JP6841178B2 - Abnormality judgment device and abnormality judgment method - Google Patents

Description

The present invention relates to an abnormality determination device and an abnormality determination method for determining an abnormality in a robot speed reducer.

An abnormality determining device for determining an abnormality of a speed reducer from a command current value or rotation information of a motor with a speed reducer is known (for example, Patent Documents 1 to 5).

Japanese Unexamined Patent Publication No. 2012-194035 Japanese Unexamined Patent Publication No. 2006-102889 Japanese Unexamined Patent Publication No. 02-088938 JP-A-2009-226488 Japanese Unexamined Patent Publication No. 2012-008030

In the abnormality determination device shown in Patent Documents 1 to 4, the abnormality can be determined, but the cause of the abnormality cannot be individually identified. Further, in the abnormality determination device shown in Patent Document 5, an abnormality determination in an abnormality mode such as a bearing failure is performed using a vibration waveform to identify the cause of the abnormality. However, the vibration waveform is easily affected by disturbance, and it may be difficult to accurately determine the abnormality.

The present invention has been made to solve such a problem, and provides an abnormality determination device and an abnormality determination method capable of identifying an abnormality cause while accurately determining an abnormality of a speed reducer. The main purpose is to do.

One aspect of the present invention for achieving the above object is
It is an abnormality determination device that determines the abnormality of the speed reducer installed in the robot.
An operation data acquisition means for acquiring a plurality of operation data during operation of the speed reducer, and
The correlation coefficient between the past operation data in the abnormality mode indicating the abnormality form of the speed reducer and the current operation data acquired by the operation data acquisition means is calculated for each abnormality mode, and the correlation coefficient is calculated. An evaluation value calculation means for calculating an evaluation value for each abnormal mode by multiplying the calculated correlation coefficient and the current operation data and adding the multiplication result.
A storage means for storing the threshold value for each abnormal mode and
By comparing the threshold value of each abnormality mode stored by the storage means with the corresponding evaluation value calculated by the evaluation value calculation means, the abnormality of the speed reducer is determined for each abnormality mode. An abnormality determining means for identifying the cause of the abnormality, and
It is an abnormality determination device characterized by being equipped with.
In this aspect, the abnormal mode is an abnormal mode due to foreign matter biting in a gear in the speed reducer, an abnormal mode due to coolant intrusion in the speed reducer, an abnormal mode due to a bearing failure in the speed reducer, and a lubricating oil in the speed reducer. It may include at least one of an abnormal mode due to deterioration of the gear and an abnormal mode due to wear of the gear in the speed reducer.
In this aspect, the operation data includes an average value of command current values for a motor driving the speed reducer, a maximum value of the command current value, an amplitude of the command current value, a rotation speed of the motor, and the motor. It may include at least one of the rotation angles of.
One aspect of the present invention for achieving the above object is
This is an abnormality determination method for determining an abnormality in the speed reducer provided in the robot.
A step of acquiring a plurality of operation data during the operation of the speed reducer, and
A correlation coefficient between the past operation data in the abnormality mode indicating the abnormality form of the speed reducer and the acquired current operation data is calculated for each abnormality mode, and the calculated correlation coefficient is used. A step of calculating an evaluation value for each abnormal mode by multiplying the current operation data and adding the multiplication result.
By comparing the threshold value set for each abnormality mode with the calculated corresponding evaluation value, the abnormality of the speed reducer is determined for each abnormality mode, and the cause of the abnormality is identified. Steps and
It may be an abnormality determination method characterized by including.

According to the present invention, it is possible to provide an abnormality determination device and an abnormality determination method capable of identifying an abnormality cause while determining an abnormality of a speed reducer with high accuracy.

It is a block diagram which shows the schematic system configuration of the robot which concerns on one Embodiment of this invention. It is a block diagram which shows the schematic system configuration of the abnormality determination apparatus which concerns on one Embodiment of this invention. It is a figure which shows an example of the correlation coefficient of each operation data for each abnormal mode. It is a flowchart which shows the flow of the abnormality determination method by the abnormality determination apparatus which concerns on one Embodiment of this invention.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
FIG. 1 is a block diagram showing a schematic system configuration of a robot according to an embodiment of the present invention. The abnormality determination device 1 according to the present embodiment is mounted on, for example, a robot 10. The abnormality determination device 1 determines an abnormality of the speed reducer 11 provided in the robot 10.

