CN113286995A - Predictive maintenance determination device, predictive maintenance determination method, and program - Google Patents

Predictive maintenance determination device, predictive maintenance determination method, and program Download PDF

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CN113286995A
CN113286995A CN202080008480.XA CN202080008480A CN113286995A CN 113286995 A CN113286995 A CN 113286995A CN 202080008480 A CN202080008480 A CN 202080008480A CN 113286995 A CN113286995 A CN 113286995A
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value
ratio
output
calculates
difference value
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CN113286995B (en
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野木贵之
竹内雄一
中村隼平
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Zhipu Machinery Co ltd
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01MTESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
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    • GPHYSICS
    • G01MEASURING; TESTING
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    • G01H3/14Measuring mean amplitude; Measuring mean power; Measuring time integral of power
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01MTESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
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Abstract

A first difference value calculation unit (521) of a predicted maintenance determination device (12a) acquires an AE output (M (t)) of an AE sensor (20) provided on the surface of a metal case (housing) of a gear box (30) (equipment), and calculates a difference value (delta 1) (first difference value) between the maximum value (Smax1) and the minimum value (Smin1) of the AE output within a predetermined time. An average value calculation unit (522) calculates the average value (Save) of AE outputs within a predetermined time. A second difference value calculation unit (523) calculates a difference value (delta 2) (second difference value) between the maximum value (Smax2) and the minimum value (Smin1) of the AE outputs that are smaller than the average value (Save) within a predetermined time. A first ratio calculation unit (524) calculates a ratio (R1) (first ratio) of the first difference value to the second difference value. When the ratio (R1) is equal to or greater than a first predetermined value (ε 1), a notification unit (54) notifies that an abnormality may occur in the gear box (30).

Description

Predictive maintenance determination device, predictive maintenance determination method, and program
Technical Field
The present invention relates to a predictive maintenance determination device, a predictive maintenance determination method, and a program for predicting the occurrence of an abnormality in a plant.
Background
It is known that strain energy accumulated before is released as an acoustic wave (AE wave) when a solid material is deformed. In addition, a damage detection device has been known in the related art, which detects damage to a gear by detecting an AE wave by an AE sensor and analyzing the waveform of the AE wave.
For example, the gear damage detection device described in patent document 1 analyzes the output of the AE sensor to detect the signal intensity in a specific frequency range, thereby detecting the occurrence of gear damage.
Documents of the prior art
Patent document
Patent document 1: japanese patent laid-open No. 2009-42151
Disclosure of Invention
Technical problem to be solved by the invention
However, the damage detection device of patent document 1 has the following problems: if an abnormality such as a damage does not actually occur in the device, the abnormality cannot be detected. Therefore, when an abnormality is detected, it is necessary to immediately stop the equipment, inspect and maintain the abnormal portion, replace a consumable part (a bearing, a seal member, or the like), perform cleaning, or the like. Therefore, it may be necessary to stop the equipment at a time other than the expected time, and not only the equipment but also measures such as stopping the production line may be necessary. Thus, a significant impact on the production process may be generated.
The present invention has been made in view of the above circumstances, and an object thereof is to provide a predictive maintenance determination device, a predictive maintenance determination method, and a program that can notify occurrence of an abnormality that affects the operation of a device before the abnormality actually occurs.
Means for solving the problems
In order to solve the above problems and achieve the object, a predictive maintenance determination device according to the present invention includes: an AE sensor provided on a surface of a housing of the apparatus; a first difference value calculation unit that acquires an output of the AE sensor and calculates a first difference value between a maximum value and a minimum value of the output for a predetermined time; an average value calculation unit that calculates an average value of the outputs over the predetermined time; a second difference value calculation unit that calculates a second difference value between a maximum value and a minimum value of the output smaller than the average value among the outputs for the predetermined time; a first ratio calculation unit that calculates a ratio of the first difference value to the second difference value; and a notification unit configured to notify the predicted maintenance of the equipment when the ratio calculated by the first ratio calculation unit is equal to or greater than a first predetermined value.
Further, a predictive maintenance determination device according to the present invention includes: a first differential value calculation section that acquires an output of an AE sensor provided on a housing surface of the device and calculates a first differential value between a maximum value and a minimum value of the output for a predetermined time; a third difference value calculation unit that calculates a third difference value between a maximum value and a minimum value of an output remaining after the output of the predetermined ratio or more of the maximum value is removed from the outputs within the predetermined time; a second ratio calculation unit that calculates a second ratio that is a ratio of the first difference value to the third difference value; and a notification section that notifies that an abnormality may occur in the device when the second ratio is a second predetermined value or more.
Further, a predictive maintenance determination device according to the present invention includes: a first differential value calculation section that acquires an output of an AE sensor provided on a housing surface of the device and calculates a first differential value between a maximum value and a minimum value of the output for a predetermined time; an average value calculation unit that calculates an average value of the outputs over the predetermined time; a third ratio calculation unit that calculates a third ratio that is a ratio of the first difference value to the average value; and a notification section that notifies that an abnormality may occur in the device based on a two-dimensional map obtained by taking the first difference value and the third ratio on each axis.
Effects of the invention
The predictive maintenance determination device of the present invention can notify the occurrence of an abnormality that affects the operation of equipment before the actual occurrence of the abnormality, that is, when a sign of the abnormality is detected. Therefore, the timing for inspecting and maintaining the equipment, replacing the consumable parts, cleaning, and the like can be set in advance. Therefore, while the equipment is stopped, the operation state of the production line can be maintained by operating other equipment or the like.
Drawings
Fig. 1 is an explanatory diagram of an acoustic emission and AE sensor.
Fig. 2 is an overall configuration diagram of a predictive maintenance determination system using the predictive maintenance determination device according to embodiment 1.
FIG. 3 is a structural diagram of an extruder according to embodiment 1
Fig. 4 is a hardware configuration diagram of the predictive maintenance determination device according to embodiment 1.
Fig. 5 is a functional configuration diagram of the predictive maintenance determination device according to embodiment 1.
Fig. 6 is an explanatory diagram of the predictive maintenance determination method according to embodiment 1.
Fig. 7 is a flowchart showing an example of a process flow performed by the predictive maintenance determination device according to embodiment 1.
Fig. 8 is a functional configuration diagram of the predictive maintenance determination device according to embodiment 2.
FIG. 9 is an explanatory diagram of a predictive maintenance determination method according to embodiment 2
Fig. 10 is a flowchart showing an example of the processing flow of embodiment 2.
Fig. 11 is an overall configuration diagram of a predictive maintenance determination system using the predictive maintenance determination device according to embodiment 3.
Fig. 12 is a functional configuration diagram of the predictive maintenance determination device according to embodiment 3.
Fig. 13 is a diagram showing an example of the determination criterion in embodiment 3.
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 embodiment 3.
Fig. 15 is an overall configuration diagram of a predictive maintenance determination system using the predictive maintenance determination device according to embodiment 4.
Fig. 16 is a functional configuration diagram of a predictive maintenance determination device according to embodiment 4.
Fig. 17 is a diagram showing an example of the determination criterion when the vibration acceleration is larger than the third prescribed value.
Fig. 18 is a flowchart showing an example of the flow of processing performed by the signal analysis unit and the fourth determination unit in embodiment 4.
Fig. 19 is a system block diagram showing an example of the system configuration of the predictive maintenance determination system according to embodiment 5.
Detailed Description
[ description of Acoustic Emission (AE: Acoustic Emission) ]
Before the description of the embodiments, acoustic emission (hereinafter referred to as AE) for determining predictive maintenance of a device will be described. AE is a phenomenon in which strain energy accumulated before deformation of a solid material is released as an acoustic wave (elastic wave, AE wave). By detecting the AE wave, abnormality of the solid material can be predicted. The frequency band of the AE wave is usually around several tens kHz to several MHz, and has a frequency band that cannot be detected by a general vibration sensor and acceleration sensor. Therefore, in order to detect the AE wave, a dedicated AE sensor is used. The AE sensor will be described in detail later.
Fig. 1 is an explanatory diagram of an acoustic emission and AE sensor. As shown in fig. 1(a), when the AE generation source P inside the solid material Q is deformed, contacted, rubbed, or the like, an AE wave W is generated. The AE wave W radially spreads from the AE generation source P and propagates inside the solid material Q at a speed corresponding to the solid material Q.
The AE wave W propagating inside the solid material Q is detected by the AE sensor 20 provided on the surface of the solid material Q. The AE sensor 20 outputs a detection signal D. Since the detection signal D is a signal indicating vibration, the detection signal D is an alternating current signal having positive and negative values. However, since it is difficult to handle the detection signal D (AE wave W) in such a state when various calculations are performed, a negative value portion of the detection signal D is generally handled as a rectified waveform after half-wave rectification. In the analysis of the AE wave W, the Square value of the rectified waveform is generally averaged over a predetermined period of time to obtain a Square Root, that is, an effective value (RMS (Root Mean Square) value) to be processed.
Although the propagation 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 in consideration of the size (propagation distance) of the solid material Q, and thus the longitudinal wave and the transverse wave are not distinguished in the present embodiment. That is, the AE wave W detected within a predetermined time is used as a measurement signal and is analyzed without distinguishing between the longitudinal wave and the transverse wave.
