ELECTRIC MOTOR MONITORING DEVICE

Abstract

This monitoring device comprises: a storage unit that stores a first model for an electric motor when the operating state of the electric motor is normal; and a model search unit that generates a second model for the electric motor when the operating state of the electric motor is abnormal. The model search unit adds a model for an additional component to the first model to generate the second model when the difference between a temperature measured by a temperature detector and an estimated temperature of the temperature detector based on the first model deviates from a defined range.The model search unit sets: a model for constituent parts of the electric motor that perform a heat exchange with the model for the additional component; and factors 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 estimated temperature of the temperature detector.

Description

Technical area

[0001] The present invention relates to an electric motor monitoring device. State of the art

[0002] The operating state of a machine can be detected by attaching a sensor to the machine. On the other hand, it is known that the operating state of a machine can be estimated through simulation without actually driving the machine (e.g., Japanese Patent Publication No. JP 63-106861A).

[0003] An electric motor is installed in the machine to drive a specific component. It is known that the temperature of an electric motor rises when the electric motor is operated. If the temperature of the electric motor becomes too high, the electric motor may not operate accurately or the constituent components of the electric motor may be damaged. For this reason, the electric motor is preferably operated within a suitable temperature range (e.g., Japanese Patent Publication No. JP 2010-268644A).

[0004] The actual temperature during operation of the electric motor can be detected by a temperature detector attached to a constituent component of the electric motor. Alternatively, a simulation method for estimating the temperature of the electric motor is known. In simulation, a method is known in which a thermal model is used to estimate the temperature of an electric motor, taking into account the heat capacity of the constituent components and the heat transfer between the components (e.g., International Publication No. WO2020 / 188650A and Japanese Unapplied Patent Publication No. JP 2008-109816A).

[0005] In the thermal model, a heat transfer coefficient or thermal resistance between the respective constituent components is specified to calculate the heat transfer between the components. The temperature of each constituent component can be calculated in the thermal model. For an electric motor, the temperature is estimated when the electric motor is driven using a thermal model that includes a stator core, a coil, a rotor core, and the like. Citation listPatent literature PTL 1: Unexamined Japanese Patent Publication No. JP 63-106861A PTL 2: Unexamined Japanese Patent Publication No. JP 2010-268644A PTL 3: International Publication No. WO2020 / 188650A PTL 4: Japanese Unopposed Patent Publication No. JP 2008-109816A Summary of the inventionTechnical problem

[0006] When the electric motor is driven, heat is generated by the stator core, the coil attached to the stator core, the bearing, and the like. Furthermore, if a constituent component of the electric motor is broken, the broken component may generate heat, and the temperature of the electric motor may rise abnormally. To identify a part that generates heat during the operating time of the electric motor, a temperature sensor can be attached to each constituent component of the electric motor. A part in which abnormal heat generation occurs can be identified by monitoring the temperature of the constituent component in the output of the temperature sensor.

[0007] However, if the temperature sensors are mounted on the respective constituent components of the electric motor, the problem arises that a large number of temperature sensors are required. Given the structure of the electric motor, it may be difficult to mount the temperature sensor on a component inside the electric motor, a rotating component, or the like. Solution to the problem

[0008] A monitoring device for an electric motor according to one aspect of the present disclosure includes a state detection unit configured to detect an operating state of an electric motor, including a measured temperature detected by a temperature detector attached to the electric motor. The monitoring device includes a temperature estimation unit configured to calculate an estimated temperature of the temperature detector based on a model for the electric motor. The monitoring device includes a memory configured to store a first model of the electric motor when the operating state of the electric motor is normal. The monitoring device includes a model search unit configured to generate a second model for the electric motor when the operating state of the electric motor is abnormal.The model for the electric motor includes a model for a rotor, a model for a stator core, a model for a coil, and a model for the temperature detector as models for constituent parts of the electric motor. A heat capacity is set in at least one of the models for the constituent parts. A coefficient related to heat transfer between the models for the constituent parts is set. The model search unit includes a component addition unit for generating the second model by adding a model for an additional component that performs heat exchange with the model for the constituent part of the electric motor to the first model when a difference between a measured temperature of the temperature detector and an estimated temperature of the temperature detector based on the first model deviates from a predetermined determination range.The model search unit includes a setting unit for setting the model for the constituent part of the electric motor that performs heat exchange with the model for the additional component and a coefficient related 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. Advantageous effects of the invention

[0009] According to an electric motor monitoring device according to one aspect of the present disclosure, information for estimating a part in which an abnormality occurs can be provided. Brief description of the drawings [ Fig. 1] Fig. 1 is a block diagram of a machine and an electric motor monitoring device according to one embodiment. [ Fig. 2] Fig.2 is a schematic cross-sectional view of a first electric motor according to an embodiment. [ Fig. 3] Fig. 3 is a first model for a first electric motor according to the embodiment. [ Fig. 4] Fig. 4 is a diagram for explaining a running pattern of an electric motor for setting a parameter in the first model for the electric motor. [ Fig. 5] Fig. 5 is a first model for a second electric motor according to the embodiment. [ Fig. 6] Fig. 6 is a graphical representation of a simulation result using parameter sets specified by a parameter calculation unit. [ Fig. 7] Fig. Figure 7 is a graph showing the temperature change of the temperature detector under normal operating condition of the electric motor. [ Fig. ] Fig.is a diagram showing a temperature change of the temperature detector under abnormal operating condition of the electric motor. [ Fig. 9] Fig. Figure 9 shows a second model obtained by adding an additional component to the first model of the first electric motor. [ Fig. 10] Fig. Figure 10 shows a second model in which the additional component performs heat exchange with a plurality of constituent parts of the electric motor. [ Fig. ] Fig. shows another second model for the first electric motor. Description of the embodiments

[0010] An electric motor monitoring device according to an embodiment is described with reference to the Fig.1 to 11. The electric motor monitoring device according to the present embodiment has a function of estimating a temperature of a predefined constituent part of an electric motor using a model for the electric motor. Specifically, the electric motor monitoring device estimates a temperature output from a temperature detector attached to a constituent part of the electric motor.

[0011] In the present embodiment, the temperature actually measured by the temperature detector is referred to as the measured temperature. Furthermore, the temperature of the constituent part estimated from the model for the electric motor is referred to as the estimated temperature. In the present embodiment, an example of estimating a temperature of a temperature detector for detecting the temperature of a coil of a stator among the constituent parts of an electric motor will be described.

[0012] The electric motor monitoring device according to the present embodiment provides an operator or another device with information for estimating the part where an abnormality occurs. For example, the operator estimates the area where the abnormality occurs by observing the information displayed on the display part of the electric motor monitoring device.

[0013] Fig.1 is a block diagram of a machine and an electric motor monitoring device according to the present embodiment. A machine 1 of the present embodiment includes an electric motor 10 for driving a constituent component of the machine 1, and a machine controller 41 for controlling the machine 1. The machine controller 41 of the present embodiment includes an arithmetic processing device (computer). The machine controller 41 includes a central processing unit (CPU) serving as a processor. The machine controller 41 includes a random access memory (RAM), a read-only memory (ROM), or the like, which is connected to the CPU via a bus.

[0014] The machine 1 according to the present embodiment is a numerically controlled machine. The machine 1 is driven based on a set of instructions described in a pre-prepared operation command 45. The machine controller 41 includes a memory 42 for storing the operation program 45 and an operation control unit 43 for generating an operation command for the electric motor 10 based on the operation program 45. The machine 1 includes a drive device 44 having a circuit that supplies power to the electric motor 10 based on the operation command generated in the operation control unit 43. The electric motor 10 is driven by the drive device 44, which supplies power.

[0015] The memory 42 may be a non-volatile storage medium capable of storing information. The memory 42 may include, for example, a storage medium such as volatile memory, non-volatile memory, magnetic storage medium, or optical storage medium. The operation control unit 43 corresponds to a processor controlled by the operation program 45. The processor reads the operation program 45 and executes the controls specified in the operation program 45 to function as the operation control unit 43.

[0016] Such a machine 1 can be any machine that contains an electric motor 10. An example of a machine 1 is a machine tool for machining a workpiece. Examples of the electric motor 10 include a main spindle motor that rotates a tool and a feed shaft motor for moving a table or a main spindle head along a predefined coordinate axis.

[0017] Fig. 2 is a cross-sectional view of a first electric motor according to the present embodiment. Referring to the Fig. 1 and Fig. 2, a first electric motor 10 is a synchronous electric motor in which a rotor 11 contains a magnet 18. The electric motor 10 includes the rotor 11 and a stator 12. The stator 12 includes a stator core 20 made of a magnetic material and a coil 16 fixed to the stator core 20. The stator core 20 is composed, for example, of a plurality of magnetic steel plates stacked in the axial direction of the shaft 13. The coil 16 is composed, for example, of a winding wound around the stator core 20 and a resin part for fixing the winding.

[0018] The rotor 11 is fixed to the shaft 13 and has a rod shape. The rotor 11 includes a rotor core 17, which is fixed to the outer peripheral surface of the shaft 13 and is made of a magnetic material, and a plurality of magnets 18 fixed to the rotor core 17. The magnet 18 according to the present embodiment is a permanent magnet.

[0019] The shaft 13 is connected to another component to transmit rotational force. The shaft 13 rotates about a rotational axis RA. The shaft 13 is supported by bearings 14 and 15, which serve as bearings. According to the present embodiment, in the electric motor 10, the side where the shaft 13 is coupled to another component is referred to as the front side. The side opposite the front side is referred to as the rear side. In the Fig. In the example shown in Figure 2, an arrow 91 indicates the front of the electric motor 10.

