Diagnostic Systems

Abstract

To provide a diagnostic system that is able to accurately estimate a detecting position for a detection value of a diagnostic sensor even in a situation where an operation speed is changed.SOLUTION: A diagnostic system 1000 includes: a diagnostic step 1a comprising one or more diagnostic sensors including at least a magnetic sensor 251; a magnetic map generation unit 511 that generates a magnetic map M, which is a correlation between a position in an escalator and a detected value of the magnetic sensor 251 during one cycle of the diagnostic step 1a; a self-position estimation unit 512 that estimates a position at which a detection value of a sound sensor 252 in the escalator is detected based on the magnetic map M and the detection value of the magnetic sensor 251 during a cyclic movement; and an anomaly estimation unit 521 that performs anomaly diagnosis, based on the detection value of the sound sensor 252.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to a diagnostic system for a passenger conveyor. [Background technology]

[0002] Patent Document 1 describes a configuration in which a sensor is installed in the internal space of a diagnostic step, and the diagnostic step is circulated within the escalator to measure the interior of the escalator. For example, during regular inspections, regular steps are replaced with diagnostic steps to improve the efficiency of regular inspections. Because the diagnostic step circulates within the escalator, it is necessary to correlate the time when data is obtained with the position of the diagnostic step at that time. In Patent Document 1, an acceleration sensor is used to obtain the timing when the diagnostic step is pulled into the back of the escalator and reverses, and the step position is estimated based on the elapsed time since the reversal. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2006-76729 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the technology described in Patent Document 1 is based on the premise that the escalator operates at a constant speed, and is therefore difficult to apply to, for example, escalators that reduce their operating speed to save power when there are no passengers. [Means for solving the problem]

[0005] The present invention 1stThe diagnostic system according to the present invention is a diagnostic system for diagnosing abnormalities in a passenger conveyor that transports passengers by circulating a plurality of steps connected in an endless manner, and includes: a diagnostic step that is included in the plurality of steps and has one or more diagnostic sensors including at least a magnetic sensor; a magnetic map generation unit that generates a magnetic map that is a correlation between positions on the passenger conveyor during one circulation of the diagnostic step and detection values ​​of the magnetic sensors; a position estimation unit that estimates positions on the passenger conveyor at which detection values ​​of the diagnostic sensors are detected based on the magnetic map and the detection values ​​of the magnetic sensors during the circulating movement; and an abnormality diagnosis unit that performs abnormality diagnosis based on the detection values ​​of the diagnostic sensors. The diagnostic step includes an acceleration sensor as the diagnostic sensor, which is a position identification sensor that can identify the position of the diagnostic step on the passenger conveyor as it circulates. The magnetic map generation unit estimates the timing at which the posture of the diagnostic step will be reversed based on the sensor output of the acceleration sensor, and generates the magnetic map using the position of the diagnostic step at that timing as a reference position. . A diagnostic system according to a second aspect of the present invention is a diagnostic system for diagnosing abnormalities in a passenger conveyor that transports passengers by circulating a plurality of steps connected endlessly, the system comprising: a diagnostic step included in the plurality of steps and having one or more diagnostic sensors including at least a magnetic sensor; a magnetic map generation unit that generates a magnetic map that is a correlation between the position on the passenger conveyor during one circulation of the diagnostic step and the detection value of the magnetic sensor; a position estimation unit that estimates the position on the passenger conveyor at which the detection value of the diagnostic sensor was detected based on the magnetic map and the detection value of the magnetic sensor during the circulating movement; and an abnormality diagnosis unit that performs abnormality diagnosis based on the detection value of the diagnostic sensor, wherein the passenger conveyor includes magnetized parts that have magnetization, and the magnetic map generation unit generates the magnetic map using the position of the diagnostic step when the magnetic sensor detects the magnetization of the magnetized part as a reference position. A diagnostic system according to a third aspect of the present invention is a diagnostic system for diagnosing abnormalities in a passenger conveyor that transports passengers by circulating a plurality of steps connected endlessly, the diagnostic system comprising: a diagnostic step included in the plurality of steps and having one or more diagnostic sensors including at least a magnetic sensor; a magnetic map generation unit that generates a magnetic map that is a correlation between positions on the passenger conveyor during one circulation of the diagnostic step and detection values ​​of the magnetic sensors; a position estimation unit that estimates positions on the passenger conveyor at which the detection values ​​of the diagnostic sensors were detected based on the magnetic map and the detection values ​​of the magnetic sensors during the circulating movement; and an abnormality diagnosis unit that performs abnormality diagnosis based on the detection values ​​of the diagnostic sensors; the passenger conveyor is provided with magnetized parts that have magnetization, and the system further comprises a correction unit that corrects output errors of the magnetic sensors based on the magnetization of the magnetized parts. [Effects of the Invention]

[0006] According to the present invention, it is possible to accurately estimate the detection position of the diagnostic sensor detection value even in a situation where the driving speed changes. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a schematic diagram showing the general configuration of an escalator. [Figure 2] FIG. 2 is a perspective view showing a schematic configuration of the diagnostic step. [Figure 3] FIG. 3 is a functional block diagram of the diagnostic system. [Figure 4] FIG. 4 is a diagram illustrating an example of noise reduction processing. [Figure 5] FIG. 5 is a diagram for explaining an example of the positioning of the diagnostic step. [Figure 6] FIG. 6 is a diagram showing an example of time-series magnetic detection data after noise reduction processing. [Figure 7] FIG. 7 is a diagram illustrating a second method of position association. [Figure 8] FIG. 8 is a diagram illustrating an example of the self-position estimation process. [Figure 9]FIG. 9 is a flowchart showing an example of the abnormality detection operation. [Figure 10] FIG. 10 is a diagram illustrating an example of abnormality occurrence determination and abnormality sign determination. [Figure 11] FIG. 11 is a block diagram showing a first modification of the configuration of the diagnostic system. [Figure 12] FIG. 12 is a block diagram showing a second modification of the configuration of the diagnostic system. [Figure 13] FIG. 13 is a block diagram showing a third modification of the configuration of the diagnostic system. [Figure 14] FIG. 14 is a block diagram showing a fourth modification of the configuration of the diagnostic system. [Figure 15] FIG. 15 is a block diagram showing a fifth modification of the configuration of the diagnostic system. [Figure 16] FIG. 16 is a block diagram showing a sixth modification of the configuration of the diagnostic system. [Figure 17] FIG. 17 is a block diagram showing a seventh modification of the configuration of the diagnostic system. DETAILED DESCRIPTION OF THE INVENTION

[0008] Hereinafter, embodiments of the present invention will be described with reference to the drawings. The examples are illustrative of the present invention, and appropriate omissions and simplifications have been made for clarity of explanation. The present invention can be implemented in various other forms. Unless otherwise specified, each component may be singular or plural. The position, size, shape, range, etc. of each component shown in the drawings may not represent the actual position, size, shape, range, etc., in order to facilitate understanding of the invention. Therefore, the present invention is not necessarily limited to the position, size, shape, range, etc. disclosed in the drawings. When there are multiple components having the same or similar functions, they may be described using the same reference numeral with different subscripts. Furthermore, when it is not necessary to distinguish between these multiple components, the subscripts may be omitted.