As shown in fig. 1(b), the AE sensor 20 is enclosed in a shield case 20 a. A wave receiving surface 20b for receiving the AE wave W is formed on the bottom surface of the AE sensor 20. The wave receiving surface 20b is formed of an insulator. Further, a magnet 20c is provided near the bottom surface of the shield case 20a, and the AE sensor 20 is fixed to the metal case 30a of the device 30 that is the predicted maintenance object by the magnet 20 c. At this time, the wave receiving surface 20b is disposed in a state of being in close contact with the surface of the metal case 30a of the device 30.
A deposited film 20d of copper or the like is formed on the wave receiving surface 20 b. Then, a piezoelectric element 20e such as lead zirconate titanate (PZT) is provided on the deposited film 20 d. 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 electric signal output from the piezoelectric element 20e is output as a detection signal D via the deposited film 20f and the connector 20 g. Since the detection signal D is weak, a preamplifier (not shown in fig. 1 (b)) may be provided inside the AE sensor 20 and output after amplifying the detection signal D in advance to suppress the influence caused by the mixed noise.
Since AE is also generated by fine damage or friction, a sign of abnormality of the device can be found as soon as possible. Since the AE waves W are radially diffused from the AE generation source P, if the housing is made of metal, the AE sensor 20 is provided to observe the AE waves W and acquire the detection signal D at any position of the housing. Further, a specific method of analyzing the detection signal D will be described later. Since the frequency band of the detectable signal of the AE sensor 20 differs depending on the type, it is preferable to consider the material of the device to be measured when selecting the AE sensor 20 to be used.
Hereinafter, embodiments of the predictive maintenance determination device, the predictive maintenance determination method, and the program according to the present disclosure will be described in detail with reference to the drawings. The present invention is not limited to these embodiments. The components in the following embodiments include components that can be replaced and easily conceived by those skilled in the art, or substantially the same components.
[ embodiment 1]
Embodiment 1 of the present disclosure is an example of a predictive maintenance determination device 12a for detecting and notifying a sign of an abnormality occurring in a plant.
[ description of the schematic configuration of the predictive maintenance determining apparatus ]
First, the overall configuration of the predictive maintenance determination system 10a using the predictive maintenance determination device 12a in the present embodiment will be described with reference to fig. 2. Fig. 2 is an overall configuration diagram of a predictive maintenance determination system using the predictive maintenance determination device according to embodiment 1. The predictive maintenance determination system 10a applies the predictive maintenance determination device 12a of the present disclosure to the determination of predictive maintenance of the gear box 30 that drives the extruder 40 by reducing the rotational driving force of the motor 22. Gearbox 30 is one example of an apparatus 30. The gear box 30 is configured by meshing a plurality of gears, and reduces the rotational driving force of the motor 22 connected to the input side and transmits it to the output side. The predicted maintenance determination system 10a detects and notifies the occurrence of cracks and wear in the gear and the signs of abnormality such as the wear of the shaft supporting the gear. The following device configuration is an example, and the equipment to be subjected to predictive maintenance is not limited to the gear box 30. Further, the driving object of the gear box 30 is not limited to the extruder 40. The outline of the extruder 40 is described later (see fig. 3).
The predicted maintenance determining device 12a acquires 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. The predicted maintenance determining device 12a performs the predicted maintenance of the gear box 30 by analyzing the output of the AE sensor 20.
As the AE sensor 20, a sensor having a frequency band capable of detecting the AE wave W propagating inside the metal case 30a is used. In particular, when the frequency band of the AE wave W to be detected is known, it is preferable to use the AE sensor 20 having high sensitivity to the frequency band. For example, in the present embodiment, the AE sensor 20 having high sensitivity in a frequency band including 150kHz is used.
Although the position of the AE sensor 20 attached to the metal case 30a of the gear case 30 is not limited, it is preferably attached to the vicinity of a portion where abnormality is likely to occur in the gear case 30. For example, the AE sensor 20 is preferably mounted near the output shaft of the gear box 30.
When it is determined that there is a sign of an abnormality occurring in the gear box 30 as a result of the determination of the predicted maintenance, the predicted maintenance determining device 12a notifies the presence of the sign of the abnormality through a monitor, a speaker, and the like, which are not shown in fig. 2.
[ description of the extruder Structure ]
Fig. 3 is a structural diagram of the extruder of embodiment 1, and in the extruder 40, for example, a resin material and a powdery filler are kneaded by rotating a screw 42 provided at a position where an output shaft 32 is extended in accordance with the rotation of the output shaft 32 rotationally driven by the output of a gear box 30. In particular, the extruder 40 shown in fig. 3 is a twin-screw extruder having two output shafts 32 disposed at an inter-shaft distance C.
The two output shafts 32 are arranged in parallel with a fixed inter-shaft distance C inside the cylindrical portion 44. The base portions of two screws 42 that rotate in the same direction while meshing with each other are connected to each output shaft 32. The output shaft 32 transmits the rotation of the motor 22, which is decelerated by the gear box 30, to the screw 42. The screw 42 rotates at a speed of, for example, 300 revolutions per minute or the like.
Two cylindrical insertion holes 46 into which the respective screws 42 are inserted are provided in the cylinder portion 44. The insertion hole 46 is a hole provided along the longitudinal direction of the cylinder portion 44, and a part of the cylinders overlap so that the two screws 42 engaged with each other can be inserted. A material supply port 47 is provided at one end side in the longitudinal direction of the cylindrical portion 44, and the material supply port 47 supplies a granular resin material to be kneaded and a powdery filler material to the insertion hole 46. A discharge port 48 is provided on the other end side in the longitudinal direction of the cylinder 44, and the discharge port 48 is used for discharging the material that has been kneaded while passing through the insertion hole 46. A heater 49 is provided on the outer periphery of the cylindrical portion 44, and the heater 49 heats the cylindrical portion 44 to heat the material supplied to the insertion hole 46.
The screw 42 has a first screw portion 42a, a second screw portion 42b, and a third screw portion 42c from one end side of the cylindrical portion 44 provided with the material supply port 47 toward the other end side of the cylindrical portion 44 provided with the discharge port 48. Although detailed description is omitted, the first, second, and third screw portions 42a, 42b, and 42c have different shapes, respectively, in order to uniformly mix the materials.
Similarly, the cylinder 44 has a first cylinder 44a, a second cylinder 44b, and a third cylinder 44c corresponding to the first screw 42a, the second screw 42b, and the third screw 42c of the screw 42 from one end provided with the material supply port 47 to the other end provided with the discharge port 48. The clearance between the screw 42 and the cylindrical portion 44 is formed to gradually decrease from the gear case 30 side toward the discharge port 48 side. Thereby, the material supplied from the material supply port 47 is further uniformly kneaded.
The total length L of the cylindrical portion 44 in the longitudinal direction, the length L1 of the first cylindrical portion 44a and the first screw portion 42a, the length L2 of the second cylindrical portion 44b and the second screw portion 42b, and the length L3 of the third cylindrical portion 44c and the third screw portion 42c are determined as appropriate depending on the material to be kneaded.
The molten resin is kneaded to be uniform in the vicinity of the tip of the screw 42. The molten resin having passed through the screw 42 is discharged from the discharge port 48 in a uniformly kneaded state.
[ description of hardware configuration of predictive maintenance determining apparatus ]
Next, the hardware configuration of the predictive maintenance determining apparatus 12a will be described with reference to fig. 4. Fig. 4 is a hardware configuration diagram of the predictive maintenance determination device according to embodiment 1.
The predictive maintenance determination device 12a includes a control unit 13, a storage unit 14, and a peripheral controller 16.
The control section 13 includes a CPU (central processing unit) 13a, a ROM (read only memory) 13b, and a RAM (random access memory) 13 c. The CPU13a is connected to the ROM13b and the RAM13c via the bus 15. The CPU13a reads the control program P1 stored in the storage section 14, and develops the control program P1 in the RAM13 c. The CPU13a operates according to the control program P1 developed in the RAM13c, thereby controlling the operation of the controller 13. That is, the control unit 13 has a general computer configuration that operates based on the control program P1.
The control section 13 is also connected to a storage section 14 and a peripheral device controller 16 via a bus 15.
The storage unit 14 is a nonvolatile memory such as a flash memory that retains stored information even when power is turned off, or an HDD (hard disk drive). The storage unit 14 stores programs including the control program P1 and AE outputs m (t). The control program P1 is a program for exhibiting the functions of the control unit 13. The AE output m (t) is a signal obtained by converting the effective value of the detection signal D output by the AE sensor 20 into a digital signal by the a/D converter 17.
The control program P1 may be embedded in the ROM13b in advance. The control program P1 may be provided as a file in a format that can be installed in the control unit 13 or in a format that can be executed, and recorded on a computer-readable recording medium such as a CD-ROM, a Floppy Disk (FD), or a CD-R, DVD (digital versatile disk). The control program P1 may be stored in a computer connected to a network such as the internet and may be provided by being downloaded via the network. The control program P1 may be provided or distributed 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 controller 16 controls operations of various connected hardware based on instructions from the control unit 13.
The a/D converter 17 converts the detection signal D output from 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 relating to the operation state of the predicted maintenance determining apparatus 12 a. Further, when the predicted maintenance determining device 12a detects a sign of an abnormality in the gear box 30 (equipment), the display device 18 notifies it.
