Management system for elevators

Abstract

The present invention provides a management system that is capable of more accurately determining the remaining life of equipment of an elevator even when working data indicating the working status of the elevator cannot be directly obtained. Provided is a management system (1) wherein a reproduction unit (27) uses operation data that has been acquired by a first server-side communication unit (25) to reproduce working data on the basis of a working model of the elevator. The operation data indicates the operation status of the elevator with regard to at least one of traveling of a car (6) and opening / closing of a car door (9) of the car (6). The working data indicates the working status of the elevator, which includes time series data when the operation indicated by the operation data is performed. An evaluation unit (28) uses the reproduced working data to evaluate, on the basis of a deterioration factor model, a deterioration factor that affects the deterioration of the equipment of the elevator. A determination unit (29) uses the evaluated deterioration factor to determine the remaining life of the equipment on the basis of a life model of the equipment.

Description

Elevator Management System

[0001] The present disclosure relates to elevator management systems.

[0002] Patent Document 1 discloses an example of a maintenance device for elevators and other elevating machines. The maintenance device includes a part life analysis and setting means for analyzing and setting the lifespan of parts. The maintenance device includes a maintenance work setting means for setting part replacement intervals and inspection intervals. The maintenance device also includes an operation data collection means for collecting operation data of the elevator.

[0003] Japanese Patent Application Publication No. 2003-238041

[0004] In the elevator maintenance device of Patent Document 1, the operation data includes, for example, data on the load on components, ambient temperature, humidity, operating speed, and rotation speed. The maintenance device performs processing such as lifespan analysis using operation data collected from each elevator via a wide-area communication network such as the Internet. However, due to limitations on the amount of communication via the communication network or functional limitations of the elevator control device, it may be impossible to obtain operation data such as car speed and time-series data on the motor's rotation speed and current, which represent the operating status of elevator and other elevator equipment. In such cases, this data cannot be used to perform more accurate lifespan analysis.

[0005] The present disclosure is directed to solving such problems, and provides a management system that can more accurately determine the remaining lifespan of elevator equipment even when operational data that indicates the operating status of the elevator cannot be directly obtained.

[0006] The management system according to the present disclosure includes an acquisition unit that acquires operation data representing the operating status of at least one of the running of an elevator car or the opening and closing of the car doors of the car; a reproduction unit that uses the operation data acquired by the acquisition unit to reproduce operation data representing the operating status of the elevator, including time series data when performing the operation represented by the operation data, based on an operation model of the elevator; an evaluation unit that uses the operation data reproduced by the reproduction unit to evaluate, based on a deterioration factor model of the equipment, deterioration factors that affect the deterioration of equipment of the elevator when performing the operation represented by the operation data; and a determination unit that uses the deterioration factors of the elevator equipment evaluated by the evaluation unit to determine the remaining lifespan of the equipment based on a lifespan model of the equipment.

[0007] According to the management system of the present disclosure, it is possible to more accurately determine the remaining lifespan of elevator equipment even when operational data indicating the operating status of the elevator cannot be directly obtained.

[0008] FIG. 1 is a configuration diagram of a management system according to embodiment 1. FIG. 2 is a block diagram showing the configuration of a reproduction unit according to embodiment 1. FIG. 3 is a diagram showing an example of a speed pattern reproduced by the reproduction unit according to embodiment 1. FIG. 4 is a diagram showing an example of a speed pattern reproduced by the reproduction unit according to embodiment 1. FIG. 5 is a diagram showing an example of a speed pattern reproduced by the reproduction unit according to embodiment 1. FIG. 6 is a diagram showing an example of operation data for an electric motor reproduced by the reproduction unit according to embodiment 1. FIG. 7 is a block diagram showing the configuration of an evaluation unit according to embodiment 1. FIG. 8 is a block diagram showing the configuration of a determination unit according to embodiment 1. FIG. 9 is a flowchart showing an example of the operation of the management system according to embodiment 1. FIG. 10 is a hardware configuration diagram of a main part of the management system according to embodiment 1.

[0009] The following describes embodiments of the subject matter of the present disclosure with reference to the accompanying drawings. In each drawing, identical or corresponding parts are designated by the same reference numerals, and redundant explanations are appropriately simplified or omitted. Note that the subject matter of the present disclosure is not limited to the following embodiments, and any component of the embodiments may be modified or omitted within the scope of the gist of the present disclosure.

[0010] First Embodiment Fig. 1 is a configuration diagram of a management system 1 according to a first embodiment.

[0011] The management system 1 is a system that manages elevators. The elevators are applied to a facility 2 having multiple floors. The facility 2 to which the elevators are applied includes, for example, one or multiple buildings. The facility 2 to which the elevators are applied may be part of a building. The facility 2 to which the elevators are applied may be either an indoor facility or an outdoor facility. The management system 1 may manage multiple elevators. In this case, the management system 1 may manage multiple elevators that are applied to the same facility 2, or may manage multiple elevators that are applied to different facilities 2.

[0012] An elevator shaft 3 is provided in a facility 2 to which the elevator is applied. The shaft 3 is a vertically long space that spans multiple floors of the facility 2. The elevator includes a hoist 4, a main rope 5, a car 6, a counterweight 7, and a control device 8.

[0013] The hoisting machine 4 has a sheave. The hoisting machine 4 is a device that has a function of generating torque to rotate the sheave. The hoisting machine 4 includes, for example, an electric motor that generates torque. The hoisting machine 4 is installed, for example, at the upper or lower part of the hoistway 3. If a machine room is provided above the hoistway 3, the hoisting machine 4 may be installed in the machine room.

[0014] The main ropes 5 are wound around sheaves of the hoisting machine 4. The main ropes 5 suspend the car 6 in the hoistway 3, thereby supporting the load of the car 6. The main ropes 5 suspend the counterweight 7 in the hoistway 3, thereby supporting the load of the counterweight 7. The main ropes 5 may be, for example, strand ropes or belt ropes.

[0015] The car 6 and counterweight 7 travel in opposite directions in the hoistway 3 as the main ropes 5 move due to the rotation of the sheave of the hoisting machine 4. The car 6 is a device that transports passengers and the like between multiple floors by traveling up and down inside the hoistway 3. The counterweight 7 is a device that balances the loads applied to the main ropes 5 on both sides of the sheave of the hoisting machine 4 between the car 6 and the counterweight 7. The car 6 and counterweight 7 travel up and down inside the hoistway 3 by being guided, for example, by guide rails (not shown). The car 6 includes a car door 9 and a weighing device 10. The car door 9 includes a door panel that separates the inside and outside of the car 6 and an electric motor that opens and closes the door panel. The weighing device 10 is a device that measures the load inside the car due to the weight of passengers and the like riding in the car 6.

[0016] The control device 8 is a device that controls the operation of the elevator. The control device 8 is installed, for example, above or below the hoistway 3. If a machine room is provided above the hoistway 3, the control device 8 may be installed in the machine room. The control device 8 controls, for example, the running of the car 6 in response to a user's call. In this example, the running of the car 6 from when it departs from the departure floor to when it stops at the destination floor is considered to be one run of the car 6. The control device 8 also controls, for example, the opening and closing of the car door 9 of the elevator car 6. In this example, the series of operations from when the car door 9 is fully opened from a fully closed state by an opening operation, when it waits in the fully open state, to when it is fully closed by a closing operation is considered to be one opening and closing of the car door 9.

[0017] The control device 8 stores control information related to elevator control. The control information includes parameters causally related to either or both of the transient heat generation and cooling of each device constituting the elevator. The parameters may be continuous, discrete, or may represent one of multiple options. The control information includes discontinuous values ​​representing the elevator status, such as an inverter drive command signal, a fan drive command signal, a door open command signal, a door close command signal, a door full open recognition signal, a door full closed recognition signal, and landing plate information. Here, the inverter is, for example, a device that outputs drive current to the electric motor of the hoisting machine 4. The fan is, for example, a device that blows air to the air-cooled devices constituting the elevator. The control information also includes continuous or discrete numerical information such as time information, information on the floor where the car 6 is located, information on the absolute or relative position of the car 6 in the elevator shaft 3, load inside the car, car travel speed command value, hoisting machine motor speed command value, hoisting machine motor speed feedback value, hoisting machine motor current command value, hoisting machine motor current feedback value, hoisting machine motor voltage command value, door opening operation start time, door full open waiting time, door closing operation completion time, door speed command value, door speed feedback value, door opening / closing motor current command value, door opening / closing motor current feedback value, and door opening / closing motor voltage command value.

[0018] An environmental sensor 11 is applied to an elevator. The environmental sensor 11 is a device that acquires data on the elevator's operating environment. The environmental sensor 11 is installed, for example, in the elevator hoistway 3 or the machine room. The environmental sensor 11 is preferably installed in a location where it is less affected by local heat generation by the equipment that makes up the elevator, such as below the control device 8. The environmental sensor 11 includes, for example, one or both of a temperature sensor and a humidity sensor. Multiple environmental sensors 11 may be installed in an elevator.

[0019] The management system 1 includes a monitoring device 12 and an analysis device 13 .

[0020] The monitoring device 12 is provided for each elevator managed by the management system 1. When the management system 1 manages multiple elevators, the management system 1 may include multiple management devices. In this case, one of the management devices corresponds to each elevator. The monitoring device 12 is provided in the facility 2 to which the corresponding elevator is applied. The monitoring device 12 monitors the status of the corresponding elevator by acquiring information about the elevator, for example, from the elevator's control device 8 and an environmental sensor 11 that acquires data on the elevator's operating environment. The monitoring device 12 is connected to the analysis device 13 via a wide-area first communication network 14, such as the Internet. The first communication network 14 may be a virtual private network (VPN) configured on a public network such as the Internet, or another secure network. The monitoring device 12 is, for example, an edge server. The monitoring device 12 transmits operation data indicating the elevator's operation status to the analysis device 13 via the first communication network 14.

