Method and system for determining anomalies of industrial machinery

Abstract

A method for determining a synchronization deviation is provided with: an acquisition step for acquiring first drive data indicating a dynamic state of a first drive mechanism; an acquisition step of acquiring second drive data indicating a dynamic state of the second drive mechanism; an extraction step of extracting a difference between the first driving data and the second driving data; a calculation step: calculating the cumulative sum of the difference; a judgment step: judging whether the cumulative sum has linearity or non-linearity; and a determination step of determining that a synchronization deviation occurs between the first drive mechanism and the second drive mechanism when the cumulative sum has non-linearity.

Description

Technical Field

[0001] The present invention relates to a method and a system for determining abnormality of industrial machinery. Background Art

[0002] In industrial machinery, it is sometimes necessary to detect the occurrence of abnormalities. Therefore, in the prior art, a sensor is used to detect a predetermined output value of the industrial machinery, and the detected output value is compared with a threshold value to determine the abnormality (for example, refer to Patent Document 1).

[0003] In addition, there is a component in industrial machinery that has a pair of drive mechanisms that move synchronously with each other. For example, Patent Document 2 discloses a workpiece transport device in a press line. The workpiece transport device has a crossbar, a pair of swing bodies, and a pair of drive mechanisms. The pair of swing bodies are respectively connected to the left and right ends of the crossbar. The pair of drive mechanisms respectively move the pair of swing bodies.

[0004] Prior art literature

[0005] Patent Literature

[0006] Patent Document 1: Japanese Patent Application Laid-Open No. 02-195498

[0007] Patent Document 2: Japanese Patent No. 4198035 Summary of the invention

[0008] Problems to be solved by the invention

[0009] In the above-mentioned workpiece transport device, a pair of driving mechanisms have the same structure as each other, so that a pair of swinging bodies move synchronously. However, sometimes the synchronization of the pair of driving mechanisms will deviate. If the synchronization of the pair of driving mechanisms deviates, it is difficult to make the workpiece transport device move with high precision. However, in the above-mentioned conventional abnormality judgment method, for each of the pair of driving devices, it is possible to judge whether there is an abnormality, but it is difficult to detect the deviation of the synchronization of the pair of driving devices. The purpose of the present invention is to detect the deviation of synchronization with high precision in an industrial mechanism including a pair of driving mechanisms that move synchronously with each other.

[0010] Means for solving problems

[0011] A method according to one embodiment of the present invention is a method executed by one or more computers in an industrial machine including a first drive mechanism and a second drive mechanism that operate synchronously with each other, in order to determine a synchronization deviation between the first drive mechanism and the second drive mechanism. The method comprises: a step of acquiring first drive data representing a dynamic state of the first drive mechanism; a step of acquiring second drive data representing a dynamic state of the second drive mechanism; a step of extracting a difference between the first drive data and the second drive data; a step of calculating a cumulative sum of the differences; a step of determining whether the cumulative sum is linear or non-linear; and a step of determining that a synchronization deviation has occurred between the first drive mechanism and the second drive mechanism when the cumulative sum is non-linear.

[0012] The system involved in other embodiments of the present invention is a system for determining a synchronization deviation between a first drive mechanism and a second drive mechanism in an industrial machine including a first drive mechanism and a second drive mechanism that perform actions synchronously with each other. The system comprises a storage device and one or more computers. The storage device stores first drive data representing a dynamic state of the first drive mechanism and second drive data representing a dynamic state of the second drive mechanism. One or more computers are connected to the storage device in a communicative manner. One or more computers extract the difference between the first drive data and the second drive data. One or more computers calculate the cumulative sum of the differences. One or more computers determine whether the cumulative sum is linear or non-linear. When the cumulative sum is non-linear, the one or more computers determine that a synchronization deviation has occurred between the first drive mechanism and the second drive mechanism.

[0013] Effects of the Invention

[0014] According to the present invention, a synchronization deviation can be detected with high accuracy in an industrial machine including a pair of drive mechanisms that operate in synchronization with each other. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 Schematic diagram showing a predictive maintenance system according to an embodiment.