The operation device 19 is, for example, a touch panel superimposed on the display device 18. The operation device 19 acquires operation information related to the setting and operation of the predictive maintenance determining apparatus 12 a.
[ description of the functional Structure of the predictive maintenance determining apparatus ]
Next, the functional configuration of the predictive maintenance determination device 12a will be described with reference to fig. 5. Fig. 5 is a functional configuration diagram of the predictive maintenance determination device according to embodiment 1. The control unit 13 of the predictive maintenance determination device 12a develops and operates the control program P1 in the RAM13c, and thereby realizes the signal acquisition unit 51, the signal analysis unit 52a, the first determination unit 53a, and the notification unit 54 shown in fig. 5 as functional units.
The signal acquisition unit 51 acquires the detection signal D output from the AE sensor 20. The signal acquisition section 51 includes an amplifier to amplify the detection signal D, and an a/D converter to convert the effective value of the detection signal D as an analog signal into an AE output m (t) as a digital signal.
The signal analyzer 52a analyzes the AE output m (t) and calculates an evaluation value for determining whether or not a sign of an abnormality is found in the gear box 30.
The signal analyzing section 52a further includes a first difference value calculating section 521, an average value calculating section 522, a second difference value calculating section 523, and a first ratio calculating section 524.
The first difference value calculation unit 521 calculates a difference value δ 1 between the maximum value Smax1 and the minimum value Smin1 of the AE output m (t) for a predetermined time (for example, for a period of 10 seconds) which is Smax1-Smin1 (first difference value). The predetermined time may be determined to be an appropriate value based on the calculation capability of the predicted maintenance determining device 12 a.
The average value calculation unit 522 calculates an average value Save of the AE outputs m (t) for a predetermined time.
The second difference value calculator 523 calculates a difference value δ 2 between the maximum value Smax2 and the minimum value Smin1 of the AE outputs m (t) less than the average value Save, from the AE outputs m (t) within a predetermined time period, Smax2-Smin1 (second difference value).
The first ratio calculation unit 524 calculates a ratio R1 of the first differential value to the second differential value as δ 1/δ 2. The ratio R1 (first ratio) is calculated by the signal analysis section 52 a. The ratio R1 is the above-described evaluation value.
The first determination unit 53a determines whether or not the ratio R1 calculated by the first ratio calculation unit 524 is equal to or greater than the first predetermined value ∈ 1.
When the first determination unit 53a determines that the ratio R1 is equal to or greater than the first predetermined value ∈ 1, the notification unit 54 notifies the gearbox 30 (equipment) of the predicted maintenance. Specifically, the notification unit 54 notifies that an abnormal sign is found in the gear box 30 by displaying it on the display device 18. Note that the notification method of the notification unit 54 is not limited to this, and the notification may be performed by lighting or blinking an indicator not shown in fig. 4, or may be performed by outputting a sound or voice from a speaker or a buzzer not shown in fig. 4.
[ description of predictive maintenance determination method ]
According to the evaluation experiment by the inventors, when the AE output M1(t) when a significant abnormality (for example, damage to a gear built in the gear box 30) occurs in the gear box 30 to be evaluated is compared with the AE output M2(t) when the gear box 30 is normal, it is known that the ratio of the difference value between the maximum value and the minimum value of the AE output M1(t) to the difference value between the maximum value and the minimum value of the AE output M2(t) is about 5. Further, since it is known that the ratio becomes a larger value as the abnormality of the gear box 30 progresses, it is desirable to determine that there is a sign of abnormality in the gear box 30 before the ratio reaches 5, for example, when the ratio is about 3.
Further, by the evaluation of the inventors, it is known that the ratio of the difference value between the maximum value and the minimum value of the AE output M2(t) when the gear case 30 is normal to the difference value between the maximum value and the minimum value of the output smaller than the average value Save in the AE output M1(t) when an abnormality occurs in the gear case 30 increases as the abnormality of the gear case 30 progresses.
Therefore, the inventors made the following judgments: in order to control and notify the sign of an abnormality, it is appropriate to determine that there is a sign of an abnormality when the ratio of the difference value between the maximum value and the minimum value of the AE output m (t) to the difference value between the maximum value and the minimum value of the output m (t) that is less than the average value Save in the AE output m (t) reaches the first predetermined value ∈ 1. The value of the first predetermined value ∈ 1 can be set to a value corresponding to the gear box 30 to be evaluated by performing an evaluation experiment or the like in advance.
Next, a method of determining whether or not an abnormal symptom is found in the gear box 30, which is performed by the predicted maintenance determining device 12a, will be described with reference to fig. 6. Fig. 6 is an explanatory diagram of the predictive maintenance determination method according to embodiment 1.
The graph 60a shown in fig. 6 is an example of the AE output m (t) from the AE sensor 20 acquired by the signal acquisition unit 51 of the predicted maintenance determination device 12 a. In fig. 6, the abscissa indicates time t, and the ordinate indicates the effective value (RMS value) of the AE output m (t) of the AE sensor 20. The AE output from the AE sensor 20 is output as a continuous waveform, but the graph 60a is a scatter diagram obtained by sampling the continuous waveform at predetermined time intervals. 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 operated together.
The signal analysis unit 52a performs the following signal processing on the AE output m (t). The first difference value calculation unit 521 calculates a difference value δ 1 between the maximum value Smax1 and the minimum value Smin1 of the AE output m (t) over a predetermined time period, for example, 10 seconds as shown in fig. 6, which is Smax1-Smin1 (first difference value).
Next, the average value calculation unit 522 calculates an average value Save of the AE outputs m (t) for a predetermined time (for example, for 10 seconds).
The second difference value calculation unit 523 calculates a difference value δ 2 between the maximum value Smax2 and the minimum value Smin1 of the AE outputs m (t) remaining after the AE outputs m (t) exceeding the average value Save are removed from the AE outputs AE (t) within a predetermined time, which is Smax2-Smin1 (second difference value).
The first ratio calculation unit 524 calculates a ratio R1 (first ratio) of the first differential value δ 1 to the second differential value δ 2. That is, the first ratio calculation unit 524 calculates the ratio R1 from δ 1/δ 2, which is R1.
The first determination unit 53a determines whether or not the ratio R1 calculated by the first ratio calculation unit 524 is equal to or greater than the first predetermined value ∈ 1. When it is determined that the ratio R1 is equal to or greater than the first predetermined value ∈ 1, the notification unit 54 notifies the display device 18 (see fig. 4) of the detection of a sign of abnormality in the gear box 30.
The predicted maintenance determining device 12a performs the above-described processing all the time while the gear box 30 and the extruder 40 are operating. The judgment by the first judgment unit 53a and the notification by the notification unit 54 are performed at predetermined time intervals, for example, at 10-second intervals.
The timing of the determination and notification is not limited to this. That is, the notification may be performed at predetermined time intervals based on the determination result of the AE output m (t) in the past predetermined time. For example, the notification may be performed based on the determination result of the AE output m (t) in a past predetermined time (for example, 10 seconds) at a timing such as once per second.
[ description of the flow of processing by the predictive maintenance determining apparatus ]
Next, a flow of processing performed by the predictive maintenance determination device 12a according to embodiment 1 will be described with reference to fig. 7. Fig. 7 is a flowchart showing an example of a process flow performed by the predictive maintenance determination device according to embodiment 1.
The signal acquiring unit 51 acquires AE output m (t) for a predetermined time from the storage unit 14 (step S11).
The first difference value calculation unit 521 calculates a first difference value δ 1 between the maximum value Smax1 and the minimum value Smin1 of the AE output m (t) for a predetermined time (step S12).
The average value calculation unit 522 calculates an average value Save of the AE outputs m (t) for a predetermined time (step S13).
The second differential value calculation unit 523 calculates a second differential value δ 2 between the maximum value Smax2 and the minimum value Smin1 of the AE outputs m (t) less than the average value Save over a predetermined time period (step S14).
The first ratio calculation part 524 calculates a ratio R1 of the first differential value δ 1 with respect to the second differential value δ 2 (step S15).
The first determination unit 53a determines whether or not the first ratio R1 is equal to or greater than the first predetermined value ∈ 1 (step S16). When it is determined that the first ratio R1 is equal to or greater than the first predetermined value ∈ 1 (step S16: yes), the process proceeds to step S17. When it is determined that the first ratio R1 is not equal to or greater than the first predetermined value ∈ 1 (no in step S16), the process returns to step S11.
If it is determined as yes in step S16, the notification unit 54 notifies the predicted maintenance of the gear box 30, that is, notifies the presence of a sign of an abnormality. Then, the predicted maintenance determining device 12a ends the processing of fig. 7.
As described above, in the predictive maintenance determination device 12a according to embodiment 1, the first differential value calculation unit 521 acquires the AE output m (t) of the AE sensor 20 provided on the surface of the metal casing 30a (casing) of the gear box 30 (equipment), and calculates the differential value δ 1 (first differential value) between the maximum value Smax1 and the minimum value Smin1 of the AE output m (t) over a predetermined time. The average value calculation unit 522 calculates an average value Save of the AE outputs m (t) for a predetermined time. The second difference value calculation unit 523 calculates a difference value δ 2 (second difference value) between the maximum value Smax2 and the minimum value Smin1 of the AE outputs m (t) less than the average value Save in the AE outputs m (t) for a predetermined time. The first ratio calculation unit 524 calculates a ratio R1 (first ratio) of the difference value δ 1 to the difference value δ 2. When the ratio R1 is equal to or greater than the first predetermined value ∈ 1, the notification unit 54 notifies that an abnormality may occur in the gear box 30. Therefore, the predicted maintenance determining device 12a notifies the timing when the AE output m (t) smaller than the AE output m (t) generated when the significant abnormality occurs in the gear box 30 is detected, and thus can notify the abnormality before the occurrence of the abnormality affecting the operation of the gear box 30.