[0021] Here, the operation data is, for example, information representative of each elevator operation, such as one run of the car 6 and one opening and closing of the car door 9. In this example, the operation data does not include time-series data that represents continuous temporal changes in numerical values, such as physical quantities including speed and current, by a series of such numerical values ​​corresponding to each point in time. Here, the operation data regarding each up-and-down run of the car 6 may be referred to as car run basic information. Furthermore, the operation data regarding each opening and closing of the car door 9 may be referred to as car door open / close basic information. In this example, the operation data includes the car run basic information and the car door open / close basic information.

[0022] The car running basic information includes, for example, the running start time of the car 6, the departure floor of the car 6 or its position in the elevator shaft 3 at the time of departure, the arrival floor of the car 6 or its position in the elevator shaft 3 at the time of arrival, the running completion time of the car 6, and the load in the car. The car running basic information does not have to include any of this information. The car running basic information does not have to include, for example, one of the running start time of the car 6 and the running completion time of the car 6.

[0023] The basic car door opening / closing information includes, for example, the floor on which the car door 9 is opened and closed, the start time of the opening operation of the car door 9, the waiting time for the car door 9 in the fully open state, and the completion time of the closing operation of the car door 9. The basic car door opening / closing information does not need to include any of this information. For example, the basic car door opening / closing information does not need to include either the start time of the opening operation of the car door 9 or the completion time of the closing operation of the car door 9. The basic car door opening / closing information may include the number of times the car door 9 has reversed.

[0024] In addition, the operation data may include information on the elevator's operating mode regarding the running of the car 6 and the opening and closing of the car door 9, for example, if the elevator is equipped with an operating mode for wheelchair users.

[0025] The analysis device 13 is a device that processes information about elevators managed by the management system 1. The analysis device 13 is, for example, a computer system including one or more server devices 15. The analysis device 13 may include three or more server devices 15. The analysis device 13 may have a multiplexed configuration including multiple server devices 15 having the same functions. Some or all of the server devices 15 that make up the analysis device 13 are installed in remote locations from the facility 2 in which the elevator corresponding to the monitoring device 12 is used. The analysis device 13 may be installed in a country or region different from that of the facility 2 in which the elevator corresponding to the monitoring device 12 is used. When the analysis device 13 is configured with multiple server devices 15, some of the server devices 15 may be installed in a country or region different from that of the other server devices 15. When the analysis device 13 is configured with multiple server devices 15, the respective server devices 15 are connected to each other, for example, via a first communication network 14. Some or all of the functions of the analysis device 13 may be installed on an on-premise server of a maintenance company that operates the management system 1, or may be installed on a cloud server. Some or all of the functions of the analysis device 13 may be implemented by processing or storage resources on a cloud service.

[0026] The analysis device 13 is connected to an internal second communication network 16, such as an intranet or private network of a maintenance company. For example, when the analysis device 13 is configured as a cloud server, the second communication network 16 may be a VPN configured on a public network such as the Internet. In the management system 1, users who are allowed to access the second communication network 16 are set. Note that the user's access authority may be granted to the user himself / herself, to a group to which the user belongs, or to a role assigned to the user. The group to which the user belongs may be, for example, a group of bases such as the maintenance company's head office 17a, branch office 17b, branch office 17c, sales office 17d, and manufacturing plant 17e, or may be a group of another organization such as the maintenance company's technical department.

[0027] The second communication network 16 is a network that can access the specification database 18 and the maintenance database 19. Part or all of the specification database 18 and the maintenance database 19 are installed on, for example, an on-premise server or a cloud server of a maintenance company. Part or all of the specification database 18 and the maintenance database 19 may also be installed in the analysis device 13.

[0028] The specification database 18 is a database that stores elevator specification information. The specification database 18 stores identification information that identifies elevators managed by the management system 1 in association with the elevator specification information. The elevator specification information includes, for example, the elevator control method, the model name of the elevator hoist 4, the model name of the elevator control device 8, the rated speed, the rated load capacity, the lift stroke, and the model name of the car door 9. The elevator specification information may also include information such as the height of each floor of the facility 2 to which the elevator is applied.

[0029] The maintenance database 19 is a database that stores elevator maintenance information. The maintenance database 19 stores identification information that identifies elevators managed by the management system 1 and the maintenance information of the elevators in association with each other. The elevator maintenance information includes, for example, information such as the operation start date when the elevator started operation after installation and the parts replacement history.

[0030] The monitoring device 12 includes a collection unit 20, a temporary storage unit 21, a first conversion unit 22, a second conversion unit 23, and a facility-side communication unit 24. Some or all of the functions of the monitoring device 12 may be installed in corresponding elevator equipment such as the control device 8.

[0031] The collection unit 20 is a part equipped with a function for collecting information from the elevator control device 8, the environmental sensor 11, etc. The collection unit 20 collects, for example, control information from the elevator control device 8. The collection unit 20 may acquire detailed information such as time-series data as control information. The collection unit 20 collects data on the operating environment from the environmental sensor 11. The collection unit 20 may also collect information on the time the information was collected. The collection unit 20 outputs the collected information to the temporary storage unit 21.

[0032] The temporary storage unit 21 is a part equipped with a function of temporarily storing information collected by the collection unit 20. The temporary storage unit 21 stores the information collected by the collection unit 20 from the elevator control device 8 and the information collected by the collection unit 20 from the environmental sensor 11 in association with each other based on information on the collection time.

[0033] The first conversion unit 22 is a component equipped with a function for extracting information from data collected from the elevator and converting it into operation data. The first conversion unit 22 reads the information collected by the collection unit 20 from the temporary storage unit 21 and converts it. The first conversion unit 22 extracts basic car travel information, such as the departure and arrival floors of the car 6, from time-series data on the position, speed, or acceleration of the car 6. The first conversion unit 22 extracts basic car door opening / closing information, such as the start time of the opening operation of the car door 9 and the completion time of the closing operation, from time-series data on the opening degree of the door panel of the car door 9. The first conversion unit 22 generates elevator operation data using the extracted information. The first conversion unit 22 may convert the data collected from the elevator into operation data sequentially each time the data is collected, or may convert the data into operation data at predetermined regular or irregular intervals. The first conversion unit 22 outputs the converted operation data to the facility communication unit 24.

[0034] The second conversion unit 23 is a component equipped with a function for resampling a portion of the operating environment data collected from the environmental sensor 11 and the like, and converting the data into data that can be communicated together with the operation data. The second conversion unit 23 reads the information collected by the collection unit 20 from the temporary storage unit 21 and performs the conversion. For example, the second conversion unit 23 resamples the operating environment data read from the temporary storage unit 21 into temperature and humidity information at a predetermined cycle. In this example, the sampling rate after resampling by the second conversion unit 23 is lower than the original sampling rate of the operating environment data collected by the collection unit 20. The second conversion unit 23 may perform the conversion by resampling sequentially, or at predetermined regular or irregular timings. The second conversion unit 23 outputs the operating environment data converted by resampling to the facility communication unit 24.

[0035] The facility communication unit 24 is a part that has a function of communicating information through the first communication network 14. The facility communication unit 24 transmits the operation data from the first conversion unit 22 to the analysis device 13 through the first communication network 14. In this example, the facility communication unit 24 associates the operation data from the first conversion unit 22 and the operating environment data from the second conversion unit 23 with each other and transmits them together to the analysis device 13 through the first communication network 14. The facility communication unit 24 is an example of a transmission unit.

[0036] The facility communication unit 24 transmits operation data and operating environment data taking into account one or both of the processing load of the analysis device 13 and the communication load of the first communication network 14. The facility communication unit 24 transmits data during times when elevators are less active, such as at night. The facility communication unit 24 may transmit data based on schedule management on the analysis device 13 side, to prevent the processing load from concentrating on the analysis device 13. The facility communication unit 24 may, for example, inquire about the processing load of the analysis device 13 and determine the timing of data transmission based on an answerback from the analysis device 13. The facility communication unit 24 may transmit data to the analysis device 13 upon receiving, for example, a regular or irregular polling trigger sent from the analysis device 13. The facility communication unit 24 may temporarily stop transmitting data when, for example, the communication load of the first communication network 14 becomes large. Note that the communication load of the first communication network 14 may be monitored by either the monitoring device 12 or the analysis device 13.

[0037] The analysis device 13 includes a first server-side communication unit 25 , an input information storage unit 26 , a reproduction unit 27 , an evaluation unit 28 , a judgment unit 29 , a lifetime information storage unit 30 , and a second server-side communication unit 31 .

[0038] The first server-side communication unit 25 is a unit that has a function of communicating information through the first communication network 14. The first server-side communication unit 25 receives operation data transmitted from the facility-side communication unit 24 through the first communication network 14. In this example, the first server-side communication unit 25 receives both operation data and operating environment data of elevators that are associated with each other through the first communication network 14. The facility-side communication unit 24 is an example of an acquisition unit. The first server-side communication unit 25 outputs the received information to the input information storage unit 26.

[0039] The input information storage unit 26 is a part equipped with a function for storing information. The input information storage unit 26 classifies and stores the elevator operation data and operating environment data received by the first server-side communication unit 25 for each target elevator. Since the amount of data for each operation in the operation data transmitted from the monitoring device 12 is small, the input information storage unit 26 may store information so as to record the lifetime history of the elevator over the entire operating period from the start of operation of the elevator.

