Auxiliary system for configuration work of elevator equipment

Abstract

Provided is an assist system that can be applied to configuration work of various devices of an elevator. The assistance system (1) has a photographing device (8) and a guidance system (9). The image capturing device (8) captures an image of a region including a target configuration position corresponding to each of the one or more devices of the elevator during the configuration operation. The configuration operation is the operation for configuring each device into the corresponding target configuration. And the guiding system (9) guides each device to be configured into a corresponding target configuration according to the image shot by the shooting device (8).

Description

Technical Field

[0001] The present disclosure relates to an auxiliary system for configuration work of an elevator installation. Background Art

[0002] Patent document 1 discloses an example of a method for configuring a buffer seat of an elevator. In this method, a visible light laser device is positioned based on a reference line material that is vertically lowered in a hoistway. The buffer seat is positioned in the pit by aligning the laser beam emitted from the visible light laser device with the position of the index of the buffer seat.

[0003] Prior art literature

[0004] Patent Literature

[0005] Patent Document 1: Japanese Patent Application Publication No. 2010-70268 Summary of the invention

[0006] Problems to be solved by the invention

[0007] Various devices including a buffer seat are arranged in an elevator. However, the method of Patent Document 1 is based on a reference line material vertically lowered in the hoistway, and therefore cannot be applied to the arrangement of devices not arranged in a pit.

[0008] The present disclosure relates to solving such a problem. The present disclosure provides an auxiliary system applicable to the arrangement work of various devices of an elevator.

[0009] Means for solving problems

[0010] The auxiliary system disclosed in the present invention comprises: a photographing device which photographs an area including positions of target configurations corresponding to one or more devices respectively during a configuration operation of configuring one or more devices of an elevator into corresponding target configurations; and a guidance system which guides the configuration of one or more devices into corresponding target configurations based on the images captured by the photographing device.

[0011] Effects of the Invention

[0012] The auxiliary system of the present disclosure can be applied to configuration work of various equipment of an elevator. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 This is a perspective view of an example of equipment of an elevator to which the auxiliary system according to the first embodiment is applied.

[0014] Figure 2 It is a top view of the hoisting machine according to the first embodiment.

[0015] Figure 3 This is a structural diagram of the auxiliary system of implementation mode 1.

[0016] Figure 4 This is a diagram showing an example of display performed by the display unit according to the first embodiment.

[0017] Figure 5 This is a diagram showing an example of display performed by the display unit according to the first embodiment.

[0018] Figure 6 This is a flowchart showing an example of the operation of the support system according to the first embodiment.

[0019] Figure 7 This is a plan view of another example of elevator equipment to which the auxiliary system according to the first embodiment is applied.

[0020] Figure 8 This is a plan view of another example of elevator equipment to which the auxiliary system according to the first embodiment is applied.

[0021] Fig. 9 This is a diagram showing another example of display performed by the display unit according to the first embodiment.

[0022] Fig.10 This is a diagram showing an example of extraction of a characteristic portion by the target arrangement acquisition unit according to the first embodiment.

[0023] Fig.11 This is a diagram showing an example of extraction of a characteristic portion by the target arrangement acquisition unit according to the first embodiment.

[0024] Fig.12 This is a diagram showing an example of extraction of a characteristic portion by the target arrangement acquisition unit according to the first embodiment.

[0025] Fig.13 This is a diagram showing an example of extraction of a characteristic portion by the target arrangement acquisition unit according to the first embodiment.

[0026] Fig.14 This is a diagram showing an example of extraction of a characteristic portion by the target arrangement acquisition unit according to the first embodiment.

[0027] Fig.15 This is a diagram showing an example of extraction of a characteristic portion by the target arrangement acquisition unit according to the first embodiment.

[0028] Fig.16 This is a diagram showing an example of extraction of a characteristic portion by the target arrangement acquisition unit according to the first embodiment.

[0029] Fig.17 This is a diagram showing an example of acquisition of a target arrangement by the target arrangement acquisition unit according to the first embodiment.

[0030] Fig.18This is a configuration diagram of a support system according to a modified example of the first embodiment.

[0031] Fig.19 This is a diagram showing an example in which the target arrangement acquisition unit according to the modification example of the first embodiment acquires a target arrangement.

[0032] Fig. 20 This is a hardware configuration diagram of the main parts of the support system according to the first embodiment.

[0033] Fig.21 This is a structural diagram of the auxiliary system of implementation mode 2.

[0034] Fig. 22 This is a diagram showing an example of a learned model in the learning unit according to the second embodiment.

[0035] Fig.23 This is a diagram showing an example of a learned model in the learning unit according to the second embodiment.

[0036] Fig.24 This is a flowchart showing an example of the operation of the support system according to the second embodiment.

[0037] Fig.25 This is a flowchart showing an example of the operation of the support system according to the second embodiment.

[0038] Fig.26 This is a diagram showing an example of display performed by a display unit according to a modified example of the second embodiment. DETAILED DESCRIPTION

[0039] The embodiment of the present disclosure will be described with reference to the accompanying drawings. In each figure, the same or corresponding parts are denoted by the same reference numerals, and repeated descriptions are appropriately simplified or omitted.

[0040] Implementation Method 1

[0041] Figure 1 This is a perspective view of an example of elevator equipment to which the support system 1 according to the first embodiment is applied.

[0042] The auxiliary system 1 is applied to the configuration operation of the elevator equipment. The elevator equipment includes, for example, devices that work in the elevator, parts that constitute the elevator, and their components. The configuration operation is the operation of configuring the elevator equipment to a target configuration corresponding to the equipment. In the configuration operation, one or more devices are respectively configured to the corresponding target configuration. The target configuration of each device is, for example, the configuration of the device under the normal operation of the elevator. Here, the configuration of the device includes the position and posture of the device. In the configuration operation, the order of configuration can also be pre-set for at least any one of the devices to be configured. The configuration operation includes, for example, the installation operation of a new elevator, the update operation of the elevator, the replacement operation of the elevator equipment, or the maintenance and inspection operation. The maintenance and inspection operation of the elevator equipment may also include the process of removing the elevator equipment and returning the equipment to its original position after adjustment or cleaning.

[0043] The elevator is used, for example, in a building with multiple floors. A hoistway of an elevator (not shown) is provided in the building. The hoistway is a vertically long space extending over multiple floors in the building. A landing station (not shown) for an elevator is provided on each floor. A landing station door is provided on each floor. The landing station door is a door that separates the landing station from the hoistway.

[0044] The elevator has a car (not shown), a traction rope 2, and a traction machine 3. The car is a device that transports users and the like between multiple floors by traveling in a vertical direction in a hoistway. The traction rope 2 is a rope that suspends the car from the hoistway. In the elevator, a plurality of traction ropes 2 may be provided. The traction machine 3 is an example of elevator equipment. Figure 1 , a perspective view of the hoisting machine 3 is shown in FIG. The hoisting machine 3 is, for example, installed in a machine room. The machine room is, for example, installed above the hoistway of the elevator. A hoisting machine base 4 is installed in the machine room. The hoisting machine base 4 is a base that serves as the base of the hoisting machine 3. The hoisting machine 3 has a motor 5 and a sheave 6. The motor 5 and the sheave 6 are examples of elevator equipment, respectively. In the configuration operation, the hoisting machine 3 may also be configured by being divided into the motor 5 and the sheave 6. The motor 5 is a device that drives the sheave 6 to rotate. The sheave 6 has a sheave groove 7. The sheave groove 7 is a groove in the sheave 6 in which the hoisting rope 2 is wound. The hoisting rope 2 is lowered from the sheave 6 to the hoistway, for example, through a rope duct installed in the machine room. In the elevator, the hoisting rope 2 is wound up by the sheave 6 driven to rotate by the motor 5, and the car travels in the vertical direction in the hoistway.

