JP2019185415A - Abnormality determination device and abnormality determination method - Google Patents

Abstract

To provide an abnormality determination device and abnormality determination method capable of preventing erroneous detection of an abnormality determination that occurs when operation is started after a production facility has been stopped for a prolonged period.SOLUTION: An abnormality of a production robot 40 provided with a speed reducer 44 is determined based on a torque value detected by a sensor 43 and a preset threshold value. When an operation stop time of the speed reducer 44 is acquired and said operation stop time exceeds a first prescribed time, a process of removing spikes from only a spike exclusion time is performed after the speed reducer 44 starts operating following the elapse of the operation stop time. Sudden spikes at the start of operation can be suppressed, and erroneous reports can be prevented, as the spikes generated in the speed reducer torque value are removed during the spike exclusion time.SELECTED DRAWING: Figure 2

Description

  The present invention relates to an abnormality determination device and an abnormality determination method for early detecting an abnormality that occurs in a movable mechanism such as a speed reducer.

In a production facility equipped with a movable mechanism such as a speed reducer, in order to prevent a long-term production stoppage due to the occurrence of a sudden failure, it is possible to quickly detect and notify the user when an abnormality occurs in the movable mechanism. It has been broken. However, when production equipment (for example, a robot) is stopped for a long time and the operation is started, the disturbance torque generated in the motor mounted on the movable mechanism may become excessive for a while and an abnormality occurs. Even though it is not, abnormalities may be detected.
Patent Document 1 discloses that erroneous detection is prevented by not performing abnormality detection processing at the time of motor operation stop, immediately before stop, immediately after start, and at low speed operation.

JP 2007-219991 A

However, Patent Document 1 does not show countermeasures against erroneous detection of abnormalities that occur after the production facility has been stopped for a long time.
The present invention has been made to solve such a conventional problem, and its purpose is to prevent erroneous detection of an abnormality that occurs when the production facility is started after being stopped for a long time. An object of the present invention is to provide an abnormality determination device and an abnormality determination method that can be performed.

  In order to achieve the above object, the present invention acquires an operation stop time that is a time during which the movable mechanism stops operating, and when the operation stop time exceeds a first predetermined time, the operation stop time has elapsed. Later, at least one of the sensor data and the threshold value acquired from the sensor is corrected for a second predetermined time after the movable mechanism starts operating.

  ADVANTAGE OF THE INVENTION According to this invention, it becomes possible to prevent the misdetection of the abnormality which arises when a production facility is stopped for a long time and it starts operation.

FIG. 1 is a diagram illustrating a configuration of an abnormality determination device and peripheral devices according to the first embodiment of the present invention. FIG. 2 is a block diagram in which the detailed configuration of the production robot shown in FIG. 1 and the functions of the CPU are configured by hardware. FIG. 3 is a flowchart showing a processing procedure of the abnormality determination device according to the first embodiment of the present invention. FIG. 4 is a graph showing changes in the rate of change of the disturbance torque over time. FIG. 5 is a graph showing a change in torque value over time and spike exclusion time. FIG. 6 is a correspondence table showing the relationship between the reduction gear stop time and ambient temperature, and spike exclusion time. FIG. 7A is a graph showing a change in the rate of change of disturbance torque over time, and FIG. 7B is a graph showing a temperature change, showing an example when the temperature is high. FIG. 8A is a graph showing a change in the rate of change of disturbance torque over time, and FIG. 8B is a graph showing a temperature change, showing an example when the temperature is low. FIG. 9 is a diagram showing the configuration of the abnormality determination device and its peripheral devices according to the second embodiment of the present invention. FIG. 10 is a block diagram in which the detailed configuration of the production robot shown in FIG. 9 and the functions of the CPU are configured by hardware. FIG. 11 is a flowchart showing a processing procedure of the abnormality determination device according to the third embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
[Description of Configuration of First Embodiment]
With reference to FIG. 1 and FIG. 2, the abnormality determination apparatus 101 which concerns on 1st Embodiment is demonstrated. As shown in FIG. 1, the abnormality determination apparatus 101 according to the first embodiment is connected to a production robot 40 (equipment having a movable mechanism) and a user interface 50 (denoted as “UI” in the drawing).

  The abnormality determination device 101 can be configured by, for example, an integrated computer, and includes a CPU 15 that executes arithmetic processing, a memory 16 that stores various data and computer programs, and various databases. The database (DB) includes an operation history DB 11, a temperature DB 12, and a sensor DB 13.

The production robot 40 includes, for example, a plurality of speed reducers 44 (movable mechanisms), and is a robot that automatically performs a welding operation of a vehicle body.
The user interface 50 includes an operation unit that performs various input operations by the user, and a display such as a monitor or a tablet that presents various data to the user.