[0040] The reproducing unit 27 is a component equipped with a function for reproducing operation data representing the elevator operation status during operation represented by the operation data, based on the elevator operation model. The operation data is data that specifically reproduces kinematic, dynamic, or electromagnetic physical quantities, such as speed and current, during each elevator operation. Here, the physical quantities in the operation data may be actual values ​​of quantities such as the speed of the car 6 or the current of the motor, as well as command values ​​or feedback values ​​of these quantities. Furthermore, for example, the motor current in the operation data may be component values ​​obtained by coordinate transformation, such as d-axis current and q-axis current. In this example, the operation data is data that represents the elevator operation status, such as the running of the car 6 and the opening and closing of the car doors 9, in more detail than the operation data. The operation data may include time-series data that represent continuous time changes in numerical values ​​of physical quantities, including speed and current, by a series of numerical values ​​corresponding to each time point. The operation data includes time-series data such as the running speed of the car 6, the hoist motor current, and the hoist motor voltage. The operation data includes, for example, time-series data such as the opening / closing speed of the car door 9, the current of the door opening / closing motor, and the voltage of the door opening / closing motor. The reproduction unit 27 reads out the operation data stored in the input information storage unit 26 and reproduces the operation data. The reproduction unit 27 reproduces the operation data based on a preset elevator operation model. The elevator operation model is, for example, a physical model that models the kinematic, dynamic, or electromagnetic characteristics of the elevator. The reproduction unit 27 may reproduce the operation data sequentially every time the first server-side communication unit 25 receives operation data from the monitoring device 12, or may convert the accumulated operation data into operation data at preset regular or irregular timing. The reproduction unit 27 outputs the reproduced operation data to the evaluation unit 28.

[0041] The evaluation unit 28 is a part equipped with a function for evaluating deterioration factors that affect the deterioration of elevator equipment during elevator operation. The evaluation unit 28 evaluates deterioration factors during elevator operation represented by operation data received from the monitoring device 12. The evaluation unit 28 performs evaluation based on a preset deterioration factor model using the operation data reproduced by the reproduction unit 27 and the operating environment data read from the input information storage unit 26. Since the deterioration mechanism differs for each elevator equipment, the deterioration factors differ for each elevator equipment. Therefore, when evaluating deterioration factors for multiple elevator equipment, the evaluation unit 28 may evaluate the deterioration factors for each equipment using multiple deterioration factor models.

[0042] The deterioration factor may be, for example, the temperature or time-series data of a device that deteriorates due to a temperature-dependent mechanism such as the Arrhenius equation or thermal expansion caused by heating or cooling. The deterioration factor may include, for example, the temperature of the device, such as the control device 8 or the traction machine 4. The deterioration factor may include, for example, the magnet temperature and winding temperature of a permanent magnet motor, bearing temperature, chip temperature and case temperature of a power semiconductor, electrolytic capacitor temperature, or battery temperature. When the deterioration factor is temperature, the deterioration factor model may be a thermal model, such as a thermal circuit model. In this case, the thermal model may incorporate heat generation or cooling due to operation of the elevator equipment. Heat generation or cooling due to operation of the elevator equipment may include, for example, Joule heating due to current or air cooling due to operation of a fan. The amount of heat generation or cooling due to operation of the elevator equipment is estimated based on, for example, the current value of the reproduced operation data.

[0043] The deterioration factor may also be information about bending that has occurred in equipment that may experience bending fatigue, such as the elevator main rope 5. The bending information includes, for example, information about the magnitude, direction, and frequency of bending. The bending information is estimated based on, for example, the running position of the car 6 in the reproduced operation data, the load inside the car, and the like.

[0044] Furthermore, the deterioration factor may be the number of times an electromagnetic contactor or other device mechanically switches electrical contacts. The number of times an electromagnetic contactor switches is estimated based on, for example, the number of times the elevator travels in the reproduced operation data, as well as the duration of current flow and the current flow.

[0045] The determination unit 29 is a component equipped with a function for determining the remaining lifespan of elevator equipment. The determination unit 29 uses the deterioration factors of the elevator equipment evaluated by the evaluation unit 28 to determine the remaining lifespan of the equipment based on a lifespan model for the equipment. The determination unit 29 may determine the remaining lifespan for each of multiple pieces of equipment. The lifespan model includes a model based on, for example, the Arrhenius equation, which associates a lifespan consumption rate, which indicates the remaining lifespan or the rate of deterioration progression, with deterioration factors such as temperature. The determination unit 29 determines the remaining lifespan of the equipment by, for example, comparing the deterioration factors evaluated by the evaluation unit 28 with data on the relationship between lifespan and deterioration factors provided by the manufacturer of the equipment. The determination unit 29 may determine the remaining lifespan of the equipment by, for example, comparing the deterioration factors evaluated by the evaluation unit 28 with the deterioration factors in the past operating history of the same type of equipment. The remaining lifespan is, for example, a numerical value that indicates what percentage of the lifespan has been consumed in the current state, where the new state of the target device at the start of use is 100% and the state at the end of the product lifespan is 0%. The determination unit 29 may predict the transition of the remaining lifespan of the device. The transition of the remaining lifespan of the device is estimated, for example, based on the past usage history of the device. The determination unit 29 may determine when the target device will reach the end of its product lifespan based on the prediction result of the transition of the remaining lifespan. The determination unit 29 outputs the determination results, such as the remaining lifespan of the target device and the time when the target device will reach the end of its product lifespan, to the lifespan information accumulation unit 30.

[0046] The lifespan information accumulation unit 30 is a part equipped with a function for accumulating and storing the determination results by the determination unit 29. In this example, the lifespan information accumulation unit 30 accumulates and stores information on the remaining lifespan determined by the determination unit 29 throughout the entire operation period from the start of elevator operation. At this time, the lifespan information accumulation unit 30 stores the determination results of the remaining lifespan for each operation period for the elevator equipment, i.e., the transition of the remaining lifespan. The remaining lifespan accumulation unit stores identification information for identifying the elevator managed by the management system 1, information for identifying the equipment to be determined for that elevator, and the determination results for that equipment, in association with each other. The remaining lifespan accumulation unit may also store the evaluation results of the deterioration factors for that equipment.

[0047] The second server-side communication unit 31 is a part that has a function of communicating information via the second communication network 16. The analysis device 13 accesses the specification database and the maintenance database 19, etc., via the second server-side communication unit 31. The analysis device 13 may use specification information read from the specification database when reproducing operation data, evaluating deterioration factors, determining remaining life, etc. The analysis device 13 may write the remaining life determination result, etc., into the maintenance information in the maintenance database 19.

[0048] The analysis device 13 may also grant, to users who can access the second communication network 16, some or all of the following access rights: access to view the information stored in the lifespan information storage unit 30; access to update the operation model used by the reproduction unit 27; access to update the degradation factor model used by the evaluation unit 28; and access to update the lifespan model used by the determination unit 29. The analysis device 13 may also grant access rights individually for each user, group, or role. The analysis device 13 may also change the presence or type of access rights to be granted in advance. For example, the analysis device 13 grants, to a user at the manufacturing plant 17e, access rights to view the information stored in the lifespan information storage unit 30, access rights to update the operation model, access rights to update the degradation factor model, and access rights to update the lifespan model. For example, the analysis device 13 grants, to a user at the sales office 17d, access rights to view the information stored in the lifespan information storage unit 30.

[0049] A user who can access the second communication network 16 or the analysis device 13 makes a maintenance decision, such as a decision to replace elevator equipment, based on the remaining lifespan determination result. The replacement decision may be made by the analysis device 13, for example, based on a predetermined criterion for the remaining lifespan. More specifically, for example, when the remaining lifespan determined by the determination unit 29 falls below a predetermined replacement criterion for each equipment, the equipment is determined to need replacement. The replacement decision may also be made by a maintenance technician in charge of elevator maintenance. More specifically, for example, the maintenance technician determines whether or not the equipment needs replacement based on the remaining lifespan determination result for the elevator and a future maintenance plan. The replacement decision may also be made by the analysis device 13, for example, based on a relative comparison with other elevators. For example, for equipment with a limited quantity, a decision may be made as to which elevator equipment should be prioritized for replacement. In this case, the analysis device 13, for example, sorts elevators of the same type in order of shortest remaining lifespan, allowing equipment with a shorter remaining lifespan to be replaced with higher priority. Such maintenance decisions make it easier to organize matters that need to be addressed in advance, such as arranging for replacement equipment and scheduling replacement work.

[0050] FIG. 2 is a block diagram showing the configuration of the reproducing unit 27 according to the first embodiment.

[0051] The reproduction unit 27 includes a speed pattern calculation unit 32, a speed pattern parameter storage unit 33, an inertia calculation unit 34, an electric motor torque calculation unit 35, a torque parameter storage unit 36, an electric motor calculation unit 37, and an electric parameter storage unit 38. The operation models used by the reproduction unit 27 include a speed pattern calculation model, an inertia calculation model, an electric motor torque calculation model, and an electric motor calculation model.

[0052] The speed pattern calculation model is a model that calculates at least one of the speed patterns of the running of the car 6 and the opening and closing of the car door 9, corresponding to the operation data. Model parameters in the speed pattern calculation model are stored in the speed pattern parameter storage unit 33. The speed pattern calculation unit 32 is a part that has a function of performing calculations based on the speed pattern calculation model. The speed pattern calculation unit 32 reads out the model parameters stored in the speed pattern parameter storage unit 33 and calculates the speed pattern.

[0053] The inertia calculation model is a model for calculating the inertia of an elevator. The motor torque calculation model is a model for calculating the torque of an elevator motor corresponding to the speed pattern calculated by the speed pattern calculation model. Model parameters in the inertia calculation model and the motor torque calculation model are stored in the torque parameter storage unit 36. The inertia calculation unit 34 is a unit equipped with a function for performing calculations based on the inertia calculation model. The motor torque calculation unit 35 is a unit equipped with a function for performing calculations based on the motor torque calculation model. The inertia calculation unit 34 reads the model parameters stored in the torque parameter storage unit 36 ​​and calculates the inertia. The motor torque calculation unit 35 reads the model parameters stored in the torque parameter storage unit 36 ​​and calculates the motor torque corresponding to the speed pattern calculated by the speed pattern calculation unit 32 using the inertia calculated by the inertia calculation unit 34.