[0009] Fig. 1 is a diagram showing an example of a passenger conveyor that is the target of diagnosis by the diagnosis system according to the present invention. In this embodiment, the passenger conveyor is an escalator, and Fig. 1 is a schematic diagram showing the general configuration of an escalator 100. The escalator 100 includes steps 1, 1a, a chain 2, a housing frame 3, a terminal gear 4, a drive motor 6, a lower terminal gear 9, handrails 8, guide rails 11a, 11b, a control device 12, an upper platform floor panel 13a, and a lower platform floor panel 13b. The terminal gear 4, drive motor 6, lower terminal gear 9, and control device 12 are provided within the housing frame 3.

[0010] In the escalator 100, a plurality of steps 1 and one diagnostic step 1a are endlessly connected by a loop-shaped chain 2. The escalator 100 transports passengers by circulating the endlessly connected plurality of steps 1 and the diagnostic step 1a. In FIG. 1, the diagnostic step 1a is hatched. The upper platform floor panel 13a is a steel plate that forms the floor surface of the upper platform of the escalator 100. The lower platform floor panel 13b is a steel plate that forms the floor surface of the lower platform of the escalator 100.

[0011] A terminal gear 4, with which the chain 2 engages, is provided within the housing frame 3 below the upper platform floor plate 13a. When the chain 2 is driven by this terminal gear 4, the steps 1, 1a connected to the chain 2 move cyclically between the upper platform floor plate 13a and the lower platform floor plate 13b. In addition, the handrail 8 rotates in synchronization with the chain 2. The terminal gear 4 is driven by a drive motor 6 having a drive gear 5. The drive motor 6 is controlled by a control device 12. A drive chain belt 7 is mounted between the drive gear 5 and the terminal gear 4. A lower terminal gear 9 is provided within the housing frame 3 below the lower platform floor plate 13b. The chain 2 engages with this lower terminal gear 9.

[0012] Each step 1, 1a has a side formed in a roughly fan shape. Each step 1, 1a is provided with a front guide roller 10a and a rear guide roller 10b. The front guide rollers 10a and rear guide rollers 10b are provided in pairs on the left and right sides of each step 1, 1a, i.e., in the front-to-back direction of the page. Within the housing frame 3, there are provided guide rails 11a on which the front guide rollers 10a run and guide rails 11b on which the rear guide rollers 10b run. The guide rails 11a, 11b are provided in pairs at the top and bottom of the housing frame 3.

[0013] When the step 1, 1a moves from the lower terminal gear 9 to the terminal gear 4, the front guide roller 10a and the rear guide roller 10b run on the upper guide rails 11a, 11b. When the step 1, 1a reaches the terminal gear 4, it moves along the terminal gear 4. When the step 1, 1a moves along the terminal gear 4 from the upper side of the terminal gear 4 to the lower side of the terminal gear 4 in the figure, the position of the step 1, 1a is reversed. The front guide roller 10a and the rear guide roller 10b of the reversed step 1, 1a transfer to the lower guide rails 11a, 11b. When the step 1, 1a moves from the terminal gear 4 to the lower terminal gear 9, the front guide roller 10a and the rear guide roller 10b run on the lower guide rails 11a, 11b. When the step 1, 1a reaches the lower terminal gear 9, it moves along the lower terminal gear 9 and its position is reversed again. The front guide rollers 10a and rear guide rollers 10b of the inverted steps 1, 1a are transferred onto the upper guide rails 11a, 11b.

[0014] FIG. 2 is a perspective view showing the schematic configuration of the diagnostic step 1a. The diagnostic step 1a has a tread portion 21 on which passengers stand, a riser portion 22 continuous with the tread portion 21, and a pair of side portions 23. Each side portion 23 is provided with a front guide roller 10a and a rear guide roller 10b. A sensor terminal 24 is provided within the diagnostic step 1a. A sensor unit 25, a control unit 26, and a wireless communication unit 27 are provided within the sensor terminal 24. Note that the structure of the step 1 is similar to that of the diagnostic step 1a, but it differs from the diagnostic step 1a in that it does not have the sensor terminal 24.

[0015] 3 is a functional block diagram showing the functional configuration of a diagnostic system according to this embodiment. Diagnostic system 1000 includes diagnostic step 1a and control device 12 provided on escalator 100, and position estimation device 51, abnormality diagnosis device 52, and communication device 53 of monitoring center 50 that remotely performs diagnostic processing. Data collection device 30 transmits and receives data to and from monitoring center 50 via network 40.

[0016] As described above, a sensor terminal 24 is provided within the diagnostic step 1a. The sensor terminal 24 is provided with a sensor unit 25, a control unit 26, and a wireless communication unit 27. The sensor unit 25 is provided with a magnetic sensor 251, a sound sensor 252, and an acceleration sensor 253 as diagnostic sensors. The control device 12 provided within the housing frame 3 of the escalator 100 is provided with a data collection device 30 including a data storage unit 301 and a communication unit 302. The magnetic detection data of the magnetic sensor 251, the sound detection data of the sound sensor 252, and the acceleration detection data of the acceleration sensor 253 are transmitted to the data collection device 30 by the wireless communication unit 27. The wireless communication unit 27 uses low-power, low-cost short-range wireless communication. A battery is used as the power source for the sensor terminal 24, and the battery is replaced if necessary, for example, during periodic inspections.

[0017] As a method of data collection, for example, the time-series detection data for one cycle of the diagnostic step 1a is temporarily stored in a memory (not shown) provided in the control unit 26. Then, when the time-series detection data for multiple cycles has been accumulated in the memory, the time-series detection data for multiple cycles is transmitted by the wireless communication unit 27. Hereinafter, the time-series detection data for multiple cycles will be referred to as a time-series detection data group. The data transmission by the wireless communication unit 27 is repeatedly performed at predetermined time intervals. The data collection device 30 stores the time-series detection data group received by the communication unit 302 in the data storage unit 301.

[0018] The plurality of time-series detection data groups accumulated in the data storage unit 301 are transmitted to the monitoring center 50 at predetermined time intervals. This transmission is executed in response to a transmission command from the monitoring center 50. For example, a transmission command for the time-series detection data groups is output from the monitoring center 50 every 24 hours. When the data collection device 30 receives the transmission command from the monitoring center 50, it transmits the time-series detection data groups for 24 hours accumulated in the data storage unit 301 to the monitoring center 50. The plurality of time-series detection data groups transmitted from the communication unit 302 are received by the communication device 53 of the monitoring center 50 via the network 40.

[0019] The monitoring center 50 includes a position estimation device 51, an abnormality diagnosis device 52, and a communication device 53. The position estimation device 51 includes a magnetic map generation unit 511, a self-position estimation unit 512, a noise reduction unit 513, and a storage unit 514. The noise reduction unit 513 performs a process of reducing noise contained in the time-series detection data (magnetic detection data, sound detection data, and acceleration detection data) used when generating the magnetic map. Details of the noise reduction process will be described later.

[0020] The magnetic map generating unit 511 generates a magnetic map based on the time-series magnetic detection data after noise reduction processing. Specifically, the magnetic map is generated by associating the detection value at each time with the position on the escalator 100 for one revolution of the time-series magnetic detection data. The magnetic map generating process will be described later. The magnetic map generating process is performed as an initial operation when the diagnostic step 1a is installed on the escalator 100. The generated magnetic map is stored in the memory unit 514.