[0045] Figure 2 It is a top view of the hoisting machine 3 according to the first embodiment.

[0046] In this example, the support system 1 supports the work of arranging the elevator equipment including the hoisting machine 3. The support system 1 includes an imaging device 8.

[0047] The photographing device 8 is a device for photographing images, such as a camera. The image photographed by the photographing device 8 may be either a static image or a dynamic image. The photographing device 8 photographs an area including the target configuration position of the traction machine 3. The photographing device 8 is arranged vertically above the sheave 6 of the traction machine 3. The photographing device 8 is arranged directly above the sheave 6. In this example, the photographing device 8 is arranged on a vertical line passing through the rotation axis of the sheave 6. The photographing device 8 may also be arranged obliquely above the area including the target configuration position of the equipment such as the traction machine 3.

[0048] Figure 3 This is a configuration diagram of the support system 1 according to the first embodiment.

[0049] The photographing device 8 is fixed to the ceiling of the machine room above the sheave 6. The photographing device 8 is fixed in a manner that does not move from the beginning to the end of the configuration operation. The photographing device 8 is fixed, for example, by anchor bolts, magnets, suction cups, or adhesive tapes. The photographing device 8 may also be installed on a rack provided in a machine room, etc. The photographing device 8 may also be fixed to the wall of the machine room, etc. The photographing device 8 may also be fixed, for example, by a magnetic suction cup, etc. The photographing device 8 may continue to be fixed after the configuration operation is completed. Alternatively, the photographing device 8 may be removed after the configuration operation is completed.

[0050] The auxiliary system 1 has a guidance system 9. The guidance system 9 is, for example, a system composed of a server device, which is installed in a building or other buildings where an elevator is installed. Alternatively, the guidance system 9 may also be a system composed of a mobile information terminal such as a smartphone carried by an operator who performs configuration operations. Alternatively, the guidance system 9 may also be a system composed of a device built into the camera 8. The guidance system 9 may also be a system composed of one device. The guidance system 9 may also be a system composed of multiple devices. In this case, the multiple devices of the guidance system 9 may also be connected to each other through a communication network such as the Internet. Part or all of the functions of the guidance system 9 may also be installed on a virtual machine on a cloud service, for example. Part or all of the functions of the guidance system 9 may also be installed on an edge server in a building where an elevator is installed, for example, connected to an external service through a communication network such as the Internet. The guidance system 9 has a storage unit 10, an input unit 11, a target configuration acquisition unit 12, a display unit 13, and a notification unit 14.

[0051] The storage unit 10 is a part for storing information. The storage unit 10 stores information such as the order of configuration of one or more devices of the elevator in the configuration operation. The input unit 11 is, for example, a part that accepts input from an operator who performs the configuration operation. The input unit 11 is, for example, a touch panel, a mouse, or a keyboard. The target configuration acquisition unit 12 is a part that acquires the target configuration corresponding to each device to be configured in the configuration operation. The display unit 13 is a part that displays a guide image superimposed on the image captured by the camera 8, and the guide image indicates the target configuration corresponding to each device. The display unit 13 is, for example, a display. The notification unit 14 is a part that notifies the operator of the configuration relationship with the target configuration of each device. The notification unit 14 is, for example, a speaker that notifies by voice.

[0052] Next, use Figure 4 and Figure 5 The functions of the support system 1 will be described.

[0053] Figure 4 and Figure 5 This is a diagram showing an example of display by the display unit 13 according to the first embodiment.

[0054] In this example, the arrangement work includes a step of replacing the existing hoisting machine 3 with a newly installed hoisting machine 3 .

[0055] exist Figure 4 , an image showing a state in which the installed hoisting machine 3 is arranged.

[0056] The display unit 13 displays an image of the installed hoisting machine 3 captured by the imaging device 8 .

[0057] The target configuration acquisition unit 12 acquires the target configuration of the hoisting machine 3 as an elevator device. The target configuration acquisition unit 12 acquires the target configuration corresponding to the hoisting machine 3, for example, based on input from an operator. In this example, the target configuration corresponding to the hoisting machine 3 is the position of the sheave groove 7 under normal operation of the elevator. The information of the target configuration includes information of a characteristic portion. The characteristic portion is one or more points or lines that represent the characteristics of the position or posture of the device configured in the target configuration. In this example, the characteristic portion is a point representing the position of the sheave groove 7. The characteristic portion is, for example, a point representing the position of the end of the sheave groove 7. The target configuration acquired by the target configuration acquisition unit 12 is, for example, stored in the storage unit 10. The characteristic portion is, for example, used as a reference for guidance in the configuration operation. The characteristic portion of the device is extracted from the image captured by the camera 8, for example, by an image processing method.

[0058] In the process of replacing the hoisting machine 3 , the worker removes the hoisting rope 2 from the sheave 6 of the installed hoisting machine 3 .

[0059] Then, the operator inputs the target arrangement by drawing the sheave groove 7 and the like of the hoisting machine 3 installed before removal on the image captured by the imaging device 8 through the input unit 11 . The target arrangement acquisition unit 12 acquires the target arrangement input through the input unit 11 .

[0060] Then, the worker removes the installed hoisting machine 3. Next, the worker temporarily places the newly installed hoisting machine 3 in the machine room.

[0061] exist Figure 5 In FIG. 1 , an image showing a state in which a newly installed hoisting machine 3 is temporarily placed is shown.

[0062] The display unit 13 displays the image of the newly installed hoisting machine 3 captured by the imaging device 8 .

[0063] The display unit 13 displays the guide image superimposed on the image captured by the imaging device 8. The guide image is an image showing the object arrangement acquired by the object arrangement acquisition unit 12. Figure 5 In the figure, an example of a guide image corresponding to the hoisting machine 3 is shown. The guide image is, for example, an image that shows the position or posture of a characteristic portion of a device configured in a target configuration. In this example, as a guide image, an image that shows the position and posture of the sheave 6 of the hoisting machine 3 configured in the target configuration is shown. In addition, as a guide image, a point that shows the position of the end of the sheave 6 of the hoisting machine 3 configured in the target configuration is shown. The guide image may also be vector image data such as points or lines that show the position and posture of the configured device. The points or lines that show the position and posture of the device are, for example, corners or edges of the outline of the device. Alternatively, the guide image may be grid image data such as an image of the device configured in the target configuration.

[0064] The operator adjusts the position of the newly installed hoisting machine 3 that is temporarily placed according to the image displayed on the display unit 13. In this example, the operator moves the hoisting machine 3 to the right side of the drawing.

[0065] In this example, the guidance system 9 obtains the position of the newly installed hoisting machine 3 by, for example, image recognition of the image captured by the imaging device 8. In this case, the display unit 13 may display an image such as an arrow indicating the direction in which the newly installed hoisting machine 3 is to move as part of the guidance image.