[0054] The motor electrical calculation model is a model that calculates at least one of the current and voltage that operate the elevator motor, corresponding to the torque calculated by the motor torque calculation model. Model parameters in the motor electrical calculation model are stored in the electrical parameter storage unit 38. The motor electrical calculation unit 37 is a part that has a function for performing calculations based on the motor electrical calculation model. The motor electrical calculation unit 37 reads the model parameters stored in the electrical parameter storage unit 38, and calculates the motor current and voltage that correspond to the torque calculated by the motor torque calculation unit 35.

[0055] The reproduction unit 27 outputs time-series data such as the speed pattern, torque, current, and voltage calculated by the speed pattern calculation unit 32, the motor torque calculation unit 35, and the motor current calculation unit 37 as operation data.

[0056] Next, an example of reproduction of operation data by the reproduction unit 27 will be described with reference to Fig. 3 to Fig. 6. Fig. 3 to Fig. 5 are diagrams showing examples of speed patterns reproduced by the reproduction unit 27 according to embodiment 1. Fig. 6 is a diagram showing examples of operation data for an electric motor reproduced by the reproduction unit 27 according to embodiment 1.

[0057] Figure 3 shows an example of a speed pattern of the running speed of the car 6 reproduced by the speed pattern calculation unit 32. In this example, a speed pattern is shown when the elevator car 6 reaches its set maximum speed, such as when traveling to a terminal floor. In Figure 3, the horizontal axis of each graph represents the passage of time. In the lower graph of Figure 3, the vertical axis represents the vertical position of the car 6 in the hoistway 3. In the center graph of Figure 3, the vertical axis represents the vertical speed of the car 6. In the upper graph of Figure 3, the vertical axis represents the vertical acceleration of the car 6.

[0058] The speed pattern calculation unit 32 receives basic car running information from the operation data as input information. In this example, the basic car running information is the running start time T ｓｔａｒｔ , the position X in the elevator shaft 3 at the time of departure of the car 6 ｓｔａｒｔ , the position X in the elevator shaft 3 when the car 6 arrives ｓｔｏｐ The basic car running information may include information on the departure floor and arrival floor of the car 6. In this case, the speed pattern calculation unit 32 may convert the information on the departure floor and arrival floor into information on the position of the car 6 in the elevator shaft 3.

[0059] The speed pattern calculation unit 32 reads out model parameters from the speed pattern parameter storage unit 33. The model parameters include, for example, a set maximum speed v ｍａｘ [m / sec], acceleration α, which is the absolute value of the maximum acceleration during acceleration ａｍｘ [m / sec ２ ], and the deceleration α which is the absolute value of the maximum acceleration during deceleration ｄｍｘ[m / sec ２ In this example, the acceleration α ａｍｘ and deceleration α ｄｍｘ The model parameter is, for example, the time t １ [sec], the time t from the end of the constant acceleration state to the maximum speed state ３ [sec], the time t from the end of the maximum speed state to the constant deceleration state ５ [sec], and the time t from the end of the constant deceleration state until the deceleration ends and the speed reaches 0 ７ The model parameters include information on the transition time between the running states of the car 6, such as [sec]. These model parameters are determined depending on the model or specifications of the elevator. The speed pattern calculation unit 32 may acquire the model parameters from, for example, the manufacturer 17e or the specification database 18 via the second communication network 16. At this time, the speed pattern calculation unit 32 may store the acquired model parameters in the speed pattern parameter storage unit 33.

[0060] The speed pattern calculation unit 32 uses this input information and model parameters to reproduce and calculate the time series data α(t) of the acceleration of the car 6, the time series data v(t) of the speed of the car 6, and the time series data x(t) of the position of the car 6, for example, as follows:

[0061] First, the speed pattern calculation unit 32 calculates a constant acceleration time t ２ [sec], and the absolute value X of the movement amount of the car 6 during acceleration ａｃｃ Calculate the constant acceleration time t [m]. ２ is calculated by the following formula (1.1), assuming that the jerk before and after reaching a constant acceleration state is constant. ａｃｃ is defined by the following equation (1.2).

[0062]

[0063]

[0064] As a result, the speed pattern calculation unit 32 calculates the time series data α of the acceleration of the car 6 during acceleration.ａｃｃ The speed pattern calculation unit 32 calculates the time series data of the acceleration of the car 6 by integrating the time series data of the acceleration of the car 6 with respect to time as shown in the following equation (1.3) with the initial speed set to 0, and calculates the time series data v ａｃｃ In equation (1.3), time t represents the time from the start of acceleration, and 0≦t≦t ａｃｃ is.

[0065]

[0066] The speed pattern calculation unit 32 also calculates the time series data v of the speed of the car 6 during acceleration. ａｃｃ By integrating (t) with time as in the following equation (1.4), the absolute value X of the movement amount of the car 6 during acceleration is obtained. ａｃｃ can be calculated.

[0067]

[0068] Next, the speed pattern calculation unit 32 calculates a constant deceleration time t ６ [sec], and the absolute value X of the movement amount of the car 6 during deceleration ｄｅｃ Calculate the constant deceleration time t [m]. ６ is calculated by the following formula (1.5), assuming that the jerk before and after reaching a constant acceleration state is constant. ｄｅｃ is defined by the following equation (1.6):

[0069]

[0070]

[0071] As a result, the speed pattern calculation unit 32 calculates the time series data α of the acceleration of the car 6 during deceleration. ｄｅｃ The speed pattern calculation unit 32 calculates the time series data of the acceleration of the car 6 during deceleration v by integrating the time series data of the acceleration of the car 6 with respect to time, using the initial speed as vmax, as shown in the following equation (1.7): ｄｅｃ In equation (1.7), time t represents the time from the start of deceleration, and 0≦t≦t ｄｅｃ is.

[0072]

[0073] The speed pattern calculation unit 32 also calculates the time series data v of the speed of the car 6 during deceleration. ｄｅｃ By integrating (t) with respect to time as in the following equation (1.8), the absolute value X of the movement amount of the car 6 during deceleration is obtained. ｄｅｃ can be calculated.

[0074]

[0075] Next, the speed pattern calculation unit 32 calculates the constant speed travel time t ４ [sec] is calculated by the following formula (1.9). ｒｕｎ is defined by the following equation (1.10):

[0076]

[0077]

[0078] In addition, the start time of the trip for car 6 is T ｓｔａｒｔ = 0, the time T １ is T １ = t １ , the end time of the constant acceleration state T ２ is T ２ =T １ +t ２ , the time T when acceleration is completed ３ is T ３ =T ２ +t ３ , the time T when deceleration begins ４ is T ４ =T ３ +t ４ , time T when reaching a constant deceleration state ５ is T ５ =T ４ +t ５ , the end time of the constant deceleration state T ６ is T ６ =T ５ +t ６ , the time T when deceleration is completed ７ is T ７ =T ６ +t ７In this case, if the acceleration during constant speed traveling is set to 0, the speed pattern calculation unit 32 can calculate the time series data α(t) of the acceleration of the car 6 as shown in the following equation (1.11). In equation (1.11), the upper sign of the compound sign is applied during ascending operation, and the lower sign of the compound sign is applied during descending operation.

[0079]

[0080] The speed pattern calculation unit 32 calculates the time series data v(t) of the speed of the car 6 by time integrating the time series data α(t) of the acceleration of the car 6 as shown in the following equation (1.12). Also, the speed pattern calculation unit 32 calculates the position X ｓｔａｒｔ Calculate the time series data x(t) of the position of the car 6 starting from the point of time T. In the formulas (1.12) and (1.13), the time t is the start time T of the car 6. ｓｔａｒｔ represents the time from the starting point, and 0≦t≦T ７ is.

[0081]

[0082]

[0083] The speed pattern calculation unit 32 is not limited to calculating the speed pattern based on the travel start time of the car 6 as described above, but may calculate the speed pattern based on the travel completion time of the car 6. In this case, the speed pattern calculation unit 32 calculates the speed pattern based on the travel completion time T ｓｔｏｐ , the position X in the elevator shaft 3 at the time of departure of the car 6 ｓｔａｒｔ , the position X in the elevator shaft 3 when the car 6 arrives ｓｔｏｐ It is also possible to accept basic car 6 running information including:

[0084] Figure 4 shows another example of the speed pattern of the running speed of the car 6 reproduced by the speed pattern calculation unit 32. In this example, a speed pattern is shown when the elevator car 6 does not reach its set maximum speed, for example, when traveling on a short floor. In Figure 4, the horizontal axis of each graph represents the passage of time. In the lower graph of Figure 4, the vertical axis represents the vertical position of the car 6 in the hoistway 3. In the center graph of Figure 4, the vertical axis represents the vertical speed of the car 6. In the upper graph of Figure 4, the vertical axis represents the vertical acceleration of the car 6.

[0085] When the elevator car 6 does not reach its set maximum speed, the car 6 travels at a constant set maximum speed for a constant speed travel time t ４ does not exist, and the constant acceleration time t ２ and constant deceleration time t ６ fluctuates according to the length of the travel section of the car 6. The speed pattern calculation unit 32 receives input information similar to that in the case where the set maximum speed of the car 6 is reached. The speed pattern calculation unit 32 reads out model parameters similar to those in the case where the set maximum speed of the car 6 is reached from the speed pattern parameter storage unit 33. At this time, the speed pattern calculation unit 32 receives the set maximum speed v as a model parameter. ｍａｘ It is not necessary to read out the

[0086] The speed pattern calculation unit 32 uses this input information and model parameters to calculate the time series data α(t) of the acceleration of the car 6, the time series data v(t) of the speed of the car 6, and the time series data x(t) of the position of the car 6, for example, as follows:

[0087] First, the speed pattern calculation unit 32 calculates the absolute value S of the movement amount of the car 6 in one run. ｒｕｎ Calculate the movement amount S of the car 6 [m]. ｒｕｎ is the position X of cage 6 at the time of departure ｓｔａｒｔ , and the position X of car 6 at the time of arrival. ｓｔｏｐ It is calculated by the following formula (1.14) using

[0088]

[0089] On the other hand, the movement amount S of the car 6 ｒｕｎis equal to the time integral of the absolute value of the time series data v(t) of the speed of the car 6, and is expressed by the following equation (1.15).