[0021] As will be described later, the self-position estimation unit 512 associates each detection value of the time-series sound detection data and time-series acceleration detection data used for abnormality diagnosis with each position on the escalator 100, based on the time-series magnetic detection data and the magnetic map. By performing the self-position estimation process, it is possible to determine at which position on the escalator 100 sound detection data and acceleration detection data detected simultaneously with specific data in the magnetic detection data were detected. The self-position estimation process in the self-position estimation unit 512 will be described later in detail.

[0022] The abnormality diagnosis device 52 diagnoses an abnormality in the escalator 100 based on the magnetic map and the detection data of the diagnostic sensor. The abnormality diagnosis device 52 includes an abnormality estimation unit 521, a noise reduction unit 522, a storage unit 523, and an alarm unit 524. The abnormality estimation unit 521 performs an abnormality estimation process (described later) based on the sound detection data after the self-location estimation process by the self-location estimation unit 512. The noise reduction unit 522 performs noise reduction process on the time-series detection data group used for the abnormality diagnosis. The alarm unit 524 performs an alarm operation when the abnormality estimation unit 521 determines that an abnormality has occurred. Upon receiving the abnormality notification by the alarm operation, an operator performs an inspection of the escalator 100. The storage unit 523 stores the determination criteria data used for the abnormality diagnosis, the time-series detection data group acquired from the data collection device 30, and the like.

[0023] (Noise reduction processing) FIG. 4 is a diagram illustrating an example of noise reduction processing in the noise reduction units 513 and 522. Here, the explanation will be given using time-series magnetic detection data included in the time-series detection data group as an example. FIG. 4 shows time-series magnetic detection data when the diagnostic step 1a is rotated at a constant speed. In FIG. 4, the vertical axis represents the detection value, and the horizontal axis represents time. Time-series magnetic detection data D1 is data from the first rotation, time-series magnetic detection data D2 is data from the second rotation, and time-series magnetic detection data D3 is data from the third rotation. The time-series magnetic detection data D2 is shifted by Δ along the vertical axis relative to the time-series magnetic detection data D1. Similarly, the time-series magnetic detection data D3 is shifted by Δ along the vertical axis relative to the time-series magnetic detection data D2. T is the time required for one rotation of the circular movement, i.e., the period.

[0024] In the example shown in FIG. 4, noise n1 occurs in the time-series magnetic detection data D1, noise n2 occurs in the time-series magnetic detection data D2, and noise n3 occurs in the time-series magnetic detection data D3. The noise reduction units 513 and 522 reduce the detection values ​​in the portions where noise n1 to n3 occurs, for example, by averaging the detection values ​​at the same timing in the time-series magnetic detection data D1 to D3 over multiple revolutions. When averaging is performed using time-series magnetic detection data for 10 revolutions, if noise occurs in only one revolution, the detection value in the noise portion is reduced to 1 / 10 by the averaging. The time-series magnetic detection data after this averaging process is used as the time-series magnetic detection data after noise reduction. Note that the noise reduction process for the time-series sound detection data and the time-series acceleration detection data is also performed in the same manner as for the time-series magnetic detection data described above.

[0025] (Magnetic map generation process) The magnetic map generating unit 511 generates a magnetic map M (magnetic detection value, position) by associating the magnetic detection value at each time with the position on the escalator 100 for one revolution of time-series magnetic detection data that has been subjected to noise reduction processing by the noise reducing unit 513. There are various methods for processing the association, but three types of processing methods will be described below.

[0026] The first method will be described. First, the movement start position of the diagnostic step 1a is set to a predetermined position. Then, the diagnostic step 1a is rotated from that position at a constant speed multiple times or more to obtain multiple time-series magnetic detection data as shown in FIG. 4. Here, taking into consideration the noise reduction process described above, an example in which the number of rotations is multiple or more will be described. However, if a noise reduction process capable of reducing noise with detection data from one rotation is adopted, the number of rotations can be one.

[0027] The diagnostic step 1a is positioned at a predetermined start position, for example, as follows: While visually observing the diagnostic step 1a, an operator manually operates the control device 12 to adjust the position of the diagnostic step 1a. By making such an adjustment, the diagnostic step 1a is positioned at a position extended from the lower platform 13b of the platform (hereinafter, this position will be referred to as reference position A), as shown in FIG.

[0028] The acquired multiple pieces of time-series magnetic detection data are transmitted to the monitoring center 50, where the noise reduction unit 513 of the position estimation device 51 performs the noise reduction process described above. As a result, time-series magnetic detection data D after noise reduction process is obtained, as shown in FIG. 6. The horizontal axis represents the elapsed time since the diagnostic step 1a passed the reference position A. The origin O (t = 0) corresponds to the reference position A shown in FIG. 5. The time-series magnetic detection data D represents the magnetism around the diagnostic step 1a while the diagnostic step 1a makes one revolution, i.e., the magnetization state of the components of the escalator 100. The circulating diagnostic step 1a returns to the reference position A every period T, and the detection value Da is detected by the magnetic sensor 251. At times t = tb, tc, te, and tf in FIG. 6, the diagnostic step 1a is positioned at B, C, E, and F in FIG. 5, respectively. Then, at t = ta, the diagnostic step 1a returns to the reference position A.

[0029] The magnetic map generator 511 generates a magnetic map that associates time-series magnetic detection data D with each position on the escalator 100 based on the moving speed of the diagnostic step 1a and the elapsed time from the reference position A. That is, the magnetic map M for one revolution of the diagnostic step 1a is expressed as a collection of data (magnetic detection value, position) such as the data group (Da, A),...,(Db, B),...,(Dc, C),...,(De, E),...,(Df, F),...,(Da, A). That is, the magnetic map M can be expressed as M(magnetic detection value, position).

[0030] A second method will be described. In the second method, a magnetic map M (magnetic detection values, positions) is generated using the detection values ​​of the acceleration sensor 253 provided in the sensor unit 25. FIG. 7 is a diagram showing time-series magnetic detection data D1 and time-series acceleration detection data D10. Symbols A to F correspond to positions A to F of the escalator 100 shown in FIG. 5. In the example shown in FIG. 5, when looking at the posture of the diagnostic step 1a, the second posture from position E to position F is upside down compared to the first posture from position A to position B. As the diagnostic step 1a moves from position B to position E, the posture of the diagnostic step 1a gradually changes from the first posture to the second posture. On the other hand, as the diagnostic step 1a moves from position F to position A, the posture of the diagnostic step 1a gradually changes from the second posture to the first posture.

[0031] The detection value of the acceleration sensor 253 provided in the diagnostic step 1a changes as the diagnostic step 1a moves. The acceleration detected by the acceleration sensor 253 includes acceleration caused by gravity and acceleration caused by vibration of the acceleration sensor 253. The general shape of the line representing the time-series acceleration detection data D10 is determined by the acceleration caused by gravity. The acceleration caused by vibration of the acceleration sensor 253 appears as a minute vibration on the line.