[0020] The electric motor 10 includes a housing 21 at the front and a housing 22 at the rear. The stator core 20 of the stator 12 is supported by the housings 21, 22. The housing 21 supports a bearing 14. A member 24 supporting a bearing 15 is fixed to the housing 22. The housings 21, 22 rotatably support the shaft 13 via the bearings 14, 15. A rear cover 23 is fixed to the part on the rear of the housing 22 to close the space within the housing 22.

[0021] A rotational position detector 32 is arranged at the end portion on the rear side of the shaft 13 to detect the rotational position or rotational speed of the shaft 13. The rotational position detector 32 according to the present embodiment includes an encoder. The temperature detector 31, which detects the temperature of the coil 16, is attached to the coil 16 of the stator 12. The temperature detector 31 according to the present embodiment is configured with a thermistor. The outputs of the temperature detector 31 and the rotational position detector 32 are input to the machine controller 41.

[0022] The constituent parts of the electric motor 10 include, for example, the rotor 11, the rotor core 17, the magnet 18, the stator 12, the stator core 20, the coil 16, the housings 21, 22, the shaft 13, the rear cover 23, the bearing support member 24, the bearings 14, 15, a temperature detector 31, and the rotation position detector 32. The constituent part of the electric motor 10 is not limited to this form, and any part constituting the electric motor 10 can be adopted. For example, a housing for covering the stator can be adopted.

[0023] An electric motor monitoring device 2 according to the present embodiment calculates an estimated temperature obtained by estimating a temperature output from a temperature detector 31 disposed in the electric motor 10. In the present embodiment, the temperature output of the temperature detector 31 disposed on the coil 16 of the stator 12 is estimated. Specifically, the electric motor monitoring device 2 estimates a temperature change of the temperature detector 31 over time.

[0024] The electric motor monitoring device 2 includes a computing unit (computer) with a CPU as a processor. The monitoring device 2 includes a memory 51 for storing information about the monitoring of the electric motor 10. The memory 51 may comprise a non-transferable storage medium that can store information. For example, the memory 51 may comprise 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 part 52 for displaying information about the electric motor 10. The display part 52 may consist of any display panel, such as a liquid crystal display panel or an organic electroluminescence (EL) display panel.

[0025] The monitoring device 2 includes a temperature estimation unit 53 for calculating an estimated temperature of the temperature detector 31. The temperature estimation unit 53 includes a loss calculation unit 54 for calculating the amount of heat generation due to the primary copper loss of the coil 16 and the amount of heat generation due to the iron loss of the stator core 20 based on an operation command of the electric motor 10. The temperature estimation unit 53 includes a temperature calculation unit 55 for estimating the temperature of the temperature detector 31 using an electric motor model (thermal model).The temperature calculation unit 55 calculates the estimated temperature of the temperature detector 31 based on the heat generation amount due to the primary copper loss and the iron loss, the heat capacity of the respective models for the constituent part, and the coefficient related to the heat transfer between the models for the constituent parts.

[0026] The monitoring device 2 according to the present embodiment has the function of calculating a parameter included in a model for an electric motor. The parameter includes a heat capacity specified in the models for the constituent parts of the electric motor 10 and a coefficient related to heat transfer between the models for the constituent parts. The monitoring device 2 includes a parameter calculation unit 63 for calculating a parameter included in the first model for the electric motor when the operating state of the electric motor is normal.

[0027] The monitoring device 2 includes a state detection unit 62 for detecting the operating state of the electric motor 10 when the electric motor 10 is actually operated. The operating state of the electric motor 10 includes a measured temperature detected by the temperature detector 31 attached to the electric motor 10. The operating state of the electric motor 10 includes an operating command of the electric motor 10 generated by the actual driving of the electric motor 10 and a rotational speed output by the rotational position detector 32. The operating command of the electric motor 10 can be detected by the operation control unit 43. Furthermore, the state detection unit 62 can detect the outside air temperature from an 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 arranged, for example, to detect a temperature in the environment of the machine 1.

[0028] The parameter calculation unit 63 of the present embodiment calculates the parameters so that the change in the estimated temperature of the temperature detector calculated by the model for the electric motor corresponds to the change in the actually measured temperature. The parameter calculation unit 63 of the present embodiment can adjust the parameters of the model for the electric motor through machine learning.

[0029] The loss calculation unit 54 of the temperature estimation unit 53 calculates the heat generation amount of the coil 16 and the stator core 20 based on the operation command generated by the operation control unit 43 and the rotational speed detected by the rotational position detector 32. Furthermore, the temperature calculation unit 55 calculates the estimated temperature of the temperature detector based on the heat generation amount of the coil 16 and the stator core 20.

[0030] The parameter calculation unit 63 calculates the estimated temperature of the temperature detector 31 using the temperature estimation unit 53. The parameter calculation unit 63 includes an evaluation unit 66 for evaluating the estimated temperature of the temperature detector by comparing the estimated temperature of the temperature detector 31 with the measured temperature of the temperature detector 31 detected by the state detection unit 62. The parameter calculation unit 63 includes a parameter changing unit 67 for changing the values ​​of the parameters based on the evaluation results of the evaluation unit 66.

[0031] The temperature estimation unit 53, the loss calculation unit 54, and the temperature calculation unit 55 each correspond to a program-controlled processor. Each unit of the state detection unit 62, the parameter calculation unit 63, the evaluation unit 66, and the parameter modification unit 67 corresponds to a processor controlled by a program. The processor executes the control defined in the program and operates as a respective unit.

[0032] Fig.shows a first model obtained by modeling the thermal motion of the first electric motor according to the present embodiment. The first electric motor model is a thermal model that simulates a normal operating state of the electric motor. The thermal model for the electric motor includes models for a variety of constituent parts. The thermal model includes parameters such as the heat capacity of the constituent parts and coefficients related to heat transfer between the constituent parts. The first electric motor model 10a of the present embodiment includes models for the main constituent parts of the first electric motor 10. The electric motor model 10a includes a rotor model 11a, a stator core model 20a, and a coil wound around the stator core model 16a.The electric motor model 10a also includes a temperature detector model 31a for detecting the temperature of the coil 16.

[0033] As in Fig. As shown in Figure 2, an air layer is located between the rotor 11 and the stator core 20. Furthermore, an air layer is located between the rotor 11 and the coil 16. The electric motor model 10a according to the present embodiment includes an air layer model 35a. The electric motor model 10a also includes an outside air model 36a as a model for the air around the electric motor 10. Thus, in the electric motor model according to the present embodiment, the air layer and the outside air are generated as models for the constituent parts of the electric motor.

[0034] The temperature detected by the temperature detector 31 is almost the same as the temperature of the coil 16. However, under a given condition, the temperature detected by the temperature detector 31 may deviate from the temperature of the coil 16 due to the low heat capacity of the temperature detector 31. For this reason, in the present embodiment, the temperature detector model 31a is also created for the temperature detector 31 as a constituent part model. The heat capacity of the temperature detector 31 may be set to zero, and the calculation may be performed assuming that the temperature of the temperature detector model is the same as the temperature of the constituent part model to which the temperature detector is attached.

[0035] In model 10a for the electric motor, a variety of parameters are specified, including the heat capacity and the heat transfer coefficient. A heat capacity is specified in the model for at least one constituent part. In model 16a for the coil, model 20a for the stator core, model 35a for the air layer, model 11a for the rotor, and model 31a for the temperature detector, the temperatures T1, T2, T3, T4, and T5 are set as variables and the heat capacities C1, C2, C3, C4, and C5 are set as constants. In addition, in model 36a for the outside air, a temperature T r set as a variable.

[0036] Heat is transferred from one constituent part of the electric motor 10 to the other constituent parts. The coefficient related to heat transfer is defined between the models for the respective constituent parts of the electric motor 10. The coefficient related to heat transfer can be the heat transfer coefficient, the coefficient obtained by multiplying the heat transfer coefficient by the contact area between the constituent parts, or the like. In this example, a coefficient is defined by multiplying the heat transfer coefficient by a contact area.

[0037] A heat transfer coefficient ha is set between model 20a for the stator core and model 16a for the coil. A heat transfer coefficient hc1 is set between model 35a for the air layer and model 16a for the coil. A heat transfer coefficient hc2 is set between model 35a for the air layer and model 20a for the stator core. A heat transfer coefficient hc3 is set between model 35a for the air layer and model 11a for the rotor. A heat transfer coefficient hd is set between model 16a for the coil and model 31a for the temperature detector. To simulate the heat loss of the stator core 20 to the outside air, a heat transfer coefficient hb is also set between model 20a for the stator core and model 36a for the outside air.

[0038] In the model 10a for the electric motor according to the present embodiment, a primary copper loss P c1 , which is generated in the coil 16 of the stator 12, is considered as heat generated by the constituent part. The amount of heat generated due to the primary copper loss is input into the model 16a for the coil. In addition, an iron loss P i of the stator core 20, which is generated by the magnetic force of the magnet 18 in the rotor 11. The amount of heat generated due to iron loss is input into the model 20a for the stator core.

