Support system

Abstract

A support system (1) comprises an extraction unit (41), a first calculation unit (42), a second calculation unit (44), and a correction unit (45). The first calculation unit (42) calculates time-series cyber data corresponding to time-series physical data extracted by the extraction unit (41), using a reproduction model including a parameter. The second calculation unit (44) calculates a parameter correction value that minimizes an error between the time-series physical data extracted by the extraction unit (41) and the time-series cyber data calculated by the first calculation unit (42). The correction unit (45) corrects the reproduction model on the basis of the correction value.

Description

Support System

[0001] The present disclosure relates to an assistance system.

[0002] Patent Document 1 describes an elevator management system. The system described in Patent Document 1 includes a monitoring device. The monitoring device acquires physical parameters corresponding to the specifications of the installation environment of the target equipment and physical parameters corresponding to the specifications of the target equipment, and modifies a standard physical model using the acquired physical parameters. The monitoring device then diagnoses the target equipment based on the modified model.

[0003] Japanese Patent Application Publication No. 2018-30699

[0004] Conventional systems have been unable to accurately correct the models used.

[0005] The present disclosure has been made to solve the above-mentioned problems. An object of the present disclosure is to provide a support system for supporting the management, design, maintenance, etc. of elevators, which is capable of accurately correcting the model used.

[0006] The support system according to the present disclosure includes an extraction unit that extracts elevator operation data stored in a storage device as time-series physical data; a first calculation unit that calculates time-series cyber data corresponding to the time-series physical data extracted by the extraction unit based on the elevator operation data stored in the storage device using a reproduction model including parameters; a second calculation unit that calculates correction values ​​for the parameters that minimize the error between the time-series physical data extracted by the extraction unit and the time-series cyber data calculated by the first calculation unit; and a correction unit that corrects the reproduction model based on the correction value calculated by the second calculation unit.

[0007] The support system according to the present disclosure can accurately correct models used in systems that provide support for elevator management, design, maintenance, etc.

[0008] FIG. 1 is a diagram showing an example of a support system in embodiment 1. FIG. 2 is a flowchart showing an example of an elevator operation. FIG. 3 is a flowchart showing an example of an operation of a support device. FIG. 4 is a diagram showing an example of a speed data calculation unit. FIG. 5 is a diagram showing an example of a torque data calculation unit. FIG. 6 is a diagram showing an example of an electric motor data calculation unit. FIG. 7 is a diagram showing an example of a support device in which a first calculation unit includes a torque data calculation unit. FIG. 8 is a flowchart showing an example of an operation of a maintenance device. FIG. 9 is a diagram showing an example of hardware resources of the support device. FIG. 10 is a diagram showing another example of hardware resources of the support device.

[0009] The following detailed description will be given with reference to the drawings. Duplicate descriptions will be simplified or omitted as appropriate. In each drawing, the same reference numerals indicate the same or corresponding parts.

[0010] Embodiment 1. Fig. 1 is a diagram showing an example of a support system 1 in embodiment 1. In the example shown in Fig. 1, the support system 1 includes an elevator 2, a support device 4, and a maintenance device 8. The support system 1 is a system for providing support for the management, design, maintenance, etc. of the elevator 2.

[0011] The elevator 2 includes a car 20, a counterweight 21, a main rope 22, a drive sheave 23, an electric motor 24, and a control device 25. The car 20 moves up and down in a hoistway. The car 20 and the counterweight 21 are suspended in the hoistway by the main rope 22. The counterweight 21 moves up and down in the hoistway in the direction opposite to the direction in which the car 20 moves.

[0012] The main rope 22 is wound around a traction sheave 23. An electric motor 24 generates torque for rotating the traction sheave 23. The rotation of the traction sheave 23 causes the main rope 22 to move. The car 20 moves up and down depending on the direction in which the traction sheave 23 rotates. That is, the car 20 is driven by the electric motor 24. The electric motor 24 is controlled by a control device 25. That is, the movement of the car 20 is controlled by the control device 25.

[0013] The elevator 2 may be equipped with various sensors 26. Each sensor 26 measures operational data.

[0014] In the example shown in Fig. 1, the elevator 2 is further provided with an acquisition device 27 and a storage device 28. Fig. 1 shows an example in which the acquisition device 27 and the storage device 28 are provided in the elevator 2 as devices separate from the control device 25. As another example, the functions of the acquisition device 27 and the functions of the storage device 28 may be provided in the control device 25. As another example, the functions of the acquisition device 27 and the functions of the storage device 28 may be provided in the assistance device 4.

[0015] As another example, one or both of the functions of the acquisition device 27 and the storage device 28 may be provided in the assistance system 1 as a device separate from the elevator 2 and the assistance device 4. In such a case, the separate device is capable of bidirectional communication with each of the elevator 2 and the assistance device 4.

[0016] The support device 4 is capable of bidirectional communication with the elevator 2. The support device 4 may be installed in a building where the elevator 2 is installed, or may be installed remotely from the building. As an example, the support device 4 may be realized by an on-premise server of a maintenance company that maintains the elevator 2. The support device 4 may be realized by a cloud server. The support device 4 may be realized by multiple servers. When the support device 4 is realized by multiple servers, the multiple servers may be installed in multiple regions of a country or in multiple countries. For example, some of the servers constituting the support device 4 may be installed in a first country, and the remaining servers constituting the support device 4 may be installed in a second country different from the first country.

[0017] The support device 4 includes, for example, a storage unit 40, an extraction unit 41, a first calculation unit 42, a comparison unit 43, a second calculation unit 44, and a correction unit 45. Data related to the specifications of the elevator 2 is stored in the storage unit 40. Hereinafter, this data will also be referred to as specification data.