[0032] In the time-series acceleration detection data D10 shown in FIG. 7, the detection value is +d in the first posture and −d in the second posture. Then, as the diagnostic step 1a moves from position B to position E, the detection value gradually changes from +d to −d, and at position P1, the detection value reverses from positive to negative. Also, as the diagnostic step 1a moves from position F to position A, the detection value gradually changes from −d to +d, and at position P2, the detection value reverses from negative to positive. The timing at which the detection value reverses can be used as a reference position for generating a magnetic map. For example, if the reversal position P1 is set as the reference position, the period from the reversal position P1 to the next reversal position P1 is one cycle of the revolution.

[0033] The magnetic map generator 511 generates a magnetic map that associates the time-series magnetic detection data D with each position on the escalator 100 based on the moving speed of the diagnostic step 1a and the time elapsed from the reference position P1. That is, the magnetic map M (magnetic detection value, position) for one revolution of the diagnostic step 1a is expressed as a collection of data (magnetic detection value, position) such as the data group (Dp, P1),...,(De, E),...,(Df, F),...,(Da, A),...,(Db, B),...,(Dp, P1). In this way, in the second method, the reversal position P1 that appears in the detection value of the acceleration sensor 253 is used as the reference position when generating the magnetic map. As a result, the magnetic map generation operation can be automated and highly accurate.

[0034] Note that the reference position of escalator 100 may be set using the detection value of sound sensor 252 instead of the detection value of acceleration sensor 253. If the position (location) where the loudest sound is detected during one revolution of diagnostic step 1a is known in advance, the timing at which the maximum detection value is detected can be set as the reference position. For example, assume that when diagnostic step 1a is at position C in FIG. 5, the motor sound of drive motor 6 is detected as the maximum detection value. In this case, position C in FIG. 6 at which detection value Dc is detected is set as the reference position. Then, a magnetic map M (magnetic detection value, position) is generated based on the moving speed of diagnostic step 1a and the elapsed time from reference position C. The magnetic map M (magnetic detection value, position) for one revolution of diagnostic step 1a is represented by a collection of data (magnetic detection value, position) such as the data group (Dc, C),...,(De, E),...,(Df, F),...,(Da, A),...,(Db, B),...,(Dc, C).

[0035] A third method will be described. In the third method, the position of the diagnostic step 1a when the magnetization of a magnetized part of the escalator 100 is detected is set as the reference position. For example, suppose that the magnetism of the drive motor 6 is detected as the maximum detection value when the diagnostic step 1a is at position C in FIG. 5. In this case, position C in FIG. 6 where detection value Dc is detected is set as the reference position, and a magnetic map M (magnetic detection value, position) is generated based on the moving speed of the diagnostic step 1a and the elapsed time from reference position C. The magnetic map M (magnetic detection value, position) for one rotation of the diagnostic step 1a is represented by a collection of data (magnetic detection value, position) such as the data group (Dc, C),...,(De, E),...,(Df, F),...,(Da, A),...,(Db, B),...,(Dc, C). In this way, by setting the position of the diagnostic step 1a when the magnetization of the magnetized part is detected as the reference position, there is no need to provide an additional sensor (acceleration sensor 253) for identifying the reference position as in the second method, which can reduce costs.

[0036] (Self-position estimation processing) Fig. 8 is a diagram illustrating an example of the self-position estimation process. In Fig. 8, the line indicated by the symbol M represents the magnetic map M (magnetic detection value, position), and is a line of the same shape as the time-series magnetic detection data D shown in Fig. 6. The line indicated by the symbol S is the time-series sound detection data of the sound sensor 252. In Fig. 8, the vertical axis represents the detection values ​​of the magnetic sensor 251 and the sound sensor 252, and the horizontal axis represents the position on the escalator 100.

[0037] Here, consider a case where Db is detected as the detection value of the magnetic sensor 251. When this detection value is fitted to the magnetic map M (magnetic detection value, position), position B is obtained. In the magnetic map M (magnetic detection value, position) of FIG. 8, the value Db is located at positions other than position B, so when fitting, the detection values ​​before and after the detection value Db are also taken into consideration and the position of the detection value Db is determined to be position B. In other words, it can be seen that the position of the diagnostic step 1a when the detection value Db of the magnetic sensor 251 is detected is position B.

[0038] Then, the detection value Sb of the sound sensor 252, which is detected at the same time as the detection value Db, is estimated to be sound detection data detected when the diagnostic step 1a is at position B. In other words, self-position estimation is the estimation of the position of the diagnostic step 1a on the escalator 100 when the detection value Sb is detected. By performing such self-position estimation processing, it is possible to know where on the escalator 100 each detection value of the time-series sound detection data S was detected.

[0039] Fig. 9 is a flowchart showing an example of an abnormality detection operation in the abnormality diagnosis device 52. The monitoring center 50 transmits a data transmission command to the data collection device 30, thereby acquiring a plurality of time-series detection data groups from the data collection device 30. Then, the abnormality diagnosis process is performed sequentially on the acquired plurality of time-series detection data groups. The flowchart shown in Fig. 9 shows the process performed in response to a single data transmission command, and is repeatedly executed at predetermined time intervals.

[0040] In step S90, a data transmission command is sent to the data collecting device 30 to collect multiple time-series detection data groups stored in the data storage unit 301. The time-series detection data groups include multiple types of time-series detection data groups corresponding to the sensors provided in the sensor unit 25. In the example shown in FIG. 3, the sensor unit 25 is provided with a magnetic sensor 251, a sound sensor 252, and an acceleration sensor 253, so the time-series detection data groups include a time-series magnetic detection data group, a time-series sound detection data group, and a time-series acceleration detection data group. In step S91, the noise reduction unit 522 performs noise reduction processing on the first time-series detection data group of the multiple time-series detection data groups.

[0041] In step S92, the abnormality estimation unit 521 determines whether or not an abnormality has occurred based on the time-series sound detection data and time-series acceleration detection data after noise reduction processing. If it is determined in step S92 that an abnormality has occurred (YES), the process proceeds to step S94, and if it is determined that an abnormality has not occurred (NO), the process proceeds to step S93. In step S93, the abnormality estimation unit 521 determines whether or not there is a sign of an abnormality based on the time-series sound detection data and time-series acceleration detection data after noise reduction processing. If it is determined in step S93 that there is a sign of an abnormality (YES), the process proceeds to step S94, and if it is determined that there is no sign of an abnormality (NO), the process proceeds to step S97.

[0042] FIG. 10 is a diagram illustrating an example of the abnormality occurrence determination in step S92 and the abnormality sign determination in step S93. In the abnormality occurrence determination and abnormality sign determination, the time-series sound detection data and time-series acceleration detection data after noise reduction processing are compared with the determination reference data. The determination reference data is stored in the storage unit 523. In the initial operation of generating the magnetic map M (magnetic detection values, position) after installing the diagnostic step 1a, a time-series detection data group is acquired from the data collecting device 30. The time-series detection data after noise reduction processing of the time-series detection data group is stored in the storage unit 523 as the determination reference data. The time-series detection data includes the time-series magnetic detection data, the time-series sound detection data, and the time-series acceleration detection data.

[0043] 10 is a diagram showing time-series sound detection data S11, S12 obtained by noise reduction processing, and time-series sound detection data S0 as judgment reference data. The horizontal axis represents time t. Line S1 is a first judgment line obtained by multiplying each value of the judgment reference data S0 by α1. Line S2 is a second judgment line obtained by multiplying each value of the judgment reference data S0 by α2 (>α1). The second judgment line S2 is used to judge whether an abnormality has occurred. The first judgment line S1 is used to judge whether an abnormality has occurred.

