Passenger conveyor diagnostic system and diagnostic method

Abstract

To provide a passenger conveyor diagnostic system capable of monitoring a passenger conveyor for a long period of time.SOLUTION: A passenger conveyor diagnostic system includes a diagnostic step formed by mounting a magnetic sensor, a diagnostic sensor, a battery, and a control unit. The passenger conveyor diagnostic system includes a storage device for accumulating a timing database for regulating operation of the magnetic sensor and the diagnostic sensor and output of the diagnostic sensor, a magnetic map generation unit for forming a magnetic map indicating a correlation with the position of the diagnostic step in the passenger conveyor by using accumulated detection values of the magnetic sensor, a position estimation unit for calculating the position of the diagnostic step from the output of the magnetic sensor and the magnetic map, and a trigger generation unit for generating a trigger for operating the diagnostic sensor from the estimated output and the timing database. The control unit controls the diagnostic operation, determines the timing of acquiring data of the diagnostic sensor by the generated trigger, and restricts the operation of the diagnostic sensor at timing other than the timing of acquiring data.SELECTED DRAWING: Figure 3

Description

[Technical Field]

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

[0002] Patent Document 1 describes an inspection jig that measures the inside of an escalator by mounting a sensor inside the internal space of a diagnostic step and circulating the diagnostic step inside the escalator. With this inspection jig, regular inspections can be made more efficient by replacing regular steps (also called "steps") with diagnostic steps during regular inspections.

[0003] Patent Document 2 also describes a diagnostic system for a passenger conveyor equipped with a diagnostic sensor. This diagnostic system can accurately estimate the detection position of the diagnostic sensor even when the diagnostic step operating speed changes. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2006-76729 [Patent Document 2] Patent application 2021-97590 publication Summary of the Invention [Problem to be solved by the invention]

[0005] However, the inspection jig described in Patent Document 1 or Patent Document 2 may be used to continuously monitor passenger conveyors in commercial operation not only during periodic inspections but also for a considerable period of time, for example, six months or more, such as in accordance with the inspection cycle, by permanently installing a battery-powered diagnostic step. In this case, to avoid disrupting commercial operation due to battery replacement, it is required that the diagnostic function be maintained without battery replacement while the diagnostic step is permanently installed on the passenger conveyor.

[0006] Furthermore, the high-precision cameras and microphones (hereinafter also referred to as "sound sensors" or "mics") installed in the diagnostic steps consume power in proportion to the operating time, so that continuous operation over a long period of time requires a larger driving battery capacity. In this case, the battery size also increases in proportion to the capacity, so an increase in the weight of a diagnostic step that is installed for a long period of time is unavoidable, and the burden of handling heavy objects increases when collecting data during periodic inspections, replacing only the battery, or removing and replacing the entire diagnostic step.

[0007] Furthermore, continuing commercial operation of a passenger conveyor with a heavy diagnostic step installed not only accelerates wear on the entire device, but also wastes power for operation. In other words, to permanently install a battery-powered diagnostic step on a passenger conveyor in commercial operation and continue monitoring for a considerable period of time, either a large-capacity battery or a device that can be driven with low power consumption is required. However, the battery capacity that can be mounted on a diagnostic step with the same external shape as a step is limited by its size and weight. The present invention has been made in consideration of the above-mentioned problems, and its purpose is to provide a step-type passenger conveyor diagnostic system that can continuously monitor for a long period of time, similar to the cycle of regular inspections. [Means for solving the problem]

[0008] The present invention, which solves the above-mentioned problems, provides a passenger conveyor diagnostic system having a diagnostic step formed by mounting at least a magnetic sensor, a diagnostic sensor, a battery, and a control unit in the internal space of one of the steps that are endlessly connected and move on a passenger conveyor that transports passengers, the passenger conveyor diagnostic system comprising: a storage device that stores a timing database that defines the operation of the magnetic sensor and the diagnostic sensor, and the output of the diagnostic sensor; a magnetic map generation unit that uses the detection values ​​of the magnetic sensor stored in the storage device to create a magnetic map that is a correlation with the position of the diagnostic step within the passenger conveyor; a position estimation unit that calculates the position of the diagnostic step from the output of the magnetic sensor and the magnetic map; and a trigger generation unit that generates a trigger to operate the diagnostic sensor based on the output of the position estimation unit and the timing database stored in the storage device, wherein the control unit operates the magnetic sensor and the diagnostic sensor based on the definitions in the timing database, determines the timing of data acquisition from the diagnostic sensor based on the generated trigger, and restricts operation of the diagnostic sensor outside of the data acquisition timings. [Effects of the Invention]

[0009] According to the present invention, a step-type passenger conveyor diagnostic system can be provided that is capable of continuous monitoring over a long period of time, similar to the cycle of a regular inspection or the like. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a schematic diagram showing a general configuration of a passenger conveyor (escalator) to which the present invention is applied. [Figure 2] 1 is a perspective view showing a schematic configuration of a diagnostic step used in a passenger conveyor diagnostic system according to an embodiment of the present invention (hereinafter also referred to as "this diagnostic system"). [Figure 3] FIG. 2 is a functional block diagram of the present diagnostic system. [Figure 4] FIG. 10 is a diagram illustrating an example of noise reduction processing. [Figure 5] FIG. 10 is a diagram illustrating an example of positioning of a diagnostic step. [Figure 6]FIG. 10 is a diagram showing an example of time-series magnetic detection data after noise reduction processing. [Figure 7] FIG. 10 is a diagram illustrating a second method of position association. [Figure 8] FIG. 10 is a diagram illustrating an example of a self-position estimation process. [Figure 9] 10 is a flowchart illustrating an example of an abnormality detection operation. [Figure 10] 10A and 10B are diagrams illustrating an example of abnormality occurrence determination and abnormality sign determination. [Figure 11] This is a diagram that defines the dimension from the terminal gear to the end of the step rail (commonly known as a "truss"). DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. As an overview of the present diagnostic system 1000 (Fig. 3), the diagnostic step 1a (Figs. 1 to 3) circulates within the escalator 100 (Figs. 1 and 4), so it is necessary to associate the time when data is obtained with the position of the diagnostic step 1a at that time. First, an acceleration sensor 253 (Fig. 3) is used to obtain the timing when the diagnostic step 1a is pulled into the back side of the escalator 100 and reverses, and the step position is estimated based on the elapsed time from the reversal. However, as will be described later with reference to Fig. 8, the present diagnostic system 1000 is able to estimate the step position more accurately.

