Motor drive control device, determination method, and program

Abstract

To enable the determination of the cause of load fluctuations in a motor drive control system. [Solution] The system comprises a motor, a mechanical load driven by the motor, a control unit for controlling the motor, a detection means for detecting drive data including input data and output data in a system including the motor and mechanical load, a state monitoring model calculation unit for calculating a state monitoring model composed of multiple parameters using the drive data, and a determination unit for determining the cause of fluctuations in the characteristics of a system including the motor and mechanical load based on changes in the parameters constituting the state monitoring model.

Description

Technical Field

[0001] The present disclosure relates to a motor drive control device, a determination method, and a program.

Background Art

[0002] Conventionally, as a method for monitoring load fluctuations in a motor drive control device, there is a method of monitoring the rotational speed in the motor drive control device. For example, as in Patent Document 1, there is a method of comparing the time from when the motor drive control device starts driving until it reaches the reference rotational speed with a preset reference start-up time for the speed.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In Patent Document 1, it is possible to monitor that the load has fluctuated in the motor drive control device, but there is a problem that the cause of the load fluctuation cannot be determined. By monitoring the rise time of the drive signal in the motor drive control system, it is possible to monitor the load fluctuation of the motor drive control system, but the cause of the load fluctuation in the motor drive control system cannot be determined.

[0005] The present disclosure has been made in view of the above problems, and an object thereof is to enable determination of the cause of load fluctuations in a motor drive control system.

Means for Solving the Problems

[0006] One embodiment of the present disclosure is a motor drive control device characterized by comprising: a motor; a mechanical load driven by the motor; a control unit for controlling the motor; a detection means for detecting drive data including input data and output data in a system including the motor and the mechanical load; a state monitoring model calculation unit for calculating a state monitoring model composed of a plurality of parameters using the drive data; and a determination unit for determining the cause of fluctuations in the characteristics of a system including the motor and the mechanical load based on changes in the parameters constituting the state monitoring model. [Effects of the Invention]

[0007] According to this disclosure, it is possible to determine the cause of load fluctuations in a motor drive control system. [Brief explanation of the drawing]

[0008] [Figure 1] Block diagram illustrating the functional configuration of a motor drive control device in the first embodiment of this disclosure. [Figure 2] A flowchart illustrating the sequence in which the functional blocks constituting the motor drive control device in the first embodiment of this disclosure function. [Figure 3] Diagram illustrating the concept of state monitoring in the first embodiment of this disclosure. [Figure 4] This figure illustrates the changes in the parameter Pa, which constitutes the state monitoring model in the first embodiment of this disclosure, due to temperature changes and changes in load torque. [Figure 5] This figure illustrates the changes in the parameter Pb, which constitutes the state monitoring model in the first embodiment of this disclosure, due to temperature changes and changes in load torque. [Figure 6] This figure illustrates the rate of change of gain from its initial value and the rate of change of dead time from its initial value with respect to temperature change when a state monitoring model is configured with a first-order lag plus dead time model in the first embodiment of this disclosure. [Figure 7]This figure illustrates the rate of change of gain from its initial value and the rate of change of dead time from its initial value with respect to the change in load torque when a state monitoring model is configured with a first-order lag plus dead time model in the first embodiment of this disclosure. [Figure 8] This figure illustrates the functional configuration of a printer transport system, which is an example of a motor-driven control device in a second embodiment of this disclosure. [Figure 9] Conceptual diagram illustrating a method for determining a state monitoring model in embodiments of this disclosure. [Modes for carrying out the invention]

[0009] The embodiments will be described in detail below with reference to the attached drawings. Note that the following embodiments do not limit the disclosures relating to the claims. While the embodiments describe multiple features, not all of these features are essential to the disclosure, and the features may be combined in any way. Furthermore, in the attached drawings, the same or similar configurations are given the same reference numeral, and redundant descriptions may be omitted.

[0010] <First Embodiment> The embodiments of this disclosure will be described in detail below with reference to the drawings. Note that the same reference numerals in the drawings indicate the same or corresponding parts.

[0011] Figure 1 is a block diagram illustrating the functional configuration of the motor drive control device 100 in the first embodiment. The motor drive control device 100 includes a control profile generation unit 101, a PWM data generation unit 102, a motor driver 103, a motor 104, a mechanical load 105, and an encoder 106. The motor drive control device 100 also includes a speed data measurement unit 107, a state monitoring model calculation unit 108, a load fluctuation cause determination unit (also simply called the "determination unit") 109, and a determination content notification unit 110.