[0044] In the example shown in FIG. 10, the line of the time-series sound detection data S11 crosses the first judgment line S1 near time tc. In this case, the abnormality estimation unit 521 determines that a sign of abnormality has been detected in any of the components of the escalator 100, that is, that an abnormality sign has occurred. The time-series sound detection data S12 is a line obtained when further time has passed since the acquisition of the time-series sound detection data S11. The line of the time-series sound detection data S12 crosses the second judgment line S2 near t=tc. In this case, the abnormality estimation unit 521 determines that an abnormality has occurred in any of the components of the escalator 100, that is, that an abnormality has occurred.

[0045] 10, the determination of an abnormality occurrence or an abnormality sign from the temporal change of the time-series sound detection data has been described, but the determination of an abnormality occurrence or an abnormality sign is also performed using the time-series acceleration detection data. If it is determined that an abnormality has occurred in at least one of the time-series sound detection data and the time-series acceleration detection data, it is determined that an abnormality has occurred in step S92. Similarly, if it is determined that an abnormality sign has occurred in at least one of the time-series sound detection data and the time-series acceleration detection data, it is determined that an abnormality sign has occurred in step S93.

[0046] Returning to the flowchart of Figure 9, in step S94, a process is performed to estimate the location on escalator 100 where an abnormality or an abnormality precursor is occurring. The noise reduction process of step S91 described above obtains noise-reduced time-series magnetic detection data, time-series sound detection data, and time-series acceleration detection data. In Figure 10, the detection value of time-series sound detection data S11, S12 at t = tc is Sc1 for time-series sound detection data S11, and Sc2 for time-series sound detection data S12. Furthermore, the detection value of the time-series magnetic detection data at t = tc is Dc, as shown in Figure 6.

[0047] The abnormality diagnosis device 52 acquires the position where the detection value Dc of the time-series magnetic detection data is obtained by having the self-position estimation unit 512 perform a self-position estimation process. In the self-position estimation process, the position C is obtained by fitting the detection value Dc to the magnetic map M (magnetic detection value, position) (see FIG. 8). As a result, it is found that the detection value Sc1 detected at the same timing as the detection value Dc is the detection value obtained when the diagnostic step 1a was located at position C. In other words, it is found that a symptom of an abnormality has occurred in a component located near position C. By performing the same process on the detection value Sc2, it is found that an abnormality has occurred in a component located near position C.

[0048] In step S94, the location where the abnormality sign or abnormality has occurred is estimated. Furthermore, in step S95, the part where the abnormality sign or abnormality has occurred is estimated. As shown in FIG. 5, the chain 2, terminal gear 4, drive gear 5, drive motor 6, etc. are provided near position C of escalator 100. In addition to estimating the location of the abnormality, abnormality estimation unit 521 also estimates the abnormal part. By estimating not only the occurrence of an abnormality but also the abnormal part, it is possible to quickly and appropriately deal with the occurrence of an abnormality.

[0049] If an abnormality occurs in the chain 2, terminal gear 4, drive gear 5, or drive motor 6, each component will produce a characteristic abnormal sound or vibration. The time-series sound detection data and time-series acceleration detection data include not only the magnitude of the sound or vibration, but also the frequency of the sound or vibration. The storage unit 523 also stores in advance failure identification data that lists the frequencies of abnormal sounds and vibrations for each component and each type of failure. The abnormality estimation unit 521 estimates the component in which an abnormality or a sign of an abnormality has occurred and the nature of the failure, based on the sound frequency and vibration frequency at position C.

[0050] In step S96, the occurrence of an abnormality or an abnormality sign is notified by notification unit 524. The notification information includes at least one of the occurrence of the abnormality or abnormality sign, the location where the abnormality or abnormality sign occurs, the part, and the details of the failure. Once the processing of step S96 is completed, the process proceeds to step S97. In step S97, it is determined whether the noise reduction processing and the abnormality occurrence or abnormality sign determination processing have been completed for all of the multiple time-series detection data groups. If it is determined in step S94 that the processing has not been completed (NO), the process returns to step S91, and if it is determined that the processing has been completed (YES), the series of diagnostic processing ends.

[0051] As described above, in the diagnostic system of this embodiment, when a diagnostic step 1a equipped with a diagnostic sensor including magnetic sensor 251 is introduced, the diagnostic step 1a is circulated to create a magnetic map M (magnetic detection value, position). This magnetic map M (magnetic detection value, position) is a map that represents the magnetic state at each position within escalator 100. Therefore, the detection position of a diagnostic sensor detection value acquired during escalator operation can be obtained by comparing the magnetic detection value detected at the same time as the detected value with the magnetic map M (magnetic detection value, position). In other words, even in situations where the operating speed changes, the detection position of the diagnostic sensor detection value can be accurately estimated, making it possible to perform continuous diagnosis.

[0052] Furthermore, in this embodiment, as shown in Fig. 3, data detected by sensor unit 25 in diagnostic step 1a is transmitted via communication to remote monitoring center 50, which is provided with position estimation device 51 and abnormality diagnosis device 52. This allows the status of escalator 100 to be constantly monitored from a remote location. Furthermore, constant monitoring of multiple escalators can be easily performed at monitoring center 50.

[0053] As described above, in the position estimation of the diagnostic step 1a, the detected position is estimated by checking the detection value of the magnetic sensor 251 against the magnetic map M (magnetic detection value, position). Therefore, in order to perform position estimation with high accuracy, it is preferable that the output of the magnetic sensor 251 is stable. Therefore, in this embodiment, the magnetization of parts provided on the escalator 100 is used to correct the offset and drift of the magnetic sensor 251.

[0054] For example, since the magnetization of the drive motor 6 is stable, the detection value of the magnetic sensor 251 at position C close to the drive motor 6 is used as the reference value for correction. Then, the detection value at position C is used as the reference, that is, the detection values ​​at other positions are corrected so that the detection value at position C is always constant. For example, if the detection value at position C becomes β times larger than the initial value, the detection values ​​at all positions are corrected by multiplying them by (1 / β). As a result, the influence of changes in the output of the magnetic sensor 251 can be eliminated, and deterioration of the self-position estimation accuracy can be prevented. This correction operation may be performed by any of the control unit 26, data collection device 30, position estimation device 51, and abnormality diagnosis device 52 provided in the sensor terminal 24.

[0055] In the above-described embodiment, a self-position estimation process was performed to associate sound detection data with a position on the escalator 100 based on the detection data of the magnetic sensor 251 and the generated magnetic map M (magnetic detection value, position). Furthermore, the self-position estimation process may also be performed using the reversal timing in the detection data of the acceleration sensor 253. The reversal timing occurs when the diagnostic step 1a moves to a specific position on the escalator 100. Therefore, by using this reversal timing as well, the accuracy of the self-position estimation can be improved, and an abnormality diagnosis can be performed with high accuracy. Note that a diagnostic sensor other than the acceleration sensor 253 may also be used. For example, an altitude sensor or the like may be further added as a diagnostic sensor, and its detection data may also be used.

[0056] The configuration of the diagnostic system 1000 is not limited to the configuration shown in the block diagram of FIG.

