WO2023170796A1 - Diagnosis device, diagnosis system, remote monitoring system, and maintenance system - Google Patents

Abstract

Provided are a diagnosis device, a diagnosis system, a remote monitoring system, and a maintenance system capable of determining abnormality in a bearing using a simple configuration. This diagnosis device diagnoses abnormality in a bearing in an elevator system. The elevator system comprises: a hoisting machine having a first sheave, an electric motor that rotates the first sheave by means of a rotary shaft, and a bearing that supports the rotary shaft; a second sheave; a main rope wound around the first sheave and the second sheave; and a car suspended by the main rope. The diagnosis device comprises a rotation angle calculation unit that calculates a total value of rotation angle by which the first sheave has rotated, and a determination unit that determines abnormality in the bearing on the basis of the total value of rotation angle calculated by the rotation angle calculation unit when the car ran in a specific section.

Description

Diagnostic equipment, diagnostic systems, remote monitoring systems and maintenance management systems

The present disclosure relates to a diagnostic device, a diagnostic system, a remote monitoring system, and a maintenance management system.

Patent Document 1 discloses a bearing diagnostic device. According to the diagnostic device, a detection sensor is provided in a bearing of a hoist in an elevator system. The detection sensor detects noise generated in the bearing. The diagnostic device can diagnose an abnormality in the bearing by analyzing the detected noise.

Japanese Patent No. 3742677

However, in the diagnostic device described in Patent Document 1, it is necessary to provide a detection sensor in the bearing. Therefore, the configuration becomes complicated.

The present disclosure has been made to solve the above problems. An object of the present disclosure is to provide a diagnostic device, a diagnostic system, a remote monitoring system, and a maintenance management system that can determine abnormalities in a bearing with a simple configuration.

A diagnostic device according to the present disclosure includes a hoist having a first sheave, an electric motor that rotates the first sheave on a rotating shaft, and a bearing that supports the rotating shaft; a second sheave; A diagnostic device for diagnosing an abnormality in the bearing in an elevator system having a main rope wound around a first sheave and the second sheave, and a car suspended from the main rope, A rotation angle calculation unit that calculates the total rotation angle of the car, and a rotation angle calculation unit that calculates the total rotation angle when the car travels in a specific section, and detects an abnormality in the bearing. and a determination unit that determines.

A diagnostic device according to the present disclosure includes a hoist having a first sheave, an electric motor that rotates the first sheave on a rotating shaft, and a bearing that supports the rotating shaft; a second sheave; A diagnostic device for diagnosing an abnormality in the bearing in an elevator system having a main rope wound around a first sheave and the second sheave, and a car suspended from the main rope, a rotation angle calculation unit that calculates the total rotation angle of the car; a total rotation angle calculation unit that calculates the rotation angle calculation unit when the car moves from the departure floor to the arrival floor; , learned to infer the amount of shaft displacement, which is the amount of change in the vertical position of the rotary shaft from the reference position, from the arrival floor and the loaded weight of the car when the car moves. A total of rotation angles calculated by the rotation angle calculation unit when the car moves from the departure floor to the arrival floor using a model storage unit that stores a model and the learned model stored in the model storage unit. an inference unit that infers the amount of axial displacement from the value, the departure floor, the arrival floor, and the loaded weight of the car when the car moves; and the amount of axial displacement inferred by the inference unit. and a determining unit that determines whether the bearing is abnormal based on the bearing.

A diagnostic system according to the present disclosure includes a hoisting machine including a first sheave, an electric motor that rotates the first sheave on a rotating shaft, and a bearing that supports the rotating shaft; a second sheave; A diagnostic system for diagnosing an abnormality in the bearing in an elevator system having a main rope wound around a first sheave and the second sheave, and a car suspended from the main rope, the system comprising: a rotation angle detection device that is installed at the base and transmits an angle signal corresponding to the angle at which the first sheave has rotated; and a rotation angle at which the first sheave has rotated based on the angle signal from the rotation angle detection device. and a diagnostic device that determines whether there is an abnormality in the bearing based on the total value of rotation angles calculated when the car travels in a specific section.

The remote monitoring system according to the present disclosure includes the diagnostic system, a monitoring device that receives information on a diagnosis result in which the diagnostic device of the diagnostic system determines that the bearing is abnormal, and transmits information on the diagnosis result to the outside. , equipped with.

The maintenance management system according to the present disclosure includes the diagnostic system, a monitoring device that receives information on a diagnostic result in which a diagnostic device of the diagnostic system determines that the bearing is abnormal, and transmits information on the diagnostic result to the outside; and an information center device that receives information on the diagnosis results from the monitoring device and creates a maintenance plan for the elevator system based on the information on the diagnosis results.

A maintenance management system according to the present disclosure includes a hoist having a first sheave, an electric motor that rotates the first sheave on a rotating shaft, and a bearing that supports the rotating shaft, a second sheave, In a maintenance management system for maintaining and managing an elevator system having a main rope wrapped around the first sheave and the second sheave, and a car suspended from the main rope, the car arrives from a departure floor. a rotation angle calculating section that calculates the total value of the rotation angles that the first sheave rotated when moving to the floor; a calculation unit that calculates an amount of axial displacement that is the amount of change in the vertical position from a reference position; a total value of the rotation angles calculated by the rotation angle calculation unit; and an amount of axial displacement calculated by the calculation unit; a learning information acquisition unit that acquires learning information including information in which the departure floor, the arrival floor, and the loading weight when the car is moved; and the learning information acquired by the learning information acquisition unit. Using the learning information, calculate the shaft displacement from the total value of the rotation angles calculated by the rotation angle calculating section, the departure floor, the arrival floor, and the loaded weight of the car when the car moves. A model generation unit that generates a trained model for inferring the quantity.

According to the present disclosure, the abnormality of the bearing is determined based on the total value of the rotation angle of the first sheave. Therefore, abnormalities in the bearing can be determined with a simple configuration.

1 is a diagram illustrating an overview of an elevator system to which a diagnostic device according to a first embodiment is applied. 1 is a schematic cross-sectional diagram of a hoisting machine to which a diagnostic device according to a first embodiment is applied; FIG. FIG. 2 is a schematic diagram of a cross section of a first sheave to which the diagnostic device according to the first embodiment is applied. FIG. 1 is a block diagram of a maintenance management system to which the diagnostic device according to the first embodiment is applied. FIG. 2 is a schematic diagram showing the positional relationship between a first sheave, a second sheave, and a main rope to which the diagnostic device according to the first embodiment is applied. 2 is a flowchart for explaining an overview of a diagnostic operation that the diagnostic device instructs the control panel in the first embodiment. 2 is a flowchart for explaining an overview of a first example of abnormality diagnosis performed by the diagnostic device in the first embodiment. 7 is a flowchart for explaining an overview of a second example of abnormality diagnosis performed by the diagnostic device in the first embodiment. 1 is a hardware configuration diagram of a diagnostic device in Embodiment 1. FIG. 7 is a flowchart for explaining an overview of an operation in which the diagnostic device according to the second embodiment calculates the amount of shaft displacement. FIG. 7 is a schematic cross-sectional diagram of a hoisting machine to which a diagnostic device according to a third embodiment is applied. FIG. 7 is a diagram showing an overview of temperature changes in a bearing to which a diagnostic device in Embodiment 3 is applied. FIG. 3 is a block diagram of a diagnostic device according to a third embodiment. 12 is a flowchart for explaining an overview of a third example of abnormality diagnosis performed by the diagnostic device in Embodiment 3. FIG. 7 is a block diagram of a maintenance management system to which a diagnostic device according to a fourth embodiment is applied. 12 is a flowchart for explaining an overview of learning operations performed by a learning device to which the diagnostic device in Embodiment 4 is applied. 12 is a flowchart for explaining an overview of inference operations performed by the diagnostic device in Embodiment 4.

Embodiments for carrying out the present disclosure will be described with reference to the accompanying drawings. In each figure, the same or corresponding parts are given the same reference numerals. Duplicate explanations of the relevant parts will be simplified or omitted as appropriate.

Embodiment 1.
FIG. 1 is a diagram showing an outline of an elevator system to which a diagnostic device according to the first embodiment is applied.

In the elevator system of FIG. 1, a hoistway 1 passes through each floor of a building 2. The machine room 3 is provided directly above the hoistway 1. The plurality of landings 4 are provided on each floor of the building 2. For example, the plurality of landings 4 include a landing 4a on the top floor and a landing 4b on the bottom floor.

The hoisting machine 5 is provided in the machine room 3. The hoist 5 includes an electric motor 6, a first sheave 7, a rotating shaft 8, and a plurality of bearings 9. Note that FIG. 1 shows one of the plurality of bearings 9. Note that the number of bearings 9 that the hoisting machine 5 has may be one. The electric motor 6 is provided in the machine room 3. The first sheave 7 is a pulley having a rope groove. The first sheave 7 is provided adjacent to the electric motor 6 as a driving sheave. A rotating shaft body 8 is passed through the center of the first sheave 7 . A central portion of the rotating shaft body 8 is fixed to the first sheave 7 . One end of the rotating shaft body 8 is fixed to the electric motor 6. Note that the rotating shaft body 8 may be formed integrally with the first sheave 7. The plurality of bearings 9 rotatably support the rotating shaft body 8.

The second sheave 10 is a pulley with a rope groove. The second sheave 10 is provided as a diversion wheel inside the hoistway 1, inside the machine room 3, or at a position spanning the hoistway 1 and the machine room 3. The second sheave 10 is provided at a position separated from the first sheave 7 by a distance x in the horizontal direction. The vertical position of the rotating shaft of the second sheave 10 is a distance y from the vertical position of the first sheave. The rotation axis of the second sheave 10 is parallel to the rotation axis of the first sheave 7.