[0016] Figure 2 It is the front view of industrial machinery.

[0017] Figure 3 It is a front view showing the workpiece conveying device.

[0018] Figure 4 It is a side view showing the first driving mechanism.

[0019] Figure 5 Detailed description of the invention is a flowchart showing a process for providing predictive maintenance service for a workpiece transport device.

[0020] Figure 6 Detailed description of the invention is a flowchart showing a process for providing predictive maintenance service for a workpiece transport device.

[0021] Fig. 7A This is a diagram showing an example of the first driving data.

[0022] Figure 7B It is a diagram showing an example of the second driving data.

[0023] Figure 8 This is a diagram showing an example of difference data between the first drive data and the second drive data.

[0024] Fig.9A This is a diagram showing an example of analysis data.

[0025] Fig. 9B This is a diagram showing an example of Gaussian distribution of analysis data.

[0026] Fig.10 This is a diagram showing an example of cumulative sum data without synchronization deviation.

[0027] Fig.11 This is a diagram showing an example of accumulated sum data with synchronization mismatch. DETAILED DESCRIPTION

[0028] Hereinafter, embodiments will be described with reference to the drawings. Figure 1 1 is a schematic diagram showing a predictive maintenance system 1 according to an embodiment of the present invention. The predictive maintenance system 1 is a system for determining a location to be maintained before a failure occurs in an industrial machine. The predictive maintenance system 1 includes industrial machines 2 and 3, a local computer 4, and a server 5.

[0029] like Figure 1 As shown, the industrial machines 2 , 3 include a forging machine 2 and a workpiece handling device 3 . Figure 2 This is a front view of industrial machines 2 and 3. The forging machine 2 includes a slider 11, a slide drive mechanism 12, a bolster 13, a bed 14, a die buffer device 15, and a forging controller 6. The slider 11 is configured to be movable up and down. An upper die 16 is mounted on the slider 11. The slide drive mechanism 12 moves the slider 11. The slide drive mechanism 12 includes, for example, a servomotor.

[0030] A bolster 13 is disposed below the slider 11. A lower die 17 is mounted on the bolster 13. A bed 14 is disposed below the bolster 13. A die cushion device 15 applies an upward load to the lower die 17 during forging. Specifically, the die cushion device 15 applies an upward load to the lower die 17 during forging. The forging controller 6 controls the movement of the slider 11 and the die cushion device 15.

[0031] The die cushion device 15 includes a cushion pad 18 and a die cushion drive mechanism 19. The cushion pad 18 is disposed below the backing plate 13. The cushion pad 18 is provided to be movable in the vertical direction. The die cushion drive mechanism 19 moves the cushion pad 18 in the vertical direction. The die cushion drive mechanism 19 includes, for example, a servo motor.

[0032] The slide drive mechanism 12 and the die cushion drive mechanism 19 are connected to the forging controller 6. The forging controller 6 includes a processor and a memory (not shown). The slide drive mechanism 12 and the die cushion drive mechanism 19 are controlled by the forging controller 6. Thus, the workpiece W1 is forged by the upper die 16 and the lower die 17.

[0033] The workpiece transport device 3 transports the workpiece W1 to be forged. The workpiece transport device 3 moves the workpiece W1 along the transport direction. The transport direction is perpendicular to Figure 2 In the direction of the paper. Below, perpendicular to Figure 2 The direction of the paper surface in is defined as the front-rear direction in the workpiece transport device 3 . Figure 2 The left-right direction in is defined as the left-right direction in the workpiece transport device 3 .

[0034] For example, the forging machine (press machine) 2 is a part of a transfer press (transfer press) composed of a plurality of forging machines, and the plurality of forging machines are arranged in parallel along the front-to-back direction. The workpiece transport device 3 transports the workpiece W1 that has been forged in the forging machine 2 to the processing position in other forging machines. Figure 2 As shown, the workpiece transport device 3 includes a first driving mechanism 21 , a second driving mechanism 22 , and a cross bar 23 .