The predicted maintenance determination device 12a according to embodiment 1 determines the predicted maintenance of the gear box 30 (equipment) that drives the extruder 40. Therefore, since the notification can be made before the occurrence of an abnormality that affects the operation of the gear box 30 or the extruder 40, it is possible to plan in advance the timing of stopping the extruder 40, checking and maintaining the gear box 30, replacing a consumable part, performing cleaning, and the like. Therefore, the production line can be prevented from stopping at an unexpected timing.
In addition, in the predictive maintenance determination device 12a according to embodiment 1, the frequency analysis performed when the AE wave W is analyzed is not normally performed. Therefore, the processing load when the AE output m (t) is analyzed can be reduced.
[ embodiment 2]
Embodiment 2 of the present disclosure is an example of a predictive maintenance determination device 12b that is provided in a predictive maintenance determination system 10b (not shown) and that detects and notifies a sign of an abnormality occurring in a device. The predicted maintenance determination device 12b has a different predicted maintenance determination method from the predicted maintenance determination device 12 a.
[ description of the functional Structure of the predictive maintenance determining apparatus ]
The functional configuration of the predicted maintenance determining apparatus 12b will be described with reference to fig. 8. Fig. 8 is a functional configuration diagram of the predictive maintenance determination device according to embodiment 2. The control unit 13 of the predictive maintenance determination device 12b develops and operates the control program P2 (not shown) in the RAM13c, and realizes the signal acquisition unit 51, the signal analysis unit 52b, the second determination unit 53b, and the notification unit 54 shown in fig. 8 as functional units.
The functions of the signal acquisition unit 51 and the notification unit 54 are the same as those of the predicted maintenance determination device 12a described above.
The signal analyzer 52b analyzes the output of the AE sensor 20 acquired by the signal acquirer 51, and calculates an evaluation value for determining whether or not a sign of an abnormality is found in the gear box 30.
The signal analyzing section 52b further includes a first differential value calculating section 521, an abnormal value removing section 525, a third differential value calculating section 526, and a second ratio calculating section 527.
The function of the first difference value calculation unit 521 is the same as that of the predicted maintenance determination device 12a described above.
The abnormal value removing unit 525 removes an output equal to or greater than a predetermined ratio U of the maximum value Smax1 of the output from the AE output m (t) for a predetermined time. The predetermined ratio U is determined based on a previous evaluation experiment or the like, and is set to, for example, 30%. The predetermined ratio U is set to a value corresponding to the gear box 30 to be evaluated by performing an evaluation experiment or the like in advance. The details will be described later.
The third differential value calculation section 526 calculates a differential value δ 3 between the maximum value Smax3 and the minimum value Smin1 of the output of the abnormal value removal section 525 (third differential value) Smax3-Smin 1.
The second ratio calculation unit 527 calculates the ratio R2 of the first differential value δ 1 to the third differential value δ 3 as δ 1/δ 3. The ratio R2 (second ratio) is the above-described evaluation value calculated by the signal analysis section 52 b.
The second determination unit 53b determines whether or not the ratio R2 calculated by the second ratio calculation unit 527 is equal to or greater than a second predetermined value (e.g., 3).
[ description of predictive maintenance determination method ]
Next, a method of determining whether or not a sign of an abnormality is found in the gear box 30, which is a determination for predictive maintenance performed by the predictive maintenance determination device 12b, will be described with reference to fig. 9. Fig. 9 is an explanatory diagram of the predictive maintenance determination method according to embodiment 2.
The graph 60b shown in fig. 9 is an example of the AE output m (t) from the AE sensor 20 acquired by the signal acquisition unit 51 of the predicted maintenance determination device 12 a. In fig. 9, the abscissa indicates time t, and the ordinate indicates the effective value (RMS value) of the AE output m (t) of the AE sensor 20. Although the AE output from the AE sensor 20 is output as a continuous waveform, the graph 60b is a scatter diagram obtained by sampling the continuous waveform at prescribed time intervals.
The first difference value calculation unit 521 calculates a difference value δ 1 between the maximum value Smax1 and the minimum value Smin1 of the AE output m (t) over a predetermined time period, for example, 10 seconds as shown in fig. 9, which is Smax1-Smin1 (first difference value).
Next, the abnormal value removing unit 525 removes the output at the predetermined ratio U or more of the maximum value Smax1 of the AE output m (t) from the AE output m (t) for the predetermined time.
The third difference value calculation unit 526 calculates a difference value δ 3 between the maximum value Smax3 and the minimum value Smin1 of the output remaining after the abnormal value removal unit 525 removes the output of the predetermined ratio U or more of the maximum value Smax1 of the AE output m (t) within the predetermined time from the AE output m (t) (third difference value) Smax3-Smin 1.
The second ratio calculation section 527 calculates a ratio R2 (second ratio) of the first differential value δ 1 to the third differential value δ 3. That is, the second ratio calculator 527 calculates the ratio R2 from δ 1/δ 3, which is R2.
The first determination unit 53a determines whether or not the ratio R2 calculated by the second ratio calculation unit 527 is equal to or greater than the second predetermined value ∈ 2. When the determination ratio R2 is equal to or greater than the second predetermined value ∈ 2, the notification unit 54 notifies the display device 18 (see fig. 4) of the detection of the abnormal sign of the gear case 30.
The predicted maintenance determining device 12b performs the above-described processing all the time while the gear box 30 and the extruder 40 are operating. The judgment by the second judgment unit 53b and the notification by the notification unit 54 are performed at predetermined time intervals, for example, at 10-second intervals.
The timing of the determination and notification is not limited to this. That is, the notification may be performed at predetermined time intervals based on the determination result of the AE output m (t) in the past predetermined time. For example, the notification may be performed based on the determination result of the AE output m (t) in a past predetermined time (for example, 10 seconds) at a timing such as once per second.
In the second embodiment, the values of the predetermined ratio U and the second predetermined value ∈ 2 are set to values corresponding to the gear case 30 to be evaluated by performing an evaluation experiment or the like in advance.
As described above, according to the evaluation experiment by the inventor, the ratio of the difference value between the maximum value and the minimum value of the AE output M1(t) when a significant abnormality occurs in the gear box 30 to be evaluated to the difference value between the maximum value and the minimum value of the AE output M2(t) when the gear box 30 is normal is about 5. Further, since it is known that the ratio becomes a larger value as the abnormality of the gear box 30 progresses, it is desirable to determine that there is a sign of abnormality in the gear box 30 before the ratio reaches 5, for example, when the ratio is about 3.
Further, according to the evaluation by the inventors, it is found that the differential value between the maximum value and the minimum value of the AE output M2(t) when the gear case 30 is in the normal state is almost equal to the differential value between the maximum value and the minimum value of the output obtained by removing data of about the first 30% of the AE output M1(t) from the AE output M1(t) when an abnormality occurs in the gear case 30.
Therefore, the inventors made the following judgments: in order to control and notify the abnormal sign, it is appropriate to determine that the abnormal sign is present when the ratio of the difference value between the maximum value and the minimum value of the AE output m (t) to the difference value between the maximum value and the minimum value of the AE output m (t) from which about the first 30% of the data is removed reaches about 3 (corresponding to the second predetermined value ∈ 2 described above).
In the case of comparing the evaluation method described in embodiment 1 with the evaluation method described in embodiment 2, it can be regarded as an almost equivalent analysis method in that the AE output m (t) and the data obtained by removing the pre-discharge data from the AE output m (t) are compared. Therefore, although any method can be applied to the determination, in the method described in embodiment 2, that is, the method of determining based on the data obtained by removing the data of the predetermined proportion of the AE output m (t) before the row, it is not necessary to calculate the average value, and the amount of calculation of the analysis processing is reduced accordingly.
[ description of the flow of processing by the predictive maintenance determining apparatus ]
Next, a flow of processing performed by the predictive maintenance determination device 12b according to embodiment 2 will be described with reference to fig. 10. Fig. 10 is a flowchart showing an example of a process flow performed by the predictive maintenance determination device according to embodiment 2.
The signal acquiring unit 51 acquires AE output m (t) for a predetermined time from the storage unit 14 (step S21).
The first difference value calculation unit 521 calculates a first difference value δ 1 between the maximum value Smax1 and the minimum value Smin1 of the AE output m (t) for a predetermined time (step S22).
The abnormal value removing unit 525 removes AE outputs m (t) at a predetermined ratio U or more of the maximum values Smax1 among the AE outputs m (t) for a predetermined time (step S23).
The third differential value calculation unit 526 calculates a third differential value δ 3 between the maximum value Smax3 after the abnormal value removal unit 525 removes the predetermined AE output m (t) and the minimum value Smin1 of the AE output m (t) (step S24).
The second ratio calculation part 527 calculates the ratio R2 of the first differential value δ 1 to the third differential value δ 3 (step S25).