The main rope 11 is wound around the first sheave 7 and the second sheave 10. For example, the main rope 11 is wrapped around the first sheave 7 and the second sheave 10 in a half-wrap manner. The wrapping angle of the main rope 11 with the first sheave 7 is θ. The wrap angle is the central angle corresponding to the arc where the sheave and rope touch. Note that the main rope 11 may be wound around the first sheave 7 and the second sheave 10 in a full wrap manner. In this case, the first sheave 7 and the main rope 11 are in contact with each other by the length of the circular arc corresponding to the central angle obtained by adding π to the wrapping angle θ.

The car 12 is suspended from one end of the main rope 11 on the first sheave 7 side inside the hoistway 1. The car 12 includes a car frame 12a, a car chamber 12b, and a weighing device 12c. The car frame 12a is suspended from the main rope 11. The car chamber 12b is supported by the car frame 12a. The weighing device 12c measures the weight inside the car chamber 12b as the loaded weight of the car 12. The counterweight 13 is suspended from the other end of the main rope 11 inside the hoistway 1 .

For example, the rotation angle detection device 14 is an encoder. The rotation angle detection device 14 is attached to the hoisting machine 5. The rotation angle detection device 14 outputs a signal according to the angle at which the rotation shaft body 8 has rotated.

The control panel 15 is provided in the machine room 3. The control panel 15 is electrically connected to the electric motor 6, the scale device 12c, and the rotation angle detection device 14. Control panel 15 may provide overall control of the elevator system. The monitoring device 16 is provided in the machine room 3. Monitoring device 16 may obtain information regarding the elevator system from control panel 15 . The monitoring device 16 can grasp the status of the elevator based on information from the control panel 15. The information center device 17 is provided at a location away from the building 2. For example, the information center device 17 is provided at an elevator system maintenance company. Information center device 17 can communicate with monitoring device 16 via a network. The information center device 17 is provided so as to be able to grasp the status of the elevator system based on information from the monitoring device 16.

The diagnostic device 20 is provided in the machine room 3. The diagnostic device 20 is electrically connected to the rotation angle detection device 14 , the control panel 15 , and the monitoring device 16 .

When the elevator system normally operates, the electric motor 6 rotates the rotating shaft 8 based on a control command from the control panel 15. The rotating shaft body 8 rotates around the rotating shaft while a vertical load is supported by a plurality of bearings 9 . The first sheave 7 rotates in synchronization with the rotating shaft body 8. The main rope 11 moves following the rotation of the first sheave 7 due to the frictional force between it and the first sheave 7. The car 12 and the counterweight 13 follow the movement of the main rope 11 and move up and down in opposite directions. The rotation angle detection device 14 transmits an angle signal every time the rotation shaft body 8 rotates by a predetermined angle. The control panel 15 operates the car 12 while measuring the position of the car 12 based on information from a plurality of sensors including the angle signal from the rotation angle detection device 14.

A diagnostic system, a remote monitoring system, and a maintenance management system are applied to the elevator system in order to keep the bearing 9 in a healthy condition. The diagnostic system includes a rotation angle detection device 14 and a diagnostic device 20. The remote monitoring system also includes a diagnostic system and a monitoring device 16. The maintenance management system includes a remote monitoring system and an information center device 17.

Various abnormalities may occur in each of the plurality of bearings 9 as the car 12 operates. For example, the internal shape of the bearing 9 may change due to wear. For example, the rotating shaft body 8 and the bearing 9 may increase in temperature due to frictional heat and may expand. At this time, as the rotating shaft 8 thermally expands in the rotating shaft direction, a load is generated between the rotating shaft 8 and the bearing 9 in the rotating shaft direction, which may cause positional deviation or the like. In this way, the load on the bearing 9 increases with expansion. The applied load can shorten the life of the bearing 9. The various abnormalities can be detected by the position of the rotating shaft body 8 in the vertical direction. That is, if the inside of the bearing 9 is worn out, the vertical position of the rotating shaft body 8 may become lower than the reference position. When the rotating shaft body 8 and the bearing 9 thermally expand, the vertical position of the rotating shaft body 8 may become higher than the reference position.

The diagnostic device 20 diagnoses an abnormality in the bearing 9 based on the angle signal from the rotation angle detection device 14. Specifically, the diagnostic device 20 calculates the total value of rotation angles, which is the amount of rotation of the rotating shaft body 8, based on the angle signal. For example, the diagnostic device 20 determines the wrapping angle θ based on the total rotation angle of the rotary shaft body 8 calculated when the car 12 moves from the top floor to the bottom floor in a specific section without stopping. Calculate the value of The diagnostic device 20 utilizes the fact that the vertical position of the rotating shaft body 8 can be estimated from the value of the wrapping angle θ, and diagnoses an abnormality in the bearing 9 based on the value of the wrapping angle θ. At this time, the diagnostic device 20 performs abnormality diagnosis, such as the presence or absence of an abnormality, the type of abnormality, and the degree of abnormality.

The diagnostic device 20 transmits diagnostic information indicating the result of the abnormality diagnosis to the monitoring device 16. The monitoring device 16 transmits diagnostic information to the information center device 17. The information center device 17 uses the received diagnostic information for maintenance management. Specifically, when the information center device 17 receives diagnostic information indicating that there is an abnormality, it notifies personnel of the maintenance company, such as workers, monitors, and operators, to that effect. Based on the diagnostic information, the information center device 17 estimates the life of the bearing 9 corresponding to the diagnostic information. The information center device 17 creates a maintenance plan including a replacement plan for the bearing 9 based on the estimated lifespan, and notifies maintenance company workers and the like of the maintenance plan.

Next, the hoisting machine 5 will be explained using FIGS. 2 and 3.

FIG. 2 is a schematic cross-sectional view of a hoisting machine to which the diagnostic device according to the first embodiment is applied. FIG. 3 is a schematic diagram of a main part of a cross section of the first sheave to which the diagnostic device according to the first embodiment is applied.

FIG. 2 shows a cross section of the hoist 5 including the first sheave 7 and the rotation axis A of the rotation shaft body 8. For example, the hoist 5 has two bearings 9. Two bearings 9 are arranged on both sides of the first sheave 7, respectively.

A rolling bearing is adopted as the bearing 9. Specifically, for example, the bearing 9 includes common types such as deep groove ball bearings, self-aligning ball bearings, angular contact ball bearings, spherical roller bearings, tapered roller bearings, cylindrical roller bearings, toroidal roller bearings, etc. bearings are adopted. For example, as an example of the bearing 9, a bearing having a gap and a contact angle between an internal rolling element and a moving surface is adopted. Note that the bearing 9 may be a sliding bearing that has an alignment effect.

FIG. 3 shows the main part of the cross section of the first sheave 7 including the rotation axis A. In FIG. 3, the first sheave 7 is shown with the main rope 11 wrapped around it. The first sheave 7 has a plurality of rope grooves 7a. In FIG. 3, one of the plurality of rope grooves 7a is shown. In this embodiment, since the rope groove 7a is provided with an undercut groove, the main rope 11 is not in contact with the bottom of the rope groove 7a. The bottom portion 7b is a portion that can be regarded as the bottom of the rope groove 7a, assuming that no undercut groove is provided. The sheave diameter D is the diameter of a portion of the sheave that is considered to be the bottom of the rope groove 7a.

The rope diameter d is the diameter of the main rope 11. The effective diameter De of the first sheave 7 is the sum of the sheave diameter D and the rope diameter d. That is, the effective diameter De=D+d/2+d/2=D+d. The effective radius Re of the first sheave 7 is calculated as De/2, which is half the effective diameter De. The effective radius Re is the distance from the rotation axis A to the center of the main rope 11 wound around the first sheave 7. That is, the effective radius Re may be calculated by adding up a half value of the sheave diameter D and a half value of the rope diameter d.

Next, the diagnostic device 20 will be explained using FIG. 4.
FIG. 4 is a block diagram of a maintenance management system to which the diagnostic device according to the first embodiment is applied. Note that illustration of the hoist 5 and the car 12 is omitted in FIG. 4 .

As shown in FIG. 4, the diagnostic device 20 includes a storage section 21, a communication section 22, a diagnostic driving command section 23, a rotation angle calculation section 24, a calculation section 25, and a determination section 26.

The storage unit 21 stores numerical information necessary for diagnostic operation of the bearing 9. The numerical values stored in the storage unit 21 may be updated at any timing. For example, when the sheave diameter D of the first sheave 7 is measured during inspection, the sheave diameter D stored in the storage unit 21 may be updated to the latest value. For example, when the rope diameter d of the main rope 11 is measured by inspection or update, the rope diameter d stored in the storage unit 21 may be updated to the latest value.

The communication unit 22 controls communication between the diagnostic device 20 and external equipment. Specifically, the communication unit 22 receives information from the scale device 12c, the rotation angle detection device 14, and the control panel 15. The communication unit 22 can transmit information to the control panel 15 and the monitoring device 16.

The diagnostic operation command unit 23 creates a command to perform a diagnostic operation and sends it to the control panel 15. The diagnostic operation is an operation in which the car 12 travels between the top floor and the bottom floor without stopping. The diagnostic operation may be an operation in which the car 12 is moved back and forth between the top floor and the bottom floor.