[0035] Figure 3 It is a front view showing the workpiece transport device 3 . Figure 4 2 is a side view showing the first driving mechanism 21. Figure 3 as well as Figure 4As shown, the first driving mechanism 21 includes a first rail 31, a first linear arm 32, a first swing arm 33, and a first slider arm 34. The first rail 31 extends in the front-rear direction. The first linear arm 32 is supported by the first rail 31. Figure 4 As shown by the arrow symbol A1 in FIG. 1 , the first linear arm 32 can move in the front-rear direction along the first rail 31. The first swing arm 33 is connected to the first linear arm 32. Figure 4 As shown by the arrow symbol A2 in FIG. 1 , the first swing arm 33 can rotate relative to the first slider arm 32 around the first axis A×1. The first slider arm 34 is connected to the first swing arm 33. Figure 4 As shown by the arrow symbol A3 in FIG. 8 , the first slider arm 34 can swing along the first swing arm 33 .

[0036] The first driving mechanism 21 includes a first linear motor 35, a first swing motor 36, and a first slider motor 37. The first linear motor 35 moves the first linear arm 32. The first swing motor 36 moves the first swing arm 33. The first slider motor 37 moves the first slider arm 34. Specifically, the first linear motor 35 moves the first linear arm 32 along the first rail 31. The first swing motor 36 swings the first swing arm 33 around the first axis A×1. The first slider motor 37 moves the first slider arm 34 along the first swing arm 33.

[0037] The second drive mechanism 22 is configured to be separated from the first drive mechanism 21 in the left-right direction. The second drive mechanism 22 has a structure that is left-right symmetrical to the first drive mechanism 21. The second drive mechanism 22 includes a second rail 41, a second linear arm 42, a second swing arm 43, and a second slider arm 44. The second rail 41 extends in the front-back direction. The second linear arm 42 is supported by the second rail 41. The second linear arm 42 can move in the front-back direction along the second rail 41. The second swing arm 43 is connected to the second linear arm 42. The second swing arm 43 can swing around the second axis A×2 relative to the second linear arm 42. The second slider arm 44 is connected to the second swing arm 43. The second slider arm 44 can move along the second swing arm 43.

[0038] The second driving mechanism 22 includes a second linear motor 45, a second swing motor 46, and a second slider motor 47. The second linear motor 45 moves the second linear arm 42. The second swing motor 46 moves the second swing arm 43. The second slider motor 47 moves the second slider arm 44. In detail, the second linear motor 45 moves the second linear arm 42 along the second rail 41. The second swing motor 46 swings the second swing arm 43 around the second axis A×2. The second slider motor 47 moves the second slider arm 44 along the second swing arm 43.

[0039] The crossbar 23 supports the workpiece W1. The crossbar 23 is disposed between the first drive mechanism 21 and the second drive mechanism 22 and extends in the left-right direction. One end of the crossbar 23 is connected to the first slider arm 34. The other end of the crossbar 23 is connected to the second slider arm 44. Vacuum cups are installed on the crossbar 23 to hold the workpiece W1 by suction.

[0040] like Figure 1 As shown, the workpiece conveying device 3 includes a feeder controller 7. The feeder controller 7 includes a processor and a memory not shown. The above-mentioned motors 35 to 37, 45 to 47 are servo motors, respectively. The feeder controller 7 controls the motors 35 to 37, 45 to 47 to synchronize the first drive mechanism 21 with the second drive mechanism 22. In detail, the feeder controller 7 synchronizes the first linear motor 35 with the second linear motor 45. The feeder controller 7 synchronizes the first swing motor 36 with the second swing motor 46. The feeder controller 7 synchronizes the first slider motor 37 with the second slider motor 47. As a result, the first drive mechanism 21 and the second drive mechanism 22 synchronize, and the cross bar 23 moves along the conveying direction to convey the workpiece W1.

