JP5377729B2 - Number detection device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To accurately estimate the number of elevator passengers. <P>SOLUTION: A measurement unit 11 measures loaded weight of a closed space at a predetermined sampling cycle. A time differential data preparation unit 12 prepares time differential data by calculating changes for every differential interval of the measured loaded weight. A waveform observation unit 13 estimates the number of elevator passengers by comparing the chronological changes of the prepared time differential data with the chronological changes of time differential data of a predetermined standard model. <P>COPYRIGHT: (C)2013,JPO&amp;INPIT

Description

  The present invention relates to a number detection device for detecting the number of passengers in an elevator.

  In order to improve the crime prevention function by the elevator, it is important to accurately detect the number of passengers in the elevator, the number of passengers getting off the elevator, and the number of people in the elevator. As a conventional number detection device, for example, in Patent Document 1, a value obtained by dividing a loaded weight by an average body weight value is set as the number of people. In Patent Document 2, the weight of a box is continuously measured while stopped, the measurement data is filtered, and the number of passengers in the elevator box is determined based on the weight data of the box. The change in the staircase load weight that occurs inside is recorded, and the number of people entering and leaving the elevator box is judged based on the staircase change.

JP-A-55-56963 (6th to 9th lines on the upper right of the second page) Japanese Patent No. 2597448 (Claim 1)

  Since the conventional number detection device is configured as described above, when the number obtained by dividing the loaded weight by the average body weight value is used as the number of persons, the number detection accuracy depends on the difference between the actual passenger weight and the average weight. There was a problem of deterioration. In addition, when a staircase change in the load weight is recorded and the number of persons is detected from the number and direction of the load weight change, the load weight value is linear or parallel to the time axis in a stepwise manner. However, since the load weight value when passengers actually get on and off shows a curvilinear change with respect to the time axis, the load weight waveform is used in combination with a means for filtering in a staircase pattern. Without it, there was a problem that the actual number of people could not be estimated.

  The present invention has been made to solve the above-described problems. The number of passengers in an elevator can be estimated with higher accuracy than the method of dividing the total loaded weight by the average body weight, and the change in the loaded weight is a staircase. An object of the present invention is to obtain an apparatus for detecting the number of people that can be estimated even if it is not a shape.

  The number detection device according to the present invention creates a time difference data by calculating a measuring means for measuring a load weight in a closed space at a predetermined sampling period, and calculating a change at every difference interval of the load weight measured by the measuring means. Comparing the time difference change of the time difference data created by the time difference data creation means and the time series change of the time difference data of the predetermined standard model, And a waveform observation means for estimation.

  According to the present invention, it is possible to estimate the number of passengers in an elevator with higher accuracy than the method of dividing the total loaded weight by the average body weight, and it is possible to estimate the change in the loaded weight even if it is not stepped. .

It is a block diagram which shows the structure of the number-of-people detection apparatus by Embodiment 1 of this invention. It is a figure which shows the time-sequential change of the loading weight of an elevator. It is a flowchart which shows the process of the people detection apparatus by Embodiment 1 of this invention. It is a figure which shows an example of the time-sequential change of the loading weight which the time difference data preparation means of the number detection apparatus by Embodiment 1 of this invention receives. It is a figure which shows an example of the time-sequential change of the time difference data produced by the time difference data creation means of the number detection apparatus by Embodiment 1 of this invention. It is a figure which shows the time-sequential change of the time difference data of the standard model currently hold | maintained by the waveform observation means of the number detection apparatus by Embodiment 1 of this invention. It is a figure which shows an example of the time-sequential change of the time difference data produced from the loading weight of the continuous boarding by the time difference data creation means of the number detection device according to Embodiment 1 of the present invention. It is a figure which shows an example of the result of having counted the number of times (estimated candidate of a boarding number) that the time-sequential change of time difference data became more than a threshold value for every threshold value by the waveform observation means of the number detection apparatus by Embodiment 1 of this invention. is there. It is a block diagram which shows the structure of the number detection apparatus by Embodiment 2 of this invention. It is a flowchart which shows the process of the people detection apparatus by Embodiment 2 of this invention. It is a figure which shows an example of the time-sequential change of the time difference data produced by the time difference data production means of the number detection apparatus by Embodiment 2 of this invention. It is a figure which shows an example of the time-sequential change of loading weight and time difference data. It is a block diagram which shows the structure of the people detection apparatus by Embodiment 3 of this invention. It is a flowchart which shows the process of the number-of-people detection apparatus by Embodiment 3 of this invention. It is a figure explaining the control of how to open the door of the elevator by the door control means of the people detection device by Embodiment 3 of this invention. It is a block diagram which shows the structure of the people detection apparatus by Embodiment 4 of this invention. It is a flowchart which shows the process of the number-of-people detection apparatus by Embodiment 4 of this invention. It is a figure which shows an example of the time series change of the loading weight containing signal noise, and time difference data. It is a block diagram which shows the structure of the number-of-people detection apparatus by Embodiment 5 of this invention. It is a flowchart which shows the process of the number-of-people detection apparatus by Embodiment 5 of this invention. It is a figure which shows an example of the time-sequential change of the time difference data produced by the time difference data creation means of the number detection apparatus by Embodiment 5 of this invention. It is a figure which shows an example of the time-sequential change of the time difference data produced by the time difference data creation means of the number detection apparatus by Embodiment 5 of this invention, and the signal noise was removed by the noise removal means. It is a block diagram which shows the structure of the people detection apparatus by Embodiment 6 of this invention. It is a flowchart which shows the process of the people detection apparatus by Embodiment 6 of this invention. It is a block diagram which shows the structure of the people detection apparatus by Embodiment 7 of this invention. It is a flowchart which shows the process of the number-of-people detection apparatus by Embodiment 7 of this invention. It is a block diagram which shows the structure of the people detection apparatus by Embodiment 8 of this invention. It is a flowchart which shows the process of the number-of-people detection apparatus by Embodiment 8 of this invention.

Embodiment 1 FIG.
FIG. 1 is a block diagram showing a configuration of a number detection device 1 according to Embodiment 1 of the present invention. The number detection device 1 includes a measuring means 11, a time difference data creating means 12, and a waveform observing means 13, and each means is constituted by software on a microcomputer.