The diagnostic operation command unit 23 acquires information on the loaded weight measured by the weighing device 12c. The diagnostic operation command unit 23 detects, based on the loaded weight of the car 12, that the car 12 is in a no-load state, which is a state in which there are no people or objects present. For example, when the diagnostic driving command unit 23 detects a no-load state as one of the conditions for performing the diagnostic driving, it transmits a command to the control panel 15 to perform the diagnostic driving. Note that the diagnostic driving command unit 23 may transmit a command to perform diagnostic driving even when the vehicle is not in a no-load state.

The rotation angle calculation unit 24 calculates the rotation angle of the rotation shaft body 8 based on the angle signal from the rotation angle detection device 14. The rotation angle calculation unit 24 calculates the total value of rotation angles, which is the amount of rotation when the car 12 travels in a specific section. Specifically, for example, when the car 12 performs a diagnostic operation, the rotation angle calculation unit 24 calculates the total value of rotation angles when the car 12 travels in the section from the top floor to the bottom floor.

The calculation unit 25 calculates the amount of shaft displacement, which is the amount of change in the position of the rotating shaft body 8 in the vertical direction, based on the total value of the rotation angles calculated by the rotation angle calculation unit 24. The amount of shaft displacement is the difference in the vertical direction between the position of the rotating shaft 8 calculated from the total value of rotation angles and the position of the rotating shaft 8 serving as a reference. That is, the calculation unit 25 calculates the shaft position, which is the vertical position of the rotating shaft 8, based on the total value of the rotation angles. At this time, the calculation unit 25 calculates the vertical position of the rotation axis A as the shaft position.

When calculating the shaft body position, the calculation unit 25 first calculates the wrap angle θ based on the angle signal. The calculation unit 25 calculates the shaft position based on the calculated wrap angle θ.

The determination unit 26 determines the abnormality of the bearing 9 using several forms of abnormality diagnosis. For example, when the determination unit 26 performs an abnormality diagnosis, the determination unit 26 causes the communication unit 22 to transmit information on the degree of abnormality indicating the result of the abnormality diagnosis to the monitoring device 16 . The abnormality degree information includes information indicating that an abnormality exists or does not exist in the bearing 9. The information on the degree of abnormality may include information indicating the type of abnormality present in the bearing 9. The information on the degree of abnormality may include information quantitatively indicating the degree of abnormality existing in the bearing 9.

Note that the determination unit 26 may calculate the degree of abnormality before determining the abnormality, and determine whether the bearing 9 is abnormal based on the degree of abnormality.

In the first example of abnormality diagnosis, the determination unit 26 determines whether the bearing 9 is abnormal based on the total value of the rotation angles calculated by the rotation angle detection device 14. At this time, the determining unit 26 determines whether the bearing 9 is abnormal based on the total value of rotation angles when the car 12 travels in a specific section under prescribed conditions such as a no-load state. For example, if the absolute value of the difference between the total value of rotation angles and the total value of reference rotation angles corresponding to the specified condition exceeds a specified threshold value, the determination unit 26 determines that there is an abnormality in the bearing 9. do. The total value of the reference rotation angles is stored in the storage unit 21 in advance. Note that the total value of the reference rotation angles may be updated in the information stored in the storage unit 21 based on the measured value during maintenance work.

In the second example of abnormality diagnosis, the determination unit 26 determines whether the bearing 9 is abnormal based on the amount of shaft displacement that is the calculation result of the calculation unit 25. For example, the determination unit 26 determines that an abnormality exists in the bearing 9 when the absolute value of the difference between the amount of shaft displacement calculated by the calculation unit 25 and the reference amount of shaft displacement exceeds a prescribed threshold value. Further, the determining unit 26 determines whether there is a shape change inside the bearing 9, based on the value of the difference between the amount of shaft displacement calculated by the calculation unit 25 and the reference amount of shaft displacement. It is determined whether there is an abnormality, such as whether the bearing 9 is expanding or whether there is a positional shift in the bearing 9. The value of the reference axial displacement amount is stored in the storage unit 21 in advance.

In the third example of abnormality diagnosis, the determining unit 26 determines that the rotating shaft body 8 and the bearing 9 expand, and that the inner ring and outer ring of the bearing 9 are aligned in the direction of the rotating shaft based on the amount of shaft displacement that is the calculation result of the calculating unit 25. The value of the load applied to the bearing 9 due to positional displacement etc. is calculated. This calculation is performed based on the fact that there is a positive correlation between the amount of expansion of the rotating shaft body 8, the increase in the amount of shaft displacement in the vertical direction corresponding to the amount of expansion of the bearing 9, and the applied load. The determination unit 26 determines whether the bearing 9 is abnormal based on the calculated load. For example, the determination unit 26 determines that an abnormality exists in the bearing 9 when the absolute value of the difference between the calculated applied load value and the reference applied load value exceeds a prescribed threshold value. The reference load value is stored in the storage unit 21 in advance.

Next, the principle by which the amount of shaft displacement is calculated from the total value of rotation angles will be explained using FIG.
FIG. 5 is a schematic diagram showing the positional relationship between the first sheave, the second sheave, and the main rope to which the diagnostic device according to the first embodiment is applied. Note that illustration of the bearing 9 and the diagnostic device 20 is omitted in FIG.

FIG. 5 shows the change in the position of the main rope 11 when the vertical position of the first sheave 7 changes. The first sheave 7 in the standard state immediately after the bearing 9 has been replaced and the main rope 11 at that time are indicated by broken lines. The first sheave 7 and the main rope 11 in a state where the bearing 9 is worn out are shown by dashed lines. The first sheave 7 with the rotating shaft 8 and bearing 9 in an expanded state and the main rope 11 at that time are shown by two-dot chain lines.

The distance x is the distance in the horizontal direction from the rotation axis of the second sheave 10 to the rotation axis of the first sheave 7. Even if there is an abnormality in the bearing 9, the distance x can be considered constant.

The distance y is the vertical position of the first sheave 7 based on the vertical height position of the rotating shaft of the second sheave 10. In the reference state, the distance y is written as _y0 . In a worn state of the bearing 9, the distance y is written as y ₁ . y ₁ is smaller than y ₀ . In the state where the rotating shaft body 8 and the bearing 9 are expanded, the distance y is described as _y2 . _y2 is greater than _y0 .

The wrap angle θ is a central angle corresponding to the arc where the first sheave 7 and the main rope 11 touch in the half-wrap method. Although not shown, the wrapping angle θ is described as θ ₀ in the standard state. When the bearing 9 is in a worn state, the wrap angle θ is written as θ ₁ . θ ₁ is smaller than θ ₀ . When the bearing 9 is in an expanded state, the wrap angle θ is written as θ ₂ . θ ₂ is greater than θ ₀ .

The axial displacement amount h is the value obtained by subtracting _y0 from the distance y in a certain state. The amount of shaft displacement h ₁ when the bearing 9 is worn is y ₁ −y ₀ . Note that h ₁ is a negative value, but in FIG. 5, the absolute value of h ₁ is shown for convenience of illustration. The shaft displacement amount h ₂ when the bearing 9 is expanded is y ₂ -y ₀ .

Based on the geometrical relationship shown in FIG. 5, the wrapping angle θ and the distances x and y satisfy the following equation (1).

In formula (1), i is a constant that changes depending on the winding method. In the case of half wrap, i=0. In the case of full wrap, i=1.

By transforming Equation (1), the following Equation (2) that represents the relationship between the amount of shaft displacement h and the wrapping angle θ is derived.

Since the value of the distance x and the value of the wrapping method i are determined by the elevator system, according to equation (2), the axial displacement amount h can be calculated based on the wrapping angle θ.

Next, the principle by which the wrapping angle θ is derived based on the total value of rotation angles will be explained.

When the wrapping angle θ changes, the traction capacity Γ of the first sheave 7 changes based on the following equation (3).

In formula (3), μ is the friction coefficient between the main rope 11 and the rope groove 7a. K is a groove coefficient corresponding to the shape of the rope groove 7a. When the traction capacity Γ changes, the amount of slippage by which the main rope 11 moves relative to the rope groove 7a when the car 12 moves changes. Since the amount of slip changes, the amount of rotation of the first sheave 7 relative to the amount of movement of the car 12 changes. That is, the total value of the rotation angles of the first sheave 7 when the car 12 travels in the same section changes depending on the value of the wrap angle θ. Further, even if the car 12 moves the same distance, the relationship between the wrap angle θ and the slip amount changes if the conditions of upward operation or downward operation are different.

The relationship between the total value Θ _up of the rotation angle of the first sheave 7 and the wrap angle θ when the car 12 runs upward in a specific section is expressed by the following equation (4).

In equation (4), _C1 is a coefficient expressing the amount of slip during upward operation. C ₁ changes depending on the tension of the main rope 11. That is, C ₁ is a function of the value of the loaded weight of the car 12. The value of r is a constant determined depending on the roping method of the elevator system. That is, the value of r differs depending on the method such as 1:1 roping, 2:1 roping, etc. X is the distance that the car 12 has moved. Re is the effective radius of the first sheave 7.

The relationship between the total value Θ _dn of the rotation angle of the first sheave 7 and the wrap angle θ when the car 12 runs downward in a specific section is expressed by the following equation (5).

In equation (5), _C2 is a coefficient expressing the amount of slip during descending operation. _C2 changes depending on the tension of the main rope 11. That is, C ₂ is a function of the value of the car 12's loaded weight. _C3 is a coefficient expressing the amount of elongation of the rope. C ₃ is a function of the value of the car 12's loaded weight.

