JP6499092B2 - Elevator load detection adjustment device and elevator - Google Patents

Description

  The present invention relates to an elevator load detection adjustment device and an elevator for adjusting a load detection value of a load detection device provided in a car.

  Conventionally, when an elevator is started to run a car, the elevator is controlled so that the car does not start suddenly due to the mass of the car or the counterweight, but runs smoothly. In this control, since it is necessary to detect the load in the car at the time of traveling, a load detection device for detecting the load in the car is attached to the car. This load detection device is configured to calculate the load in the car based on the mass of a user or an object that has entered the car from the amount of deflection of the vibration-proof rubber attached to the lower part of the car floor. . In order to calculate the load in the car, it is necessary to store the load detection values at the time of no load and the maximum load in the nonvolatile memory. The maximum loading time is when the loading capacity in the car is 100% of the maximum loading capacity allowed for the car (100% of the rated load).

  However, with the aging of the anti-vibration rubber, the anti-vibration rubber is cured, so that an error occurs between the load detection value of the load detection device and the actual load in the car. In general, in this type of load detection device, there is a possibility that a difference in load detection value may occur even when the load (mass) is the same, depending on the ambient temperature and changes in the mounting state. When a difference occurs in the load detection value, the car may move in the reverse direction at the time of departure, or may move so as to start suddenly, and the ride comfort may deteriorate.

  Therefore, the maximum load weight is prepared for the car at regular intervals, and load detection adjustment is performed in an actual load test. Alternatively, in the case where traveling with poor riding comfort such as popping out is detected due to a difference in the load detection value, the load detection value at the time of maximum loading is stored again and load detection adjustment is performed. As an example of load detection adjustment, a technique has been devised for calculating a load detection value at maximum loading from the weight data of the worker and the current load detection value of the car.

  For example, Patent Document 1 discloses an elevator load detection adjustment apparatus that can adjust a load detector with a simple operation without preparing multiple weights in an elevator car.

  In the technique disclosed in Patent Document 1, when the operator switches to the load detection adjustment mode by the changeover switch provided on the in-car operation panel and the operator operates the landing button with no load in the car, the control device The output data of the load detector at this time is written into the RAM. Next, the worker gets on the car, operates the operation buttons on the operation panel in the car, inputs the weight data of the worker, and the control device writes the output data of the load detector at this time in the RAM. Then, the gain coefficient and the overload load data are calculated from these data, and are written in the EEPROM together with the no-load load data. At the time of periodic inspection, the operator operates the operation button to input the weight data of the operator, and the control device writes the output data of the load detector at this time in the RAM. Further, when the weight data of the operator is input, the control device calculates the load detection value using each data written in the EEPROM. The control device compares the load detection value with the output data of the actual load detector, determines whether the error exceeds the error level, and notifies the display device of the necessity of adjustment based on the determination result. The controller rewrites the EEPROM data by readjustment as necessary, and adjusts so that the load amount can be accurately detected.

JP 7-330245 A

  When the technique described in Patent Document 1 is used, it is necessary for the expert engineer to go directly to the target elevator to calculate the load detection value at the time of maximum loading.

  However, since the difference in the load detection value occurs due to a change in ambient temperature or the like, even if the load detection value at the time of maximum loading is once adjusted, there is a possibility that the difference occurs after a certain period. For this reason, it is necessary to periodically adjust the load detection value, which leads to an increase in the amount of work by specialist engineers.

  The present invention has been made in consideration of the above situation, and is capable of adjusting the load detection value at the time of maximum loading without performing a special operation by a specialist engineer. And to provide an elevator.

  In one embodiment of the present invention, an image obtained by photographing passengers in a car is analyzed to identify passengers, and weight information of passengers registered in advance is acquired. Next, the car load at the time of maximum loading is calculated from the acquired weight information and the current car load detection value detected by the car load detection unit that outputs the load detection value corresponding to the car load. A maximum load detection value corresponding to the detection value is calculated. Then, the calculated maximum loading load detection value registered in the recording unit is compared with the calculated maximum loading load detection value to determine whether the maximum loading load detection value registered in the recording unit is good or bad. Based on the above, the maximum loading load detection value registered in the recording unit is corrected.

According to the present invention, it is possible to calculate a load detection value at the time of maximum loading without performing a special operation by a professional engineer, and it is possible to reduce the work amount of the professional engineer.
Problems, configurations, and effects other than those described above will be clarified by the following description of embodiments.

It is a figure showing the outline of the elevator concerning one embodiment of the present invention. It is a block diagram which shows the control system of the elevator which concerns on one Embodiment of this invention. FIG. 3A is an example of a face image database, and FIG. 3B is an example of a weight information database. It is a graph which shows the example of a relationship between a load detection value and load amount. It is a block diagram which shows the hardware structural example of the computer used for an elevator control apparatus. It is a flowchart which shows the operation example of the load detection adjustment apparatus of the elevator which concerns on one Embodiment of this invention. It is another example of a weight information database.

