Monitoring device for motor

Abstract

The monitoring device is provided with: a storage unit that stores a first model of the motor when the operating state of the motor is normal; and a model search unit that generates a second model of the motor when the operating state of the motor is abnormal. When the difference between the measured temperature of the temperature detector and the estimated temperature of the temperature detector based on the first model is out of the determination range, the model search unit adds the model of the addition member to the first model and generates a second model. The model search unit sets a model of a constituent part of the motor that exchanges heat with the model of the additional component and a coefficient relating to the heat transfer of the additional component so that the estimated temperature of the temperature detector based on the second model corresponds to the measured temperature of the temperature detector.

Description

Technical Field

[0001] The present invention relates to a monitoring device for an electric motor. Background Art

[0002] The operating state of a machine can be acquired by attaching a sensor to the machine. On the other hand, it is known to estimate the operating state of a machine by simulation without actually driving the machine (for example, Japanese Patent Application Laid-Open No. 63-106861).

[0003] In a machine, an electric motor is arranged to operate a predetermined component. It is known that the temperature of the electric motor rises as it is driven. If the temperature of the electric motor becomes too high, the electric motor may not operate accurately or the components of the electric motor may be damaged. Therefore, it is preferred to drive the electric motor within an appropriate temperature range (for example, Japanese Patent Publication No. 2010-268644).

[0004] The actual temperature when the motor is driven can be detected by a temperature detector installed on the components of the motor. Alternatively, a simulation for estimating the temperature of the motor is known. In the simulation, in order to estimate the temperature of the motor, a method using a thermal model that takes into account the heat capacity of the components and the heat transfer between the components is known (for example, International Publication No. 2020 / 188650 and Japanese Patent Publication No. 2008-109816).

[0005] In the thermal model, a heat transfer coefficient or thermal resistance is set between each component, and the heat transfer between the components is calculated. In the thermal model, the temperature of each component can be calculated. In the case of electric motors, it is known to use a thermal model including a stator core, a coil, and a rotor core to estimate the temperature when the motor is driven.

[0006] Prior art literature

[0007] Patent Literature

[0008] Patent Document 1: Japanese Patent Application Laid-Open No. 63-106861

[0009] Patent Document 2: Japanese Patent Application Publication No. 2010-268644

[0010] Patent Document 3: International Publication No. 2020 / 188650

[0011] Patent Document 4: Japanese Patent Application Publication No. 2008-109816 Summary of the invention

[0012] Problems to be solved by the invention

[0013] When the motor is driven, the stator core, the coil fixed to the stator core, the bearing, etc. generate heat. In addition, when the components of the motor are damaged, the damaged components generate heat and the temperature of the motor may rise abnormally. In order to identify the portion generating heat during the driving of the motor, a temperature sensor can be installed on each component of the motor. In addition, by monitoring the temperature of the components using the output of the temperature sensor, the portion generating abnormal heat can be identified.

[0014] However, if the temperature sensor is installed on each component of the motor, a plurality of temperature sensors are required. In addition, considering the structure of the motor, it is sometimes difficult to install the temperature sensor on the internal components or rotating components of the motor.

[0015] Means for solving problems

[0016] The monitoring device of the motor of the disclosed method is provided with a state acquisition unit, which acquires the operation state of the motor including the measured temperature detected by the temperature detector installed on the motor. The monitoring device is provided with a temperature estimation unit that calculates the estimated temperature of the temperature detector based on the model of the motor. The monitoring device is provided with a storage unit that stores the first model of the motor when the operation state of the motor is normal. The monitoring device is provided with a model search unit that generates a second model of the motor when the operation state of the motor is abnormal. The model of the motor includes a model of the rotor, a model of the stator core, a model of the coil, and a model of the temperature detector as models of the components of the motor. The heat capacity is set in the model of at least one component. The coefficient related to the heat transfer between the models of the components is set. The model search unit includes a component adding unit, which adds the model of the additional component that performs heat exchange with the model of the component of the motor to the first model to generate the second model when the difference between the measured temperature of the temperature detector and the estimated temperature of the temperature detector based on the first model is out of a predetermined judgment range. The model search unit includes a setting unit that sets a model of a component of the motor that exchanges heat with the model of the additional component and a coefficient related to heat transfer of the additional component so that the estimated temperature of the temperature detector based on the second model corresponds to the measured temperature of the temperature detector.

[0017] Effects of the Invention

[0018] According to the monitoring device for the electric motor of the aspect of the present disclosure, it is possible to provide information for estimating a portion where an abnormality has occurred. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a block diagram of a monitoring device for a machine and a motor in an embodiment.

[0020] Figure 2It is a schematic cross-sectional view of the first electric motor in the embodiment.

[0021] Figure 3 This is a first model of the first electric motor in the embodiment.

[0022] Figure 4 It is a graph explaining the operation pattern of the electric motor for setting the parameters in the first model of the electric motor.

[0023] Figure 5 This is a first model of the second electric motor in the embodiment.

[0024] Figure 6 This is a graph of simulation results using the parameters set by the parameter calculation unit.

[0025] Figure 7 This is a graph showing the temperature change of the temperature detector when the operation state of the motor is normal.

[0026] Figure 8 This is a graph showing the temperature change of the temperature detector when the operating state of the motor is abnormal.

[0027] Fig. 9 This is a second model obtained by adding additional components to the first model of the first electric motor.

[0028] Fig.10 This is a second model in which an additional component exchanges heat with multiple components of the motor.

[0029] Fig.11 is another second model of the first motor. DETAILED DESCRIPTION

[0030] Reference Figures 1 to 11 , a motor monitoring device in an embodiment is described. The motor monitoring device in this embodiment has a function of estimating the temperature of a predetermined component of the motor using a model of the motor. In particular, the motor monitoring device estimates the temperature output by a temperature detector installed in a component of the motor.

[0031] In this embodiment, the temperature actually measured by the temperature detector is referred to as the measured temperature. In addition, the temperature of the component estimated using the model of the motor is referred to as the estimated temperature. In this embodiment, an example of estimating the temperature of the temperature detector that detects the temperature of the stator coil among the components of the motor is described.

[0032] The motor monitoring device of the present embodiment provides information for estimating the abnormal portion to the operator or other devices. For example, the operator estimates the abnormal portion by observing the information displayed on the display unit of the motor monitoring device.

[0033] Figure 1 This is a block diagram of a monitoring device for a machine and a motor in this embodiment. The machine 1 in this embodiment includes a motor 10 for driving components of the machine 1 and a machine control device 41 for controlling the machine 1. The machine control device 41 in this embodiment is composed of a processing device (computer). The machine control device 41 includes a CPU (Central Processing Unit) as a processor. The machine control device 41 has a RAM (Random Access Memory) and a ROM (Read Only Memory) connected to the CPU via a bus.

[0034] The machine 1 of this embodiment is a numerical control type machine. The machine 1 is driven according to the instruction statement recorded in the pre-generated action program 45. The machine control device 41 includes a storage unit 42 that stores the action program 45 and an action control unit 43 that generates an action instruction of the motor 10 according to the action program 45. The machine 1 includes a drive device 44, which includes a circuit that supplies power to the motor 10 based on the action instruction generated by the action control unit 43. The motor 10 is driven by the power supplied by the drive device 44.

[0035] The storage unit 42 can be composed of a non-temporary storage medium that can store information. For example, the storage unit 42 can be composed of a storage medium such as a volatile memory, a non-volatile memory, a magnetic storage medium, or an optical storage medium. The action control unit 43 is equivalent to a processor driven according to the action program 45. The processor reads the action program 45 and implements the control determined by the action program 45, thereby functioning as the action control unit 43.

[0036] As such a machine 1, any machine having a motor 10 can be used. For example, a machine tool that processes a workpiece can be exemplified as the machine 1. As the motor 10, a spindle motor that rotates a tool or a feed axis motor that moves a table or a spindle head along a predetermined coordinate axis can be exemplified.

[0037] Figure 2 2 is a cross-sectional view of the first electric motor of the present embodiment. Figure 1 and Figure 2 The first motor 10 is a synchronous motor having a rotor 11 with a magnet 18. The motor 10 includes a rotor 11 and a stator 12. The stator 12 includes a stator core 20 formed of a magnetic material and a coil 16 fixed to the stator core 20. The stator core 20 is formed of, for example, a plurality of magnetic steel plates stacked in the axial direction of the shaft 13. The coil 16 includes, for example, a winding wound on the stator core 20 and a resin portion that fixes the winding.

[0038] The rotor 11 is fixed to a rod-shaped shaft 13. The rotor 11 is fixed to the outer peripheral surface of the shaft 13 and includes a rotor core 17 formed of a magnetic material and a plurality of magnets 18 fixed to the rotor core 17. The magnets 18 of this embodiment are permanent magnets.

[0039] The shaft 13 is connected to other components to transmit rotational force. The shaft 13 rotates around the rotation axis RA. The shaft 13 is supported by bearings 14 and 15 as bearings. In this embodiment, in the motor 10, the side where the shaft 13 is connected to other components is called the front side. In addition, the side opposite to the front side is called the rear side. Figure 2 In the example shown, arrow 91 indicates the front side of the electric motor 10 .

[0040] The motor 10 includes a housing 21 at the front side and a housing 22 at the rear side. The stator core 20 of the stator 12 is supported by the housings 21 and 22. The housing 21 supports the bearing 14. A bearing support member 24 supporting the bearing 15 is fixed to the housing 22. The housings 21 and 22 support the shaft 13 rotatably via the bearings 14 and 15. A rear cover 23 that closes the space inside the housing 22 is fixed to the end of the rear side of the housing 22.