  In the abnormality determination apparatus 101, information processing calculation is executed by the CPU 15 executing control based on the computer program and various data stored in the memory 16. Therefore, the functions of the communication circuit 21, the arithmetic circuit 22, the abnormality determination circuit 23, and the alarm circuit 24 can be executed as shown in FIG. The “abnormality” in the present invention is a concept that includes various factors that hinder the normal operation and malfunction of the movable mechanism, such as operation stop of the movable mechanism, malfunction of the movable mechanism, and deterioration of lubricating oil. .

Next, functions of the production robot 40, the user interface 50, and the abnormality determination device 101 will be described with reference to FIG.
As shown in FIG. 2, the production robot 40 includes a speed reducer 44 that operates with a motor, a sensor 43 provided in the speed reducer 44, a measurement circuit 42, and a communication circuit 41.

  The sensor 43 detects a torque value generated in a motor provided in the speed reducer 44. For example, when a plurality of reduction gears 44 are mounted on the production robot 40, the torque value of the motor installed in each reduction gear 44 is detected. The detected torque value is transmitted to the abnormality determination device 101. In the present embodiment, a speed reducer will be described as an example of the movable mechanism, but the present invention is not limited to this.

The measurement circuit 42 calculates the difference between the torque value detected by the sensor 43 and the control value of the speed reducer 44. For example, the difference between the torque value of the motor of the reduction gear 44 and the control value of the motor (this is referred to as “disturbance torque”) is calculated. Further, the measurement circuit 42 acquires operation data of the speed reducer 44 based on the torque value detected by the sensor 43. The operation data includes various data related to the operation such as the operation date of the speed reducer 44, the time when the operation was started, the time when the operation was stopped, the time when the operation was continuously performed, and the time when the operation was continuously stopped. Further, the operation data includes data related to the operation of the plurality of reduction gears 44 included in the production robot 40, data related to the stop position of the motor, and the like.
Furthermore, the measurement circuit 42 acquires the ambient temperature such as the environmental temperature of the facility where the speed reducer 44 is installed or the temperature inside the speed reducer 44. In addition, when the reduction gear 44 is maintained (repair, replacement, lubricating oil renewal, etc.) by the production robot 40, the measurement circuit 42 acquires maintenance data indicating that this maintenance has been performed. .

  The communication circuit 41 transmits the disturbance torque calculated by the measurement circuit 42, the operation data acquired by the measurement circuit 42, the ambient temperature, maintenance data, and the torque value detected by the sensor 43 to the abnormality determination device 101. .

  As shown in FIG. 2, the abnormality determination device 101 includes a communication circuit 21, an arithmetic circuit 22, an abnormality determination circuit 23, and an alarm circuit 24. Further, as shown in FIG. 1, the functions of the communication circuit 21, the arithmetic circuit 22, the abnormality determination circuit 23, and the alarm circuit 24 are set by a program and processed by the CPU 15 shown in FIG. Is also possible.

  The communication circuit 21 communicates with the communication circuit 41 of the production robot 40. The torque value detected by the sensor 43 and the disturbance torque calculated by the measurement circuit 42 are received and output to the sensor DB 13. The operation data of the speed reducer 44 is output to the operation history DB 11. The maintenance data of the speed reducer 44 is output to the memory 16.

  The memory 16 stores maintenance data of the speed reducer 44 received from the communication circuit 21. When the reduction gear 44 is maintained, maintenance data is transmitted in real time and stored in the memory 16. In addition to real time, maintenance data input by the user from the user interface 50 after the actual maintenance is completed is stored. Therefore, the latest maintenance data is recorded in the memory 16.

  The operation history DB 11 stores operation data of the production robot 40 received from the communication circuit 21. As described above, the operation data includes various data related to the operation, such as the operation date of the speed reducer 44, the time when the operation was started, the time when the operation was stopped, the time when the operation was continued, the time when the operation was continuously stopped, and the like. Data relating to the operation of the machine 44, data relating to the motor stop position, and the like are included.

  The sensor DB 13 stores the motor torque value and disturbance torque detected by the sensor 43 and received from the communication circuit 21.

  The temperature DB 12 stores the ambient temperature received from the communication circuit 21 such as the environmental temperature of the facility where the production robot 40 is installed, the internal temperature of the speed reducer 44, and the surface temperature. Further, the temperature DB 12 may store temperature data in a production facility where the production robot 40 is installed, or temperature data collected from the outside via a network. Moreover, you may memorize | store the temperature data of the area where the production facility is located.