[0018] The maintenance device 8 is capable of bidirectional communication with the support device 4. The maintenance device 8 may be installed in a building in which the elevator 2 is installed, or may be installed remotely from the building. As an example, the maintenance device 8 may be realized by an on-premise server of a maintenance company that maintains the elevator 2. The maintenance device 8 may also be realized by a terminal carried by a maintenance worker of the maintenance company. If the maintenance company owns multiple terminals for maintenance workers, each of the multiple terminals may be a maintenance device 8.

[0019] The maintenance device 8 includes, for example, a storage unit 80 and a detection unit 81. FIG. 1 shows an example in which the storage unit 80 is included in the maintenance device 8. As another example, the function of the storage unit 80 may be included in the support device 4. Both the function of the storage unit 80 and the function of the detection unit 81 may be included in the support device 4. As another example, the function of the storage unit 80 may be included in a device separate from the support device 4 and the maintenance device 8.

[0020] Next, the functions of the assistance system 1 will be described in detail with reference to Figures 2 to 8. Figure 2 is a flowchart showing an example of the operation of the elevator 2.

[0021] In the elevator 2, the acquisition device 27 acquires operation data of the elevator 2 (Yes in S101). For example, the acquisition device 27 acquires operation data from the control device 25. The acquisition device 27 may acquire operation data from the sensor 26. The acquisition device 27 may acquire operation data from other devices. It is preferable that the acquisition device 27 acquires all operation data that can be acquired. The operation data acquired by the acquisition device 27 is stored in the storage device 28 (S102).

[0022] 3 is a flowchart showing an example of the operation of the support device 4. In the support device 4, the extraction unit 41 extracts the operation data of the elevator 2 stored in the storage device 28 as time-series physical data (S201). The time-series physical data extracted by the extraction unit 41 is data acquired by the acquisition device 27, for example, actual measured data. The extraction unit 41 may extract the time-series physical data each time the car 20 makes a run. The extraction unit 41 may also extract the time-series physical data periodically.

[0023] The first calculation unit 42 calculates time-series cyber data corresponding to the time-series physical data extracted by the extraction unit 41 (S202). In contrast to the time-series physical data, the time-series cyber data is data obtained by calculation. The first calculation unit 42 performs the calculation in S202 based on the operation data of the elevator 2 stored in the storage device 28. Specifically, the first calculation unit 42 performs the calculation in S202 based on the operation data stored in the storage device 28, other than the time-series physical data extracted by the extraction unit 41. The first calculation unit 42 may also perform the calculation in S202 based on the specification data of the elevator 2 stored in the storage unit 40.

[0024] In S202, the first calculation unit 42 uses a reproduction model for calculating the time-series cyber data. This reproduction model includes parameters. As an example, the reproduction model is an equation. In such a case, the parameters are expressed as coefficients. The reproduction model is registered in advance.

[0025] 1 shows a preferred example in which the first calculation unit 42 includes a speed data calculation unit 50, a torque data calculation unit 60, and an electric motor data calculation unit 70. The first calculation unit 42 may include only one or two of the speed data calculation unit 50, the torque data calculation unit 60, and the electric motor data calculation unit 70.

[0026] Fig. 4 is a diagram showing an example of the speed data calculation unit 50. In the example shown in Fig. 4, the speed data calculation unit 50 includes a travel distance calculation unit 51, a running time calculation unit 52, an acceleration time series data calculation unit 53, and a speed time series data calculation unit 54.

[0027] When the first calculation unit 42 includes the speed data calculation unit 50, the extraction unit 41 extracts speed time series physical data as the time series physical data in S201. The speed time series physical data is operational data related to the speed of the car 20. The reproduction model also includes a speed reproduction model for generating a speed pattern of the car 20. The speed reproduction model includes a speed parameter as the parameter. The speed data calculation unit 50 calculates speed time series cyber data corresponding to the speed time series physical data using the speed reproduction model.

[0028] As an example, consider a case where the car 20 travels from a certain departure floor to a certain arrival floor. In this case, data indicating the departure floor, data indicating the arrival floor, and data indicating the start time are input to the speed data calculation unit 50 as operation data of the elevator 2.

[0029] The travel distance calculation unit 51 calculates the distance traveled by the car 20 during the trip using at least one model constituting the speed reproduction model. The model may include the parameters (speed parameters) shown in Group A. The initial values ​​of each parameter may be set based on the specification data of the elevator 2. Group A: Number of floors, distance from the lowest floor of each floor The travel distance calculation unit 51 calculates the travel distance of the car 20 by applying the departure floor, arrival floor, etc. to the model.

[0030] The running time calculation unit 52 calculates the time that the car 20 travels at a constant speed during the run, using at least one model that constitutes the speed reproduction model. The model may include the parameters (speed parameters) shown in Group B. The initial values ​​of each parameter may be set based on the specification data of the elevator 2. Group B: motor lock time before running, acceleration start jerk time, acceleration, acceleration end jerk time, rated speed, deceleration start jerk time, deceleration, deceleration end jerk time, motor lock time after landing The running time calculation unit 52 calculates the running time of the car 20 at a constant speed by applying the travel distance, etc. calculated by the travel distance calculation unit 51 to the model.

[0031] The acceleration time series data calculation unit 53 calculates the acceleration time series data of the car 20 during the run using at least one model that constitutes the speed reproduction model. The model may include the parameters shown in group B. The acceleration time series data calculation unit 53 calculates the acceleration time series data of the car 20 by applying the start time, the running time calculated by the running time calculation unit 52, and the like to the model.

[0032] The speed time series data calculation unit 54 calculates speed time series data of the car 20 during the run using at least one model that constitutes the speed reproduction model. The speed time series data calculation unit 54 calculates speed time series data of the car 20 by applying the acceleration time series data calculated by the acceleration time series data calculation unit 53, etc. to the model. As an example, the speed time series data calculation unit 54 integrates the acceleration time series data calculated by the acceleration time series data calculation unit 53.

[0033] The speed time series data calculated by the speed time series data calculation unit 54 is the speed time series cyber data v ｃｙｂｅｒ The velocity data is output from the velocity data calculation unit 50 as (t).