The second determination unit 53b determines whether or not the second ratio R2 is equal to or greater than the second predetermined value ∈ 2 (step S26). When it is determined that the second ratio R2 is equal to or greater than the second predetermined value ∈ 2 (step S26: yes), the process proceeds to step S27. On the other hand, when it is determined that the second ratio R2 is not equal to or greater than the second predetermined value ε 2 (NO in step S26), the process returns to step S21.
If it is determined as yes in step S26, the notification unit 54 notifies the predicted maintenance of the gear box 30, that is, displays a sign of the detected abnormality. Then, the predicted maintenance determining device 12b ends the processing of fig. 10.
As described above, in the predictive maintenance determination device 12b according to embodiment 2, the first differential value calculation unit 521 acquires the AE output m (t) of the AE sensor 20 provided on the surface of the metal casing 30a (casing) of the gear box 30 (equipment), and calculates the differential value δ 1 (first differential value) between the maximum value Smax1 and the minimum value Smin1 of the AE output m (t) over a predetermined time. The third difference value calculation unit 526 calculates a difference value δ 3 (third difference value) between the maximum value Smax3 and the minimum value Smin1 of the AE outputs m (t) remaining after the outputs at the predetermined ratio U or more of the maximum value Smax1 are removed from the AE outputs m (t) within the predetermined time. Then, the second ratio calculation section 527 calculates a ratio R2 (second ratio) of the differential value δ 1 to the differential value δ 3. When the second determination unit 53b determines that the ratio R2 is equal to or greater than the second predetermined value ∈ 2, the notification unit 54 notifies that a sign of an abnormality is found in the gear box 30. Therefore, the predicted maintenance determining device 12b can notify the occurrence of an abnormality that affects the operation of the gear box 30 before notifying the occurrence of an abnormality because it notifies the timing when the AE output m (t) smaller than the AE output m (t) generated when a significant abnormality occurs in the gear box 30 is detected.
The predicted maintenance determination device 12b according to embodiment 2 determines the predicted maintenance of the gear box 30 (equipment) that drives the extruder 40. Therefore, since the notification can be made before the occurrence of an abnormality that affects the operation of the gear box 30 or the extruder 40, it is possible to plan in advance the timing of stopping the extruder 40, checking and maintaining the gear box 30, replacing a consumable part, performing cleaning, and the like. Therefore, the production line can be prevented from stopping at an unexpected timing.
[ embodiment 3]
Next, as embodiment 3 of the present disclosure, a predictive maintenance determination device 12c shown in fig. 11 will be described. Fig. 11 is an overall configuration diagram of a predictive maintenance determination system using the predictive maintenance determination device according to embodiment 3.
The predictive maintenance determination system 10c detects and notifies the signs of abnormality such as cracks and wear generated in the gear box 30 that drives the extruder 40 by reducing the rotational driving force of the motor 22, and wear of the shaft supporting the gear. The predictive maintenance determination device 12c is provided in the predictive maintenance determination system 10c, and detects and notifies a sign of the occurrence of an abnormality of the equipment. The predicted maintenance determination device 12c has a different predicted maintenance determination method from the predicted maintenance determination devices 12a and 12 b.
[ description of the functional Structure of the predictive maintenance determining apparatus ]
Next, the functional configuration of the predictive maintenance determination device 12c will be described with reference to fig. 12. Fig. 12 is a functional configuration diagram of the predictive maintenance determination device according to embodiment 3. The control unit 13 of the predictive maintenance determination device 12c operates by developing a control program P2 (not shown) in the RAM13c, and realizes the signal acquisition unit 51, the signal analysis unit 52b, the third determination unit 53c, and the notification unit 54 shown in fig. 12 as functional units.
The signal acquisition unit 51 functions in the same manner as the predictive maintenance determination devices 12a and 12b described above. Note that the function of the notification unit 54 is as described in embodiment 1. That is, in the case of the present embodiment, the notification unit 54 notifies the result of the determination by the third determination unit 53 c.
The signal analyzer 52c analyzes the AE output m (t) acquired by the signal acquirer 51, and calculates an evaluation value for determining whether or not a sign of an abnormality is found in the gear box 30.
The signal analyzing section 52c further includes a first differential value calculating section 521, an average value calculating section 522, and a third ratio calculating section 528.
The functions of the first difference value calculation unit 521 and the average value calculation unit 522 are the same as those of the predictive maintenance determination device 12a described above. The third ratio calculator 528 calculates a ratio R3(δ 1/Save: third ratio) which is a ratio of the difference value δ 1 (first difference value) between the maximum value Smax1 and the minimum value Smin1 of the AE outputs m (t) within the predetermined time calculated by the first difference value calculator 521 to the average value Save of the AE outputs m (t) within the predetermined time calculated by the average value calculator 522.
The third determination unit 53c determines the state of the gear box 30 based on the difference value δ 1 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 is described below.
[ description of the determination method of the predictive maintenance determination device ]
Next, a determination method performed by the third determination unit 53c of the predictive maintenance determination device 12c will be described with reference to fig. 13. The inventors set the AE sensors 20 in a plurality of gear boxes 30 in various states, and analyzed a plurality of data (the number of data is about 2000 (sampling frequency is about 100Hz)) acquired during 20 seconds, respectively. As a result of the analysis, a determination method suitable for determining the state of the gear box 30 is created. Fig. 13 is a diagram showing an example of the determination criterion in embodiment 3.
In fig. 13, the difference value δ 1 (first difference value) is taken on the vertical axis, and the third ratio R3(δ 1/Save) is taken on the horizontal axis. The third determination unit 53c determines whether or not there is a possibility of an abnormality occurring in the gear box 30 based on the two-dimensional map 80a formed of the difference value δ 1 and the third ratio R3.
Specifically, when the differential value δ 1 is smaller than the differential value first threshold Td1 and the third ratio R3 is smaller than the ratio first threshold Tr1, that is, when the differential value δ 1 and the third ratio R3 are located inside the region W1 of fig. 13, the third judging section 53c judges that the gear case 30 is normal. At this time, the notification unit 54 does not perform any notification. At this time, the notification unit 54 may notify that the gear box 30 is normal at this time.
Further, when the differential value δ 1 is smaller than the differential value first threshold Td1, and the third ratio R3 is greater than or equal to the ratio first threshold Tr1 and smaller than the ratio second threshold Tr2 that is larger than the ratio first threshold Tr1, that is, when the differential value δ 1 and the third ratio R3 are located inside the region W2 in fig. 13, the third judgment section 53c judges that the gear case 30 is in a low-frequency subsequent observation required state (for example, a state in which subsequent observation is required approximately once a year). Then, the notification unit 54 notifies that the subsequent observation state is required at a low frequency (for example, approximately once a year).
Further, when the differential value δ 1 is equal to or greater than the differential value first threshold Td1, and is smaller than the differential value second threshold Td2 that is greater than the differential value first threshold Td1, and the third ratio R3 is smaller than the ratio second threshold Tr2, that is, when the differential value δ 1 and the third ratio R3 are located inside the region W3 in fig. 13, the third judging section 53c judges that the gear box 30 is in the medium-frequency subsequent observation-needed state. Then, the notification unit 54 notifies that the follow-up observation state is required at a medium frequency (for example, once in about 6 months).
Further, when the differential value δ 1 is equal to or greater than the differential value second threshold Td2, and is smaller than the differential value third threshold Td3 that is greater than the differential value second threshold Td2, and the third ratio R3 is smaller than the ratio second threshold Tr2, that is, when the differential value δ 1 and the third ratio R3 are located inside the region W3 in fig. 13, the third judging section 53c judges that the gear box 30 is in a high-frequency subsequent observation-needed state. Then, the notification unit 54 notifies that follow-up observation is necessary at a high frequency (for example, once in about 3 months).
When the differential value δ 1 is smaller than the differential value second threshold Td2 and the third ratio R3 is the ratio second threshold Tr2, that is, when the differential value δ 1 and the third ratio R3 are located inside the region W5 of fig. 13, the third determination section 53c determines that the gearbox 30 is in the maintenance required state in which the degree of emergency is low. Then, the notification unit 54 notifies that the maintenance is required with a low degree of urgency (for example, a state in which maintenance is recommended within 2 to 3 years).
Further, when the differential value δ 1 is equal to or greater than the differential value second threshold Td2, and is smaller than the differential value third threshold Td3 that is greater than the differential value second threshold Td2, and the third ratio R3 is equal to or greater than the ratio second threshold Tr2, that is, when the differential value δ 1 and the third ratio R3 are located inside the region W6 in fig. 13, the third determination unit 53c determines that the gearbox 30 is in a maintenance required state in which the degree of emergency is moderate. Then, the notification unit 54 notifies that maintenance is required with a moderate degree of urgency (for example, a state in which maintenance is recommended within 1 to 2 years).
When the differential value δ 1 is equal to or greater than the differential value third threshold Td3, that is, when the differential value δ 1 and the third ratio R3 are inside the region W7 in fig. 13, the third determination unit 53c determines that the gear box 30 is in a maintenance-required state in which the degree of emergency is high. Then, the notification unit 54 notifies that the maintenance is required in a high emergency (for example, a state in which maintenance is recommended within 1 year).