[0041] A rotation position detector 32 for detecting the rotation position or rotation speed of the shaft 13 is disposed at the rear end of the shaft 13. The rotation position detector 32 of the present embodiment is constituted by an encoder. A temperature detector 31 for detecting the temperature of the coil 16 is fixed to the coil 16 of the stator 12. The temperature detector 31 of the present embodiment is constituted by a thermistor. The outputs of the temperature detector 31 and the rotation position detector 32 are input to the mechanical control device 41.

[0042] As components of the motor 10, there can be exemplified a rotor 11, a rotor core 17, a magnet 18, a stator 12, a stator core 20, a coil 16, a housing 21, 22, a shaft 13, a rear cover 23, a bearing support member 24, bearings 14, 15, a temperature detector 31, and a rotation position detector 32. As components of the motor 10, there is no limitation to this form, and any components constituting the motor 10 can be used. For example, a housing covering the stator can also be used.

[0043] The motor monitoring device 2 of the present embodiment calculates an estimated temperature obtained by estimating the temperature output from the temperature detector 31 disposed in the motor 10. In the present embodiment, the temperature output from the temperature detector 31 disposed in the coil 16 of the stator 12 is estimated. In particular, the motor monitoring device 2 estimates the change in the temperature of the temperature detector 31 with respect to the passage of time.

[0044] The monitoring device 2 for the motor is composed of a calculation processing device (computer) including a CPU as a processor. The monitoring device 2 includes a storage unit 51 that stores information related to the monitoring of the motor 10. The storage unit 51 can be composed of a non-temporary storage medium that can store information. For example, the storage unit 51 can be composed of a storage medium such as a volatile memory, a non-volatile memory, a magnetic storage medium, or an optical storage medium. The monitoring device 2 includes a display unit 52 that displays information related to the motor 10. The display unit 52 can be composed of any display panel such as a liquid crystal display panel or an organic EL (Electro Luminescence) display panel.

[0045] The monitoring device 2 includes a temperature estimating unit 53 that calculates an estimated temperature of the temperature detector 31. The temperature estimating unit 53 includes a loss calculating unit 54 that calculates a heat value caused by the primary copper loss of the coil 16 and a heat value caused by the iron loss of the stator core 20 based on an operation command of the motor 10. The temperature estimating unit 53 includes a temperature calculating unit 55 that estimates the temperature of the temperature detector 31 using a model (thermal model) of the motor. The temperature calculating unit 55 calculates the estimated temperature of the temperature detector 31 based on the heat value caused by the primary copper loss and the iron loss, the heat capacity of the model of each component, and the coefficient related to heat transfer between the models of the component.

[0046] The monitoring device 2 in this embodiment has a function of calculating parameters included in the model of the motor. The parameters include the heat capacity set in the model of the component of the motor 10 and the coefficient related to the heat transfer between the models of the component. The monitoring device 2 includes a parameter calculation unit 63, which calculates the parameters included in the first model of the motor when the operating state of the motor is normal.

[0047] The monitoring device 2 includes a state acquisition unit 62 for acquiring the operating state of the motor 10 when the motor 10 is actually driven. The operating state of the motor 10 includes the measured temperature detected by the temperature detector 31 installed on the motor 10. The operating state of the motor 10 includes the operating command of the motor 10 generated by actually driving the motor 10 and the rotation speed output from the rotation position detector 32. The operating command of the motor 10 can be obtained from the operation control unit 43. In addition, the state acquisition unit 62 can acquire the temperature of the outside air from the outside air temperature detector 33 that detects the temperature of the environment in which the machine 1 is arranged. The outside air temperature detector 33 is configured to detect the temperature around the machine 1, for example.

[0048] The parameter calculation unit 63 of the present embodiment calculates parameters so that the change in the estimated temperature of the temperature detector calculated by the motor model corresponds to the change in the actual measured temperature. The parameter calculation unit 63 of the present embodiment can set the parameters of the motor model by machine learning.

[0049] The loss calculation unit 54 of the temperature estimation unit 53 calculates the heat generated by the coil 16 and the stator core 20 based on the operation command generated by the operation control unit 43 and the rotation speed detected by the rotation position detector 32. In addition, the temperature calculation unit 55 calculates the estimated temperature of the temperature detector based on the heat generated by the coil 16 and the stator core 20.

[0050] The parameter calculation unit 63 calculates the estimated temperature of the temperature detector 31 by using the temperature estimation unit 53. The parameter calculation unit 63 includes an evaluation unit 66 that evaluates the estimated temperature of the temperature detector 31 by comparing the estimated temperature of the temperature detector 31 with the measured temperature of the temperature detector 31 acquired by the state acquisition unit 62. The parameter calculation unit 63 includes a parameter changing unit 67 that changes the value of the parameter based on the evaluation result of the evaluation unit 66.

[0051] The temperature estimation unit 53, the loss calculation unit 54, and the temperature calculation unit 55 are each equivalent to a processor driven according to a program. The state acquisition unit 62, the parameter calculation unit 63, the evaluation unit 66, and the parameter change unit 67 are each equivalent to a processor driven according to a program. The processor functions as each unit by implementing the control specified by the program.

[0052] Figure 3 The first model represents the first model obtained by modeling the transfer of heat of the first motor in the present embodiment. The first model of the motor is a thermal model that simulates the normal operating state of the motor. The thermal model of the motor includes models of multiple components. The thermal model includes parameters such as the heat capacity of the components and the coefficient related to the heat transfer between the components. The first model 10a of the motor in the present embodiment includes models of the main structural parts that constitute the first motor 10. The model 10a of the motor includes a model 11a of the rotor, a model 20a of the stator core, and a model 16a of the coil wound on the stator core. In addition, the model 10a of the motor includes a model 31a of a temperature detector for detecting the temperature of the coil 16.

[0053] Reference Figure 2, an air layer exists between the rotor 11 and the stator core 20. Also, an air layer exists between the rotor 11 and the coil 16. The model 10a of the motor in the present embodiment includes a model 35a of the air layer. In addition, the model 10a of the motor includes a model 36a of the outside air as a model of the air around the motor 10. In this way, in the model of the motor in the present embodiment, the air layer and the outside air are generated as models of the components of the motor.

[0054] The temperature detected by the temperature detector 31 is substantially equal to the temperature of the coil 16. However, under predetermined conditions, due to the small heat capacity of the temperature detector 31, the temperature detected by the temperature detector 31 may be different from the temperature of the coil 16. Therefore, in the present embodiment, a model 31a of the temperature detector is also generated as one of the models of the component for the temperature detector 31. Alternatively, the heat capacity of the temperature detector 31 may be set to zero, and the temperature of the model of the temperature detector may be calculated to be the same as the temperature of the model of the component to which the temperature detector is mounted.

[0055] In the model 10a of the motor, a plurality of parameters including heat capacity and coefficients related to heat transfer are set. Heat capacity is set in the model of at least one component. In each of the models of the coil 16a, the stator core 20a, the air layer 35a, the rotor 11a, and the temperature detector 31a, a temperature T is set as a variable. 1 , T 2 , T 3 , T 4 , T 5 and the heat capacity C as a constant 1 , C 2 , C 3 , C 4 , C 5 In addition, the temperature T is set as a variable in the model 36a of the outside air. r .

[0056] The heat of one component of the motor 10 is transferred to other components. Coefficients related to heat transfer are set between the models of the components of the motor 10. As the coefficient related to heat transfer, a heat transfer coefficient or a coefficient obtained by multiplying the heat transfer coefficient by the contact area between the components can be used. In the example here, a coefficient obtained by multiplying the heat transfer coefficient by the contact area is determined.

[0057] A coefficient ha related to heat transfer is set between the model 20a of the stator core and the model 16a of the coil. A coefficient hc1 related to heat transfer is set between the model 35a of the air layer and the model 16a of the coil. A coefficient hc2 related to heat transfer is set between the model 35a of the air layer and the model 20a of the stator core. A coefficient hc3 related to heat transfer is set between the model 35a of the air layer and the model 11a of the rotor. A coefficient hd related to heat transfer is set between the model 16a of the coil and the model 31a of the temperature detector. In addition, in order to simulate the release of heat from the stator core 20 to the outside air, a coefficient hb related to heat transfer is set between the model 20a of the stator core and the model 36a of the outside air.

[0058] In the motor model 10a of the present embodiment, the primary copper loss P generated in the coil 16 of the stator 12 is considered as the heat generated by the components. c1 The heat generated by the primary copper loss is input to the coil model 16a. In addition, the iron loss P of the stator core 20 generated by the magnetic force of the magnet 18 of the rotor 11 is considered. i The model 20a of the stator core is input with heat generated by iron loss.

[0059] Heat moves between components such as the coil and the stator core depending on the magnitude of the coefficient related to heat transfer. In addition, the temperature of each component rises or falls based on the difference between the input heat amount and the output heat amount. Figure 3 The temperature change rate of each component of the first model 10a of the first electric motor shown can be expressed by the following equations (1) to (5). In each component, the temperature change rate can be calculated by dividing the difference between the input heat amount and the output heat amount by the heat capacity.