In the diagnostic device 20, the storage unit 21 stores the values of constants i, x, y ₀ , r, X, Re, C ₁ , C ₂ , and C ₃ included in equations (1) to (5). . At this time, the storage unit 21 stores the latest values of each constant corresponding to the hoisting machine 5. Here, the moving distance X of the car 12 is stored in association with a specific section. Note that the diagnostic device 20 may obtain from the control panel 15 a measured value of the distance traveled during the diagnostic operation as the travel distance X.

When performing an abnormality diagnosis, the rotation angle calculation unit 24 calculates the total value Θ _up or Θ _dn of the rotation angle of the first sheave 7 in accordance with the operation of the car 12.

In the second and third examples of abnormality diagnosis, the calculation unit 25 uses the constants and functions stored in the storage unit 21 and the total rotation angle calculated by the rotation angle calculation unit 24 to calculate the equation (4). ) or formula (5), the wrap angle θ corresponding to the total value of the rotation angles is calculated. The calculation unit 25 calculates the shaft displacement amount h based on equation (2) using the coefficients stored in the storage unit 21 and the calculated wrap angle θ.

In the first example of the abnormality diagnosis, the determination unit 26 determines whether the bearing 9 is abnormal based on the total value Θ _up or Θ _dn of the rotation angles calculated by the rotation angle calculation unit 24 . The reason why _{it is} possible to determine whether there is an abnormality in the bearing 9 from the total value of the rotation angle is that if the _coefficients This is because it becomes a value.

In the second example of abnormality diagnosis, the determining unit 26 determines whether the bearing 9 is abnormal based on the shaft displacement amount h calculated by the calculating unit 25.

In the third example of abnormality diagnosis, the determination unit 26 calculates the value of the load generated in the bearing 9 based on the shaft displacement amount h calculated by the calculation unit 25. For example, when the bearing 9 is a rolling bearing, the expansion of the rotating shaft body 8 causes the positions of the inner ring and outer ring of the bearing 9 to shift in the rotating shaft direction. With this positional shift, the contact angle of the rolling elements changes, and the rotating shaft body 8 becomes tensed, thereby increasing the load applied to the rolling elements. The load generated on the bearing 9 due to positional changes, elastic deformation, etc. of the rolling elements is expressed as a load value. The determination unit 26 calculates the value of the applied load by applying the axial displacement amount h to the function for calculating the applied load stored in the storage unit 21. Here, the function for calculating the applied load is a function of the shaft displacement amount h. The determination unit 26 determines whether the bearing 9 is abnormal based on the value of the applied load. For example, the determining unit 26 determines that there is an abnormality in the bearing 9 in which the value of the applied load increases by comparing it with the reference applied load. Note that the determination unit 26 may quantitatively reflect the influence of the load on the bearing 9 in the value of the degree of abnormality.

Next, an example of diagnostic operation will be explained using FIG. 6.
FIG. 6 is a flowchart for explaining the outline of the diagnostic operation that the diagnostic device instructs the control panel in the first embodiment.

In the flowchart shown in FIG. 6, the specific section in the diagnostic operation is the section from the top floor landing 4a to the bottom floor landing 4b. In the abnormality diagnosis, the longer the distance that the car 12 travels without stopping, the closer the calculated value of the wrap angle θ becomes to the value of the actual wrap angle. Therefore, the specific section may be selected from the top floor to the bottom floor.

For example, the diagnostic device 20 starts the operation of the flowchart after confirming that no person or object is loaded in the car 12 using information from the weighing device 12c.

In step S001, the diagnostic device 20 transmits a command to the control panel 15 to perform a diagnostic operation. The control panel 15 starts diagnostic operation.

After that, the operation of step S002 is performed. In step S002, the car 12 moves from the current landing 4 to the bottom floor landing 4b.

After that, the operation of step S003 is performed. In step S003, the car 12 moves to the landing 4a on the top floor without stopping. The transition of the moving speed during the diagnostic operation of the flowchart is similar to the transition of the moving speed of the car during the diagnostic operation of a general elevator system. The car 12 arrives at the landing 4a on the top floor. The diagnostic device 20 calculates the total value Θ _up of the rotation angles by which the rotary shaft body 8 rotated during the upward operation of the car 12 in step S003.

After that, the operation of step S004 is performed. In step S004, the car 12 moves to the lowest floor landing 4b without stopping. The car 12 arrives at the landing 4b on the lowest floor. The diagnostic device 20 calculates the total value Θ _dn of the rotation angles by which the rotary shaft body 8 rotated during the downward operation of the car 12 in step S004.

After that, the operation of step S005 is performed. In step S005, the diagnostic device 20 uses the calculated rotation angle total values Θ _up and Θ _dn to determine an abnormality in the bearing 9 as an abnormality diagnosis. At this time, the diagnostic device 20 determines whether the bearing 9 is abnormal using the average value of the total rotation angle values Θ _up and Θ _dn . Note that the diagnostic device 20 may determine whether the bearing 9 is abnormal using at least one of the rotation angle total values Θ _up and Θ _dn .

After that, the diagnostic device 20 ends the operation of the flowchart.

Next, a first example of abnormality diagnosis will be described using FIG. 7.
FIG. 7 is a flowchart for explaining an overview of a first example of abnormality diagnosis performed by the diagnostic apparatus in the first embodiment.

For example, the diagnostic device 20 starts the abnormality diagnosis shown in FIG. 7 after the diagnostic operation. Note that, even if the diagnostic device 20 does not perform the diagnostic operation, if it detects that the car 12 has moved through a specific section, it may perform the abnormality diagnosis.

In step S101, the diagnostic device 20 detects that the car 12 has moved in a specific section.

After that, the operation of step S102 is performed. In step S102, the diagnostic device 20 detects that the first sheave 7 has stopped based on information such as the angle signal from the rotation angle detection device 14.

After that, the operation of step S103 is performed. In step S103, the rotation angle calculation unit 24 of the diagnostic device 20 calculates the total value Θ _i of rotation angles caused by the movement of the car 12 in a specific section. Note that Θ _i is calculated from at least one of Θ _up and Θ _dn .

After that, the operation of step S104 is performed. In step S104, the determining unit 26 of the diagnostic device 20 determines whether the absolute value of the difference between the calculated total value Θ _i of rotation angles and the reference total value Θ ₀ of rotation angles exceeds a threshold value. That is, it is determined whether "|Θ ₀ -Θ _i |>threshold".

In step S104, if "|Θ ₀ - Θ _i |>threshold" is not satisfied, the operation in step S105 is performed. In step S105, the determination unit 26 determines that there is no abnormality in the bearing 9, that is, it is normal. The determination unit 26 creates information on the degree of abnormality including the fact that there is no abnormality and the value of "|Θ ₀ -Θ _i |" as information on the diagnosis result. The diagnostic device 20 transmits information on the diagnostic results to the monitoring device 16. The diagnostic device 20 ends the abnormality diagnosis.

In step S104, if "|Θ ₀ −Θ _i |>threshold", the operation in step S106 is performed. In step S106, the determination unit 26 determines that there is an abnormality in the bearing 9. The determination unit 26 creates information on the degree of abnormality including the fact that there is an abnormality and the value of "|Θ ₀ −Θ _i |" as information on the diagnosis result. The diagnostic device 20 transmits information on the diagnostic results to the monitoring device 16. The diagnostic device 20 ends the abnormality diagnosis.

After the operation of step S105 or step S106 is performed, the operation of step S107 is performed. In step S107, the monitoring device 16 transmits information on the diagnosis result to the information center device 17. The information center device 17 displays information on the diagnosis results to maintenance company workers and the like. The information center device 17 creates a maintenance inspection plan for the elevator system based on the information of the diagnosis results.

After that, the operation of the flowchart ends.

Next, a second example of abnormality diagnosis will be described using FIG. 8.
FIG. 8 is a flowchart for explaining an overview of a second example of abnormality diagnosis performed by the diagnostic apparatus in the first embodiment.

For example, the diagnostic device 20 starts the abnormality diagnosis shown in FIG. 8 after the diagnostic operation. Note that, even if the diagnostic device 20 does not perform the diagnostic operation, if it detects that the car 12 has moved through a specific section, it may perform the abnormality diagnosis.

The operations performed from step S201 to step S203 are the same as the operations performed from step S101 to step S103 in the flowchart of FIG.

After the operation in step S203 is performed, the operation in step S204 is performed. In step S204, the calculation unit 25 of the diagnostic device 20 calculates the axial displacement amount h _i based on the total rotation angle value Θ _i calculated in step S203.

After that, the operation of step S205 is performed. In step S205, the determination unit 26 of the diagnostic device 20 determines whether the absolute value of the difference between the calculated shaft displacement amount hi and the reference shaft displacement amount _h0 exceeds a threshold value. That is, it is determined whether "|h ₀ -h _i |>threshold".

In step S205, if "|h ₀ -h _i |>threshold" is not satisfied, the operation in step S206 is performed. In step S206, the determination unit 26 determines that there is no abnormality in the bearing 9, that is, it is normal. The determination unit 26 creates information on the degree of abnormality including the fact that there is no abnormality and the value of "|h ₀ - _{h i} |" as information on the diagnosis result. The diagnostic device 20 transmits information on the diagnostic results to the monitoring device 16. The diagnostic device 20 ends the abnormality diagnosis.

In step S205, if "|h ₀ -h _i |>threshold", the operation in step S207 is performed. In step S207, the determining unit 26 determines that there is an abnormality in the bearing 9. The determination unit 26 creates abnormality degree information including the fact that there is an abnormality and the value of "|h ₀ -h _i |" as diagnostic result information. The diagnostic device 20 transmits information on the diagnostic results to the monitoring device 16. The diagnostic device 20 ends the abnormality diagnosis.