[0039] The heat moves between the respective constituent parts, such as the coil and the stator core, depending on the magnitude of the heat transfer coefficient. Each constituent part also has a temperature rise and fall based on the difference between the amount of heat entering and the amount of heat leaving. The temperature change rate of each constituent part of the Fig. The first model 10a of the first electric motor shown in Figure 3 can be expressed by the following equations (1) to (5). In each constituent part, the temperature change rate can be calculated by dividing the difference between the incoming heat amount and the outgoing heat amount by the heat capacity. [Math. 1] dTdt=Pc1+ha(T2−T1)+hc1(T3−T1)C1 dT2dt=Pi+ha(T1−T2)+hb(Tr−T2)+hc2(T3−T2)C2 dT3dt=hc1(T1−T3)+hc2(T2−T3)+hc3(T4−T3)C3 dT4dt=hc3(T3−T4)C4 dT5dt=hd(T1−T5)C5 T1: Temperature of the coil , C1: Heat capacity of the coil T2: Temperature of the stator core , C2: Heat capacity of the stator core T3: Temperature of the air layer , C3: Heat capacity of the air layer T4: Rotor temperature , C4: Heat capacity of the rotor T5: Temperature of the temperature detector , C5: Heat capacity of the temperature detector T6: Outside air temperature , C6: Heat capacity of the outside air ha, hb, hc1, hc2, hc3, hd: heat transfer coefficient P c1 : Primary copper loss P i : Iron loss

[0040] The heat capacities C1, C2, C3, C4, and C5 of the respective constituent parts are constant and can be set in advance. Each of the heat transfer-related coefficients ha, hb, hc1, hc2, hc3, and hd is the coefficient obtained by multiplying the heat transfer coefficient by the contact area. The coefficients ha, hb, hc1, hc2, hc3, and hd are constant and can be set in advance. The loss calculation unit 54 of the temperature estimation unit 53 calculates the primary copper loss P c1 in the coil 16 and the iron loss P i in the stator core as described below. The temperature calculation unit 55 of the temperature estimation unit 53 can calculate the amount of temperature change in one minute time dt based on the equations (1) to (5) described above.

[0041] The following is the calculation method for the primary copper loss P c1and the iron loss P i described in equations (1) and (2). The speed of the electric motor 10 and the load factor of the electric motor 10 (percentage relative to the maximum load) can be set in advance by the operator depending on the work performed by the machine. The loss calculation unit 54 of the temperature estimation unit 53 calculates the primary copper loss P c1 and the iron loss P i Table 1 shows a loss diagram for the loss calculation. [Table 1] Table 1 Loss map Rotational speed N [rpm] Loss P m at maximum power [kW] Loss P n at no load [kW] Current I m at maximum power [A] 0 3.12 0.001 166.8 1000 4.01 0.0239 166.8 2000 2.57 0.064 166.4 3000 2.7 0.065 165.7 4000 2.73 0.086 165.3 5000 2.72 0.179 165.4 6000 4.49 0.2 165.4 7000 4.03 0.227 158 8000 3.066 0.27 150.3 9000 4.38 0.256 145.8 10000 3.55 0.282 142 11000 5.68 0.291 137 12000 3.5 0.348 135

[0042] Table 1 shows the loss at maximum power, the loss at no load and the current at maximum power as a function of the rotational speed (rpm) of the electric motor 10. A loss P mAt maximum power, the loss when the load factor of the electric motor is 100% is a value determined by the speed of the electric motor. A loss P n At no load, the loss occurs when the load factor of the electric motor is zero, which depends on the speed of the electric motor. A current I m At maximum power, the current value is when the load factor is 100% at each speed. The loss diagram shown in Table 1 can be generated from the actual operation of an electric motor. This loss map can be stored, for example, in the memory 51 of the monitoring device 2.

[0043] The loss calculation unit 54 calculates a total loss Pt which is the primary copper loss P c1 and the iron loss P i The total loss Pt can be calculated using the following equations (6) and (7). [Math. 2] Pt=k2⋅LF2+k1⋅LF+Pn k1=Pm−Pn−k2 Pt: Total loss P m : Loss at maximum power L F : Load factor of the electric motor k1, k2: constant

[0044] The total loss P t can be explained by the loss P m at maximum power, the loss P n at no load and calculate a load factor LF of the electric motor. Since the speed and load factor of the electric motor are defined, the loss P m at maximum power and the loss P n at no load from Table 1. The constants k1 and k2 can be specified in advance by the operator. The primary copper loss P c1 can then be calculated using equations (8) and (9). [Math. 3] Pc1=r1⋅I2 I=Im⋅LF P c1 : Primary copper loss I: Current r1: primary resistance I m: Current at maximum power

[0045] The primary copper loss P c1 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 calculated by multiplying the current I m at maximum power with the load factor LF of the electric motor. The current I m at maximum power can be taken from Table 1. For this purpose, a primary resistance r1 of the coil 16 is measured in advance. Then the iron loss P i can be calculated by equation (10) below. The iron loss P i can be calculated by subtracting the primary copper loss P c1 of the total loss P t be calculated. [Math. 4] Pi=Pt−Pc1 P i : Iron loss

[0046] The temperature estimation unit 53 acquires the operating pattern of the electric motor, including the rotational speed and load factor for driving the engine 1, from the state acquisition unit 62. The temperature calculation unit 55 of the temperature estimation unit 53 can initially set the temperatures T1 to T5 of the respective constituent parts to arbitrary temperatures. For example, the temperature calculation unit 55 sets the temperatures T1 to T5 of the constituent parts to the normal outside air temperature T r . The temperature T r the outside air can be determined in advance depending on the location of machine 1.

[0047] The loss calculation unit 54 of the temperature estimation unit 53 calculates the primary copper loss and the iron loss based on the rotational speed and load factor of the electric motor in the operating pattern. Next, the temperature calculation unit 55 can calculate the change amount of a temperature T5 of the temperature detector 31 for the minute time dt by solving the above equations (1) to (5). In this way, the operator can determine the running pattern of the electric motor and estimate the change in the temperature of the temperature detector over time when the electric motor is operated in the running pattern.

[0048] In the model 10a for the electric motor according to the present embodiment, the temperature of only one of a plurality of constituent parts in the electric motor needs to be accurately estimated. The temperatures of the constituent parts other than the one constituent part may deviate from the actual temperatures. In this example, the temperature T5 of the temperature detector model 31a only needs to be accurately estimated. The temperature T1 of the coil 16a model, the temperature T2 of the stator core 20a model, the temperature T3 of the air layer 35a model, and the temperature T4 of the rotor 11a model may deviate from the actual temperatures.

[0049] Furthermore, the heat capacities C1 to C5 set in the electric motor model 10a and the heat transfer coefficients ha, hb, hc1, hc2, hc3, and hd set between the constituent parts have unique values ​​depending on the material, shape, arrangement, and the like of the constituent parts. However, in the electric motor model 10a according to the present embodiment, at least some of the parameters of the plurality of heat capacities and the plurality of heat transfer coefficients are set to values ​​that differ from the actual heat capacities or the actual heat transfer coefficients.

[0050] Each parameter is adjusted so that the temperature change T5 of the temperature detector model 31a corresponds to the actual temperature change. For example, even if the temperatures of the coil, stator core, and the like deviate further from the actual temperatures, the parameters of the electric motor model are adjusted so that the temperature detector temperature displays a value close to the actual temperature. It should be noted that as a result of calculating the heat capacity and heat transfer coefficient, all heat capacities of the constituent parts and all heat transfer-related coefficients can accurately correspond to the actual heat capacity and heat transfer-related coefficient.When the temperature estimation unit estimates the temperatures of the constituent parts, the temperatures of all constituent parts can be exactly consistent with the actual temperatures of the constituent parts.

[0051] The electric motor monitoring device 2 according to the present embodiment is configured to be capable of switching between a normal model generation mode for calculating a parameter of a first model of an electric motor when an operating state of the electric motor is normal, and an abnormal model generation mode for generating a second model of the electric motor when the operating state of the electric motor is abnormal. In the normal model generation mode, parameters including a coefficient related to heat transfer and a heat capacity of a constituent part are set in the first model 10a for the electric motor.

[0052] Referring to Fig. 1, the parameter calculation unit 63 of the present embodiment generates a first model for an electric motor in a normal model creation mode. The parameter calculation unit 63 sets the heat capacity, the heat transfer coefficient, and the constants k1 and k2 in equations (6) and (7) included in the model 10a for the electric motor. The operator actually drives the electric motor 10 according to a predetermined running pattern. The state detection unit 62 detects the load factor of the electric motor 10, the rotational speed of the electric motor 10, and the temperature output from the temperature detector 31 as a state of the electric motor 10. In addition, the state detection unit 62 detects the outside air temperature from the outside air temperature detector 33.

[0053] Fig.shows a diagram of a running pattern when the electric motor is driven to set the parameters of the first model for the electric motor according to the present embodiment. Fig. shows the no-load running pattern. In this running pattern, the speed of the electric motor 10 is gradually increased without loading the electric motor 10. The speed of the electric motor 10 is increased by temporarily increasing the load factor of the electric motor at predetermined time intervals.

[0054] The temperature detected by the temperature detector 31 gradually rises. At times t1 to t7, the rotational speed of the electric motor 10 is increased by temporarily increasing the load factor of the electric motor 10. The state detection unit 62 detects the operating state of the electric motor 10 and the temperature output from the temperature detector 31 during the period in which the rotational speed of the electric motor 10 is gradually increased. More specifically, the state detection unit 62 detects the load factor of the electric motor 10, the rotational speed of the electric motor 10, and the temperature output from the temperature detector 31 every predefined minute and stores them in the memory 51. In the present embodiment, a constant outside air temperature is assumed, but the embodiment is not limited to this. The state detection unit 62 may detect the outside air temperature every minute from the outside air temperature detector 33.

[0055] Referring to Fig. 1, the state detection unit 62 detects a torque command included in the operation command generated by the operation control unit 43 of the machine controller 41. The torque command corresponds to the load factor of the electric motor 10, so that the state detection unit 62 can calculate the load factor from the torque command.