[0066] In addition, for example, in the notification unit 14, a first range and a second range are pre-set regarding the relationship of the arrangement such as the distance between the newly installed hoisting machine 3 and the target arrangement corresponding to the hoisting machine 3. The first range is, for example, a range in which, when the position and posture of the newly installed hoisting machine 3 are within the first range, it indicates that the newly installed hoisting machine 3 is close to the target arrangement. The second range is, for example, a range in which, when the position and posture of the newly installed hoisting machine 3 are within the second range, it indicates that the newly installed hoisting machine 3 is arranged in the target arrangement within the range of the allowable error. The second range is included in the first range. The notification unit 14 determines, for example, whether the position and posture of the newly installed hoisting machine 3 obtained by image recognition or the like enters the first range and the second range. When the position and posture of the newly installed hoisting machine 3 enter the first range, the notification unit 14 emits a first voice, thereby notifying the operator that the newly installed hoisting machine 3 is close to the target arrangement. The first voice is, for example, a preset voice such as a warning sound or a voice broadcast. When the position and posture of the newly installed hoisting machine 3 enter the second range, the notification unit 14 emits a second voice, thereby notifying the operator that the newly installed hoisting machine 3 is arranged in the target arrangement. The second voice is, for example, a pre-set voice such as a warning sound or a voice broadcast, which is different from the first voice. The operator is guided by the display of the display unit 13 and the notification of the notification unit 14 to arrange the newly installed hoisting machine 3 in the target arrangement.

[0067] Then, the operator winds the traction rope 2 around the sheave 6 of the newly installed hoisting machine 3. If there is equipment to be further arranged, the operator performs the operation of arranging the equipment. At this time, the auxiliary system 1 guides the arrangement of the equipment in the same way as the guidance of the arrangement of the hoisting machine 3. On the other hand, if there is no equipment to be further arranged, the operator ends the arrangement operation.

[0068] Next, use Figure 6 An example of the operation of the support system 1 will be described.

[0069] Figure 6 This is a flowchart showing an example of the operation of the support system 1 according to the first embodiment.

[0070] exist Figure 6 2 shows an example of the operation of the auxiliary system 1 for guiding the arrangement of arbitrary equipment of the elevator.

[0071] In step S11, the target arrangement acquisition unit 12 acquires the target arrangement of the target device to be arranged. Then, the operation of the support system 1 proceeds to step S12.

[0072] In step S12, the display unit 13 displays a guide image showing the object arrangement corresponding to the device in a superimposed manner on the image of the target device captured by the imaging device 8. Then, the operation of the support system 1 proceeds to step S13.

[0073] In step S13, the notification unit 14 determines whether the position and posture of the target device enters the first range. If the determination result is "yes", the operation of the support system 1 proceeds to step S14. On the other hand, if the determination result is "no", the operation of the support system 1 proceeds to step S12.

[0074] In step S14, the notification unit 14 emits the first voice. Then, the operation of the support system 1 proceeds to step S15.

[0075] In step S15, the notification unit 14 determines whether the position and posture of the target device enters the second range. If the determination result is "yes", the operation of the support system 1 proceeds to step S16. On the other hand, if the determination result is "no", the operation of the support system 1 proceeds to step S12.

[0076] In step S16, the notification unit 14 emits the second voice. Then, the operation of the support system 1 for guiding the placement of the target device ends. At this time, if there is another device to be continuously placed during the placement operation, the support system 1 starts guiding the placement of the other device.

[0077] Here, the photographing device 8 may also have a plurality of cameras. Each camera is arranged at a position suitable for guiding the configuration of any device. The position suitable for guiding the configuration of the device is, for example, a position for photographing the device from a direction suitable for guiding the configuration of the device. The direction suitable for guiding the configuration of the device is, for example, a direction in which the allowable error of the configuration of the device is the largest, or a direction perpendicular to the direction in which the allowable error of the configuration of the device is the smallest. Alternatively, each camera may be arranged so as to be able to observe the configuration of each device in a three-dimensional manner. In the case where the device to be configured includes a hoisting machine 3, an arbitrary camera is arranged, for example, vertically above the sheave 6 of the hoisting machine 3. The camera is arranged directly above the sheave 6. In addition, any other arbitrary camera is arranged vertically below the sheave 6 of the hoisting machine 3. The camera is arranged directly below the sheave 6. The photographing device 8 may also have a camera that is arranged only vertically above or vertically below the sheave 6 of the hoisting machine 3.

[0078] The equipment to be configured in the configuration operation may also be equipment other than the traction machine 3. The equipment to be configured in the configuration operation may also be, for example, a car door device. The car door device is a device that is installed in the car and opens and closes so that the users of the elevator can get on and off the car. In this case, the imaging device 8 may also include a camera installed on the rear wall of the car room of the car. Here, the car room is the part of the car where the users take the elevator. The rear wall of the car room is, for example, the inner wall of the car room facing the space for the users to take the elevator. The rear wall of the car room is opposite to the car door device installed on the front surface of the car.

[0079] Figure 7 This is a plan view of another example of elevator equipment to which the support system 1 according to the first embodiment is applied.

[0080] exist Figure 7 , a plan view of a landing sill 15 is shown as another example of the elevator equipment.

[0081] The landing sill 15 is a sill that guides the opening and closing of the landing door. The characteristic part of the target configuration corresponding to the landing sill 15 is, for example, a point indicating the positions of both ends of the landing sill 15 under normal operation of the elevator. At this time, the imaging device 8 includes, for example, a camera that captures the landing sill 15 from vertically above.

[0082] Figure 8 This is a plan view of another example of elevator equipment to which the support system 1 according to the first embodiment is applied.

[0083] exist Figure 8 , a top view of a floor stop device 16 is shown as another example of an elevator device.

[0084] The stop device 16 is a device for detecting the stop of the car at each floor. The stop device 16 is, for example, installed in the car. The stop device 16 detects the stop plate installed at each floor through the detection unit 17. The detection unit 17 has a groove, and the stop plate passes through the groove when the car is traveling. The characteristic part of the target configuration corresponding to the stop device 16 is, for example, a point indicating the position of the end of the groove. At this time, the shooting device 8 includes, for example, a camera that shoots the stop device 16 from vertically above or vertically below. The camera is, for example, installed in the car. Alternatively, the camera can also be installed vertically above or vertically below the stop plate of any floor in the hoistway.

[0085] Fig. 9 This is a diagram showing another example of display by the display unit 13 according to the first embodiment.

[0086] exist Fig. 9 On the left side of FIG, an image showing a state where the installed traction machine 3 is arranged is shown. Fig. 9 On the right side of , an image showing a state in which a newly installed hoisting machine 3 is arranged is shown.

[0087] In this example, the size of the existing hoisting machine 3 is different from the size of the newly installed hoisting machine 3. On the other hand, the size of the sheave 6 of the existing hoisting machine 3 is the same as the size of the sheave 6 of the newly installed hoisting machine 3. At this time, the auxiliary system 1 can guide the arrangement of the newly installed hoisting machine 3 by the target arrangement based on the input with the sheave groove 7 of the existing hoisting machine 3 as a reference.

[0088] As described above, the auxiliary system 1 of the first embodiment includes the imaging device 8 and the guidance system 9. The imaging device 8 captures an area including the positions of the target configurations corresponding to one or more devices of the elevator in the configuration operation. The configuration operation is an operation of arranging each device into the corresponding target configuration. The guidance system 9 guides the arrangement of each device into the corresponding target configuration based on the image captured by the imaging device 8.

[0089] The auxiliary system 1 guides the configuration work based on the image captured by the camera 8. Therefore, the auxiliary system 1 can be applied to the configuration work of various equipment of the elevator regardless of the type of equipment to be configured and the location to be configured. In addition, since it is not necessary to mark lines during the configuration work, the auxiliary system 1 can also be applied to the configuration work of equipment that is not directly installed in the building, such as the sheave 6.

[0090] Furthermore, the guidance system 9 acquires a target arrangement corresponding to at least one of the one or more devices based on an input from an operator who performs an arrangement operation.

[0091] The target arrangement is input by the operator who performs the arrangement work, and therefore, the target arrangement can be set according to the situation such as the location to be arranged and the equipment to be arranged.

[0092] Furthermore, the guidance system 9 includes a display unit 13. The display unit 13 displays a guidance image showing the object arrangement corresponding to at least one of the one or more devices, superimposed on the image captured by the imaging device 8.