After the operation of step S206 or the operation of step S207 is performed, the operation of step S208 is performed. In step S208, the monitoring device 16 transmits information on the diagnosis result to the information center device 17. The information center device 17 displays information on the diagnosis results to the maintenance company workers. The information center device 17 creates a maintenance inspection plan for the elevator system based on the information of the diagnosis results.

After that, the operation of the flowchart ends.

In addition, in step S207, the determination unit 26 determines that the abnormality in the bearing 9 is due to an internal shape change or thermal expansion of the rotating shaft body 8 and the bearing 9, based on the difference between the value of h _i and the value of h ₀ . It may be determined that For example, when the difference between the value of h _i and the value of h ₀ becomes a negative value, the determination unit 26 may determine that an internal shape change has occurred in the bearing 9. When the difference between the value of h _i and the value of h ₀ is a positive value, the determination unit 26 may determine that thermal expansion is occurring in the rotating shaft body 8 and the bearing 9.

Note that in step S206 and step S207, the determination unit 26 may create abnormality degree information including the difference between the value of h _i and the value of h ₀ . In this case, in step S208, the information center device 17 may analyze the transition of the difference. Specifically, the information center device 17 may analyze that the wear of the bearing 9 is progressing based on the trend that the difference is a negative value and is decreasing.

The third example of abnormality diagnosis is similar to that shown in FIG. 8 except that the determination unit 26 calculates the applied load and the determination unit 26 determines the abnormality of the bearing 9 based on the applied load. Almost the same operation as in the flowchart is performed.

According to the first embodiment described above, the diagnostic device 20 includes the rotation angle calculation section 24 and the determination section 26. The diagnostic device 20 determines whether there is an abnormality in the bearing 9 based on the total value of the rotation angles of the first sheave 7 calculated when the car 12 travels in a specific section. A device that outputs an angle signal indicating the rotation angle of the first sheave 7 is provided in a general elevator system. Therefore, an abnormality in the bearing 9 can be determined with a simple configuration without attaching an additional device to the hoisting machine 5.

The diagnostic system also includes a rotation angle detection device 14 and a diagnostic device 20. In the diagnostic system, an abnormality in the bearing 9 is determined based on information on the total value of the rotation angles of the first sheave 7. Therefore, an abnormality in the bearing 9 can be determined with a simple configuration.

Additionally, the remote monitoring system includes a diagnostic system and a monitoring device 16. The monitoring device 16 can transmit information indicating the diagnosis result of the diagnostic device 20 to the outside. Therefore, abnormalities in the bearing 9 can be transmitted to the outside.

The maintenance management system also includes a diagnostic system, a monitoring device 16, and an information center device 17. The information center device 17 creates a maintenance plan based on the diagnosis results of the diagnostic device 20. Therefore, it is possible to diagnose an abnormality in the bearing 9 from a remote location and create a plan for replacement or the like based on the diagnosis result. As a result, the labor required for inspection can be reduced.

The diagnostic device 20 also includes a calculation section 25. The diagnostic device 20 calculates the amount of shaft displacement and determines whether the bearing 9 is abnormal based on the amount of shaft displacement. Therefore, abnormalities caused by changes in the shape of the bearing 9 can be determined. As a result, the accuracy of abnormality diagnosis can be improved.

Furthermore, the diagnostic device 20 calculates the wrapping angle θ of the main rope 11 with respect to the first sheave 7, and calculates the amount of shaft displacement based on the wrapping angle θ. At this time, the diagnostic device 20 calculates the value of the shaft displacement amount h based on equation (2). Therefore, the amount of axial displacement can be calculated based on the geometric relationship of the configuration in the elevator system.

Furthermore, the diagnostic device 20 calculates the value of the wrap angle θ using equations (4) and (5). Therefore, the amount of shaft displacement can be calculated based on the actual traction capacity.

Furthermore, the diagnostic device 20 determines that there is an abnormality in which the internal shape of the bearing 9 is changing based on the amount of shaft displacement. For example, the internal shape of the bearing 9 may be caused by wear, damage, etc. Therefore, the type of abnormality in the bearing 9 can be determined.

Furthermore, the diagnostic device 20 calculates the value of the load generated on the bearing 9. The diagnostic device 20 determines that there is an abnormality in which the applied load value is increasing. Therefore, the type of abnormality in the bearing 9 can be determined. In particular, an increase in the load value is a phenomenon that shortens the life of the bearing 9, but it is not a direct abnormality such as wear of the bearing 9, and is difficult to inspect. Diagnostic device 20 is capable of determining such types of abnormalities.

Furthermore, the diagnostic device 20 determines the type of abnormality in the bearing 9 based on the difference between the calculated amount of shaft displacement and the reference value of the amount of shaft displacement. Note that the reference value for the amount of shaft displacement may be set arbitrarily. For example, the amount of shaft displacement calculated immediately after inspection by a worker may be set as the reference value of the amount of shaft displacement. Therefore, the accuracy of determining the type of abnormality can be improved.

Further, the diagnostic device 20 is based on the total value of rotation angles calculated when the car 12 is operated back and forth between the top floor and the bottom floor without stopping as a specific section, that is, when the car 12 is operated up and down. Then, the abnormality of the bearing 9 is determined. An abnormality in the bearing 9 is determined based on an estimation of the amount of slippage between the main rope 11 and the first sheave 7. By using the total value of rotation angles when the car 12 operates from the top floor to the bottom floor without stopping, the accuracy of abnormality diagnosis of the bearing 9 can be improved.

Furthermore, the diagnostic device 20 further includes a diagnostic driving command section 23. The diagnostic device 20 causes the control panel 15 to perform a diagnostic operation when detecting a no-load state in which no object exists inside the car 12. The amount of slip between the main rope 11 and the first sheave 7 is affected by the loaded weight of the car 12. By performing a diagnostic operation, the diagnostic device 20 can perform an abnormality diagnosis under conditions that exclude uncertain factors such as usage status by the user. As a result, the accuracy of abnormality diagnosis can be improved.

Note that the value stored in the storage unit 21 may be updated at any timing. For example, each reference value stored in the storage unit 21 may be updated. For example, the information center device 17 may transmit the updated reference value information to the diagnostic device 20 via the monitoring device 16. In this case, the diagnostic device 20 causes the storage unit 21 to newly store the updated reference value.

Note that the determination unit 26 may create information on the degree of abnormality and determine whether the bearing 9 is abnormal based on the degree of abnormality. Specifically, in the first example of the abnormality diagnosis, the determination unit 26 may create information on the degree of abnormality based on the total value of the rotation angles. The degree of abnormality may include an abnormality determination value corresponding to the total value of rotation angles. In the second example of abnormality diagnosis, the determination unit 26 may create information on the degree of abnormality based on the amount of shaft displacement. The degree of abnormality may include an abnormality determination value corresponding to the value of the amount of shaft displacement. In the third example of abnormality diagnosis, the determination unit 26 may create information on the degree of abnormality based on the applied load. The degree of abnormality may include an abnormality determination value corresponding to the value of applied load. In either example, the determination unit 26 may determine that the bearing 9 is abnormal when the abnormality determination value of the degree of abnormality exceeds a prescribed threshold value.

Note that the diagnostic device 20 may be applied to an elevator system without a machine room or an elevator system in which a machine room is provided at the bottom of the hoistway. At this time, the formula used when calculating the amount of shaft displacement from the total value of rotation angles may be appropriately selected based on the positional relationship between the first sheave, the second sheave, and the main rope. Further, in this case, the diagnostic device 20 and the monitoring device 16 may be provided inside the hoistway.

Next, an example of hardware constituting the diagnostic device 20 will be described using FIG. 9.
FIG. 9 is a hardware configuration diagram of the diagnostic device in the first embodiment.

Each function of the diagnostic device 20 can be realized by a processing circuit. For example, the processing circuit includes at least one processor 100a and at least one memory 100b. For example, the processing circuitry includes at least one dedicated hardware 200.

When the processing circuit includes at least one processor 100a and at least one memory 100b, each function of the diagnostic device 20 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. At least one of software and firmware is stored in at least one memory 100b. At least one processor 100a realizes each function of the diagnostic device 20 by reading and executing a program stored in at least one memory 100b. At least one processor 100a is also referred to as a central processing unit, processing unit, arithmetic unit, microprocessor, microcomputer, or DSP. For example, the at least one memory 100b is a non-volatile or volatile semiconductor memory such as RAM, ROM, flash memory, EPROM, EEPROM, etc., a magnetic disk, a flexible disk, an optical disk, a compact disk, a mini disk, a DVD, etc.

If the processing circuitry comprises at least one dedicated hardware 200, the processing circuitry may be implemented, for example, in a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC, an FPGA, or a combination thereof. Ru. For example, each function of the diagnostic device 20 is realized by a processing circuit. For example, each function of the diagnostic device 20 is realized by a processing circuit.

Regarding each function of the diagnostic device 20, some parts may be realized by dedicated hardware 200, and other parts may be realized by software or firmware. For example, the function of calculating the total value of rotation angles is realized by a processing circuit as dedicated hardware 200, and the functions other than the function of calculating the total value of rotation angles are realized by at least one processor 100a using at least one memory. It may also be realized by reading and executing a program stored in the computer 100b.

In this way, the processing circuit realizes each function of the diagnostic device 20 using the hardware 200, software, firmware, or a combination thereof.

Although not shown, each function of the monitoring device 16 is also realized by a processing circuit equivalent to the processing circuit that realizes each function of the diagnostic device 20. Although not shown, each function of the information center device 17 is also realized by a processing circuit equivalent to a processing circuit that realizes each function of the diagnostic device 20.

