map 80a (step S45). After that, the processing of FIG. 18 is ended.

As described above, the predictive maintenance judging device 12d of the fourth embodiment obtains the output of the vibration sensor 70 (acceleration sensor) provided on the surface of the gear box 30 (machine), and the output of the vibration sensor 70 is When the output is greater than the third specific value ε3, the notification unit 54 notifies the gear box 30 that an abnormality may occur based on the minimum or average value of the output of the AE sensor 20 and the difference value δ1 (first difference value). Furthermore, when the output of the vibration sensor 70 is the third specific value ε3 or less, based on the difference value δ1 (first difference value) and the third ratio R3, it is reported that the gear box 30 may be abnormal. Thereby, even when the gear box 30 generates high vibration acceleration, the predictive maintenance judging device 12d can notify the abnormality before causing the abnormality that affects the operation of the gear box 30.

[Fifth Embodiment] The fifth embodiment of the present invention is an example of the predictive maintenance determination device 12e provided in the predictive maintenance determination system 10e (refer to FIG. 19) that detects and reports signs of abnormalities in the equipment.

Fig. 19 is a system block diagram showing an example of the system configuration of the predictive maintenance judgment system of the fifth embodiment. The predictive maintenance judging system 10e sends the outputs of the AE sensors 21a, 21b, ... (amplified by the preamplifier) installed in a plurality of gear boxes 31a, 31b, ... to the predictive maintenance judging device 12e via the network 100, respectively , And determine the state of each gear box 31a, 31b, ... in the predictive maintenance determining device 12e. In addition, the gear boxes 31a, 31b are respectively rotationally driven by the motors 23a, 23b, ..., and drive the extruders 41a, 41b, .... In addition, the output of the AE sensors 21a, 21b, ... is provided with identification information that is specific to the gearbox in which each AE sensor is installed.

Since the gearboxes 31a, 31b,... and the predictive maintenance determination device 12e are connected via the network 100, the location of the predictive maintenance determination device 12e does not need to be near the gearboxes 31a, 31b,..., and can be far away from the gearboxes 31a, 31b, …The location. In addition, the gear boxes 31a, 31b, ... connected to the predictive maintenance judging device 12e are not limited to gear boxes installed in the same factory, and may be gear boxes installed in a plurality of factories.

The predictive maintenance determination device 12e has the same configuration as any of the aforementioned predictive maintenance determination devices 12a to 12d. Furthermore, the predictive maintenance judging device 12e analyzes the output of each AE sensor 21a, 21b,... The same judgment method for any of 53d is used to judge the state of the gearboxes 31a, 31b, ....

Then, if it is determined that there is an abnormality in the state of the gear boxes 31a, 31b, ..., the notification unit 54 included in the maintenance determination device 12e is predicted to notify the determined content.

In addition, since the outputs of the AE sensors 21a, 21b, ... are given specific identification information for the gearboxes provided with each AE sensor, the gearboxes 31a, 31b, ... need not be of the same type. That is, the predictive maintenance judging device 12e may have multiple judgment logics for judging different AE outputs M(t) obtained from different types of gearboxes, and the AE output M(t) received by the predictive maintenance judging device 12e , Use the determination logic corresponding to the gear box that detects the AE output M(t) to determine the state of the gear box.

In addition, when the predictive maintenance determination device 12e determines that an abnormality has occurred in the gear box, it can return the determination result to the gear box via the network 100. In addition, a notification device such as an alarm not shown in FIG. 19 provided in the gear box may be used to notify the determination result.

As described above, the predictive maintenance judging device 12e of the fifth embodiment is connected to the AE sensors 21a, 21b provided on the surface of one or more gear boxes 31a, 31b (machines) via the network 100, and obtains the The output of AE sensor 21a, 21b. In this way, the abnormality determination of the gear box (machine) can be performed at a location far away from the gear box (machine).