[0093] This allows the operator to simultaneously check the device to be arranged and the guide image and perform the arrangement work. Therefore, the support system 1 can more efficiently perform the guidance of the arrangement work.

[0094] Furthermore, the guide image indicating the target arrangement corresponding to at least any one of the one or more devices is an image of one or more characteristic portions of the device arranged in the target arrangement.

[0095] The auxiliary system 1 guides the configuration operation through the characteristic parts of the equipment. As a result, the reference for position alignment becomes clear. Therefore, the auxiliary system 1 can guide the configuration operation more effectively. In addition, in the case where the configuration operation includes a process of replacing an existing equipment with a newly installed equipment of a different overall size or shape, the configuration guidance can be more effectively performed through the common characteristic parts of the existing equipment and the newly installed equipment.

[0096] Furthermore, the guidance system 9 includes a notification unit 14. In the notification unit 14, a first range is preset for a target arrangement corresponding to at least one of the one or more devices. The notification unit 14 notifies that the device has entered the first range by a first voice.

[0097] Thus, the operator can confirm the configuration of the device regardless of the display of the display unit 13. Here, the first range is, for example, a range such as the following: when the position and posture of the device to be configured are within the first range, it means that the device is close to the target configuration. Alternatively, the first range may be, for example, a range such as the following: when the position and posture of the device to be configured are within the first range, it means that the device is configured to the target configuration within the range of the allowable error.

[0098] Furthermore, the notification unit 14 sets a second range in advance for the target configuration corresponding to at least one of the one or more devices for which the first range is set. The second range is included in the first range. The notification unit 14 notifies the device that it has entered the second range by a second voice.

[0099] Thus, by receiving notifications based on different voices such as the first voice and the second voice, the operator can confirm the relationship between the configuration of the device to be configured and the target configuration corresponding to the device. Here, the second range is, for example, the following range, etc.: when the position and posture of the device to be configured are within the second range, it means that the device is configured to the target configuration within the range of the allowable error. Alternatively, the second range may also be a range that includes the third range. The third range is, for example, the following range, etc.: when the position and posture of the device to be configured are within the third range, it means that the device is configured to the target configuration within the range of the allowable error.

[0100] Furthermore, the imaging device 8 is installed so as not to move from the start to the end of the arrangement work.

[0101] Thus, the position of the imaging device 8 can be used as a reference, so the support system 1 can guide the arrangement work more accurately.

[0102] Furthermore, when the one or more devices in the arrangement operation include the hoisting machine 3 , the imaging device 8 is arranged vertically above or vertically below the sheave 6 of the hoisting machine 3 .

[0103] Furthermore, when one or more devices in the arrangement operation include a car door device, the imaging device 8 is arranged on the rear wall of the car room of the car in which the car door device is installed.

[0104] In this way, the imaging device 8 is arranged at a position suitable for guiding the arrangement of the equipment, so that the support system 1 can guide the arrangement work more accurately.

[0105] In addition, the target configuration acquisition unit 12 may also acquire the target configuration corresponding to each device based on design information such as a design drawing. For example, when the configuration operation is the installation operation of a new elevator, each device can be guided to the configuration based on the design information. In addition, the target configuration acquisition unit 12 may also acquire the target configuration of the device based on the relative configuration of the device to be configured in the configuration operation relative to the surrounding devices. For example, when the device to be configured in the configuration operation is the traction machine 3, the target configuration of the traction machine 3 may be acquired based on the horizontal distance between the sheave groove 7 of the sheave 6 of the traction machine 3 and the edge of the rope duct in the machine room. Thus, the auxiliary system 1 can guide the sheave 6 to the following configuration: the traction rope 2 descending from the sheave groove 7 in the hoistway is not likely to interfere with the edge of the rope duct. At this time, for example, when the configuration operation is a replacement operation, the diameter of the sheave 6 or the number of sheave grooves 7 may also change before and after the replacement.

[0106] In addition, in the configuration operation such as replacement operation or maintenance inspection operation of elevator equipment, at least one of more than one equipment may be configured at a position after the elevator equipment that has been configured before the configuration operation is removed. In this case, the target configuration acquisition unit 12 may also acquire the target configuration corresponding to the equipment based on the configuration of the already configured equipment before it is removed. For example, in the case where the configuration operation includes a process of replacing the already installed hoisting machine 3 with the newly installed hoisting machine 3, the target configuration acquisition unit 12 detects the configuration of the sheave groove 7 of the already installed hoisting machine 3 before removal by image recognition of the image of the already installed hoisting machine 3 captured by the imaging unit. The target configuration acquisition unit 12 obtains the configuration of the sheave groove 7, for example, the configuration in which the position of the sheave groove 7 does not change before and after the replacement, as the target configuration of the newly installed hoisting machine 3 based on the acquired position of the sheave groove 7. In this case, the operator does not need to input the target configuration from the input unit 11. As a result, the operability of the configuration operation is improved. In addition, in the maintenance inspection operation of the elevator equipment, for example, the equipment that has been configured before the configuration operation and the equipment that is configured to the position and posture of the equipment in the configuration operation may be the same equipment.

[0107] In addition, the storage unit 10 stores a preset order of arrangement of one or more devices in the arrangement operation. At this time, the target arrangement acquisition unit 12 may also acquire a target arrangement corresponding to the device according to the relative arrangement of the device arranged before the device in the order stored in the storage unit 10 for at least one of the one or more devices. At this time, the target arrangement acquisition unit 12 determines whether the device is arranged in accordance with the order stored in the storage unit 10. The target arrangement acquisition unit 12 acquires a target arrangement based on the relative arrangement of the device when the arrangement order of the device follows the order stored in the storage unit 10. For example, in the arrangement operation, when the motor 5 and the sheave 6 of the hoisting machine 3 are arranged separately in this order, the target arrangement acquisition unit 12 acquires the target arrangement of the sheave 6 according to the position or posture where the motor 5 is arranged. The storage unit 10 may also store information on the relative arrangement of the motor 5 and the sheave 6 of the hoisting machine 3. At this time, the target arrangement acquisition unit 12 may also acquire the target arrangement of the sheave 6 according to the position or posture of the arranged motor 5 by referring to the relative arrangement of the sheave 6 from the storage unit 10. At this time, interference with the already arranged device can be suppressed.

[0108] Next, use Figure 10 to Figure 12 A specific example of extracting a characteristic portion of a device will be described.

[0109] Figure 10 to Figure 12 This is a diagram showing an example of extraction of a characteristic portion by the object arrangement acquisition unit 12 according to the first embodiment.

[0110] In this example, the target configuration acquisition unit 12 extracts the characteristic part by an image processing method such as template matching. As the characteristic part of the device, the target configuration acquisition unit 12 extracts, for example, the corner of the contour of the device, which is an example of a point indicating the position and posture of the device.

[0111] exist Fig.10 , an image of a device captured by the camera 8 and a model image of the device are shown. The model image of the device is, for example, a similar image of the device captured in the past or a similar image generated based on design information of the device. A similar image based on design information is, for example, a CAD image (CAD: Computer Aided Design). In addition, in the model image of the device, the characteristic part of the device is known.

[0112] The target configuration acquisition unit 12 detects the position of the device on the captured image by scanning the model image on the captured image captured by the imaging device 8. The target configuration acquisition unit 12 may scan the model image while performing image transformation such as affine transformation or homography transformation including enlargement and reduction and rotation of the model image. The target configuration acquisition unit 12 calculates the similarity or difference between the range on the captured image on which the model image is superimposed and the model image while scanning the model image.