The speed reducer 11 is provided, for example, in each joint portion (shoulder joint, wrist joint, knee joint, ankle joint, etc.) 12 of the robot 10. A motor 13 is connected to the joint portion 12 via a speed reducer 11. The motor 13 rotationally drives the joint portion 12 via the speed reducer 11. The motor 13 is provided with a rotation sensor 14 that detects rotation information of the motor 13. The rotation information includes, for example, the rotation angle, rotation speed, rotation acceleration, rotation speed, and the like of the motor 13. The rotation sensor 14 is composed of, for example, an encoder or a potentiometer.

The motor 13 and the rotation sensor 14 are connected to the control device 15. The control device 15 feedback-controls the motor 13 based on the rotation information detected by the rotation sensor 14, for example. The control device 15 outputs a command current value for controlling the motor 13 to the motor 13. The motor 13 rotationally drives the joint portion 12 via the speed reducer 11 in response to the command current value from the control device 15.

By the way, although the conventional abnormality determination device can perform abnormality determination, there has been a problem that the cause of the abnormality cannot be individually identified. Further, even if the cause of the abnormality can be identified, it may be difficult to accurately determine the abnormality due to the influence of disturbance or the like.

On the other hand, the abnormality determination device 1 according to the present embodiment can identify the cause of the abnormality while determining the abnormality of the speed reducer 11 with high accuracy. The abnormality determination device 1 determines an abnormality of the speed reducer 11 provided in the robot 10 based on the command current value from the control device 15 of the robot 10 and / or the rotation information from the rotation sensor 14.

FIG. 2 is a block diagram showing a schematic system configuration of the abnormality determination device according to the present embodiment. The abnormality determination device 1 according to the present embodiment includes an operation data acquisition unit 2 that acquires a plurality of operation data during operation of the speed reducer 11, and past operation data in an abnormality mode indicating an abnormality form of the speed reducer 11. , The correlation coefficient of the current operation data acquired by the operation data acquisition unit 2 is calculated for each abnormal mode, the calculated correlation coefficient is multiplied by the current operation data, and the multiplication result is added. Therefore, the evaluation value calculation unit 3 that calculates the evaluation value for each abnormal mode, the storage unit 4 that stores the threshold value of each abnormal mode, the threshold value of each abnormal mode stored by the storage unit 4, and the evaluation value calculation unit. It is provided with an abnormality determination unit 5 for determining an abnormality of the speed reducer 11 for each abnormality mode and identifying the cause of the abnormality by comparing the corresponding evaluation values calculated in 3 with each other.

As described above, in the abnormality determination device according to the present embodiment, the correlation coefficient between the past operation data and the current operation data in the abnormality mode is calculated, and the calculated correlation coefficient is multiplied by the current operation data. Then, the multiplication result is added to calculate the evaluation value. By comparing the evaluation value reflecting the past operation data in this actual abnormal mode with the threshold value set according to each abnormal mode, the speed reducer 11 is abnormal without being affected by disturbance or the like. Can be judged with high accuracy. Further, the cause of the abnormality can be identified by determining the abnormality of the speed reducer 11 for each abnormality mode. That is, it is possible to identify the cause of the abnormality while determining the abnormality of the speed reducer 11 with high accuracy.

The abnormality determination device 1 includes, for example, a CPU (Central Processing Unit) 1a that performs arithmetic processing and the like, and a ROM (Read Only Memory) and a RAM (Random Access Memory) that store arithmetic programs and the like executed by the CPU. The hardware is configured around a microcomputer including a memory 1b, an interface unit (I / F) 1c that inputs and outputs signals to and from the outside, and the like. The CPU 1a, the memory 1b, and the interface unit 1c are connected to each other via a data bus or the like.

The operation data acquisition unit 2 is a specific example of the operation data acquisition means. The operation data acquisition unit 2 acquires a plurality of operation data at the time of operation of the speed reducer 11 based on the command current value from the control device 15 and the rotation information from the rotation sensor 14. The operation data includes, for example, the average value of the command current value, the maximum value of the command current value, the amplitude of the command current value, the standard deviation of the command current value, the rotation speed of the motor 13, the rotation angle of the motor 13, and the like.

The operation data acquisition unit 2 calculates, for example, the average value, the maximum value, the amplitude, the standard deviation, and the like of the command current values based on the command current values output from the control device 15. Alternatively, the operation data acquisition unit 2 calculates, for example, the rotation speed, the rotation angle, and the like of the motor 13 based on the rotation information output from the rotation sensor 14.

The evaluation value calculation unit 3 is a specific example of the evaluation value calculation means. The evaluation value calculation unit 3 has correlation coefficients α, β, and γ of the past operation data in the abnormality mode indicating the abnormal form of the speed reducer 11 and the current operation data acquired by the operation data acquisition unit 2. , ... are calculated for each abnormal mode.