[0012] 1 is a schematic diagram showing the general configuration of an escalator 100 to which the present invention is applied. The escalator 100 includes steps 1, 1a, a step chain 2, a housing frame 3, a terminal gear 4, a drive motor 6, a lower terminal gear 9, handrails 8, step rails 11a, 11b, a control panel 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 panel 12 are provided within the housing frame 3.

[0013] In the escalator 100, a plurality of steps 1 and one diagnostic step 1a are endlessly connected by a loop-shaped step 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.

[0014] A terminal gear 4, with which the step chain 2 engages, is provided within the housing frame 3 below the upper platform floor plate 13a. When the step chain 2 is driven by this terminal gear 4, the steps 1, 1a connected to the step chain 2 move in a circular motion between the upper platform floor plate 13a and the lower platform floor plate 13b. In addition, the handrail 8 rotates in synchronization with the step chain 2.

[0015] 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 panel 12. A drive step chain belt 7 is mounted between the drive gear 5 and the terminal gear 4. A lower terminal gear 9 is provided in the housing frame 3 below the lower platform floor plate 13b. The step chain 2 is engaged with this lower terminal gear 9.

[0016] 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 (collectively referred to as "step rollers 10" when no distinction is required). 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 and back directions of the page. Within the housing frame 3, there are provided step rails 11a on which the front guide rollers 10a run, and step rails 11b on which the rear guide rollers 10b run. The step rails 11a, 11b are provided in pairs at the top and bottom of the housing frame 3.

[0017] When the steps 1, 1a move from the lower terminal gear 9 to the terminal gear 4, the front guide rollers 10a and rear guide rollers 10b run on the upper step rails 11a, 11b. When the steps 1, 1a reach the terminal gear 4, they move along the terminal gear 4. When the steps 1, 1a move along the terminal gear 4 from the upper side of the terminal gear 4 to the lower side of the terminal gear 4, the position of the steps 1, 1a is reversed.

[0018] The front guide rollers 10a and rear guide rollers 10b of the reversed step 1, 1a transfer onto the lower step rails 11a, 11b. When the step 1, 1a moves from the terminal gear 4 to the lower terminal gear 9, the front guide rollers 10a and rear guide rollers 10b run on the lower step rails 11a, 11b. When the step 1, 1a reaches the lower terminal gear 9, it moves along the lower terminal gear 9 and reverses its position again. The front guide rollers 10a and rear guide rollers 10b of the reversed step 1, 1a transfer onto the upper step rails 11a, 11b.

[0019] FIG. 2 is a perspective view showing the schematic configuration of a diagnostic step 1a used in the diagnostic system 1000. 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.

[0020] 3 is a functional block diagram showing the functional configuration of diagnostic system 1000. Diagnostic system 1000 includes diagnostic step 1a provided on escalator 100, control device 12a corresponding to control panel 12, position estimation device 51 and data collection device 30 associated therewith, monitoring center 50 that performs diagnostic processing remotely, and abnormality diagnosis device 52 and communication device 53 associated therewith. Data collection device 30 transmits and receives data to and from monitoring center 50 via network 40.

[0021] The control unit 26, the control device 12a, the position estimation device 51, and the abnormality diagnosis device 52 are formed by a computer executing a program, and there is no visible distinction in shape. The affiliation and arrangement of each part are free, and the arrangement in Figure 3 is merely an example. For example, part or all of the position estimation device 51 may be included in the monitoring center 50. Also, part or all of the abnormality diagnosis device 52 may be included in the control unit 26 of the diagnosis step 1a (not shown). In that case, the diagnostic data may be stored in a removable storage medium or the like and exchanged as needed.

[0022] As described above, the diagnostic step 1a is provided with a sensor terminal 24. The sensor terminal 24 is provided with a sensor unit 25, a control unit 26, a wireless communication unit 27, a timing database 28, and a trigger generation unit 29. The sensor unit 25 is provided with a magnetic sensor 251, a sound sensor 252, an acceleration sensor 253, and a camera 254 as diagnostic sensors. The control panel 12 provided in the housing frame 3 of the escalator 100 is provided with a data collection device 30 having a data storage unit 301 and a communication unit 302, and a position estimation device 51. The timing database 28 and the trigger generation unit 29 are formed by a computer or a memory associated therewith that constitutes any of the control unit 26, the control panel a12, the position estimation device 51, or the abnormality diagnosis device, and therefore can be freely arranged.

[0023] The magnetic detection data from the magnetic sensor 251, the sound detection data from the sound sensor 252, and the acceleration detection data from the acceleration sensor 253 are transmitted to the data collection device 30 by the wireless communication unit 27. A low-power, low-cost short-range wireless communication is used for the wireless communication unit 27. A battery 23 is used as the power source for the sensor terminal 24, and is replaced if necessary, for example, during periodic inspection. Note that the sound sensor 252 and the acceleration sensor 253 can sometimes be combined into one sensor.