[0034] The first calculation unit 42 may include an acceleration data calculation unit or a position data calculation unit instead of or in addition to the velocity data calculation unit 50. Both the acceleration data calculation unit and the position data calculation unit may be included in the first calculation unit 42.

[0035] The acceleration data calculation unit corresponds to the speed data calculation unit 50, where the speed is converted to acceleration. When the first calculation unit 42 includes an acceleration data calculation unit, the extraction unit 41 extracts acceleration time-series physical data as the time-series physical data in S201. The acceleration time-series physical data is operational data related to the acceleration of the car 20. The reproduction model also includes an acceleration reproduction model for generating an acceleration pattern of the car 20. The acceleration reproduction model includes acceleration parameters as the parameters. The acceleration data calculation unit calculates acceleration time-series cyber data corresponding to the acceleration time-series physical data using the acceleration reproduction model.

[0036] The position data calculation unit corresponds to the speed data calculation unit 50, which has converted the speed into position. When the first calculation unit 42 includes a position data calculation unit, the extraction unit 41 extracts position time-series physical data as the time-series physical data in S201. The position time-series physical data is operation data related to the position of the car 20. The reproduction model also includes a position reproduction model for generating a position pattern of the car 20. The position reproduction model includes position parameters as the parameters. The position data calculation unit calculates position time-series cyber data corresponding to the position time-series physical data using the position reproduction model.

[0037] Fig. 5 is a diagram showing an example of the torque data calculation unit 60. In the example shown in Fig. 5, the torque data calculation unit 60 includes a basic data calculation unit 61, a static torque calculation unit 62, a dynamic torque calculation unit 63, a loss torque calculation unit 64, and an addition unit 65.

[0038] When the first calculation unit 42 includes the torque data calculation unit 60, the extraction unit 41 extracts torque time-series physical data as the time-series physical data in S201. The torque time-series physical data is operation data related to the torque of the electric motor 24. The reproduction model also includes a torque reproduction model that includes torque parameters as the parameters. The torque data calculation unit 60 calculates torque time-series cyber data corresponding to the torque time-series physical data using the torque reproduction model.

[0039] In an example in which the car 20 travels from a certain departure floor to a certain arrival floor, data indicating the load factor of the car 20 and the speed time-series physical data are input to the torque data calculation unit 60 as operation data of the elevator 2. The load factor of the car 20 is, for example, 0 (0%) when the car 20 is unloaded, i.e., when nothing is loaded in the car 20, and is 1 (100%) when the car 20 is loaded with the rated load.

[0040] In the torque data calculation unit 60, a basic data calculation unit 61 calculates basic data necessary for torque calculation. A static torque calculation unit 62, a dynamic torque calculation unit 63, and a loss torque calculation unit 64 each calculate a value of a torque component for each specific time interval using an equation of motion. An adder 65 adds up the torque components calculated by the static torque calculation unit 62, the dynamic torque calculation unit 63, and the loss torque calculation unit 64. The value added by the adder 65 is the torque time-series cyber data τ ｃｙｂｅｒ The torque data is output from the torque data calculation unit 60 as (t).

[0041] In the example shown in FIG. 5, the basic data calculation unit 61 includes a weight calculation function F1, a position calculation function F2, and an acceleration calculation function F3.

[0042] The weight calculation function F1 calculates the load weight in the car 20 during the current run using at least one model constituting the torque reproduction model. The model may include the parameters (torque parameters) shown in Group C. The initial values ​​of each parameter may be set based on the specification data of the elevator 2. Group C: Rated load capacity of the car 20, counter rate, tare weight of the car 20, weight of the counterweight 21. For example, the counter rate is 0.5 if the weight of the counterweight 21 balances the total weight of the car 20 loaded with 50% of the rated load capacity, and is 0.4 if the weight of the counterweight 21 balances the total weight of the car 20 loaded with 40% of the rated load capacity. The weight calculation function F1 calculates the load weight in the car 20 by applying the load rate of the car 20, etc., to the model.

[0043] The position calculation function F2 calculates the position of the car 20 during the travel using at least one model that constitutes the torque reproduction model. As an example, the position calculation function F2 calculates the position of the car 20 by integrating the speed time-series physical data using the model.

[0044] The acceleration calculation function F3 calculates the acceleration of the car 20 during the travel using at least one model that constitutes the torque reproduction model. As an example, the acceleration calculation function F3 calculates the acceleration of the car 20 by differentiating the speed time-series physical data using the model.

[0045] In the example shown in FIG. 5, the static torque calculation unit 62 includes an unbalanced torque calculation function F4, an unbalanced torque calculation function F5, and an addition function F6.

[0046] The unbalanced torque calculation function F4 uses at least one model constituting the torque reproduction model to calculate a first torque component of the unbalanced torque that does not change with the up and down movement of the car 20. The unbalanced torque is a torque that occurs when the weight acting on the car 20 side of the main rope 22 and the weight acting on the counterweight 21 side are not balanced. The model may include parameters shown in group C and parameters shown in group D (torque parameters). The initial value of each parameter may be set based on the specification data of the elevator 2. Group D: Diameter of the traction sheave 23, roping ratio

[0047] The unbalanced torque calculation function F4 performs the necessary calculations by applying the output of the weight calculation function F1, etc. to the model. An example of a model used in the unbalanced torque calculation function F4 is shown below. First torque component [Nm] = (M1 - M2) x ((diameter of driving sheave 23) / 2) / (roping ratio) x (gravitational acceleration) Here, M1 is the weight acting on the car 20 side of the main rope 22 that does not change due to the up and down movement of the car 20. M2 is the weight acting on the counterweight 21 side of the main rope 22 that does not change due to the up and down movement of the car 20.