[0012] The control profile generation unit 101 is a functional block that generates a speed command profile for driving the motor drive control device 100.

[0013] The PWM data generation unit 102 is a functional block that converts the speed command profile generated by the control profile generation unit 101 into PWM data. The PWM data is data that specifies the speed by duty.

[0014] The motor driver 103 rotationally drives the motor 104 based on the PWM data generated by the PWM data generation unit 102.

[0015] The motor 104 is rotationally driven by the motor driver 103. An example of the motor 104 is a DC motor, but the present disclosure is not limited to DC motors.

[0016] The mechanical load 105 is mechanical parts etc. connected to the motor 103, and examples include gears, pulleys, belts, rollers, etc.

[0017] The encoder 106 is a rotational speed detection means for detecting the rotational speed of the motor 104, and examples include rotary encoders, etc.

[0018] The speed data measurement unit 107 is a functional block that converts the detection value of the encoder 106 into speed data.

[0019] The state monitoring model calculation unit 108 receives voltage data from the PWM data generation unit 102. This voltage data, like the PWM data, indicates speed. Here, speed refers not to the target speed, but to the speed directly instructed to the motor. The state monitoring model calculation unit 108 also receives voltage data from the speed data measurement unit 107. This voltage data indicates the speed detected by the encoder 106. The state monitoring model calculation unit 108 is a functional block that calculates a state monitoring model 302 (see Figure 3) for monitoring the state of the motor drive control device 100. Here, the state monitoring model 302 shows the dynamic characteristics of the motor drive control device 100. The control profile generation unit 101 receives the PWM data generated by the PWM data generation unit 102 as input and outputs the speed data converted by the speed data measurement unit 107, and feedback control is performed. Therefore, the control profile generation unit 101 also functions as a control unit. The state monitoring model calculation unit 108 can also be realized by the processor reading and executing a program stored in a memory unit (not shown), such as ROM.

[0020] The load fluctuation cause determination unit 109 is a functional block that monitors changes in the parameters constituting the state monitoring model 302 calculated by the state monitoring model calculation unit 108, and determines the cause of the load fluctuation in the motor drive control device 100.

[0021] In Figure 1, the load fluctuation cause determination unit 109 is provided in the motor drive control device 100, but the load fluctuation cause determination unit 109 may also be a functional block provided outside the motor drive control device 100. An example of the load fluctuation cause determination unit 109 being provided in an external device is an external server when the motor drive control device 100 is a printer.

[0022] The determination content notification unit 110 is a functional block that notifies the user of the motor drive control device 100 of the content determined by the load fluctuation cause determination unit 109. An example of the determination content notification unit 110 is a display unit provided in a printer. In Figure 1, the determination content notification unit 110 is provided in the motor drive control device 100, but like the load fluctuation cause determination unit 109, the determination content notification unit 110 may be a functional block provided outside the motor drive control device 100. An example of the determination content notification unit being provided outside the motor drive control device 100 is a PC or smartphone connected externally when the motor drive control device 100 is a printer.

[0023] The state monitoring model 302 calculated by the state monitoring model calculation unit 108 in Figure 1 has multiple parameters. An example of the state monitoring model 302 is the first-order lag plus dead time model, which has three parameters: time constant, gain, and dead time. Here, dead time represents the delay in the rise time of the output value relative to the command value. Dead time is sometimes defined as the time it takes from the start of the control profile until it reaches 90% of the command value, but the definition in the first-order lag plus dead time model is not limited to the above definition. If the state monitoring model 302 is P, then the state monitoring model 302 constructed by the first-order lag plus dead time model is:

[0024]

number

[0025] It is expressed as a transfer function equation as shown above. Here, K is the gain, L is the dead time, and T is the time constant, which are parameters of the state monitoring model 302. Note that e is Napier's number and s is a complex number, and they are used in the same way as they are used in mathematical expressions using general transfer functions.

[0026] Figure 2 is a flowchart showing the sequence in which the functional blocks constituting the motor drive control device 100 shown in Figure 1 function in the first embodiment.

[0027] First, the motor drive control device 100 rotates the motor 104 and the mechanical load 105 using the speed command profile generated by the control profile generation unit 101 (S201).