[0024] 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.

[0025] 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.

[0026] 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 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.

[0027] The magnetic map generation unit 511 generates a magnetic map M based on the time-series magnetic detection data after noise reduction processing. Specifically, for one revolution of the time-series magnetic detection data, the magnetic map M is generated by associating the detection value at each time with the position on the escalator 100. The magnetic map generation process will be described later. The magnetic map generation process is performed as an initial operation when the diagnostic step 1a is installed on the escalator 100. The generated magnetic map M is stored in the memory unit 514.

[0028] 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 M. 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.

[0029] Monitoring center 50 includes an abnormality diagnosis device 52 and a communication device 53. Abnormality diagnosis device 52 performs abnormality diagnosis of escalator 100 based on a magnetic map and detection data from a diagnostic sensor. Abnormality diagnosis device 52 includes an abnormality estimation unit 521, a noise reduction unit 522, a storage unit 523, and an alarm unit 524. Abnormality estimation unit 521 performs abnormality estimation processing, which will be described later, based on sound detection data after self-location estimation processing has been performed by self-location estimation unit 512.

[0030] Noise reduction unit 522 performs noise reduction processing on the time-series detection data group used for abnormality diagnosis. Notification unit 524 performs a notification operation when abnormality estimation unit 521 determines that an abnormality has occurred. Upon receiving the abnormality notification from the notification operation, an operator performs inspection work on escalator 100. Memory unit 523 stores criteria data used for abnormality diagnosis, the time-series detection data group acquired from data collection device 30, and the like.

[0031] (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 is 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.

[0032] Time-series magnetic detection data D1 is data from the first cycle, time-series magnetic detection data D2 is data from the second cycle, and time-series magnetic detection data D3 is data from the third cycle. Time-series magnetic detection data D2 is shown shifted by Δ along the vertical axis relative to time-series magnetic detection data D1. Similarly, time-series magnetic detection data D3 is shown shifted by Δ along the vertical axis relative to time-series magnetic detection data D2. T is the time required for one cycle of circular movement, i.e., the period.

[0033] 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 the noises n1 to n3 occur, for example, by averaging the detection values ​​at the same timing in the time-series magnetic detection data D1 to D3 over multiple revolutions.

[0034] When averaging is performed using time-series magnetic detection data for 10 revolutions, if noise occurs only in one revolution, the detected value of the noise portion will be 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 process. Note that noise reduction process for time-series sound detection data and time-series acceleration detection data is also performed in the same way as for the time-series magnetic detection data described above.

[0035] (Magnetic map generation process) The magnetic map generation 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 the time-series magnetic detection data that has been subjected to noise reduction processing by the noise reduction unit 513. There are various methods for processing the association, but three types of processing methods will be explained below. The magnetic map M is a position detection means that utilizes the fact that the steel step rails 11a, 11b have a unique magnetization pattern (D in FIG. 6, Da to Dp in FIG. 7) that does not change easily.

[0036] 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.

[0037] FIG. 5 is a diagram illustrating an example of positioning of the diagnostic step 1a. Positioning of the diagnostic step 1a to a predetermined position at the start of its movement is performed, for example, as follows: An operator manually operates the control panel 12 to adjust the position of the diagnostic step 1a while visually observing the diagnostic step 1a. By making such adjustments, the diagnostic step 1a is positioned at a position extended from the lower platform 13b of the boarding / exiting door (hereinafter, this position will be referred to as reference position A), as shown in FIG.

[0038] FIG. 6 is a diagram showing an example of time-series magnetic detection data after noise reduction processing. The acquired multiple pieces of time-series magnetic detection data are transmitted to the monitoring center 50, and the noise reduction unit 513 of the position estimation device 51 performs the noise reduction processing described above. As a result, time-series magnetic detection data D after noise reduction processing as shown in FIG. 6 is obtained. 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.

[0039] The time-series magnetic detection data D represents the magnetism around the diagnostic step 1a while it makes one circuit, i.e., the magnetization state of the parts of the escalator 100 (mainly the steel step rails 11a and 11b). The diagnostic step 1a, which moves in a circular motion, reaches 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 positions of the diagnostic step 1a are B, C, E, and F in FIG. 5, respectively. Then, at t=ta, the diagnostic step 1a returns to reference position A.

[0040] 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).

[0041] The second method will now 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.

[0042] 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.

[0043] 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.

[0044] 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.

[0045] 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.

[0046] 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 rotation 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, suppose that when diagnostic step 1a is at position C in Figure 5, the motor sound of drive motor 6 is detected as the maximum detection value.

[0047] In this case, the position C in Figure 6 where the 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 movement speed of the diagnostic step 1a and the elapsed time from the 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).

[0048] A third method will now be described. In the third method, the position of the diagnostic step 1a when the magnetization of a magnetized part among the parts provided on the escalator 100 is detected is set as the reference position. For example, when the diagnostic step 1a is at position C in FIG. 5, the magnetism of the drive motor 6 is detected as the maximum detection value. In that case, position C in FIG. 6 where the 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 movement speed of the diagnostic step 1a and the elapsed time from the reference position C.

[0049] The magnetic map M (magnetic detection value, position) for one revolution 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 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 as in the second method. This allows for cost reduction.

[0050] (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.

[0051] 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.

[0052] 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.

[0053] 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.

[0054] In step S90, a data transmission command is sent to the data collecting device 30 to collect a plurality of time-series detection data groups stored in the data storage unit 301. The time-series detection data groups include a plurality of types of time-series detection data groups corresponding to the sensors provided in the sensor unit 25, and data acquisition position information generated by the position estimation device 51.