[0048] The unbalance torque calculation function F5 uses at least one model constituting the torque reproduction model to calculate a second torque component of the unbalance torque that changes due to the up and down movement of the car 20. The model may include the parameters shown in group D, the parameters (torque parameters) shown in group E, and the parameters (torque parameters) shown in group F. The initial values ​​of each parameter may be set based on the specification data of the elevator 2. Group E: Ascending and descending stroke, hoistway pit depth, hoistway top clearance, height of the frame supporting the car 20 Group F: weight-related information of the main rope, weight-related information of the balancing rope, weight-related information of the governor rope, weight-related information of the control cable connecting the car 20 and the control device 25

[0049] The unbalanced torque calculation function F5 performs the necessary calculations by applying the output of the position calculation function F2, etc. to the model. An example of a model used in the unbalanced torque calculation function F5 is shown below. Second torque component [Nm] = (m1 - m2) x ((diameter of driving sheave 23) / 2) / (roping ratio) x (gravitational acceleration) Here, m1 is the weight acting on the car 20 side of the main rope 22 that changes due to the up and down movement of the car 20. m2 is the weight acting on the counterweight 21 side of the main rope 22 that changes due to the up and down movement of the car 20.

[0050] The addition function F6 adds the output of the unbalance torque calculation function F4 and the output of the unbalance torque calculation function F5 to calculate the static torque time series data τ ｓｔａｔｉｃ (t) is calculated.

[0051] In the example shown in FIG. 5, the dynamic torque calculation unit 63 includes an acceleration / deceleration torque calculation function F7, an acceleration / deceleration torque calculation function F8, an acceleration / deceleration torque calculation function F9, and an addition function F10.

[0052] The acceleration / deceleration torque calculation function F7 uses at least one model constituting the torque reproduction model to calculate a third torque component of the acceleration / deceleration torque that does not change due to the up and down movement of the car 20. The acceleration / deceleration torque is the torque required when accelerating and decelerating the car 20. The model may include parameters shown in group C and parameters shown in group D. The acceleration / deceleration torque calculation function F7 performs the required calculations by applying the output of the weight calculation function F1, the output of the acceleration calculation function F3, etc. to the model.

[0053] The acceleration / deceleration torque calculation function F8 uses at least one model constituting the torque reproduction model to calculate a fourth torque component of the acceleration / deceleration torque that changes due to the up and down movement of the car 20. This model may include parameters shown in group D, parameters shown in group E, and parameters shown in group F. The acceleration / deceleration torque calculation function F8 performs the necessary calculations by applying the output of the position calculation function F2, the output of the acceleration calculation function F3, etc. to this model.

[0054] The acceleration / deceleration torque calculation function F9 calculates a fifth torque component, which is necessary for accelerating and decelerating the rotating body, of the acceleration / deceleration torque using at least one model constituting the torque reproduction model. The model may include parameters shown in group D and parameters (torque parameters) shown in group G. Group G: inertia information of the electric motor 24, inertia information of the governor, inertia information of pulleys, etc. The acceleration / deceleration torque calculation function F9 performs the necessary calculations by applying the output of the acceleration calculation function F3, etc. to the model.

[0055] The addition function F10 adds the output of the acceleration / deceleration torque calculation function F7, the output of the acceleration / deceleration torque calculation function F8, and the output of the acceleration / deceleration torque calculation function F9 to calculate the dynamic torque time series data τ ｄｙｎａｍｉｃ (t) is calculated.

[0056] The loss torque calculation unit 64 calculates the loss torque using at least one model constituting the torque reproduction model. The model may include parameters (torque parameters) shown in Group H. The initial values ​​of each parameter may be set based on the specification data of the elevator 2. Group H: loss torque (speed-independent component), loss torque (speed-dependent component) The loss torque calculation unit 64 calculates the loss torque time-series data τ by applying the speed time-series physical data and the like to the model. ｌｏｓｓ (t) is calculated.

[0057] As described above, the static torque time series data τ ｓｔａｔｉｃ The dynamic torque calculation unit 63 calculates the dynamic torque time series data τ ｄｙｎａｍｉｃ The loss torque calculation unit 64 calculates the loss torque time series data τ ｌｏｓｓ The adder 65 calculates the static torque time series data τ ｓｔａｔｉｃ (t), dynamic torque time series data τ ｄｙｎａｍｉｃ (t), and loss torque time series data τ ｌｏｓｓ By adding (t), the torque time series cyber data τ ｃｙｂｅｒ (t) is calculated.

[0058] Fig. 6 is a diagram showing an example of a motor data calculation unit 70. In the example shown in Fig. 6, the motor data calculation unit 70 includes an electrical angular velocity calculation unit 71, a current / voltage calculation unit 72, a determination unit 73, and a field-weakening current calculation unit 74. Note that the following description of Fig. 6 will be given assuming that the motor 24 is a permanent magnet synchronous motor. Other types of motors, such as a DC motor, an induction motor, or a synchronous motor, may also be used as the motor 24.

[0059] When the first calculation unit 42 includes the motor data calculation unit 70, the extraction unit 41 extracts motor time-series physical data as the time-series physical data in S201. The motor time-series physical data is operation data related to the motor 24. As an example, the motor time-series physical data is operation data related to the voltage or current of the motor 24. Furthermore, the reproduction model includes a motor reproduction model including motor parameters as the parameters. The motor data calculation unit 70 calculates motor time-series cyber data corresponding to the motor time-series physical data using the motor reproduction model.

[0060] In an example in which the car 20 travels from a certain departure floor to a certain arrival floor, the operation data of the elevator 2 includes torque current feedback time series data i ｑ (t) and the speed time series physical data are input to the motor data calculation unit 70. The torque current feedback time series data i ｑ (t) is time series data of the actual q-axis current value among the actual current values ​​obtained by coordinate transformation (dq-axis coordinate transformation) of the actual current value flowing through the electric motor 24 in a rotating coordinate system. The q-axis current is a current component of the current flowing through the electric motor 24 that is proportional to the generated torque.