[0028] Next, the state monitoring model calculation unit 108 acquires speed data (input speed data) that indicates the speed indicated by the PWM data generated by the PWM data generation unit 102 used for rotational drive of S201. The state monitoring model calculation unit 108 also acquires speed data (output speed data) that has been converted by the speed data measurement unit 107 used for rotational drive of S201 (S202). Here, depending on the control method, data other than speed data may be acquired. For example, position data may be acquired, or speed data and position data may be acquired. These will be collectively referred to as drive data. The drive data includes input data and output data, with input speed data corresponding to input data and output speed data corresponding to output data.

[0029] Next, using the input speed data acquired in S202 and the output speed data, the state monitoring model calculation unit 108 calculates the state monitoring model 302 using a specific calculation algorithm (S203).

[0030] Next, the load fluctuation cause determination unit 109 determines the cause of the load fluctuation in the motor drive control device 100 by monitoring the changes in the parameters of the state monitoring model 302 calculated in S203 (S204).

[0031] Next, the determination content display unit 110 notifies the user of the motor drive control device 100 of the content determined by the load fluctuation cause determination unit 109 (S205).

[0032] By repeating the flow from S201 to S205 described above, the motor drive control device 100 repeatedly calculates the state monitoring model 302 and determines the cause of the load fluctuation in the motor drive control device 100.

[0033] Figure 3 is a diagram illustrating the concept of state monitoring in the first embodiment. It shows how the state changes sequentially from state 1 to state 2 and then to state n over time. The state monitoring model calculation unit 108 in Figure 1 and the state monitoring model 302 calculated in flow S203 in Figure 3 mathematically represent the four functional blocks of the motor drive control device 100: the motor driver 103, motor 104, mechanical load 105, and encoder 106. In other words, the motor drive control system 301 in reality and the virtual state monitoring model 302 correspond to each other. Therefore, if there is a change in the motor drive control system 301 in reality, a change will also be observed in the virtual state monitoring model 302. Thus, by monitoring the virtual state monitoring model 302 calculated from the input speed data and output speed data acquired from the motor drive control system 301 in reality, it is possible to monitor changes in the motor drive control system 301.

[0034] Changes in the motor drive control system 301 are reflected in the state monitoring model 302, and the cause of the change in the motor drive control system 301 can be determined by using the differences in the change trends of the parameters that make up the state monitoring model 302. As an example, the case where the state monitoring model 302 is composed of parameters Pa and Pb is shown below.

[0035] Figure 4 shows the parameter Pa, with the horizontal axis representing operating time and the vertical axis representing the parameter value. The solid line shows the change due to temperature changes of the motor 104, and the dashed line shows the change due to load torque changes of the mechanical load 105. The parameter Pa changes when the temperature of the motor 104 in the motor drive control device 100 changes, but does not change due to factors other than temperature changes of the motor 104.

[0036] On the other hand, Figure 5 shows the parameter Pb, with the horizontal axis representing operating time and the vertical axis representing the parameter value. The solid line shows the change due to temperature changes in the motor 104, and the dashed line shows the change due to changes in the load torque of the mechanical load 105. The parameter Pb changes when the load torque of the mechanical load 105 in the motor drive control device 100 changes, but does not change due to factors other than changes in the load torque of the mechanical load 105.

[0037] Following the flowchart in Figure 2, the state monitoring model 302 is repeatedly calculated, and changes in parameters Pa and Pb are monitored. If the monitoring result shows that only parameter Pa has changed and parameter Pb has not changed, it can be determined from the difference in the change trends of parameters Pa and Pb that the motor drive control device 100 has changed due to a change in temperature in the motor 104. On the other hand, if the monitoring result shows that only parameter Pb has changed and parameter Pa has not changed, it can be determined from the difference in the change trends of parameters Pa and Pb that the motor drive control device 100 has changed due to a change in load torque in the mechanical load 105. Note that the above example shows how to determine the cause of change in the motor drive control device 100 based on the difference in the change trends of the parameters in a state monitoring model 302 composed of two parameters.

[0038] Here, we will explain an example of determining the cause of load fluctuations in the motor drive control device 100, where the state monitoring model 302 is a first-order lag plus dead time model having three parameters: time constant, gain, and dead time. In this example, two causes of load fluctuations are determined: a change in temperature in the motor 104 and a change in load torque in the mechanical load 105.