[0113] Then, if Fig.11 As shown, the target configuration acquisition unit 12 detects the position with the greatest similarity or the position with the least dissimilarity as the position of the device on the captured image. In addition, when the model image is rotated or converted such as enlarged or reduced during scanning, the target configuration acquisition unit 12 may also detect conversion parameters such as the rotation angle of the model image and the magnification of the enlargement or reduction.

[0114] Then, if Fig.12 As shown, the target configuration acquisition unit 12 sets the configuration of the characteristic part of the model image configured at the position detected by scanning as the configuration of the characteristic part of the device on the captured image. The characteristic part in the model image is known, so the target configuration acquisition unit 12 can extract the configuration of the characteristic part of the device on the captured image by the position of the model image detected during scanning and the converted parameters.

[0115] Next, use Fig.13 and Fig.14 Another specific example of extracting a characteristic portion of a device will be described.

[0116] Fig.13 and Fig.14 This is a diagram showing another example of extraction of characteristic portions by the target arrangement acquisition unit 12 according to the first embodiment.

[0117] like Fig.13 As shown, the image of the device on the captured image and the model image may not be strictly consistent. In this case, the object arrangement acquisition unit 12 detects the approximate position of the device on the captured image by scanning the model image.

[0118] Then, if Fig.14 As shown, the target configuration acquisition unit 12 sets a processing area for performing detailed detection of the characteristic portion in an area including the configuration of the characteristic portion of the model image configured at the position detected by scanning, etc. In this example, the target configuration acquisition unit 12 sets two processing areas, namely, an upper processing area and a lower processing area.

[0119] The object arrangement acquisition unit 12 performs corner detection processing in each set processing area. In the corner detection processing, for example, a well-known algorithm such as Harris corner detection or Shi-Tomasi corner detection can be applied. The object arrangement acquisition unit 12 extracts the corners detected in this way as feature parts.

[0120] Next, use Fig.15 Another specific example of extracting a characteristic portion of a device will be described.

[0121] Fig.15 This is a diagram showing another example of extraction of characteristic portions by the target arrangement acquisition unit 12 according to the first embodiment.

[0122] The target configuration acquisition unit 12 calculates image feature quantities in the model image and the captured image respectively. The image feature quantities calculated here are, for example, SIFT (Scale-Invariant Feature Transform), SURF (Speed ​​Up Robust Feature), or HOG (Histogram of Oriented Gradient). The image feature quantities calculated here are rotation-invariant and scale-invariant features. Fig.15 For example, key points detected by feature quantities such as SIFT are shown.

[0123] The target configuration acquisition unit 12 matches the key points detected in the model image with the key points detected in the captured image. Thus, the target configuration acquisition unit 12 can detect the position of the device on the captured image. Even when the device is rotated or enlarged or reduced in the captured image, matching can be performed by using rotation-invariant and scale-invariant feature quantities.

[0124] The target configuration acquisition unit 12 sets the configuration of the characteristic part of the model image after matching as the configuration of the characteristic part of the device on the captured image. Alternatively, the target configuration acquisition unit 12 may set a processing area for performing detailed detection of the characteristic part in an area including the configuration of the characteristic part of the model image after matching. In this case, the target configuration acquisition unit 12 performs corner detection processing in each set processing area, thereby extracting the detected corner as the characteristic part.

[0125] In addition, if Fig.16 As shown, the target arrangement acquisition unit 12 may extract, as a characteristic portion of a device, for example, an edge of a contour of the device as an example of a line indicating the position and posture of the device. Fig.161 is a diagram showing another example of the extraction of the feature part by the target configuration acquisition unit 12 of the first embodiment. The target configuration acquisition unit 12 extracts the edge as the feature part through the same steps as the case of extracting the corner as the feature part. Here, in the edge detection process, for example, a well-known algorithm such as Canny's edge detection can be applied. In the edge detection process, noise removal and line differentiation can also be performed. By displaying the edge as a guide image that is intuitive and easier to understand, the operator can more easily perform the equipment configuration work.

[0126] In addition, if Fig.17 As shown, the object arrangement acquisition unit 12 may acquire a plurality of candidates for the object arrangement of the device based on the image of the device captured by the image capture device 8 . Fig.17 1 is a diagram showing an example of the object configuration acquired by the object configuration acquisition unit 12 in Embodiment 1. Candidates for the object configuration of a device are, for example, candidates for characteristic parts of the device, etc. In this example, candidates for characteristic parts are, for example, a plurality of corners extracted by an image processing method.

[0127] At this time, the guidance system 9, for example, presents multiple candidates of the target configuration to the operator through the display unit 13. The operator selects one or more candidates from the multiple candidates of the presented target configuration through the input unit 11. The target configuration acquisition unit 12 extracts the candidate selected by the operator as the target configuration of the device. In this example, the candidate not selected by the operator is excluded from the target configuration of the device. As a result, the operator can easily input the target configuration.

[0128] In addition, the guide image representing the target configuration corresponding to at least one of the one or more devices may be an image of the device configured in the target configuration. For example, in a case where the configuration operation includes a process of replacing the already installed hoisting machine 3 with a newly installed hoisting machine 3, the display unit 13 may also display the image of the already installed hoisting machine 3 before removal as a guide image and overlap it on the image of the newly installed hoisting machine 3 configured in the configuration operation. At this time, the image of the already installed hoisting machine 3 as a guide image is overlapped and displayed as a semi-transparent image so that the position can be compared with the image of the newly installed hoisting machine 3. Alternatively, the image of the already installed hoisting machine 3 as a guide image may be overlapped and displayed as an image of only the outline, for example.

[0129] Fig.18 This is a configuration diagram of a support system 1 according to a modified example of the first embodiment.

[0130] The guidance system 9 has a communication unit 18. The communication unit 18 is a part that outputs information to an external device of the guidance system 9 in a wired or wireless manner. The communication unit 18 can also output information to an external device through a communication network such as the Internet. The communication unit 18 outputs information of a target configuration or information of a guidance image, for example. The communication unit 18 outputs information to a display device 19 outside the guidance system 9, for example. The display device 19 can also be a mobile information terminal such as a smart phone carried by an operator. In addition, the operator can also wear the display device 19 during the configuration operation. The display device 19 is, for example, a device such as an HMD (Head Mounted Display) that displays the input image superimposed on the image of the operator's field of view. The display device 19 displays images, for example, through AR technology (AR: Augmented Reality) or VR technology (VR: Virtual Reality). As a result, the operator can confirm the configuration relationship between the device and the target configuration while performing the configuration operation, thereby improving the operation efficiency of the configuration operation. In addition, the information on the target arrangement or the guide image may be information obtained as three-dimensional information from images captured by a plurality of cameras of the imaging device 8 .

[0131] Fig.19 This is a diagram showing an example of acquisition of a target arrangement by the target arrangement acquisition unit 12 according to another modification of the first embodiment.

[0132] like Fig.19 As shown, the target configuration acquisition unit 12 acquires the target configuration based on the image captured by the camera 8 before the already configured equipment is removed and the image captured by the camera 8 after the equipment is removed. For example, in a case where the configuration operation includes a process of replacing the already installed hoisting machine 3 with the newly installed hoisting machine 3, the target configuration acquisition unit 12 acquires the image of the already installed hoisting machine 3 before it is removed. In addition, the target configuration acquisition unit 12 acquires the image of the already installed hoisting machine 3 after it is removed. The target configuration acquisition unit 12 extracts the position or posture of the already installed hoisting machine 3 in the image captured by the camera 8 by taking the difference of the acquired images. The target configuration acquisition unit 12 acquires the target configuration corresponding to the position or posture of the newly installed hoisting machine 3 based on the extracted position of the already installed hoisting machine 3.