[0056] The parameter calculation unit 63 calculates the parameters of the model 10a for the electric motor based on the variables acquired by the state detection unit 62. The parameter calculation unit 63 according to the present embodiment calculates parameters including the heat capacities C1, C2, C3, C4, and C5 and the heat transfer coefficients ha, hb, hc1, hc2, hc3, and hd based on the heat-generating amount in the coil 16 and the stator core 20 and the temperature detected by the temperature detector 31. In addition, the parameter calculation unit 63 calculates the constants k1 and k2 in equations (6) and (7) as parameters. The parameter calculation unit 63 calculates the parameters so that the change in the estimated temperature of the model 31a for the temperature detector when performing the simulation approximates the change in the actually measured temperature.

[0057] The parameter calculation unit 63 sets an initial value for each parameter. The initial values ​​of the parameters can be set arbitrarily. The parameter calculation unit 63 calculates the amount of heat generated due to the primary copper loss of the coil 16 and the amount of heat generated due to the iron loss of the stator core 20 with the aid of the loss calculation unit 54. The loss calculation unit 54 calculates the primary copper loss P c1 and the iron loss P i using Table 1 and equations (6) to (10) based on the rotational speed of the electric motor 10 and the load factor of the electric motor 10 detected by the state detecting unit 62.

[0058] Equations (6) and (7) for calculating the primary copper loss P c1 and iron loss P icontain the constants k1 and k2. In addition, the loss calculation unit 54 calculates the loss for the specified minute time dt, ie, the heat-generating amount for one minute. Thus, the loss calculation unit 54 calculates the primary copper loss P c1 and the iron loss P i in equations (1) and (2) based on the actual measured values ​​including the operating command (load factor) for the electric motor and the output of the rotation position detector 32.

[0059] The parameter calculation unit 63 estimates the temperature of the constituent part using the temperature calculation unit 55. The temperature calculation unit 55 calculates the estimated temperature of the temperature detector 31 based on the first electric motor model 10a using the respective parameters and the loss calculated by the loss calculation unit 54. In other words, the temperature of the temperature detector model 31a is estimated by simulation.

[0060] The temperature calculation unit 55 can calculate the change in the estimated temperature detected by the temperature detector 31 over time after the start of the drive of the electric motor 10 based on the experimentally set parameters. The model temperature for each constituent part of the electric motor 10 can be calculated using the differential equations of equations (1) to (5) above. The initial value of the model temperature for each constituent part can be set, for example, to the outside air temperature, that is, the room temperature at the start of the drive of the electric motor 10.

[0061] The evaluation unit 66 of the parameter calculation unit 63 compares the temperature (estimated temperature) of the temperature detector model 31a calculated by the temperature calculation unit 55 with the temperature actually measured by the temperature detector 31, and thus evaluates the parameter set provisionally set in the first model 10a for the electric motor. In this example, the evaluation unit 66 evaluates only the temperature of the temperature detector model 31a, without evaluating any variables other than the temperature of the temperature detector model 31a. The temperature change of the temperature detector model 31a only needs to be close to the actual temperature change, and the temperature of at least some of the temperatures of the other constituent parts is not evaluated.

[0062] Subsequently, the parameter change unit 67 of the parameter calculation unit 63 changes the parameter based on the evaluation result in the evaluation unit 66. Then, based on the changed parameter, the calculation of the loss by the loss calculation unit 54, the calculation of the estimated temperature of the model for the temperature detector by the temperature calculation unit 55, the evaluation by the evaluation unit 66, and the change of the parameter by the parameter change unit 67 are repeated through the same calculation as above. If the evaluation by the evaluation unit meets the predetermined conditions of FIG. 1, the determination can be made as the final parameter.

[0063] In this regard, the number of combinations of a plurality of parameters in the model 10a for the electric motor is very large. The plurality of parameters can be defined by a machine learning method. For example, the plurality of parameters can be set by a Bayesian optimization method. In Bayesian optimization, an objective function to be evaluated is generated for explanatory variables, including parameters to be input. Then, the parameters for which the objective function is predicted to be minimum or maximum are searched for and set. By repeating this parameter search, the optimal value of the parameters can be determined. In addition, the range within which each parameter is set can be set in advance.

[0064] In this example, with respect to the temperature of the temperature detector 31, a difference between the temperature (estimated temperature) of the temperature detector model 10a, which is estimated by the model 31a for the electric motor, and the actually measured temperature detected by the temperature detector 31 is set as the objective function. In other words, with respect to the temperature of the temperature detector 31, the objective function may use a difference between the predicted value calculated from equations (1) to (5) based on the experimentally set parameters and the value actually measured by the temperature detector 31. For example, the average value of the differences within one minute of time or the like may be used as the objective function. Then, the parameter changing unit 67 searches for the next parameter to reduce the objective function.

[0065] With Bayesian optimization, the parameter search and evaluation can be repeated. The evaluation unit 66 can accept the parameter values ​​at this time as long as the objective function lies within a specified range. However, if the objective function deviates from the specified range, the next parameter search can be performed. With the Bayesian optimization method, the computational effort is reduced because the search is performed by predicting the range in which the solution exists.

[0066] The parameters of the electric motor model 10a can be set using any method in addition to setting the parameters by Bayesian optimization. For example, a range within which each parameter is set can be defined in advance. The parameter changing unit 67 of the parameter calculating unit 63 randomly sets a plurality of parameters within a parameter range. The temperature calculating unit 55 estimates the temperature of the model 31a for the temperature detector based on the set parameters. The evaluation unit 66 can evaluate the set parameters based on the actual measured values ​​of the temperatures detected by the temperature detector 31. Such a parameter setting method is called a random search method.

[0067] Alternatively, the parameter change unit 67 can adjust parameters at predetermined intervals within the range in which the parameters are set. The temperature calculation unit 55 estimates the temperature of the model 31a for the temperature detector using the set parameters. The evaluation unit 66 performs an evaluation for all combinations of discretely set parameters. This method is called the grid search method.

[0068] In the random search method or the grid search method, the evaluation unit 66 evaluates the temperature of the temperature detector 31, as in the Bayesian optimization method. The evaluation unit 66 can adopt the parameter values ​​at this time as long as the objective function lies within a predefined determination range. Alternatively, the evaluation unit 66 can also adopt the parameters for which the objective function is optimal. The evaluation unit 66 can determine a parameter in the model 10a for the electric motor such that the estimated temperature of the temperature detector 31 agrees well with the actual temperature measured and detected by the temperature detector 31.

[0069] In the present embodiment, the parameters are set so that a temperature change detected by the temperature detector 31 can be accurately estimated. In the present embodiment, only the temperature of the temperature detector that detects the temperature of the coil can be evaluated during parameter evaluation, since the temperatures of the constituent parts not connected to the temperature detector 31 may deviate from the actual temperatures. In this way, parameters can be set in a short period of time with little computational effort. The generated first model 10a of the electric motor can be stored in the memory 51.

[0070] In the above embodiment, for setting the parameters of the first model 10a of the electric motor, idle operation is described as the operation pattern for driving the electric motor 10, but the embodiment is not limited to this. When setting the parameters of the first model 10a of the electric motor, it is advantageous to operate the electric motor 10 in various operation patterns to detect the operating state of the electric motor 10. For example, a running pattern in which the load factor of the electric motor 10 repeatedly increases and decreases can be adopted. The load factor of the electric motor 10 can be changed greatly to change the rotational speed of the electric motor. The temperature detected by the temperature detector 31 increases or decreases rapidly. As described above, it is possible to adopt a running pattern with a steep temperature change of the electric motor.

[0071] In the above embodiment, the coil including the windings, which serves as a constituent part of the electric motor for estimating temperature, was described as an example, but the embodiment is not limited to this. Any constituent part of the electric motor can be used as a constituent part for calculating the estimated temperature. Then, a temperature detector can be attached to a constituent part to calculate the estimated temperature.

[0072] In the above embodiment, a synchronous electric motor in which the rotor has a permanent magnet is described, but the embodiment is not limited to this. The overall monitoring device according to the present embodiment can be applied to any electric motor. For example, the model for the electric motor in the present embodiment can also be applied to an induction motor in which the rotor does not have a permanent magnet.

[0073] Fig. 5 shows a model for a second electric motor according to the present embodiment. Fig.Figure 5 illustrates a first model 30a when the operating state of the second electric motor is normal. In this case, the second electric motor is an induction motor. The rotor of an induction motor includes a basket-shaped conductor made of stainless steel, copper, or the like. The basket-shaped conductor is attached to the shaft and rotates along with the shaft. In an induction motor, the magnetic force generated by the stator coil causes an induced current to flow inside the basket-shaped conductor. A magnetic field is generated around the basket-shaped conductor, and the rotor rotates.

[0074] In an asynchronous motor, a secondary copper loss P (c2)as secondary loss when current flows through the basket-shaped conductor of the rotor. The secondary loss corresponds to the Joule heat dissipated by the current flowing through the basket-shaped conductor. In model 30a for the second electric motor, heat is generated in the rotor due to the secondary copper loss. The heat capacities of the constituent parts and the heat transfer coefficients between the constituent parts of the second electric motor are comparable to those of the first model 10a for the first electric motor.

[0075] In the differential equation for the temperature change of the constituent part in model 30a of the second electric motor, the differential equation for calculating the temperature change of the rotor is different from that of the first model 10a of the first electric motor. The differential equation for expressing the temperature change of the rotor is represented by equation (11) below. [Math. 5] dT4dt=Pc2+hc3(T3−T4)C4 P c2 : Secondary copper loss

[0076] In equation (11), the heat-generating amount of secondary copper loss P c2 added to equation (4) of Model 11a for the rotor of the first electric motor. The differential equations representing the temperature changes in the other components—the coil, the stator core, the air layer, and the temperature detector—are the same as the differential equations in a thermal model for the first electric motor.