[0057] (Diagnostic system configuration variation 1) FIG. 11 is a block diagram showing a first modification of the configuration of the diagnostic system 1000. In the diagnostic system 1000 of FIG. 3, a plurality of time-series detection data groups stored in the data storage unit 301 are transmitted by the communication unit 302 to the communication device 53 of the monitoring center 50 via the network 40. On the other hand, in the diagnostic system 1000A shown in FIG. 11, the communication unit 302 of the control device 12 and the communication device 53 of the monitoring center 50 are omitted. In the diagnostic system 1000A, a system is adopted in which the plurality of time-series detection data groups stored in the data storage unit 301 are collected by an operator during regular inspection and sent to the monitoring center 50. For example, a portable storage medium such as a USB flash drive or a portable hard disk drive is used to collect the data. Since the communication unit 302 and the communication device 53 are not required, costs related to the communication system can be reduced.

[0058] (Diagnostic system configuration variation 2) 12 is a block diagram showing a second modification of the configuration of the diagnostic system 1000. In the diagnostic system 1000B of the second modification, the data storage unit 301 and the communication unit 302, which were provided in the control device 12, are provided in the diagnostic step 1a. A plurality of time-series detection data groups stored in the data storage unit 301 are transmitted from the communication unit 302 provided in the diagnostic step 1a to the communication device 53 of the monitoring center 50 via the network 40.

[0059] (Diagnostic system configuration variation 3) Fig. 13 is a block diagram showing a third modification of the configuration of the diagnostic system 1000. The diagnostic system 1000C of the third modification does not include the communication unit 302 and the communication device 53 that are provided in the diagnostic system 1000B of Fig. 12. A plurality of time-series detection data groups stored in the data storage unit 301 are collected by an operator during regular inspection and sent to the monitoring center 50. The position estimation device 51 and the abnormality diagnosis device 52 of the monitoring center 50 create a magnetic map M (magnetic detection values, position) and perform diagnostic processing based on the collected time-series detection data groups.

[0060] (Diagnostic system configuration variation 4) Fig. 14 is a block diagram showing a fourth modification of the configuration of diagnostic system 1000. In diagnostic system 1000D of the fourth modification, position estimation device 51 and abnormality diagnosis device 52, which are provided in monitoring center 50 in diagnostic system 1000 of Fig. 3, are provided in control device 12 of escalator 200. However, notification unit 524, which is provided in abnormality diagnosis device 52 of Fig. 3, is arranged in monitoring center 50.

[0061] In the diagnostic system 1000D, the generation and storage of the magnetic map M (magnetic detection values, position), and the diagnostic processing excluding the processing of step S96 in the diagnostic processing shown in Fig. 9 are performed by the position estimation device 51 and the abnormality diagnosis device 52 provided in the control device 12. If the diagnostic processing results in the occurrence of an abnormality or a sign of an abnormality, notification information is transmitted from the communication unit 302 to the communication device 53 of the monitoring center 50 via the network 40. The notification information is then presented by the notification unit 524. Of course, the monitoring center 50 can also acquire the time-series detection data group stored in the data storage unit 301 of the data collection device 30 by transmitting a transmission command for the time-series detection data group to the control device 12.

[0062] (Diagnostic system configuration variation 5) Fig. 15 is a block diagram showing a fifth modification of the configuration of the diagnostic system 1000. The diagnostic system 1000E of the fifth modification is configured by replacing the communication unit 302 of the data collecting device 30 with a wireless communication unit 302A for short-range communication in the diagnostic system 1000D shown in Fig. 14, omitting the communication device 53 of the monitoring center 50, and providing an information processing device 54 such as a personal computer in place of the notification unit 524 of the monitoring center 50. The wireless communication unit 302A receives detection data of the sensors 251 to 253 from the wireless communication unit 27 provided in the diagnostic step 1a.

[0063] As a result of the diagnostic processing by the position estimation device 51 and the abnormality diagnosis device 52 provided in the control device 12, the generated magnetic map M (magnetic detection values, position) and the time-series detection data group stored in the data storage unit 301 are collected by an operator during regular inspection and sent to the monitoring center 50. At the monitoring center 50, the diagnostic processing results and the magnetic map M (magnetic detection values, position) can be confirmed by an information processing device 54. The information processing device 54 can also confirm and analyze the collected time-series detection data group.

[0064] 15, the abnormality diagnosis device 52 is not provided with the notification unit 524, but the abnormality diagnosis device 52 may be provided with the notification unit 524. By providing the notification unit 524, an operator can confirm an abnormal state during a regular inspection and can deal with the abnormality on the spot. Of course, even in a configuration without the notification unit 524, the diagnosis result stored in the storage unit 523 can be read out by a personal computer or the like to confirm the diagnosis result.

[0065] (Diagnostic system configuration variation 6) Fig. 16 is a block diagram showing a sixth modification of the configuration of the diagnostic system 1000. In the diagnostic system 1000F of the sixth modification, the data storage unit 301, the communication unit 302, the position estimation unit 51, and the abnormality diagnosis unit 52, which are provided in the control device 12 in the diagnostic system 1000D of Fig. 14, are arranged in the diagnostic step 1a, and the wireless communication unit 27, which is provided in the diagnostic step 1a, is omitted.

[0066] In the diagnostic system 1000F, the storage of detection data detected by the sensor unit 25, the generation of a magnetic map M (magnetic detection values, position) based on the detection data, and diagnostic processing based on the detection data and the magnetic map M (magnetic detection values, position) are all performed by a data storage unit 301, a position estimation device 51, and an abnormality diagnosis device 52 provided in the diagnostic step 1a. The diagnostic results are transmitted from the communication unit 302 to a communication device 53 of the monitoring center 50 via the network 40. The monitoring center 50 issues a notification by a notification unit 524 based on the received diagnostic results. Of course, the monitoring center 50 can also acquire the time-series detection data group stored in the data storage unit 301 by transmitting a transmission command for the time-series detection data group to the control device 12.

[0067] (Diagnostic system configuration variation 7) Fig. 17 is a block diagram showing a seventh modification of the configuration of the diagnostic system 1000. The diagnostic system 1000G of the seventh modification is configured by omitting the communication unit 302 provided in the diagnostic step 1a and the communication device 53 of the monitoring center 50 in the diagnostic system 1000F shown in Fig. 16, and by arranging an information processing device 54 such as a personal computer in place of the notification unit 524 of the monitoring center 50.

[0068] As a result of the diagnostic processing by the position estimation device 51 and the abnormality diagnosis device 52 provided in the diagnostic step 1a, the generated magnetic map M (magnetic detection values, position) and the time-series detection data group stored in the data storage unit 301 are collected by an operator during a regular inspection and sent to the monitoring center 50. At the monitoring center 50, the diagnostic processing results and the magnetic map M (magnetic detection values, position) can be confirmed using an information processing device 54. The information processing device 54 can also be used to confirm and analyze the collected time-series detection data group. Furthermore, as in the case of the fifth modification, during a regular inspection, an operator can read out the diagnostic results stored in the storage unit 523 using a personal computer or the like, thereby confirming the diagnostic results and dealing with any abnormalities on the spot. In addition, an alarm unit 524 may be provided.