  The arithmetic circuit 22 calculates an abnormality determination for the speed reducer 44 based on the torque value and disturbance torque stored in the sensor DB 13 and the maintenance data stored in the memory 16. Specifically, the rate of change of disturbance torque generated in the motor of the speed reducer 44 is calculated, and it is determined whether or not it is abnormal by comparison with a preset rate of change threshold. Alternatively, the degree of abnormality of disturbance torque generated in the motor is calculated, and it is determined whether or not it is abnormal by comparing the degree of abnormality with a preset abnormality degree threshold.

  (A) The method for calculating the change rate of the disturbance torque and (B) the method for calculating the degree of abnormality of the disturbance torque will be described below.

(A) Method of calculating change rate of disturbance torque A reference value of disturbance torque is set, and the change rate is calculated by comparing the reference value with the calculated disturbance torque. For example, when the reference value is “100” and the detected disturbance torque is “120”, the change rate is calculated to be 20% as shown in the following equation (1).
(120/100) -1 = 0.2 = 20% (1)
Then, the calculated rate of change is compared with a preset rate of change threshold (for example, 15%), and if the rate of change exceeds the rate of change threshold, an abnormality has occurred in the speed reducer 44. to decide. In the above example, since 20%> 15%, it is determined that the reduction gear 44 is abnormal.

  As an example, the reference value can be set as an average value of disturbance torque in a predetermined time during normal operation. Moreover, you may use the average value of the disturbance torque data of the same month one year ago. By using the disturbance torque data of the same month, it is possible to use the data when the time and season environments match, so that more accurate judgment can be made. It is also possible to set the reference value to a numerical value other than the average value.

(B) Method of calculating the degree of abnormality of disturbance torque If the degree of abnormality is a (x ′), the degree of abnormality a (x ′) is calculated by the following equation (2).
a (x ′) = {(x′−m) ² } / 2s ² (2)
In equation (2), “x ′” is a newly measured disturbance torque, “m” is a sample average of the disturbance torque, and “s” is a standard deviation of the disturbance torque.

Then, the calculated abnormality degree is compared with a preset abnormality degree threshold value, and if the abnormality degree exceeds the abnormality degree threshold value, it is determined that an abnormality has occurred in the reduction gear 44.
The abnormality detection method is not limited to the above (A) and (B), and for example, a method using a probability distribution such as a method using a moving average, kernel density estimation, density ratio estimation, or the like can also be adopted. It is.

  FIG. 4 is a graph showing the change of the disturbance torque calculated by the above-described equation (1) with respect to time, the horizontal axis is time, and the vertical axis is the change rate [%]. FIG. 4 shows the change in the rate of change when the production robot 40 is operated until March 4, and then is suspended for two days from March 5, March 6, and restarted from March 7. ing.

  On March 4, which is just before the end of the operation, the rate of change is almost 0%. That is, no great disturbance torque change has occurred. Further, on March 7 immediately after the start of re-operation, a great change has occurred in the disturbance torque, and the rate of change exceeds 20%. After that, the rate of change gradually decreased as time passed on March 8 and March 9.

  For example, if the change rate threshold value for determining an abnormality is set to 15%, the change rate on March 7 exceeds the change rate threshold value, so it is determined that there is an abnormality.

  Further, when it is determined that an abnormality has occurred in the speed reducer 44 in the above processing, the arithmetic circuit 22 sets the operation stop time of the speed reducer 44 based on the operation data stored in the operation history DB 11. Calculate. Specifically, when it is determined that an abnormality has occurred in the speed reducer 44, the operation is stopped for a long time before the occurrence of the abnormality based on the operation data stored in the operation history DB 11. Determine whether time exists. This determination result is output to the abnormality determination circuit 23.

  The abnormality determination circuit 23 includes a false alarm prevention circuit 231, a spike removal circuit 232, and a determination calculation circuit 233.

The false alarm prevention circuit 231 determines whether or not there is an operation stop time longer than the first predetermined time (for example, a stop due to a long vacation) based on the operation stop time of the speed reducer 44 acquired by the arithmetic circuit 22. To do. The first predetermined time is, for example, one day, one week, or one month. Then, when there is an operation stop time longer than the first predetermined time, a process for removing a spike that is superimposed on the torque value for a certain time after the start of operation after this operation stop time. Set the time to be executed (hereinafter referred to as “spike exclusion time”).
At this time, the spike exclusion time is calculated based on the ambient temperature stored in the temperature DB 12. The “spike” indicates a sudden change in the torque value superimposed on the torque value of the motor of the speed reducer 44, for example, a component having a cycle of 2 hours or less (a predetermined cycle or less).