  The measuring means 11 is an elevator weight sensor, for example, and measures the elevator load weight at a predetermined sampling period. The time difference data creating unit 12 calculates time-by-difference change of the loaded weight measured by the measuring unit 11 and creates time difference data. The waveform observation means 13 compares the time series change of the time difference data created by the time difference data creation means 12 with the time series change of the time difference data of the standard model or a predetermined threshold, and the number of passengers who ride in the elevator, Estimate the number of people getting off the elevator and the number of people in the elevator.

  FIG. 2 is a diagram showing time-series changes in the elevator load weight, where the horizontal axis indicates time t (i) and the vertical axis indicates the load weight W (i) measured at time t (i). . Fig.1 (a) shows the time-series change of the load weight when two people get on the elevator continuously. When two people ride continuously, the weight change caused by the first person getting on and the second person getting on The interval of weight change due to this is short.

  At this time, in Patent Document 2, since the number of passengers and the number of passengers getting on the elevator are calculated from the direction and number of changes in the loaded weight, the waveform of the loaded weight W (i) shown in FIG. As shown in FIG. 1 (b) or FIG. 1 (c), it must be filtered into a waveform showing a linear and step-like change, but in FIG. 1 (b) and FIG. Because it makes a difference, it must be filtered accurately. In the case of FIG. 1 (a), since it is a time-series change of the loaded weight when two people ride continuously, it is correct to filter to FIG. 1 (c), but when one person gets on. However, since there is a possibility that the waveform of the loaded weight as shown in FIG. 1A may be obtained, in some cases, filtering to FIG. 1B may be a correct answer. Thus, in the method of Patent Document 2, it is difficult to accurately filter the loaded weight in order to estimate the number of passengers or the number of passengers getting off.

  Accordingly, in the first embodiment, the configuration shown in FIG. 1 is used to calculate time-difference data by calculating a change in the load weight difference interval measured at a predetermined sampling period. The number of passengers and the number of people getting off are estimated by comparing the time-series change with the time-series change of the standard model or a predetermined threshold.

Next, the operation will be described.
FIG. 3 is a flowchart showing the processing of the number-of-people detection apparatus 1 according to Embodiment 1 of the present invention. In step ST101, the measurement unit 11 starts measurement when a predetermined measurement start condition determined in advance is satisfied. As a measurement start condition of the measuring means 11, for example, there is a predetermined time. In step ST102, the measuring means 11 measures the elevator load weight W (i) at a predetermined sampling period. In step ST103, the measurement unit 11 ends the measurement when a predetermined measurement end condition determined in advance is satisfied. As a measurement end condition of the measuring unit 11, for example, there is a predetermined time. The measurement end condition may be a predetermined elapsed time from the measurement start time.

  In step ST104, the time difference data creation means 12 receives the measurement end signal from the measurement means 11, and the load weight W (i) measured by the measurement means 11 from the measurement start to the measurement end is measured from the measurement means 11. Receive.

  FIG. 4 is a diagram showing an example of a time-series change of the loading weight W (i) received by the time difference data creation means 12, and here, a graph of when two people get off after two people get on the elevator An example is shown. In FIG. 4, the horizontal axis represents time t (i), and the vertical axis represents the load weight W (i) measured at time t (i). Here, i is the sampling number of the measuring means 11, and t (i) −t (i−1) is the sampling period of the measuring means 11.

Then, in step ST104 of FIG. 3, the time difference data creation means 12 uses the following equation (1) from the received load weight W (i) to change the load weight W (i) for each difference interval. To calculate time difference data W_diff (i).
W_diff (i) = (W (i + Δi) −W (i)) / (Δi) (1)
Here, Δi represents the difference interval.

  FIG. 5 is a diagram illustrating an example of a time-series change of the time difference data W_diff (i) created by the time difference data creation unit 12. In FIG. 5, the horizontal axis represents time t (i), and the vertical axis represents time difference data W_diff (i). In FIG. 5, the upwardly convex waveform means that the loaded weight has increased, and means that a person has entered the elevator. Conversely, a downwardly convex waveform means that the loaded weight has decreased, and that a person has got out of the elevator. The thresholds A to F shown in FIG. 5 will be described later.

FIG. 6 is a diagram showing a time-series change of the time difference data W_m (i) of the standard model created from the loaded weight of the elevator when one person gets on.
In step ST105 of FIG. 3, the waveform observation means 13 receives the time difference data W_diff (i) created by the time difference data creation means 12, and the time series change of the received time difference data W_diff (i) is upward. When the waveform has a convex waveform, for example, the value of the time difference data W_m (i) of the standard model stored in advance shown in FIG. 6 is scanned in the time axis direction, and the received time difference data W_diff ( The normalized cross-correlation function z (τ) shown in the following equation (2) representing the similarity between the time series change of i) and the time series change of the time difference data W_m (i) of the standard model is calculated.

ここで、τは基準となる時刻ｔ（ｉ）からのずれ量を示し、バーＷ_mは標準モデルの時間差分データＷ_m（ｉ）の平均を示し、バーＷ_diffは受信した時間差分データＷ_diff（ｉ）の平均を示す。

Here, τ represents the amount of deviation from the reference time t (i), the bar W_m represents the average of the time difference data W_m (i) of the standard model, and the bar W_diff represents the received time difference data W_diff (i). The average is shown.

  In step ST105, the waveform observation means 13 sets the number of passengers as the number of times that the calculated value of the cross-correlation function z (τ) is equal to or greater than a predetermined threshold S_overlap that is held in advance.

  On the other hand, in step ST105, when the time series change of the received time difference data W_diff (i) has a downwardly convex waveform, the waveform observing means 13 shows, for example, FIG. When the time difference data W_m (i) of the standard model is scanned in the time axis direction with the value of the time difference data W_m (i) of the standard model negative, the time difference of the received time difference data W_diff (i) and the time difference data W_m (i) of the standard model The normalized cross-correlation function z (τ) shown in the above equation (2) representing the similarity to the series change is calculated, and the calculated cross-correlation function z (τ) is equal to or greater than a predetermined threshold S_overlap that is held in advance. The number of times of getting off is the number of people getting off.

  A method in which the waveform observation means 13 estimates the number of passengers and the number of people getting off using the time difference data W_m (i) of the standard model as described above is referred to as a number estimation method (1).