[0069] 3 and 11-17, the functional units in the configuration, for example, the functional units in the position estimation device 51 and the abnormality diagnosis device 52, may be realized by a program executed by a combination of an electric circuit, an electronic circuit, a logic circuit, and an integrated circuit incorporating them, as well as a microcomputer, a processor, and similar arithmetic devices, a ROM, a RAM, a flash memory, a hard disk, an SSD, a memory card, an optical disk, and similar storage devices, a bus, a network, and similar communication devices, and various peripheral devices, and the present invention can be realized in any of the above-mentioned embodiments. Furthermore, in the embodiments, two or more programs may be realized as one program, and one program may be realized as two or more programs.

[0070] According to the embodiment of the present invention described above, the following advantageous effects are achieved.

[0071] (C1) As shown in Figures 1 and 3, diagnostic system 1000 is a diagnostic system 1000 that diagnoses abnormalities in escalator 100, which is a passenger conveyor that transports passengers by circulating a plurality of steps 1, 1a connected endlessly, and includes: diagnostic step 1a included in the plurality of steps 1, 1a and equipped with one or more diagnostic sensors including at least magnetic sensor 251; magnetic map generation unit 511 that generates magnetic map M (magnetic detection value, position) which is the correlation between the position on escalator 100 during one circulation of diagnostic step 1a and the detection value of magnetic sensor 251; self-position estimation unit 512 that estimates the position on escalator 100 where the detection value of sound sensor 252 was detected based on magnetic map M (magnetic detection value, position) and the detection value of magnetic sensor 251 during circular movement; and abnormality estimation unit 521 that performs abnormality diagnosis based on the detection value of sound sensor 252.

[0072] As shown in Fig. 8, magnetic map M (magnetic detection value, position) represents the correlation between the position on escalator 100 and the detection value of magnetic sensor 251 while diagnostic step 1a makes one circulation. Then, based on magnetic map M (magnetic detection value, position) and the detection value of magnetic sensor 251 during circulation, the position on escalator 100 where the detection value of sound sensor 252 was detected is estimated. Therefore, even in situations where the operating speed changes during escalator operation, the detection position of the detection value of the diagnostic sensor can be accurately estimated, making it possible to perform continuous diagnosis.

[0073] (C2) As shown in Figures 5 and 7, the diagnostic step 1a is equipped with an acceleration sensor 253 and a sound sensor 252 as diagnostic sensors that can identify the position of the circulating diagnostic step 1a on the escalator 100, and the magnetic map generator 511 may generate the magnetic map M (magnetic detection value, position) using the position identified by the position identification sensor (e.g., reversal position P1) as a reference position. By using the position identified by the position identification sensor as the reference position when generating the magnetic map, the magnetic map generation operation can be automated and made more accurate.

[0074] (C3) Alternatively, the diagnostic step 1a may be provided with an acceleration sensor 253 as a position identification sensor, and the magnetic map generator 511 may estimate the timing at which the posture of the diagnostic step 1a is reversed based on the sensor output of the acceleration sensor 253, and generate the magnetic map M (magnetic detection value, position) using the reversal position P1 of the diagnostic step 1a at that timing as a reference position. The detection of the reversal position P1 by the acceleration sensor 253 can be easily performed with high accuracy.

[0075] (C4) As shown in Figures 5 and 6, the escalator 100 includes a magnetized part (e.g., the drive motor 6), and the magnetic map generator 511 may generate the magnetic map M (magnetic detection value, position) using the position C of the diagnostic step 1a when the magnetic sensor 251 detects the magnetization of the magnetized part as the reference position. By using the position of the diagnostic step 1a when the magnetization of the magnetized part is detected as the reference position, there is no need to provide an additional sensor (acceleration sensor 253) for identifying the reference position. This allows for cost reduction.

[0076] (C5) As shown in Figures 5 and 7, self-position estimation unit 512 may estimate the position where the detection value of sound sensor 252 acting as a diagnostic sensor is detected, based on magnetic map M (magnetic detection value, position) and the detection values ​​(e.g., reversal position P1) of magnetic sensor 251 and acceleration sensor 253 acting as a position identification sensor during circular movement. Reversal position P1 detected by acceleration sensor 253 occurs when diagnostic step 1a moves to a specific position on escalator 100. Therefore, by also using this reversal position P1 in self-position estimation, the accuracy of self-position estimation can be improved, and abnormality diagnosis can be performed with high accuracy.

[0077] (C6) Furthermore, escalator 100 may be provided with a magnetized part (for example, drive motor 6) that has magnetization, and the output error of magnetic sensor 251 may be corrected based on the magnetization of the magnetized part. For example, correction processing may be performed by control unit 26 or data collection device 30. As a result, the influence of changes in the output of magnetic sensor 251 can be eliminated, and deterioration of the self-position estimation accuracy can be prevented.

[0078] (C7) As in the process of step S95 in Fig. 9, the abnormality estimation unit 521 estimates the abnormal part based on the position estimated by the self-position estimation unit 512 and the detection data of the diagnostic sensor (for example, the sound sensor 252). By not only detecting the occurrence of an abnormality but also estimating the abnormal part, it is possible to deal with the occurrence of an abnormality quickly and appropriately.

[0079] (C8) As shown in Figures 3 and 12, the diagnostic system further includes a communication unit 302 provided on the housing frame 3 of escalator 100 or on diagnostic step 1a, on which drive motor 6 for circulating multiple steps 1, 1a is disposed, and monitoring center 50 as a remote monitoring unit that communicates with communication unit 302 to receive and transmit data and that is provided with self-position estimation unit 512 and abnormality diagnosis device 52, and transmits detection data from the diagnostic sensor to monitoring center 50 via communication unit 302. Thus, escalator 100 can be constantly monitored remotely.

[0080] (C9) Furthermore, as shown in Fig. 3, communication unit 302 may be provided on housing frame 3 of escalator 100, and diagnostic step 1a may further include wireless communication unit 27 that transmits detection data from the diagnostic sensor to communication unit 302 provided on housing frame 3 by wireless communication, and communication unit 302 may transmit the detection data transmitted from diagnostic step 1a to monitoring center 50. A short-range wireless device with low power consumption may be used for wireless communication unit 27, and a small-capacity power source such as a battery may be used as the power source to be provided on diagnostic step 1a.

[0081] (C10) As shown in Figures 14 and 16, self-position estimation unit 512 and abnormality estimation unit 521 are provided on housing frame 3 or diagnostic step 1a of escalator 100, on which drive motor 6 for circulating multiple steps 1, 1a is disposed, and further includes communication unit 302 provided on housing frame 3 or diagnostic step 1a, and monitoring center 50 that receives and transmits data by communicating with communication unit 302, and the diagnosis result of abnormality estimation unit 521 is transmitted to monitoring center 50 by communication unit 302.

[0082] In such a configuration, monitoring center 50 only needs to prepare a device that can receive the inspection results, and it is possible to receive the diagnosis results via an information terminal such as a personal computer or mobile phone via the Internet. Therefore, even without setting up a large-scale monitoring center, it is possible for workers to receive the diagnosis results via an information terminal and inspect escalators 100 that have abnormalities.