[0060] [Formula 1]

[0061]

[0062]

[0063]

[0064]

[0065]

[0066] T 1 : Coil temperature C 1 : Heat capacity of coil

[0067] T 2 : Temperature of stator core C 2 : Heat capacity of stator core

[0068] T 3 : Temperature of the air layer C 3 : Heat capacity of the air layer

[0069] T 4 : Rotor temperature C 4 : Heat capacity of the rotor

[0070] T 5 : Temperature of the temperature detector C 5 : Heat capacity of temperature detector

[0071] T r : Temperature of outside air

[0072] ha, hb, hcl, hc2, hc3, hd: coefficients related to heat transfer

[0073] P e 1: Primary copper loss

[0074] P i : Iron loss

[0075] Heat capacity of components C 1 , C 2 , C 3 , C 4 , C 5 The coefficients ha, hb, hc1, hc2, hc3, and hd related to heat transfer are obtained by multiplying the heat transfer coefficient by the contact area. The coefficients ha, hb, hc1, hc2, hc3, and hd are constants and can be determined in advance. The loss calculation unit 54 of the temperature estimation unit 53 calculates the primary copper loss P in the coil 16 as described later. c1 and the iron loss P in the stator core i The temperature calculation unit 55 of the temperature estimation unit 53 can calculate the amount of change in temperature within the micro time dt based on the above-mentioned equations (1) to (5).

[0076] Next, the primary copper loss P included in equations (1) and (2) is c1 and iron loss P i The calculation method of the motor 10 is described below. The rotation speed of the motor 10 and the load factor (ratio to the maximum load) of the motor 10 can be set in advance by the operator according to the operation performed by the machine. The loss calculation unit 54 of the temperature estimation unit 53 calculates the primary copper loss P c1 and iron loss P i Table 1 shows the loss map used to calculate the loss.

[0077] [Table 1]

[0078] Table 1 Loss mapping

[0079]

[0080] Table 1 shows the loss at maximum output, the loss at no load, and the current at maximum output relative to the rotation speed (rotation speed) of the motor 10. m This is the loss when the motor load factor is 100%, and is a value determined by the motor's rotation speed. n This is the loss when the motor load factor is zero and depends on the motor rotation speed. The current I at maximum output m It is the current value when the load factor is 100% at each rotation speed. The loss map shown in Table 1 can be generated by actually driving the motor. This loss map can be stored in the storage unit 51 of the monitoring device 2, for example.

[0081] The loss calculation unit 54 calculates the primary copper loss P c1 and iron loss P i The total loss P t Total loss P t It can be calculated by the following formula (6) and formula (7).

[0082] [Formula 2]

[0083] P t =k2·LF 2 +k1·LF+P n …(6)

[0084] k1=P m -P n -k2…(7)

[0085] P t : Total loss

[0086] P m : Loss at maximum output

[0087] P n : Loss at no load

[0088] LF: Motor load factor

[0089] k1, k2: constants

[0090] Total loss P t The loss P at maximum output can be m , loss at no load P n Since the rotation speed and load factor of the motor are determined, the loss P at maximum output is calculated according to Table 1. m and the loss at no load Pn The constants k1 and k2 can be determined in advance by the operator. c1 It can be calculated by the following formula (8) and formula (9).

[0091] [Formula 3]

[0092] P c1 = r1·I 2 …(8)

[0093] I=I m ·LF…(9)

[0094] P c1 :Primary copper loss

[0095] I: Current

[0096] r1: primary resistance

[0097] I m : Current at maximum output

[0098] Primary copper loss P c1 This corresponds to the Joule heat of the current flowing through the coil 16. In addition, the current I flowing through the coil 16 can be reduced by the current I at the maximum output. m Multiply by the motor load factor LF to calculate. Current I at maximum output m It can be obtained from Table 1. Here, the primary resistance r1 of the coil 16 is measured in advance. Next, the iron loss P i It can be calculated by the following formula (10). Iron loss P i can be obtained by t Subtract the primary copper loss P c1 to calculate.

[0099] [Formula 4]

[0100] P i =P t -P c1 …(10)

[0101] P i : Iron loss

[0102] The temperature estimation unit 53 acquires the operation mode of the motor including the rotation speed and the load factor for driving the machine 1 from the state acquisition unit 62. First, the temperature calculation unit 55 of the temperature estimation unit 53 can calculate the temperature T of each component. 1 ~T 5 For example, the temperature calculation unit 55 sets the temperature T 1 ~T 5 Set to normal outside air temperature T r The outside air temperature Tr It can be determined in advance according to the place where the machine 1 is arranged.

[0103] The loss calculation unit 54 of the temperature estimation unit 53 calculates the primary copper loss and the iron loss based on the rotation speed and the load factor of the motor in the operation mode. Then, the temperature calculation unit 55 can calculate the temperature T of the temperature detector 31 within the micro time dt by solving the above equations (1) to (5). 5 In this way, the operator can determine the operation mode of the motor and estimate the change in the temperature of the temperature detector over time when the motor is operated in the operation mode.

[0104] However, in the motor model 10a of the present embodiment, it is sufficient that the temperature of one of the multiple components of the motor can be estimated with high accuracy. The temperature of components other than the one component may deviate from the actual temperature. In this example, it is sufficient that the temperature T of the temperature detector model 31a can be estimated with high accuracy. 5 The temperature T of the coil model 16a is 1 , the temperature T of the stator core model 20a 2 , the temperature T of the model 35a of the air layer 3 and the temperature T of the rotor model 11a 4 It is also possible to deviate from the actual temperature.

[0105] Furthermore, the heat capacity C set in the motor model 10a is 1 ~C 5 The coefficients ha, hb, hc1, hc2, hc3, and hd set between the components and related to heat transfer have inherent values ​​depending on the material, shape, and arrangement of the components. However, in the model 10a of the motor of the present embodiment, at least some of the parameters of the plurality of heat capacities and the plurality of heat transfer-related coefficients may be set to values ​​deviating from the actual heat capacities or the actual heat transfer-related coefficients.

[0106] Each parameter is set to the temperature T of the model 31a of the temperature detector. 5 The change in temperature corresponds to the change in actual temperature. For example, even if the temperature of the coil and the stator core is farther away from the actual temperature, the parameters of the model of the motor can be set in such a way that the temperature of the temperature detector represents a value close to the actual temperature. In addition, as a result of calculating the heat capacity and the coefficient related to heat transfer, the total heat capacity of the components and the coefficient related to the total heat transfer can also correspond to the actual heat capacity and the coefficient related to the actual heat transfer with high accuracy. Moreover, when the temperature estimating unit estimates the temperature of the components, the temperature of all the components can also correspond to the actual temperature of the components with high accuracy.

[0107] The monitoring device 2 of the motor of the present embodiment is configured to be switchable and implement a normal model generation mode, in which the parameters of the first model of the motor are calculated when the motor is in a normal operating state, and an abnormal model generation mode, in which the second model of the motor is generated when the motor is in an abnormal operating state. In the normal model generation mode, parameters including coefficients related to heat transfer and thermal capacities of components are set in the first model 10a of the motor.

[0108] Reference Figure 1 , the parameter calculation unit 63 of the present embodiment generates a first model of the motor in the normal model generation mode. The parameter calculation unit 63 sets the heat capacity, the coefficient related to heat transfer, and the constants k1 and k2 in the equations (6) and (7) included in the model 10a of the motor. The operator actually drives the motor 10 according to a predetermined operation mode. The state acquisition unit 62 acquires the load factor of the motor 10, the rotation speed of the motor 10, and the temperature output from the temperature detector 31 as the state of the motor 10. In addition, the state acquisition unit 62 acquires the temperature of the outside air from the outside air temperature detector 33.

[0109] Figure 4 A graph showing an operation pattern when the motor is driven in order to set the parameters included in the first model of the motor according to the present embodiment. Figure 4 1 shows an operation mode when there is no load. In this operation mode, no load is applied to the motor 10, and the rotation speed of the motor 10 is gradually increased. The rotation speed of the motor 10 is increased by temporarily increasing the load factor of the motor at predetermined time intervals.

[0110] The temperature detected by the temperature detector 31 gradually increases. At times t1 to t7, the rotation speed of the motor 10 is increased by temporarily increasing the load factor of the motor 10. The state acquisition unit 62 acquires the operating state of the motor 10 and the temperature output from the temperature detector 31 during the period of gradually increasing the rotation speed of the motor 10. More specifically, the state acquisition unit 62 acquires the load factor of the motor 10, the rotation speed of the motor 10, and the temperature output from the temperature detector 31 at predetermined intervals, and stores them in the storage unit 51. In the present embodiment, a certain outside air temperature is used, but it is not limited to this method. The state acquisition unit 62 may also acquire the outside air temperature from the outside air temperature detector 33 at intervals.

[0111] Reference Figure 1The state acquisition unit 62 acquires the torque command included in the motion command generated by the motion control unit 43 of the mechanical control device 41. The torque command corresponds to the load factor of the motor 10, so the state acquisition unit 62 can calculate the load factor based on the torque command.

[0112] The parameter calculation unit 63 calculates the parameters of the motor model 10a based on the variables acquired by the state acquisition unit 62. The parameter calculation unit 63 of the present embodiment calculates the parameters including the heat capacity C based on the heat generated in the coil 16 and the stator core 20 and the temperature detected by the temperature detector 31. 1 , C 2 , C 3 , C 4 , C 5 and parameters of coefficients ha, hb, hc1, hc2, hc3, and hd related to heat transfer. In addition, the parameter calculation unit 63 calculates constants k1 and k2 in equations (6) and (7) as parameters. The parameter calculation unit 63 calculates the parameters in such a way that the change in the estimated temperature of the model 31a of the temperature detector during the simulation is close to the change in the actual measured temperature.