The spike removal circuit 232 performs processing for removing spikes generated in the torque value of the motor of the speed reducer 44 during the spike exclusion time (second predetermined time).
By removing the spike from the torque value, the torque value is corrected. Therefore, since spikes superimposed on the torque value are removed during the spike exclusion time, it is possible to prevent erroneous detection of abnormality determination due to spikes exceeding the threshold value. Further, instead of removing the spike, it is possible to change the threshold for determining abnormality of the disturbance torque in the “spike exclusion time” described above. In this case, even when a spike occurs, the abnormality determination threshold is set high, so that erroneous detection of abnormality determination due to the spike exceeding the threshold can be prevented. Or you may use together the process which removes a spike and raises a threshold value.

  Hereinafter, the spike removal procedure will be described with reference to FIG. FIG. 5 is a graph showing a change in torque value over time and spike exclusion time. As shown in FIG. 5, on March 7 when the speed reducer 44 is restarted from a stopped state, a torque spike (q1, q2, q3, etc.) occurs due to disturbance torque due to the influence of the operation stop time. ing. Further, a threshold value Tth is set for the torque value, and when the torque value exceeds the threshold value Tth, it is determined that there is an abnormality.

  The spike removal circuit 232 removes spikes by performing a process of removing a waveform having a short cycle from the torque value on March 7. This process detects a waveform that suddenly rises or falls and returns to its original state. If this period is shorter than a predetermined period (for example, 2 hours), the change in torque value is a spike caused by disturbance torque. It is determined that there is, and this waveform is removed. The spike waveforms q1, q2, q3 shown in FIG. 5 are removed. Therefore, it is possible to avoid the torque value from exceeding the threshold value Tth due to a spike that occurs suddenly after the start of the operation of the speed reducer 44. Since the spike exclusion time is set to 1 day (24 hours), spikes occurring in the torque values after March 8 are not removed.

  In addition, although an example in which a waveform having a period shorter than the predetermined period is determined as a spike and the spike is removed has been described, the following methods (a) to (d) may be employed. .

(A) An average value of torque values within the spike exclusion time (second predetermined time) is calculated, and correction is performed to replace the torque value (sensor data) at the spike exclusion time with the above average value.

(B) A moving average of torque values is calculated, and correction is performed to replace the torque value at the spike exclusion time with the above moving average.

(C) Calculate the variance of the torque value within the spike exclusion time, and calculate the variance at normal times when sufficient time has elapsed since the start of the reduction gear operation and stable operation To do. Then, the torque value of the spike exclusion time is multiplied by a numerical value obtained by dividing “variance of normal period” by “dispersion of spike exclusion time” to obtain a corrected torque value.

(D) Within the spike exclusion time, the threshold value Tth for determining an abnormality in the torque value is set high.

  And also when employ | adopting the method of said (a)-(c), the spike in spike exclusion time can be removed or suppressed. Further, by adopting the above method (d), the threshold value Tth is set relatively high compared to the normal time, so that the torque value hardly exceeds the threshold value Tth, and erroneous detection can be prevented. Moreover, you may use together said (a)-(c) and (d).

Based on the torque value from which the spike has been removed, the determination calculation circuit 233 determines that an abnormality has occurred in the speed reducer 44 when the torque value exceeds the above-described threshold value. That is, it is determined that the speed reducer 44 is abnormal when the torque value exceeds a threshold value (see Tth in FIG. 5) even though the spike is removed at the exclusion time.
Specifically, as shown in FIG. 5, when the torque value after the spike waveforms q1 to q3 are removed exceeds the threshold value Tth, it is determined that there is an abnormality.

  As described above, the abnormality determination circuit 23 having the false alarm prevention circuit 231, the spike removal circuit 232, and the determination calculation circuit 233 acquires the operation stop time of the speed reducer 44, and the operation stop time exceeds the first predetermined time. Control for correcting at least one of a torque value (sensor data) and a threshold value for determining abnormality of the torque value for a second predetermined time after the reduction gear 44 starts operating after the operation stop time has elapsed. It has a function as a part.

  When the abnormality determination circuit 23 determines that an abnormality has occurred in the speed reducer 44, the alarm circuit 24 outputs an alarm to the user interface 50 to notify the user of the occurrence of the abnormality.

  Then, in the abnormality determination device 101 according to the first embodiment, for example, when the operation of the production robot 40 is finished and the operation is started two days later, or after a holiday, a long non-operation state continues. In such a case, erroneous detection of abnormality during subsequent operation is prevented.