[0039] Figure 6 shows the rate of change of the gain from its initial value and the rate of change of the dead time from its initial value in the state monitoring model 302 with respect to the temperature change of the motor 104. In Figure 6, the horizontal axis represents the change in temperature, and the vertical axis represents the rate of change of the parameters. The solid line represents the rate of change of the gain from its initial value, and the dashed line represents the rate of change of the dead time from its initial value. With increasing temperature, the rate of change of the gain from its initial value increases, but the rate of change of the dead time from its initial value remains at 0%.

[0040] Figure 7 also shows the rate of change of the gain from its initial value and the rate of change of the dead time from its initial value in the state monitoring model 302 with respect to the change in load torque of the mechanical load 105. In Figure 7, the horizontal axis represents the change in load torque, and the vertical axis represents the rate of change of the parameters. Note that the line type classification in Figure 7 is the same as in Figure 6. With increasing load torque, the rate of change of the gain from its initial value increases, and the rate of change of the dead time from its initial value decreases.

[0041] Comparing Figures 6 and 7, the rate of change from the initial value of the gain increases in both the case of rising temperature and increasing load torque, but the change is larger when the load torque increases.

[0042] On the other hand, the rate of change of the dead time from its initial value remains constant when the temperature rises, but decreases when the load torque increases.

[0043] Therefore, when the state monitoring model 302 is configured as a first-order lag plus dead time model, it is possible to determine the cause of load fluctuations in the motor drive control device 100 by using the difference in the trends of change between gain and dead time. For example, if both gain and dead time increase, it can be determined that the temperature has risen. Also, if the gain increases and the dead time decreases, it can be determined that the load torque has increased.

[0044] Up to this point, we have introduced the first-order lag plus dead time model as an example of the state monitoring model 302. However, by increasing the number of parameters constituting the state monitoring model 302 to three or more, or by combining differences in the change trends of the parameters, it is possible to determine changes in the motor drive control device 100 from three or more causes.

[0045] <Second Embodiment> A second embodiment of this disclosure relates to a condition monitoring model corresponding to a printer transport system, which is an example of a motor drive control device.

[0046] An example of the motor drive control device 100 being part of the transport system in a printer will be described. Figure 8 shows the functional configuration of the transport system in a printer, which consists of a motor 801, a motor shaft 802, a motor pulley 803, a belt 804, a transport roller pulley 805, a transport roller shaft 806, and a transport roller 807. However, for the transport system in a printer, the power transmission from the motor 801 to the transport roller 807 is not limited to the belt 804, and a configuration using gears to transmit power is also acceptable. The state monitoring model 302 of the printer transport system shown in Figure 8 can be configured as shown in Equation 1.

[0047]

number

[0048]

number

[0049]

number

[0050] In this case, the parameters of Equation 1 are as follows:

[0051]

number

[0052] Each parameter of the state monitoring model 302 shown in Equation 1 corresponds to the motor 801, motor shaft 802, motor pulley 803, belt 804, transport roller pulley 805, transport roller shaft 806, and transport roller 807 shown in Figure 8. Therefore, when the state inside the transport system changes, the numerical values ​​of the corresponding parameters in the state monitoring model 302 change. Thus, by checking the changed parameters in the state monitoring model 302, it is possible to identify the location where the state change occurred in the printer's transport system. For example, in the state monitoring model 302, the torque coefficient K mtr If a change is observed, it is possible to identify that a change has occurred in the motor 801 in the transport system. Note that in the printer transport system shown in Figure 8, the sequence of events from when the transport system is driven to when the cause of the load fluctuation is determined via the state monitoring model and when the determination result is reported is the same as in Figure 2 of the first embodiment, so the explanation will be omitted.

[0053] <Method for calculating the state monitoring model> The input u and output y of the controlled object shown in Figure 9 correspond to the data u (see Figure 1) input from the PWM data generation unit 102 to the state monitoring model calculation unit 108 and the data y (see Figure 1) input from the speed data measurement unit 107 to the state monitoring model calculation unit 108, respectively. The internal model corresponds to the state monitoring model.

[0054] In the field of data-driven control research, FRIT (Fictious Reference Iterative Tuning) for internal model control is used.

[0055]

number

[0056] teeth,

[0057]

number

[0058] It is expressed as follows. Here,

[0059]

number

[0060] That is the case.