Further, a two-dimensional map 80a may be generated with the ratio R1(═ δ 1/δ 2) used in embodiment 1 or the ratio R2(═ δ 1/δ 3) used in embodiment 2 as the horizontal axis and the differential value δ 1 as the vertical axis, and the state of the gear box 30 may be evaluated based on the position of the evaluation value plotted in the two-dimensional map 80 a. That is, as described in embodiment 3, a plurality of threshold values corresponding to the evaluation functions of the vertical axis and the horizontal axis may be set, and the state of the gear box 30 may be evaluated based on the relationship between the measured evaluation value and the threshold value.
In the present 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 may be mounted on faces corresponding to respective axial directions of the gear case 30, and the outputs of the respective AE sensors 20 may be individually evaluated by the two-dimensional map 80a shown in fig. 13. Thus, since each axial state of the gear box 30 can be evaluated by simultaneously measuring a plurality of passages, the position of the gear box 30 where an abnormality occurs can be determined more accurately.
The position where the AE sensor 20 is provided may be varied, for example, on the input shaft side (the motor 22 side), the output shaft side (the extruder 40 side), the intermediate shaft side (the center portion of the gear case 30) of the gear case 30, and the like.
[ description of data processing flow by predictive maintenance determination device ]
Next, the flow of the determination process performed by the signal analysis unit 52c and the third determination unit 53c will be described with reference to fig. 14. 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 embodiment 3.
The signal acquiring unit 51 acquires AE output m (t) for a predetermined time from the storage unit 14 (step S31).
The signal analyzer 52c rearranges the AE outputs m (t) acquired in step S31 in the predetermined time period in descending order (step S32).
The signal analyzer 52c removes the sporadic values from the AE outputs m (t) rearranged in descending order in step S32 (step S33). Specifically, AE outputs M (t) rearranged in descending order are classified, for example, every 100 (0. ltoreq. M (t) <100, 101. ltoreq. M (t) < 200.), and when only two or less data exist in every 100 after classification, the two or less data are removed.
The first differential value calculation section 521 determines the maximum value Smax1 and the minimum value Smin1 of the AE output m (t) (step S34).
The average value calculation unit 522 calculates an average value Save of the AE outputs m (t) for a predetermined time period (step S35).
The first differential value calculating section 521 calculates a first differential value δ 1 between the maximum value Smax1 and the minimum value Smin 1. Then, the third ratio calculation section 528 calculates a third ratio R3(═ δ 1/Save) (step S36).
The third determination unit 53c determines the state of the gear box 30 based on the criteria described with reference to fig. 13 (step S37).
As described above, in the predictive maintenance determination device 12c according to embodiment 3, the first difference value calculation unit 521 acquires the AE output m (t) of the AE sensor 20 provided on the surface of the metal casing 30a (casing) of the gear box 30 (equipment), and calculates the difference value δ 1 (first difference value) between the maximum value Smax1 and the minimum value Smin1 of the AE output m (t) over a predetermined time. The average value calculation unit 522 calculates an average value Save of the AE outputs m (t) for a predetermined time. The third ratio calculation unit 528 calculates a third ratio R3 that is the ratio of the difference value δ 1 (first difference value) to the average value Save. Then, the notification portion 54 notifies that an abnormality may occur in the gearbox 30 based on the differential value δ 1 and the third ratio R3, that is, based on the two-dimensional map 80 a. Therefore, the predicted maintenance determining device 12c notifies the timing when the AE output m (t) smaller than the AE output m (t) generated when the significant abnormality occurs in the gear box 30 is detected, and thus can notify the abnormality before the occurrence of the abnormality affecting the operation of the gear box 30.
The determination method described in embodiment 3, that is, the determination method based on the two-dimensional map 80a in fig. 13 can be applied to embodiment 1 and embodiment 2. By making the determination based on the plurality of determination criteria in this manner, the state of the gear box 30 can be determined in more detail.
[ embodiment 4]
Embodiment 4 of the present disclosure is an example of a predictive maintenance determination device 12d that is provided in a predictive maintenance determination system 10d and that detects and notifies a sign of an abnormality occurring in a device.
First, the overall configuration of a predictive maintenance determination system 10d using the predictive maintenance determination device 12d according to the present embodiment will be described with reference to fig. 15. Fig. 15 is an overall configuration diagram of a predictive maintenance determination system using the predictive maintenance determination device according to embodiment 4.
The predictive maintenance determination system 10d has a structure in which the vibration sensor 70 is added to the structure of the predictive maintenance determination system 2a described with reference to fig. 2. The vibration sensor 70 is disposed on the surface of the metal case 30a of the gear housing 30, and measures the magnitude of the vibration acceleration generated by the gear housing 30. Specifically, the magnitude of the vibration acceleration in the range of several Hz to several tens Hz lower than the frequency range in which the AE sensor 20 performs measurement is detected. In addition, the vibration sensor 70 is one example of the acceleration sensor of the present disclosure, and for example, a piezoelectric acceleration sensor or the like is used.
The predictive maintenance determination system 10d measures the state of the gear box 30, and when the vibration acceleration is larger than a predetermined acceleration, the method for determining the state of the gear box 30 described in embodiment 3 is switched to another determination method. That is, when the magnitude of the vibration acceleration generated in the gear box 30 is larger than the third predetermined value ∈ 3, which is a predetermined acceleration, the predicted maintenance determination system 10d determines the state of the gear box 30 based on a determination criterion different from that in fig. 13. On the other hand, when the magnitude of the vibration acceleration generated in the gear box 30 is equal to or less than the third predetermined value ∈ 3, the state of the gear box 30 is determined based on the criterion shown in fig. 13. According to the evaluation test of the inventors, the third predetermined value ε 3 is preferably 10m/s2Left and right.
Fig. 16 is a functional configuration diagram of a predictive maintenance determination device according to embodiment 4. The control unit 13 of the predictive maintenance determination device 12d develops and operates the control program P3 (not shown) in the RAM13c, and realizes the signal acquisition unit 55, the signal analysis unit 52d, the fourth determination unit 53d, and the notification unit 54 shown in fig. 16 as functional units.
The signal acquisition unit 55 acquires AE output m (t) for a predetermined time from the storage unit 14. Further, the signal acquisition section 55 acquires vibration acceleration from the vibration sensor 70.
In addition to the functions described in embodiment 3, the signal analysis unit 52d includes a vibration acceleration determination unit 520. The vibration acceleration determination unit 520 determines whether or not the vibration acceleration acquired by the vibration sensor 70 is greater than a third predetermined value ∈ 3.
Note that the function of the notification unit 54 is as described in embodiment 1. That is, in the case of the present embodiment, the notification unit 54 notifies the result of the determination by the fourth determination unit 53 d.
The fourth determination unit 53d determines the state of the gear box 30 by a determination method corresponding to the magnitude of the vibration acceleration acquired by the vibration sensor 70. The specific determination method is described later.
When the magnitude of the vibration acceleration generated in the gear box 30 is larger than the third predetermined value ∈ 3, the predicted maintenance determining device 12d determines the state of the gear box 30 based on a determination criterion (two-dimensional map 80b) shown in fig. 17, for example. Fig. 17 is a diagram showing an example of the determination criterion when the vibration acceleration is larger than the third prescribed value ∈ 3.
In fig. 17, the vertical axis represents the differential value δ 1 (first differential value), and the horizontal axis represents the average value Save of the minimum value Smin1 of the AE outputs m (t) or the AE outputs m (t). The fourth determination section 53d determines whether or not an abnormality is likely to occur in the gear box 30 based on the two-dimensional map 80b formed of the differential value δ 1 and the minimum value Smin1 (or the average value Save).
Specifically, when the differential value δ 1 is smaller than the differential value first threshold Td1 and the minimum value Smin1 (or the average value Save) is smaller than the signal output threshold Ts1, that is, when the differential value δ 1 and the minimum value Smin1 (or the average value Save) are located inside the region W11 of fig. 17, the fourth determination section 53d determines that the gear box 30 is in a low-frequency subsequent observation required state (for example, a state in which subsequent observation of around once a year is required). Then, the notification unit 54 notifies that the subsequent observation state is required at a low frequency (for example, approximately once a year).
In addition, when the difference value δ 1 is equal to or greater than the difference value first threshold Td1, is smaller than the difference value second threshold Td2 that is larger than the difference value first threshold Td1, and the minimum value Smin1 (or the average value Save) is smaller than the signal output threshold Ts1, that is, when the difference value δ 1 and the minimum value Smin1 (or the average value Save) are located inside the area W12 in fig. 17, the fourth determination unit 53d determines that the gear box 30 is in the intermediate-frequency subsequent observation-required state. Then, the notification unit 54 notifies that the follow-up observation state is required at a medium frequency (for example, once in about 6 months).
In addition, when the difference value δ 1 is equal to or greater than the difference value second threshold Td2, is smaller than the difference value third threshold Td3, and the minimum value Smin1 (or the average value Save) is smaller than the signal output threshold Ts1, that is, when the difference value δ 1 and the minimum value Smin1 (or the average value Save) are located inside the region W13 in fig. 17, the fourth determination unit 53d determines that the gear box 30 is in a high-frequency subsequent observation-required state. Then, the notification unit 54 notifies that follow-up observation is necessary at a high frequency (for example, once in about 3 months).