[0041] The local computer 4 communicates with the forging controller 6 and the feed controller 7. Figure 1 As shown, the local computer 4 includes a processor 51, a storage device 52, and a communication device 53. The processor 51 is, for example, a central processing unit (CPU). Alternatively, the processor 51 may also be a processor other than a CPU.

[0042] The storage device 52 includes non-volatile memory such as ROM and volatile memory such as RAM. The storage device 52 may also include auxiliary storage devices such as a hard disk or a solid state drive (SSD). The storage device 52 is an example of a non-transitory recording medium that can be read by a computer. The storage device 52 stores computer instructions and data for controlling the local computer 4. The communication device 53 communicates with the server 5.

[0043] The server 5 collects data for predictive maintenance from the workpiece transport device 3 via the local computer 4. The server 5 performs predictive maintenance services based on the collected data. The server 5 communicates with the client computer 8. The server 5 provides predictive maintenance services to the client computer 8. The predictive maintenance services will be described later.

[0044] The server 5 includes a first communication device 55, a second communication device 56, a processor 57, and a storage device 58. The first communication device 55 communicates with the local computer 4. The second communication device 56 communicates with the client computer 8. The processor 57 is, for example, a central processing unit CPU (Central Processing Unit). Alternatively, the processor 57 may be a processor other than a CPU. The processor 57 executes processing for predictive maintenance services according to a program.

[0045] The storage device 58 includes a non-volatile memory such as a ROM and a volatile memory such as a RAM. The storage device 58 may also include an auxiliary storage device such as a hard disk or a solid state drive SSD (Solid State Drive). The storage device 58 is an example of a non-transitory recording medium that can be read by a computer. The storage device 58 stores computer instructions and data for controlling the server 5.

[0046] The above communication may be performed via a mobile communication network such as 3G, 4G, or 5G. Alternatively, the communication may be performed via other wireless communication networks such as satellite communication. Alternatively, the communication may be performed via a computer communication network such as a LAN, VPN, or the Internet. Alternatively, the communication may be performed via a combination of these communication networks.

[0047] Next, a process for providing a predictive maintenance service for the workpiece transport device 3 will be described. Figure 5 as well as Figure 6 is a flowchart showing the process for predictive maintenance service for the workpiece transport device 3. Figure 5As shown, in step S101, the server 5 acquires first drive data. The first drive data is sent from the feed controller 7 to the local computer 4. The server 5 receives the first drive data from the local computer 4 and saves the first drive data to the storage device 58.

[0048] The first drive data indicates the dynamic state of the first drive mechanism 21. The first drive data includes, for example, the motor torque of the first slider motor 37. The first slider motor 37 is feedback-controlled by the feed controller 7, and the motor torque of the first slider motor 37 is represented, for example, by a torque command value from the feed controller 7 to the first slider motor 37. The feed controller 7 acquires the motor torque of the first slider motor 37 at a predetermined sampling period. The number of samples is, for example, several hundreds to several thousands, but is not limited thereto. The first drive data includes a plurality of motor torque values ​​sampled within a predetermined time.

[0049] In step S102, the server 5 acquires the second drive data. The second drive data is sent from the feed controller 7 to the local computer 4. The server 5 receives the second drive data from the local computer 4 and saves the second drive data to the storage device 58. The second drive data represents the dynamic state of the second drive mechanism 22. The second drive data includes, for example, the motor torque of the second slider motor 47. The second slider motor 47 is feedback-controlled by the feed controller 7, and the motor torque of the second slider motor 47 is represented, for example, by a torque command value from the feed controller 7 to the second slider motor 47.

[0050] Fig. 7A This is a diagram showing an example of the first driving data. Fig. 7A The first drive data represents the motor torque waveform of the first slider motor 37. The server 5 acquires the motor torque waveform of the first slider motor 37 as the first drive data. Figure 7B It is a diagram showing an example of the second driving data. Figure 7B The second drive data shown represents the motor torque waveform of the second slider motor 47. The server 5 acquires the motor torque waveform of the second slider motor 47 as the second drive data.