[0061] Evaluation function J FRIT teeth,

[0062]

number

[0063] The evaluation function J is as follows: FRIT By minimizing it using the least squares method,

[0064]

number

[0065] It is possible to calculate this.

[0066] In the first embodiment,

[0067]

number

[0068] In the second embodiment,

[0069]

number

[0070] That is the case.

[0071] Td, shown in Figure 9, is an internal component of the state monitoring model calculation unit 108, and in the first embodiment, for example,

[0072]

number

[0073] In the second embodiment, for example,

[0074]

number

[0075] That is the case.

[0076] Embodiments of the present disclosure may also be implemented by a computer in a system or device that includes one or more circuits (e.g., application-specific integrated circuits (ASICs)) for performing one or more functions of the embodiments described above, which are recorded on a storage medium (which may be more entirely referred to as a “non-temporary computer-readable storage medium”), and / or for performing one or more functions of the embodiments described above, and or by being implemented by a computer in a system or device that includes one or more circuits (e.g., application-specific integrated circuits (ASICs)) for performing one or more functions of the embodiments described above, which are recorded on a storage medium. The computer may comprise one or more processors (e.g., a central processing unit (CPU), a microprocessing unit (MPU)), and may include separate computers or a network of separate processors for reading and executing computer-executable instructions. Computer-executable instructions may be provided to the computer from, for example, a network or a storage medium. The storage medium may include, for example, one or more of the following: hard disks, random access memory (RAM), read-only memory (ROM), storage for distributed computing systems, optical discs (Compact Discs (CDs), Digital Multipurpose Discs (DVDs), or Blu-ray Discs (BDs) (registered trademarks)), flash memory devices, and memory cards.

[0077] <Technical Features of This Disclosure> This disclosure includes the following configurations, methods, and programs.

[0078] [Configuration 1] Motor and, Mechanical loads driven by motors, A control unit that controls the motor, A detection means for detecting drive data including input data and output data in a system including the motor and the mechanical load, A state monitoring model calculation unit calculates a state monitoring model composed of multiple parameters using the aforementioned drive data, A determination unit that determines the cause of the variation in characteristics in the system including the motor and the mechanical load based on changes in the parameters constituting the state monitoring model, A motor drive control device characterized by comprising:

[0079] [Configuration 2] The aforementioned state monitoring model represents the dynamic characteristics of the system including the motor and the mechanical load. A motor drive control device as described in Configuration 1.

[0080] [Configuration 3] There are differences in the change trends among the multiple parameters that constitute the state monitoring model, and the cause of the change is determined by using the differences in the change trends among the parameters. A motor drive control device as described in configuration 1 or 2.

[0081] [Structure 4] If the parameter that tends not to change with changes in load torque but tends to change with temperature changes changes, and the parameter that tends to change with changes in load torque but tends not to change with temperature changes does not change, the determination unit determines that the cause of the fluctuation is the temperature change. A motor drive control device according to any one of configurations 1 to 3.

[0082] [Composition 5] If the parameter, which tends not to change with changes in load torque but tends to change with temperature changes, does change, the determination unit determines that the cause of the change is the temperature change. A motor drive control device according to any one of configurations 1 to 4.

[0083] [Composition 6] The aforementioned state monitoring model has three parameters: time constant, gain, and dead time. A motor drive control device according to any one of configurations 1 to 5.

[0084] [Composition 7] The state monitoring model has three parameters: a time constant, a gain, and a dead time. By using the difference in the change trends of the time constant parameter and the dead time parameter, it determines whether the cause of the fluctuation is a rise in the motor temperature or a fluctuation in the mechanical load. A motor drive control device having any one of configurations 1 to 5.

[0085] [Structure 8] The drive data includes, as input data, data relating to the voltage for driving the motor. A motor drive control device according to any one of configurations 1 to 7.

[0086] [Composition 9] The aforementioned voltage corresponds to the PWM data specifying the speed of the motor. A motor drive control device as described in configuration 8.

[0087] [Configuration 10] The drive data includes the speed of the motor detected by the encoder as output data. A motor drive control device according to any one of configurations 1 to 9.

[0088] [Composition 11] The mechanical load includes a motor pulley, a belt, and a conveyor roller driven by the motor via a conveyor roller pulley. The drive data includes the speed of the transport roller as output data. A motor drive control device according to any one of configurations 1 to 10.