In addition, when the difference value δ 1 is smaller than the difference value second threshold Td2 and the minimum value Smin1 (or the average value Save) is equal to or greater than the signal output threshold Ts1, that is, when the difference value δ 1 and the minimum value Smin1 (or the average value Save) are located inside the area W14 in fig. 17, the fourth determination unit 53d determines that the gear box 30 is in the maintenance-required state in which the degree of emergency is low. Then, the notification unit 54 notifies that the maintenance is required with a low degree of urgency (for example, a state in which maintenance is recommended within 2 to 3 years).
In addition, when the differential value δ 1 is equal to or greater than the differential value second threshold Td2, is smaller than the differential value third threshold Td3, and is equal to or greater than the minimum value Smin1 (or the average value Save) and the signal output threshold Ts1, that is, when the differential value δ 1 and the minimum value Smin1 (or the average value Save) are located inside the region W15 in fig. 17, the fourth determination unit 53d determines that the gearbox 30 is in the maintenance required state in which the degree of emergency is moderate. Then, the notification unit 54 notifies that maintenance is required with a moderate degree of urgency (for example, a state in which maintenance is recommended within 1 to 2 years).
When the differential value δ 1 is equal to or greater than the differential value third threshold Td3, that is, when the differential value δ 1 and the minimum value Smin1 (or the average value Save) are inside the region W16 in fig. 17, the fourth determination unit 53d determines that the gear box 30 is in a maintenance-required state with a high degree of urgency. Then, the notification unit 54 notifies that the maintenance is required in a high emergency (for example, a state in which maintenance is recommended within 1 year).
Next, the flow of the determination process performed by the signal analysis unit 52c and the fourth determination unit 53d will be described with reference to fig. 18. Fig. 18 is a flowchart showing an example of the flow of processing performed by the signal analysis unit and the fourth determination unit in embodiment 4.
The signal acquisition unit 55 acquires vibration acceleration from the vibration sensor 70. (step S41).
The signal acquiring unit 55 acquires AE output m (t) for a predetermined time from the storage unit 14 (step S42).
The vibration acceleration determination unit 520 determines whether or not the vibration acceleration is greater than the third predetermined value ∈ 3 (step S43). When it is determined that the vibration acceleration is greater than the third prescribed value ε 3 (step S43: YES), the process proceeds to step S44. On the other hand, when it is determined that the vibration acceleration is not greater than the third prescribed value ε 3 (step S43: NO), the flow 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). Then, the process of fig. 18 is ended.
The fourth determination unit 53d determines the state of the gear box 30 based on the two-dimensional map 80b (step S45). Then, the process of fig. 18 is ended.
As described above, the predicted maintenance determining device 12d according to embodiment 4 acquires the output of the vibration sensor 70 (acceleration sensor) provided on the surface of the gear box 30 (equipment), and when the output of the vibration sensor 70 is greater than the third predetermined value ∈ 3, the notification unit 54 notifies the gear box 30 that an abnormality may occur based on the minimum value or the average value of the outputs of the AE sensors 20 and the difference value δ 1 (first difference value). When the output of the vibration sensor 70 is equal to or less than the third predetermined value, it is notified that there is a possibility of abnormality occurring in the gear box 30 based on the differential value δ 1 (first differential value) and the third ratio R3. Therefore, even when the gear box 30 generates a high vibration acceleration, the predicted maintenance determining device 12d can notify the occurrence of an abnormality that affects the operation of the gear box 30.
[ embodiment 5]
Embodiment 5 of the present disclosure is an example of a predictive maintenance determination device 12e that is provided in a predictive maintenance determination system 10e (see fig. 19) and that detects and notifies a sign of an abnormality occurring in a device.
Fig. 19 is a system block diagram showing an example of the system configuration of the predictive maintenance determination system according to embodiment 5. The predictive maintenance determination system 10e transmits the outputs (outputs amplified by the preamplifiers) of the AE sensors 21a, 21b, … provided in the plurality of gear boxes 31a, 31b, … to the predictive maintenance determination device 12e via the internet 100, and the predictive maintenance determination device 12e determines the states of the gear boxes 31a, 31b, …. The gear boxes 31a and 31b are driven to rotate by motors 23a, 23b, and …, respectively, to drive the extruders 41a, 41b, and …. Further, identification information for determining the gear box provided with each AE sensor is added to the outputs of the AE sensors 21a, 21b, ….
Since the gearboxes 31a, 31b, … and the predictive maintenance determination device 12e are connected via the internet 100, the installation position of the predictive maintenance determination device 12e need not be in the vicinity of the gearboxes 31a, 31b, …, but may be a position remote from the gearboxes 31a, 31b, …. The gearboxes 31a, 31b, and … connected to the predicted maintenance determining device 12e are not limited to those installed in the same factory, and may be those installed in a plurality of factories.
The predicted maintenance determining device 12e has the same configuration as any of the above-described predicted maintenance determining devices 12a to 12 d. The predicted maintenance determining device 12e determines the state of the gear boxes 31a, 31b, and … from the outputs of the AE sensors 21a, 21b, and … by the same determination method as any of the first determining unit 53a, the second determining unit 53b, the third determining unit 53c, and the fourth determining unit 53d described above.
When it is determined that there is an abnormality in the state of the gear boxes 31a, 31b, …, the notification unit 54 included in the predicted maintenance determination device 12e notifies the determination.
Since the identification information for determining the gear box provided with each AE sensor is added to the output of the AE sensors 21a, 21b, …, the gear boxes 31a, 31b, … need not be the same model. That is, the predicted maintenance determining means 12e may include a plurality of determination logics for determining different AE outputs m (t) obtained from gear boxes of different models, and for the AE output m (t) received by the predicted maintenance determining means 12e, the state of the gear box is determined using the determination logic corresponding to the gear box in which the AE output m (t) is detected.
Further, when the predicted maintenance determining device 12e determines that an abnormality has occurred in the gearbox, the determination result may be sent back to the gearbox via the internet 100. The determination result may be notified by a notification device such as an alarm not shown in fig. 19 provided in the gear box.
As described above, the predicted maintenance determination device 12e according to embodiment 5 is connected to the AE sensors 21a and 21b provided on the surfaces of one or more gear boxes 31a and 31b (devices) via the internet 100, and acquires the outputs of the AE sensors 21a and 21 b. Therefore, the abnormality determination of the gear box (equipment) can be performed at a place distant from the gear box (equipment).
Description of the reference symbols
10a, 10b, 10c, 10d, 10e predictive maintenance determination system, 12a, 12b, 12c, 12d, 12e predictive maintenance determination device, 20, 21a, 21b AE sensor, 22 motor, 30, 31a, 31b gear box (device), 40 extruder, 51 signal acquisition unit, 52a, 52b, 52c signal analysis unit, 53a first determination unit, 53b second determination unit, 53c third determination unit, 54 notification unit, 70 vibration sensor (acceleration sensor), 80a, 80b two-dimensional map, 100 internet, 520 vibration acceleration determination unit, 521 first difference value calculation unit, 522 average value calculation unit, 523 second difference value calculation unit, 524 first ratio calculation unit, 525 abnormal value removal unit, 526 third difference value calculation unit, 527 second ratio calculation unit, Save average value, Smax1, Smax2, Smax3 maximum value, Smin1 minimum value, δ 1 differential value (first differential value), δ 2 differential value (second differential value), δ 3 differential value (third differential value), M (t), M1(t), M2(t) AE output, R1 ratio (first ratio), R2 ratio (second ratio), R3 ratio (third ratio), U prescribed ratio, Td1 differential value first threshold, Td2 differential value second threshold, Td3 differential value third threshold, Tr1 ratio first threshold, Tr2 ratio second threshold, Ts1 signal output threshold, epsilon 1 first prescribed value, epsilon 2 second prescribed value, epsilon 3 third prescribed value.

Claims (14)

1. A predictive maintenance determination device, comprising:
a first differential value calculation section that acquires an output of an AE sensor provided on a housing surface of the device and calculates a first differential value between a maximum value and a minimum value of the output for a predetermined time;
an average value calculation unit that calculates an average value of the outputs over the predetermined time;
a second difference value calculation unit that calculates a second difference value between a maximum value and a minimum value of the output smaller than the average value among the outputs for the predetermined time;
a first ratio calculation unit that calculates a first ratio that is a ratio of the first difference value to the second difference value; and
a notification unit that notifies that an abnormality may occur in the device when the first ratio is equal to or greater than a first predetermined value.
2. A predictive maintenance determination device, comprising:
a first differential value calculation section that acquires an output of an AE sensor provided on a housing surface of the device and calculates a first differential value between a maximum value and a minimum value of the output for a predetermined time;
a third difference value calculation unit that calculates a third difference value between a maximum value and a minimum value of an output remaining after the output of the predetermined ratio or more of the maximum value is removed from the outputs within the predetermined time;
a second ratio calculation unit that calculates a second ratio that is a ratio of the first difference value to the third difference value; and
a notification section that notifies that an abnormality may occur in the device when the second ratio is a second predetermined value or more.
3. A predictive maintenance determination device, comprising:
a first differential value calculation section that acquires an output of an AE sensor provided on a housing surface of the device and calculates a first differential value between a maximum value and a minimum value of the output for a predetermined time;
an average value calculation unit that calculates an average value of the outputs over the predetermined time;
a third ratio calculation unit that calculates a third ratio that is a ratio of the first difference value to the average value; and
a notifying section that notifies that an abnormality may occur in the device based on a two-dimensional map obtained by taking the first differential value and the third ratio on each axis.