[0090]

[0091] Equation (1.15) can be expressed by dividing it into components corresponding to each running state of the car 6, as in the following equation (1.16).

[0092]

[0093] Of these components, the following two components S １ and S ６ can be calculated using the model parameters as in the following equations (1.17) and (1.18).

[0094]

[0095]

[0096] Also, the velocity at each of the following times is v １ = v (T １ ), v ２ = v(T ２ ), v ５ = v (T ５ ), and v ６ = v(T ６ ) In this case, the maximum speed of the car 6 in the speed pattern in this case is v ｍａｘ ' [m / sec], which can be expressed as in the following equations (1.19) to (1.22).

[0097]

[0098]

[0099]

[0100]

[0101] Also, the speed of cage 6 is v ２ From velocity v ｍａｘ The contribution to the travel distance due to the constant jerk up to ３ ' [m], and the speed of the car 6 is v ｍａｘ ´ to speed v５ The contribution to the travel distance due to the constant jerk up to ５ In this case, these distances are expressed by the following equations (1.23) and (1.24).

[0102]

[0103]

[0104] From the above, equation (1.16) can be expressed as the following equation (1.25) using equations (1.17) to (1.24): Furthermore, from the waveform of the acceleration of the car 6, the relationship of the following equation (1.26) holds.

[0105]

[0106]

[0107] Therefore, from the formula (1.25) and the formula (1.26), the movement amount S of the car 6 is ｒｕｎ , acceleration α ａｍｘ , deceleration α ｄｍｘ , and the transition time t １ , t ３ , t ５ , and t ７ Using the constant acceleration time t ２ and constant deceleration time t ６ The following relation is obtained: ２ and constant deceleration time t ６ If one of these can be calculated, the other can be calculated from this relational expression. ２ To calculate this, we need to find the solution of the quadratic equation expressed by the following equation (1.27a): The coefficients A, B, and C in this quadratic equation are given by the following equations (1.27b) to (1.27d).

[0108]

[0109]

[0110]

[0111]

[0112] The speed pattern calculation unit 32 calculates the constant acceleration time t ２ After calculating the constant deceleration time t ６ Calculate.

[0113]

[0114] As described above, the speed pattern calculation unit 32 calculates t １ , t ２ , t ３ , t ５ , t ６ , and t ７ The numerical information for each time can be obtained. ｓｔａｒｔ = 0, the time T １ is T １ = t １ , the end time of the constant acceleration state T ２ is T ２ =T １ +t ２ , the time T when acceleration changes to deceleration ３ is T ３ =T ２ +t ３ , time T when reaching a constant deceleration state ５ is T ５ =T ３ +t ５ , the end time of the constant deceleration state T ６ is T ６ =T ５ +t ６ , the time T when deceleration is completed ７ is T ７ =T ６ +t ７ At this time, the speed pattern calculation unit 32 can calculate the time series data α(t) of the acceleration of the car 6 as shown in the following equation (1.29). Here, in equation (1.29), the upper sign of the compound sign is applied during ascending operation, and the lower sign of the compound sign is applied during descending operation.

[0115]

[0116] The speed pattern calculation unit 32 calculates the time series data v(t) of the speed of the car 6 by time integrating the time series data α(t) of the acceleration of the car 6 as shown in equation (1.12). Also, the speed pattern calculation unit 32 calculates the position X ｓｔａｒｔ The time series data x(t) of the position of the car 6 is calculated with the start point being

[0117] The speed pattern calculation unit 32 determines whether to use the calculation method when the set maximum speed of the elevator car 6 is reached or the calculation method when the set maximum speed of the elevator car 6 is not reached, as follows, for example. The speed pattern calculation unit 32 determines whether to use the calculation method when the set maximum speed of the elevator car 6 is reached or the calculation method when the set maximum speed of the elevator car 6 is not reached, as follows, for example. ｌｏｎｇｒｕｎ＿ｌｉｍｉｔ [m] is calculated and stored in advance. Here, the reference value S ｌｏｎｇｒｕｎ＿ｌｉｍｉｔ corresponds to the minimum movement amount at which the car 6 reaches its set maximum speed.

[0118]

[0119] The speed pattern calculation unit 32 calculates the movement amount S of the car 6. ｒｕｎ is calculated, and the reference value S ｌｏｎｇｒｕｎ＿ｌｉｍｉｔ For example, the speed pattern calculation unit 32 selects a calculation method by comparing S ｒｕｎ ≧S ｌｏｎｇｒｕｎ＿ｌｉｍｉｔ In this case, the calculation method for the case where the set maximum speed of the elevator car 6 described in FIG. 3 is obtained is adopted. ｒｕｎ <S ｌｏｎｇｒｕｎ＿ｌｉｍｉｔ In this case, the calculation method for the case where the set maximum speed of the elevator car 6 described in FIG. 4 is not achieved is adopted.

[0120] FIG. 5 shows an example of a speed pattern of the opening and closing speed of the car door 9 during an opening operation, which is reproduced by the speed pattern calculation unit 32. In FIG. 5, the horizontal axis of each graph represents the passage of time. In the graph at the bottom of FIG. 5, the vertical axis represents the opening degree of the door panel of the car door 9, i.e., the position of the door panel in the opening and closing direction. In the graph at the center of FIG. 5, the vertical axis represents the opening and closing speed of the car door 9. In the graph at the top of FIG. 5, the vertical axis represents the opening and closing acceleration of the car door 9.

[0121] The speed pattern calculation unit 32 receives, as input information, basic opening / closing information for the car door 9, which is included in the operation data. In this example, the basic opening / closing information for the car door 9 includes the start time of the opening operation of the car door 9 and the waiting time for the car door 9 in the fully open state.

[0122] The speed pattern calculation unit 32 calculates the speed patterns of the opening and closing speeds of the car doors 9 during the opening and closing operations, respectively, using the same calculation method as for the speed pattern of the traveling speed of the car 6. Note that the speed pattern calculation unit 32 may read out model parameters, using the opening degrees when fully open and when fully closed, from the speed pattern parameter storage unit 33. Furthermore, the speed pattern calculation unit 32 calculates time-series data of the position, speed, and acceleration when the car doors 9 are opened and closed, using the waiting time in the fully open state included in the operation data as the time from when the car doors 9 are fully opened to when the closing operation starts.

[0123] FIG. 6 shows an example of the torque of the electric motor of the hoist machine 4 reproduced by the electric motor torque calculation unit 35, and the voltage and current of the electric motor of the hoist machine 4 reproduced by the electric motor current calculation unit 37. In FIG. 6, the horizontal axis of each graph represents the passage of time. In the graph in the first row from the top of the figure, the vertical axis represents the running speed of the car 6 in the up and down direction. In the graph in the second row from the top of the figure, the vertical axis represents the torque of the electric motor of the hoist machine 4. In the graph in the third row from the top of the figure, the vertical axis represents the voltage of the electric motor of the hoist machine 4. In the graph in the fourth row from the top of the figure, the vertical axis represents the current of the electric motor of the hoist machine 4. An example of reproduction of operation data for the electric motor of the hoist machine 4 will be described below, but the reproduction unit 27 may also reproduce operation data for the electric motor that opens and closes the car doors 9 in a similar manner.

[0124] The inertia calculation unit 34 reads model parameters from the torque parameter storage unit 36. The model parameters include, for example, information on the weight of the car 6 and the counterweight 7. The model parameters include, for example, information on the moment of inertia of each rotating body, such as the sheave and hoist of the hoist 4. The model parameters include, for example, information on ropes, such as the main rope 5 and compensating rope, and cables, such as control cables that supply power to the car 6 and transmit signals. The information on the ropes and cables includes information corresponding to the mass per unit length and the length of the ascending / descending stroke. These model parameters are determined according to the elevator model or specifications. The inertia calculation unit 34 may obtain the model parameters from, for example, the manufacturer 17e or the specification database 18 via the second communication network 16. At this time, the inertia calculation unit 34 may store the obtained model parameters in the torque parameter storage unit 36. Based on the read model parameters, the inertia calculation unit 34 calculates the inertia J [kgm ２ The inertia calculation unit 34 may use any known method for deriving the inertia.

[0125] The motor torque calculation unit 35 receives as input information basic car running information from the operation data. In this example, the car running basic information includes a car load β. The car load β is expressed as a ratio of the load in the car 6 to the rated load. In this example, the car load β is 0 when there is no load and 1 when the rated load is carried. The motor torque calculation unit 35 also receives as input information time-series data of the acceleration α(t), speed v(t), and position x(t) of the car 6 reproduced by the speed pattern calculation unit 32 based on the operation data. The motor torque calculation unit 35 also receives as input information the inertia J of the entire elevator calculated by the inertia calculation unit 34.