[Description of Operation of First Embodiment]
Next, the operation of the abnormality determination device 101 according to the first embodiment will be described. FIG. 3 is a flowchart showing a processing procedure of the abnormality determination device 101 according to the first embodiment.
First, in step S11, the arithmetic circuit 22 acquires the disturbance torque stored in the sensor DB 13 and the maintenance data stored in the memory 16, and determines whether or not an abnormality has occurred in the speed reducer 44. For the operation.

  In step S <b> 12, the arithmetic circuit 22 determines whether an abnormality has occurred in the speed reducer 44. Specifically, based on the disturbance torque stored in the sensor DB 13, the abnormality is determined using the above-described (A) method of calculating the disturbance torque change rate and (B) the method of calculating the disturbance torque abnormality degree. can do. At this time, referring to the maintenance data, if it is stored in the maintenance data that the reduction gear 44 has been maintained, it is determined that no abnormality has occurred because the reduction gear 44 has already been maintained. To do.

If it is determined in step S12 in FIG. 3 that an abnormality has occurred, in step S13, the arithmetic circuit 22 refers to the reduction gear operation data recorded in the operation history DB 11, Perform data analysis.
In the data analysis process, it is analyzed whether or not there is a long operation stoppage time before an abnormality is detected (for example, within 3 days).
In step S14, the false alarm prevention circuit 231 determines whether the operation stop time has exceeded the first predetermined time. The first predetermined time is set to one day (24 hours), for example.

In the example shown in FIG. 4 described above, the operation stop time is continuous for two days before March 7 (within 3 days) when the change rate amplitude is determined to be abnormal. It is determined that the time has exceeded the first predetermined time. Thereafter, the process proceeds to step S15.
If the operation stop time is equal to or shorter than the first predetermined time, after other factor analysis is performed in step S21, the process proceeds to step S20, and an alarm signal is output to the user interface 50. Further, the fact that an alarm has been output is recorded in the operation history DB 11.

  In step S15, the false alarm prevention circuit 231 calculates the spike exclusion time (second predetermined time) with reference to the operation data and the ambient temperature.

  As a specific example, when the operation stop time is one day, the spike exclusion time is set to the predetermined time T1, and as the operation stop time becomes longer, the spike exclusion time is set to be longer than the predetermined time T1. When the operation stop time is long, after the operation is started, the time that the motor mounted on the speed reducer 44 does not operate stably tends to increase, so by increasing the spike exclusion time, Prevent false detection. As another specific example, the spike exclusion time is set longer as the temperature around the reduction gear 44 is lower. When the temperature around the reducer 44 is low, it is judged that the time until the motor temperature rises and operates normally is long, so the spike exclusion time is set long to prevent false detection of abnormalities. To do.

  In step S16, the spike removal circuit 232 removes spikes that are superimposed on the torque value within the spike exclusion time set in step S15 by the method described above. For example, spikes (q1, q2, q3, etc.) shown in FIG. 5 are removed.

  In step S17, the determination calculation circuit 233 determines whether or not the torque value is abnormal. Specifically, when the torque value after removing the spike exceeds the threshold value Tth, it is determined to be abnormal.

In addition to the method of determining an abnormality by comparing the torque value and the threshold value Tth, it is also possible to determine the abnormality using the above-described change rate of the disturbance torque.
For example, as shown in FIG. 4, on March 7, which is the working day after the operation stop time, the change rate of the disturbance torque exceeds the change rate threshold of 15%. If the change rate of the disturbance torque still exceeds the change rate threshold even after the processing for removing the spike is performed, it is determined that the speed reducer 44 is abnormal. Further, after the spike exclusion time has elapsed, it is determined that an abnormality has occurred even when the rate of change of the disturbance torque exceeds the rate of change threshold.

  As another method, when the disturbance torque abnormality degree is calculated and the spike is removed, the disturbance torque abnormality degree still exceeds the abnormality threshold value, or spike exclusion is performed. If the degree of abnormality exceeds the degree of abnormality threshold after a lapse of time, it is possible to determine that the reduction gear 44 is abnormal.

  If no abnormality has occurred in the torque value by the above process (NO in step S17), this process ends.

  On the other hand, if a spike occurs after the spike exclusion time has elapsed (YES in step S17), it is determined that an abnormality has occurred in the speed reducer 44, and the process proceeds to step S18.

  In step S18, the alarm circuit 24 determines whether to output an alarm. If it is determined to output an alarm, the alarm circuit 24 outputs an alarm signal to the user interface 50 in step S20. Further, the fact that an alarm has been output is recorded in the operation history DB 11. The determination as to whether or not to output an alarm can be made by the user through the user interface 50, for example.