10a, 10b, 10c, 10d, 10e: predictive maintenance judgment system 12a, 12b, 12c, 12d, 12e: predictive maintenance judging device 13: Control Department 13a: CPU 13b: ROM 13c: RAM 14: Memory Department 15: Bus line 16: Peripheral machine controller 17: A/D converter 18: display device 19: operating device 20, 21a, 21b: AE sensor 20a: Protective cover 20b: Wave surface 20c: Magnetic body 20d: Evaporated film 20e: Piezo element 20f: Evaporated film 20g: connector 22, 23a, 23b: Motor 30, 31a, 31b: gear box (machine) 30a: Metal shell 32: output shaft 40, 41a, 41b: Extruder 42: Screw 42a: 1st screw part 42b: 2nd screw part 42c: 3rd screw part 44: Cylinder 44a: The first cylinder 44b: 2nd cylinder 44c: 3rd cylinder 46: Through hole 47: Material supply port 48: spout 49: heater 51: Signal Acquisition Department 52a, 52b, 52c, 52d: Signal Analysis Department 53a: First Judgment Section 53b: Second Judgment Section 53c: Judgment Section 3 53d: Judgment Section 4 54: Notification Department 55: Signal Acquisition Department 60a, 60b: figure 70: Vibration sensor (acceleration sensor) 80a, 80b: two-dimensional graph 100: Internet 520: Vibration acceleration determination unit 521: The first difference value calculation unit 522: Average calculation unit 523: Second difference calculation unit 524: The first ratio calculation unit 525: Outlier Removal Department 526: Third difference calculation unit 527: The second ratio calculation unit 528: The third ratio calculation unit C: Distance between shafts D: detection signal L: Full length L1, L2, L3: length M(t), M1(t), M2(t): AE output P: AE source P1: Control program Q: solid materials R1: Ratio (Ratio 1) R2: Ratio (Ratio 2) R3: Ratio (Ratio 3) Save: Average Smax1, Smax2, Smax3: maximum Smin1: minimum value t: moment Td1: The first threshold of the difference value Td2: The second threshold of the difference value Td3: The third threshold of the difference value Tr1: ratio 1st threshold Tr2: The second threshold of the ratio Ts1: signal output threshold U: specific ratio W: AE wave W1, W2, W3, W4, W5, W6, W7, W11, W12, W13, W14, W15, W16: area δ1: Difference value (first difference value) δ2: Difference value (2nd difference value) δ3: Difference value (third difference value) ε1: The first specific value ε2: Second specific value ε3: The third specific value

Figure 1 (a), (b) are the explanatory diagrams of the AE and AE sensors. Fig. 2 is an overall configuration diagram of a predictive maintenance judging system using the predictive maintenance judging device of the first embodiment. Fig. 3 is a structural diagram of the extruder of the first embodiment. Fig. 4 is a hardware configuration diagram of the predictive maintenance judging device of the first embodiment. Fig. 5 is a functional block diagram of the predictive maintenance judging device of the first embodiment. Fig. 6 is an explanatory diagram of the predictive maintenance judgment method of the first embodiment. Fig. 7 is a flowchart showing an example of the flow of processing performed by the predictive maintenance judging device of the first embodiment. Fig. 8 is a functional configuration diagram of the predictive maintenance judging device of the second embodiment. Fig. 9 is an explanatory diagram of the predictive maintenance judgment method of the second embodiment. Fig. 10 is a flowchart showing an example of the flow of processing in the second embodiment. Fig. 11 is an overall configuration diagram of a predictive maintenance judging system using the predictive maintenance judging device of the third embodiment. Fig. 12 is a functional block diagram of the predictive maintenance judging device of the third embodiment. Fig. 13 is a diagram showing an example of the judgment criterion of the third embodiment. FIG. 14 is a flowchart showing an example of the flow of processing performed by the signal analysis unit and the third determination unit in the third embodiment. Fig. 15 is an overall configuration diagram of a predictive maintenance judging system using the predictive maintenance judging device of the fourth embodiment. Fig. 16 is a functional block diagram of the predictive maintenance judging device of the fourth embodiment. Fig. 17 is a diagram showing an example of the criterion for determining when the vibration acceleration is greater than the third specific value. Fig. 18 is a flowchart showing an example of the flow of processing performed by the signal analysis unit and the fourth judgment unit in the fourth embodiment. Fig. 19 is a system block diagram showing an example of the system configuration of the predictive maintenance judgment system of the fifth embodiment.