[0113] The parameter calculation unit 63 sets the initial value of each parameter. The initial value of the parameter can be set by any method. The parameter calculation unit 63 uses the loss calculation unit 54 to calculate the heat generated by the primary copper loss of the coil 16 and the heat generated by the iron loss of the stator core 20. The loss calculation unit 54 calculates the primary copper loss P based on the rotation speed of the motor 10 and the load factor of the motor 10 obtained by the state acquisition unit 62, using Table 1 and equations (6) to (10). c1 and iron loss P i .

[0114] Calculate the copper loss P c1 and iron loss P i The constants k1 and k2 are included in the equations (6) and (7). Furthermore, the loss calculation unit 54 calculates the loss in the predetermined micro time dt, that is, the heat generated in the micro time. In this way, the loss calculation unit 54 calculates the primary copper loss P in the equations (1) and (2) based on the measured values ​​including the motor operation command (load factor) and the output of the rotation position detector 32. c1 and iron loss P i .

[0115] The parameter calculation unit 63 estimates the temperature of the components using the temperature calculation unit 55. The temperature calculation unit 55 calculates the estimated temperature of the temperature detector 31 based on the first model 10a of the motor using the various parameters and the loss calculated by the loss calculation unit 54. That is, the temperature of the temperature detector model 31a is estimated by simulation.

[0116] The temperature calculation unit 55 can calculate the change in the estimated temperature detected by the temperature detector 31 with the passage of time after the start of the drive of the motor 10 based on the temporarily set parameters. The temperature of the model of each component of the motor 10 can be calculated using the differential equations of the above-mentioned equations (1) to (5). The initial value of the temperature of the model of each component can be set to, for example, the temperature of the outside air when the drive of the motor 10 is started, that is, the room temperature.

[0117] The evaluation unit 66 of the parameter calculation unit 63 compares the temperature (estimated temperature) of the model 31a of the temperature detector calculated by the temperature calculation unit 55 with the measured temperature actually measured by the temperature detector 31, thereby evaluating the parameters temporarily set in the first model 10a of the motor. In the example here, the evaluation unit 66 does not evaluate variables other than the temperature of the model 31a of the temperature detector, but only evaluates the temperature of the model 31a of the temperature detector. As long as the change in the temperature of the model 31a of the temperature detector is close to the change in the actual temperature, at least part of the temperatures of other components are not evaluated.

[0118] Next, the parameter changing unit 67 of the parameter calculating unit 63 changes the parameters based on the evaluation result of the evaluating unit 66. And based on the changed parameters, the calculation of the loss by the loss calculating unit 54, the calculation of the estimated temperature of the model of the temperature detector of the temperature calculating unit 55, the evaluation by the evaluating unit 66, and the change of the parameters by the parameter changing unit 67 are repeated by the same calculation as above. When the evaluation by the evaluating unit satisfies the predetermined conditions, the parameters can be determined as the final parameters.

[0119] Here, the number of combinations of multiple parameters in the model 10a of the motor is very large. Multiple parameters can be determined by a machine learning method. For example, multiple parameters can be set by a Bayesian optimization method. In Bayesian optimization, an objective function that is an evaluation object is generated for an explanatory variable containing a parameter that becomes an input. Then, a parameter that is predicted to be the minimum or maximum of the objective function is searched and set. By repeating the search for the parameter, the optimal value of the parameter can be set. In addition, the range of setting each parameter can be determined in advance.

[0120] In the example here, regarding the temperature of the temperature detector 31, the difference between the temperature of the model 31a of the temperature detector estimated by the model 10a of the motor (estimated temperature) and the measured temperature detected by the actual temperature detector 31 is set as the objective function. That is, regarding the temperature of the temperature detector 31, the objective function can use the difference between the predicted value calculated according to equations (1) to (5) based on the temporarily set parameters and the actual measured value detected by the temperature detector 31. As the objective function, for example, the average value of the difference in a small time period can be used. Then, the parameter changing unit 67 searches for the next parameter so that the objective function becomes smaller.

[0121] In Bayesian optimization, parameter search and parameter evaluation can be repeated. If the objective function is within a predetermined judgment range, the evaluation unit 66 can adopt the value of the parameter at that time. On the other hand, when the objective function deviates from the predetermined judgment range, the next parameter search can be performed. In the Bayesian optimization method, since the search is performed while predicting the region where the solution exists, the amount of computational processing can be suppressed.

[0122] The parameters included in the model 10a of the motor can be set by any method other than the setting of the parameters based on Bayesian optimization. For example, the range of setting each parameter can be predetermined. The parameter changing unit 67 of the parameter calculation unit 63 randomly sets a plurality of parameters within the range of the parameters. The temperature calculation unit 55 estimates the temperature of the model 31a of the temperature detector based on the set parameters. The evaluation unit 66 can evaluate the set parameters based on the measured value of the temperature obtained from the temperature detector 31. Such a parameter setting method is called a random search method.

[0123] Alternatively, the parameter changing unit 67 can set the parameter at predetermined intervals within the range of the set parameter. The temperature calculating unit 55 estimates the temperature of the model 31a of the temperature detector using the set parameter. The evaluating unit 66 evaluates all combinations of discretely set parameters. This method is called a grid search method.

[0124] In the random search method or the grid search method, similarly to the Bayesian optimization method, the evaluation unit 66 can use the temperature of the temperature detector 31 as the object of evaluation. If the objective function is within a predetermined determination range, the evaluation unit 66 can adopt the value of the parameter at that time. Alternatively, the evaluation unit 66 can adopt the parameter that is optimal for the objective function. The evaluation unit 66 can determine the parameter in the model 10a of the motor that the estimated temperature of the temperature detector 31 is very consistent with the measured temperature detected by the actual temperature detector 31.

[0125] In the present embodiment, the parameters are set in such a way that the change in the temperature detected by the temperature detector 31 can be estimated with high accuracy. In the present embodiment, the temperature of the components other than the temperature detector 31 may deviate from the actual temperature, so in the evaluation of the parameters, only the temperature of the temperature detector that detects the temperature of the coil can be evaluated. Therefore, the parameters can be set in a short time with a small amount of calculation. The storage unit 51 can store the generated first model 10a of the motor.

[0126] In the above-mentioned embodiment, as the operation mode for driving the motor 10 in order to set the parameters of the first model 10a of the motor, the operation under no-load is shown, but it is not limited to this mode. When determining the parameters of the first model 10a of the motor, it is preferable to operate the motor 10 in various operation modes to obtain the operating state of the motor 10. For example, an operation mode in which the load factor of the motor 10 is repeatedly increased and decreased can be adopted. The load factor of the motor 10 can be greatly changed, and the rotation speed of the motor can be changed. The temperature detected by the temperature detector 31 rises or falls sharply. In this way, an operation mode including a sharp temperature change of the motor can be adopted.

[0127] In the above embodiment, the coil including the winding is used as an example of the component of the motor for estimating the temperature, but the present invention is not limited to this method. As the component for calculating the estimated temperature, any component of the motor can be used. Moreover, a temperature detector can be installed in the component for calculating the estimated temperature.

[0128] In addition, in the above-mentioned embodiment, a synchronous motor having a permanent magnet in the rotor is described, but the present invention is not limited to this mode. The monitoring system in this embodiment can be applied to any motor. For example, the model of the motor in this embodiment can also be applied to an induction motor having no permanent magnet in the rotor.

[0129] Figure 5 A model of the second electric motor according to the present embodiment is shown. Figure 5 The first model 30a is when the operating state of the second motor is normal. Here, the second motor is an induction motor. The rotor of the induction motor includes a cage-shaped conductor formed of stainless steel or copper. The cage-shaped conductor is fixed to the shaft and rotates integrally with the shaft. In the induction motor, the induced current flows inside the cage-shaped conductor due to the magnetic force generated by the coil of the stator. A magnetic field is generated around the cage-shaped conductor, and the rotor rotates.

[0130] In an induction motor, the current flows through the cage conductor of the rotor, which generates secondary copper loss P. c2The secondary loss corresponds to the Joule heat caused by the current flowing through the cage conductor. In the model 30a of the second motor, heat caused by the secondary copper loss is generated in the rotor. The heat capacity in the components of the second motor and the coefficient related to the heat transfer between the components are the same as those in the first model 10a of the first motor.

[0131] The differential equation for temperature change of the components in the model 30a of the second electric motor is different from the first model 10a of the first electric motor in that the differential equation for calculating the temperature change of the rotor is the following equation (11).

[0132] [Formula 5]

[0133]

[0134] P c2 : Secondary copper loss

[0135] In equation (11), the secondary copper loss P is added to equation (4) of the model 11a of the rotor of the first motor. c2 The differential equations representing the temperature changes of the other coils, stator core, air layer, and temperature detector are the same as those in the thermal model of the first motor.

[0136] The loss calculation unit 54 calculates the amount of heat generated by the secondary copper loss generated in the conductor of the rotor. The loss calculation unit 54 estimates the current flowing in the cage conductor. The loss calculation unit 54 can calculate the secondary copper loss based on the current flowing through the conductor, the secondary resistance of the conductor, the inductance of the conductor, and the mutual inductance of the conductor, the stator, and the coil. The inductance, mutual inductance, and secondary resistance of the conductor can be determined in advance.