If it is not determined to output an alarm (NO in step S18), in step S19, the output of the alarm is recorded in the operation history DB.
Thus, when the reduction gear 44 has a long operation stop time, the spike exclusion time can be set based on the operation stop time, thereby preventing false alarms.

[Description of Modified Example of First Embodiment]
In the first embodiment described above, the spike exclusion time is set when the speed reducer 44 has stopped for a long time and has stopped for a first predetermined time (for example, one day). Further, an example in which the spike exclusion time is set longer as the first predetermined time is longer has been described.

In the modification, the spike exclusion time is set according to the temperature around the reduction gear 44 in addition to the length of the first predetermined time.
FIG. 6 is an example of a correspondence table showing the relationship between the operation stop time (first predetermined time) of the speed reducer 44, the average ambient temperature, and the spike exclusion time. For example, when the average ambient temperature of the speed reducer 44 is 10 ° C. and the operation stop time of the speed reducer 44 is 2 days, the spike exclusion time is set to 1 day (24 hours). When the average ambient temperature of the speed reducer 44 is 30 ° C. and the operation stop time of the speed reducer is 2 days, the spike exclusion time is set to 0.5 days (12 hours).

  FIG. 7A is a graph showing the change in the rate of change of disturbance torque when the ambient temperature of the speed reducer 44 is around 30 ° C. The speed reducer 44 is operated until July 1, The figure shows the case where the speed reducer 44 is stopped for two days on July 3 and the operation is started on July 4. Moreover, FIG.7 (b) is a graph which shows the temperature change of the time corresponding to Fig.7 (a).

  As shown in FIG. 7A, a large disturbance torque is generated on July 4 when the operation is started, and there is a time zone (waveform Q1) in which the rate of change exceeds 20%. Therefore, if the spike generated in the torque value is not removed, it is erroneously detected that an abnormality has occurred in the speed reducer 44. However, since the spike exclusion time is set to 0.5 days (12 hours) from the correspondence table of FIG. 6, the amplitude of the waveform Q1 included in 12 hours on July 4 is suppressed due to the spike removal, which is abnormal. No alarm is output.

  FIG. 8A is a graph showing changes in the rate of change of disturbance torque when the ambient temperature of the speed reducer 44 is around 10 ° C., which is relatively lower than that in FIG. 7. 44, the reduction gear 44 is stopped for two days on March 26 and March 27, and the operation is started on March 28. Moreover, FIG.8 (b) is a graph which shows the temperature change of the time corresponding to Fig.8 (a).

  As shown in FIG. 8 (a), on March 28 when the operation started, there is a time zone in which the disturbance torque changes greatly, and there are time zones (waveforms Q2, Q3) where the rate of change exceeds 15%. To do. Therefore, if the spike generated in the torque value is not removed, it is erroneously detected that an abnormality has occurred in the speed reducer 44. However, since the spike exclusion time is set to 1 day (24 hours) from the correspondence table in FIG. 6, the waveforms Q2 and Q3 included in 24 hours on March 28 have their amplitudes suppressed by the removal of the spikes. No alarm is output.

  That is, when the ambient temperature is high, the spike exclusion time is set short, and when the ambient temperature is low, the spike exclusion time is set relatively long. In other words, when the ambient temperature is low, the spike exclusion time is set longer than when the ambient temperature is relatively high. By setting the spike exclusion time in consideration of the ambient temperature, false alarms can be prevented more reliably.

[Description of Effects of First Embodiment]
As described above, the abnormality determining device and the abnormality determining method according to the first embodiment and the modification can achieve the following effects.
(1)
A spike exclusion time (second predetermined time) is set when the operation stop time of the device (production robot 40) provided with the speed reducer 44 (movable mechanism) exceeds a first predetermined time (for example, one day). Then, when the speed reducer 44 is operated after the operation stop time, at least one of the torque value (sensor data) and the threshold value Tth is corrected by the spike exclusion time. Therefore, even when a spike occurs suddenly in the torque value due to the long operation stop time, it is possible to prevent false alarms due to the spike.

(2)
A predetermined period (for example, 2 hours) is set, and a waveform having the predetermined period or less is regarded as a spike and removed by a change in the torque value of the speed reducer 44. That is, a component having a predetermined period or less is removed from the waveform indicating a change with time of the torque value within the spike exclusion time (second predetermined time). Specifically, spikes superimposed on the torque value of the speed reducer 44 such as spike waveforms q1 and q2 shown in FIG. 5 can be removed with higher accuracy. Therefore, it is possible to prevent false alarms due to torque spikes that occur after starting operation.