[0061] The electrical angular velocity calculation unit 71 calculates the electrical angular velocity ω of the electric motor 24 during the running, using at least one model constituting the electric motor reproduction model. ｒｅ (t). The model may include parameters (motor parameters) shown in group J. The initial values ​​of the parameters may be set based on the specification data of the elevator 2. Group J: diameter of the traction sheave 23, roping ratio, number of pole pairs of the electric motor 24. The electric angular velocity calculation unit 71 calculates the electric angular velocity ω of the electric motor 24 by applying the speed time-series physical data and the like to the model. ｒｅ (t) is calculated.

[0062] The current / voltage calculation unit 72 calculates various values ​​related to the current and voltage of the motor 24 using at least one model constituting the motor reproduction model. The model may include parameters (motor parameters) shown in group K. The initial values ​​of each parameter may be set based on the specification data of the elevator 2. Group K: winding resistance value of the motor 24, no-load induced voltage, d-axis inductance, q-axis inductance, limit voltage The current / voltage calculation unit 72 calculates various values ​​related to the current and voltage of the motor 24 using the torque / current feedback time series data i ｑ (t), and the electrical angular velocity ω calculated by the electrical angular velocity calculation unit 71 ｒｅ (t) etc. are applied to the model to perform the necessary calculations.

[0063] For example, the current / voltage calculation unit 72 may use a model for obtaining a value related to the current of the electric motor 24 and a model for obtaining a value related to the voltage of the electric motor 24. By using an appropriate model, the current / voltage calculation unit 72 can calculate the current / voltage ｄ＿ｃｙｂｅｒ (t), V ｄ＿ｃｙｂｅｒ (t), V ｑ＿ｃｙｂｅｒ (t), I ｒｍｓ＿ｃｙｂｅｒ (t), and V ｒｍｓ＿ｃｙｂｅｒ (t) may be calculated. ｄ＿ｃｙｂｅｒ (t) is the time series data of the d-axis current. ｄ＿ｃｙｂｅｒ (t) is the time series data of the d-axis voltage. ｑ＿ｃｙｂｅｒ (t) is the time series data of the q-axis voltage. ｒｍｓ＿ｃｙｂｅｒ (t) is the time series data of the effective current (uvw). ｒｍｓ＿ｃｙｂｅｒ (t) is the time series data of the effective voltage (uvw).

[0064] An example of a model used in the current / voltage calculation unit 72 is shown below: In this model, the differential component may be omitted.

[0065]

[0066] The determination unit 73 determines whether the voltage of the electric motor 24 exceeds the limit voltage by using at least one model constituting the electric motor reproduction model. Specifically, the determination unit 73 determines whether field-weakening control should be considered in the current / voltage calculation unit 72. The model may include parameters shown in group K.

[0067] The field-weakening current calculation unit 74 calculates the field-weakening current using at least one model constituting the motor reproduction model. The model may include parameters shown in group K.

[0068] The field-weakening current is a reactive current component that can equivalently reduce the no-load induced voltage component so that the terminal voltage of the motor 24 during high-speed rotation does not exceed the DC bus voltage of the inverter. Note that the above-mentioned inverter is an example of a power converter that supplies power to the motor 24. If the value of the square root of the sum of the squares of the d-axis voltage Vd and the q-axis voltage Vq does not exceed the limit voltage, there is no need to flow the field-weakening current. If the value of the square root of the sum of the squares of Vd and Vq exceeds the limit voltage, the field-weakening current calculation unit 74 calculates the field-weakening current id using the following equation. The field-weakening current calculation unit 74 can use the solution of the following quadratic equation with the smaller absolute value as the field-weakening current id.

[0069] Here, a = R ２ + (ω ｒｅ L ｄ ) ２ b = 2ω ｒｅ (L ｄ (Ri ｑ +ω ｒｅ Φ ｍ )-RL ｑ i ｑ ) c = (ω ｒｅ L ｑ i ｑ ) ２ + (Ri ｑ +ω ｒｅ Φ ｍ ) ２ -V ｌｉｍ ２ is.

[0070] When the field-weakening current calculation unit 74 calculates the field-weakening current, the current / voltage calculation unit 72 performs recalculation taking the calculated field-weakening current into consideration. When the determination unit 73 determines that there is no need to recalculate the field-weakening current, the result calculated by the current / voltage calculation unit 72 is output from the motor data calculation unit 70 as motor time-series cyber data.

[0071] The comparison unit 43 compares the time-series physical data extracted by the extraction unit 41 in S201 with the time-series cyber data corresponding to the time-series physical data (S203). The time-series cyber data is the data calculated by the first calculation unit 42 in S202. That is, the comparison unit 43 calculates the difference between the time-series physical data extracted by the extraction unit 41 and the time-series cyber data calculated by the first calculation unit 42.

[0072] The second calculation unit 44 calculates correction values ​​of the parameters that minimize the error between the time-series physical data extracted by the extraction unit 41 and the time-series cyber data calculated by the first calculation unit 42 (S204). The second calculation unit 44 may calculate the value of the parameter itself or the amount of variation as the correction value. The calculation in S204 may use the least squares method or a machine learning technique. Other methods may also be used in the calculation in S204.

[0073] The correction unit 45 corrects the reproduction model based on the correction value calculated by the second calculation unit in S204 (S205).

[0074] For example, if the first calculation unit 42 is equipped with a speed data calculation unit 50, the comparison unit 43 compares the speed time series physical data extracted by the extraction unit 41 with the speed time series cyber data calculated by the speed data calculation unit 50 in S203.

[0075] Also, in this example, the second calculation unit 44 calculates correction values ​​for the speed parameters in S204 that minimize the error between the speed time-series physical data and the speed time-series cyber data. The second calculation unit 44 may calculate C_TML1, C_Tj1, C_Tj2, C_Tj3, C_Tj4, C_Acc, C_Dec, and C_TML2 as the correction values. C_TML1 is a correction value related to the motor lock time before traveling. C_Tj1-C_Tj4 are correction values ​​related to the jerk time, respectively. C_Acc is a correction value related to acceleration. C_Dec is a correction value related to deceleration. C_TML2 is a correction value related to the motor lock time after landing.