[0137] Total losses in induction motors P t and primary copper loss P c1 It can be calculated in the same way as the total loss and primary copper loss in a synchronous motor. i Ability to consider secondary copper loss P c2 It is calculated by the following formula (12).

[0138] [Formula 6]

[0139] P i =P t -P c1 -P c2 …(12)

[0140] P i : Iron loss

[0141] In this way, the primary copper loss, the iron loss, and the secondary copper loss are calculated in the first model 30a of the second motor. The parameter calculation unit 63 can also calculate the parameters included in the first model 30a of the second motor when the motor's operating state is normal by the same control as the first model 10a of the first motor in the first model 30a of the second motor. In addition, the temperature estimation unit 53 can calculate the estimated temperature of the components when the motor's operating state is normal using the first model 30a of the second motor.

[0142] Figure 6 The graph shows the estimated temperature of the temperature detector estimated by the temperature estimating unit using the parameters calculated by the parameter calculating unit of the present embodiment. Here, an example of the second electric motor is shown. Figure 6 2 shows a graph when a simulation is performed using parameter set A and parameter set B having different values. Parameter set A and parameter set B are calculated by parameter calculation unit 63. Table 2 shows the parameters included in parameter set A and parameter set B.

[0143] [Table 2]

[0144] Table 2 Parameters

[0145] Unit of coefficient related to heat transfer: [W / K]

[0146] Unit of mass: [kg]

[0147] Parameter Group A Parameter Group B The coefficient ha related to heat transfer 5.48 6.72 The coefficient related to heat transfer hb 10.82 13.78 The coefficient related to heat transfer hc1 2.82 1.49 The coefficient related to heat transfer hc2 1.056 13.35 The coefficient related to heat transfer hc3 7.5 7.26 The coefficient hd related to heat transfer 14.7 4.88 The mass of the coil is m1 1.37 1.37 Mass of stator coil m2 23.19 24.2 The mass of the air layer m3 0.00347 0.000353 The mass of the rotor is m4 3.43 4.7 The mass of the temperature detector m5 0.072 0.02

[0148] Parameter group A and parameter group B are obtained by driving the second motor in different operation modes. Table 2 shows the coefficients related to heat transfer obtained by multiplying the heat transfer coefficient between the components of the motor by the contact area. In addition, the heat capacity is calculated by multiplying the specific heat of the material of each component by the mass. The specific heat of each material can be determined in advance, so the mass m of the component used to calculate the heat capacity is shown in Table 2. If parameter group A is compared with parameter group B, it can be seen that the coefficients hc2 and hd related to heat transfer and the mass m of the rotor 4 Some parameters have greatly different values ​​between the two parameter groups A and B.

[0149] On the other hand, refer to Figure 6 It can be seen that the estimated temperature of the temperature detector calculated using parameter group B is very consistent with the estimated temperature of the temperature detector calculated using parameter group A. In particular, the temperature changes are very consistent both during the period when the temperature rises and during the period when the temperature changes within a predetermined range. Figure 6 The temperature change shown is very consistent with the temperature change detected by the temperature detector 31 when the motor 10 is actually driven.

[0150] There are parameters with greatly different values ​​between parameter group A and parameter group B. Therefore, it is known that the value of at least one of parameter group A and parameter group B is different from the parameter group in the actual motor. In particular, it is known that at least some of the parameters of the plurality of heat capacities and the plurality of coefficients related to heat transfer are set to values ​​different from the actual heat capacity or the actual coefficient related to heat transfer. For example, it is known that the coefficient related to heat transfer of at least one of the coefficient hc2 of parameter group A and the coefficient hc2 of parameter group B is far from the actual coefficient related to heat transfer.

[0151] Thus, in the motor monitoring device of this embodiment, even if at least some of the parameters are different from actual values, the temperature of the temperature detector can be estimated with high accuracy. In addition, the parameter calculation unit of this embodiment can set the parameters of such a motor model.

[0152] In addition, in the present embodiment, one temperature detector is installed on the motor, but the present invention is not limited to this embodiment. Multiple temperature detectors may be installed on multiple components of the motor. The evaluation unit of the parameter calculation unit can compare the measured temperatures of the multiple temperature detectors with the estimated temperatures obtained by the simulation. The parameter change unit can set the parameters of the first model of the motor so that the estimated temperatures of the multiple components are close to the measured temperatures detected by the actual temperature detectors.

[0153] The more temperature detectors are installed in the motor, the closer the values ​​of the multiple parameters of the first model of the motor can be to the actual values. In addition, the estimated temperature of the components of each motor can be close to the actual measured temperature. As a result of installing multiple temperature detectors, the total heat capacity and the coefficient related to the total heat transfer can also be roughly the same as the actual heat capacity and the coefficient related to the actual heat transfer. In this case, when the temperature of the component is estimated by the temperature estimation unit, the temperature of all the components corresponds to the actual temperature of the component with high accuracy.

[0154] Next, an abnormal model generation mode for generating a second model of the motor when the motor operating state is abnormal will be described. Furthermore, the motor monitoring device 2 of this embodiment provides information for estimating a portion where an abnormality has occurred to an operator or other devices based on the second model of the motor.

[0155] Reference Figure 1The motor monitoring device 2 of the present embodiment includes a model search unit 71 that generates a second model of the motor when the motor's operating state is abnormal. The model search unit 71 includes a temperature determination unit 72 that determines whether the difference between the measured temperature of the temperature detector 31 and the estimated temperature of the temperature detector 31 based on the first model is within a predetermined determination range.

[0156] The model search unit 71 includes a component adding unit 73, which generates a second model by adding a model of an additional component that performs heat exchange with the model of the component part of the motor to the first model when the difference between the measured temperature of the temperature detector 31 and the estimated temperature of the temperature detector 31 based on the first model is out of a predetermined determination range. That is, when the difference between the estimated temperature and the measured temperature is large, the component adding unit 73 adds the model of the additional component to the model when the operating state of the motor is normal.

[0157] The model search unit 71 includes a setting unit 74 for setting a model of a component of the motor that performs heat exchange with a model of an additional component. In addition, the setting unit 74 sets the heat capacity of the additional component and a coefficient related to heat transfer of the additional component. As the coefficient related to heat transfer of the additional component, a coefficient related to heat transfer between the model of the component of the motor that performs heat exchange and the additional component is included. In addition, the monitoring device 2 in this embodiment includes an abnormal part estimation unit 75 that estimates an abnormality generated in the motor 10 or around the motor 10. The monitoring device 2 includes a notification unit 76 that notifies other devices of information related to the second model of the motor.

[0158] The above-mentioned model search unit 71, temperature determination unit 72, component addition unit 73 and setting unit 74 are each equivalent to a processor driven according to a pre-generated program. In addition, the abnormal part estimation unit 75 and the notification unit 76 are equivalent to a processor driven according to a pre-generated program. The processor reads the program and implements the control specified in the program, thereby functioning as each unit.

[0159] In the following description, Figure 2 The first motor and Figure 3 The first model of the first motor shown is described, but is not limited to this method. Figure 5 The model of the second motor shown can also be controlled in the same manner as the first motor. In addition, as in the normal model generation mode, the temperature detected by the temperature detector 31 attached to the coil 16 is described as an example.

[0160] If an abnormality occurs in the motor, the temperature of the motor may rise. In this embodiment, when the temperature measured by the temperature detector installed in the motor deviates from a predetermined determination range based on the estimated temperature when the motor is normal, it is determined that an abnormality has occurred in the motor or around the motor. In other words, it is determined that the operating state of the motor is abnormal.

[0161] Figure 7 Graph showing temperature change when the first motor is in a normal operating state. Figure 1 and Figure 7 The vertical axis of the graph is the temperature of the temperature detector 31 attached to the coil 16. The horizontal axis is the elapsed time. The solid line represents the measured temperature actually detected by the temperature detector 31. That is, it represents the measured temperature acquired by the state acquisition unit 62.

[0162] In the operation example here, power is supplied at time t0, and the load of the motor 10 increases sharply. As the current increases, the temperature of the temperature detector 31 increases sharply. At time t1, the current supplied to the motor 10 is reduced. The speed of the motor 10 is maintained at a substantially constant speed under no load. After time t1, the temperature of the temperature detector 31 gradually decreases over time.

[0163] exist Figure 7 , the estimated temperature of the temperature detector 31 estimated by the first model 10a of the first motor is indicated by a dotted line. The first model 10a of the motor is pre-generated in the normal model generation mode. When the operation state of the motor is normal, it can be seen that the estimated temperature of the temperature detector 31 estimated by the first model 10a of the motor is very consistent with the measured temperature detected by the temperature detector 31.

[0164] Figure 8 A graph showing temperature changes when an abnormality occurs in the operating state of the first electric motor. Figure 8 The operating conditions and Figure 7 The operating conditions are the same. Figure 1 , Figure 2 as well as Figure 8 , the load is increased from time t0 to time t1. At time t1, the load is set to zero. In the interval from time t0 to time t2, the motor is in a normal operating state. The measured temperature detected by the temperature detector 31 corresponds well to the estimated temperature calculated by the first model 10a of the motor.