[0055] 3, the sensor unit 25 is provided with a magnetic sensor 251, a sound sensor 252, an acceleration sensor 253, and a camera 254, and therefore the time-series detection data group includes 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.

[0056] In step S92, based on the time-series sound detection data and the time-series acceleration detection data after noise reduction processing, it is determined whether or not an abnormality has occurred by the abnormality estimation unit 521. If it is determined in step S92 that an abnormality has occurred (YES), the process proceeds to step S95, and if it is determined that an abnormality has not occurred (NO), the process proceeds to step S93.

[0057] In step S93, the abnormality estimation unit 521 determines whether or not there is an abnormality sign based on the time-series sound detection data and the time-series acceleration detection data after noise reduction processing. If it is determined in step S93 that there is an abnormality sign (YES), the process proceeds to step S95, and if it is determined that there is no abnormality sign (NO), the process proceeds to step S97.

[0058] 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 the abnormality sign determination, the time-series sound detection data and the time-series acceleration detection data after noise reduction processing are compared with determination reference data.

[0059] The judgment reference data is stored in the memory unit 523. During the initial operation of generating the magnetic map M (magnetic detection values, position) after installing the diagnostic step 1a, a group of time-series detection data is acquired from the data collecting device 30. The memory unit 523 stores the time-series detection data after noise reduction processing of the group of time-series detection data as judgment reference data. The time-series detection data includes time-series magnetic detection data, time-series sound detection data, and time-series acceleration detection data.

[0060] 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.

[0061] 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.

[0062] 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.

[0063] Returning to the flowchart in Figure 9, in step S95, an abnormality precursor or a part where an abnormality has occurred is estimated based on the data collection position information generated by position estimation device 511 and transmitted during data collection. As shown in Figure 5, near position C on escalator 100, step chain 2, terminal gear 4, drive gear 5, drive motor 6, etc. are provided. In addition to estimating the abnormal position, 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.

[0064] If an abnormality occurs in the step chain 2, terminal gear 4, drive gear 5, or drive motor 6, each part 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 memory unit 523 also stores in advance failure identification data that lists the frequencies of abnormal sounds and abnormal vibrations for each part and each type of failure. The abnormality estimation unit 521 estimates the part 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.

[0065] In step S96, the occurrence of an abnormality or an abnormality sign is notified by the 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 has occurred, 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 S97 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.

[0066] As described above, in the diagnostic system 1000 of this embodiment, when a diagnostic step 1a provided with a diagnostic sensor including the 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 the escalator 100.

[0067] Therefore, the detection position of the diagnostic sensor detection value acquired during operation of escalator 100 can be obtained by comparing the magnetic detection value detected at the same time as the detection value with the magnetic map M (magnetic detection value, position). In other words, even in a situation where the operating speed changes, the detection position of the diagnostic sensor detection value can be estimated with high accuracy, making it possible to perform continuous diagnosis.

[0068] 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 100 can be easily performed at monitoring center 50.

[0069] 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.

[0070] 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.

[0071] In the above-described embodiment, a self-position estimation process is performed to associate sound detection data with a position on escalator 100 based on the detection data of 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 acceleration sensor 253.

[0072] The reversal timing occurs when the diagnostic step 1a moves to a specific position on the escalator 100. Therefore, by utilizing this reversal timing, it is possible to improve the accuracy of self-position estimation and perform an abnormality diagnosis 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 be used in combination.

[0073] The configuration of the diagnostic system 1000 is not limited to the configuration shown in the block diagram of Fig. 3. 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 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 the information processing device 54.

[0074] The collected time-series detection data group can also be confirmed and analyzed by the information processing device 54. Furthermore, as in the case of the fifth modification, during regular inspection, an operator can read out the diagnosis results stored in the storage unit 523 using a personal computer or the like, thereby confirming the diagnosis results and dealing with any abnormalities on the spot. Also, a notification unit 524 may be provided.

[0075] Figure 11 is a diagram that defines the distances X and Y from the terminal gears 4 and 9 to the ends Q and U of the step rail 11b. The positions of the ends Q and U of the step rail 11b shown in Figure 11 are determined according to the shape of the building. Meanwhile, it is inevitable that the step chain 2 will stretch over time in operation, and it is necessary to maintain an optimal state of slack and tension to accommodate this.

[0076] For this reason, the axis of the lower terminal gear 9 is adjusted so as to move little by little away from the upper terminal gear 4. The limit of this adjustment is controlled by the distance X from the terminal gear 9 to the end Q of the step rail 11b, and once this limit is exceeded, the step chain 2 is deemed to have reached the end of its life and is replaced. Note that in order to maintain an optimal state of slack and tension in the step chain 2, it is also possible to adjust the distance Y between the upper terminal gear 4 and the upper end U of the step rail 11b, but this is not common practice as it would require a complex mechanism in relation to the drive motor 6.

[0077] These distances X and Y from the terminal gears 4 and 9 to both ends Q and U of the step rail 11b are managed according to the design or specification values, although the inspection frequency may differ. The magnetic map M is also defined based on these ends Q and U of the step rail 11b. In other words, the position of each inspection target is a predetermined position in the longitudinal direction of the step rail 11b, which is specified based on the design or specification values ​​and stored as the timing database 28.

[0078] 3, 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 electric circuits, electronic circuits, logic circuits, and integrated circuits incorporating them, as well as microcomputers, processors, and similar computer arithmetic devices, ROMs, RAMs, flash memories, hard disks, SSDs, memory cards, optical disks, and similar storage devices, buses, networks, and similar communication devices, and peripheral devices. Furthermore, the distinction, placement, and affiliation of the functional units are free, and names are also free as long as the meaning is the same.