  Hereinafter, an example of an embodiment for carrying out the present invention will be described with reference to the accompanying drawings. In addition, in each figure, about the component which has the substantially same function or structure, the same code | symbol is attached | subjected and the overlapping description is abbreviate | omitted.

<1. One Embodiment>
[Elevator overview]
Drawing 1 is a figure showing the outline of the elevator concerning one embodiment.
In FIG. 1, an elevator 100 is wound around a hoistway 1 formed in a building structure, a car 6 on which a user rides, a hoisting machine 8a, a counterweight 10, a hoisting machine 8a, and a curling car 8b. The main rope 7 for suspending the car 6 and the counterweight 10 and the elevator control device 2 are provided.

  The hoistway 1 is formed in a building structure, and a machine room 1A is provided on the top thereof. The hoisting machine 8a is disposed in the machine room 1A, rotates forward or reverse by a motor (not shown), and moves the car 6 up and down by winding the main rope 7. Further, a curling wheel 8b on which the main rope 7 is mounted is provided in the vicinity of the hoisting machine 8a. Further, the hoisting machine 8a is provided with an encoder 9 that is directly connected to a motor (not shown) and generates a pulse proportional to the speed of the motor.

  The hoistway 1 is for a plurality of floors, and a landing door 13 is installed at each landing. The car 6 stops at the landing level 14 (depot) indicating the stop position of each floor according to the destination floor, and the car door 11 and the landing door 13 of the floor on which the floor is landed open. The announcement device 12 conveys information such as the arrival of the car 6 to the destination floor and the opening / closing state of the car door 11 to the user by voice or the like.

  The image recognition device 3 is installed on the back of the ceiling of the car 6 and is connected to the car camera 17 installed in the car 6. The image recognition device 3 detects and recognizes the user from the captured image of the car camera 17.

  A car load detecting device 4 for detecting a load applied to the car 6, that is, a load in the car 6, is attached to the center of the lower floor of the car 6. The image recognition device 3 and the car load detection device 4 are connected to an elevator control device 2 that controls the operation of the elevator 100 via a tail cord 5.

  The elevator control device 2 is connected to a monitoring center (not shown) that monitors the state of the elevator 100 via a telephone line or the like. If there is an abnormality in the elevator 100, the monitoring center performs control such as stopping the elevator 100 or operating the elevator 100 at a reduced speed.

[Control system of elevator load detection and adjustment device]
FIG. 2 is a block diagram showing a control system of the elevator 100.
The elevator 100 includes an image recognition device 3, a car load detection device 4, an elevator control device 2, an announcement device 12, and a car camera 17. The elevator control device 2, the image recognition device 3, and the car load detection device 4 are examples of components of the elevator load detection adjustment device 90. The car load detection device 4 can use a car load detection device that is generally set under the floor of the elevator car.

  The car load detector 4 includes a car load detector 41. The in-car load detection unit 41 calculates the mass of a user or an object that has entered the car 6 from the deflection amount of an unillustrated elastic device (for example, an anti-vibration rubber) attached to the lower floor of the car 6. Output data (load detection value) corresponding to the load in the car 6 is output. Further, the car load detection unit 41 transmits the current load detection value of the car 6 to the maximum load detection value calculation unit 21 in the elevator control device 2.

The image recognition device 3 includes a person determination unit 31 and a personal information database 32.
The person determination unit 31 acquires a photographed image in the car 6 photographed by the car camera 17 (an example of a photographing device), and identifies a passenger U (person) boarding the car 6 from the photographed image. The weight information of the specified person is acquired from the personal information database 32. The person determination unit 31 transmits the acquired weight information to the maximum loading load detection value calculation unit 21.

  In addition, the person determination unit 31 performs image processing such as noise removal on the captured image captured by the in-car camera 17. In addition, the person determination unit 31 analyzes the captured image on which the image processing has been performed, and outputs the analysis result to the maximum loading load detection value calculation unit 21. In the maximum load detection value calculation unit 21, it is determined based on the analysis result of the captured image input from the person determination unit 31 whether or not the passenger U is on the center part of the car floor. For example, a DSP (Digital Signal Processor) specialized for digital signal image processing may be used for the person determination unit 31.

[Personal information database]
The personal information database 32 includes a face image database 33a and a weight information database 33b.

FIG. 3 shows an example of the personal information database 32. FIG. 3A is an example of the face image database 33a, and FIG. 3B is an example of the weight information database 33b.
The record of the face image database 33a has a face image field and ID information (FIG. 3A). That is, in the face image database 33a, the face image of the passenger U and the ID information (an example of individual identification information) of the passenger U are registered in association with each other.