[0126] The electric motor torque calculation unit 35 reads out the model parameters from the torque parameter storage unit 36. The model parameters include, for example, the rated load L ｒａｔｅｄ[kg], roping ratio rop, sheave diameter R of the hoisting machine 4 [m], counter rate γ, gravitational acceleration g [m / sec ２ ], lifting stroke TR [m], rope unbalance torque proportional coefficient k [Nm / m], correction parameter ε [m], loss torque angular velocity proportional coefficient k ｌｏｓｓ１ , loss torque squared angular velocity proportional coefficient k ｌｏｓｓ２ , and the angular velocity independent component of the loss torque τ ｌ０ Here, the counter rate γ is 0<γ<1. In this example, the counter rate γ is set to a value close to 0.5. These model parameters are determined according to the elevator model or specifications. The motor torque calculation unit 35 may acquire the model parameters from, for example, the factory 17e or the specification database 18 via the second communication network 16. At this time, the motor torque calculation unit 35 may store the acquired model parameters in the torque parameter storage unit 36.

[0127] The motor torque calculation unit 35 uses the input information and the model parameters to calculate the time series data τ of the output torque of the motor. ｍｏｔｏｒ The time series data of the torque (t) [Nm] and the angular velocity of the motor ω(t) [rad / sec] are reproduced and calculated, for example, as follows: Note that although the calculation formulas described below are simplified, the motor torque calculator may reproduce the time series data using more rigorous calculation formulas.

[0128] The motor torque calculation unit 35 reproduces the operation data using a motion equation related to the torque output by the electric motor of the hoisting machine 4, which is expressed by the following equation (2.1). In equation (2.1), the upper sign of the compound sign is applied during ascent operation, and the lower sign of the compound sign is applied during descent operation. The angular velocity ω(t) of the electric motor is expressed by the following equation (2.2). The in-car unbalanced load torque τ ｌｏａｄ [Nm] is expressed by the following equation (2.3). Also, the rope unbalance torque τ ｒｏｐｅ [Nm] is expressed by the following equation (2.4): Rope unbalance torque τ ｒｏｐｅ depends on the position x(t) of the car 6. The rope unbalance torque τ ｒｏｐｅbecomes 0 at the intermediate position of the car 6. In addition, the loss torque τ ｌｏｓｓ [Nm] is expressed by the following equation (2.5): ｌｏｓｓ The polarity of the loss torque τ is reversed depending on the running direction of the car 6. ｌｏｓｓ The components of are expressed by the following equations (2.6) and (2.7).

[0129]

[0130]

[0131]

[0132]

[0133]

[0134]

[0135]

[0136] The electric motor power calculation unit 37 receives as input information the output torque τ of the electric motor reproduced by the electric motor torque calculation unit 35. ｍｏｔｏｒ The time series data of the angular velocity ω(t) and the angular velocity ω(t) are accepted.

[0137] The motor electrical calculation unit 37 reads out model parameters from the electrical parameter storage unit 38. The model parameters include, for example, the number of motor pole pairs p and the number of armature winding magnetic flux linkages Φ ｆ [Wb], armature winding resistance value R ａ [Ω], armature winding self-inductance L ａ [H], etc. These model parameters are determined depending on the elevator model or specifications, etc. The motor electrical calculation unit 37 may acquire the model parameters from, for example, the manufacturer 17e or the specification database 18 via the second communication network 16. At this time, the motor electrical calculation unit 37 may store the acquired model parameters in the electrical parameter storage unit 38.

[0138] The motor electrical calculation unit 37 uses the input information and model parameters to calculate the time series data i of the d-axis armature current. ｄａ(t) [A], time series data of q-axis armature current i ｑａ (t) [A], time series data of d-axis armature voltage v ｄａ (t) [V], and the time series data of the q-axis armature voltage v ｑａ (t) [V] is reproduced and calculated, for example, as follows. Note that, although an example using an equation expressed in the dq-axis coordinate system for a surface permanent magnet synchronous motor (SPMSM) will be described below, the motor electrical calculation unit 37 can also reproduce operation data for other motors, such as interior permanent magnet synchronous motors (IPMSM), induction motors (IM), and direct current motors (DCM), by using relational expressions between current and torque according to the type of motor. The motor electrical calculation unit 37 reproduces the d-axis armature voltage v ｄａ (t) and q-axis armature voltage v ｑａ The calculation and output of (t) may be omitted.

[0139] In a surface permanent magnet synchronous motor, the generated torque τ ｅ (t) [Nm] and q-axis armature current i ｑａ The relationship between the q-axis armature current i and the q-axis armature current i is expressed by the following equation (3.1). ｑａ (t) is sometimes called the torque current component.

[0140]

[0141] Here, as shown in the following equation (3.2), the generated torque τ of equation (3.1) ｅ (t), and the output torque τ reproduced by equation (2.1) ｍｏｔｏｒ (t) are considered to be equal. This gives the reproduced output torque τ ｍｏｔｏｒ Using (t), the motor electrical calculation unit 37 calculates the q-axis armature current i ｑａ (t) can be calculated using the following formula (3.3).

[0142]

[0143]

[0144] In addition, when the coordinate axis perpendicular to the q axis is the d axis, the d axis armature current i ｄａ (t) corresponds to the axis with respect to the magnetic flux. Therefore, the d-axis armature current i ｄａ(t) is a parameter that can also be used for field weakening control to suppress induced voltage information in the high speed rotation range. Therefore, the d-axis armature current i ｄａ (t) is expressed by the following equation (3.4). The motor electrical calculation unit 37 calculates the d-axis armature current i using the reproduced angular velocity ω(t) of the motor according to the relationship of equation (3.4). ｄａ (t) can be calculated.

[0145]

[0146] The motor current calculation unit 37 calculates the q-axis armature current i ｑａ (t) and d-axis armature current i ｄａ By vector-composing (t), the time series data of the motor winding current can be calculated.

[0147] In addition, the motor current calculation unit 37 calculates the q-axis armature current i ｑａ (t) and d-axis armature current i ｄａ From (t), the q-axis armature voltage v is calculated using the voltage-current equation. ｑａ (t) and d-axis armature voltage v ｄａ The voltage-current equation expressed in dq-axis rotating coordinates for the surface permanent magnet synchronous motor when the elevator car 6 is running is expressed by the following equation (3.5). ｅ (t)Φ ｆ corresponds to the electrical angular velocity electromotive force induced by the magnetic flux linkage generated by the permanent magnet, which is the field magnet that links to the armature winding.

[0148]

[0149] Here, the electric motor angular velocity ω in equation (3.5) ｅ (t) [rad / sec] is the motor angular velocity expressed in electrical angle, and is expressed by the following equation (3.6) using the mechanical angular velocity ω(t) of the motor.

[0150]

[0151] The motor electrical calculation unit 37 calculates the q-axis armature voltage v ｑａ (t) and d-axis armature voltage v ｄａBy vector-composing (t), the time series data of the motor winding voltage can be calculated.

[0152] 6 shows an example of time-series data of actual measurements of the speed of the car 6, and the torque, voltage, and current of the electric motor, and operation data reproduced by the reproduction unit 27. Using the operation model in this way, the reproduction unit 27 can reproduce and output detailed operation data.

[0153] FIG. 7 is a block diagram showing the configuration of the evaluation unit 28 according to the first embodiment.

[0154] The evaluation unit 28 includes a deterioration factor calculation unit 39 and a deterioration factor parameter storage unit 40. The deterioration factor calculation unit 39 is a unit equipped with a function for evaluating deterioration factors as, for example, time-series data including information on time changes. Model parameters in the deterioration factor model used by the deterioration factor calculation unit 39 are stored in the deterioration factor parameter storage unit 40. The deterioration factor calculation unit 39 receives, as input information, operation data reproduced from operation data from the reproduction unit 27. In this example, the reproduced operation data includes the acceleration α(t) of the car 6, the speed v(t) of the car 6, the position x(t) of the car 6, and the output torque τ of the motor. ｍｏｔｏｒ (t), motor angular velocity ω(t), d-axis armature current i ｄａ (t), q-axis armature current i ｑａ (t), d-axis armature voltage v ｄａ (t), and the q-axis armature voltage v ｑａ The deterioration factor calculation unit 39 reads out, as input information, time-series data of the operating environment, for example, from the input information storage unit 26. The evaluation unit 28 calculates the deterioration factor, for example, as follows.

[0155] When the degradation factor is, for example, time-series data on the temperature of the target device, the degradation factor calculation unit 39 reads out heat-related model parameters from the degradation factor parameter storage unit 40. The heat-related model parameters include, for example, information such as the heat capacity value and thermal resistance value of the thermal model of the device, and the heat flow rate of heat entering and leaving the device. The heat flow rate may include one or both of heat generation and cooling. The degradation factor calculation unit 39 calculates time-series data on the positive or negative temperature difference occurring between the device and the ambient temperature based on the thermal model of the device, for example, using the heat generation amount calculated based on the time-series data on the current. The degradation factor calculation unit 39 calculates the temperature time-series data of the device as a degradation factor by, for example, adding the temperature difference calculated by the thermal model to the time-series data on the ambient temperature of the device, which is the operating environment of the device.

[0156] When the deterioration factor is, for example, information about the bending of a target device in which bending fatigue may occur, the deterioration factor calculation unit 39 reads out model parameters about the bending of the device. The model parameters about the bending include, for example, shape information about the diameter of the device, such as the main rope 5, and information about the number, position, and diameter of the sheaves around which the main rope 5 is wound. The deterioration factor calculation unit 39 calculates, for example, time-series data about the position of the car 6 for each portion or a representative portion of the main rope 5, time-series data about the bending strain, etc., as a deterioration factor.

[0157] FIG. 8 is a block diagram showing the configuration of the determining unit 29 according to the first embodiment.

[0158] The determination unit 29 includes a generation unit 41, a remaining life calculation unit 42, and a life determination parameter storage unit 43. The generation unit 41 receives data on the deterioration factors evaluated by the evaluation unit 28 and generates feature data representing the characteristics of the time changes in the deterioration factors. The remaining life calculation unit 42 uses the feature data generated by the generation unit 41 to calculate the remaining life of elevator equipment based on a life model of the equipment. Model parameters of the life model are stored in the life determination parameter storage unit 43. The model parameters of the life model may include, for example, a frequency factor and activation energy in the Arrhenius equation. The model parameters of the life model may include data related to life, such as the relationship between the expected life provided by the manufacturer of the equipment and deterioration factors such as the temperature of the operating environment. The model parameters of the life model may include historical information that determines the relationship between the actual operating history of the equipment and the remaining life. The life model may be expressed in the form of a data table or a mathematical formula. The determination unit 29 determines the remaining life, for example, as follows.