The abnormal modes include, for example, an abnormal mode due to foreign matter biting in the gear in the speed reducer 11 (hereinafter, gear biting mode), an abnormal mode due to the intrusion of coolant (cooling water) in the speed reducer 11 (hereinafter, coolant intrusion mode). Abnormal mode due to bearing failure in the reducer 11 (hereinafter, bearing failure mode), abnormal mode due to deterioration of lubricating oil (hereinafter, grease, etc.) in the reducer 11 (hereinafter, lubricating oil deterioration mode), gear in the reducer 11 Includes abnormal mode due to wear (hereinafter referred to as gear wear mode), etc.

The past operation data in each of the above-mentioned abnormal modes is, for example, each operation data (mean value, maximum value of command current value, which is acquired by the operation data acquisition unit 2 until a failure of each abnormal mode occurs. Amplitude, standard deviation, etc.). The past operation data in each abnormal mode is stored in the storage unit 4 or the like. The storage unit 4 is composed of, for example, the memory 1b or the like. The past operation data in each abnormal mode may be stored in the failure record data storage unit of the cloud or the server.

The evaluation value calculation unit 3 calculates the correlation coefficient of the average value of the command current values by using, for example, the following formula.

In the above equation, n is the number of data, x _n is the past command current value in _{each abnormal mode, and x n} − is the average value of the past command current values in each abnormal mode. Incidentally, x n _-, in the above-mentioned formula, which has given the upper bar to x _n, hereinafter referred to similarly for the other parameters. y _n is the current command current value acquired by the operation data acquisition unit 2, and y _n- is the average value of the current command current values acquired by the operation data acquisition unit 2. The evaluation value calculation unit 3 may similarly calculate the correlation coefficient of other operation data.

FIG. 3 is a diagram showing an example of the correlation coefficient of each operation data (mean value, maximum value, amplitude, standard deviation of command current value) for each abnormal mode (bearing failure mode, gear wear mode, lubricating oil deterioration mode). Is.

The evaluation value calculation unit 3 multiplies the calculated correlation coefficients α _m , β _m , γ _m , ... Of each abnormal mode by the corresponding current operation data acquired by the operation data acquisition unit 2, respectively. and, by adding the multiplication results to calculate an evaluation value U _m of the abnormality each mode.

_{For example, the evaluation value calculation unit 3 has the correlation coefficients α m} , β _m , γ _m , ... In each abnormality mode m (m = 1, 2, 3, ...), And the operation data acquisition unit 2. obtained current operating data by (mean value I _m of the command current value -, the rotation speed V _m of the motor _13, the maximum value I _pn command current _value, ...) and, to a respective multiplier, the multiplication result by adding, to calculate the evaluation value U _m of each abnormal mode.
Evaluation value of abnormal mode m U _m = α _{m Im-} + β _m V _m + γ _m I _pm ...

As described above, the correlation coefficient between the past operation data in the abnormal mode that actually occurred and the current operation data is calculated, the calculated correlation coefficient is multiplied by the current operation data, and the multiplication is performed. The evaluation value is calculated by adding the results. As a result, it is possible to calculate an evaluation value that accurately indicates the abnormal state of the speed reducer, which is not easily affected by disturbance or the like.

The operation data _{(I m -, V m,} I pm ···) by increasing the number of, by calculating an evaluation value, it only becomes stronger correlation with abnormalities in the abnormal mode, the accuracy of the evaluation value On the other hand, the calculation load increases. Therefore, in the present embodiment, it is preferable to set the operation data as the mean value, the maximum value, the amplitude, and the standard deviation of the command current values in consideration of the accuracy of the evaluation value and the calculation load. However, the operation data is not limited to this, and can be arbitrarily set according to the abnormal mode for determining.

The abnormality determination unit 5 is a specific example of the abnormality determination means. The abnormality determination unit 5 determines the abnormality of the speed reducer 11 for each abnormality mode by comparing the threshold value of each abnormality mode with the corresponding evaluation value calculated by the evaluation value calculation unit 3, respectively, and determines the abnormality of the speed reducer 11 for each abnormality mode. Identify the cause of.

The threshold value of each abnormal mode is stored in the storage unit 4 in advance. The storage unit 4 is a specific example of the storage means. The threshold value of each abnormal mode is set in advance by experimentally obtaining the value of each evaluation value when an abnormality of each abnormal mode (gear biting, coolant intrusion, grease deterioration, etc.) occurs. The threshold value of each abnormal mode stored in the storage unit 4 is configured so that the user can appropriately change the setting.