  The record of the weight information database 33b has an ID information field and a weight information field (FIG. 3B). In the example of FIG. 3B, when the ID is “001”, the weight is “60 kg”, and when the ID is “002”, the weight is “48 kg”.

  Registration of information in the personal information database 32 is performed by the maintenance console 18 carried by a professional engineer at the time of inspection. In addition, for registration of information in the personal information database 32, an operation panel (not shown) in the car 6 or a cryptographic operation performed by changing the function assignment of the call button may be used. Alternatively, the personal information database 32 may be created in advance by another device, and the personal information database 32 may be recorded in a non-illustrated nonvolatile recording unit of the image recognition device 3. The registered person is preferably a person who frequently uses the elevator, such as the owner, manager, guard, or resident of the building where the elevator 100 is installed.

  The person determination unit 31 searches the face image database 33a based on the photographed image (face image) of the in-car camera 17 and specifies the passenger U (ID information) boarding the car 6. Then, the weight information database 33 b is searched based on the ID information, and the weight information of the specified person is extracted from the personal information database 32.

  The face image database 33a and the weight information database 33b may be combined into one database. The personal information database 32 only needs to associate at least a face image and weight information.

  Returning to the description of FIG. The elevator control device 2 includes a maximum loading load detection value calculation unit 21, a maximum loading load detection value pass / fail determination unit 22, a maximum loading load detection value correction unit 23, and a maximum loading load detection value recording unit 24. Prepare. When the passenger U is carrying a heavy load or has a passenger, there is a difference between the load detection value output from the car load detection unit 41 and the weight information registered in the ID card C. Occur. In such a case, each part of the elevator control device 2 cooperates to correct the difference.

  The maximum loading load detection value calculation unit 21 (an example of a calculation unit) performs a process of calculating a maximum loading load detection value corresponding to the load detection value of the car 6 at the maximum loading. When the load detection adjustment is the initial adjustment, the maximum loading load detection value calculation unit 21 executes the following process. In the initial adjustment, the maximum load detection value calculation unit 21 loads the current load detection value in the car 6 transmitted from the car load detection unit 41, the weight information transmitted from the person determination unit 31, and nothing. The maximum load detection value at the time of loading is calculated from the load detection value transmitted from the in-car load detection unit 41 during loading. Then, the maximum load detection value calculation unit 21 uses each data (load detection value at no load, current load detection value, weight information) used when obtaining the maximum load detection value, and the maximum loading time. The load detection value is recorded in the maximum loading load detection value recording unit 24.

  When the load detection adjustment is performed after the second time, the maximum load detection value calculation unit 21 loads the current load detection value in the car 6 transmitted from the car load detection unit 41 and the person determination unit 31. The maximum loading load detection value is calculated from the transmitted weight information. Then, the maximum loading load detection value calculation unit 21 outputs the maximum loading load detection value to the maximum loading load detection value pass / fail determination unit 22.

  In addition, when the weight information is acquired, the maximum load detection value calculation unit 21 instructs the announcement command unit 25 to make an announcement for prompting the passenger U to get into the center of the car 6. . The center part of the floor board of the car 6 is a predetermined area including the center or the center. The in-car load detection device 4 is attached to the center of the lower floor of the car 6. Therefore, by making an announcement and positioning the passenger U at the center of the floor board in the car 6, the error during measurement can be minimized and the adjustment accuracy of the maximum load detection value can be increased.

[Example of relationship between load detection value and load]
FIG. 4 is a graph showing an example of the relationship between the load detection value and the load amount. A method of calculating the maximum load detection value will be described with reference to FIG.

  For example, in the initial adjustment, the operation is started when a specialist engineer operates a changeover switch on an operation panel (not shown) in the car 6 to establish a load detection adjustment mode. The operation panel and the elevator control device 2 are connected via a tail cord 5. The expert engineer gets down from the car 6 to the landing, puts the inside of the car 6 into an unloaded state, and presses a landing button (not shown), for example. By this operation, the load detection value D0 of the in-car load detection unit 41 when there is no load is transmitted to the maximum load detection value calculation unit 21.

  Next, when the professional engineer gets on the car 6, the in-car camera 17 photographs the professional engineer. The person determination unit 31 specifies that the person in the car 6 is a professional engineer from the photographed image, and acquires the weight information of the professional engineer registered in the personal information database 32 in advance. The person determination unit 31 transmits the weight information (see FIG. 4) of the load amount W1 acquired from the personal information database 32 to the maximum loading load detection value calculation unit 21. At this time, the car load detector 41 transmits the current load detection value D1 (see FIG. 4) in the car 6 to the maximum load detection value calculator 21. The maximum load detection value calculation unit 21 records the load detection value D0 at the time of no load, the weight information of the load amount W1, and the load detection value D1 in the current car 6 in the RAM 53 (see FIG. 5).