[0077] The loss calculation unit 54 calculates the amount of heat generated by secondary copper loss in the rotor conductor. The loss calculation unit 54 estimates the current flowing through the basket-shaped conductor. The loss calculation unit 54 can calculate the secondary copper loss from the current flowing through the conductor, the secondary resistance of the conductor, the inductance of the conductor, and the mutual inductance between the conductor, the stator, and the coil. The inductance of the conductor, the mutual inductance, and the secondary resistance of the conductor can be defined in advance.

[0078] The total loss P t and the primary copper loss P c1 in an asynchronous motor can be calculated in a similar way to the total loss and the primary copper loss in a synchronous motor. Then the iron loss P i taking into account the secondary copper loss P (c2)can be calculated according to equation (12). [Math. 6] Pi=Pt−Pc1−Pc2 P i : Iron loss

[0079] In this way, the primary copper losses, iron losses, and secondary copper losses are calculated in the first model 30a of the second electric motor. Also, in the first model 30a of the second electric motor, the parameter calculation unit 63 can calculate parameters included in the first model 30a of the second electric motor when the operating state of the first electric motor is normal, through the same control as that of the first model 10a of the first electric motor. Then, the temperature estimation unit 53 can calculate the estimated temperature of the constituent part when the operating state of the electric motor is normal using the first model 30a of the second electric motor.

[0080] Fig.1 shows a graph of the estimated temperature of the temperature detector, which is estimated by the temperature estimation unit using the parameters calculated by the parameter calculation unit of the present embodiment. In this case, an example of a second electric motor is shown. Fig. Figure 6 shows a diagram when the simulation is performed with a parameter set A and a parameter set B whose values ​​are different from each other. The parameter set A and the parameter set B are calculated by the parameter calculation unit 63. The parameters included in the parameter set A and the parameter set B are listed in Table 2. [Table 2] Table 1 Parameter Unit of heat transfer coefficients: [W / K] Unit of mass: [kg] Parameter set A Parameter set B Heat transfer coefficient ha 5.48 6.72 Heat transfer coefficient hb 10.82 13.78 Heat transfer coefficient hc1 2.82 1.49 Heat transfer coefficient hc2 1.056 13.35 Heat transfer coefficient hc3 7.5 7.26 Heat transfer coefficient hd 14.7 4.88 Mass m1 of the coil 1.37 1.37 Mass m2 of the stator core 23.19 24.2 Mass m3 of the air layer 0.00347 0.000353 Mass m4 of the rotor 3.43 4.7 Masse m5 des Temperaturdetektors 0.072 0.02

[0081] Parameter set A and parameter set B are determined by operating the second electric motor with different running patterns. Table 2 describes the heat transfer coefficients, which are determined by multiplying the heat transfer coefficients between the respective constituent parts of the electric motor and the contact surfaces. In addition, the heat capacity is also calculated by multiplying the specific heat of the material of each of the constituent parts by the mass. The specific heat of each material can be predetermined, so Table 2 specifies the mass m of each constituent part for calculating the heat capacity. Comparing parameter set A with parameter set B, it can be seen that some parameters, such as the heat transfer coefficients hc2 and hd and the rotor mass m4, have very different values ​​between the two parameter sets A and B.

[0082] On the other hand, Fig. 6 shows that the estimated temperature of the temperature detector calculated using parameter set B is in good agreement with the estimated temperature of the temperature detector calculated using parameter set A. In particular, the temperature change during both the period in which the temperature increases and the period in which the temperature fluctuates within a given range is in good agreement. In addition, the Fig. 6, the temperature change estimated by the temperature estimation unit 53 agrees well with the temperature change detected by the temperature detector 31 when the electric motor 10 is actually driven.

[0083] There are parameters whose values ​​differ significantly between parameter set A and parameter set B. It can be seen that at least one parameter from the group of parameter set A and parameter set B has different values ​​than the parameter set of the current electric motor. In particular, it can be seen that at least some of the numerous heat capacities and the numerous heat transfer-related coefficients are set to values ​​that differ from the actual heat capacities or the actual heat transfer-related coefficients. For example, with the coefficient hc2 of parameter set A and the coefficient hc2 of parameter set B, it can be seen that at least one of the heat transfer-related coefficients is far from the actual heat transfer-related coefficient.

[0084] As described above, in the electric motor monitoring device of the present embodiment, the temperature of the temperature detector can be accurately estimated even if at least some of the plurality of parameters deviate from the actual values. Furthermore, the parameter calculation unit of the present embodiment can adjust parameters of such a model of the electric motor.

[0085] Although a temperature detector is mounted on the electric motor in the present embodiment, the present embodiment is not limited thereto. A plurality of temperature detectors may be mounted on a plurality of constituent parts of the electric motor. The evaluation unit of the parameter calculation unit may compare the measured temperatures of the plurality of temperature detectors with the estimated temperature obtained through the simulation. The parameter changing unit may adjust the parameter of the first model of the electric motor so that the estimated temperature of the plurality of constituent parts approaches the measured temperature detected by the actual temperature detectors.

[0086] The more temperature detectors mounted on the electric motor, the closer the respective values ​​of the various parameters of the first model of the electric motor can be to the actual values. Furthermore, the estimated temperature of the constituent part of each electric motor can be made close to the actually measured temperature. As a result of mounting the multiple temperature detectors, all heat capacities and all heat transfer-related coefficients can be substantially identical to the actual heat capacities and heat transfer-related coefficients. In this case, when the temperature estimation unit estimates the temperatures of the constituent parts, the temperatures of all constituent parts accurately correspond to the actual temperatures of the constituent parts.

[0087] Next, a mode for generating an abnormality model will be described for generating a second model of the electric motor when the operating state of the electric motor is abnormal. Furthermore, an electric motor monitoring device 2 according to the present embodiment provides an operator or other device with information for estimating a part where an abnormality occurs based on the second model of the electric motor.

[0088] Referring to Fig. 1, the electric motor monitoring device 2 of the present embodiment includes a model search unit 71 for generating a second model for the electric motor when the operating state of the electric motor is abnormal. The model search unit 71 includes a temperature determination unit 72 for determining 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.

[0089] When a difference between the measured temperature of the temperature detector 31 and the estimated temperature of the temperature detector 31 based on the first model deviates from a predetermined determination range, the model search unit 71 includes a component addition unit 73 for generating a second model by adding a model for an additional component that performs heat exchange with a model for a constituent part of the electric motor to the first model. In other words, when the difference between the estimated temperature and the measured temperature is large, the component addition unit 73 adds the model of the additional component to the model when the operating state of the electric motor is normal.

[0090] The model search unit 71 includes a setting unit 74 for setting a model for a constituent part of the electric motor that performs heat exchange with a model for the additional component. The setting unit 74 sets the heat capacity of the additional component and the heat transfer coefficient of the additional component. The heat transfer coefficient of the additional component includes a heat transfer coefficient between the model of the constituent part of the electric motor that performs heat exchange and the additional component. The monitoring device 2 according to the present embodiment further includes an abnormal part estimation unit 75 for estimating an abnormality occurring in the electric motor 10 or around the electric motor 10.The monitoring device 2 includes a notification unit 76 for notifying another device of information about the second model of the electric motor.

[0091] Each of the model search unit 71, the temperature determination unit 72, the component addition unit 73, and the setting unit 74 corresponds to a processor controlled according to a pre-prepared program. Furthermore, the abnormal part estimation unit 75 and the notification unit 76 correspond to a processor controlled according to a pre-prepared program. By reading the program and executing the control defined in the program, the processor functions like each of the units.

[0092] In the following description, the Fig. 2 shown first electric motor and the one in Fig. 3 is described for the first electric motor, but is not limited thereto. For the second electric motor and the Fig. In the model shown in Figure 5 for the second electric motor, a similar control can be performed as for the first electric motor. Furthermore, similar to the normal model creation mode, the temperature detected by the temperature detector 31 attached to the coil 16 will be described using an example.

[0093] If an abnormality occurs in the electric motor, the temperature of the electric motor may rise. If the measured temperature of the temperature detector attached to the electric motor deviates from a predetermined determination range based on the estimated temperature during normal operation of the electric motor, it is determined that an abnormality has occurred in the electric motor or the surrounding area of ​​the electric motor. In other words, it is determined that the operating condition of the electric motor is abnormal.

[0094] Fig. Figure 7 shows a diagram illustrating a temperature change during normal operation of the first electric motor. The vertical axis of the diagram represents the temperature of the temperature detector 31 attached to the coil 16 (see Fig. 1 and Fig. 7). The horizontal axis represents the elapsed time. The solid line indicates the measured temperature actually detected by the temperature detector 31. In other words, the measured temperature detected by the state detection unit 62 is displayed.

[0095] In this example, the power supply is started at time t0, and the load of the electric motor 10 is rapidly increased. As the current increases, the temperature of the temperature detector 31 rises rapidly. At time t1, the current supplied to the electric motor 10 is reduced. The speed of the electric motor 10 is maintained at a substantially constant no-load speed. After time t1, the temperature of the temperature detector 31 gradually decreases over time.

[0096] In Fig. The estimated temperature of the temperature detector 31, which is estimated from the first model 10a of the first electric motor, is represented by a dashed line. The first model 10a of the electric motor is created in advance in the normal model creation mode. It can be seen that, under the normal operating state of the electric motor, the estimated temperature of the temperature detector 31, which is estimated from the first model 10a of the electric motor, is in good agreement with the measured temperature detected by the temperature detector 31.