The abnormality determination unit 5 may determine the abnormality including the sign of the abnormality of the speed reducer 11 for each abnormality mode. The sign of this abnormality refers to, for example, a state in which the speed reducer 11 cannot be said to be abnormal at this time, but the abnormality occurs after several hours or several cycles of driving. In this case, the threshold value of each abnormal mode may be set by experimentally obtaining the value of each evaluation value when a sign of abnormality of each abnormal mode occurs in advance, for example.

When each evaluation value calculated by the evaluation value calculation unit 3 becomes equal to or higher than the threshold value of the corresponding abnormality mode, the abnormality determination unit 5 determines that the abnormality mode is abnormal. Then, the abnormality determination unit 5 identifies the determined abnormality in the abnormality mode as the cause of the abnormality in the speed reducer 11.

For example, the abnormality determining unit 5, the evaluation value U ₁ of the evaluation value calculation unit 3 gear biting mode is calculated by m = 1 is, when it becomes the corresponding abnormal mode threshold U _set1 or more, abnormal inclusive gear mesh Is determined. Then, the abnormality determination unit 5 identifies the determined abnormality of the gear engagement as the cause of the abnormality of the speed reducer 11.

_{Similarly, when the evaluation value U 2 of} the coolant intrusion mode m = 2 calculated by the evaluation value calculation unit 3 _{becomes equal to} or higher than the threshold value U set 2 of the corresponding abnormality mode, the abnormality determination unit 5 determines that the coolant intrusion is abnormal. judge. Then, the abnormality determination unit 5 identifies the determined abnormality of the coolant intrusion as the cause of the abnormality of the speed reducer 11.

As described above, by comparing the highly accurate evaluation value reflecting the past operation data in each abnormal mode with the threshold value set according to each abnormal mode, the evaluation value is not affected by disturbance or the like. The abnormality of the speed reducer 11 can be determined with high accuracy. Further, the cause of the abnormality can be identified by determining the abnormality of the speed reducer 11 for each abnormality mode. For example, the user can take an immediate and appropriate response to the identified cause of abnormality of the speed reducer 11.

The abnormality determination unit 5 may notify the user of the abnormality determination result and the abnormality cause in each abnormality mode by using the notification device 6 or the like. The notification device 6 includes, for example, a display device that displays a determination result, an abnormality cause, and the like, a light device that notifies the fact, a speaker, a communication device that remotely notifies a third party, and the like. Further, the abnormality determination unit 5 may display the display device instructing the replacement of the speed reducer 11 according to the abnormality determination result in each abnormality mode.

FIG. 4 is a flowchart showing a flow of an abnormality determination method by the abnormality determination device according to the present embodiment.

The operation data acquisition unit 2 has an average value, a maximum value, an amplitude, a standard deviation, a rotation speed of the motor 13, and an angle of rotation of the command current value based on the command current value from the control device 15 and the rotation information from the rotation sensor 14. Etc. Acquire the current operation data (step S101).

The evaluation value calculation unit 3 is a phase of the past operation data in the abnormality mode indicating the abnormal form of the speed reducer 11 stored in the storage unit 4 and the current operation data acquired by the operation data acquisition unit 2. The number of relationships is calculated for each abnormal mode (step S102).

The evaluation value calculation unit 3 multiplies the calculated correlation coefficient of each abnormal mode by the corresponding current operation data acquired by the operation data acquisition unit 2, and adds the multiplication result to obtain the abnormal mode. The evaluation value for each is calculated (step S103).

The abnormality determination unit 5 determines the abnormality of the speed reducer 11 for each abnormality mode by comparing the threshold value of each abnormality mode with the corresponding evaluation value calculated by the evaluation value calculation unit 3, respectively, and determines the abnormality of the speed reducer 11 for each abnormality mode. (Step S104).

The abnormality determination unit 5 notifies the user of the abnormality determination result and the abnormality cause in each abnormality mode by using the notification device 6 or the like (step S105).

As described above, the abnormality determination device 1 according to the present embodiment has the operation data acquisition unit 2 for acquiring a plurality of operation data during the operation of the speed reducer 11 and the past operation in the abnormality mode indicating the abnormality form of the speed reducer 11. The correlation coefficient between the data and the current operation data acquired by the operation data acquisition unit 2 is calculated for each abnormal mode, the calculated correlation coefficient is multiplied by the current operation data, and the multiplication result is obtained. The evaluation value calculation unit 3 that calculates the evaluation value for each abnormal mode by adding, the storage unit 4 that stores the threshold value of each abnormal mode, the threshold value of each abnormal mode stored by the storage unit 4, and the evaluation value. By comparing the corresponding evaluation values calculated by the calculation unit 3 with each other, the abnormality determination unit 5 for determining the abnormality of the speed reducer 11 for each abnormality mode and identifying the cause of the abnormality is provided. ..