[0159] First, the generation unit 41 generates feature data. The generation unit 41 receives, as input information, data on the deterioration factors evaluated by the evaluation unit 28. If the target equipment is an equipment that deteriorates according to the Arrhenius equation, the deterioration factors are, for example, time-series data on the temperature of the equipment. The generation unit 41 generates, for example, frequency distribution data as feature data of the time-series data on the temperature. The frequency distribution data is data represented, for example, by a histogram. The generation unit 41 divides the temperature into multiple classes. The generation unit 41 counts the frequency of the deterioration factor data for each of the divided classes. For example, the generation unit 41 counts, for example, the cumulative stay time in a temperature range corresponding to a divided class for the time-series data on the temperature of the equipment, as the frequency of the class. The generation unit 41 may generate the feature data collectively by batch processing on a daily or monthly basis. The generation unit 41 may also generate information such as temperature pulsation as feature data. The temperature pulsation information may be calculated by, for example, the rainflow method, or may be the fluctuation range of the maximum and minimum values ​​in each run, etc. The generation unit 41 similarly generates feature data such as a histogram or pulsation for information on deterioration factors other than temperature, such as the position of the car 6.

[0160] Next, the remaining life calculation unit 42 calculates the remaining life using the feature data. The remaining life calculation unit 42 receives the feature data generated by the generation unit 41 as input information. The remaining life calculation unit 42 reads the model parameters in the life model from the life judgment parameter storage unit 43. In this example, the remaining life calculation unit 42 receives frequency distribution data for temperature as feature data. The life model of the target device is expressed by the relationship between the expected life and temperature, for example, as shown in the following equation (4.1). Here, the life L ｎ [hr] represents the life under actual use conditions. ０ [hr] represents the lifespan under rated use, i.e., the lifespan according to the product specifications. ０ [°C] indicates the temperature during rated use. Temperature T ｎ [°C] indicates the temperature under actual use conditions.

[0161]

[0162] For example, the temperature in the k-th class of the frequency distribution is T ｎ (k) [°C], and the cumulative stay time t(k) [hr] is obtained as the feature data as the frequency of the class. The frequency distribution is calculated for the deterioration factor data of a target period u, such as one month. Here, the time label u is label information such as "March 2023" that represents the target period. The length of the target period u is expressed by the time w(u) [hr]. The temperature T of the kth class ｎ Lifetime L corresponding to (k) ｎ (k) [hr] is expressed as the following equation (4.2).

[0163]

[0164] In this case, the life consumption rate η(k) corresponding to the temperature of the kth class is expressed as the life L ｎ It is calculated as the ratio of the cumulative stay time t(k) to (k) by the following equation (4.3):

[0165]

[0166] When the total number of classes in the frequency distribution is m, the lifetime consumption H(u) of the target device in the target period u is expressed by the following equation (4.4).

[0167]

[0168] The remaining life calculation unit 42 calculates the cumulative life consumption H(u) by integrating the life consumption H(u) calculated using the formulas (4.1) to (4.4) as shown in the following formula (4.5): ｓｕｍ Here, in the formula (4.5), the lifetime consumption amount H(u) is calculated from, for example, the time when the target device starts operating. ０ The sum is calculated over each period from the target period u to the target period u.

[0169]

[0170] The remaining life calculation unit 42 calculates, for example, the cumulative life consumption H(u) for the target period u and a threshold value H ｔｈ Using the above, the cumulative life consumption rate L of the target equipment is calculated by the following formula (4.6).ｓｐａｎ (u) is calculated. ｓｐａｎ (u) is the threshold value of the life span H ｔｈ This makes it easy to understand how much life is left of the target device.

[0171]

[0172] The remaining life calculation unit 42 calculates the cumulative life consumption rate L of the target device. ｓｐａｎ The remaining life of the target device may be calculated by subtracting (u) from 1. The remaining life calculation unit 42 outputs the cumulative life consumption rate or remaining life calculated in this way.

[0173] Next, an example of the operation of the management system 1 will be described with reference to Fig. 9. Fig. 9 is a flowchart showing an example of the operation of the management system 1 according to the first embodiment.

[0174] In step S11, the collection unit 20 of the monitoring device 12 collects elevator control information and operating environment information. Then, in step S12, the first conversion unit 22 converts the collected information into operation data. Then, in step S13, the second conversion unit 23 resamples the collected operating environment information. Then, in step S14, the facility communication unit 24 determines whether the processing load of the analysis device 13 or the communication load of the first communication network 14 is high. If it is determined that the load is high, the processing of the monitoring device 12 proceeds again to step S14. On the other hand, if it is determined that the load is not high, the processing of the monitoring device 12 proceeds to step S15. In step S15, the facility communication unit 24 transmits both the operation data and the resampled operating environment data to the analysis device 13. Then, the processing of the monitoring device 12 proceeds to step S11.

[0175] In step S21, the first server-side communication unit 25 of the analysis device 13 receives both the operation data and the resampled operating environment data from the monitoring device 12. Then, in step S22, the reproduction unit 27 reproduces the operation data from the operation data based on the operation model. Then, in step S23, the evaluation unit 28 evaluates the deterioration factors of the elevator equipment based on the deterioration factor model of the equipment from the operation data and the operating environment data. Then, in step S24, the determination unit 29 evaluates the remaining life of the equipment from the deterioration factors of the elevator equipment. Then, in step S25, the life information accumulation unit 30 accumulates and stores the remaining life determination result made by the determination unit 29. The processing of the analysis device 13 then proceeds to step S21.

[0176] The monitoring device 12 may collect operation data from the elevator control device 8 or the like. At this time, the first conversion unit 22 converts the collected operation data into operation data so as to reduce the communication load through the first communication network 14. The monitoring device 12 may also collect operation data from the elevator control device 8 or the like. At this time, the monitoring device 12 may transmit the collected operation data to the analysis device 13 without converting it. The analysis device 13 reproduces the operation data from the collected operation data based on an operation model.

[0177] As described above, the management system 1 according to the first embodiment includes a first server-side communication unit 25, a reproduction unit 27, an evaluation unit 28, and a determination unit 29. The first server-side communication unit 25 acquires operation data. The operation data represents the operation status of at least one of the elevator car 6 traveling or the opening and closing of the car door 9 of the car 6. The reproduction unit 27 uses the operation data acquired by the first server-side communication unit 25 to reproduce operation data based on an elevator operation model. The operation data is data representing the operation status of the elevator, including time-series data during the operation represented by the operation data. The evaluation unit 28 uses the operation data reproduced by the reproduction unit 27 to evaluate deterioration factors that affect the deterioration of elevator equipment during the operation represented by the operation data, based on a deterioration factor model for the equipment. The determination unit 29 uses the deterioration factors of the elevator equipment evaluated by the evaluation unit 28 to determine the remaining lifespan of the equipment based on a lifespan model for the equipment.

[0178] With this configuration, even when the analysis device 13 that performs the lifespan assessment of elevator equipment uses operational data including, for example, time-series data, lighter operational data is communicated between the monitoring device 12 in the facility 2 and the analysis device 13. The analysis device 13 reproduces the operational data using the operational data, enabling lifespan assessment based on detailed operational data while minimizing communication traffic through the first communication network 14. Therefore, even when operational data cannot be directly obtained due to communication traffic restrictions, the management system 1 can more accurately determine the remaining lifespan of elevator equipment. Furthermore, the management system 1 may manage multiple elevators, ranging from thousands to tens of thousands of units. Even in this case, the management system 1 can perform practical remaining lifespan assessments that are more economical in terms of the development and maintenance of communication infrastructure and communication costs. Because the lifespan of each piece of elevator equipment can be affected by factors such as the operating environment and operating conditions, the actual lifespan of each piece of equipment may differ from its original design lifespan. Meanwhile, the management system 1, by determining the remaining lifespan of equipment while taking into account factors such as elevator operating conditions, can prevent unrealistic situations such as replacing equipment with a long remaining lifespan or reaching the end of its lifespan before replacement. Furthermore, the analysis device 13 can reproduce detailed information, such as the frequency of elevator operation, as operational data. This allows the analysis device 13 to more accurately evaluate deterioration factors, particularly temperature, and improve the accuracy of remaining lifespan determinations based on deterioration factors. Furthermore, the analysis device 13 can evaluate the lifespan of multiple elevators using similar models, such as an operation model, a deterioration factor model, and a lifespan model, making it possible to compare the conditions of other elevators with similar specifications and understand differences.

[0179] Furthermore, the operation models used by the reproduction unit 27 include a speed pattern calculation model, an inertia calculation model, an electric motor torque calculation model, and an electric motor electricity calculation model. The speed pattern calculation model is a model that calculates at least one of the speed patterns of the running of the car 6 and the opening and closing of the car doors 9, corresponding to the operation data. The inertia calculation model is a model that calculates the inertia of the elevator. The electric motor torque calculation model is a model that calculates the torque of the elevator motor, corresponding to the speed pattern calculated by the speed pattern calculation model, using the inertia calculated by the inertia calculation model. The electric motor electricity calculation model is a model that calculates at least one of the current or voltage that operates the elevator motor, corresponding to the torque calculated by the electric motor torque calculation model.

[0180] With this configuration, the management system 1 can reproduce the movement of the car 6 from the operation data, and can reproduce the electromechanical characteristics of the elevator equipment based on the reproduced movement of the car 6.