[0079] (Features of the present invention) For a newly installed, state-of-the-art escalator, it would be easy to implement a continuous remote monitoring system using the Internet of Things (IoT). However, for an escalator 100 installed several decades ago, the compact, detachable diagnostic step 1a of the diagnostic system 1000 is suitable. In this case, to prolong the life of the battery 23 installed in the diagnostic step 1a, monitoring is performed at the minimum necessary intermittent frequency, recording the minimum necessary data, and power-saving operation is performed, allowing for progress observation over several months and collecting data collectively. This eliminates the need for point-by-point communication.

[0080] This diagnostic system 1000 is equipped with a position sensor (not shown), a camera 254, a microphone 252, an acceleration sensor 253, a wireless communication unit 27, and a battery 23 on one of the steps of the passenger conveyor 100, and detects the magnetic pattern unique to the step rails 11a and 11b with the magnetic sensor 251, identifies the step position, and determines the shutter opportunity when the step approaches the area that needs to be monitored. Note that the detection characteristics of the magnetic sensor 251 and the acceleration sensor 253 change depending on factors such as the type of variable speed operation compatible with human sensors and the number of people on board, so a correction means prepared in advance is also used in combination to improve accuracy.

[0081] In the present diagnostic system 1000, it is basically advantageous to use the magnetic sensor 251 for position detection, but the diagnostic sensor may also serve as a position sensor. In this case, the magnetic sensor 251 and acceleration sensor 253 require less drive current than the camera 254 and microphone 252, and are therefore positioned as constantly operating devices. In contrast, the camera 254 and microphone 252, which require a larger drive current, are operated in pinpoint mode to save power. Locations requiring monitoring are associated with the magnetic map M to determine shutter opportunities.

[0082] Furthermore, even in environments where it is difficult to take advantage of wireless equipment such as beacons or Wi-Fi® due to individual fire shutters or upper and lower partitions that block radio waves as required by the Building Standards Act, the diagnostic system 1000 is suitable because it can detect position using the magnetic map M without using radio waves. The diagnostic system 1000 is equipped with a magnetic sensor 251 compatible with the magnetic map M in addition to the diagnostic sensor as the diagnostic step 1a, and creates in advance a magnetic map M of the step movement direction when the escalator 100 is in operation. The parts of the escalator 100 to be diagnosed are stored in association with the position of the unique change pattern in the magnetic map M (hereinafter also referred to as "position information").

[0083] During diagnostic operation, the diagnostic system 1000 keeps only the magnetic sensor 251, which requires a small amount of data and consumes little power, in operation and in standby mode. As the escalator operates, the diagnostic steps obtain magnetic changes corresponding to their movement, mainly from the step rails 11a and 11b. These magnetic changes are compared with a magnetic map M created in advance, and the position of the magnetic sensor 251 in the longitudinal direction of the step rails 11a and 11b is continuously estimated.

[0084] The diagnostic system 1000 normally operates the magnetic sensor 251 and compares the output of the magnetic sensor 251 with the magnetic map M. When a region to be diagnosed is detected based on the comparison result, it is determined that it is a photo opportunity for the camera 254. Since the advanced sensors that are activated only at photo opportunities require a large amount of drive power compared to the standby power-saving mode, the diagnostic system 1000 immediately returns to the standby power-saving mode after collecting data for the minimum necessary short time.

[0085] In this way, the diagnostic system 1000 operates an advanced diagnostic sensor that generates a large amount of data and consumes a lot of power only at a position suited to the area to be diagnosed based on the position information detected by the magnetic sensor 251, and stores the measurement data acquired by the sensor. As a result, the battery capacity mounted on the diagnostic step 1a can be minimized, making it smaller and lighter.

[0086] The diagnostic system 1000 not only reduces the weight of the battery 23, but also has the synergistic effect of simplifying the hardware and software (hereinafter referred to as "hardware and software") of the diagnostic steps as a whole. In this way, the weight of the diagnostic step 1a and the amount of data transmitted can be reduced, which reduces the workload of the worker using the diagnostic system 1000, which is the main component of the diagnostic system 1000, as well as the time required for communication and various other burdens.

[0087] (Differences between the present invention and the prior art) Conventionally, as a device of this type, there is an existing technology called a diagnostic step, in which a sensor is mounted in the internal space of the step and circulates inside the escalator to measure the inside of the escalator in order to improve the efficiency of the work of identifying abnormalities and their causes during escalator inspections.Currently, a technology has been disclosed in a patent publication in which a regular step is replaced with a diagnostic step only during regular inspections, and this technology is used to improve the efficiency of regular inspections.

[0088] Another example uses the detection output of the acceleration sensor 253 to identify the time when the step passes through two end points where it reverses direction, and estimates the current position of the diagnostic step based on the elapsed time traveled at a constant speed from there. The diagnostic step circulates within the escalator, and it is necessary to detect the parts and locations to be diagnosed and acquire and save the measurement data of the diagnostic sensor at a position suitable for diagnosis. In this case, any change in the moving speed will cause an error in the estimated position.

[0089] As described above, in the prior art, acceleration sensor 253 is used to obtain the timing at which the diagnostic step is pulled into the back side of escalator 100 and reverses, and the step position is estimated from the time elapsed since the reversal. This method does not have enough resolution to identify a position suitable for diagnosis, so it was necessary to operate the diagnostic sensor continuously while circulating inside escalator 100 and store the measurement data.

[0090] In other words, the results will differ significantly depending on whether or not accuracy can be achieved in identifying the location of the diagnostic target area along the entire length of escalator 100. The best time to take a photo with camera 254 is when it is closest to the diagnostic target, and the same is true for microphone 252. Therefore, when diagnosing escalator 100, accurate position information of diagnostic step 1a is required.