[0097] Fig. Figure 8 is a diagram illustrating a temperature change when an abnormality occurs in the operating state of the first electric motor. The operating state of Fig. 8 is the same as the operating state of Fig. 7. With reference to the Fig. 1, Fig. 2 and Fig. 8, the load is increased from time t0 to time t1. At time t1, the load is set to zero. In a period from time t0 to time t2, the operating state of the electric motor is normal. The temperature measured by the temperature detector 31 is in good agreement with the estimated temperature calculated by the first model 10a of the electric motor.

[0098] However, in a period EP from time t2 to time t3, an abnormality occurs in the electric motor 10, and the measured temperature temporarily rises. In this case, an example will be described in which the lubrication condition of the bearings 14 and 15 of the electric motor 10 is temporarily deteriorated. 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 condition of the electric motor returns to normal.

[0099] The model search unit 71 of the monitoring device 2 determines that the operating state of the electric motor 10 in the EP section is abnormal. The model search unit 71 generates a second model of the electric motor if the operating state of the electric motor 10 is abnormal. The model search unit 71 generates a second model by adding an additional component to the first model. Then, in the EP section, the model search unit 71 adjusts the parameters for the model of the constituent part of the electric motor that performs heat exchange with the additional component and the second model so that they closely correspond to the change in the actually measured temperature.

[0100] Subsequently, the monitoring device 2 displays information about the second model of the electric motor on the display part and informs the operator of this information. The operator can estimate the location of the electric motor where the abnormality has occurred based on the information about the second model of the electric motor. Alternatively, the abnormal part estimation unit 75 estimates the location where the abnormality occurs based on the second model of the electric motor.

[0101] During the period in which the electric motor is operating, the state detection unit 62 of the monitoring device 2 detects the operating state of the electric motor at predetermined time intervals. The temperature estimation unit 53 calculates an estimated temperature of each constituent part of the electric motor based on the operating state detected by the state detection unit 62 and the first model of the electric motor. Specifically, in the present embodiment, the estimated temperature of the temperature detector 31 is calculated at predetermined time intervals.

[0102] The state detection unit 62 detects the measured temperature output of the temperature detector 31 at predetermined time intervals. The memory 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, for example, at every one-second interval.

[0103] 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 deviates from a predetermined determination range. The temperature determination unit 72 may, for example, calculate a moving average of the difference between the measured temperature and the moving temperature. The temperature determination unit 72 may, for example, calculate a moving average of the last 1 minute. Then, if the moving average deviates from a predetermined determination range, it can be determined that the difference between the measured temperature and the determination temperature deviates from the determination range. The temperature determination unit 72 may determine that an abnormality occurred at a time point in the middle of the moving average section.

[0104] It should be noted that the temperature determination unit can determine whether the difference between the measured temperature and the estimated temperature deviates from the determination range through any 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. If the absolute value is greater than the determination value, it can be determined that the difference between the measured temperature and the actually measured temperature deviates from the determination range.

[0105] According to Fig. 8, the temperature determination unit 72 determines that the difference between the measured temperature and the estimated temperature in a section EP from time t2 to time t3 deviates from the determination range. In other words, 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 identify the start time and end time of the section EP in which the measured temperature of the temperature detector 31 is abnormal.

[0106] Fig. Fig. 9 shows an example of a second model of the electric motor according to the present embodiment. Referring to Figs. Fig. 1, Fig. 3, Fig. 8 and Fig. 9, the model search unit 71 generates a second model 10b of the first electric motor, as in Fig. 9. When the section EP in which the temperature of the electric motor is abnormal occurs, the component addition unit 73 of the model search unit 71 adds a model 81a of an additional component X to the Fig. 3. The component addition unit 73 creates the second model 10b by adding the model 81a of the additional component X, which performs heat exchange with the model for the constituent part of the electric motor.

[0107] The setting unit 74 of the model search unit 71 selects a model of a constituent part of the electric motor that performs heat exchange with the additional component X. In the Fig. In the example shown in Figure 9, priorities are set for constituent parts of the first model of the electric motor. The coil is set as the first priority. The setting unit 74 sets the coil model 16a as the model of the constituent part that performs heat exchange with the additional component X. The setting unit 74 changes an equation for calculating the temperature of the constituent part of the electric motor. The setting unit 74 can set the temperature T X and the heat capacity C X for the additional component X. The setting unit 74 sets a coefficient hx1 that relates to the heat transfer between the model 16a of the coil and the model 81a of the additional component X. In this example, the setting unit 74 sets the heat generation amount P X generated by the additional component X.

[0108] In the second electric motor model 10b, the temperature change rate T1 of the coil model 16a is expressed by the following equation (13). In equation (13) of the temperature change rate of the coil model 16a, an element of heat transfer from the additional component X is added to equation (1). In addition, the temperature change rate T X of the additional component X is expressed by equation (14). Equation (14) contains elements that relate to the heat-generating quantity P X and heat exchange with model 16a for the coil. [Math. 7] dT1dt=Pc1+ha(T2−T1)+hc1(T3−T1)+hx1(Tx−T1)C1 dTxdt=Px+hx1(T1−Tx)Cx T x : Temperature of the additional component X , Cx: Heat capacity of the additional component hx1: Heat transfer coefficient P x : Heat generation amount of the additional component X

[0109] The setting unit 74 sets the heat capacity C x , the heat-generating quantity P X and the heat transfer-related coefficient hx1 in the second model 10b such that the estimated temperature of the model 31a of the temperature detector of the second model 10b corresponds to the measured temperature of the temperature detector 31 in the section EP. The parameters of the other constituent parts defined in the first model 10a are used unchanged. In the present embodiment, the ranges of the numerical values ​​of the heat capacity C X , the heat-generating quantity P X and the coefficient hx1 related to the heat transfer of the additional component X. The setting unit 74 performs a grid search process to change a parameter at predetermined intervals within a range of each parameter.

[0110] The heat generation quantity P Xassume a constant value that does not depend on the load of the electric motor. In addition, the amount of heat generated P X be a fixed value that does not change within the parameter range. The initial temperature T X of the additional component in section EP, an average value of the temperatures of several constituent parts of the electric motor that performs heat exchange with the additional component X can be assumed. Alternatively, the initial temperature T X the temperature of a constituent part of the electric motor that carries out the heat exchange with the additional component.

[0111] In addition, the additional component X can be kept at a constant temperature. In other words, the temperature T X of the additional component X is set to a given temperature. In this case, equation (14) is not required, and the heat capacity C Xthe additional component X is not necessary.

[0112] The loss calculation unit 54 of the temperature estimation unit 53 retrieves the operating state of the electric motor in the EP section from the memory 51 and calculates the loss. The temperature calculation unit 55 of the temperature estimation unit 53 calculates the estimated temperature from the model 31a of the temperature detector using the second model 10b in the EP section. For the parameters, except for the parameters related to the additional component X, the same values ​​as for the parameters of the first model 10a are used.

[0113] The temperature determination unit 72 of the model search unit 71 retrieves the measured temperature of the temperature detector 31 in the EP section from the memory 51. The temperature determination unit 72 calculates a difference between the measured temperature of the temperature detector 31 and the estimated temperature. The difference between the measured temperature of the temperature detector 31 and the estimated temperature is calculated as the value of the moving average over a predetermined period of time. The temperature determination unit 72 can calculate the difference between the measured temperature and the estimated temperature of the temperature detector 31 at each sampling time interval.The memory 51 stores the constituent parts of the electric motor with which the additional component X performs heat exchange, the values ​​of parameters such as the heat capacity of the second model 10b and the difference between the measured temperature and the estimated temperature of the temperature detector 31.

[0114] Next, the setting unit 74 changes the parameter related to the additional component X within a predetermined range of the parameter and repeats a similar calculation and saves the calculation result. The setting unit 74 changes the parameters of the heat transfer coefficient hx1, the heat capacity C X and the heat generation quantity P Xgradually at predetermined intervals. The model search unit 71 calculates the difference between the measured temperature and the estimated temperature while gradually changing the parameter contained in the second model. The model search unit 71 performs the calculation in all parameter combinations. The memory 51 stores the difference between the measured temperature and the actually measured temperature for each parameter combination.

[0115] Subsequently, the setting unit 74 changes a constituent part of the electric motor in which the additional component X performs heat exchange. For example, the setting unit 74 sets the air layer model 35a as a constituent part that performs heat exchange with the additional component X. The constituent part of the electric motor in which the additional component X performs heat exchange can be determined based on a predetermined priority, 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 in the EP section and the estimated temperature, while changing the parameter such as the heat capacity of the second model 10b. The memory 51 stores the calculation result.

[0116] In this way, the setting unit 74 generates the second model and performs a calculation in which the additional component X performs heat exchange with the constituent parts of the electric motor. The setting unit 74 performs a calculation in which the additional component X performs heat exchange with a constituent part for all components. In each second model, a difference between the measured temperature of the temperature detector 31 in the EP section and the estimated temperature is calculated.

[0117] Next, the model search unit 71 determines two constituent parts by increasing the number of constituent parts of the electric motor in which the additional component X performs heat exchange by one, and repeats a similar calculation and stores the calculation result. 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 EP section when the number of constituent parts of the electric motor that performs heat exchange is two, and stores the calculation result. The model search unit 71 repeats the calculation and storage for all combinations of the two constituent parts.Next, the model search unit 71 determines three constituent parts by increasing the number of constituent parts of the electric motor in which the additional component X performs heat exchange by one, and repeats a similar calculation and stores the calculation result.