And in step ST105, the waveform observation means 13 calculates | requires the number of people in an elevator using following Formula (3).
Current number of people in the elevator = Number of people in front of the door + Number of passengers-Number of people getting off (3)
In the above formula (3), it is assumed that the initial value of the number of people present before opening the door is held in the waveform observation means 13 in advance.

In step ST105, the waveform observing means 13 may estimate the number of passengers and the number of people getting off by the next number of people estimation method (2) different from the number of people estimation method (1).
In step ST105, the waveform observing means 13 sets a threshold value at a predetermined position at a value of 0 or more of the received time difference data W_diff (i), and the threshold value set by the time series change of the time difference data W_diff (i). The above number of times is the number of passengers.
For example, when a threshold value is set at the position C in FIG. 5, the number of times that the time-series change of the time difference data W_diff (i) becomes equal to or greater than the threshold value C is two, and the waveform observation means 13 determines the number of passengers. Estimated 2 people.

  On the other hand, in step ST105, the waveform observing means 13 sets a threshold value at a predetermined position with a value of 0 or less in the received time difference data W_diff (i), and the time series change of the time difference data W_diff (i) is a threshold value. The number of times the following has occurred is the number of people getting off.

  This number estimation method (2) does not need to hold the model waveform W_m (i) in advance as in the number estimation method (1), and it is necessary to calculate the similarity with the model waveform W_m (i). Therefore, the amount of computing resources to be used can be reduced.

FIG. 7 is a diagram showing an example of a time-series change of the time difference data W_diff (i) created from the loaded weight of the continuous boarding shown in FIG.
In step ST105, the waveform observing means 13 sets the time difference of the time difference data W_diff (i) when the threshold value is set at a position of, for example, B that is 0 or more of the time difference data W_diff (i) shown in FIG. The number of times that the threshold value B is exceeded is two, and the number of passengers is estimated to be two.

On the other hand, even when the passengers get off continuously, the waveform observation means 13 can estimate the number of people getting off in the same manner.
In this way, the number of passengers and the number of people getting off can be estimated by this number estimating method (2) even when continuously getting on or getting off.

  Furthermore, in step ST105, the waveform observing means 13 estimates the number of passengers and the number of people getting off by the following number of person estimation method (3), which is different from the number of person estimation method (1) and the number of person estimation method (2). good.

  In step ST105, the waveform observing means 13 sets a plurality of predetermined threshold values in a value of 0 or more of the received time difference data W_diff (i), and the time-series change of the time difference data W_diff (i) exceeds the set threshold value. The number of occurrences is counted for each threshold, the most frequently counted number is estimated as the number of passengers, a plurality of predetermined thresholds are set in the received time difference data W_diff (i) of 0 or less, and the time difference data The number of times that the time series change of W_diff (i) is equal to or less than the set threshold value is counted for each threshold value, and the most frequently counted number is estimated as the number of people getting off.

  For example, when the waveform observing means 13 receives the time difference data W_diff (i) shown in FIG. 5, the threshold value A, B, C, for example, is set at a value of 0 or more of the time difference data W_diff (i) shown in FIG. 5. , D, E, and F, a plurality of predetermined thresholds are set, and the number of times that the time series change of the time difference data W_diff (i) is equal to or greater than the set threshold, that is, the estimated number of passengers is counted for each threshold. To do.

  FIG. 8 is a diagram illustrating an example of a result obtained by counting the number of times (the estimated number of passengers) that the time-series change of the time difference data W_diff (i) is equal to or greater than the threshold for each threshold. In FIG. 5, the threshold A is exceeded once (1 person), the threshold B is exceeded twice (2 persons), the threshold C is exceeded twice (2 persons), and the threshold D is exceeded 2 times. Times (2 people), 3 times (3 people) exceeding the threshold E, 2 times (2 people) exceeding the threshold F, as shown in FIG. Since the value is the largest at 4, the waveform observation means 13 estimates the number of passengers as two.

On the other hand, when the passenger gets off, the waveform observing means 13 similarly sets the number of persons getting off by setting a plurality of predetermined threshold values in the value of 0 or less of the time difference data W_diff (i) shown in FIG. Can be estimated.
The number of people estimation method (3) has a smaller amount of computing resources than the number of people estimation method (1), and can estimate the number of passengers and the number of people getting off more accurately than the number of people estimation method (2).

  Moreover, when the waveform observing means 13 receives the time difference data W_diff (i) shown in FIG. 7 when the passenger has continuously boarded, the waveform observing means 13 uses a value of 0 or more of the time difference data W_diff (i) shown in FIG. For example, a number of predetermined threshold values such as threshold values A, B, C, D, E, and F are set, and the number of times that the time series change of the time difference data W_diff (i) is equal to or greater than the set threshold value, that is, the number of passengers Are estimated for each threshold.

  In FIG. 7, the threshold A is exceeded twice (2 people), the threshold B is exceeded 2 times (2 people), the threshold C is exceeded 3 times (3 people), and the threshold D is exceeded 2 times. The number of times (two people), the number exceeding the threshold E is two times (two people), and the number exceeding the threshold F is one time (one person), resulting in the count result shown in FIG. As shown in FIG. 8, since the count value of two estimation candidates for the number of passengers is 4, which is the largest, the waveform observation means 13 estimates the number of passengers as two.

On the other hand, even when the passengers get off continuously, the waveform observation means 13 can estimate the number of people getting off in the same manner.
In this way, the number of passengers and the number of people getting off can be estimated by this number estimating method (3) even when continuously getting on or getting off.

  In the first embodiment, an example of an existing elevator weight sensor has been described as an example of the measuring means 11, but the measuring means 11 may not be an existing elevator weight sensor. Even in the closed space where the entrance / exit is secured, the weight sensor dedicated to the number detection device 1 capable of measuring the load weight of the closed space is used as the measuring means 11, and the number of people entering and exiting the closed space according to the method of the first embodiment. The number of people and the number of people present can be estimated. However, by utilizing the existing elevator weight sensor as the measuring means 11, there is an effect that the introduction cost of the number-of-people detection device 1 of the present invention can be reduced.

  As described above, according to the first embodiment, the time difference data creating unit 12 calculates time-difference data by calculating a change in the load weight difference interval measured by the measuring unit 11 at a predetermined sampling period. The waveform observing means 13 compares the time-series change of the time difference data created by the time-difference data creating means 12 with the time-series change of the standard model or a predetermined threshold value, By estimating the number of passengers, it is possible to estimate the number of passengers on the elevator, the number of people getting off, and the number of people in the elevator with higher accuracy than the method of dividing the total loaded weight by the average weight, and even if the change in the loaded weight is not stepped. The effect that it can estimate is acquired.