[0089] [method] Motor and, Mechanical loads driven by motors, A control unit that controls the motor, A method for determining the cause of fluctuations in a motor drive control device equipped with the following: A detection step for detecting drive data including input data and output data in a system including the motor and the mechanical load, A state monitoring model calculation step that calculates a state monitoring model composed of multiple parameters using the aforementioned drive data, A determination step of determining the cause of the variation in characteristics in the system including the motor and the mechanical load based on the change in the parameters constituting the state monitoring model, A method for determining the thumbnail.

[0090] [program] Motor and, Mechanical loads driven by motors, A control unit that controls the motor, A program for causing a computer to execute a method for determining the cause of fluctuations in a motor drive control device equipped with the following: A detection step for detecting drive data including input data and output data in a system including the motor and the mechanical load, A state monitoring model calculation step that calculates a state monitoring model composed of multiple parameters using the aforementioned drive data, A determination step of determining the cause of the variation in characteristics in the system including the motor and the mechanical load based on the change in the parameters constituting the state monitoring model, A program that causes a computer to execute something.

Claims

1. Motor and, Mechanical loads driven by motors, A control unit that controls the motor, A detection means for detecting drive data including input data and output data in a system including the motor and the mechanical load, A state monitoring model calculation unit calculates a state monitoring model composed of multiple parameters using the aforementioned drive data, A determination unit that determines the cause of the variation in characteristics in the system including the motor and the mechanical load based on changes in the parameters constituting the state monitoring model, A motor drive control device characterized by comprising:

2. The aforementioned state monitoring model represents the dynamic characteristics of the system including the motor and the mechanical load. The motor drive control device according to claim 1.

3. There are differences in the change trends among the multiple parameters that constitute the state monitoring model, and the cause of the fluctuation is determined by using the differences in the change trends among the parameters. The motor drive control device according to claim 1.

4. If the parameter that tends not to change with changes in load torque but tends to change with temperature changes changes, and the parameter that tends to change with changes in load torque but tends not to change with temperature changes does not change, the determination unit determines that the cause of the fluctuation is the temperature change. The motor drive control device according to claim 1.

5. If the parameter, which tends not to change with changes in load torque but tends to change with temperature changes, does change, the determination unit determines that the cause of the change is the temperature change. The motor drive control device according to claim 1.

6. The aforementioned state monitoring model has three parameters: time constant, gain, and dead time. The motor drive control device according to claim 1.

7. The state monitoring model has three parameters: a time constant, a gain, and a dead time. By using the difference in the change trends of the time constant parameter and the dead time parameter, it determines whether the cause of the fluctuation is a rise in the motor temperature or a fluctuation in the mechanical load. A motor drive control device according to claim 1.

8. The drive data includes, as input data, data relating to the voltage for driving the motor. The motor drive control device according to claim 1.

9. The aforementioned voltage corresponds to the PWM data specifying the speed of the motor. The motor drive control device according to claim 8.

10. The drive data includes the speed of the motor detected by the encoder as output data. The motor drive control device according to claim 1.

11. The mechanical load includes a motor pulley, a belt, and a conveyor roller driven by the motor via a conveyor roller pulley. The drive data includes the speed of the transport roller as output data. The motor drive control device according to claim 1.

12. Motor and, Mechanical loads driven by motors, A control unit that controls the motor, A method for determining the cause of fluctuations in a motor drive control device equipped with the following: A detection step for detecting drive data including input data and output data in a system including the motor and the mechanical load, A state monitoring model calculation step that calculates a state monitoring model composed of multiple parameters using the aforementioned drive data, A determination step of determining the cause of the variation in characteristics in the system including the motor and the mechanical load based on the change in the parameters constituting the state monitoring model, A method for determining the thumbnail.

13. Motor and, Mechanical loads driven by motors, A control unit that controls the motor, A program for causing a computer to execute a method for determining the cause of fluctuations in a motor drive control device equipped with the following: A detection step for detecting drive data including input data and output data in a system including the motor and the mechanical load, A state monitoring model calculation step that calculates a state monitoring model composed of multiple parameters using the aforementioned drive data, A determination step of determining the cause of the variation in characteristics in the system including the motor and the mechanical load based on the change in the parameters constituting the state monitoring model, A program that causes a computer to execute something.

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