[0051] In step S103, the server 5 extracts the difference between the first drive data and the second drive data. The server 5 extracts the difference in motor torque between the first slider motor 37 and the second slider motor 47 at the same time from the first drive data and the second drive data. The server 5 saves the extracted difference as differential data in the storage device 58. The differential data includes a plurality of differential values ​​of the motor torque sampled within a predetermined time. Figure 81 is a diagram showing an example of difference data between the first slider motor 37 and the second slider motor 47 .

[0052] In step S104, the server 5 generates analysis data. The server 5 generates analysis data from the difference data according to fast Fourier transform. Fig.9A is a diagram showing an example of analysis data. Fig.9A In FIG. 1 , the horizontal axis is frequency and the vertical axis is amplitude. The analysis data represents the power spectrum value at each frequency of the fast Fourier transform.

[0053] In step S105, the server 5 extracts feature values ​​from the analysis data. The server 5 converts the analysis data into Gaussian distribution, and obtains the mean and standard deviation of the analysis data as feature values. Fig. 9B is a graph showing an example of Gaussian distribution of analysis data. Fig. 9B In the equation (1), the horizontal axis is the probability variable x, which represents the power spectrum value. The vertical axis represents the probability density f(x). The probability density f(x) is represented by the following equation (1). In equation (1), "μ" is the mean value. "δ" is the standard deviation.

[0054]

[0055] In step S106, the server 5 saves the analysis data and the characteristic quantities μ and δ to the storage device 58. Figure 6 As shown, in step S107, the server 5 determines whether the first and second drive mechanisms 21 and 22 are normal. The server 5 determines whether the first slider motor 37 and the second slider motor 47 are normal based on the characteristic quantities μ and δ corresponding to the differential data between the first slider motor 37 and the second slider motor 47. The determination of whether the first slider motor 37 and the second slider motor 47 are normal can also be performed according to a determination method known in quality engineering.

[0056] For example, the server 5 uses the MT method (Mahalanobis Taguchi method or Martin method) to determine whether the first slider motor 37 and the first slider arm 34, the second slider motor 47 and the second slider arm 44 are normal. In this case, the server 5 calculates the Mahalanobis distances of the feature quantities μ and δ received by the server 5 based on the feature quantities μ and δ when the first slider motor 37 and the first slider arm 34, the second slider motor 47 and the second slider arm 44 are normal. When the Mahalanobis distance is larger than the threshold value, the server 5 determines that at least one of the first slider motor 37 and the first slider arm 34, the second slider motor 47 and the second slider arm 44 is abnormal. However, the server 5 may also use other methods to determine whether the first and second drive mechanisms 21 and 22 are normal.

[0057] In step S107, when the server 5 determines that the first slider motor 37 and the second slider motor 47 are not normal, the processing is advanced to step S108. Figure 6 The first slider motor 37 and the second slider motor 47 are abnormal, which means that the first slider motor 37 and the second slider motor 47 have not failed, but have deteriorated to a certain extent.

[0058] In step S201 , the server 5 calculates the cumulative sum of the differences. For example, the server 5 obtains the cumulative sum of the differences between the motor torques of the first slider motor 37 and the second slider motor 47 from the difference between the first slider motor 37 and the second slider motor 47 described above. Fig.10 This is a diagram showing an example of cumulative sum data showing the cumulative sum of differences.

[0059] In step S202, the server 5 determines whether the cumulative sum has linearity. The server 5 determines whether the cumulative sum has linearity based on a known linearity determination method, for example. Fig.10 as well as Fig.11 As shown, the server 5 determines whether the change in the cumulative sum with respect to time is linear or non-linear. As an indicator of linearity, for example, when the residual sum of squares (RSS) between the data interpolation line and the data is 2.0 to 3.0 or less, the server 5 can also determine that there is linearity. However, the value of the linearity indicator is not limited to this, and it can also be an appropriate value corresponding to the model to be analyzed. Fig.10 Represents the cumulative sum data for a situation with linearity. Fig.11 Indicates the cumulative sum of data for situations where there is no linearity. Fig.11As shown, when the cumulative sum does not have linearity, in step S203 , the server 5 determines that there is a synchronization deviation between the first drive mechanism 21 and the second drive mechanism 22 .