As a result, by comparing the evaluation value reflecting the past operation data in each abnormal mode with the threshold value set according to each abnormal mode, the speed reducer 11 is abnormal without being affected by disturbance or the like. Can be judged with high accuracy. Further, the cause of the abnormality can be identified by determining the abnormality of the speed reducer 11 for each abnormality mode. That is, it is possible to identify the cause of the abnormality while determining the abnormality of the speed reducer 11 with high accuracy.

Although some embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other embodiments, and various omissions, replacements, and changes can be made without departing from the gist of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and are also included in the scope of the invention described in the claims and the equivalent scope thereof.

The present invention can also be realized, for example, by causing the CPU 1a to execute a computer program for the process shown in FIG.

Programs can be stored and supplied to a computer using various types of non-transitory computer readable media. Non-transitory computer-readable media include various types of tangible storage media. Examples of non-temporary computer-readable media include magnetic recording media (eg, flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (eg, magneto-optical disks), CD-ROMs (Read Only Memory), CD-Rs, It includes a CD-R / W and a semiconductor memory (for example, a mask ROM, a PROM (Programmable ROM), an EPROM (Erasable PROM), a flash ROM, and a RAM (random access memory)).

The program may be supplied to the computer by various types of transient computer readable media. Examples of temporary computer-readable media include electrical, optical, and electromagnetic waves. The temporary computer-readable medium can supply the program to the computer via a wired communication path such as an electric wire and an optical fiber, or a wireless communication path.

1 Abnormality judgment device, 2 Operation data acquisition unit, 3 Evaluation value calculation unit, 3 Evaluation value calculation unit, 4 Storage unit, 5 Abnormality judgment unit, 6 Notification device, 10 Robot, 11 Reducer, 12 Joint part, 13 Motor, 14 rotation sensor, 15 control device

Claims (4)

It is an abnormality determination device that determines the abnormality of the speed reducer installed in the robot.
An operation data acquisition means for acquiring a plurality of operation data during operation of the speed reducer, and
The correlation coefficient between the past operation data in the abnormality mode indicating the abnormality form of the speed reducer and the current operation data acquired by the operation data acquisition means is calculated for each abnormality mode, and the correlation coefficient is calculated. An evaluation value calculation means for calculating an evaluation value for each abnormal mode by multiplying the calculated correlation coefficient and the current operation data and adding the multiplication result.
A storage means for storing the threshold value for each abnormal mode and
By comparing the threshold value of each abnormality mode stored by the storage means with the corresponding evaluation value calculated by the evaluation value calculation means, the abnormality of the speed reducer is determined for each abnormality mode. An abnormality determining means for identifying the cause of the abnormality, and
An abnormality determination device comprising. The abnormality determination device according to claim 1.
The abnormal mode is
Abnormal mode due to foreign matter biting in the gear in the speed reducer, abnormal mode due to coolant intrusion in the speed reducer, abnormal mode due to bearing failure in the speed reducer, abnormal mode due to deterioration of lubricating oil in the speed reducer, and deceleration. Including at least one of the abnormal modes due to wear of the gears in the aircraft,
An abnormality determination device characterized in that. The abnormality determination device according to claim 1 or 2.
The operation data includes the average value of the command current values for the motor driving the speed reducer, the maximum value of the command current value, the amplitude of the command current value, the rotation speed of the motor, and the rotation angle of the motor. Including at least one of them,
An abnormality determination device characterized in that. This is an abnormality determination method for determining an abnormality in the speed reducer provided in the robot.
A step of acquiring a plurality of operation data during the operation of the speed reducer, and
The correlation coefficient between the past operation data in the abnormality mode indicating the abnormality form of the speed reducer and the acquired current operation data is calculated for each abnormality mode, and the calculated correlation coefficient is used. A step of calculating an evaluation value for each abnormal mode by multiplying the current operation data and adding the multiplication result.
By comparing the threshold value set for each abnormality mode with the calculated corresponding evaluation value, the abnormality of the speed reducer is determined for each abnormality mode, and the cause of the abnormality is identified. Steps and
An abnormality determination method comprising.

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