[0083] (C11) As shown in Figures 11, 13, 15, and 17, housing frame 3 of escalator 100, on which drive motor 6 for circulating multiple steps 1, 1a is disposed, or diagnostic step 1a further includes data storage unit 301 that accumulates detection data from sensor unit 25. In this case, the detection data accumulated in data storage unit 301 is collected by an operator, and self-position estimation unit 512 and abnormality estimation unit 521 perform data analysis of the detection data, eliminating the need for a communication device.

[0084] (C12) As shown in Figures 15 and 17, self-position estimation unit 512 and abnormality estimation unit 521 are provided on housing frame 3 or diagnostic step 1a of escalator 100 on which drive motor 6 for circulating multiple steps 1, 1a is disposed, and housing frame 3 or diagnostic step 1a on which self-position estimation unit 512 and abnormality estimation unit 521 are provided further includes memory unit 523 that stores the diagnosis result of abnormality estimation unit 521. In this case, during regular inspection, an operator can read out the diagnosis result stored in memory unit 523 using a personal computer or the like, thereby confirming the diagnosis result and dealing with the abnormality on the spot.

[0085] The above-described embodiments and various modifications are merely examples, and the present invention is not limited to these details as long as the features of the invention are not impaired. For example, the present invention can be applied to passenger conveyors other than escalators. Furthermore, although various embodiments and modifications have been described above, the present invention is not limited to these details. Other aspects conceivable within the scope of the technical concept of the present invention are also included within the scope of the present invention. [Explanation of symbols]

[0086] 1...step, 1a...diagnostic step, 2...chain, 3...casing frame, 4...terminal gear, 6...drive motor, 9...lower terminal gear, 12...control device, 24...sensor terminal, 25...sensor unit, 26...control unit, 27...wireless communication unit, 30...data collection device, 50...monitoring center, 51...position estimation device, 52...abnormality diagnosis device, 53...communication device, 54...information processing device, 251...magnetic sensor, 252...sound sensor, 253...acceleration sensor, 301...data storage unit, 302...communication unit, 511...magnetic map generation unit, 512...self-position estimation unit, 513, 522...noise reduction unit, 514, 523...storage unit, 521...abnormality estimation unit, 524...alarm unit, 1000, 1000A to 1000G...diagnosis system

Claims

1. A diagnostic system for diagnosing abnormalities in a passenger conveyor that transports passengers by circulating a plurality of steps connected in an endless manner, comprising: a diagnostic step included in the plurality of steps, the diagnostic step including one or more diagnostic sensors including at least a magnetic sensor; a magnetic map generator that generates a magnetic map that is a correlation between a position on the passenger conveyor and a detection value of the magnetic sensor during one cycle of the diagnostic step; a position estimation unit that estimates a position on the passenger conveyor where the detection value of the diagnostic sensor is detected based on the magnetic map and the detection value of the magnetic sensor during circulation movement; an abnormality diagnosis unit that performs abnormality diagnosis based on the detection value of the diagnostic sensor, the diagnostic step includes, as the diagnostic sensor, an acceleration sensor serving as a position specifying sensor that can specify the position of the diagnostic step on the passenger conveyor, the diagnostic step moving in a circular motion; The magnetic map generation unit estimates the timing at which the posture of the diagnostic step will be reversed based on the sensor output of the acceleration sensor, and generates the magnetic map using the position of the diagnostic step at that timing as a reference position.

2. A diagnostic system for diagnosing abnormalities in a passenger conveyor that transports passengers by circulating a plurality of steps connected in an endless manner, comprising: a diagnostic step included in the plurality of steps, the diagnostic step including one or more diagnostic sensors including at least a magnetic sensor; a magnetic map generator that generates a magnetic map that is a correlation between a position on the passenger conveyor and a detection value of the magnetic sensor during one cycle of the diagnostic step; a position estimation unit that estimates a position on the passenger conveyor where the detection value of the diagnostic sensor is detected based on the magnetic map and the detection value of the magnetic sensor during circulation movement; an abnormality diagnosis unit that performs abnormality diagnosis based on the detection value of the diagnostic sensor, the passenger conveyor includes a magnetized component having magnetization; The magnetic map generating unit generates the magnetic map using a position of the diagnostic step when the magnetic sensor detects the magnetization of the magnetized part as a reference position.

3. A diagnostic system for diagnosing abnormalities in a passenger conveyor that transports passengers by circulating a plurality of steps connected in an endless manner, comprising: a diagnostic step included in the plurality of steps, the diagnostic step including one or more diagnostic sensors including at least a magnetic sensor; a magnetic map generator that generates a magnetic map that is a correlation between a position on the passenger conveyor and a detection value of the magnetic sensor during one cycle of the diagnostic step; a position estimation unit that estimates a position on the passenger conveyor where the detection value of the diagnostic sensor is detected based on the magnetic map and the detection value of the magnetic sensor during circulation movement; an abnormality diagnosis unit that performs abnormality diagnosis based on the detection value of the diagnostic sensor, The passenger conveyor is provided with a magnetized part having magnetism, The diagnostic system further comprises a correction unit that corrects an output error of the magnetic sensor based on the magnetization of the magnetized part.

4. 10. The diagnostic system of claim 1, The position estimation unit estimates a position where the detection value of the diagnostic sensor is detected based on the magnetic map and the detection values ​​of the magnetic sensor and the acceleration sensor during circular movement.

5. The diagnostic system according to any one of claims 1 to 4, The abnormality diagnosis unit estimates an abnormal part based on the position estimated by the position estimation unit and the detection data of the diagnostic sensor.

6. The diagnostic system according to any one of claims 1 to 4, a communication device provided on a fixed portion of the passenger conveyor where a drive device for circulating the steps is disposed or on the diagnostic step; a remote monitoring unit that communicates with the communication device to receive and transmit data, and that is provided with the position estimation unit and the abnormality diagnosis unit; A diagnostic system that transmits detection data from the diagnostic sensor to the remote monitoring unit via the communication device.

7. 7. The diagnostic system of claim 6, the communication device is provided at the fixed portion of the passenger conveyor, the diagnostic step further includes a wireless communication device that transmits detection data of the diagnostic sensor to the communication device provided in the fixed part by wireless communication; The communication device transmits the detection data transmitted from the diagnostic step to the remote monitoring unit.

8. The diagnostic system according to any one of claims 1 to 4, the position estimation unit and the abnormality diagnosis unit are provided on a fixed portion of the passenger conveyor where a drive device for circulating the plurality of steps is disposed, or on the diagnosis step; a communication device provided on the fixed portion or the diagnostic step of the passenger conveyor; a remote monitoring unit that communicates with the communication device to receive and transmit data; A diagnostic system in which the diagnostic result of the abnormality diagnostic unit is transmitted to the remote monitoring unit by the communication device.

9. The diagnostic system according to any one of claims 1 to 4, The fixed portion of the passenger conveyor on which a drive device for circulating the plurality of steps is disposed or the diagnostic step is The diagnostic system further comprises a data storage unit that stores detection data from the diagnostic sensor.

10. The diagnostic system according to any one of claims 1 to 4, the position estimation unit and the abnormality diagnosis unit are provided on a fixed portion of the passenger conveyor where a drive device for circulating the plurality of steps is disposed, or on the diagnosis step; The diagnostic system, wherein the fixed unit or the diagnostic step provided with the position estimation unit and the abnormality diagnosis unit further includes a diagnostic result storage unit that stores a diagnostic result of the abnormality diagnosis unit.

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