[0181] The determination unit 29 also generates feature data representing the characteristics of time changes in the deterioration factors evaluated by the evaluation unit 28 for the elevator equipment. The determination unit 29 calculates the remaining life of the equipment using the generated feature data. The determination unit 29 also generates frequency distribution data for each class of the deterioration factors as feature data. The determination unit 29 calculates the remaining life using the frequencies for each class of the deterioration factors in the frequency distribution data and the life consumption rates corresponding to the deterioration factors of each class in the life model.

[0182] With this configuration, the management system 1 can determine the remaining life more accurately by taking into account the influence of time-varying deterioration factors and the influence of previous and subsequent operations such as operation frequency.

[0183] The management system 1 also includes a lifespan information accumulation unit 30. The lifespan information accumulation unit 30 accumulates and stores information on the remaining lifespan determined by the determination unit 29.

[0184] With this configuration, the management system 1 can use the accumulated history of remaining life determination results to formulate or assist in the formulation of a maintenance plan.

[0185] Furthermore, the first server-side communication unit 25 acquires, as operation data regarding the running of the car 6, at least one of the start time of the running of the car 6 and the completion time of the running of the car 6, the departure floor of the car 6 or its position at the time of departure, the arrival floor of the car 6 or its position at the time of arrival, and loading information of the car 6. Furthermore, the first server-side communication unit 25 acquires, as operation data regarding the opening and closing of the car door 9, at least one of the start time of the opening operation of the car door 9 and the completion time of the closing operation of the car door 9, the waiting time for the car door 9 in the fully open state, and the floors on which the car door 9 is opened and closed.

[0186] With this configuration, the management system 1 can reproduce detailed operation data, including time-series data on the running of the car 6 and the opening and closing of the car doors 9, based on the minimum necessary operation data. Therefore, even when operation data cannot be directly obtained, the management system 1 can more accurately determine the remaining lifespan of the elevator equipment.

[0187] The first server-side communication unit 25 also acquires environmental data. The environmental data is data observed in the facility 2 to which the elevator is applied, and includes the temperature of the elevator's operating environment. The evaluation unit 28 evaluates the deterioration factors using the environmental data acquired by the first server-side communication unit 25.

[0188] This configuration allows the management system 1 to take into account the influence of factors external to the elevator, such as the weather, for example electronic equipment that may be affected by temperature and humidity.

[0189] In addition, the reproduction unit 27 reproduces, as operating data regarding the running of the car 6, at least one of time series data of the acceleration of the car 6, time series data of the speed of the car 6, time series data of the position of the car 6, time series data of the torque of the electric motor that runs the car 6, time series data of the angular velocity of the electric motor that runs the car 6, time series data of the current of the electric motor that runs the car 6, and time series data of the voltage of the electric motor that runs the car 6.

[0190] With this configuration, the management system 1 can reproduce detailed specific operation data including time series data on the travel of the car 6. Therefore, even when the operation data cannot be directly obtained, the management system 1 can more accurately determine the remaining lifespan of the elevator equipment.

[0191] Furthermore, a part or all of the analysis device 13 may be disposed in the facility 2 to which the elevator is applied. A part or all of the analysis device 13 may be integrated with the monitoring device 12. For example, for an elevator in which the control device 8 does not output detailed information such as operation data, the monitoring device 12 may acquire information about the elevator operation through an external sensor such as an acceleration sensor provided in the car 6. In this case, for example, the first conversion unit 22 may convert the vertical acceleration of the car 6 acquired by the acceleration sensor into operation data. This allows the management system 1 to more accurately determine the remaining lifespan of the elevator equipment even when elevator operation data cannot be obtained directly from the control device 8 due to functional limitations of the control device 8, etc.

[0192] Next, an example of the hardware configuration of the management system 1 will be described with reference to Fig. 10. Fig. 10 is a hardware configuration diagram of the main part of the management system 1 according to the first embodiment.

[0193] Each function of the management system 1 may be realized by a processing circuit. The processing circuit includes at least one processor 100 a and at least one memory 100 b. The processing circuit may include at least one dedicated hardware 200 in addition to or in place of the processor 100 a and the memory 100 b.

[0194] When the processing circuit includes a processor 100a and a memory 100b, each function of the management system 1 is realized by software, firmware, or a combination of software and firmware. At least one of the software and firmware is written as a program. The program is stored in the memory 100b. The processor 100a realizes each function of the management system 1 by reading and executing the program stored in the memory 100b.

[0195] The processor 100a is also called a CPU (Central Processing Unit), processing unit, arithmetic unit, microprocessor, microcomputer, or DSP. The memory 100b is composed of non-volatile or volatile semiconductor memory such as RAM, ROM, flash memory, EPROM, or EEPROM.

[0196] Where the processing circuitry comprises dedicated hardware 200, the processing circuitry may be implemented, for example, as a single circuit, multiple circuits, a programmed processor, parallel programmed processors, an ASIC, an FPGA, or a combination thereof.

[0197] Each function of the management system 1 can be realized by a processing circuit. Alternatively, each function of the management system 1 can be realized collectively by a processing circuit. Some of the functions of the management system 1 may be realized by dedicated hardware 200, and other parts may be realized by software or firmware. In this way, the processing circuit realizes each function of the management system 1 by dedicated hardware 200, software, firmware, or a combination of these.

[0198] The management system according to the present disclosure can be applied to elevator management.

[0199] REFERENCE SIGNS LIST 1 Management system, 2 Facility, 3 Hoistway, 4 Hoisting machine, 5 Main rope, 6 Cage, 7 Counterweight, 8 Control device, 9 Cage door, 10 Weighing device, 11 Environmental sensor, 12 Monitoring device, 13 Analysis device, 14 First communication network, 15 Server device, 16 Second communication network, 17a Head office, 17b Branch office, 17c Branch office, 17d Sales office, 17e Manufacturing plant, 18 Specification database, 19 Maintenance database, 20 Collection unit, 21 Temporary storage unit, 22 First conversion unit, 23 Second conversion unit, 24 Facility side communication unit, 25 First server side communication unit, 26 Input information storage unit, 27 Reproduction unit, 28 Evaluation unit, 29 Determination unit, 30 Life information storage unit 31 Second server side communication unit, 32 Speed ​​pattern calculation unit, 33 Speed ​​pattern parameter storage unit, 34 Inertia amount calculation unit, 35 Motor torque calculation unit, 36 Torque parameter storage unit, 37 Motor electrical calculation unit, 38 Electrical parameter storage unit, 39 Deterioration factor calculation unit, 40 Deterioration factor parameter storage unit, 41 Generation unit, 42 Remaining life calculation unit, 43 Life judgment parameter storage unit, 100a Processor, 100b Memory, 200 Dedicated hardware

Claims

1. an acquisition unit that acquires operation data representing an operation status regarding at least one of the running of an elevator car and the opening and closing of a car door of the elevator car; a reproducing unit that reproduces operation data representing an operation status of the elevator, including time-series data when performing the operation represented by the operation data, based on an operation model of the elevator, using the operation data acquired by the acquiring unit; an evaluation unit that uses the operation data reproduced by the reproduction unit to evaluate deterioration factors that affect deterioration of equipment of the elevator when the elevator operates as represented by the operation data, based on a deterioration factor model of the equipment; a determination unit that determines a remaining life of the equipment based on a life model of the equipment using the deterioration factors of the equipment of the elevator evaluated by the evaluation unit; A management system comprising:

2. The operation model used by the reproduction unit is a speed pattern calculation model that calculates a speed pattern of at least one of the running of the car or the opening and closing of the car door, corresponding to the operation data; an inertia calculation model for calculating an inertia of the elevator; an electric motor torque calculation model that calculates a torque of the electric motor of the elevator corresponding to the speed pattern calculated by the speed pattern calculation model, using the inertia calculated by the inertia calculation model; an electric motor calculation model that calculates at least one of a current and a voltage for operating the electric motor of the elevator, corresponding to the torque calculated by the electric motor torque calculation model; Including, The management system according to claim 1 .

3. the determination unit generates feature data representing features of time changes in the deterioration factors evaluated by the evaluation unit for the elevator equipment, and calculates the remaining life of the equipment using the generated feature data. The management system according to claim 1 .

4. the determination unit generates frequency distribution data for each class of deterioration factors as the feature data, and calculates the remaining life using the frequency of each class of deterioration factors in the frequency distribution data and a life consumption rate corresponding to each class of deterioration factors in the life model. The management system according to claim 3 .

5. a lifespan information storage unit that stores information on the remaining lifespan determined by the determination unit; The management system according to claim 1 , comprising:

6. The acquisition unit acquires, as the operation data regarding the travel of the car, at least one of a travel start time of the car and a travel completion time of the car, a departure floor of the car or a position at the time of departure of the car, an arrival floor of the car or a position at the time of arrival of the car, and loading information of the car. The management system according to any one of claims 1 to 4.

7. the acquisition unit acquires, as the operation data regarding the opening and closing of the car door, at least one of a start time of the opening operation of the car door and a completion time of the closing operation of the car door, a waiting time for the car door in a fully open state, and a floor on which the car door is opened or closed. The management system according to any one of claims 1 to 4.

8. the acquisition unit acquires environmental data including a temperature of an operating environment of the elevator observed in a facility to which the elevator is applied, the evaluation unit evaluates a deterioration factor using the environmental data acquired by the acquisition unit. The management system according to any one of claims 1 to 4.

9. the reproduction unit reproduces, as the operation data regarding the running of the car, at least one of time series data of the acceleration of the car, time series data of the speed of the car, time series data of the position of the car, time series data of the torque of the electric motor that runs the car, time series data of the angular velocity of the electric motor that runs the car, time series data of the current of the electric motor that runs the car, and time series data of the voltage of the electric motor that runs the car. The management system according to any one of claims 1 to 4.

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