[0133] Next, use Fig. 20 An example of the hardware configuration of the support system 1 will be described.

[0134] Fig. 20 This is a hardware configuration diagram of the main parts of the support system 1 according to the first embodiment.

[0135] Each function of the support system 1 can be realized by a processing circuit. The processing circuit has at least one processor 100a and at least one memory 100b. The processing circuit may also have at least one dedicated hardware 200 together with the processor 100a and the memory 100b, or instead of them.

[0136] When the processing circuit has a processor 100a and a memory 100b, each function of the auxiliary system 1 is implemented by software, firmware, or a combination of software and firmware. At least one of the software and firmware is described as a program. The program is stored in the memory 100b. The processor 100a reads out and executes the program stored in the memory 100b, thereby implementing each function of the auxiliary system 1.

[0137] The processor 100a is also called a CPU (Central Processing Unit), a processing device, an arithmetic device, a microprocessor, a microcomputer, or a DSP. The memory 100b is composed of a nonvolatile or volatile semiconductor memory such as a RAM, a ROM, a flash memory, an EPROM, or an EEPROM.

[0138] In the case where the processing circuit has dedicated hardware 200, the processing circuit is implemented by, for example, a single circuit, a complex circuit, a programmed processor, parallel programmed processors, an ASIC, an FPGA, or a combination thereof.

[0139] Each function of the auxiliary system 1 can be implemented by a processing circuit separately. Alternatively, each function of the auxiliary system 1 can also be implemented uniformly by a processing circuit. Regarding each function of the auxiliary system 1, a part can be implemented by dedicated hardware 200, and another part can be implemented by software or firmware. In this way, the processing circuit implements each function of the auxiliary system 1 through dedicated hardware 200, software, firmware, or a combination thereof.

[0140] Implementation Method 2

[0141] The support system 1 of the first embodiment acquires the target configuration corresponding to the hoisting machine 3 based on the input from the operator. The support system 1 of the second embodiment learns the relationship between the image captured by the imaging device 8 and the target configuration inputted in the image by the operator through the input unit 11 in the past through machine learning. Furthermore, the support system 1 infers the target configuration in the image captured by the imaging device 8 using the learned model generated by learning.

[0142] Fig.21 2 is a block diagram of the guidance system 9 according to the second embodiment. The guidance system 9 according to the second embodiment further includes a learning unit 20 and an inference unit 21 .

[0143] The learning unit 20 obtains a set of an image captured by the camera 8 and a target configuration input by the operator for the image through the input unit 11 in the past as learning data. Here, the learning data is data obtained by associating the image captured by the camera 8 and the target configuration input by the operator for the image. The learning unit 20 learns the target configuration in the image captured by the camera 8 based on the acquired learning data. That is, a learning model for inferring the optimal target configuration based on the image captured by the camera 8 is generated. In addition, the image captured by the camera 8 is, for example, the same as in Embodiment 1, an image of an area where equipment is configured from vertically above. Here, the combination of data included in the learning data corresponds to the process of configuring the operation. For example, in the process of newly configuring equipment, the image captured by the camera 8 is an image that does not include the equipment. Thus, the combination of the image captured by the camera 8 and the target configuration input by the operator for the image is obtained as learning data. In addition, in the process of replacing an existing equipment with a newly installed equipment, the image captured by the camera 8 is an image that includes the existing equipment. Thereby, a combination of the image captured by the imaging device 8 and the object arrangement input by the worker with respect to the image is acquired as learning data.

[0144] Next, use Fig. 22 and Fig.23 An example of a learned model learned by the learning unit 20 will be described. Fig. 22 and Fig.23 : is a diagram showing an example of a learned model in the learning unit 20 of the second embodiment. The learning unit 20 can perform learning using a known learning algorithm such as supervised learning or reinforcement learning. As an example, a learning algorithm based on supervised learning using a neural network is described. In this example, the learning unit 20 learns the target configuration for the image data of the installed hoisting machine 3 through supervised learning according to the neural network model. Here, supervised learning refers to the following method: by providing a group of input and output data to a learning device such as the learning unit 20, the features in these learning data are learned, and a learned model is generated. The learned model generated here is used for inference of the output based on the input by an inference device such as the inference unit 21.

[0145] A neural network includes an input layer consisting of multiple neurons, an intermediate layer consisting of multiple neurons, and an output layer consisting of multiple neurons. In each neuron, an activation function is applied to the input value and output. The activation function is, for example, a nonlinear function such as a sigmoid function or a ramp function.

[0146] For example, if it is Fig. 22In the three-layer neural network shown in the figure, when multiple inputs are input to the input layer (X1, X2, X3, ...), the output value is multiplied by the weight W0 (w01, w02, w03, ...) and input to the middle layer (Y1, Y2, ...). In addition, the output value from the middle layer is further multiplied by the weight W1 (w11, w12, w13, ...) and input to the output layer (Z1, Z2, Z3, ...). Each neuron in the output layer outputs output data according to the input value. In this way, the output of the neural network changes according to the value of each component of the weight vectors W0 and W1. In this example, the learned model is represented by the weight vectors W0 and W1.

[0147] Or, if Fig.23 As shown, a learning algorithm using a neural network with more than two intermediate layers can also be applied. If it is such a neural network, when multiple inputs are input to the input layer (X1, X2, X3, ...), the output value is multiplied by the weight W0 (w01, w02, w03, ...) and input to the first intermediate layer (Y11, Y12, ...). In addition, the output value from the first intermediate layer is further multiplied by the weight W1 (w11, w12, w13, ...) and input to the second intermediate layer. Repeat this step in the same way, assuming that the integer n is a natural number greater than 2, and the output value from the nth intermediate layer is further multiplied by the weight Wn (wn1, wn2, wn3, ...) and input to the output layer. Each neuron in the output layer outputs output data according to the input value. In this way, the output through the neural network will change according to the value of each component of the weight vector W0, W1, ..., Wn. In this example, the learned model is represented by the weight vector W0, W1, ..., Wn. In addition, the connection between adjacent layers may not be fully connected. For example, a neural network may also include a convolutional layer, etc. In addition, a neural network may also include a pooling layer, etc.

[0148] The data input to the input layer may be, for example, the feature quantity of the image extracted from the image. The feature quantity of the image may include, for example, the position of the edge in the image. The data input to the input layer may also include, for example, information such as a label for determining the type of device configured as the target configuration. The data output from the output layer may be, for example, the position and posture of the target configuration of the device. In the case where the target configuration can be labeled, the data output from the output layer may also be a value such as the probability of attaching each label as the target configuration.

[0149] In the second embodiment, the neural network of the learning unit 20 learns the object configuration in the image data captured by the camera 8 by so-called supervised learning according to the learning data, which is produced based on the combination of the image captured by the camera 8 and the object configuration on the image that was previously input by the operator through the input unit 11. That is, the neural network adjusts the weight vectors W0 and W1, etc., so that the result of the image captured by the camera 8 being input to the input layer and the object configuration output from the output layer, that is, the object configuration, is close to the object configuration that was previously input by the operator through the input unit 11, thereby learning. The learning unit 20 can learn according to the learning data by a known method such as the error back propagation method, for example.

[0150] The learning unit 20 generates a learned model by executing the above-described learning. The storage unit 10 stores the learned model generated by the learning unit 20.

[0151] In addition, the case where supervised learning is applied in the learning algorithm used in the learning unit 20 is described, but it is not limited to this. Regarding the learning algorithm, it only needs to be able to learn the relationship between the image captured by the camera 8 and the target configuration, and other well-known methods such as genetic programming, functional logic programming or support vector machines can also be used for machine learning. In addition, as a learning algorithm used in the learning unit 20, deep learning (DeepLearning) that learns the extraction of image feature quantities itself can also be used. In addition, the learning unit 20 can also use algorithms such as reinforcement learning to learn the relationship between the image captured by the camera 8 and the target configuration. The reward for reinforcement learning can be, for example, an evaluation input by an operator after the operation, or it can be the time or working hours required for the operation.