12a: Predictive maintenance judging device

13: Control Department

51: Signal Acquisition Department

52a: Signal Analysis Department

53a: First Judgment Section

54: Notification Department

521: The first difference value calculation unit

522: Average calculation unit

523: Second difference calculation unit

524: The first ratio calculation unit

Claims (14)

A predictive maintenance judging device, which is provided with: The first difference value calculation unit, which obtains the output of the AE sensor installed on the surface of the casing of the machine, and calculates the first difference value of the maximum value and the minimum value of the aforementioned output for a specific time share; The average value calculation unit, which calculates the average value of the aforementioned output for the aforementioned specific time share; A second difference value calculation unit that calculates the second difference value of the maximum value and the minimum value of the output that does not reach the average value in the output of the specific time share; A first ratio calculation unit that calculates the ratio of the first difference value to the second difference value, that is, the first ratio; and The notification unit notifies that an abnormality may occur in the aforementioned equipment when the aforementioned first ratio is greater than or equal to the first specific value. A predictive maintenance judging device, which is provided with: The first difference value calculation unit, which obtains the output of the AE sensor installed on the surface of the casing of the machine, and calculates the first difference value of the maximum value and the minimum value of the aforementioned output for a specific time share; A third difference value calculation unit that calculates a third difference value of the maximum value and minimum value of the output remaining after removing the output for which the maximum value is a specific ratio or more in the output of the specific time share; A second ratio calculation unit that calculates the ratio of the first difference value to the third difference value, that is, the second ratio; and The notification unit notifies that an abnormality may occur in the aforementioned equipment when the aforementioned second ratio is greater than or equal to the second specific value. A predictive maintenance judging device, which is provided with: The first difference value calculation unit, which obtains the output of the AE sensor installed on the surface of the casing of the machine, and calculates the first difference value of the maximum value and the minimum value of the aforementioned output for a specific time share; The average value calculation unit, which calculates the average value of the aforementioned output for the aforementioned specific time share; A third ratio calculation unit that calculates the ratio of the first difference value to the average value, that is, the third ratio; and The notification unit, based on a two-dimensional graph in which the first difference value and the third ratio are taken on each axis, reports that an abnormality may occur in the machine. A predictive maintenance judging device, which is provided with: The first difference value calculation unit, which obtains the output of the AE sensor installed on the surface of the casing of the machine, and calculates the first difference value of the maximum value and the minimum value of the aforementioned output for a specific time share; The average value calculation unit, which calculates the average value of the aforementioned output for the aforementioned specific time share; A second difference value calculation unit that calculates the second difference value of the maximum value and the minimum value of the output that does not reach the average value in the output of the specific time share; A first ratio calculation unit that calculates the ratio of the first difference value to the second difference value, that is, the first ratio; and The notification unit, based on a two-dimensional graph in which the first difference value and the first ratio are taken on each axis, reports that an abnormality may occur in the machine. A predictive maintenance judging device, which is provided with: The first difference value calculation unit, which obtains the output of the AE sensor installed on the surface of the casing of the machine, and calculates the first difference value of the maximum value and the minimum value of the aforementioned output for a specific time share; A third difference value calculation unit that calculates a third difference value of the maximum value and minimum value of the output remaining after removing the output for which the maximum value is a specific ratio or more in the output of the specific time share; A second ratio calculation unit that calculates the ratio of the first difference value to the third difference value, that is, the second ratio; and The notification unit, based on a two-dimensional graph in which the first difference value and the second ratio are taken on each axis, reports that an abnormality may occur in the machine. For example, the predictive maintenance judging device of claim 3, in which the output of an acceleration sensor installed on the surface of the casing of the machine is obtained, and when the output of the acceleration sensor is greater than the third specific value, The aforementioned notification unit, based on a two-dimensional graph of the minimum or average output of the aforementioned AE sensor and the aforementioned first difference value taken on each axis, reports that the aforementioned machine may be abnormal; When the output of the acceleration sensor is below the third specific value, Based on a two-dimensional graph of the aforementioned first difference value and the aforementioned third ratio taken on each axis, it is reported that the aforementioned machine may be abnormal. For example, the predictive maintenance judging device of any one of request items 1 to 6, which is connected to the AE sensor installed on the surface of more than one machine via a network, and obtains the output of the AE sensor. Such as the predictive maintenance