  Then, the maximum loading load detection value calculation unit 21 uses the load detection value D0 at the time of no load recorded in the RAM 53, the weight information of the load amount W1, and the load detection value D1 in the current car 6. A calculation formula for the maximum load detection value represented by the linear function L (see FIG. 4) is calculated. When the horizontal axis representing the load amount is x and the vertical axis representing the load detection value is y, the linear function L is expressed by the following equation (1).

      y = {(D1-D0) / W1} x + D0 (1)

  The maximum loading load detection value calculation unit 21 uses the linear function L, and the maximum loading to be transmitted from the car load detection unit 41 when the load amount Wmax is 100% of the maximum loading amount of the car 6. An hourly load detection value Dmax (see FIG. 4) is calculated and recorded in the RAM 53. Then, the maximum load detection value calculation unit 21 calculates the load detection value D0 at the time of no load, the weight information of the load amount W1, the load detection value D1 in the current car 6 and the maximum load detection value Dmax. The data is recorded in a nonvolatile recording unit such as a rewritable nonvolatile storage 57 (see FIG. 5).

  In the initial adjustment described above, the weight information of the load amount W1 is acquired from the personal information database 32. However, a specialist engineer may input his / her weight by operating the operation panel. Alternatively, the load detection value D0 at the time of no load, the load amount W1, and a calculation formula calculated from the load detection value D1 in the current car 6 and the maximum load detection value Dmax at the time of loading are calculated at the stage of factory shipment or the like. May be calculated in advance and recorded in the nonvolatile storage 57 or the like. Further, at the time of factory shipment or the like, each data may be recorded in the ROM 52 (see FIG. 5), and data calculated in the second and subsequent adjustments may be recorded in the nonvolatile storage 57 or the like.

  In the second and subsequent adjustments, for example, the passenger U who is not a professional engineer gets on the car 6 and the photographing is performed by the car camera 17, so that the load detection adjustment mode is established and the operation is started. The person determination unit 31 specifies that the person in the car 6 is a professional engineer from the photographed image, and acquires the weight information of the professional engineer registered in the personal information database 32 in advance. The person determination unit 31 transmits the weight information of the load amount W2 (see FIG. 4) acquired from the personal information database 32 to the maximum loading load detection value calculation unit 21. Further, at this time, the car load detection unit 41 transmits the current load detection value D2 (see FIG. 4) in the car 6 to the maximum load detection value calculation unit 21. The maximum load detection value calculation unit 21 records the weight information of the load amount W2 and the current load detection value D2 in the car 6 in the RAM 53 (see FIG. 5).

  Then, the maximum loading load detection value calculation unit 21 uses the load detection value D0 at the time of no load, the weight information of the load amount W2, and the load detection value D2 in the current car 6 recorded in the RAM 53, A calculation formula for the maximum load detection value represented by the linear function L ′ (see FIG. 4) is calculated. The linear function L ′ is expressed by the following equation (2).

      y = {(D2-D0) / W2} x + D0 (1)

  The maximum loading load detection value calculation unit 21 uses the linear function L ′ to transmit the maximum load to be transmitted from the car load detection unit 41 when the load amount Wmax is 100% of the maximum loading amount of the car 6. A load detection value Dmax ′ during loading (see FIG. 4) is calculated and recorded in the RAM 53. Then, the maximum loading load detection value calculation unit 21 outputs the maximum loading load detection value Dmax ′ to the maximum loading load detection value pass / fail determination unit 22.

  Returning to the description of FIG. The maximum loading load detection value pass / fail determination unit 22 (an example of a determination unit) is registered in the recording unit (last recorded) and the maximum loading load detection value calculated by the maximum loading load detection value calculation unit 21. The pass / fail detection value is compared with the maximum load detection value. The criterion for pass / fail judgment is, for example, whether or not the difference (rate of increase / decrease) between the two is within a specified value. If the difference exceeds the specified value, “No”, and if the difference is within the specified value, “Good”. To do. The maximum loading load detection value pass / fail determination unit 22 outputs the pass / fail determination result to the maximum load load detection value correction unit 23. In the present embodiment, the specified value is ± 10%, but is not limited to this example.

  The maximum loading load detection value correction unit 23 (an example of a correction unit) determines that the maximum loading load detection value calculation unit 21 determines that the determination result of the maximum loading load detection value pass / fail determination unit 22 is “No”. The result calculated this time will be positive, and the maximum load detection value will be corrected. On the other hand, the maximum loading load detection value correction unit 23 does not perform correction if the result of the pass / fail determination by the maximum load detection value pass / fail determination unit 22 is “good”.