[0076] The corrector 45 corrects the velocity parameters using the correction values ​​calculated by the second calculator 44, thereby optimizing (correcting) the velocity reproduction model.

[0077] If the first calculation unit 42 includes an acceleration data calculation unit, the comparison unit 43 compares the acceleration time-series physical data extracted by the extraction unit 41 with the acceleration time-series cyber data calculated by the acceleration data calculation unit in S203. The second calculation unit 44 calculates correction values ​​for acceleration parameters that minimize the error between the acceleration time-series physical data and the acceleration time-series cyber data in S204. The second calculation unit 44 may calculate C_TML1, C_Tj1, C_Tj2, C_Tj3, C_Tj4, C_Acc, C_Dec, and C_TML2 as the correction values. The correction unit 45 optimizes (corrects) the acceleration reproduction model by correcting the acceleration parameters using the correction values ​​calculated by the second calculation unit 44.

[0078] When the first calculation unit 42 includes a position data calculation unit, the comparison unit 43 compares the position time series physical data extracted by the extraction unit 41 with the position time series cyber data calculated by the position data calculation unit in S203. The second calculation unit 44 calculates correction values ​​for position parameters that minimize the error between the position time series physical data and the position time series cyber data in S204. The second calculation unit 44 may calculate C_TML1, C_Tj1, C_Tj2, C_Tj3, C_Tj4, C_Acc, C_Dec, and C_TML2 as the correction values. The correction unit 45 optimizes (corrects) the position reproduction model by correcting the position parameters using the correction values ​​calculated by the second calculation unit 44.

[0079] Furthermore, when the first calculation unit 42 includes the torque data calculation unit 60, the comparison unit 43 compares, in S203, the torque time series physical data extracted by the extraction unit 41 with the torque time series cyber data calculated by the torque data calculation unit 60. In this example, in S204, the second calculation unit 44 calculates correction values ​​of the torque parameters that minimize the error between the torque time series physical data and the torque time series cyber data.

[0080] Fig. 7 is a diagram showing an example of the assistance device 4 when the first calculation unit 42 includes a torque data calculation unit 60. In the example shown in Fig. 7, the comparison unit 43 includes a unit unification function F11 and a comparison function F12.

[0081] As an example, the comparison unit 43 receives torque current feedback time series data i as torque time series physical data. ｑThe torque time-series physical data (t) is input. This value has a 1:1 correlation with the torque value, but its unit is amperes [A]. On the other hand, the unit of the torque time-series cyber data is newton meters [Nm]. Therefore, the unit unification function F11 converts the unit of the torque time-series physical data extracted by the extraction unit 41 from [A] to [Nm] using a specific conversion model. The conversion model includes conversion parameters. The comparison function F12 calculates the difference between the torque time-series physical data whose unit has been converted by the unit unification function F11 and the torque time-series cyber data calculated by the torque data calculation unit 60.

[0082] In the example shown in FIG. 7 , the second calculation unit 44 includes a correction value calculation function F13 and a correction value calculation function F14. The correction value calculation function F13 calculates correction values ​​for torque parameters included in the torque reproduction model. The correction value calculation function F13 may calculate C_Tacc, C_Tspd, C_Tpos, and C_Tcnst as the correction values. C_Tacc is a correction value for an acceleration-dependent torque component. C_Tspd is a correction value for a velocity-dependent torque component. C_Tpos is a correction value for a position-dependent torque component. C_Tcnst is a correction value for an offset torque component.

[0083] The correction unit 45 corrects the torque parameters using the correction values ​​calculated by the correction value calculation function F13, thereby optimizing (correcting) the torque reproduction model.

[0084] Furthermore, the correction value calculation function F14 calculates a correction value for the conversion parameter included in the conversion model. The correction value calculation function F14 may calculate a correction value C_Φm related to magnetic flux as the correction value. The conversion parameter is corrected using the correction value calculated by the correction value calculation function F14, thereby optimizing (correcting) the conversion model. The correction function may be implemented by the correction unit 45.

[0085] Note that acceleration, velocity, and position can be converted into one another using differential or integral calculations. Therefore, when the first calculation unit 42 includes the velocity data calculation unit 50, the comparison unit 43 may be provided with a conversion function such as the unit unification function F11. That is, the conversion function uses a specific conversion model to convert the time-series physical data extracted by the extraction unit 41 into data comparable to the time-series cyber data calculated by the first calculation unit 42. The comparison function of the comparison unit 43 then calculates the difference between the data converted by the conversion function (time-series physical data) and the time-series cyber data calculated by the first calculation unit 42.

[0086] That is, when the first calculation unit 42 includes the velocity data calculation unit 50, the extraction unit 41 may extract acceleration time-series physical data or position time-series physical data as time-series physical data corresponding to the velocity time-series cyber data. Similarly, when the first calculation unit 42 includes an acceleration data calculation unit, the extraction unit 41 may extract velocity time-series physical data or position time-series physical data as time-series physical data corresponding to the acceleration time-series cyber data. When the first calculation unit 42 includes a position data calculation unit, the extraction unit 41 may extract acceleration time-series physical data or velocity time-series physical data as time-series physical data corresponding to the position time-series cyber data.

[0087] If the first calculation unit 42 includes the motor data calculation unit 70, the comparison unit 43 compares the motor time-series physical data extracted by the extraction unit 41 with the motor time-series cyber data calculated by the motor data calculation unit 70 in S203. If the first calculation unit 42 includes the motor data calculation unit 70 shown in FIG. 6, the comparison unit 43 receives the motor time-series physical data, ｄ＿ａｃｔ (t), V ｄ＿ａｃｔ (t), V ｑ＿ａｃｔ (t), I ｒｍｓ＿ａｃｔ (t), and V ｒｍｓ＿ａｃｔ (t) is input.