  Further, according to the first embodiment, it is possible to estimate the number of passengers, the number of people getting off, and the number of people who are present even when the passengers get on and off continuously.

Embodiment 2. FIG.
In the first embodiment, the number of passengers and the number of passengers getting off are estimated from the loaded weight W (i) and the time difference data W_diff (i). However, in the flowchart shown in FIG. The number of people getting off is estimated after a predetermined measurement end condition is satisfied by the measuring means 11. For this reason, the number of passengers and the number of people getting off cannot be known unless a predetermined measurement end condition is satisfied, and the number of passengers and the number of people getting off cannot be estimated immediately after boarding and getting off the passenger. Therefore, in the second embodiment, a method for estimating the number of passengers and the number of people getting off immediately after the passengers get on and off the vehicle will be described.

  FIG. 9 is a block diagram showing the configuration of the number-of-people detection apparatus 1 according to Embodiment 2 of the present invention. The number detection device 1 includes a measuring means 11, a time difference data creating means 12, a waveform observing means 13, and a processing unit determining means 14, and each means is constituted by software on a microcomputer.

  In FIG. 9, the processing unit determination means 14 sequentially receives the time difference data W_diff (i) created by the difference data creation means 12 and the processing unit for one time when the number of persons is estimated by the waveform observation means 13. By determining whether or not the minute time difference data W_diff (i) has been created, the waveform observation means 13 dynamically determines the data processing unit when estimating the number of passengers and the number of passengers getting off. The measuring means 11, the time difference data creating means 12, and the waveform observing means 13 have the same configuration as that shown in FIG.

Next, the operation will be described.
FIG. 10 is a flowchart showing the processing of the number detection device 1 according to the second embodiment of the present invention. In step ST201, the measurement unit 11 starts measurement when a predetermined measurement start condition is satisfied. As a measurement start condition of the measuring unit 11, for example, there is a predetermined time. In step ST202, the measuring means 11 measures the load weight of the elevator.

  In step ST203, the measurement means 11 determines whether or not a predetermined measurement end condition is satisfied. In step ST203, if the predetermined measurement end condition is not satisfied, the process proceeds to step ST204. If the predetermined measurement end condition is satisfied, in step ST207, the measuring unit 11 ends the measurement. As a measurement end condition of the measuring means 11, for example, there is a predetermined time. Further, the measurement end condition may be a predetermined elapsed time from the start of measurement.

  In step ST204, the time difference data creation means 12 sequentially receives the loaded weight measured by the measurement means 11, and uses the above equation (1) to obtain time difference data W_diff (i) as shown in FIG. ) Sequentially.

  In step ST205, the processing unit determination means 14 sequentially receives the time difference data W_diff (i) created by the difference data creation means 12, and the processing unit for one time when the waveform observation means 13 estimates the number of people. It is determined whether or not the minute time difference data W_diff (i) has been created.

Here, a method is shown in which the processing unit determination unit 14 determines whether the time difference data W_diff (i) for one processing unit when the number of persons is estimated by the waveform observation unit 13 is created.
FIG. 11 is a diagram illustrating an example of a time-series change of the time difference data W_diff (i) created by the time difference data creation unit 12. When the passenger gets on the elevator, as shown in FIG. 11, the time difference data W_diff (i) shows a value greater than 0 at time t (i), and then the time difference data W_diff (i) at time t (i + x). ) Again indicates a value of 0. On the other hand, when the passenger gets off the elevator, the time difference data W_diff (i) shows a value smaller than 0 at time t (i), and then the time difference data W_diff (i) is again at time t (i + x). A value of 0 is indicated. From this, the processing unit determination means 14 determines that, for example, at time t (i + x), the time difference data W_diff (i) for one processing unit for which the waveform observation means 13 estimates the number of people has been created. . The time difference data W_diff (i) for one processing unit for which the waveform observing means 13 estimates the number of people at this time is time difference data from time t (i−1) to t (i + x).

  In step ST205 of FIG. 10, until the processing unit determination means 14 can determine that the time difference data W_diff (i) for one processing unit when the number of persons is estimated by the waveform observation means 13 has been created, steps ST202 to ST202. The procedure of step ST204 is repeated.

  In step ST205, when the processing unit determining means 14 determines that the time difference data W_diff (i) for one processing unit when the number of persons is estimated by the waveform observing means 13 has been created, in step ST206, the waveform observation is performed. The means 13 receives the time difference data W_diff (i) for one processing unit when estimating the number of persons from the time difference data creating means 12 or the processing unit determining means 14 and described in the first embodiment. The number of passengers and the number of people getting off are estimated by any one of methods (1), (2), and (3). Moreover, the waveform observation means 13 calculates | requires the number of people in an elevator by said Formula (3).

  In the second embodiment, as shown in FIG. 9, the processing unit determining means 14 is shown as an independent component, but the time difference data creating means 12 or the waveform observing means 13 replaces the processing unit determining means 14 with each other. You may comprise.

  As described above, according to the second embodiment, the same effects as those of the first embodiment can be obtained, and data when the processing unit determining means 14 estimates the number of passengers and the number of people getting off by the waveform observation means 13. By dynamically determining the processing unit, it is possible to estimate the number of passengers and the number of passengers getting on the elevator immediately after the passengers get on and off the vehicle.

Embodiment 3 FIG.
In the first embodiment, the number of passengers and the number of passengers getting off are estimated based on the loaded weight W (i) and the time difference data W_diff (i). When two passengers get on the elevator at the same time, There may be a time series change of the loading weight W (i) as shown in FIG. 12 (a) and a time series change of the time difference data W_diff (i) as shown in FIG. 12 (b). In this case, it is difficult to determine that the number of persons is two by the number estimation methods (1), (2), and (3) by the waveform observation unit 13 described in the first embodiment. Therefore, in the third embodiment, a method for further improving the estimation accuracy of the number of passengers and the number of people getting off will be described.

  FIG. 13 is a block diagram showing a configuration of the number-of-people detection apparatus 1 according to Embodiment 3 of the present invention. The number detection device 1 includes a measuring means 11, a time difference data creating means 12, a waveform observing means 13, and a door control means 15, and each means is constituted by software on a microcomputer.