Embodiment 2.
FIG. 10 is a flowchart for explaining an overview of the operation of the diagnostic device according to the second embodiment to calculate the amount of shaft displacement. Note that parts that are the same as or equivalent to those in Embodiment 1 are given the same reference numerals. Description of this part will be omitted.

In the second embodiment, the calculation unit 25 calculates the shaft displacement amount h by further using the value of the loaded weight of the car 12 measured by the weighing device 12c.

Specifically, when calculating the shaft displacement amount h, the calculation unit 25 uses the value of the loaded weight of the car 12 to calculate the coefficients C ₁ , C ₂ , and C ₃ in equations (4) and (5). Correct each value. Since the coefficients C ₁ , C ₂ , and C ₃ are all functions of the value of the loaded weight, each has a numerical value corresponding to the value of the loaded weight measured by the weighing device 12c. The calculation unit 25 calculates the wrap angle θ using the corrected coefficients C ₁ , C ₂ , and C ₃ . The calculation unit 25 calculates the shaft displacement amount h using the calculated wrap angle θ.

FIG. 10 shows a flowchart of the operation in which the calculation unit 25 calculates the shaft displacement amount h by performing correction based on the loaded weight.

The operations performed from step S301 to step S303 are similar to the operations performed from step S201 to step S203 in the flowchart of FIG.

After the operation in step S303 is performed, the operation in step S304 is performed. In step S304, the diagnostic device 20 acquires information on the loaded weight of the car 12 when the car 12 moves in a specific section from the weighing device 12c. Note that the diagnostic device 20 may acquire the information in step S301. The calculation unit 25 of the diagnostic device 20 corrects the values of the coefficients C ₁ , C ₂ , and C ₃ based on the value of the loaded weight.

After that, the operation of step S305 is performed. In step S305, the calculation unit 25 calculates the shaft displacement amount h using the total rotation angle value Θ _i and the corrected coefficients C ₁ , C ₂ , and C ₃ .

Thereafter, the calculation unit 25 ends the operation of calculating the axial displacement amount h. The diagnostic device 20 performs various abnormality diagnoses using the shaft displacement amount h.

According to the second embodiment described above, the diagnostic device 20 calculates the wrap angle θ based on the information on the loaded weight of the car 12 and the total value of the rotation angle. Therefore, the diagnostic device 20 can perform an abnormality diagnosis even when the car 12 is occupied by a person or the like. As a result, the diagnostic device 20 can perform abnormality diagnosis when the elevator system is in normal operation, rather than during special operation.

Note that, by correcting the calculation result of the shaft displacement amount h using the value of the loaded weight of the car 12 measured by the weighing device 12c, the calculation unit 25 calculates the corrected shaft displacement amount h′. good. In this case, the calculation unit 25 does not correct the values of the coefficients C ₁ , C ₂ , and C ₃ when calculating the axial displacement amount h. For example, the calculation unit 25 may calculate a correction coefficient corresponding to the value of the loaded weight of the car 12, and calculate the corrected shaft displacement amount h' by integrating the correction coefficient and the shaft displacement amount h. .

Embodiment 3.
FIG. 11 is a schematic cross-sectional view of a hoisting machine to which the diagnostic device according to the third embodiment is applied. FIG. 12 is a diagram showing an overview of temperature changes in a bearing to which the diagnostic device according to the third embodiment is applied. Note that parts that are the same as or equivalent to those in Embodiment 1 or 2 are given the same reference numerals. Description of this part will be omitted.

As shown in FIG. 11, in the third embodiment, the bearing 9 is provided with a bearing temperature measuring device 30. Although not shown, the bearing temperature measuring device 30 may be provided adjacent to the bearing 9 in the direction of the rotation axis. The bearing temperature measuring device 30 measures the temperature of the bearing 9. Bearing temperature measuring device 30 may transmit the measured temperature to diagnostic device 20 .

FIG. 12 shows an example of a graph showing the change in temperature of the bearing 9 over time. As an example, the time course of the temperature of a bearing 9 in an elevator system installed in an office building is shown. The vertical axis is the bearing temperature of the bearing 9 measured by the bearing temperature measuring device 30. The horizontal axis is time. The horizontal axis shows a period of one week.

For example, in an office building on weekdays, the operating rate of the hoisting machine 5 is high during the time period from 7:00 to 18:00. The bearing temperature increases or decreases in correspondence with the operating rate. For example, on weekdays, the temperature of the bearing 9 tends to rise from around 7:00. The bearing temperature continues to rise until around 18:00. After that, the operating rate drops rapidly, so the bearing temperature drops and continues to drop until around 7:00 the next day. The bearing temperature repeatedly rises and falls in such a cycle.

Even in office buildings on holidays, bearing temperatures change at the same frequency as on weekdays. However, in office buildings on holidays, the occupancy rate is generally lower than on weekdays, so the maximum bearing temperature on holidays is lower than the maximum bearing temperature on weekdays.

Note that the tendency of bearing temperature changes differs depending on the installation location, such as commercial facilities and residential condominiums. Furthermore, the value of the bearing temperature varies depending on the season due to the influence of the outside temperature.

When the bearing temperature rises, the bearing 9 expands. At this time, the temperature of the rotating shaft body 8 rises together with the bearing 9. The rotating shaft body 8 expands together with the bearing 9. Therefore, the bearing temperature affects the load generated on the bearing 9.

Next, a diagnosis system according to the third embodiment will be explained using FIG. 13.
FIG. 13 is a block diagram of a diagnostic device according to the third embodiment. Note that in FIG. 13, illustration of the hoisting machine 5 is omitted.

In the third embodiment, the diagnostic system further includes a bearing temperature measuring device 30. As shown in FIG. 13, the diagnostic device 20 acquires bearing temperature information from the bearing temperature measuring device 30.

The load function stored in the storage unit 21 of the third embodiment is a function of the shaft displacement amount h and the bearing temperature.

When calculating the applied load, the determination unit 26 reflects the current bearing temperature acquired from the bearing temperature measuring device 30 in the calculation result. Specifically, the determination unit 26 calculates the value of the applied load by inputting the shaft displacement amount h calculated by the calculation unit 25 and the bearing temperature measured by the bearing temperature measurement device 30 into the applied load function. do. The applied load value has higher accuracy than the applied load value calculated in the first embodiment. The determination unit 26 determines whether the bearing 9 is abnormal based on the load value whose accuracy is improved depending on the bearing temperature.

Next, a third example of abnormality diagnosis in the third embodiment will be described using FIG. 14.
FIG. 14 is a flowchart for explaining an overview of a third example of abnormality diagnosis performed by the diagnostic apparatus according to the third embodiment.

In the flowchart shown in FIG. 14, the operations performed from step S401 to step S404 are similar to the operations performed from step S201 to step S204 in the flowchart of FIG.

After the operation in step S404, the operation in step S405 is performed. In step S405, the determination unit 26 acquires bearing temperature information from the bearing temperature measuring device 30.

Thereafter, the operation of step S406 is performed. In step S406, the determination unit 26 calculates the applied load based on the shaft displacement amount h calculated in step S404 and the acquired bearing temperature.

Thereafter, the operation of step S407 is performed. In step S407, the determining unit 26 determines whether the bearing 9 is abnormal based on the applied load value. Specifically, the determination unit 26 determines whether the calculated load value exceeds a prescribed threshold value.

In step S407, if the applied load value does not exceed the prescribed threshold value, the operation in step S408 is performed. In step S408, the determination unit 26 determines that there is no abnormality in the bearing 9, that is, it is normal. The determination unit 26 creates information on the degree of abnormality that includes the fact that there is no abnormality and the value of the calculated load as information on the diagnosis result. The diagnostic device 20 transmits information on the diagnostic results to the monitoring device 16. The diagnostic device 20 ends the abnormality diagnosis.

In step S407, if the load value exceeds the prescribed threshold, the operation in step S409 is performed. In step S409, the determining unit 26 determines that there is an abnormality in the bearing 9. The determination unit 26 creates information on the degree of abnormality that includes the fact that there is an abnormality and the calculated load value as information on the diagnosis result. The diagnostic device 20 transmits information on the diagnostic results to the monitoring device 16. The diagnostic device 20 ends the abnormality diagnosis.

After the operation of step S408 or step S409 is performed, the operation of step S410 is performed. In step S410, the monitoring device 16 transmits information on the diagnosis result to the information center device 17. The information center device 17 displays information on the diagnosis results to maintenance company workers and the like. The information center device 17 creates a maintenance inspection plan for the elevator system based on the information of the diagnosis results. At this time, the information center device 17 may perform a lifespan diagnosis of the bearing 9.

According to the third embodiment described above, the diagnostic device 20 calculates the applied load based on the measured value of the temperature of the bearing 9 and the amount of shaft displacement. Therefore, the accuracy of abnormality diagnosis can be improved.

Note that the determination unit 26 may estimate the amount of expansion of the bearing 9 based on the measured value of the temperature of the bearing 9. In this case, the determination unit 26 calculates a corrected shaft displacement amount by removing the influence of the expansion amount of the rotating shaft body 8 and bearing 9 from the value of the shaft displacement amount calculated by the calculation unit 25, and adds The applied load may be calculated based on this. Therefore, the state of the internal shape of the bearing 9 can be determined with higher accuracy.