[0088] Also, in this example, the second calculation unit 44 calculates correction values ​​for the motor parameters in S204 that minimize the error between the motor time-series physical data and the motor time-series cyber data. The second calculation unit 44 may calculate C_Ld, C_Lq, C_R, and C_Vlim as the correction values. C_Ld is a correction value related to the d-axis inductance. C_Lq is a correction value related to the q-axis inductance. C_R is a correction value related to the winding resistance. C_Vlim is a correction value related to the voltage (limit voltage) at which the supply of field-weakening current is started.

[0089] The correction unit 45 corrects the motor parameters using the correction values ​​calculated by the second calculation unit 44, thereby optimizing (correcting) the motor reproduction model.

[0090] 8 is a flowchart showing an example of the operation of the maintenance device 8. The maintenance device 8 determines whether or not a correction value for the parameter has been received from the support device 4 (S301). When the second calculation unit 44 in the support device 4 calculates the correction value for the parameter in S204, the correction value is transmitted to the maintenance device 8. When the maintenance device 8 receives the correction value, a determination of Yes is made in S301. When a determination of Yes is made in S301, the storage unit 80 stores the correction value received from the support device 4, i.e., the correction value calculated by the second calculation unit 44 (S302).

[0091] The detection unit 81 detects modulation of the correction value stored by the storage unit 80. For example, the maintenance device 8 determines whether or not there is a specific modulation in the correction value stored by the storage unit 80 (S303). In S303, the following items may be determined: - Is there a large deviation from the theoretical value? - Is there a large deviation from the initial value? - Is there a large short-term change? - Is there a large long-term change? - Is there a large deviation from values ​​based on other elevators?

[0092] For example, if the amount of change from the initial value exceeds the threshold, a Yes is determined in S303. If the amount of short-term change in the correction value exceeds the threshold, a Yes is determined in S303. If a Yes is determined in S303, the detection unit 81 detects modulation of the correction value (S304).

[0093] In the example shown in this embodiment, time-series cyber data corresponding to time-series physical data is calculated using a reproduction model including parameters. Furthermore, correction values ​​of the parameters are calculated so that the error between the time-series physical data and the time-series cyber data is minimized. Then, the reproduction model is corrected based on the correction values. Therefore, in the example shown in this embodiment, the reproduction model can be corrected with high accuracy.

[0094] Furthermore, the correction values ​​can be useful information when supporting elevator management, design, maintenance, etc. For example, with regard to speed parameters, the correction values ​​C_TML1 and C_TML2 related to the motor lock time can be useful information in elevator design. Similarly, the correction value C_Dec related to the deceleration can be useful information in elevator design.

[0095] Regarding torque parameters, the correction value C_Tacc for the acceleration-dependent torque component can be useful information for understanding inertia. The correction value C_Tspd for the speed-dependent torque component can be useful information for understanding loss torque (speed-dependent component). The correction value C_Tpos for the position-dependent torque component can be useful information for understanding the unit mass of the main rope 22. The correction value C_Tcnst for the offset torque component can be useful information for understanding the detection error of the weighing device.

[0096] Regarding the motor parameters, the correction value C_Vlim for the limit voltage can be useful information for understanding the state of the power supply voltage.

[0097] Furthermore, in the example shown in this embodiment, the modulation of the correction value is detected by the detection unit 81. The modulation of the correction value can be useful information particularly in elevator maintenance work. Maintenance work includes periodic inspections, regular testing, maintenance, and proactive response to problems.

[0098] In the present embodiment, an example has been described in which the assistance system 1 has a function for detecting modulation of the correction value. The assistance system 1 does not have to have this detection function. For example, a maintenance worker or manager of the elevator 2 may look at the correction value calculated by the second calculation unit 44 and determine whether or not modulation occurs. In such a case, it is preferable that the assistance system 1 has a function for saving the correction value, a function for displaying the correction value, a function for transmitting the correction value, or the like.

[0099] 9 is a diagram showing an example of hardware resources of the support device 4. The support device 4 includes, as hardware resources, a processing circuit 100 including a processor 101 and a memory 102. The processing circuit 100 may include multiple processors 101. The processing circuit 100 may include multiple memories 102.

[0100] In this embodiment, the units denoted by reference numerals 40 to 45 indicate functions possessed by the support device 4. The function of the storage unit 40 is realized by the memory 102. The functions of the units denoted by reference numerals 41 to 45 can be realized by software written as a program, firmware, or a combination of software and firmware. The program is stored in the memory 102. The support device 4 realizes the functions of the units denoted by reference numerals 41 to 45 by executing the program stored in the memory 102 by the processor 101 (computer).

[0101] The processor 101 is also called a CPU (Central Processing Unit), central processing unit, processing unit, arithmetic unit, microprocessor, microcomputer, or DSP. The memory 102 may be a semiconductor memory, a magnetic disk, a flexible disk, an optical disk, a compact disk, a minidisk, or a DVD. Usable semiconductor memories include RAM, ROM, flash memory, EPROM, and EEPROM.

[0102] Fig. 10 is a diagram showing another example of hardware resources of the assistance device 4. In the example shown in Fig. 10, the assistance device 4 includes a processing circuit 100 including a processor 101, a memory 102, and dedicated hardware 103. Fig. 10 shows an example in which some of the functions of the assistance device 4 are realized by the dedicated hardware 103. All of the functions of the assistance device 4 may be realized by the dedicated hardware 103. The dedicated hardware 103 may be a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC, an FPGA, or a combination thereof.