  In FIG. 13, when the measurement means 11 measures the load weight of an elevator, the door control means 15 controls so that a passenger passes through the way of opening an elevator door one by one. The measuring means 11, the time difference data creating means 12, and the waveform observing means 13 have the same configuration as that shown in FIG.

Next, the operation will be described.
FIG. 14 is a flowchart showing processing of the number-of-people detection apparatus 1 according to Embodiment 3 of the present invention. In step ST301, the measurement unit 11 starts measurement when a predetermined measurement start condition is satisfied. As a measurement start condition of the measuring means 11, for example, there is a predetermined time.

  In step ST302, the door control means 15 opens the door of the elevator. FIG. 15 is a diagram for explaining how the door control means 15 opens the elevator door. In step ST302, when the door control means 15 opens the door of the elevator, the door control means 15 controls the opening of the door so that it opens only to the width W_n through which only one passenger can pass as shown in FIG. 15 (a). . Or when the door control means 15 opens a door, as shown in FIG.15 (b), you may make a shield appear so that only one passenger can pass. It is assumed that the width W_n that can be passed by only one person is held in the door control means 15 in advance. The door control method as described above is referred to as a door control method (1).

  In step ST303 of FIG. 14, the measuring means 11 measures the load weight of the elevator. In step ST304, the measurement unit 11 ends the measurement when a predetermined measurement end condition is satisfied. As a measurement end condition of the measuring means 11, for example, there is a predetermined time. Further, the measurement end condition may be a predetermined elapsed time from the start of measurement. In step ST305, the door control means 15 closes the door of the elevator. In FIG. 14, the processes of step ST306 and step ST307 are the same as the processes of step ST104 and step ST105 shown in FIG.

  In addition, you may use the door open signal of a door as a measurement start condition of the measurement means 11 in step ST301. In this case, the order of the door opening operation in step ST302 and the measurement starting operation in step ST301 are interchanged. In step ST301 in which the order is changed, the measuring unit 11 receives a door open signal from the door control unit 15 and starts measurement.

  Moreover, you may use the door closing signal of a door as a measurement termination condition of the measurement means 11 in step ST304. In this case, the order of the door closing operation in step ST305 and the measurement ending operation in step ST304 are interchanged. In step ST304 where the order has been changed, the measuring means 11 receives the door closing signal from the door control means 15 and ends the measurement.

Moreover, in step ST302, the door control means 15 may control how to open the door by the next door control method (2) different from the door control method (1). In step ST302, when opening the door of the elevator, the door control means 15 opens at a normal speed (speed A) to a width that allows only one passenger to pass as shown in FIG. The opening of the door is controlled so that the door is fully opened at a speed (speed B) slower than the speed of. Moreover, in step ST302, when the door control means 15 opens the door of an elevator, as shown in FIG.15 (b), as shown in FIG. The door is opened in such a manner that it appears at A) and then the shield is withdrawn at a speed (speed B) slower than the normal speed. It is assumed that the speed A and the speed B are determined in advance by the door control means 15.
People who could not pass through the door because they only opened to a width that only one person can pass through, such as holding a large baggage, will pass through the door after the time has passed in the door control method (2). Will be able to.

Moreover, in step ST302, when the door control means 15 is controlling the opening method of the door by the door control method (2), when the door opening button near the door is pressed, the door control means 15 is faster than the speed B. Control may be performed so that the door is fully opened, or the shield is withdrawn at a speed higher than speed B.
Thereby, it becomes possible to pass through the door without waiting until the door is fully opened.

Moreover, in step ST302, when the door control means 15 is controlling the door opening method by the door control method (2), when the door close button near the door is pressed, the door is reversed and closed. Control may be performed, or control may be performed such that a blocking object appears and cannot pass.
Thereby, when the outside air is cold, the door can be closed quickly, or when it is desired to quickly shut off the outside air with a shield, the door can be closed quickly. In addition, the door can be closed quickly, and the elevator can be started early.

Moreover, in step ST302, the door control means 15 may control the opening method of the door by the following door control method (3) different from the door control methods (1) and (2). In step ST302, when opening the door of the elevator, the door control means 15 opens it to a width that allows only one passenger to pass as shown in FIG. 15 (a), and opens the door to full open after a certain period of time. Moreover, in step ST302, when the door control means 15 opens the door of an elevator, as shown in FIG.15 (b), a shield appears so that it may become a width | variety which only a passenger can pass one by one, and a fixed time Control how the door opens so that the shield is removed after the passage.
If the door opens only to the width that only one person can pass at a time, the person who could not pass through the door because of holding a large baggage, etc. Will be able to pass through.

In step ST302, when the door control means 15 is controlling the opening method of the door by the door control method (3), when the door opening button near the door is pressed, the door immediately opens to the full opening. Or may be controlled so as to immediately remove the shield.
Thereby, it becomes possible to pass through the door without waiting until the door is fully opened.

Moreover, in step ST302, when the door control means 15 is controlling the opening method of the door by the door control method (3), when the door close button near the door is pressed, the door is reversed and closed. Control may be performed, or control may be performed such that a blocking object appears and cannot pass.
Thereby, when the outside air is cold, the door can be closed quickly, or when it is desired to quickly shut off the outside air with a shield, the door can be closed quickly. In addition, the door can be closed quickly, and the elevator can be started early.

  In the third embodiment, as the door control means 15, an existing elevator door controller may be used, or a dedicated door controller of the number detection device 1 may be used. However, by utilizing the existing elevator door controller as the door control means 15, there is an effect that the introduction cost of the number-of-people detection device 1 of the present invention can be reduced.

  As described above, according to the third embodiment, the same effects as those of the first embodiment can be obtained, and when the measuring unit 11 measures the load weight of the elevator, the door control unit 15 is provided with the elevator door. By controlling so that passengers pass through one by one, it is possible to prevent multiple passengers from lying down side by side and get on and off the elevator at the same time, and further improve the estimation accuracy of the number of passengers and the number of passengers getting off The effect of being able to be obtained.

Embodiment 4 FIG.
In the second embodiment, the number of passengers and the number of passengers getting off are estimated based on the loaded weight W (i) and the time difference data W_diff (i). When two passengers get on the elevator at the same time, There may be a time series change of the loading weight W (i) as shown in FIG. 12 (a) and a time series change of the time difference data W_diff (i) as shown in FIG. 12 (b). In this case, it is difficult to determine that the number of persons is two by the number estimating methods (1), (2), and (3) by the waveform observation unit 13 described in the second embodiment. Therefore, in the fourth embodiment, a method for further improving the estimation accuracy of the number of passengers and the number of people getting off will be described.