  The maximum loading load detection value recording unit 24 (an example of a recording unit) is corrected by the maximum loading load detection value calculated by the maximum loading load detection value calculation unit 21 or the maximum loading load detection value pass / fail determination unit 22. Record the maximum loaded load detection value. For example, a nonvolatile storage 57 (see FIG. 5) or an EEPROM (not shown) is applied to the maximum load detection value recording unit 24. In the maximum load detection value recording unit 24, the maximum load detection value calculation unit 21 uses a calculation formula (first order) used when obtaining the maximum load detection value from the current load detection value in the car 6. Function) is recorded.

  Announce command unit 25 (an example of an output unit) causes passenger U to ride on the center part of the floor board of car 6 with respect to announcement device 12 when maximum load detection value calculation unit 21 obtains weight information. A command is issued to make an announcement.

  The announcement device 12 notifies the passenger U to get on the center part of the floor board of the car 6 by voice or the like based on the command from the announcement command unit 25. The announcement device 12 includes, for example, a sound output device (speaker) (not shown) and a display device such as a liquid crystal panel (not shown). Announcement device 12 can display a message on a display device as well as performing audio output using an audio output device.

[Example computer hardware configuration]
Next, a hardware configuration of a computer constituting the elevator control device 2 of the elevator 100 described above will be described.

  FIG. 5 is a block diagram illustrating a hardware configuration example of a computer used in the elevator control device 2. In the present embodiment, the person determination unit 31 has the same hardware configuration as that of the computer 50. However, each part of the computer 50 is selected according to the function and usage purpose of each apparatus.

  The computer 50 is hardware used as a so-called computer. The computer 50 includes a CPU (Central Processing Unit) 51, a ROM (Read Only Memory) 52, and a RAM (Random Access Memory) 53 connected to the bus 54. Further, the computer 50 includes a display unit 55, an operation unit 56, a nonvolatile storage 57, and a network interface 58.

  The CPU 51 reads out the program code of software that implements each function according to the present embodiment from the ROM 52 and executes it. That is, when the CPU 51 executes the program code read from the ROM 52, each function of the elevator control device 2 is realized. The computer 50 may include a processing device such as an MPU (Micro-Processing Unit) instead of the CPU 51.

  In the RAM 53, variables, parameters, and the like generated during the arithmetic processing are temporarily written. The display unit 55 is a liquid crystal display monitor, for example, and displays a result of processing performed by the computer 50 and the like. For example, a keyboard, a mouse, or the like is used for the operation unit 56, and a specialist engineer or a passenger U can perform predetermined operation inputs and instructions.

  Examples of the non-volatile storage 57 include a hard disk drive (HDD), a solid state drive (SSD), a flexible disk, an optical disk, a magneto-optical disk, a CD-ROM, a CD-R, a magnetic tape, and a non-volatile memory card. Used. In addition to the OS (Operating System) and various parameters, the nonvolatile storage 57 stores a program for causing the computer 50 to function. For example, a network interface card (NIC) or the like is used as the network interface 58, and various types of data can be transmitted to and received from a monitoring center (not shown) via a network N such as a LAN.

  2 is realized by the non-volatile storage 57 or EEPEOM (not shown).

[Example of operation of elevator controller]
FIG. 6 is a flowchart illustrating an operation example of the load detection adjusting device for an elevator according to the embodiment. The operation of the elevator load detection and adjustment device will be described with reference to FIG.

  First, the maximum load detection value calculation unit 21 determines whether or not the passenger U has boarded the car 6 (S1). Whether or not the passenger U has entered the car 6 can be determined from, for example, the load detection value of the car load detection unit 41 or the analysis result of the captured image of the car camera 17 by the person determination unit 31. When the passenger U is not on board (NO in S1), the maximum load detection value calculation unit 21 returns to the process of step S1 and waits until the passenger U gets on the car 6.

  Next, when the passenger U gets in the car 6 in step S1 (YES in S1), the person determination unit 31 analyzes the captured image of the in-car camera 17 to determine whether the passenger U has luggage. (S2). When the passenger U has a luggage (YES in S2), the person determination unit 31 does not determine the passenger U and returns to step S1.

  For example, when determining whether or not to correct the maximum load detection value with an error of 10% as a specified value, depending on the clothes and luggage of the passenger U, the actual weight of the passenger U (including clothes and luggage) There is a possibility that an error of 10% or more may occur between the registered weight information. For example, a case where a person with a weight of 60 kg has a luggage of 6 kg or more corresponds to this. Therefore, when the person determination unit 31 detects that the passenger U has luggage, the adjustment accuracy of the load detection value is maintained at a certain level or higher by not performing the determination of the passenger U, that is, the correction process. The Regarding the difference in the clothes of passengers U and the presence or absence of luggage, for example, a model of image data of passengers U who have arrived in particular clothes or passengers U with luggage is stored in the personal information database 32 or the like. The person determination unit 31 may make a determination based on the similarity between the captured image and the model.