[0103] The hardware resources of the maintenance device 8 are similar to those shown in FIG. 9 or 10 . The maintenance device 8 includes a processing circuit including a processor and a memory as its hardware resources. The processing circuit may include multiple processors. The processing circuit may include multiple memories. The maintenance device 8 realizes the functions of the parts indicated by the reference numerals 80 and 81 by executing a program stored in the memory using a processor (computer). The maintenance device 8 may include a processing circuit including a processor, memory, and dedicated hardware as its hardware resources. Some or all of the functions of the maintenance device 8 may be realized by dedicated hardware.

[0104] The hardware resources of the acquisition device 27 and the storage device 28 are similar to those shown in FIG. 9 or 10 . The acquisition device 27 and the storage device 28 each include a processing circuit including a processor and a memory as a hardware resource. The processing circuit may include multiple processors. The processing circuit may include multiple memories. The acquisition device 27 and the storage device 28 realize the above-mentioned functions by executing a program stored in the memory using a processor (computer). The acquisition device 27 and the storage device 28 may each include a processing circuit including a processor, memory, and dedicated hardware as a hardware resource. Some or all of the functions of the acquisition device 27 and the storage device 28 may be realized by dedicated hardware.

[0105] The support system according to the present disclosure can be applied to a system that supports the management, design, or maintenance of elevators.

[0106] REFERENCE SIGNS LIST 1 Support system 2 Elevator 20 Cage 21 Counterweight 22 Main rope 23 Driving sheave 24 Electric motor 25 Control device 26 Sensor 27 Acquisition device 28 Storage device 4 Support device 40 Memory unit 41 Extraction unit 42 First calculation unit 43 Comparison unit 44 Second calculation unit 45 Correction unit 50 Speed ​​data calculation unit 51 Travel distance calculation unit 52 Travel time calculation unit 53 Acceleration time series data calculation unit 54 Speed ​​time series data calculation unit 60 Torque data calculation unit 61 Basic data calculation unit 62 Static torque calculation unit 63 Dynamic torque calculation unit 64 Loss torque calculation unit 65 Addition unit 70 Motor data calculation unit 71 Electrical angular velocity calculation unit 72 Current / voltage calculation unit, 73 Determination unit, 74 Weakening field current calculation unit F1 Weight calculation function, F2 Position calculation function, F3 Acceleration calculation function, F4 Unbalance torque calculation function, F5 Unbalance torque calculation function, F6 Addition function, F7 Acceleration / deceleration torque calculation function, F8 Acceleration / deceleration torque calculation function, F9 Acceleration / deceleration torque calculation function, F10 Addition function, F11 Unit unification function, F12 Comparison function, F13 Correction value calculation function, F14 Correction value calculation function 8 Maintenance device 80 Storage unit, 81 Detection unit 100 Processing circuit, 101 Processor, 102 Memory, 103 Dedicated hardware

Claims

1. an extraction unit that extracts elevator operation data stored in a storage device as time-series physical data; a first calculation unit that calculates time-series cyber data corresponding to the time-series physical data extracted by the extraction unit based on the operation data of the elevator stored in the storage device, using a reproduction model including parameters; a second calculation unit that calculates a correction value of the parameter such that an error between the time-series physical data extracted by the extraction unit and the time-series cyber data calculated by the first calculation unit is minimized; a correction unit that corrects the reproduction model based on the correction value calculated by the second calculation unit; a storage unit that stores the correction value calculated by the second calculation unit; a detection unit that detects a modulation of the correction value stored in the storage unit; A support system with

2. the extraction unit extracts speed time-series physical data, which is operation data related to the speed of the elevator car, as the time-series physical data; the reproduction model includes a speed reproduction model for generating a speed pattern of the car, the velocity reproduction model includes a velocity parameter as the parameter, the first calculation unit calculates velocity time-series cyber data corresponding to the velocity time-series physical data using the velocity reproduction model; The assistance system according to claim 1 , wherein the second calculation unit calculates a correction value of the speed parameter that minimizes an error between the speed time-series physical data and the speed time-series cyber data.

3. the extraction unit extracts, as the time-series physical data, torque time-series physical data which is operation data related to torque of an electric motor of the elevator; the reproduction model includes a torque reproduction model including a torque parameter as the parameter, the first calculation unit calculates torque time-series cyber data corresponding to the torque time-series physical data by using the torque reproduction model; 3. The assistance system according to claim 1, wherein the second calculation unit calculates the correction value of the torque parameter such that an error between the torque time-series physical data and the torque time-series cyber data is minimized.

4. the extraction unit extracts, as the time-series physical data, electric motor time-series physical data which is operation data related to an electric motor of the elevator; the reproduction model includes an electric motor reproduction model including electric motor parameters as the parameters, the first calculation unit calculates electric motor time-series cyber data corresponding to the electric motor time-series physical data by using the electric motor reproduction model; 3. The assistance system according to claim 1, wherein the second calculation unit calculates the correction values ​​of the motor parameters such that an error between the motor time-series physical data and the motor time-series cyber data is minimized.

5. the extraction unit extracts acceleration time-series physical data, which is operation data related to the acceleration of the elevator car, as the time-series physical data; the reproduction model includes an acceleration reproduction model for generating an acceleration pattern of the car; the acceleration reproduction model includes an acceleration parameter as the parameter, the first calculation unit calculates acceleration time-series cyber data corresponding to the acceleration time-series physical data using the acceleration reproduction model; 3. The assistance system according to claim 1, wherein the second calculation unit calculates a correction value of the acceleration parameter that minimizes an error between the acceleration time-series physical data and the acceleration time-series cyber data.

6. the extraction unit extracts position time-series physical data, which is operation data related to a position of the elevator car, as the time-series physical data; the reproduction model includes a position reproduction model for generating a position pattern of the car, the position reproduction model includes a position parameter as the parameter, the first calculation unit calculates position time-series cyber data corresponding to the position time-series physical data using the position reproduction model; 3. The assistance system according to claim 1, wherein the second calculation unit calculates a correction value of the position parameter that minimizes an error between the position time-series physical data and the position time-series cyber data.