[0060] like Fig.10 As shown, when the cumulative sum is not linear, in step S204, the server 5 determines that there is no synchronization deviation between the first drive mechanism 21 and the second drive mechanism 22. In step S205, the server 5 determines that the degradation of either the first drive mechanism 21 or the second drive mechanism 22 is in progress.

[0061] The server 5 also performs the same processing as described above on the first drive data associated with the first linear motor 35 and the second drive data associated with the second linear motor 45. Furthermore, the server 5 also performs the same processing as described above on the first drive data associated with the first swing motor 36 and the second drive data associated with the second swing motor 46. Thus, the server 5 determines whether there is a synchronization deviation between the first drive mechanism 21 and the second drive mechanism 22. Furthermore, the server 5 determines whether the degradation of any one of the first drive mechanism 21 and the second drive mechanism 22 is in progress.

[0062] The server 5 provides the above-mentioned determination result as a predictive maintenance service to the client computer 8. For example, the server 5 sends the determination result to the client computer 8 via e-mail. Alternatively, the server 5 may display the determination result on a management screen displayed by a web browser.

[0063] In the system involved in the present embodiment described above, it is determined whether the cumulative sum of the difference between the first drive data and the second drive data is linear or non-linear. And, in the case where the cumulative sum is non-linear, it is determined that a synchronization deviation occurs between the first drive mechanism 21 and the second drive mechanism 22. Thus, in the workpiece transport device 3 including the first drive mechanism 21 and the second drive mechanism 22 that operate synchronously with each other, the synchronization deviation is detected with high accuracy.

[0064] One embodiment of the present invention has been described above, but the present invention is not limited to the above embodiment, and various changes can be made without departing from the scope of the invention. For example, the processing for the above-mentioned predictive maintenance service is not limited to the workpiece conveying device 3, but can also be performed on the forging machine 2. Alternatively, the industrial machinery is not limited to the forging machine 2 and the workpiece conveying device 3, but can also include other machines such as welding machines or cutting machines, or workpiece conveying devices used by these.

[0065] The structure of the workpiece conveying device 3 may also be changed. For example, a part of the above-mentioned motor may be omitted. Or a motor may be added. The structure of the server 5 may also be changed. For example, the server 5 may also include a plurality of computers. The processing based on the above-mentioned server 5 may also be distributed and executed on a plurality of computers. The server 5 may also include a plurality of processors. Part or all of the processing based on the above-mentioned server 5 may also be executed by the local computer 4. For example, the processing of steps S101 to S105 may also be executed by the local computer 4.

[0066] Part of the above-mentioned processing may be omitted or changed. The order of the above-mentioned processing may also be changed. For example, the method for determining abnormalities based on the analysis data is not limited to the above-mentioned embodiment and may be changed. The feature quantity may also include only one of the mean μ and the standard deviation δ of the Gaussian distribution. The analysis data is not limited to the fast Fourier transform and may also be obtained by other frequency analysis such as the discrete Fourier transform.

[0067] The first drive data and the second drive data are not limited to the command value of the motor torque, but may be other parameters such as the motor current value, the motor position, or the motor rotation speed that represent the dynamic state of the first drive mechanism and the second drive mechanism.

[0068] Industrial Applicability

[0069] According to the present invention, in an industrial machine including a pair of drive mechanisms that operate in synchronization with each other, a synchronization deviation is detected with high accuracy.