Note that in Embodiments 1 to 3, the reference value of the shaft displacement amount may be selected depending on the time period in which the total value of the rotation angles is calculated. As shown in FIG. 12, the temperature of the bearing 9 is lowest in the morning. That is, the total value of the rotation angles is calculated in the morning, and the calculated value of the amount of shaft displacement is the value of the amount of shaft displacement in a state where the amount of expansion of the rotating shaft body 8 and the bearing 9 is the smallest. The determination unit 26 may set the value of the shaft displacement amount calculated in the morning as the reference value of the shaft displacement amount. The determination unit 26 can accurately calculate the expansion amount of the rotating shaft body 8 and the bearing 9 by subtracting the reference value from the value of the shaft displacement amount calculated in the evening.

Embodiment 4.
FIG. 15 is a block diagram of a maintenance management system to which the diagnostic device according to the fourth embodiment is applied. Note that the same or corresponding parts as those in Embodiment 1 to Embodiment 3 are given the same reference numerals. Description of this part will be omitted.

In the maintenance management system of Embodiment 4, a learned model that infers the amount of shaft displacement is created by supervised machine learning. The amount of axial displacement is inferred by the learning model. The diagnostic device 20 diagnoses an abnormality in the bearing 9 based on the inferred amount of shaft displacement.

As shown in FIG. 15, the information center device 17 further includes a learning device 40. The learning device 40 includes a learning information acquisition section 41 and a model generation section 42.

The learning information acquisition unit 41 acquires learning information for performing learning from the control panel 15 and the diagnostic device 20 via the monitoring device 16. The learning information acquisition unit 41 accumulates the acquired information. The learning information includes the total value of rotation angles calculated by the rotation angle calculation unit 24 when the car 12 moves in a specific section, and the amount of shaft displacement calculated by the calculation unit 25 based on the total value of the rotation angles. , is information in which the departure floor of the specific section, the arrival floor of the specific section, and the loaded weight of the car 12 that moved in the specific section are associated with each other.

Note that in order to improve the accuracy of the output, the learning information may include even more information. Specifically, the learning information may include at least one of the date, day of the week, and time zone in which the total value of rotation angles was calculated. The learning information may include at least one of daily usage frequency, daily cumulative mileage, and daily cumulative rotation angle on the day when the total rotation angle value was calculated. The learning information may include at least one of the temperature of the hoist and the temperature of the machine room on the day when the total value of the rotation angles was calculated. The learning information may include information in which the amount of shaft displacement calculated by the diagnostic device 20 is associated with the amount of shaft displacement actually measured by the displacement measuring device.

The model generation unit 42 performs learning based on the learning information acquired by the learning information acquisition unit 41 and generates a learned model. At this time, the model generation unit 42 performs learning using a commonly used supervised machine learning method. The model generation unit 42 stores information about the generated trained model. The model generation unit 42 transmits information about the generated learned model.

The learned model includes the total value of the rotation angles calculated by the rotation angle calculation unit 24 when the car 12 moves in a specific section, the departure floor of the specific section, the arrival floor of the specific section, and the This is a model that uses as input information the loaded weight of the car 12 that has moved over a specific section. The learned model is a model whose output information is an inferred value of the amount of axial displacement in response to input information. That is, the learned model is a model that outputs the amount of axial displacement in place of the calculation unit 25.

The diagnostic device 20 further includes a model storage section 43, an information acquisition section 44, and an inference section 45.

The model storage unit 43 stores information on learned models. For example, the model storage unit 43 receives learned model information from the model generation unit 42 and stores the latest learned model information.

The information acquisition unit 44 acquires information to be input to the learned model. Specifically, the information acquisition unit 44 acquires information corresponding to the input information from the control panel 15 and the rotation angle calculation unit 24, and associates the information with the input information. For example, the information acquisition unit 44 acquires information corresponding to input information when diagnostic driving is performed.

Note that when the learned model corresponds to more input information, the information acquisition unit 44 acquires the corresponding input information.

In the abnormality diagnosis, the inference unit 45 uses the learned model stored in the model storage unit 43 to infer the amount of axial displacement from the information acquired by the information acquisition unit 44.

In the second or third example of abnormality diagnosis, the determination unit 26 diagnoses an abnormality in the bearing 9 based on the amount of shaft displacement inferred by the inference unit 45. That is, the determination unit 26 performs abnormality diagnosis using the axial displacement amount inferred by the inference unit 45 instead of the axial displacement amount calculated by the calculation unit 25. At this time, the determination unit 26 creates information on the degree of abnormality based on the amount of shaft displacement inferred by the inference unit 45.

Note that, in the second or third example of the abnormality diagnosis, the determination unit 26 may further perform the abnormality diagnosis using the shaft displacement amount calculated by the calculation unit 25. In this case, the determination section 26 compares the degree of abnormality based on the amount of shaft displacement inferred by the inference section 45 and the degree of abnormality based on the amount of shaft displacement calculated by the calculation section 25, and uses the result as the diagnosis result of the abnormality diagnosis. You can also output it as Further, the determination unit 26 corrects the degree of abnormality based on the amount of shaft displacement calculated by the calculation unit 25 with the degree of abnormality based on the amount of shaft displacement inferred by the inference unit 45, and outputs the result as the diagnosis result of the abnormality diagnosis. You may.

Next, the operation of the learning device 40 will be explained using FIG. 16.
FIG. 16 is a flowchart for explaining an overview of the learning operation performed by the learning device to which the diagnostic device according to the fourth embodiment is applied.

As shown in FIG. 16, in step S501, the learning information acquisition unit 41 of the learning device 40 acquires and accumulates learning information. Note that the learning information acquisition unit 41 may acquire and accumulate learning information at any timing, regardless of the learning operation.

Thereafter, the operation of step S502 is performed. In step S502, the model generation unit 42 of the learning device 40 performs supervised learning processing using the learning information to generate a learned model.

After that, the operation of step S503 is performed. In step S503, the model generation unit 42 stores the trained model. The model generation unit 42 transmits the learned model to the diagnostic device 20 via the monitoring device 16.

After that, the learning device 40 ends the learning operation.

Note that the learning operation of the learning device 40 may be performed at any timing. Specifically, the learning operation is performed at predetermined intervals. The learning operation is performed after the sheave diameter or the diameter of the main rope 11 is inspected during maintenance inspection, based on the learning information accumulated after the inspection.

Note that the learning information used in the learning operation may be differentiated and used according to the time period in which the total value of the rotation angles was calculated. Specifically, for example, the learning information acquisition unit 41 accumulates learning information acquired in the morning, when the temperature of the bearing 9 is low, as the first learning information. The learning information acquisition unit 41 accumulates learning information acquired in the afternoon, when the temperature of the bearing 9 is higher than in the morning, as second learning information. In this case, the model generation unit 42 separately creates a learned model based on the first learning information and a learned model based on the second learning information. The model generation unit 42 distinguishes and manages a trained model created based on the first learning information and a trained model created based on the second learning information.

Next, the operation inferred by the diagnostic device 20 will be explained using FIG. 17.
FIG. 17 is a flowchart for explaining an overview of the inference operation performed by the diagnostic device in the fourth embodiment.

The diagnostic device 20 infers the amount of shaft displacement when diagnosing an abnormality. For example, after a diagnostic operation is performed, the diagnostic device 20 infers the amount of shaft displacement.

In step S601, the information acquisition unit 44 acquires input information to be input to the learned model.

Thereafter, the operation of step S602 is performed. In step S602, the inference unit 45 inputs the input information to the learned model. The inference unit 45 performs output processing of the learned model.

Thereafter, the operation of step S603 is performed. In step S603, the inference unit 45 infers the amount of axial displacement based on the learned model and outputs it as output information.

Thereafter, the operation of step S604 is performed. In step S604, the determination unit 26 determines whether the bearing 9 is abnormal based on the amount of shaft displacement output by the inference unit 45.

The diagnostic device 20 completes the inference operation. After that, the diagnostic device 20 continues the abnormality diagnosis.

According to the fourth embodiment described above, the maintenance management system includes the rotation angle calculation section 24, the calculation section 25, the learning information acquisition section 41, and the model generation section 42. The maintenance management system creates a learned model that outputs the amount of shaft displacement by inputting information such as the total value of the rotation angle of the first sheave 7 calculated by the rotation angle calculation unit 24. For example, the output shaft displacement amount can be used to determine whether the bearing 9 is abnormal. That is, the abnormality of the bearing 9 can be determined based on the total value of the rotation angles. Therefore, the maintenance management system can determine the abnormality of the bearing 9 with a simple configuration.

The diagnostic device 20 also includes a model storage section 43 and an inference section 45. The diagnostic device 20 infers the amount of axial displacement from the total value of the rotation angles based on the learned model. The diagnostic device 20 determines whether the bearing 9 is abnormal based on the inferred amount of shaft displacement. Therefore, an abnormality in the bearing 9 can be determined with a simple configuration. Further, since it is not necessary to calculate the amount of axial displacement each time, the amount of calculation by the diagnostic device 20 can be reduced. Furthermore, since the diagnostic device 20 performs inference based on the learned model, it is possible to perform edge processing and the like and perform inference with higher accuracy compared to when inference is performed by the information center device 17 or the like.

Note that the learned model may be a model that outputs the value of the wrapping angle instead of the amount of axial displacement. In this case, in the abnormality diagnosis, the inference unit 45 uses the learned model stored in the model storage unit 43 to infer the value of the wrap angle from the information acquired by the information acquisition unit 44.

Although not illustrated, each function of the learning device 40 is realized by a processing circuit equivalent to the processing circuit that realizes each function of the diagnostic device 20. Furthermore, the diagnostic device 20 may include each function of the learning device 40. Further, each function of the learning device 40 may be provided not in the information center device 17 but in a cloud server or the like.