[0091] Therefore, conventional diagnostic steps required the processing power of hardware and software to store the continuously input measurement data. In this case, costs and weight including batteries increased, and the communication time and communication costs for retrieving data from the diagnostic step and transmitting it to the remote monitoring center also increased, resulting in a lack of convenience. Therefore, the diagnostic system 1000 has made it possible to measure data using a simpler diagnostic step 1a.

[0092] The diagnostic system 1000 uses the detection output of the entire time-series waveform of the magnetic sensor 251, compares it with the magnetic map M, and performs correlation calculations to estimate the current position of the diagnostic step 1a with high accuracy. As a result, the diagnostic system 1000 is advantageous for diagnosing individual parts or components that require more accurate position information when diagnosing the escalator 100. The diagnostic system 1000 not only collects high-output and more accurate information, but also aims to save energy and simplify the system by activating advanced sensors in response to photo opportunities based on accurate position information from the diagnostic step 1a, and minimizing their full operation time.

[0093] (basic type) This diagnostic system 1000 uses a diagnostic step 1a equipped with a magnetic sensor 251 and at least one diagnostic sensor in the internal space of the step of escalator 100. The diagnostic sensors for fault diagnosis include a sound sensor, an acceleration sensor 253, and a camera 254. This diagnostic step 1a has a database that associates the positions of the parts to be diagnosed with a magnetic map M inside escalator 100, and compares the measurement data of magnetic sensor 251 with the database to determine the timing to operate the diagnostic sensor. This diagnostic system 1000 diagnoses escalator 100 based on data from the diagnostic sensor that is operated and measured at the determined timing.

[0094] (Modifications and application examples) 1) Operate using an installed system rather than bringing in equipment. In this diagnostic system 1000, after a worker installs diagnostic steps on escalator 100, a scheduling function is used to perform measurements using diagnostic sensors at specific times (for example, 8:00 every day). Measurement data is accumulated, and diagnosis and trend analysis are performed when the worker next visits, allowing for more accurate diagnosis.

[0095] 2) In addition to the magnetic database and the location of the part to be diagnosed, on-site data is reflected in determining the measurement timing. In this diagnostic system 1000, after a worker installs diagnostic step 1a by operating the installation type described above, magnetic sensor 251 and diagnostic sensor are continuously operated while escalator 100 is circulated. From the measurement data of the diagnostic sensor, priority monitoring locations are determined based on high vibration, high noise, etc., and the locations to be measured using the schedule function are registered in a database associated with magnetic map M.

[0096] 3) Estimate the self-position in conjunction with the output of other sensors. The diagnostic system 1000 performs self-location estimation by combining a magnetic sensor 251 and a conventional acceleration sensor 253. That is, the diagnostic system 1000 performs a rough location estimation using the acceleration sensor 253, and then determines the precise location by comparing the time-series waveform of the magnetic sensor 251 with the magnetic database near the estimated location. As a result, the diagnostic system 1000 can estimate the location even if the data waveform of the magnetic sensor 251 to be compared is short.

[0097] 4) Changes in the operating speed of the escalator 100 are also taken into consideration in the time series waveforms of the magnetic database and the magnetic sensor 251. When comparing the magnetic database with magnetic sensor 251, diagnostic system 1000 calculates a correlation function if the waveform is shifted in the time direction and determines the position where the waveforms are closest. In this case, diagnostic system 1000 may also prepare waveforms in the magnetic database that have been stretched or shortened by a constant factor (0.5 to 2 times, for example) in the time direction, and by comparing with these waveforms, it may be possible to apply diagnostic system 1000 to escalator 100, which changes its operating speed, such as a low-speed, low-power mode when there are no passengers, or a considerate mode for the elderly and children. Conversely, diagnostic processing may be performed at an appropriately high speed.

[0098] 5) Diagnostic sensor data and diagnostic results display location In addition to being able to check the results on the diagnostic step 1a itself or by workers on-site using a computer or smartphone, this diagnostic system 1000 can also send the results to a remote monitoring center, where support staff at the remote monitoring center, the building management company, or the owner can check the results.

[0099] 6) Locations where magnetic map generation, position estimation, and diagnostic functions are installed In addition to being installed in the diagnostic step 1a main body, the diagnostic system 1000 can have some functions distributed to a personal computer carried by an operator and to a remote monitoring center 50. The above-mentioned modified examples and application examples 1) to 6) can be realized by combining them as appropriate.

[0100] The diagnostic system 1000 can be summarized as follows. [1] This diagnostic system 1000 is provided with a diagnostic step formed by mounting at least a magnetic sensor 251, diagnostic sensors 252-254, a battery 23, and a control unit 26 in the internal space of any one of the steps 1 that are endlessly connected to and move in a passenger conveyor 100 that transports passengers, and diagnoses the passenger conveyor 100. This diagnostic system 1000 further includes a timing database 28, storage devices 301, 514, 523 that store data and programs including the timing database 28, a magnetic map generation unit 511, a position estimation unit 512, and a trigger generation unit 29.

[0101] The diagnostic step 1a is a step in which any one of the plurality of steps 1 is replaced with the diagnostic step 1a to form an inspection jig for the passenger conveyor 100, and enables continuous diagnosis of the passenger conveyor 100 even during normal operation. The diagnostic step 1a is configured by mounting at least a magnetic sensor 251, a diagnostic sensor, and a battery 23 in the internal space of the step 1.

[0102] The storage devices 301, 514, and 523 store the outputs of the timing database 28 and the diagnostic sensors 252 to 254, and also store programs that are read and operated by a computer. The control unit 26 is disposed in the diagnostic step 1a, and controls the diagnostic operation by computer processing, and operates the magnetic sensor 251 and the diagnostic sensors 252 to 254 based on the timing database 28.