[0165] However, in the interval EP from time t2 to time t3, an abnormality occurs in the motor 10 and the measured temperature rises temporarily. Here, an example is shown in which the lubrication state of the bearings 14 and 15 of the motor 10 temporarily deteriorates. As a result of the deterioration of the lubrication of the bearings 14 and 15, the bearings 14 and 15 generate heat and the temperature rises. The temperature of the temperature detector 31 attached to the coil 16 also rises. After time t3, the operating state of the motor returns to the normal state.

[0166] The model search unit 71 of the monitoring device 2 detects that the operating state of the motor 10 is abnormal in the interval EP. The model search unit 71 generates a second model of the motor when the operating state of the motor 10 is abnormal. The model search unit 71 adds the additional component to the first model to generate the second model. Then, the model search unit 71 sets the model of the component of the motor that performs heat exchange with the additional component and the parameters of the second model in the interval EP in a manner that corresponds well to the change in the actual measured temperature.

[0167] Next, the monitoring device 2 displays information related to the second model of the motor on the display unit and notifies the operator. The operator can observe the information related to the second model of the motor to estimate the abnormal part of the motor. Alternatively, the abnormal part estimation unit 75 estimates the abnormal part based on the second model of the motor.

[0168] While the motor is being driven, the state acquisition unit 62 of the monitoring device 2 acquires the operating state of the motor at predetermined time intervals. The temperature estimation unit 53 calculates the estimated temperature of each component of the motor based on the operating state acquired by the state acquisition unit 62 and the first model of the motor. In particular, in the present embodiment, the estimated temperature of the temperature detector 31 is calculated at predetermined time intervals.

[0169] The state acquisition unit 62 acquires the measured temperature output from the temperature detector 31 at predetermined time intervals. The storage unit 51 stores the time, the estimated temperature of the temperature detector 31 calculated by the first model, and the measured temperature of the temperature detector 31. Such sampling of the operating state can be performed at intervals of, for example, 1 second.

[0170] The temperature determination unit 72 determines whether the difference between the estimated temperature of the temperature detector 31 and the measured temperature of the temperature detector 31 is out of a predetermined determination range. For example, the temperature determination unit 72 can calculate a moving average of the difference between the measured temperature and the moving temperature. The temperature determination unit 72 can calculate the moving average within the past 1 minute, for example. Then, when the moving average is out of a predetermined determination range, it can be determined that the difference between the measured temperature and the determination temperature is out of the determination range. The temperature determination unit 72 can determine that an abnormality has occurred at the time in the middle of the moving average interval.

[0171] In addition, the temperature determination unit can determine whether the difference between the measured temperature and the estimated temperature is out of the determination range by arbitrary control. For example, the temperature determination unit determines whether the absolute value of the difference between the measured temperature and the estimated temperature is greater than a predetermined determination value. When the absolute value is greater than the determination value, it can be determined that the difference between the measured temperature and the actual temperature is out of the determination range.

[0172] Reference Figure 8 , the temperature determination unit 72 determines that the difference between the measured temperature and the estimated temperature is out of the determination range in the interval EP from time t2 to time t3. That is, the temperature determination unit 72 determines that the measured temperature is higher than the determination value based on the estimated temperature. The temperature determination unit 72 can determine the start time and end time of the interval EP in which the measured temperature of the temperature detector 31 is abnormal.

[0173] Fig. 9 An example of a second model of the electric motor according to the present embodiment is shown. Figure 1 , Figure 3 , Figure 8 as well as Fig. 9 The model search unit 71 generates Fig. 9 The component adding unit 73 of the model searching unit 71 searches for the second model 10b of the first motor when the temperature abnormality of the motor occurs in the interval EP. Figure 3 The first model 10a of the first electric motor shown in the figure is added with a model 81a of an additional component X. The component adding unit 73 adds the model 81a of the additional component X that performs heat exchange with the model of the constituent part of the electric motor to generate the second model 10b.

[0174] The setting unit 74 of the model search unit 71 selects a model of a component of the motor that performs heat exchange with the additional component X. Fig. 9 In the example shown, the priority is set for the components of the first model of the motor. The coil is determined to be the first in the priority. The setting unit 74 sets the coil model 16a as the model of the component that exchanges heat with the additional component X. The setting unit 74 changes the formula for calculating the temperature of the components of the motor. The setting unit 74 can determine the temperature T for the additional component X. X and heat capacity C X The setting unit 74 determines the coefficient hx1 related to heat transfer between the coil model 16a and the model 81a of the additional component X. In this example, the setting unit 74 sets the heat generation P generated by the additional component X to X .

[0175] In the second model 10b of the electric motor, the temperature T of the model 16a of the coil 1The rate of change of is given by the following equation (13). In the equation (13) for the rate of change of temperature of the coil model 16a, the term of heat transfer from the additional component X is added to equation (1). In addition, the temperature T of the additional component X is X The rate of change is given by equation (14). In equation (14), the heat value P X and items related to heat exchange of coil model 16a.

[0176] [Formula 7]

[0177]

[0178]

[0179] Tx: Temperature of additional component X

[0180] Cx: Heat capacity of additional component X

[0181] hx1: coefficient related to heat transfer

[0182] Px: The heat generated by the additional component X

[0183] The setting unit 74 sets the heat capacity C in the second model 10b in the period EP. X , calorific value P X The heat transfer coefficient hx1 is used to make the estimated temperature of the model 31a of the temperature detector of the second model 10b correspond to the measured temperature of the temperature detector 31. The parameters of the other components specified in the first model 10a are used without change. In this embodiment, the heat capacity C of the additional component X is predetermined. X , calorific value P X , and the range of the numerical value of the coefficient hx1 related to heat transfer. The setting unit 74 implements a grid search method of changing the parameter at predetermined intervals within the range of each parameter.

[0184] Here, the heat value P X A constant value that does not depend on the load of the motor can be used. X Alternatively, the initial temperature T of the additional component in the interval EP may be unchanged and a fixed value may be used. X The average value of the temperatures of the plurality of components of the motor that perform heat exchange with the additional component X can be used. Alternatively, the initial temperature T X The temperature of a component of the electric motor that exchanges heat with the additional component may be used.

[0185] Furthermore, the additional component X may be maintained at a constant temperature. That is, the temperature T of the additional component X XIn this case, there is no need for equation (14) and no need to add the heat capacity C of component X. X .

[0186] The loss calculation unit 54 of the temperature estimation unit 53 obtains the operating state of the motor in the interval EP from the storage unit 51 and calculates the loss. The temperature calculation unit 55 of the temperature estimation unit 53 calculates the estimated temperature of the model 31a of the temperature detector using the second model 10b in the interval EP. The parameters other than the parameters related to the additional component X use the same values ​​as the parameters of the first model 10a.

[0187] The temperature determination unit 72 of the model search unit 71 obtains the measured temperature of the temperature detector 31 in the interval EP from the storage unit 51. The temperature determination unit 72 calculates the difference between the measured temperature of the temperature detector 31 and the estimated temperature. Here, a moving average value of a predetermined time length is calculated as the difference between the measured temperature of the temperature detector 31 and the estimated temperature. The temperature determination unit 72 can calculate the difference between the measured temperature of the temperature detector 31 and the estimated temperature for each sampling time interval. The storage unit 51 stores the components of the motor for heat exchange of the additional component X, the values ​​of parameters such as the heat capacity of the second model 10b, and the difference between the measured temperature of the temperature detector 31 and the estimated temperature.

[0188] Next, the setting unit 74 changes the parameters related to the additional component X within the predetermined range of the parameters and repeats the same calculation and storage of the calculation results. The setting unit 74 changes the coefficient hx1 and the heat capacity C related to heat transfer little by little at predetermined intervals. X And the heat value P X The model search unit 71 calculates the difference between the measured temperature and the estimated temperature while gradually changing the parameters included in the second model. The model search unit 71 performs calculations by combinations of all parameters. The storage unit 51 stores the difference between the measured temperature and the actual temperature for each combination of parameters.

[0189] Next, the setting unit 74 changes one component of the motor with which the additional component X performs heat exchange. For example, the setting unit 74 sets the model 35a of the air layer as a component with which the additional component X performs heat exchange. The component of the motor with which the additional component X performs heat exchange can be determined based on a predetermined priority order, for example. Then, the setting unit 74 and the temperature determination unit 72 calculate the difference between the measured temperature of the temperature detector 31 and the estimated temperature in the interval EP while changing parameters such as the heat capacity of the second model 10b. The storage unit 51 stores the calculation results.

[0190] In this way, the setting unit 74 generates a second model and performs calculations in a manner that the additional component X exchanges heat with the components of each motor. The setting unit 74 performs calculations for all components in which the additional component X exchanges heat with one component. In each second model, the difference between the measured temperature of the temperature detector 31 and the estimated temperature in the interval EP is calculated.

[0191] Next, the model search unit 71 increases the number of components of the motor that performs heat exchange by the additional component X by one and specifies two components, and repeats the same calculation and storage of the calculation results. The model search unit 71 repeats the calculation of the difference between the measured temperature and the estimated temperature of the temperature detector 31 in the interval EP when there are two components of the motor that performs heat exchange, and stores the calculation results. The model search unit 71 repeats the calculation and storage for all combinations of the two components. Next, the model search unit 71 increases the number of components of the motor that performs heat exchange by one and specifies three components, and repeats the same calculation and storage of the calculation results.

[0192] In this way, the model search unit 71 repeatedly performs calculation and storage for each additional component X that performs heat exchange with the motor. The calculation is performed for all combinations of components that can perform heat exchange with the additional component X. In the example here, the calculation and storage are repeated until the additional component X performs heat exchange with all components of the motor at the same time.