[0152] In addition, the data input to the input layer may also be the image data itself. The image data input when the learning unit 20 performs learning includes not only the image captured by the camera 8, but also the CG image (CG: Computer Graphics) generated using the three-dimensional CAD, etc. The image data input when learning may also be image data after the CG image is converted in a manner similar to the actual image captured by the camera 8. In this case, the image data input when learning is generated, for example, by a technique such as GAN (Generative Adversarial Network). In the GAN at this time, for example, as a generation network, a network that generates similar images for learning is used. In addition, as a recognition network, a network that recognizes the actual image captured by the camera 8 and the similar image generated by the generation network is used. By increasing the number of images for learning in this way, the accuracy of learning in the learning unit 20 can be improved. In addition, the data of the target configuration related to the image data generated in this way can be manually set by an operator, etc., or can be automatically set based on information of components of the three-dimensional CAD data that is the basis of the CG image, etc.

[0153] The inference unit 21 infers the object arrangement in the image captured by the imaging device 8 using the learned model. That is, by inputting the image captured by the imaging device 8 to the learned model, the object arrangement inferred from the image can be output.

[0154] Next, use Fig.24 An example of the learning process in the learning unit 20 will be described. Fig.24 2 is a flowchart showing an example of the operation of the support system 1 according to the second embodiment. Fig.24 , an example of the learning process in the learning unit 20 is shown.

[0155] Here, the support system 1 of the second embodiment uses Figure 6 The image of the installed traction machine 3 obtained by the operation of the auxiliary system 1 shown in the figure and the target configuration input by the operator are used as learning data. Figure 6 After the processing shown in the figure, the following learning processing is performed. Figure 6 The following learning process is performed during the processing shown, and this process is repeated.

[0156] In step S21, the learning unit 20 obtains learning data, which is created based on a combination of an image captured by the imaging device 8 and a target configuration previously input by the operator for the image through the input unit 11. In the second embodiment, the learning unit 20 simultaneously obtains the image and target configuration of the installed hoisting machine 3, but the learning unit 20 may input the image and target configuration of the installed hoisting machine 3 in association with each other, or obtain the image and target configuration data of the installed hoisting machine 3 at different times.

[0157] Then, in step S22, the learning unit 20 learns the target configuration of the equipment in the image data captured by the shooting device 8 through supervised learning according to the learning data, and generates a learned model. The learning data is produced based on a combination of the image captured by the shooting device 8 and the target configuration input by the operator for the image through the input unit 11 in the past.

[0158] Then, in step S23 , the storage unit 10 stores the learned model generated by the learning unit 20 .

[0159] Next, use Fig.25 An example of inference processing of the inference unit 21 for the object arrangement in the image captured by the imaging device 8 will be described. Fig.25 2 is a flowchart showing an example of the operation of the support system 1 according to the second embodiment. Fig.25 In the example of the inference processing in the inference unit 21, Figure 6 The actions involved in the inference processing are performed in step S11, and the subsequent actions are Figure 6 Same action as shown.

[0160] In step S31 , the inference unit 21 acquires an image captured by the imaging device 8 .

[0161] Then, in step S32, the inference unit 21 inputs the image captured by the imaging device 8 to the learned model stored in the storage unit 10. The inference unit 21 obtains the target arrangement for the image data captured by the imaging device 8 based on the output of the learned model.

[0162] Then, in step S33, the inference unit 21 outputs the target configuration for the image data captured by the image capturing device 8 obtained by the learned model. The target configuration is the target configuration of any equipment of the elevator to be configured in the area of ​​the image in the configuration operation. The target configuration acquisition unit 12 acquires the target configuration output by the inference unit 21 as the target configuration of the equipment. Then, the operation of the auxiliary system 1 enters Figure 6 In step S12, the output target configuration is displayed superimposed on the image captured by the camera 8.

[0163] As described above, the support system 1 of the second embodiment has a learning unit 20. The learning unit 20 generates a learned model by machine learning using learning data. The learning data includes an image captured by the camera 8 and a target configuration of equipment configured in the area of ​​the image in the elevator equipment. The learned model is used to infer the target configuration based on the image captured by the camera 8. In addition, the support system 1 has an inference unit 21. The inference unit 21 uses the learned model to infer the target configuration of the equipment based on the image captured by the camera. The guidance system 9 obtains the target configuration corresponding to the equipment based on the inference of the inference unit 21. According to this structure, the operator does not need to input the target configuration through the input unit 11, and the effect of reducing the burden of the operator inputting the target configuration and the effect of being able to determine the target configuration even if not an expert can be obtained.

[0164] In addition, in embodiment 2, it is explained that the inference unit 21 uses the learned model generated by the learning unit 20 of the auxiliary system 1 to output the target configuration for the image data captured by the shooting device 8, but the inference unit 21 can also obtain the learned model generated by an external system (not shown) of the auxiliary system 1, and output the target configuration for the image data captured by the shooting device 8 based on the learned model obtained from the external system.

[0165] In addition, one or both of the learning unit 20 and the inference unit 21 may be mounted on a device connected via a communication network such as the Internet and arranged outside the building where the elevator is installed. For example, the learning unit 20 may be mounted on a learning device that is an independent device. In addition, the inference unit 21 may be mounted on an inference device that is an independent device. In addition, one or both of the learning unit 20 and the inference unit 21 may be mounted on a virtual machine on a cloud service, etc.

[0166] In addition, the learning unit 20 may also use learning data produced in a plurality of elevators for learning. In this case, the plurality of elevators may be installed in different buildings. In addition, the plurality of elevators may be elevators operating in the same area. Alternatively, the plurality of elevators may be elevators operating in multiple areas. Elevators that are objects of obtaining learning data in the learning unit 20 may also be added or excluded in the middle of the operation of the auxiliary system 1. In addition, the learning unit 20 of a certain auxiliary system 1 may also obtain a learned model generated by the learning unit 20 of another auxiliary system 1. In this case, the learning unit 20 of the auxiliary system 1 that has obtained the learned model may also relearn by using the learning data obtained in the auxiliary system 1 to update the learned model.

[0167] Next, use Fig.26 A modification example of the second embodiment will be described.

[0168] Fig.26 1 is a diagram showing an example of display by the display unit 13 of a modified example of Embodiment 2. In this modified example, the learned model is a model that can infer the target configuration of the device configured in the area of ​​the image captured by the imaging device 8 and the characteristic part of the device. The characteristic part of the device inferred in the learned model is one or more characteristic parts.

[0169] Next, the configuration operation of configuring the hoisting machine 3 is described as an example. In this example, the existing hoisting machine is replaced with a newly installed hoisting machine 3. In the configuration operation, after the existing hoisting machine is removed, the newly installed hoisting machine 3 is temporarily placed near the target configuration. At this time, the camera 8 captures an area including both the temporarily placed newly installed hoisting machine 3 and the position of the target configuration.

[0170] The learning unit 20 obtains a group of the image captured by the imaging device 8, the target configuration of the newly installed hoisting machine 3 inputted by the operator through the input unit 11 for the image in the past, and the characteristic part of the newly installed hoisting machine 3 temporarily placed in the image as learning data. The characteristic part of the newly installed hoisting machine 3 is inputted by the operator through the input unit 11, for example. The characteristic part of the newly installed hoisting machine 3 can also be input together with the input of the target configuration, for example. In addition, the learned model in the learning unit 20 can also be a composite model that independently includes a model for obtaining the target configuration and a model for obtaining the characteristic part. At this time, the learning unit 20 can also independently obtain: learning data for the model for obtaining the target configuration and learning data for the model for obtaining the characteristic part.