  FIG. 16 is a block diagram showing a configuration of the number-of-people detection apparatus 1 according to Embodiment 4 of the present invention. This number detection device 1 includes a measuring means 11, a time difference data creating means 12, a waveform observing means 13, a processing unit determining means 14 and a door control means 15, each means being constituted by software on a microcomputer. Yes.

  In FIG. 16, the measuring means 11, the time difference data creating means 12, the waveform observing means 13, and the processing unit determining means 14 are the same as the configuration shown in FIG. 9 of the second embodiment, and the door control means 15 is the same as that described above. The configuration is the same as that of the third embodiment shown in FIG.

Next, the operation will be described.
FIG. 17 is a flowchart showing processing of the number-of-people detection apparatus 1 according to Embodiment 4 of the present invention. In step ST401, the measurement unit 11 starts measurement when a predetermined measurement start condition is satisfied. As a measurement start condition of the measuring means 11, for example, there is a predetermined time.

  In step ST402, the door control means 15 controls how to open the door, as in step ST302 of the third embodiment. In step ST403, the measuring means 11 measures the loaded weight.

  In step ST404, the measurement unit 11 determines whether or not a predetermined measurement end condition is satisfied. If the predetermined measurement end condition is not satisfied, the process proceeds to step ST405, where the predetermined measurement end condition is satisfied. If so, measurement ends in step ST409. As a measurement end condition of the measuring means 11, for example, there is a predetermined time. Alternatively, the measurement end condition may be a predetermined elapsed time from the start of measurement.

  In step ST405, the door control means 15 closes the elevator door. In FIG. 17, the processing of step ST406, step ST407, and step ST408 is the same as the processing of step ST204, step ST205, and step ST206 shown in FIG.

  In addition, you may use the door open signal of a door as a measurement start condition of the measurement means 11 in step ST401. In this case, the order of the door opening operation in step ST402 and the measurement start operation in step ST401 are interchanged. In step ST401 where the order has been changed, the measurement unit 11 receives the door open signal from the door control unit 15 and starts measurement.

  Further, a door closing signal of the door may be used as the measurement end condition of the measuring means 11 in step ST404. In this case, the order of the door closing operation in step ST405 and the measurement end operation in step ST404 are interchanged. In step ST404 in which the order is changed, the measuring unit 11 receives a door closing signal from the door control unit 15 and ends the measurement.

  As described above, according to the fourth embodiment, the same effect as in the second embodiment is obtained, and the door control means 15 controls the passengers to pass through the elevator doors one by one. By doing so, it is possible to prevent a plurality of passengers from lying down and get on and off the elevator at the same time, and to further improve the estimation accuracy of the number of passengers and the number of passengers getting off.

Embodiment 5 FIG.
In the first embodiment, the number of passengers and the number of passengers getting off are estimated from the loaded weight W (i) and the time difference data W_diff (i). The loaded weight W (i) is as shown in FIG. May contain signal noise. As a result, as shown in FIG. 18B, signal noise also occurs in the time difference data W_diff (i), and the estimation of the number of passengers and the number of people getting off may be incorrect. A method for removing noise will be described.

  FIG. 19 is a block diagram showing a configuration of the number-of-people detection apparatus 1 according to Embodiment 5 of the present invention. The number detection device 1 includes a measuring means 11, a time difference data creating means 12, a waveform observing means 13, and a noise removing means 16, and each means is constituted by software on a microcomputer.

  In FIG. 19, the noise removing unit 16 removes signal noise included in the time difference data W_diff (i) created by the time difference data creating unit 12 and outputs the signal noise to the waveform observing unit 13. The measuring means 11, the time difference data creating means 12, and the waveform observing means 13 are the same as the configuration shown in FIG. 1 of the first embodiment, and a description thereof is omitted here.

Next, the operation will be described.
FIG. 20 is a flowchart showing processing of the number-of-people detection apparatus 1 according to Embodiment 5 of the present invention. In FIG. 20, the processing from step ST501 to step ST504 is the same as the processing from step ST101 to step ST104 shown in FIG. 3 of the first embodiment, and the description thereof is omitted here.

  In step ST505, the noise removing unit 16 receives the time difference data W_diff (i) from the time difference data creating unit 12, and removes the signal noise included in the time difference data W_diff (i).

  FIG. 21 is a diagram illustrating an example of a time-series change of the time difference data W_diff (i) created by the time difference data creation unit 12. In step ST505, for example, as shown in FIG. 21, when the passenger gets on, the noise removing means 16 displays the time difference data W_diff (i) greater than 0 at time t (i) If the time difference data W_diff (i) again shows a value of 0 at t (i + x), it is determined that one boarding operation has been completed at t (i + x), and the times t (i) to t (i + x) When the sum of the values of the time difference data between them is a value equal to or less than the threshold value W_judge, it is determined that the value of the time difference data W_diff (i) between the times t (i) to t (i + x) is signal noise. To convert it to 0.

  On the other hand, since the time difference data W_diff (i) shows a negative value when the passenger gets off, the noise removing unit 16 has the time difference data W_diff (i) smaller than 0 at time t (i), for example. If the time difference data indicates a value of 0 again at time t (i + x) after indicating the value, it is determined that one getting-off operation is completed at t (i + x). And the noise removal means 16 is time t (i), when the absolute value of the sum of the values of the time difference data between times t (i) to t (i + x) is a value equal to or smaller than a predetermined threshold value W_judge. The value of the time difference data W_diff (i) between ˜t (i + x) is determined to be signal noise and converted to 0. It is assumed that the predetermined threshold value W_judge is held in the noise removing unit 16 in advance.

  FIG. 22 is a diagram showing an example of a time-series change of the time difference data W_diff (i) created by the time difference data creating unit 12 and from which the signal noise is removed by the noise removing unit 16, as shown in FIG. 18 (b). The time difference data W_diff (i) including the signal noise is converted into the time difference data W_diff (i) from which the signal noise is removed as shown in FIG.