[0118] In this way, the model search unit 71 repeats the calculation and storage by increasing the number of constituent parts of the electric motor in which the additional component X performs heat exchange by one. The calculation is performed for all combinations of the constituent parts in which the additional component X can perform heat exchange. In this example, the calculation and storage are repeated until the additional component X performs heat exchange simultaneously with all constituent parts of the electric motors.

[0119] 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 measured temperature and the estimated temperature of the temperature detector 31 from the plurality of calculation results stored in the memory 51. For example, in the EP section, the second model with the smallest root mean square of the difference between the measured temperature and the estimated temperature of the temperature detector 31 is selected. For this second model, the model search unit 71 determines from the memory 51 the constituent parts of the electric motor in which the additional component X performs heat exchange, as well as parameters such as the heat capacity of the additional component X, the heat transfer coefficient, and the heat generation amount of the additional component X.

[0120] Fig. 10 shows a second model searched by the model search unit when an abnormality occurs in the bearing. Among the plurality of second models searched by the model search unit 71, the second model 10c with the smallest difference between the measured temperature and the estimated temperature of the temperature detector 31 is shown. Fig. For example, Figure 8 shows a temperature change of the temperature detector when an abnormality occurs in the bearing. As shown in Fig. As shown in Figure 2, the temperatures of bearings 14 and 15 rise when an abnormality occurs in the bearing.

[0121] Bearings 14 and 15 are located near rotor 11, coil 16, and the air layer between rotor 11 and coil 16. The heat generated in bearings 14 and 15 is easily transferred to rotor 11, coil 16, and the air layer between rotor 11 and coil 16. For this reason, when the model search unit 71 searches for the second model, the second model 10c is generated such that the additional component X that generates heat exchanges with the coil, the rotor, and the air layer between the coil and the rotor. In other words, the models for the constituent parts of the electric motor in which the model 81a of the additional component X exchanges heat are the coil model 16a, the air layer model 35a, and the rotor model 11a.

[0122] In the second model 10c of the electric motor, the rate of change of temperature T1 of model 16a for the coil is expressed by equation (13) above. The rate of change of temperature T3 of model 35a for the air layer is given by equation (15) below. The rate of change of temperature T4 of model 11a for the rotor is given by equation (16) below. In addition, the rate of change of temperature T X of the additional component X is expressed by equation (17). [Math. 8] dT3dt=hc1(T1−T3)+hc2(T2−T3)+hc3(T4−T3)+hx2(Tx−T3)C3 dT4dt=hc3(T3−T4)+hx3(Tx−T4)C4 dTxdt=Px+hx1(T1−Tx)+hx2(T3−Tx)+hx3(T4−Tx)Cx T x : Temperature of the additional component X , Cx: Heat capacity of the additional component hx1, hx2, hx3: Heat transfer coefficient P x : Heat generation amount of the additional component X

[0123] The setting unit 74 sets a parameter that minimizes the difference between the measured temperature and the estimated temperature of the temperature detector in the section EP where the abnormality occurs. In this example, the setting unit 74 sets a coefficient hx1 related to the heat transfer between the model 81a for the additional component X and the model 16a for the coil, a coefficient hx2 related to the heat transfer between the model 81a for the additional component X and the model 35a for the air layer, and a coefficient hx3 related to the heat transfer between the model 81a for the additional component X and the model 11a for the rotor. In addition, the setting unit 74 sets the heat capacity C X and the heat generation quantity P X in the additional component X. This sets the values ​​of the parameters related to the additional component X.

[0124] Then, the display part 52 of the monitoring device 2 displays information about the second model 10c created by the model search unit 71. In this case, the information about the second model 10c for which the estimated temperature of the temperature detector best matches the measured temperature is displayed on the display part 52. The display part 52 displays at least one piece of information selected from a group of the model for the constituent part of the electric motor that performs heat exchange with the model 81a for the additional component, the heat capacity C X of the model 81a for the additional component, the heat transfer coefficients hx1, hx2 and hx3 and the heat generation quantity P X is selected.

[0125] The operator can estimate the part and cause of the abnormality based on the information from the second model. It can be estimated that there is a heat-generating part near the constituent part of the electric motor that performs heat exchange with the auxiliary component X. In addition, the operator can estimate the distance between the constituent part of the electric motor and the auxiliary component X based on the heat transfer coefficient. For example, if the heat transfer coefficient is large, it can be estimated that the distance between the heat-generating part and the constituent part of the electric motor that performs heat exchange is short.

[0126] 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. Furthermore, the cause of heat generation can be estimated based on the amount of heat generated by the additional component. For example, if the amount of heat generated is within a specified range, it can be estimated as a bearing lubrication defect.

[0127] In this way, the operator can estimate the area where the electric motor abnormality occurs and its cause based on the information related to the second model searched by the model search unit. The operator can detect that an abnormality has occurred before the electric motor fails. The operator can repair or replace the electric motor before the electric motor fails. Alternatively, it is possible to analyze countermeasures until the electric motor fails. For example, the load on the machine can be reduced until the electric motor is replaced to delay the time of electric motor failure.

[0128] In the above embodiment, the model search unit 71 performs a calculation for all combinations of the additional component and the constituent parts of the electric motor. Furthermore, the model search unit 71 changes all parameters of the second model within a predetermined range. Then, the second model is selected in which the difference between the measured temperature and the estimated temperature of the temperature detector is minimized, but the embodiment is not limited to this.

[0129] For example, a permissible range for the difference between the estimated temperature and the measured temperature of the temperature detector can be set in advance. The setting unit can stop the search for the second model when the difference between the estimated temperature and the measured temperature of the temperature detector is within a permissible range. The setting unit can adopt a constituent part of the electric motor that performs heat exchange with the additional component at this time and parameters of the second model.

[0130] Alternatively, the memory can store the second model generated in the past. The priority of the constituent parts of the electric motor in which the additional component performs heat exchange and the priority of the value of the parameter of the second model can be determined in advance based on the previous results. The setting unit can perform the search in order of priority. Then, the search for 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.

[0131] Furthermore, in the present embodiment, after the second model is generated when the electric motor is abnormal, the information about the second model is displayed on the display part, but the embodiment is not limited to this. The monitoring device 2 according to the present embodiment includes the notification unit 76 that notifies another device of information about the second model. For example, the notification unit 76 may notify another device of at least one piece of information selected from the group consisting of the model of the constituent part of the electric motor that performs heat exchange with the model of the additional component, the heat capacity of the additional component, and the heat transfer coefficient of the additional component.

[0132] The other device can perform any control in response to the notification unit 76. For example, the machine controller 41 can receive information about the second model from the monitoring device 2. Then, the machine controller 41 can change the operating state of the machine 1. For example, the machine controller 41 can reduce the speed at which the electric motor is driven or change the rate of speed increase and decrease.

[0133] Referring to Fig. 1, the monitoring device 2 of the present embodiment includes an abnormal part estimation unit 75. The abnormal part estimation unit 75 can estimate an abnormal part of the electric motor based on the information about the second model generated by the model search unit 71. The model search unit 71 of the monitoring device 2 creates a second model of the electric motor each time an abnormality occurs in the electric motor. Then, the operator inputs the part and the cause of the abnormality into the monitoring device 2. The memory 51 stores the part and the cause of the abnormality together with the second model for the electric motor. The memory 51 stores the second model for the electric motor generated in the past, as well as the part and the cause of the abnormality input by the operator.

[0134] The abnormal part estimation unit 75 estimates the part and cause of the abnormality with respect to the second model for the electric motor generated this time based on the second model for the electric motor generated in the past and the part and cause of the abnormality. For example, the abnormal part estimation unit 75 selects a second model from among the second models acquired in the past in which the constituent part of the electric motor that performs heat exchange with the additional component in the current second model is the same. Then, the abnormal part estimation unit 75 selects a second model with similar parameters (heat transfer coefficient, heat capacity, and heat generation amount). A determination range can be specified for each parameter.The abnormal part estimation unit 75 can determine whether the parameter is a narrow value based on the determination range. The abnormal part estimation unit 75 can select a plurality of second models. The display part 52 can display the previous second model selected by the abnormal part estimation unit 75, as well as the part and the cause of the abnormality.

[0135] The abnormal parts estimation unit can estimate the part and cause of the abnormality of the electric motor using any method. For example, the abnormal parts estimation unit can estimate the part and cause of the abnormality of the electric motor using machine learning. The abnormal parts estimation unit generates a learning model for estimating a part and cause of an abnormality of the electric motor based on a second model for the electric motor in the past. For example, the abnormal parts estimation unit can perform supervised learning. The abnormal parts estimation unit generates a learning model using the second model for the electric motor in the past and the part and cause of the abnormality as teacher data.The abnormal part estimation unit can estimate the part and the cause of the abnormality based on the second model for the electric motor, this time generated using the learning model. The display unit can display the part and the cause of the abnormality of the electric motor. Furthermore, the notification unit 76 can transmit the occurrence of the abnormality and the cause of the abnormality estimated by the abnormal part estimation unit 75 to another device.

[0136] The above example illustrates a case where an abnormality occurs in a constituent part of an electric motor and heat is generated. However, there is also the case where an abnormality occurs in a component external to the electric motor and a heat-generating body is generated. For example, abnormal heat generation may occur in a device connected to the electric motor or in a device near the electric motor. When such abnormal heat generation occurs, the heat may be transferred to the electric motor. The temperature of the electric motor may rise due to heat transfer from the heat-generating body.