[0171] The inference unit 21 uses the learned model based on the learning unit 20 to infer the target configuration of the newly installed hoisting machine 3 and the characteristic portion of the newly installed hoisting machine 3 temporarily placed in the image based on the image captured by the imaging device 8. In the guidance system 9, based on the target configuration and characteristic portion of the newly installed hoisting machine 3 inferred in this way, the newly installed hoisting machine 3 is guided to the target configuration. For example, Fig.26 As shown, the display unit 13 displays a guide image superimposed on the image captured by the camera 8. In this example, an image showing the position and posture of the sheave 6 of the newly installed hoisting machine 3 configured in the target configuration is shown as a guide image. In this image, the position of the characteristic portion of the newly installed hoisting machine 3 when it is configured in the target configuration is shown. In addition, the position of the characteristic portion of the newly installed hoisting machine 3 that will be configured in the target configuration from the temporary placement position thereafter is shown as a guide image. According to this structure, the characteristic portion of the current device and the characteristic portion of the device after being configured in the target configuration are displayed at the same time, so that the auxiliary system 1 can guide the configuration operation more effectively. Therefore, the operability of the configuration operation can be improved.

[0172] Industrial Applicability

[0173] The auxiliary system disclosed in the present invention can be applied to the configuration work of elevator equipment.

[0174] Description of symbols

[0175] 1: auxiliary system; 2: traction rope; 3: traction machine; 4: traction machine base; 5: motor; 6: sheave; 7: sheave groove; 8: camera; 9: guidance system; 10: storage unit; 11: input unit; 12: target configuration acquisition unit; 13: display unit; 14: notification unit; 15: floor station sill; 16: floor stop device; 17: detection unit; 18: communication unit; 19: display device; 20: learning unit; 21: reasoning unit; 100a: processor; 100b: memory; 200: dedicated hardware.

Claims

1. An auxiliary system for configuration work of an elevator device, comprising: A photographing device for photographing an area including positions of target configurations corresponding to the one or more devices of the elevator, during a configuration operation of respectively configuring the one or more devices of the elevator into corresponding target configurations; and A guidance system guides the configuration of the one or more devices into corresponding target configurations according to the images captured by the camera.

2. The auxiliary system for configuration work of elevator equipment according to claim 1, wherein: The boot system stores a pre-set order of configuration of the one or more devices in the configuration operation, and determines whether, for at least any one of the one or more devices, the device is configured in accordance with the stored order. If the configuration order is in accordance with the stored order, the target configuration corresponding to the device is obtained based on the relative configuration of the device configured before the device in the stored order.

3. The auxiliary system for configuration work of an elevator device according to claim 1 or 2, wherein: When at least one of the one or more devices is to be arranged at a position after removing the elevator device that has been arranged before the arrangement operation, the guidance system obtains a target arrangement corresponding to the device based on the arrangement of the already arranged device before being removed.

4. The auxiliary system for elevator equipment configuration work according to any one of claims 1 to 3, wherein: The guidance system acquires the target arrangement based on a difference between an image captured by the imaging device before the arranged device is removed and an image captured by the imaging device after the device is removed.

5. The auxiliary system for configuration work of an elevator device according to any one of claims 1 to 4, wherein: In the guidance system, the target arrangement corresponding to at least any one of the one or more devices is acquired based on an input from an operator who performs the arrangement work.

6. The auxiliary system for configuration work of elevator equipment according to claim 5, wherein: In the guidance system, the target arrangement corresponding to at least any one of the one or more devices is acquired based on a candidate selected by an operator performing the arrangement work from a plurality of candidates presented to the operator by the guidance system.

7. The auxiliary system for configuration work of an elevator device according to any one of claims 1 to 6, wherein: The guidance system includes a display unit configured to display, for at least any one of the one or more devices, a guidance image indicating an object arrangement corresponding to the device in a superimposed manner on the image captured by the imaging device.

8. The auxiliary system for elevator equipment configuration work according to any one of claims 1 to 7, wherein: The guidance system includes a communication unit that outputs a guidance image representing a target configuration corresponding to at least one of the one or more devices to a display device, and the display device displays the input image by overlapping it with an image in the field of view of an operator performing the configuration operation.

9. The auxiliary system for configuration work of an elevator installation according to claim 7 or 8, wherein: The guide image indicating the object arrangement corresponding to at least any one of the one or more devices is an image of the device arranged in the object arrangement.

10. The auxiliary system for configuration work of an elevator installation according to claim 7 or 8, wherein: The guide image indicating the object arrangement corresponding to at least any one of the one or more devices is an image of one or more characteristic parts of the device arranged in the object arrangement.

11. The auxiliary system for configuration work of an elevator installation according to any one of claims 1 to 10, wherein: The guidance system includes a notification unit configured to notify, by a first voice, at least any one of the one or more devices that the device has entered a first range preset for a target arrangement corresponding to the device.

12. The auxiliary system for configuration work of an elevator installation according to claim 11, wherein: The notification unit notifies at least one of the one or more devices for which the first range is set, through a second voice, that the device has entered a second range included in the first range and preset for a target configuration corresponding to the device.

13. The auxiliary system for configuration work of an elevator installation according to any one of claims 1 to 12, wherein: The photographing device is arranged not to move from the beginning to the end of the configuration work.

14. The auxiliary system for configuration work of an elevator installation according to any one of claims 1 to 13, wherein: When the one or more devices in the arrangement operation include a hoisting machine, the imaging device is arranged vertically above or vertically below a sheave of the hoisting machine. The guide system guides the sheave to be arranged in a target arrangement based on the sheave groove of the sheave.

15. The auxiliary system for configuration work of an elevator installation according to any one of claims 1 to 13, wherein: When the one or more devices in the configuration operation include a floor stop device, the camera is arranged in the car vertically above or vertically below the floor stop device, and the floor stop device has a detection unit that detects the floor stop of the car at each floor. The guide system guides the floor stop device to be configured into a target configuration based on the groove of the detection part. In the floor stop device, the floor stop plates arranged on each floor pass through the groove of the detection part when the car travels.

16. The auxiliary system for configuration work of an elevator installation according to any one of claims 1 to 15, wherein: The auxiliary system has a learning unit that uses the following learning data to generate a learned model for inferring target configuration based on the image taken by the shooting device through machine learning, and the learning data includes the image taken by the shooting device and the target configuration of the device among the one or more devices configured in the area of ​​the image.

17. The auxiliary system for configuration work of an elevator installation according to any one of claims 1 to 16, wherein: The auxiliary system includes an inference unit that uses the following learned model to infer the target configuration of the device based on the image captured by the camera, the learned model is generated by machine learning using the following learning data, and is used to infer the target configuration based on the image captured by the camera, the learning data including the image captured by the camera and the target configuration of the device in the area of ​​the image that is configured in the one or more devices, The guidance system acquires a target configuration corresponding to the device based on the inference of the inference unit.

18. The auxiliary system for configuration work of an elevator installation according to claim 17, wherein: The learned model used by the inference unit in the inference is a learned model for inferring the target configuration of the device configured in the area of ​​the image among the one or more devices and one or more characteristic parts of the device based on the image captured by the imaging device, The inference unit infers the target configuration and one or more characteristic parts of the device based on the image captured by the imaging device. The guidance system guides the device to be configured into the target configuration inferred by the inference unit based on the target configuration inferred by the inference unit and one or more characteristic parts.

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