judging device of claim 1, wherein the aforementioned machine drives the gear box of the extruder. A predictive maintenance judgment method, which includes: The first difference value calculation program, which obtains the output of the AE sensor installed on the surface of the casing of the machine, and calculates the first difference value of the maximum and minimum values of the aforementioned output for a specific time share; The average value calculation program, which calculates the average value of the aforementioned output for the aforementioned specific time share; The second difference value calculation program, which calculates the second difference value of the maximum value and the minimum value of the output that does not reach the aforementioned average value in the aforementioned output of the aforementioned specific time share; A first ratio calculation program that calculates the ratio of the first difference value to the second difference value, that is, the first ratio; and The notification program, when the aforementioned first ratio is greater than or equal to the first specific value, informs the aforementioned equipment that there is a possibility of abnormality. A predictive maintenance judgment method, which includes: The first difference value calculation program, which obtains the output of the AE sensor installed on the surface of the casing of the machine, and calculates the first difference value of the maximum value and the minimum value of the aforementioned output for a specific time share; The third difference value calculation program, which calculates the third difference value of the maximum value and the minimum value of the output remaining after removing the output whose maximum value is more than a specific ratio in the output of the specific time share; A second ratio calculation program that calculates the ratio of the first difference value to the third difference value, that is, the second ratio; and The notification program, when the aforementioned second ratio is greater than or equal to the second specific value, informs the aforementioned equipment that there is a possibility of an abnormality. A predictive maintenance judgment method, which includes: The first difference value calculation program, which obtains the output of the AE sensor installed on the surface of the casing of the machine, and calculates the first difference value of the maximum and minimum values of the aforementioned output for a specific time share; The average value calculation program, which calculates the average value of the aforementioned output for the aforementioned specific time share; The third ratio calculation program, which calculates the ratio of the aforementioned first difference value to the aforementioned average value, that is, the third ratio; and The notification program is based on taking a two-dimensional graph of the aforementioned first difference value and the aforementioned third ratio on each axis, and reports that an abnormality may occur in the aforementioned machine. A program that enables a computer to control the predictive maintenance determination device that obtains the output of the AE sensor installed on the surface of the casing of the machine to function as the following parts, namely: The first difference value calculation unit, which calculates the first difference value between the maximum value and the minimum value of the aforementioned output for a specific time share; The average value calculation unit, which calculates the average value of the aforementioned output for the aforementioned specific time share; A second difference value calculation unit that calculates the second difference value of the maximum value and the minimum value of the output that does not reach the average value in the output of the specific time share; A first ratio calculation unit that calculates the ratio of the first difference value to the second difference value, that is, the first ratio; and The notification unit notifies that an abnormality may occur in the aforementioned equipment when the aforementioned first ratio is greater than or equal to the first specific value. A program that enables a computer to control the predictive maintenance determination device that obtains the output of the AE sensor installed on the surface of the casing of the machine to function as the following parts, namely: The first difference value calculation unit, which calculates the first difference value between the maximum value and the minimum value of the aforementioned output for a specific time share; A third difference value calculation unit that calculates a third difference value of the maximum value and minimum value of the output remaining after removing the output for which the maximum value is a specific ratio or more in the output of the specific time share; A second ratio calculation unit that calculates the ratio of the first difference value to the third difference value, that is, the second ratio; and The notification unit notifies that an abnormality may occur in the aforementioned equipment when the aforementioned second ratio is greater than or equal to the second specific value. A program that enables a computer to control the predictive maintenance determination device that obtains the output of the AE sensor installed on the surface of the casing of the machine to function as the following parts, namely: The first difference value calculation unit, which obtains the output of the AE sensor installed on the surface of the casing of the machine, and calculates the first difference value of the maximum value and the minimum value of the aforementioned output for a specific time share; The average value calculation unit, which calculates the average value of the aforementioned output for the aforementioned specific time share; A third ratio calculation unit that calculates the ratio of the first difference value to the average value, that is, the third ratio; and The notification unit, based on a two-dimensional graph in which the first difference value and the third ratio are taken on each axis, reports that an abnormality may occur in the machine.

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