  In step ST105 shown in FIG. 3, the waveform observing means 13 receives the time difference data W_diff (i) from the time difference data creating means 12, but in step ST506 shown in FIG. 20, the waveform observing means 13 is a noise removing means. 16 receives the time difference data W_diff (i) after noise removal. Since the method for detecting the number of persons after receiving the time difference data W_diff (i) is the same as the process of step ST105 shown in FIG. 3 of the first embodiment, description thereof is omitted here.

  In the fifth embodiment, the noise removing unit 16 is an independent component in FIG. 19, but the time difference data creating unit 12 or the waveform observing unit 13 may include the noise removing unit 16. .

  As described above, according to the fifth embodiment, the same effect as in the first embodiment can be obtained, and the time difference data W_diff (i) created by the time difference data creating unit 12 by the noise removing unit 16 can be obtained. By removing the signal noise contained in the vehicle, it is possible to further improve the estimation accuracy of the number of passengers and the number of passengers getting off.

Embodiment 6 FIG.
In the second embodiment, the number of passengers and the number of passengers getting off are estimated from the loaded weight W (i) and the time difference data W_diff (i). The loaded weight W (i) is as shown in FIG. May contain signal noise. As a result, as shown in FIG. 18B, signal noise also occurs in the time difference data W_diff (i), and the estimation of the number of passengers and the number of people getting off may be erroneous. In the sixth embodiment, this signal A method for removing noise will be described.

  FIG. 23 is a block diagram showing a configuration of the number-of-people detection apparatus 1 according to Embodiment 6 of the present invention. This number detection device 1 includes a measuring means 11, a time difference data creating means 12, a waveform observing means 13, a processing unit determining means 14, and a noise removing means 16, each means being constituted by software on a microcomputer. Yes.

  In FIG. 23, the measuring means 11, the time difference data creating means 12, the waveform observing means 13, and the processing unit determining means 14 are the same as the configuration shown in FIG. 9 of the second embodiment, and the noise removing means 16 is the same as that described above. This is the same means as the noise removing means 16 shown in FIG.

Next, the operation will be described.
FIG. 24 is a flowchart showing processing of the number-of-people detection apparatus 1 according to Embodiment 6 of the present invention. In FIG. 24, the processing from step ST601 to step ST605 is the same as the processing from step ST201 to step ST205 shown in FIG. 10 of the second embodiment, and a description thereof will be omitted here.

  In Step ST606, the noise removing unit 16 receives the time difference data W_diff (i) from the processing unit determining unit 14, and removes the signal noise included in the time difference data W_diff (i). Since the method for removing signal noise after reception of the time difference data W_diff (i) is the same as the process in step ST505 shown in FIG. 20 of the fifth embodiment, description thereof is omitted here.

  In step ST206 shown in FIG. 10, the waveform observation means 13 receives the time difference data W_diff (i) from the time difference data creation means 12 or the processing unit determination means 14, but in step ST607 shown in FIG. The means 13 receives the time difference data W_diff (i) after noise removal from the noise removing means 16. Since the method for detecting the number of persons after receiving the time difference data W_diff (i) is the same as the process in step ST105 shown in FIG. 3 of the first embodiment, description thereof is omitted here.

  In the sixth embodiment, the noise removing unit 16 is shown as an independent component in FIG. 23, but the time difference data creating unit 12, the waveform observing unit 13, or the processing unit determining unit 14 is replaced with the noise removing unit 16. You may comprise so that it may contain.

  As described above, according to the sixth embodiment, the same effect as in the second embodiment can be obtained, and the time difference data W_diff (i) created by the time difference data creating unit 12 by the noise removing unit 16 can be obtained. By removing the signal noise contained in the vehicle, it is possible to further improve the estimation accuracy of the number of passengers and the number of passengers getting off.

Embodiment 7 FIG.
In the third embodiment, the number of passengers and the number of people getting off are estimated from the loaded weight W (i) and the time difference data W_diff (i). The loaded weight W (i) is as shown in FIG. May contain signal noise. As a result, as shown in FIG. 18B, signal noise also occurs in the time difference data W_diff (i), and the estimation of the number of passengers and the number of people getting off may be incorrect. A method for removing noise will be described.

  FIG. 25 is a block diagram showing the configuration of the number-of-people detection apparatus 1 according to Embodiment 7 of the present invention. This person detection device 1 includes a measuring means 11, a time difference data creating means 12, a waveform observing means 13, a door control means 15 and a noise removing means 16, each means being constituted by software on a microcomputer. .

  In FIG. 25, the measurement means 11, the time difference data creation means 12, the waveform observation means 13, and the door control means 15 are the same as the configuration shown in FIG. 13 of the third embodiment, and the noise removal means 16 is the same as that of the above embodiment. The configuration is the same as that of the fifth embodiment shown in FIG. 19, and the description thereof is omitted here.

Next, the operation will be described.
FIG. 26 is a flowchart showing processing of the number-of-people detection apparatus 1 according to Embodiment 7 of the present invention. In FIG. 26, the processing from step ST701 to step ST706 is the same as the processing from step ST301 to step ST306 shown in FIG. 14 of the third embodiment, and the description thereof is omitted here.

  In step ST707, the noise removing unit 16 receives the time difference data W_diff (i) from the time difference data creating unit 12, and removes the signal noise included in the time difference data W_diff (i). Since the method for removing signal noise after reception of the time difference data W_diff (i) is the same as the processing in step ST505 of FIG. 20 in the fifth embodiment, description thereof is omitted here.

  In step ST307 shown in FIG. 14, the waveform observing means 13 receives the time difference data W_diff (i) from the time difference data creating means 12, but in step ST708 shown in FIG. 26, the waveform observing means 13 is a noise removing means. 16 receives the time difference data W_diff (i) after noise removal. Since the method for detecting the number of persons after receiving the time difference data W_diff (i) is the same as the process in step ST105 shown in FIG. 3 of the first embodiment, description thereof is omitted here.

  In the seventh embodiment, the noise removing unit 16 is an independent component in FIG. 25. However, the time difference data creating unit 12 or the waveform observing unit 13 may be configured to include the noise removing unit 16. good.

  As described above, according to the seventh embodiment, the same effect as in the third embodiment can be obtained, and the time difference data W_diff (i) created by the time difference data creating unit 12 by the noise removing unit 16 can be obtained. By removing the signal noise contained in the vehicle, it is possible to further improve the estimation accuracy of the number of passengers and the number of passengers getting off.