As described above, the diagnostic device according to the present disclosure can be used in an elevator system.

1 Hoistway, 2 Building, 3 Machine room, 4, 4a, 4b landing, 5 Hoisting machine, 6 Electric motor, 7 First sheave, 7a Rope groove, 7b Bottom, 8 Rotating shaft, 9 Bearing, 10th 2 Sheave, 11 Main rope, 12 Car, 12a Car frame, 12b Car room, 12c Weighing device, 13 Counterweight, 14 Rotation angle detection device, 15 Control panel, 16 Monitoring device, 17 Information center equipment, 20 Diagnostic equipment , 21 Memories, 22 Communication Department, 23 Diagnosis Driving Directors, 24 -rotation angle calculation department, 25 operations department, 26 judgment unit, 30 -axis temperature measuring device, 40 learning device, 41 learning information acquisition, 42 model generation department, 43 Model storage unit, 44 Information acquisition unit, 45 Inference unit, 100a Processor, 100b Memory, 200 Hardware, A Rotation axis

Claims (18)

1. A hoist having a first sheave, an electric motor that rotates the first sheave on a rotating shaft, and a bearing that supports the rotating shaft, a second sheave, and the first sheave and the second sheave. A diagnostic device for diagnosing an abnormality in the bearing in an elevator system having a main rope wrapped around a sheave and a car suspended from the main rope,
   a rotation angle calculation unit that calculates a total value of rotation angles of the first sheave;
   a determination unit that determines whether the bearing is abnormal based on a total value of rotation angles calculated by the rotation angle calculation unit when the car travels in a specific section;
   Diagnostic equipment with
2. a calculation unit that calculates an amount of shaft displacement, which is the amount of change in the vertical position of the rotating shaft body from a reference position, based on the total value of the rotation angles calculated by the rotation angle calculation unit;
   further comprising;
   The diagnostic device according to claim 1, wherein the determination unit determines whether the bearing is abnormal based on the amount of shaft displacement calculated by the calculation unit.
3. The calculation unit calculates a wrap angle of the main rope with respect to the first sheave based on the total value of the rotation angles calculated by the rotation angle calculation unit, and calculates the shaft displacement based on the calculated wrap angle. The diagnostic device according to claim 2, which calculates a quantity.
4. The calculation unit calculates the calculated wrap angle θ, the distance x in the horizontal direction between the center of the first sheave and the center of the second sheave, and the first sheave when the first sheave is at the reference position. The vertical distance y ₀ between the center of the sheave and the center of the second sheave, and the constant i indicating the winding method of the main rope around the first sheave and the second sheave, are expressed as follows: The diagnostic device according to claim 3, wherein the axial displacement amount h is calculated by applying equation (1).
   

   
5. The arithmetic unit is
   When the car is in upward operation, the total value Θ _up of rotation angles when the car is in upward operation in the specific section, a constant r indicating the roping method of the elevator system, the distance X of the specific section, the Calculate the wrap angle θ by applying an effective radius Re, which is half the sum of the sheave diameter of the first sheave and the diameter of the main rope, and a coefficient C ₁ to the following equation (2),
   When the car runs down, the total rotation angle Θ _dn , constant r, distance X, effective radius Re, coefficient C ₂ , and coefficient C ₃ when the car runs down the specific section are Calculating the wrapping angle θ by applying the following equation (3),
   The diagnostic device according to claim 3 or 4.
   

   

   
   

   
6. The diagnostic device according to any one of claims 3 to 5, wherein the calculation unit calculates the wrap angle based on the measured value of the loaded weight of the car and the total value of the rotation angle.
7. 7. The determination unit determines, based on the shaft displacement amount, that the bearing has an abnormality in which an internal shape of the bearing has changed. Diagnostic equipment.
8. The determination unit calculates the value of the load generated on the bearing due to expansion of at least one of the bearing and the rotating shaft body based on the amount of shaft displacement, and determines the load as an abnormality of the bearing. The diagnostic device according to any one of claims 2 to 7, which determines that there is an abnormality in which the value is increasing.
9. The diagnostic device according to claim 8, wherein the determination unit determines whether the bearing is abnormal based on the measured value of the temperature of the bearing and the amount of shaft displacement.
10. The determination unit determines the type of abnormality in the bearing based on the difference between the shaft displacement amount calculated by the calculation unit and a reference value of the shaft displacement amount. The diagnostic device described in .
11. The determination unit determines the rotation calculated by the rotation angle calculation unit when the car performs upward and downward operation between the highest floor and the lowest floor set for the car as the specific section without stopping. The diagnostic device according to any one of claims 1 to 10, wherein an abnormality of the bearing is determined based on a total value of angles.
12. When it is detected that there is no object inside the car based on the measured value of the loaded weight of the car, the car moves between the top and bottom floors set for the car without stopping. a diagnostic operation command unit that sends a command to perform a diagnostic operation of ascending and descending operations;
    further comprising;
    Any one of claims 1 to 10, wherein the determination unit determines whether the bearing is abnormal based on a total value of rotation angles calculated by the rotation angle calculation unit when the diagnostic operation is performed. The diagnostic device described in .
13. The total value of the rotation angles calculated by the rotation angle calculation unit when the car moves from the departure floor to the arrival floor, the departure floor, the arrival floor, and the loaded weight of the car when the car moves. and a model storage unit that stores a learned model for inferring an amount of shaft displacement, which is the amount of change in the vertical position of the rotating shaft body from a reference position.
    Using the learned model stored in the model storage unit, the total value of rotation angles calculated by the rotation angle calculation unit when the car moves from the departure floor to the arrival floor, the departure floor, and the an inference unit that infers the axial displacement amount from the arrival floor and the loaded weight of the car when the car moves;
    further comprising;
    The diagnostic device according to any one of claims 1 to 12, wherein the determination unit determines whether the bearing is abnormal based on the shaft displacement amount inferred by the inference unit.
14. A hoist having a first sheave, an electric motor that rotates the first sheave on a rotating shaft, and a bearing that supports the rotating shaft, a second sheave, and the first sheave and the second sheave. A diagnostic device for diagnosing an abnormality in the bearing in an elevator system having a main rope wrapped around a sheave and a car suspended from the main rope,
    a rotation angle calculation unit that calculates a total value of rotation angles of the first sheave;
    The total value of the rotation angles calculated by the rotation angle calculation unit when the car moves from the departure floor to the arrival floor, the departure floor, the arrival floor, and the loaded weight of the car when the car moves. and a model storage unit that stores a learned model for inferring an amount of shaft displacement, which is the amount of change in the vertical position of the rotating shaft body from a reference position.
    Using the learned model stored in the model storage unit, the total value of rotation angles calculated by the rotation angle calculation unit when the car moves from the departure floor to the arrival floor, the departure floor, and the an inference unit that infers the axial displacement amount from the arrival floor and the loaded weight of the car when the car moves;
    a determination unit that determines whether the bearing is abnormal based on the shaft displacement amount inferred by the inference unit;
    Diagnostic equipment with
15. A hoist having a first sheave, an electric motor that rotates the first sheave on a rotating shaft, and a bearing that supports the rotating shaft, a second sheave, and the first sheave and the second sheave. A diagnostic system for diagnosing an abnormality in the bearing in an elevator system having a main rope wrapped around a sheave and a car suspended from the main rope,
    a rotation angle detection device that is provided on the hoist and transmits an angle signal corresponding to the angle at which the first sheave has rotated;
    Based on the angle signal from the rotation angle detection device, calculate the total value of the rotation angle through which the first sheave has rotated, and based on the total value of the rotation angle calculated when the car runs in a specific section. The diagnostic device according to any one of claims 1 to 14, which determines whether the bearing is abnormal;
    Diagnostic system with.
16. A diagnostic system according to claim 15,
    a monitoring device that receives information on a diagnosis result in which the diagnosis device of the diagnosis system determines that the bearing is abnormal, and transmits information on the diagnosis result to the outside;
    Remote monitoring system with.
17. A diagnostic system according to claim 15,
    a monitoring device that receives information on a diagnosis result in which a diagnostic device of the diagnostic system determines that the bearing is abnormal, and transmits information on the diagnosis result to the outside;
    an information center device that receives information on the diagnosis results from the monitoring device and creates a maintenance plan for the elevator system based on the information on the diagnosis results;
    A maintenance management system equipped with
18. A hoist having a first sheave, an electric motor that rotates the first sheave on a rotating shaft, and a bearing that supports the rotating shaft, a second sheave, and the first sheave and the second sheave. In a maintenance management system that performs maintenance management of an elevator system having a main rope wrapped around a sheave and a car suspended from the main rope,
    a rotation angle calculation unit that calculates a total value of rotation angles of the first sheave when the car moves from the departure floor to the arrival floor;
    a calculation unit that calculates an amount of shaft displacement, which is the amount of change in the vertical position of the rotating shaft body from a reference position, based on the total value of the rotation angles calculated by the rotation angle calculation unit;
    The total value of the rotation angles calculated by the rotation angle calculation unit, the axial displacement amount calculated by the calculation unit, the departure floor, the arrival floor, and the loaded weight when the car moves are associated with each other. a learning information acquisition unit that acquires learning information including the information that has been learned;
    The total value of the rotation angles calculated by the rotation angle calculation unit using the learning information acquired by the learning information acquisition unit, the departure floor, the arrival floor, and the car when the car moves. a model generation unit that generates a trained model for inferring the amount of axial displacement from the loaded weight of the
    A maintenance management system equipped with

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