  Next, when the passenger U has no baggage in step S2 (NO in S2), the person determination unit 31 analyzes a photographed image of the in-car camera 17 and is in the car 6 Is determined (S3).

  Next, the person determination unit 31 determines whether or not there is weight information of the passenger U in the personal information database 32 (weight information database 33b) (S4). When there is no weight information of the passenger U in the personal information database 32 (NO in S4), the person determination unit 31 returns to the process of step S1.

  Next, when there is the weight information of the passenger U in the personal information database 32 in step S4 (YES in S4), the person determination unit 31 uses the acquired weight information of the passenger U (load amount W2 in FIG. 4) as an elevator control device. 2 is transmitted to the maximum load detection value calculation unit 21 (S5).

  Next, when the weight information of the passenger U is transmitted from the person determination unit 31, the maximum load detection value calculation unit 21 instructs the announcement command unit 25 to make an announcement toward the passenger U. The announcement command unit 25 instructs the announcement device 12 to make an announcement for prompting the passenger U to get on the center of the floor board of the car 6. The announcement device 12 outputs a voice, for example, “Please get in the center of the elevator” (S6). Further, a message “Please get in the center of the elevator” may be displayed on the display device together with the sound output.

  Next, the person determination unit 31 analyzes the captured image after image processing input from the car camera 17, and determines whether or not the passenger U is on the center of the floor board of the car 6 (S7). . At this time, if the passenger U is not on the center part of the floor board of the car 6 or if the passenger U does not move to the center part of the floor board of the car 6 even after a predetermined time has elapsed (NO in S8). The maximum loading load detection value calculation unit 21 stops the calculation, returns to the process of step S1, and waits until the ID card C is held over the ID card reader 16 again.

  Next, when the passenger U is riding on the center part of the floor board of the car 6 in step S6 (YES in S7), the maximum load detection value calculating unit 21 detects the car load of the car load detecting device 4. The load detection value (load detection value D2 in FIG. 4) in the car 6 is acquired from the unit 41 (S7).

  Next, the maximum loading load detection value calculation unit 21 calculates the maximum from the weight information transmitted from the person determination unit 31 and the current load detection value in the car 6 transmitted from the car load detection unit 41. A load detection value (Dmax ′) during loading is calculated (S9). The calculated maximum loading load detection value (Dmax ′) is output to the maximum loading load detection value pass / fail determination unit 22.

  Next, the maximum loading load detection value pass / fail determination unit 22 registers the maximum loading load detection value (Dmax ′) input from the maximum loading load detection value calculation unit 21 in the nonvolatile storage 57 (recorded last). The maximum loading load detection value (Dmax) is compared. The maximum loading load detection value pass / fail determination unit 22 has an error of ± 10% or more between the calculated maximum loading load detection value (Dmax ′) and the registered maximum loading load detection value (Dmax). It is determined whether or not (S10). The result of the pass / fail judgment is output to the maximum loading load detection value correction unit 23.

  Next, when the error between the two is ± 10% or more in step S10 (the result of the pass / fail judgment is “No”) (YES in S10), the maximum load detection value correction unit 23 calculates the maximum load. Correction processing is performed with the hourly load detection value (Dmax ′) as positive (S11). For example, the maximum loading load detection value correction unit 23 uses the maximum loading load detection value (Dmax) registered in the maximum loading load detection value recording unit 24 as the currently calculated maximum loading load detection value (Dmax ′). ) And registered as a new maximum load detection value (Dmax ′). Alternatively, an average value of the maximum loading load detection value (Dmax) and the maximum loading load detection value (Dmax ′) may be calculated and registered as a new maximum loading load detection value. After the process of step S10 is complete | finished, this flowchart is complete | finished.

  On the other hand, if the error between the two is less than ± 10% (the result of the pass / fail judgment is “good”) (NO in S10), the maximum load detection value correction unit 23 is the maximum load detection value calculation unit. 21 is positive, and the correction is not performed. The maximum load detection value calculation unit 21 returns to the process of step S <b> 1 and waits until the ID card C is held over the ID card reader 16 again.