Embodiment 8 FIG.
In the fourth embodiment, the number of passengers and the number of passengers getting off are estimated from the loaded weight W (i) and the time difference data W_diff (i). The loaded weight W (i) is as shown in FIG. May contain signal noise. As a result, as shown in FIG. 18B, signal noise is also generated in the time difference data W_diff (i), and the estimation of the number of passengers and the number of passengers getting off may be erroneous. A method for removing noise will be described.

  FIG. 27 is a block diagram showing a configuration of the number-of-people detection apparatus 1 according to the eighth embodiment of the present invention. This number detection device 1 includes a measuring means 11, a time difference data creating means 12, a waveform observing means 13, a processing unit determining means 14, a door control means 15 and a noise removing means 16, each means on a microcomputer. Consists of software.

  In FIG. 27, the measurement means 11, the time difference data creation means 12, the waveform observation means 13, the processing unit determination means 14, and the door control means 15 are the same as the configuration shown in FIG. The means 16 is the same as that shown in FIG. 19 of the fifth embodiment, and a description thereof is omitted here.

Next, the operation will be described.
FIG. 28 is a flowchart showing processing of the number detection device 1 according to the eighth embodiment of the present invention. In FIG. 28, the processing from step ST801 to step ST807 is the same as the processing from step ST401 to step ST407 in FIG. In Step ST808, the noise removing unit 16 receives the time difference data W_diff (i) from the time difference data creating unit 12, and removes the signal noise included in the time difference data W_diff (i). Since the method for removing signal noise after reception of the time difference data W_diff (i) is the same as the processing in step ST505 of FIG. 20 in the fifth embodiment, description thereof is omitted here.

  In step ST408 shown in FIG. 17, the waveform observation means 13 receives the time difference data W_diff (i) from the time difference data creation means 12 or the processing unit determination means 14, but in step ST809 shown in FIG. The means 13 receives the time difference data W_diff (i) after noise removal from the noise removing means 16. Since the method for detecting the number of persons after receiving the time difference data W_diff (i) is the same as the process in step ST105 shown in FIG. 3 of the first embodiment, description thereof is omitted here.

  In the eighth embodiment, the noise removing means 16 is an independent component in FIG. 27, but the time difference data creating means 12, the waveform observing means 13 or the processing unit determining means 14 includes the noise removing means 16. You may comprise as follows.

  As described above, according to the eighth embodiment, the same effect as in the fourth embodiment can be obtained, and the time difference data W_diff (i) created by the time difference data creating unit 12 by the noise removing unit 16 can be obtained. By removing the signal noise contained in the vehicle, it is possible to further improve the estimation accuracy of the number of passengers and the number of passengers getting off.

  DESCRIPTION OF SYMBOLS 1 Person number detection apparatus, 11 Measuring means, 12 Time difference data preparation means, 13 Waveform observation means, 14 Processing unit determination means, 15 Door control means, 16 Noise removal means.

Claims (12)

A measuring means for measuring the load weight of the closed space at a predetermined sampling period;
A time difference data creating means for creating a time difference data by calculating a change for each difference interval of the load weight measured by the measuring means;
Waveform observation means for comparing the time series change of the time difference data created by the time difference data creation means and the time series change of the time difference data of a predetermined standard model to estimate the number of passengers in the closed space People detection device.   The waveform observation means calculates a normalized cross-correlation function between the time series change of the time difference data created by the time difference data creation means and the time series change of the standard model held in advance, and estimates the number of passengers The number-of-people detection device according to claim 1. A measuring means for measuring the load weight of the closed space at a predetermined sampling period;
A time difference data creating means for creating a time difference data by calculating a change for each difference interval of the load weight measured by the measuring means;
A plurality of thresholds are set for the time series change of the time difference data created by the time difference data creation means, and the number of times that the time series change of the time difference data exceeds the set threshold is counted most. A number detection device comprising waveform observation means for estimating the number of counted times as the number of passengers.   4. A processing unit determining means for determining time difference data having a value larger than a predetermined value as a processing unit of time difference data when estimating the number of passengers. The number detection device of any one statement.   When the absolute value of the total value of the period from when the value of the time difference data becomes larger than the predetermined value until it again shows a value smaller than the predetermined value is equal to or less than the predetermined threshold, the time of the period 2. A noise removing unit that uses difference data as signal noise, and the waveform observing unit estimates the number of passengers using time difference data that has not been converted into signal noise by the noise removing unit. The number-of-people detection device according to claim 1.   The number detection device according to any one of claims 1 to 5, wherein the number of passengers in the elevator is estimated by using an elevator weight sensor as measuring means. A measuring means for measuring the load weight of the closed space at a predetermined sampling period;
A time difference data creating means for creating a time difference data by calculating a change for each difference interval of the load weight measured by the measuring means;
Waveform observation means for comparing the time series change of the time difference data created by the time difference data creation means and the time series change of the time difference data of a predetermined standard model to estimate the number of people getting off in the closed space. People detection device.   The waveform observation means calculates a normalized cross-correlation function between the time series change of the time difference data created by the time difference data creation means and the time series change of the standard model held in advance, and estimates the number of passengers getting off. The number-of-people detection device according to claim 7. A measuring means for measuring the load weight of the closed space at a predetermined sampling period;
A time difference data creating means for creating a time difference data by calculating a change for each difference interval of the load weight measured by the measuring means;
A plurality of threshold values are set for the time series change of the time difference data created by the time difference data creating means, and the number of times when the time series change of the time difference data is equal to or less than the set threshold is counted. A number detection device comprising waveform observation means for estimating the number of times counted as the number of people getting off.   10. A processing unit determining means for determining time difference data having a value smaller than a predetermined value as a processing unit of time difference data when estimating the number of passengers getting off is provided. The number detection device of any one statement.   When the absolute value of the total value of the period from when the value of the time difference data becomes larger than the predetermined value until it again shows a value smaller than the predetermined value is equal to or less than the predetermined threshold, the time of the period 8. A noise removing unit that uses the difference data as signal noise is provided, and the waveform observing unit estimates the number of passengers using the time difference data that has not been converted into signal noise by the noise removing unit. The number detection device according to any one of claims 10 to 10.   The number detection device according to any one of claims 7 to 11, wherein the number of passengers getting off the elevator is estimated by using an elevator weight sensor as the measuring means.

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