[0070] Description of symbols

[0071] 5. Server (Computer)

[0072] 21. First drive mechanism

[0073] 22 Second driving mechanism

[0074] 23 Crossbar

[0075] 34 First slider arm

[0076] 37 First Slider Motor

[0077] 44 Second slider arm

[0078] 47 Second slider motor

[0079] 58 Storage Device

Claims

1. A method, in an industrial machine including a first drive mechanism and a second drive mechanism that operate synchronously with each other, the method being executed by one or more computers in order to determine a synchronization deviation between the first drive mechanism and the second drive mechanism, This method has: Acquiring first driving data representing a dynamic state of the first driving mechanism; acquiring second driving data representing a dynamic state of the second driving mechanism; extracting a difference between the first drive data and the second drive data; Obtaining a cumulative sum of the differences; Determining whether the cumulative sum is linear or non-linear; as well as When the cumulative sum has non-linearity, it is determined that the synchronization deviation occurs between the first drive mechanism and the second drive mechanism.

2. The method according to claim 1, in, This method also has: Performing frequency analysis on the differential data representing the difference to obtain analysis data representing the power spectrum of the differential data; Obtaining a Gaussian distribution of the analysis data and acquiring a feature quantity representing the Gaussian distribution; as well as Based on the feature amount, it is determined whether the first drive mechanism and the second drive mechanism are abnormal.

3. The method according to claim 2, in, This method also has: When it is determined based on the feature amount that the first drive mechanism and the second drive mechanism are abnormal and it is determined that the cumulative sum has linearity, it is determined that deterioration of one of the first drive mechanism and the second drive mechanism is in progress.

4. The method according to claim 1, in, The first driving mechanism comprises a first motor, The second driving mechanism comprises a second motor, The first driving data represents a torque waveform of the first motor, The second drive data represents a torque waveform of the second motor.

5. The method according to claim 1, in, The industrial machine is a workpiece transport device that transports a workpiece to be subjected to forging.

6. The method according to claim 5, in, The industrial machine also has: a crossbar extending between the first driving mechanism and the second driving mechanism and holding the workpiece; The first driving mechanism comprises: a first arm connected to one end of the crossbar; and a first motor to move the first arm; The second driving mechanism comprises: a second arm connected to the other end of the crossbar; and The second motor moves the second arm.

7. A system for determining a synchronization deviation between a first drive mechanism and a second drive mechanism in an industrial machine including the first drive mechanism and the second drive mechanism that operate synchronously with each other, The system has: a storage device storing first drive data indicating a dynamic state of the first drive mechanism and second drive data indicating a dynamic state of the second drive mechanism; and One or more computers are connected to the storage device in a communicative manner. the one or more computers, extracting a difference between the first driving data and the second driving data, Find the cumulative sum of the differences, Determine whether the cumulative sum is linear or non-linear, When the cumulative sum has non-linearity, it is determined that the synchronization deviation has occurred between the first drive mechanism and the second drive mechanism.

8. The system of claim 7, in, the one or more computers, performing frequency analysis on the differential data representing the difference to obtain analysis data representing the power spectrum of the differential data, Obtaining a Gaussian distribution of the analysis data, and acquiring a feature quantity representing the Gaussian distribution, Whether the first drive mechanism and the second drive mechanism are abnormal is determined based on the feature amount.

9. The system of claim 8, in, the one or more computers, When it is determined based on the feature amount that the first drive mechanism and the second drive mechanism are abnormal and it is determined that the cumulative sum has linearity, it is determined that deterioration of one of the first drive mechanism and the second drive mechanism is in progress.

10. The system according to claim 7, in, The first driving mechanism comprises a first motor, The second driving mechanism comprises a second motor, The first driving data represents a torque waveform of the first motor, The second drive data represents a torque waveform of the second motor.

11. The system according to claim 7, in, The industrial machine is a workpiece transport device that transports a workpiece to be subjected to forging.

12. The system according to claim 11, in, The industrial machine also has: a crossbar extending between the first driving mechanism and the second driving mechanism and holding the workpiece; The first driving mechanism comprises: a first arm connected to one end of the crossbar; and a first motor to move the first arm; The second driving mechanism comprises: a second arm connected to the other end of the crossbar; and The second motor moves the second arm.

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