[Effect of one embodiment]
According to the embodiment configured as described above, the person determination unit 31 specifies the passenger U from the photographed image of the car camera 17, searches the personal information database 32, and acquires the weight information of the passenger U. Next, using the weight information (load amount W2) acquired by the person determination unit 31 and the load detection value (D2) in the current car 6 detected by the car load detection unit 41, the maximum loading load The detection value calculator 21 calculates the maximum load detection value (Dmax ′). Next, the maximum loading load detection value pass / fail judgment unit 22 calculates the maximum loading load detection value (Dmax ′) and the maximum loading registered last recorded in the maximum loading load detection value recording unit 24. The hourly load detection value (Dmax) is compared. When the error exceeds a specified value, the maximum loading load detection value correction unit 23 corrects the last registered maximum loading load detection value (Dmax) (for example, the maximum loading load detection value (Dmax). Replace with ')).

  Thus, since it becomes possible to adjust the load detection value at the time of maximum loading using the weight information of the passenger U acquired by identifying the passenger U from the captured image of the camera 17 in the car 100 of the elevator 100, a professional engineer May not go directly to the target elevator 100. Therefore, the adjustment frequency of the load detection value when the elevator 100 is fully loaded can be increased.

  Further, it is possible to adjust the load detection value at the time of maximum loading without performing a special operation by a professional engineer, and the work amount of the professional engineer can be reduced.

<2. Other>
In the above-described embodiment, the human weight may change as the period elapses after the information is registered in the weight information database 33b. Therefore, it is desirable to update the weight information every predetermined period. The maximum loading load detection value calculation unit 21 may not calculate the maximum loading load detection value using the corresponding weight information when the acquired weight information has not been updated for a predetermined period or more. Alternatively, the maximum loading load detection value calculation unit 21 may make an announcement requesting the passenger U to update the weight information by the announcement device 12 when the weight information has not been updated for a predetermined period or longer.

FIG. 7 is another example of the weight information database.
The record of the weight information database 33b1 has an ID information field, a weight information field, and a registration date field. In the example of FIG. 7, the weight “60 kg” of ID “001” is registered on October 30, 2015, and the weight “48 kg” of ID “002” is registered on February 28, 2015. For example, assuming that the predetermined period as an update standard is 3 months and the date of adjustment date is November 15, 2015, the weight information of ID '002' is information older than about 8 months ago . By not using such old weight information for adjustment of the load detection value, the adjustment accuracy of the load detection value is maintained at a certain level or more.

  On the other hand, when it is necessary to adjust the load detection value using the weight information that has not been updated for a predetermined period or longer, the error range at the time of pass / fail judgment is narrowed. For example, in each of the above-described embodiments, the specified error value at the time of pass / fail judgment is narrowed from ± 10% to ± 5%. By doing in this way, when the weight information whose accuracy is not ensured is used, the adjustment accuracy of the load detection value is maintained at a certain level or more.

  In addition, with respect to the face images registered in the face image database 33a in FIG. 2, the human phase of the passenger U's face may change due to aging or the like after a period of time has elapsed since the registration of the passenger U's face image. . Therefore, the face image may be updated every predetermined period.

  Further, in the above-described embodiment, in order to increase the accuracy of identifying a person in the car 6 by image recognition, the information of “predetermined person's elevator usage time” is used when the person determining unit 31 identifies the person. Also good. Alternatively, information such as “predetermined clothes (color, pattern, pattern, etc.)” and “predetermined luggage” may be used. For example, the above information is effective when a building owner always wears a suit, and a worker of a building structure where the elevator 100 is installed always has the same work clothes and work tools.

  Further, in the above-described embodiment, the weight information database 33b uses “weight information to be used when it is determined that the person has the baggage and weight information of the same person and when the baggage is determined to have little or no baggage. You may make it have "weight information". The person determination unit 31 determines the presence or absence of the baggage possessed by the passenger U from the captured image, selects one of the weight information, and transmits the selected weight information to the maximum loading load detection value calculation unit 21. To do. Thereby, the correction process using appropriate weight information close to the weight (load) of the passenger U in the car 6 is performed according to the presence or absence of the baggage possessed by the passenger U.

  In the above-described embodiment, the accuracy of adjustment can be improved by increasing the number of samples of weight information and determining whether the registered maximum loading load detection value is acceptable. For example, if the image recognition apparatus 3 determines 10 face images and obtains 10 pieces of weight information, and if all of the maximum load detection values are “No”, the calculated maximum load detection is performed. The median value is set as the correction value.

  Furthermore, the present invention is not limited to the above-described embodiments, and various other application examples and modifications can be taken without departing from the gist of the present invention described in the claims. is there.

  For example, the above-described exemplary embodiments are detailed and specific descriptions of the configuration of the apparatus and the system in order to explain the present invention in an easy-to-understand manner, and are not necessarily limited to those having all the configurations described above. . Further, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment. In addition, the configuration of another embodiment can be added to the configuration of a certain embodiment. Moreover, it is also possible to add, delete, and replace other configurations for a part of the configuration of each exemplary embodiment.