[0193] After all calculations are completed, the setting unit 74 of the model search unit 71 selects the second model with the smallest difference between the temperature measured by the temperature detector 31 and the estimated temperature from the plurality of calculation results recorded in the storage unit 51. For example, in the interval EP, the second model with the smallest mean square of the difference between the temperature measured by the temperature detector 31 and the estimated temperature is selected. The model search unit 71 obtains parameters including the components of the motor with which the additional component X performs heat exchange, the heat capacity of the additional component X, the coefficient related to heat transfer, and the heat amount of the additional component X from the storage unit 51 for the second model.

[0194] Fig.10 10c shows the second model searched by the model search unit when the bearing is abnormal. 10c shows the second model 10c in which the difference between the measured temperature of the temperature detector 31 and the estimated temperature is the smallest among the plurality of second models searched by the model search unit 71. Figure 8 The temperature change of the temperature detector when an abnormality occurs in the bearing is shown in FIG. Figure 2 When an abnormality occurs in the bearing, the temperature of the bearings 14 and 15 rises.

[0195] The bearings 14 and 15 are close to the rotor 11, the coil 16, and the air layer between the rotor 11 and the coil 16. The heat generated by the bearings 14 and 15 is easily transferred to the rotor 11, the coil 16, and the air layer between the rotor 11 and the coil 16. Therefore, when the model search unit 71 searches for the second model, the second model 10c is generated in such a way that the additional component X that generates heat exchanges heat with the coil, the rotor, and the air layer between the coil and the rotor. That is, the model of the constituent parts of the motor with which the model 81a of the additional component X exchanges heat becomes the model 16a of the coil, the model 35a of the air layer, and the model 11a of the rotor.

[0196] In the second model 10c of the electric motor, the temperature T of the model 16a of the coil 1 The rate of change is expressed as the above equation (13). The temperature T of the air layer model 35a is 3 The rate of change is expressed as the following equation (15). The temperature T of the rotor model 11a 4 The rate of change of is given by the following equation (16). In addition, the temperature T of the additional component X is X The rate of change of becomes formula (17).

[0197] [Formula 8]

[0198]

[0199]

[0200]

[0201] Tx: Temperature of additional component X

[0202] Cx: Heat capacity of additional component X

[0203] hx1, hx2, hx3: coefficients related to heat transfer

[0204] Px: The heat generated by the additional component X

[0205] The setting unit 74 sets the parameters that minimize the difference between the measured temperature of the temperature detector and the estimated temperature in the abnormality generating period EP. In the example here, the setting unit 74 sets the coefficient hx1 related to the heat transfer between the model 81a of the additional component X and the model 16a of the coil, the coefficient hx2 related to the heat transfer between the model 81a of the additional component X and the model 35a of the air layer, and the coefficient hx3 related to the heat transfer between the model 81a of the additional component X and the model 11a of the rotor. In addition, the setting unit 74 sets the heat capacity C of the additional component X. X and calorific value P X In this way, the values ​​of the parameters related to the additional component X are set.

[0206] Then, the display unit 52 of the monitoring device 2 displays information about the second model 10c generated by the model search unit 71. Here, the information about the second model 10c corresponding to the measured temperature and having the best estimated temperature of the temperature detector is displayed on the display unit 52. The display unit 52 displays the model of the components of the motor that perform heat exchange with the model 81a of the additional component, the heat capacity C of the model 81a of the additional component, and the heat capacity C of the model 81a of the additional component. X , coefficients related to heat transfer hx1, hx2, hx3 and heat generation P X at least one piece of information.

[0207] The operator can estimate the location and cause of the abnormality based on the information of the second model. The portion generating heat can be estimated based on the component of the motor that performs heat exchange with the additional component X. It can be estimated that there is a portion generating heat near the component of the motor that performs heat exchange with the additional component X. In addition, the operator can estimate the distance between the component of the motor and the additional component X based on the coefficient related to heat transfer. For example, when the heat transfer coefficient is large, it can be estimated that the distance between the portion generating heat and the component of the motor that performs heat exchange is close.

[0208] In addition, the operator can estimate the material and size of the additional component based on the heat capacity of the additional component. For example, if the heat capacity is large, it can be estimated that the component is made of metal or has a large mass. Moreover, the cause of the heat generation can be estimated based on the heat generation of the additional component. For example, if the heat generation is within a predetermined range, it can be estimated that the bearing is poorly lubricated.

[0209] In this way, the operator can estimate the location and cause of the motor abnormality based on the information related to the second model searched by the model search unit. The operator can understand that the abnormality has occurred before the motor fails. The operator can repair or replace the motor before it fails. Alternatively, the countermeasures until the motor fails can be analyzed. For example, the load of the machine can be reduced before the motor is replaced, delaying the time when the motor fails.

[0210] In the above embodiment, the model search unit 71 calculates all combinations of the additional components and the components of the motor. In addition, the model search unit 71 changes all parameters of the second model within a predetermined range. In addition, the second model with the smallest difference between the measured temperature of the temperature detector and the estimated temperature is selected, but the present invention is not limited to this mode.

[0211] For example, the permissible range of the difference between the estimated temperature and the measured temperature of the temperature detector can be predetermined. Furthermore, the setting unit can also end the search of the second model when the difference between the estimated temperature and the measured temperature of the temperature detector is within the permissible range. The setting unit can use the components of the motor that perform heat exchange with the additional component at this time and the parameters of the second model.

[0212] Alternatively, the storage unit can store the second model generated in the past. Furthermore, the priority of the components of the motor for which the additional components are to be used for heat exchange and the priority of the values ​​of the parameters of the second model can be predetermined based on the past results. The setting unit can perform the search in the order of the priority. Furthermore, the search of the second model can be terminated when the difference between the estimated temperature and the measured temperature of the temperature detector is within the allowable range.

[0213] In addition, in the present embodiment, after the second model of the motor abnormality is generated, the information related to the second model is displayed on the display unit, but the present invention is not limited to this mode. The monitoring device 2 of the present embodiment includes a notification unit 76 for notifying other devices of the information related to the second model. For example, the notification unit 76 can notify other devices of at least one of the model of the component part of the motor that performs heat exchange with the model of the additional component, the heat capacity of the additional component, and the coefficient related to heat transfer of the additional component.

[0214] Other devices can receive the notification from the notification unit 76 and perform arbitrary control. For example, the machine control device 41 can obtain information related to the second model from the monitoring device 2. In addition, the machine control device 41 can change the operating state of the machine 1. For example, the machine control device 41 can reduce the speed of the motor drive or change the speed increase rate and decrease rate.

[0215] Reference Figure 1 The monitoring device 2 of this embodiment includes an abnormal part estimation unit 75. The abnormal part estimation unit 75 may also estimate the abnormal part of the motor based on the information of the second model generated by the model search unit 71. The model search unit 71 of the monitoring device 2 generates a second model of the motor whenever an abnormality occurs in the motor. Then, the operator inputs the abnormal part and the cause to the monitoring device 2. The storage unit 51 stores the abnormal part and the cause together with the second model of the motor. The second model of the motor generated in the past and the abnormal part and the cause input by the operator are saved in the storage unit 51.

[0216] The abnormal part estimation unit 75 estimates the abnormal part and cause related to the second model of the motor generated this time, based on the second model of the motor generated in the past and the abnormal part and cause. For example, the abnormal part estimation unit 75 selects a second model obtained in the past that has the same components as the motor that performs heat exchange with the additional components in the second model this time. Then, the abnormal part estimation unit 75 selects a second model whose parameters (coefficient related to heat transfer, heat capacity, and heat generation) are close. It is possible to set a judgment range for each parameter. The abnormal part estimation unit 75 can determine whether the parameter is a close value based on the judgment range. The abnormal part estimation unit 75 can also select multiple second models. The display unit 52 can display the past second model selected by the abnormal part estimation unit 75 and the abnormal part and cause.

[0217] The abnormal part estimation unit can estimate the abnormal part and cause of the motor by any method. For example, the abnormal part estimation unit can estimate the abnormal part and cause of the motor by machine learning. The abnormal part estimation unit generates a learning model for estimating the abnormal part and cause of the motor based on the second model of the motor in the past. For example, the abnormal part estimation unit can implement supervised learning. The abnormal part estimation unit generates a learning model using the second model of the motor in the past and the abnormal part and cause as supervisory data. The abnormal part estimation unit can use the learning model to estimate the abnormal part and cause based on the second model of the motor generated this time. The display unit can display the abnormal part and cause of the motor. Moreover, the abnormal occurrence part and the cause of the abnormality estimated by the abnormal part estimation unit 75 can also be sent to other devices by the notification unit 76.

[0218] In the above-mentioned embodiment, a case where abnormality occurs in a component included in the motor and heat is generated is shown. However, there is a case where an abnormality occurs in a component outside the motor and a heating element is generated. For example, abnormal heat may be generated in a device connected to the motor or in a device close to the motor. If such abnormal heat is generated, there is a case where heat is transferred to the motor. Sometimes the temperature of the motor rises due to the transfer of heat from the heating element.

[0219] Fig.11 A second model is shown when abnormal heat is generated around the motor of the present embodiment. The second model 10d searched by the model search unit 71 is shown. The heat generating body is represented as an additional component Y that generates heat. For example, sometimes the spindle head of a machine tool includes a motor. The motor is connected to a spindle that holds a tool. The spindle is rotated by the drive of the motor. However, sometimes an abnormality occurs in the spindle head and the spindle contacts the housing of the spindle head. As a result, sometimes the spindle generates heat and transfers heat to the motor.