[0103] The computer (control unit 26, control device 12a, position estimation device 51, abnormality diagnosis device 52) is preferably a one-chip microcomputer that can operate for long periods of time even with very little power, but other forms are acceptable as long as they are small and energy-saving. Note that, since each of the above-mentioned functional units is formed by a computer, they do not have a visible shape, and there is no need to clearly distinguish between them, so they can be freely arranged.

[0104] The magnetic map generation unit 511 uses the detection values ​​of the magnetic sensor 251 stored in the storage device to form a magnetic map M which is a correlation with the position of the diagnostic step 1a within the passenger conveyor 100. The position estimation unit calculates the position of the diagnostic step 1a from the output of the magnetic sensor 251 and the magnetic map M. The trigger generation unit 29 generates triggers to operate the diagnostic sensors 252 to 254 based on the position estimation unit and the timing database 28 stored in the storage device.

[0105] The trigger determines the timing of data acquisition by the diagnostic sensors 252-254 based on the output of the position estimation unit. The diagnostic system 1000 limits the operation of the diagnostic sensors outside of the determined data acquisition timings to save power. The battery 23 is preferably a lithium-ion battery or the like, which has a large power capacity relative to its shape and weight, and is charged or replaced at each maintenance cycle to maintain or restore power supply capacity. Therefore, even if the diagnostic system 1000 uses a step-type diagnostic tool that makes battery replacement difficult during normal operation, the reduced power consumption allows continuous monitoring without battery replacement for long periods of time, similar to the cycle of regular inspections.

[0106] [2] In the above [1], it is preferable that the diagnostic sensors 252 to 254 include at least one microphone 252. The microphone 252 can detect abnormal sounds and use them to determine a malfunction. By analyzing the frequency of the detected abnormal sounds, the diagnostic system 1000 can identify the type and degree of the abnormality by using sounds with specific frequencies that indicate the type and degree of the abnormality.

[0107] [3] In the above [1], it is preferable to have at least one camera 254 as a diagnostic sensor. The camera 254 can capture images of the abnormal location and provide the captured image for fault diagnosis. For example, a 60 fps camera captures 60 frames per second compared to a 30 fps camera. This allows for clearer detection of abnormalities in the diagnostic target area in moving images, but consumes more power. The diagnostic system 1000 operates the camera 254 for only the minimum necessary time to capture images, thereby reducing power consumption even with a high-performance camera 254.

[0108] [4] In the above [1], the timing of acquiring data from the diagnostic sensors is generated based on the output of the magnetic sensor 251, the magnetic map M, and the output of the diagnostic sensors. Information indicating a predetermined position on the step rail 11b is written in advance in the magnetic map M. Information indicating the predetermined position (for example, position C in Figures 5 and 8) is read by the magnetic sensor 251 as the output of the diagnostic sensors 252 to 254.

[0109] The read output of the magnetic sensor 251 generates the data acquisition timing of the diagnostic sensor, which indicates a predetermined position on the step rail 11b written in the magnetic map M. The data acquisition timing is information indicating the location that needs to be inspected so that data can be acquired efficiently. In this way, the diagnostic system 1000 acquires data by operating the diagnostic sensor for only the minimum necessary time based on the generated data acquisition timing, so that there is no waste in information processing, including power consumption, and it is efficient.

[0110] [5] In the above [1], information indicating a predetermined position on the step rail 11b is written in advance in the magnetic map M, and the predetermined position is preferably defined as a distance from longitudinal ends Q and U of the step rail 11b shown in FIG. 11 as a reference, and this definition is preferably stored as the timing database 28. The positions of ends Q and U of the step rail 11b are defined in accordance with the shape of the building, and are suitable as the most stable reference within the escalator 100, excluding natural disasters such as earthquakes. Therefore, this diagnostic system 1000 can obtain more accurate diagnostic results.

[0111] [6] In the above [5], it is advisable to set specified distances X and Y from the reference ends Q and U to the terminal gears 4 and 9. In particular, the distance X from the lower terminal gear 4 to the end Q is adjusted so as to remove slack in the step chain 2, which inevitably stretches depending on the operating time of the escalator 100 and the magnitude of the load, and move the axis of the lower terminal gear 4 away from it in a direction that maintains tension, and the adjustment limit is clearly indicated by the distance X, so that the lifespan of the step chain 2 can be determined reliably and easily.

[0112] [7] In [5] or [6] above, the above definition may be based on design information or specification information. Even if the distances X and Y from the reference ends Q and U to the terminal gears 4 and 9 change gradually due to adjustments or other factors, the current dimensions can be measured by the diagnostic step 1a of the diagnostic system 1000. However, the specified distances X and Y before adjustment can be obtained from the design information or specification information, stored in the timing database 28 as a magnetic map M, and read out as needed to compare with the measured values. If the comparison value is equal to or greater than a predetermined value, an abnormality can be easily determined.

[0113] [8] In any of the above [1] to [6], it is preferable to further include an analysis device (e.g., the control unit 26, the control device 12a, or the abnormality diagnosis device 52 in FIG. 3), a communication device (e.g., 27, 40, 53, 302 in FIG. 3), and a remote monitoring unit (e.g., the monitoring center 50 in FIG. 3). In this case, the analysis device analyzes the diagnostic data stored in the storage devices 514 and 523. Data is transmitted and received by the wireless communication unit 27 of the diagnostic step 1a, the communication unit 302 of the control device 12a, the network 40, and the communication device 53 disposed in the monitoring center 50. The outputs of the diagnostic sensors 252 to 254 and the outputs of the analysis devices 26 and 12 are transmitted to the remote monitoring unit 50 by these communication devices 27, 40, 53, 302. Analysis may also be performed by the remote monitoring unit (monitoring center) 50.