  Each of the above-described configurations, functions, processing units, processing means, and the like may be realized by hardware by designing a part or all of them with, for example, an integrated circuit. Each of the above-described configurations, functions, and the like may be realized by software by interpreting and executing a program that realizes each function by the processor. Information such as programs, tables, and files for realizing each function can be stored in a recording device such as a memory, a hard disk, or an SSD (Solid State Drive), or a recording medium such as an IC card, an SD card, or a DVD.

  Further, the control lines and information lines indicate what is considered necessary for the explanation, and not all the control lines and information lines on the product are necessarily shown. Actually, it may be considered that almost all the components are connected to each other.

  Further, in this specification, the processing steps describing time-series processing are not limited to processing performed in time series according to the described order, but are not necessarily performed in time series, either in parallel or individually. The processing (for example, parallel processing or object processing) is also included.

  DESCRIPTION OF SYMBOLS 2 ... Elevator control apparatus, 3 ... Image recognition apparatus, 4 ... Car load detection apparatus, 6 ... Car, 12 ... Announcement apparatus, 17 ... Camera in car, 21 ... Maximum load detection value calculation part at the time of loading, 22 ... Maximum Load detection value good / bad determination unit when loading, 23 ... Maximum load detection value correction unit during loading, 24 ... Maximum load detection value recording unit during loading, 25 ... Announcement command unit, 26 ... Image processing unit, 31 ... Person determination unit, 32 ... personal information database, 33a ... face image database, 33b, 33b1 ... weight information database, 41 ... load detection unit in car, 50 ... computer, 51 ... CPU, 52 ... ROM, 53 ... RAM, 57 ... non-volatile storage, 90 ... Elevator load detection and adjustment device, 100 ... Elevator control device, D1, D2 ... Load detection value, Dmax, Dm x'... maximum load when the load detection value, W1, W2, Wmax ... loading

Claims (5)

A photographing device for photographing the inside of the car,
A person determination unit that identifies passengers in the car from a captured image captured by the imaging device, and acquires weight information of the passengers registered in advance;
From the weight information of the passenger acquired by the person determination unit and the current load detection value of the car detected by the car load detection unit that outputs a load detection value corresponding to the load in the car, the maximum A calculation unit for calculating a maximum load detection value corresponding to the load detection value of the car at the time of loading;
A recording unit for recording the maximum load when the load detection value,
And when the load detection value the maximum load that the computation unit is calculated, by comparing the maximum load when the load detection value registered in the recording unit, the difference between the two said maximum load when the load detection value compared to a specified value A determination unit for determining whether or not it has exceeded ,
When the determination unit determines that the difference exceeds a specified value, the maximum loading load detection value registered in the recording unit is corrected using the maximum loading load detection value calculated by the calculation unit. A correction unit to perform,
Elevator load detection and adjustment device. A personal information database in which at least the passenger's face image and the passenger's weight information are associated with each other;
The elevator load detection adjustment device according to claim 1, wherein the person determination unit extracts weight information of the passenger from the personal information database based on the identified facial image of the passenger. The person determination unit determines whether or not the passenger in the car has a baggage from the captured image captured by the imaging device, and if the passenger has a baggage, the identification of the passenger The elevator load detection and adjustment device according to claim 1. The person determination unit analyzes the captured image captured by the imaging device and outputs an analysis result to the calculation unit. The calculation unit is configured to output the analysis result of the captured image based on the analysis result of the captured image. It is determined whether or not the vehicle is on the center of the floor of the car, and when the passenger is not on the center of the floor of the car, the process of calculating the maximum load detection value is not performed. Item 4. The elevator load detection adjusting device according to any one of Items 1 to 3. A car that goes up and down,
And the image capturing apparatus for capturing the passenger in the car,
A person determination unit that identifies passengers in the car from a captured image captured by the imaging device, and acquires weight information of the passengers registered in advance;
A load detection unit in the car that outputs a load detection value corresponding to the load in the car; and
From the passenger weight information acquired by the person determination unit and the current load detection value of the car detected by the car load detection unit, the maximum corresponding to the load detection value of the car at the time of maximum loading A calculation unit for calculating a load detection value at the time of loading;
A recording unit for recording the maximum load when the load detection value,
And when the load detection value the maximum load that the computation unit is calculated, by comparing the maximum load when the load detection value registered in the recording unit, the difference between the two said maximum load when the load detection value compared to a specified value A determination unit for determining whether or not it has exceeded ,
When the determination unit determines that the difference exceeds a specified value, the maximum loading load detection value registered in the recording unit is corrected using the maximum loading load detection value calculated by the calculation unit. A correction unit to perform,
Elevator with.

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