[0220] When a heat source is generated around such a motor, the temperature determination unit 72 of the model search unit 71 identifies the section EP where the abnormality has occurred. The component adding unit 73 adds the model 82a of the additional component Y to the first model 10a to generate the second model 10d. The model search unit 71 sets the model of the component that performs heat exchange with the model 82a of the additional component Y and the parameters of the second model 10d so that the estimated temperature of the temperature detector 31 corresponds to the measured temperature. The model 20a of the stator core is set as the component that performs heat exchange with the model 82a of the additional component Y. In addition, the heat capacity C related to the additional component Y is set. Y , calorific value P Y , and parameters of the coefficient hy related to heat transfer.

[0221] The operator can estimate the location and cause of the abnormality by referring to the second model 10d and the parameters of the second model 10d. Alternatively, the abnormal location estimation unit can estimate the location and cause of the abnormality. The monitoring device of this embodiment can also generate a second model related to an abnormality occurring outside the motor.

[0222] In the above embodiment, the case where the abnormal component generates heat is shown, but the present invention is not limited to this mode. If an abnormality occurs in the motor and its surroundings, the temperature of the motor may drop. For example, foreign matter that absorbs heat from the components of the motor may adhere to the motor.

[0223] When liquid such as coolant splashes onto the outer peripheral surface of the motor 10, a component having a lower temperature than the component of the motor 10 contacts the stator core 20, and the temperature of the stator core 20 decreases. The temperature determination unit 72 detects that the measured temperature detected by the temperature detector 31 is lower than the determination value of the estimated temperature of the temperature detector 31 when the motor is in a normal operating state. For example, the temperature determination unit 72 detects that the measured temperature is lower than a predetermined temperature range for the estimated temperature.

[0224] The component adding unit 73 adds a model of an additional component having a zero calorific value to the first model 10a to generate a second model. The model of the additional component is set to have a heat capacity. The initial temperature of the additional component can be predetermined. Through the search of the second model by the model searching unit 71, the model of the additional component is set to perform heat exchange with the model of the stator core. In addition, the parameters of the second model are set in such a way that the estimated temperature of the temperature detector corresponds well to the measured temperature.

[0225] On the other hand, when liquid such as mechanical coolant intrudes into the interior of the motor 10, components whose temperature is lower than that of the components of the motor come into contact with the coil 16, the rotor 11, and the stator core 20, and the temperature of these components decreases. The component adding unit 73 adds a model of an additional component with zero heat generation to the first model 10a to generate a second model. A predetermined heat capacity is set in the model of the additional component. The initial temperature of the additional component can be predetermined. Through the exploration of the second model, the model of the additional component is set to perform heat exchange with the model of the coil, the model of the rotor, and the model of the stator core. In addition, the parameters of the second model are set in such a way that the estimated temperature of the temperature detector corresponds well to the measured temperature.

[0226] As described above, the monitoring device of the present embodiment can generate not only a model of abnormal heat generation in and around the motor but also a model of abnormal heat absorption in and around the motor.

[0227] The first model of the motor in the above-mentioned embodiment is composed of a model of the coil, a model of the stator core, a model of the temperature detector, a model of the air layer, a model of the rotor, and a model of the external air, but is not limited to this method. The first model of the motor may also include models of other components. For example, the first model of the motor may also include a model of a housing supporting the stator and the rotor, a model of a bearing, and a model of a shaft supporting the rotor. Alternatively, the first model of the motor may not include a part of the model. For example, the model of the motor may not include a model of the air layer.

[0228] The motor monitoring device of this embodiment is configured to be able to switch between the normal model generation mode and the abnormal model generation mode, but is not limited to this mode. The motor monitoring device may not have the function of the normal model generation mode. The first model of the motor when the motor's operating state is normal may also be generated by other devices.

[0229] In addition, in this embodiment, the motor monitoring device is composed of a computing device different from the mechanical control device, but the present invention is not limited to this method. The mechanical control device may also have the function of the motor monitoring device. That is, the processor of the mechanical control device may also function as a model search unit, a temperature estimation unit, and a parameter calculation unit.

[0230] In each of the above-mentioned controls, the order of the steps can be appropriately changed within the range in which the functions and effects are not changed. The above-mentioned embodiments can be combined as appropriate.

[0231] In the above-mentioned figures, the same or equivalent parts are marked with the same reference numerals. In addition, the above-mentioned embodiment is an example and does not limit the invention. In addition, in the embodiment, changes of the embodiment shown in the scope of the patent protection are included.

[0232] Explanation of symbols

[0233] 2 Monitoring device

[0234] 10 Electric Motor

[0235] Model of 10A electric motor

[0236] 11a Rotor Model

[0237] 14, 15 bearings

[0238] Model of 16a coil

[0239] 20a stator core model

[0240] 30A electric motor model

[0241] 31a Temperature Detector Model

[0242] Model of 35a air layer

[0243] 36a Model of outside air

[0244] 51 Storage

[0245] 52 Display unit

[0246] 53. Temperature estimation unit

[0247] 54 Loss Calculation Department

[0248] 55 Temperature calculation unit

[0249] 62 Status acquisition unit

[0250] 63 parameter calculation unit

[0251] 66 Evaluation Department

[0252] 67 Parameter Change Department

[0253] 71 Model Search Department

[0254] 72 Temperature determination unit

[0255] 73 parts addition

[0256] 74 Setting Department

[0257] 75 Abnormal Part Estimation Department

[0258] 76 Notification Department

[0259] 81a, 82a models.

Claims

1. A monitoring device for an electric motor, characterized in that: The monitoring device comprises: a state acquisition unit that acquires an operating state of the motor including a measured temperature detected by a temperature detector attached to the motor; a temperature estimating unit that calculates an estimated temperature of the temperature detector based on a model of the motor; A storage unit that stores a first model of the motor when the operating state of the motor is normal; and a model search unit that generates a second model of the motor when the operating state of the motor is abnormal, The model of the motor includes a rotor model, a stator core model, a coil model, and a temperature sensor model as models of the components of the motor. A heat capacity is set in the model of at least one component, The coefficients related to the heat transfer between the components of the model are set. The model search unit comprises: a component adding unit that generates a second model by adding a model of an additional component that performs heat exchange with the model of the component of the motor to the first model when the difference between the measured temperature of the temperature detector and the estimated temperature of the temperature detector based on the first model is out of a predetermined determination range; and A setting unit sets a model of a component of the motor that exchanges heat with the model of the additional component and a coefficient related to heat transfer of the additional component so that the estimated temperature of the temperature detector based on the second model corresponds to the measured temperature of the temperature detector.

2. The motor monitoring device according to claim 1, characterized in that: The monitoring device includes: a notification unit that notifies other devices of information related to the second model of the motor; The notification unit notifies at least one of a model of a component of the motor that performs heat exchange with the model of the additional component, a heat capacity of the additional component, and a coefficient related to heat transfer with respect to the additional component.

3. The motor monitoring device according to claim 1 or 2, characterized in that: The monitoring device includes: a display unit that displays information related to a second model of the motor; The display unit displays at least one information of a model of a component of the motor that performs heat exchange with the model of the additional component, a heat capacity of the additional component, and a coefficient related to heat transfer with respect to the additional component.

4. The motor monitoring device according to any one of claims 1 to 3, characterized in that: The setting unit sets an additional component that generates heat.

5. The motor monitoring device according to claim 4, characterized in that: The model search unit sets the model of the additional component so as to perform heat exchange with the model of the coil and the model of the rotor when an abnormality occurs in the bearing of the motor.

6. The motor monitoring device according to claim 4, characterized in that: The model search unit sets the model of the additional component so as to perform heat exchange with the model of the stator core when a heat generating element is generated outside the motor.

7. The motor monitoring device according to any one of claims 1 to 6, characterized in that: The monitoring device includes: a parameter calculation unit that calculates parameters of a first model of the motor; The state acquisition unit acquires the motor operation command generated by actually driving the motor. The parameters include the heat capacity set in the model of the component parts and the coefficients related to the heat transfer between the models of the component parts. The temperature estimation unit includes: a loss calculation unit that calculates a heat value caused by a primary copper loss of the coil and a heat value caused by an iron loss of the stator core based on the operation instruction; and a temperature calculation unit that calculates an estimated temperature of the temperature detector using a first model of the motor based on the heat value of the coil and the heat value of the stator core. The parameter calculation unit includes: an evaluation unit that evaluates the estimated temperature of the temperature detector by comparing the estimated temperature of the temperature detector with the measured temperature of the temperature detector; and a parameter changing unit that changes the value of the parameter based on the evaluation result of the evaluation unit so that the estimated temperature of the temperature detector approaches the measured temperature. The mode in which the parameter calculation unit calculates the parameters of the first model of the electric motor and the mode in which the model search unit generates the second model of the electric motor can be switched.

8. The motor monitoring device according to any one of claims 1 to 7, characterized in that: The monitoring device comprises: an abnormal part estimating unit for estimating an abnormal part; The storage unit stores a second model of the motor and an abnormal location generated in the past. The abnormal part estimating unit estimates the abnormal part related to the second model of the motor generated this time, based on the second model of the motor generated in the past and the abnormal part.

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