[0137] Fig.10 shows a second model for the case where abnormal heat generation occurs around the electric motor, as in the present embodiment. Shown is a second model 10d searched by the model search unit 71. The heat-generating body is represented as an additional component Y that generates heat. For example, the main spindle head of the machine may include an electric motor. The electric motor is coupled to a main spindle that holds a tool. The main spindle rotates under the drive of the electric motor. However, there is a case where an abnormality occurs in the main spindle head and the main spindle comes into contact with the main spindle head housing. As a result, the main spindle may generate heat and transfer the heat to the electric motor.

[0138] When a heat-generating body occurs around such an electric motor, the temperature determination unit 72 of the model search unit 71 identifies a section EP where an abnormality has occurred. The component addition unit 73 adds a 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 parameters of a model for a constituent part that performs heat exchange with the model 82a for the additional component Y and 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 a constituent part that performs heat exchange with the model 82a of the additional component Y. In addition, parameters including a heat capacity C Y , a heat generation quantity P Yand a coefficient hy relating to the heat transfer with respect to the additional component Y.

[0139] The operator can estimate the part and cause of the abnormality by referring to the second model 10d and the parameters of the second model 10d. Alternatively, the abnormal part estimation unit can estimate the part and cause of the abnormality. The monitoring device according to the present embodiment can also generate a second model related to an abnormality occurring outside the electric motor.

[0140] In the above embodiment, a case was described where the component in which the abnormality occurred generates heat, but the embodiment is not limited to this. If an abnormality occurs in and around the electric motor, the temperature of the electric motor may drop. For example, foreign matter that absorbs heat from a constituent part of the electric motor may adhere to the electric motor.

[0141] When a liquid such as a cooling liquid is applied to the outer peripheral surface of the electric motor 10, a component having a temperature lower than the temperature of the constituent parts of the electric motor 10 comes into contact with the stator core 20, and the temperature of the stator core 20 drops. The temperature determination unit 72 determines that the measured temperature detected by the temperature detector 31 is lower than a determination value based on the estimated temperature of the temperature detector 31 when the operating state of the electric motor is normal. For example, the temperature determination unit 72 determines that the measured temperature is lower than a predetermined temperature range with respect to the estimated temperature.

[0142] The component addition unit 73 generates a second model by adding a model for an additional component with a heat generation amount of zero to the first model 10a. The model for the additional component is set to have a heat capacity. The initial temperature of the additional component can be set in advance. Since the second model is searched by the model search unit 71, the model for the additional component is set to perform heat exchange with the model for the stator core. Furthermore, the parameter of the second model is adjusted so that the estimated temperature of the temperature detector closely matches the measured temperature.

[0143] On the other hand, when a liquid, such as a cooling liquid of an engine, enters the interior of the electric motor 10, a component whose temperature is lower than the temperature of the constituent part of the electric motor comes into contact with the coil 16, the rotor 11, and the stator core 20, and the temperature of these components drops. The component addition unit 73 creates a second model by adding a model for an additional component with a heat generation amount of zero to the first model 10a. A predetermined heat capacity is set in the model for the additional component. The initial temperature of the additional component can be set in advance. When searching the second model, the model for 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.Then the parameter of the second model is adjusted so that the estimated temperature of the temperature detector agrees well with the measured temperature.

[0144] As described above, the monitoring device according to the present embodiment can generate not only a model in which abnormal heat generation occurs in the electric motor and the surroundings of the electric motor, but also a model in which abnormal heat absorption occurs in the electric motor and the surroundings of the electric motor.

[0145] The first model for the electric motor according to the above embodiment includes the model for the coil, the model for the stator core, the model for the temperature detector, the model for the air layer, the model for the rotor, and the model for the outside air, but the embodiment is not limited to these. The first model for the electric motor may include models for other constituent parts. For example, the first model for the electric motor may include a model for the housing for supporting the stator and the rotor, a model for a bearing, a model for a shaft for supporting the rotor, and the like. Alternatively, the first model for the electric motor may not include some models. For example, the model for the electric motor may not include the model for the air layer.

[0146] The electric motor monitoring device according to the present embodiment is configured to switch between the normal model generation mode and the abnormal model generation mode, but the electric motor monitoring device is not limited to this. The electric motor monitoring device may not have the normal model generation mode function. The first model of the electric motor in the normal operating state of the electric motor may be generated by another device.

[0147] Furthermore, in the present embodiment, the electric motor monitoring device includes an arithmetic processing device different from the engine controller, but the embodiment is not limited to this. The engine controller may have the function of an electric motor monitoring device. In other words, the processor of the engine controller may function as a model search unit, temperature estimation unit, parameter calculation unit, and the like.

[0148] For each of the control schemes described above, the sequence of steps can be changed as appropriate, as long as the functions and actions remain unchanged. The embodiments described above can be combined as desired.

[0149] In each of the drawings described above, identical or equivalent parts are designated by identical reference numerals. The above embodiments are examples and do not limit the invention. Furthermore, the embodiments include modifications of the embodiments defined in the claims. List of reference symbols 2 monitoring device 10 Electric motor 10a Model for electric motor 11a Model for rotor 14, 15 camps 16a Model of the coil 20a Model for stator core 30a model for electric motor 31a Model for temperature detector 35a Model for the air layer 36a Model for outside air 51 storage 52 Display section 53 Temperature estimation unit 54 Loss calculation unit 55 Temperature calculation unit 62 Condition recording unit 63 Parameter calculation unit 66 Evaluation unit 67 Parameter change unit 71 Model search unit 72 Temperature determination unit 73 Component additional unit 74 Adjustment unit 75 Unit for estimating abnormal parts 76 Notification unit 81a, 82a model QUOTES CONTAINED IN THE DESCRIPTION

[0000] This list of documents submitted by the applicant was generated automatically and is included solely for the convenience of the reader. This list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions. Cited patent literature

[0000] JP 63-106861A [0002, 0005] JP 2010-268644A [0003, 0005] WO 2020 / 188650A [0004, 0005] JP 2008-109816A [0004, 0005]

Claims

[1] Electric motor monitoring device, comprising: a state detection unit configured to detect an operating state of an electric motor, including a measured temperature detected by a temperature detector attached to the electric motor; a temperature estimation unit configured to calculate an estimated temperature of the temperature detector based on a model for the electric motor; a memory configured to store a first model for the electric motor when the operating state of the electric motor is normal; and a model search unit configured to generate a second model for the electric motor when the operating state of the electric motor is abnormal, the model for the electric motor including a model for a rotor, a model for a stator core, a model for a coil, and a model for the temperature detector as models for constituent parts of the electric motor, a heat capacity is set in at least one of the models for the constituent parts, a coefficient related to the heat transfer between the models for the constituent parts is set, and the model search unit includes: a component addition unit configured to generate the second model by adding a model for an additional component to the first model, which performs heat exchange with the model for the constituent part of the electric motor when a difference between the measured temperature of the temperature detector and the estimated temperature of the temperature detector based on the first model deviates from a predefined determination range, and a setting unit configured to set the model for the constituent part of the electric motor that performs heat exchange with the model for the additional component and a coefficient related 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. [2] The electric motor monitoring device according to claim 1, further comprising a notification unit configured to notify another device of information related to the second model for the electric motor, wherein the notification unit notifies the other device of at least one piece of information selected from a group consisting of the model for the constituent part of the electric motor which performs heat exchange with the model for the additional component, a heat capacity of the additional component and a coefficient relating to heat transfer with respect to the additional component. [3] The electric motor monitoring device according to claim 1 or 2, further comprising a display part configured to display information related to the second model for the electric motor, the display part displaying at least one piece of information selected from a group consisting of the model for the constituent part of the electric motor that performs heat exchange with the model for the additional component, the heat capacity of the additional component, and the heat transfer coefficient related to the additional component. [4] The electric motor monitoring device according to any one of claims 1 to 3, wherein the adjusting unit adjusts the additional component that generates heat. [5] The electric motor monitoring device according to claim 4, wherein the model searching unit sets the model for the additional component to perform heat exchange with the model for the coil and the model for the rotor when an abnormality occurs in a bearing of the electric motor. [6] The electric motor monitoring device according to claim 4, wherein the model searching unit sets the model for the additional component to perform heat exchange with the model for the stator core when a heat-generating body occurs outside the electric motor. [7] The electric motor monitoring device according to any one of claims 1 to 6, further comprising a parameter calculation unit configured to calculate a parameter of the first model for the electric motor, wherein the state detection unit detects an operation command of the electric motor generated by the actual operation of the electric motor, the parameter includes the heat capacity set on the model for the constituent part and the coefficient related to heat transfer between the models for the constituent parts, the temperature estimation unit includes a loss calculation unit configured to calculate a heat generation amount due to a primary copper loss of the coil and a heat generation amount due to an iron loss of the stator core based on the operation command, and a temperature calculation unit configured to calculate the estimated temperature of the temperature detector using the first model for the electric motor based on the heat generation amount of the coil and the heat generation amount of the stator core, the parameter calculation unit includes an evaluation unit configured to evaluate 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 configured to change a value of the parameter based on an evaluation result of the evaluation unit so that the estimated temperature of the temperature detector approaches the measured temperature, and a mode in which the parameter of the first model for the electric motor is calculated by the parameter calculation unit and a mode in which the second model for the electric motor is generated by the model search unit are switchable. [8] The electric motor monitoring device according to any one of claims 1 to 7, further comprising an abnormal part estimation unit configured to estimate an abnormal part, wherein the memory stores the second model for the electric motor generated in the past and the abnormal part, and the abnormal part estimating unit estimates an abnormal part related to a second model for the electric motor generated this time based on the second model for the electric motor generated in the past and the abnormal part.

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