(3)
During the spike exclusion time, the average value of the torque value is calculated and the average value is corrected to be the torque value within the spike exclusion time, so that the spike at the spike exclusion time can be removed or reduced, and the spike It is possible to prevent false alarms due to.

(4)
By calculating the moving average of the torque values and correcting the torque value at the spike exclusion time as the moving average, spikes at the spike exclusion time can be removed or reduced, and false alarms due to spikes can be prevented. be able to.

(5)
During the spike exclusion time, the torque value is multiplied by (variance value in normal time / variance value of the correction time), and this calculation result is corrected to be the torque value at the spike exclusion time, resulting in a spike in the torque value. Even if this occurs, it is possible to reduce the spike from exceeding the threshold, and to prevent false alarms due to the spike.

(6)
The longer the operation stop time is, the longer the spike exclusion time is set. Therefore, even when spikes are likely to occur during operation after a long stop, the spikes can be removed to prevent false alarms.

(7)
Since the spike exclusion time is calculated based on the ambient temperature of the speed reducer 44, a time zone during which spikes are likely to occur can be set as the spike exclusion time. For example, when the ambient temperature is low, the time period in which the spike occurs after the operation is started also becomes longer. Therefore, by setting the spike exclusion time longer, it is possible to prevent false alarms due to the spike.

(8)
As the ambient temperature of the speed reducer 44, the environmental temperature of the facility where the speed reducer 44 is installed or the temperature inside the speed reducer 44 can be used, so a more accurate temperature can be used, and false alarms due to spikes are reported. Can be prevented.

[Description of Second Embodiment]
With reference to FIG. 9, FIG. 10, the abnormality determination apparatus 102 which concerns on 2nd Embodiment is demonstrated. FIG. 9 and FIG. 10 are different from FIG. 1 and FIG. 2 described above in that the operation history DB 11 is not provided. Other than that, the configuration is the same as in FIGS.

  In the second embodiment, the arithmetic circuit 22 shown in FIG. 10 does not use operation data, and based on the torque value stored in the sensor DB 13, the torque value is the same continuously for a certain time (first predetermined time). The time during which the value is maintained is recognized as the operation stop time. That is, if the torque value does not change, it can be determined that the speed reducer 44 is not operating, and therefore the operation stop time can be obtained without using the operation data stored in the operation history DB 11. Since the configuration and operation other than those described above are the same as those of the first embodiment described above, description thereof is omitted.

  In this way, in the abnormality determination device 102 according to the second embodiment, in addition to the effects described in the first embodiment, the operation history DB 11 is not provided, so that the device configuration can be simplified and the size can be reduced. It is possible to reduce the cost.

[Description of Third Embodiment]
Next, a third embodiment of the present invention will be described. Since the configuration of the abnormality determination device according to the third embodiment is the same as that shown in FIGS. 1 and 2 described in the first embodiment, description of the configuration is omitted.
The third embodiment is different from the first embodiment described above in that the spike exclusion time (second predetermined time) is set using past sensor data stored in the sensor DB 13 (storage unit). .

  That is, in the first embodiment described above, when the stop time of the speed reducer 44 exceeds the first predetermined time, the spike exclusion time is set according to the first predetermined time. On the other hand, in the third embodiment, for example, a past statistical torque value of “a spike has occurred for 3 days when the speed reducer stops for 20 days and then starts operation”. If data exists, the spike exclusion time is set based on this torque value. That is, when the stop time of the speed reducer 44 is 20 days, the spike exclusion time is set to 3 days.

  Furthermore, in addition to the torque value stored in the sensor DB 13, the ambient temperature stored in the temperature DB 12 can be used. For example, as past data, torque value data indicating that when the speed reducer stopped for two days and then started operation, the ambient temperature was 30 ° C. and a spike due to disturbance torque occurred for two days. If there is data on the ambient temperature, the spike exclusion time is set based on these data. That is, when the stop time of the speed reducer 44 is 2 days and the ambient temperature is around 30 ° C., the spike exclusion time is set to 2 days.

  FIG. 11 is a flowchart illustrating a processing procedure of the abnormality determination device according to the third embodiment. The flowchart shown in FIG. 11 is different from the process shown in FIG. 3 described above in that the process shown in step S15a is different and the other processes are the same as those in FIG.

  In step S15a, the false alarm prevention circuit 231 determines the spike exclusion time (second predetermined time) based on the past torque value data stored in the sensor DB 13 and the past ambient temperature data stored in the temperature DB 12. ) Is calculated. Then, based on the calculated spike exclusion time, spikes are removed in step S16. Since the process after step S17 is the same as that of 1st Embodiment, description is abbreviate | omitted.