4. A predictive maintenance determination device, comprising:
a first differential value calculation section that acquires an output of an AE sensor provided on a housing surface of the device and calculates a first differential value between a maximum value and a minimum value of the output for a predetermined time;
an average value calculation unit that calculates an average value of the outputs over the predetermined time;
a second difference value calculation unit that calculates a second difference value between a maximum value and a minimum value of the output smaller than the average value among the outputs for the predetermined time;
a first ratio calculation unit that calculates a first ratio that is a ratio of the first difference value to the second difference value; and
a notifying section that notifies that an abnormality may occur in the device based on a two-dimensional map obtained by taking the first differential value and the first ratio on each axis.
5. A predictive maintenance determination device, comprising:
a first differential value calculation section that acquires an output of an AE sensor provided on a housing surface of the device and calculates a first differential value between a maximum value and a minimum value of the output for a predetermined time;
a third difference value calculation unit that calculates a third difference value between a maximum value and a minimum value of an output remaining after the output of the predetermined ratio or more of the maximum value is removed from the outputs within the predetermined time;
a second ratio calculation unit that calculates a second ratio that is a ratio of the first difference value to the third difference value; and
a notifying section that notifies that an abnormality may occur in the device based on a two-dimensional map obtained by taking the first differential value and the second ratio on each axis.
6. The predictive maintenance decision device of claim 3,
acquiring an output of an acceleration sensor provided on a surface of a casing of the apparatus, and when the output of the acceleration sensor is greater than a third prescribed value,
the notifying section notifies that an abnormality may occur in the equipment based on a two-dimensional map obtained by taking a minimum value or an average value of the output of the AE sensor and the first differential value on each axis,
when the output of the acceleration sensor is equal to or less than the third predetermined value,
notifying that an abnormality may occur in the device based on a two-dimensional map obtained by taking the first differential value and the third ratio on the respective axes.
7. The predictive maintenance determination device according to any one of claims 1 to 6,
the AE sensor provided on the surface of one or more devices is connected via the internet, and the output of the AE sensor is acquired.
8. The predictive maintenance determination device according to any one of claims 1 to 7,
the apparatus is a gearbox driving an extruder.
9. A predictive maintenance decision method, comprising:
a first difference value calculating step of acquiring an output of an AE sensor provided on a surface of a housing of the device and calculating a first difference value between a maximum value and a minimum value of the output within a predetermined time;
an average value calculation step of calculating an average value of the outputs within the predetermined time;
a second difference value calculating step of calculating a second difference value between a maximum value and a minimum value of the outputs smaller than the average value among the outputs for the predetermined time;
a first ratio calculation step of calculating a first ratio which is a ratio of the first differential value to the second differential value; and
a notification step of notifying that an abnormality is likely to occur in the device when the first ratio is a first prescribed value or more.
10. A predictive maintenance decision method, comprising:
a first difference value calculating step of acquiring an output of an AE sensor provided on a surface of a housing of the device and calculating a first difference value between a maximum value and a minimum value of the output within a predetermined time;
a third difference value calculation step of calculating a third difference value between a maximum value and a minimum value of outputs remaining after the output of the predetermined proportion or more of the maximum value is removed from the outputs within the predetermined time;
a second ratio calculating step of calculating a second ratio which is a ratio of the first difference value to the third difference value; and
a notification step of notifying that an abnormality may occur in the apparatus when the second ratio is a second prescribed value or more.
11. A predictive maintenance decision method, comprising:
a first difference value calculating step of acquiring an output of an AE sensor provided on a surface of a housing of the device and calculating a first difference value between a maximum value and a minimum value of the output within a predetermined time;
an average value calculation step of calculating an average value of the outputs within the predetermined time;
a third ratio calculating step of calculating a third ratio which is a ratio of the first differential value to the average value; and
a notifying step of notifying that an abnormality may occur in the device based on a two-dimensional map obtained by taking the first differential value and the third ratio on each axis.
12. A program, characterized in that,
a computer that controls a predicted maintenance determination device for acquiring an output of an AE sensor provided on a housing surface of an apparatus is caused to function as:
a first difference value calculation unit that calculates a first difference value between a maximum value and a minimum value of the output within a predetermined time;
an average value calculation unit that calculates an average value of the outputs over the predetermined time;
a second difference value calculation unit that calculates a second difference value between a maximum value and a minimum value of the output smaller than the average value among the outputs for the predetermined time;
a first ratio calculation unit that calculates a first ratio that is a ratio of the first difference value to the second difference value; and
a notification unit that notifies that an abnormality may occur in the device when the first ratio is equal to or greater than a first predetermined value.
13. A program, characterized in that,
a computer that controls a predicted maintenance determination device for acquiring an output of an AE sensor provided on a housing surface of an apparatus is caused to function as:
a first difference value calculation unit that calculates a first difference value between a maximum value and a minimum value of the output within a predetermined time;
a third difference value calculation unit that calculates a third difference value between a maximum value and a minimum value of an output remaining after the output of the predetermined ratio or more of the maximum value is removed from the outputs within the predetermined time;
a second ratio calculation unit that calculates a second ratio that is a ratio of the first difference value to the third difference value; and
a notification section that notifies that an abnormality may occur in the device when the second ratio is a second predetermined value or more.
14. A program, characterized in that,
a computer that controls a predicted maintenance determination device for acquiring an output of an AE sensor provided on a housing surface of an apparatus is caused to function as:
a first differential value calculation section that acquires an output of an AE sensor provided on a housing surface of the device and calculates a first differential value between a maximum value and a minimum value of the output for a predetermined time;
an average value calculation unit that calculates an average value of the outputs over the predetermined time;
a third ratio calculation unit that calculates a third ratio that is a ratio of the first difference value to the average value; and
a notifying section that notifies that an abnormality may occur in the device based on a two-dimensional map obtained by taking the first differential value and the third ratio on each axis.
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Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH07270228A (en) * 1994-03-29 1995-10-20 Kawasaki Steel Corp Anomaly diagnosis method for low speed rotary machine
JP2001304954A (en) * 2000-04-20 2001-10-31 Rion Co Ltd Fault diagnosis method and device
CN1906473A (en) * 2004-09-13 2007-01-31 日本精工株式会社 Abnormality diagnosis device and abnormality diagnosis method
JP2007192828A (en) * 2003-07-29 2007-08-02 Nsk Ltd Abnormality diagnostic device, rolling bearing system having this, and method of diagnosing abnormality
CN101782468A (en) * 2009-01-16 2010-07-21 日立电线株式会社 Abnormality detection method and abnormality detection system for operating body
JP2010230606A (en) * 2009-03-30 2010-10-14 Nidec Sankyo Corp Device and method for inspection of abnormal noise
CN106334726A (en) * 2015-07-07 2017-01-18 日本电产新宝株式会社 Die abnormality prediction system, press machine provided with the same, and die abnormality prediction method
CN108139367A (en) * 2015-10-28 2018-06-08 株式会社神户制钢所 The abnormal detector of whirler, the method for detecting abnormality of whirler and whirler
CN109900475A (en) * 2017-12-08 2019-06-18 株式会社日立大厦系统 Bearing check device

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH066955B2 (en) * 1985-09-28 1994-01-26 ダイキン工業株式会社 Operation inspection device for rotary compressor
JP3543026B2 (en) * 1995-03-24 2004-07-14 松下冷機株式会社 Diagnosis device for mechanical sliding parts
JP2001324417A (en) * 2000-05-15 2001-11-22 Non-Destructive Inspection Co Ltd Method and device for evaluating damage in bearing
JP2009042151A (en) 2007-08-10 2009-02-26 Jtekt Corp Defect detecting device and electric power steering device
KR101302519B1 (en) * 2012-07-05 2013-09-02 주식회사 포스코 Method for detecting abnormality of facilities by using probability density of vibration
TWI583936B (en) * 2016-06-24 2017-05-21 國立中山大學 Method of detecting precision machine status

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH07270228A (en) * 1994-03-29 1995-10-20 Kawasaki Steel Corp Anomaly diagnosis method for low speed rotary machine
JP2001304954A (en) * 2000-04-20 2001-10-31 Rion Co Ltd Fault diagnosis method and device
JP2007192828A (en) * 2003-07-29 2007-08-02 Nsk Ltd Abnormality diagnostic device, rolling bearing system having this, and method of diagnosing abnormality
CN1906473A (en) * 2004-09-13 2007-01-31 日本精工株式会社 Abnormality diagnosis device and abnormality diagnosis method
CN101782468A (en) * 2009-01-16 2010-07-21 日立电线株式会社 Abnormality detection method and abnormality detection system for operating body
JP2010230606A (en) * 2009-03-30 2010-10-14 Nidec Sankyo Corp Device and method for inspection of abnormal noise
CN106334726A (en) * 2015-07-07 2017-01-18 日本电产新宝株式会社 Die abnormality prediction system, press machine provided with the same, and die abnormality prediction method
CN108139367A (en) * 2015-10-28 2018-06-08 株式会社神户制钢所 The abnormal detector of whirler, the method for detecting abnormality of whirler and whirler
CN109900475A (en) * 2017-12-08 2019-06-18 株式会社日立大厦系统 Bearing check device

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