[0114] The remote monitoring unit 50 displays the outputs of the diagnostic sensors 252-254 and the outputs of the analyzers 26, 12, 52, so that a service center or the like other than the on-site location can make thorough preparations based on the diagnostic results of the diagnostic system 1000 before an operator travels to the site, thereby improving the efficiency of maintenance work. Also, since there is no need to store unnecessary data in the diagnostic step 1a, a simple memory (not shown) in the control unit 26 is sufficient.

[0115] [9] In the above [8], the communication device 27, 302 is preferably capable of wireless communication. If wireless communication is possible, diagnostic data stored in the storage device (memory of the control unit 26) of the diagnostic step 1a can be transmitted contactlessly to a tablet terminal or laptop computer carried by a worker waiting nearby. Furthermore, the laptop computer can be used as an operation console to transmit operation command signals contactlessly to the control unit 26 of the diagnostic step 1a. Furthermore, the remote communication capability of the wireless communication can be Wi-Fi® or any other technology that allows short-range communication slightly longer than the overall length of the passenger conveyor 100 to be diagnosed. [Explanation of symbols]

[0116] 1...Step, 1a...Diagnostic step, 2...Step chain, 3...Housing frame, 4...Terminal gear, 6...Drive motor, 9...Lower terminal gear, 10...Step roller, 10a...Front guide roller, 10b...Rear guide roller, 11a, 11b...Step rail, 12...Control panel, 12a...Control device, 23...Battery, 24...Sensor terminal, 25...Sensor unit, 26...Control unit, 27...Wireless communication unit, 28...Timing database, 29...Trigger generation unit, 30...Data collection device, 40...Network, 50...Monitoring center, 51...Position estimation device, 52...Abnormality diagnosis device, 53...Communication device, 54...information processing device, 100...passenger conveyor (escalator), 251...magnetic sensor, 252...sound sensor (microphone), 253...acceleration sensor, 254...camera, 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...passenger conveyor diagnostic system (this diagnostic system), Q, U...end of step rail (11b), X, Y...distance (from terminal gears 4, 9 to ends Q, U of step rail 11b)

Claims

1. A passenger conveyor diagnostic system including a diagnostic step formed by mounting at least a magnetic sensor, a diagnostic sensor, a battery, and a control unit in an internal space of any of steps that are endlessly connected and move on a passenger conveyor that transports passengers, a storage device that stores a timing database that defines the operation of the magnetic sensor and the diagnostic sensor, and an output of the diagnostic sensor; a magnetic map generating unit that generates a magnetic map that is a correlation between the detected values ​​of the magnetic sensors stored in the storage device and the positions of the diagnostic steps in the passenger conveyor; a position estimation unit that calculates a diagnostic step position based on the output of the magnetic sensor and the magnetic map; a trigger generating unit that generates a trigger for operating the diagnostic sensor based on an output of the position estimating unit and the timing database stored in the storage device; and the control unit operates the magnetic sensor and the diagnostic sensor based on the definition of the timing database; determining a timing for acquiring data from the diagnostic sensor based on the generated trigger; restricting the operation of the diagnostic sensor at times other than the data acquisition timing; Passenger conveyor diagnostic system.

2. The diagnostic sensor includes at least one microphone.

10. The passenger conveyor diagnostic system of claim 1.

3. The diagnostic sensor includes at least one camera.

10. The passenger conveyor diagnostic system of claim 1.

4. the data acquisition timing of the diagnostic sensor is generated based on the output of the magnetic sensor, the magnetic map, and the output of the diagnostic sensor; 10. The passenger conveyor diagnostic system of claim 1.

5. The magnetic map has information indicating a predetermined position on the step rail written therein in advance, the predetermined position is defined by a distance from a reference point to an end of the step rail in the longitudinal direction, storing the definition in the timing database; 10. The passenger conveyor diagnostic system of claim 1.

6. The distance dimension from the end portion to the terminal gear as the reference is set forth in the above-mentioned regulation.

6. The passenger conveyor diagnostic system of claim 5.

7. The provision is based on design information or specification information, 7. The passenger conveyor diagnostic system according to claim 5 or 6.

8. an analysis device that analyzes the diagnostic data stored in the storage device; a communication device disposed in the diagnostic step; a remote monitoring unit that receives and transmits data via the communication device and displays the output of the diagnostic sensor and the output of the analysis device; Furthermore, transmitting an output of the diagnostic sensor and an output of the analysis device to the remote monitoring unit via the communication device; The passenger conveyor diagnostic system according to any one of claims 1 to 6.

9. The communication device is a wireless communication device.

9. The passenger conveyor diagnostic system of claim 8.

10. A passenger conveyor diagnostic method for diagnosing a passenger conveyor in which endlessly connected steps move to transport passengers, comprising: a diagnostic step is formed by installing at least a magnetic sensor, a diagnostic sensor, a control unit for controlling a diagnostic operation, a storage device, and a battery in the internal space of the step; The control unit activating the magnetic sensor and the diagnostic sensor based on the specifications of the timing database stored in the storage device; storing the output of the diagnostic sensor in the memory device; a magnetic map generation unit that uses the detected values ​​of the magnetic sensors stored in the storage device to generate a magnetic map that is a correlation with the position of the diagnostic step in the passenger conveyor; a position estimation unit that calculates a diagnostic step position from the output of the magnetic sensor and the magnetic map; causing a trigger generation unit to generate a trigger for operating the diagnostic sensor based on the position estimation unit and the timing database stored in the storage device; determining a timing for acquiring data from the diagnostic sensor based on the generated trigger; restricting the operation of the diagnostic sensor at times other than the data acquisition timing; Passenger conveyor diagnostic method.

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