  Thus, by setting the spike exclusion time based on the past statistical data stored in the sensor DB 13 (memory) and the temperature DB 12, it is possible to set an appropriate spike exclusion time. Therefore, it is possible to prevent false alarm reporting with higher accuracy.

  The target device for detecting an abnormality is not limited to the production robot 40. For example, an automobile engine may be used instead of the motor, and a transmission may be used instead of the speed reducer 44. In addition, a moving body such as a rotating mechanism of a moving body, a playground equipment at an amusement park, a machine tool such as a three-dimensional printer, that is, all devices having a rotating mechanism and a mechanism for transmitting the rotating mechanism can be targeted. Further, other types of devices may be targeted.

  In addition, an abnormality determination device may be arranged at a remote location, and necessary signals and data may be transmitted / received via a communication line to detect an abnormality of the device. Moreover, one abnormality determination apparatus may detect abnormality of a some apparatus. In addition, the plurality of devices may be arranged at different locations. Further, the communication circuit 21, the arithmetic circuit 22, the abnormality determination circuit 23, the alarm circuit 24, and the like can be configured using a computer.

  Each function shown in the above-described embodiments may be implemented by one or a plurality of processing circuits. The processing circuit includes a programmed processing device such as a processing device including an electrical circuit. Processing devices also include devices such as application specific integrated circuits (ASICs) and conventional circuit components arranged to perform the functions described in the embodiments.

  As mentioned above, although embodiment of this invention was described, it should not be understood that the description and drawing which form a part of this indication limit this invention. From this disclosure, various alternative embodiments, examples, and operational techniques will be apparent to those skilled in the art.

11 Operation history DB
12 Temperature DB
13 Sensor DB (storage unit)
15 CPU
DESCRIPTION OF SYMBOLS 16 Memory 21 Communication circuit 22 Arithmetic circuit 23 Abnormality judgment circuit 24 Alarm circuit 40 Production robot 41 Communication circuit 42 Measurement circuit 43 Sensor 44 Reducer 50 User interface 101,102 Abnormality judgment apparatus 231 False alarm prevention circuit 232 Spike removal circuit 233 Determination arithmetic circuit

Claims (11)

An abnormality determination apparatus including a control unit that determines abnormality of a device including a movable mechanism based on sensor data acquired from a sensor installed in the movable mechanism and a preset threshold value,
The controller is
Obtaining an operation stop time, which is a time during which the movable mechanism stops operating;
When the operation stop time exceeds a first predetermined time, at least one of the sensor data and the threshold value during a second predetermined time after the movable mechanism starts operating after the operation stop time has elapsed. An abnormality determination device characterized by correcting the above. The control unit corrects the sensor data by removing a component having a predetermined period or less included in a waveform indicating a change with time of the sensor data within the second predetermined time. The abnormality determination device according to claim 1. The said control part correct | amends the said sensor data by making the said sensor data in the said 2nd predetermined time into the average value of the said sensor data in the said 2nd predetermined time. Item 10. An abnormality determination device according to Item 1. The abnormality determination device according to claim 1, wherein the control unit corrects the sensor data by setting the sensor data within the second predetermined time as a moving average of the sensor data. . The control unit is configured to obtain a value obtained by dividing a variance of the sensor data in a normal time of the movable mechanism by a variance of the sensor data within the second predetermined time, and the sensor data within the second predetermined time. The abnormality determination device according to claim 1, wherein the sensor data is corrected by multiplying by. The abnormality determination device according to claim 1, wherein the control unit sets the second predetermined time longer as the operation stop time is longer. The abnormality determination apparatus according to claim 1, wherein the control unit sets the second predetermined time based on an ambient temperature of the movable mechanism during the operation stop time. . The abnormality determination device according to claim 7, wherein the ambient temperature of the movable mechanism is an environmental temperature of a facility where the movable mechanism is installed, or a temperature inside the movable mechanism. The abnormality determination device according to claim 1, wherein the control unit changes the threshold according to the operation stop time. A storage unit for storing the sensor data;
The abnormality determination according to any one of claims 1 to 5, wherein the control unit sets the second predetermined time based on past sensor data stored in the storage unit. apparatus. An abnormality determination method for determining an abnormality of a device including a movable mechanism based on sensor data acquired from a sensor installed in the movable mechanism and a preset threshold value,
Obtaining an operation stop time during which the movable mechanism has stopped operating;
When the operation stop time exceeds a first predetermined time, at least one of the sensor data and the threshold value during a second predetermined time after the movable mechanism starts operating after the operation stop time has elapsed. An abnormality determination method characterized by correcting the error.

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