Bearing diagnosis device and bearing diagnosis method

Abstract

The present invention provides a bearing diagnosis device and a bearing diagnosis method. The bearing diagnosis device has a magnetic sensor and a vibration sensor, and diagnoses the state of a bearing that supports a rotating shaft of a drive unit that circulates and operates a device machine. The bearing diagnosis device includes: a bearing rotation period calculation unit that calculates a rotation period of the bearing using a magnetic signal detected by the magnetic sensor; a natural frequency calculation unit that calculates a natural frequency of the bearing; a diagnosis unit that diagnoses the state of the bearing based on the natural frequency of the bearing; a device vibration period calculation unit that calculates a device vibration period, which is a period of vibration repeatedly generated from device machines other than the bearing accompanying the circulating operation; a vibration level determination unit that determines a vibration level of a vibration signal detected by the vibration sensor other than a vibration signal corresponding to the device vibration period; and a scheduling unit that changes a time period during which the magnetic sensor performs detection when the vibration level exceeds a given vibration level.

Description

Technical Field

[0001] The present invention relates to a bearing diagnosis device and a bearing diagnosis method. Background Art

[0002] Techniques for diagnosing the state of a bearing that supports a rotating shaft of a drive unit that drives equipment machinery are known. For example, Patent Document 1 discloses a bearing information analysis device "comprising: a magnetic sensor that detects magnetism generated from a structural member of the bearing; a vibration sensor that detects vibration generated in the bearing; a signal collection unit that collects the magnetic signal of the magnetic sensor and the vibration signal of the vibration sensor detected at the same timing from the bearing; a signal processing unit that calculates a theoretically natural frequency of the bearing, that is, a theoretical natural frequency, based on a specification value of the bearing, and calculates a natural frequency based on a detection result of the bearing, that is, a detected natural frequency, from the signals collected by the signal collection unit; and a display unit that displays information calculated by the signal processing unit" (Claim 1).

[0003] Prior Art Documents

[0004] Patent Documents

[0005] Patent Document 1: JP-A-2020-143934

[0006] In the technique described in Patent Document 1, it is assumed that the analysis device is temporarily installed in the bearing during maintenance of equipment machinery or the like. Therefore, it is not possible to grasp the trend related to the continuous behavior of the bearing over a certain number of days. Assuming that the analysis device of Patent Document 1 is continuously installed in the bearing, when the equipment machinery is operating normally, the influence of noise generated outside the bearing becomes large, and it is difficult to accurately analyze the state of the bearing. Summary of the Invention

[0007] An object of the present invention is to provide a bearing diagnosis device and a bearing diagnosis method that can continuously and accurately diagnose the state of a bearing.

[0008] In order to solve the above problems, the bearing diagnosis device of the present invention has a magnetic sensor and a vibration sensor, and diagnoses the state of the bearing of the rotating shaft of the drive unit that circulates the equipment machine. The bearing diagnosis device includes: a bearing rotation period calculation unit that calculates the rotation period of the bearing using the magnetic signal detected by the magnetic sensor; a natural frequency calculation unit that calculates the natural frequency of the bearing using the magnetic signal detected by the magnetic sensor; a diagnosis unit that diagnoses the state of the bearing based on the natural frequency of the bearing; an equipment vibration period calculation unit that calculates the period of vibration, i.e., the equipment vibration period, that is repeatedly generated from the equipment machine other than the bearing along with the cyclic operation based on the rotation period of the bearing; a vibration level determination unit that determines whether the vibration signal other than the vibration signal corresponding to the equipment vibration period among the vibration signals detected by the vibration sensor is below a given vibration level; and a scheduling unit that changes the time period during which the magnetic sensor performs detection when the given vibration level is exceeded.

[0009] Effects of the Invention

[0010] According to the present invention, a bearing diagnosis device and a bearing diagnosis method that can continuously and accurately diagnose the state of a bearing can be provided. Other problems, structures, and effects than those described above will be clarified by the following description of the mode for carrying out the invention. Description of the Drawings

[0011] Figure 1 It is a schematic structural diagram of an escalator according to an embodiment of the present invention.

[0012] Figure 2 It is a cross-sectional view showing the structure of a rolling bearing.

[0013] Figure 3 It is a functional block diagram showing the structure of the bearing diagnosis device according to Embodiment 1.

[0014] Figure 4 It is a flowchart for explaining the bearing diagnosis method.

[0015] Figure 5 It is an example of a peak graph obtained by performing a fast Fourier transform on the magnetic signal detected by the magnetic sensor when the state of the bearing is normal, with the horizontal axis being the frequency and the vertical axis being the signal intensity.

[0016] Figure 6 It is a flowchart for explaining the method of diagnosing the trend of the state of the bearing.

[0017] Figure 7 It is a functional block diagram showing the structure of the passenger conveyor diagnosis system according to Embodiment 2.

[0018] Description of Reference Numerals

[0019] 1...Escalator, 2...Frame, 3...Control panel, 4...Rail part, 5...Step, 6...Handrail, 7...Drive mechanism, 8...Transfer chain, 9...Step chain, 10...Handrail drive device, 11...Drive sprocket, 12...Driven sprocket, 13...Guide rail, 14...Conveyor belt member, 15...Handrail drive chain, 16...Transfer pulley, 17...Outer ring, 18...Rolling element, 19...Cage, 20...Inner ring, 30...Bearing diagnosis device, 31...Sensor module, 311...Magnetic sensor, 312...Vibration sensor, 313...Amplifier filter section, 314...ADC, 32...Control module, 321...Natural frequency calculation section, 322...Bearing rotation period calculation section, 323...Diagnosis section, 324...Equipment vibration period calculation section, 325...Vibration level determination section, 326...Scheduling section, 327...Storage section, 328...Output section, 41...Passenger conveyor, 42...Drive section, 43...Communication section, 329...Communication section, 51...Monitoring server Detailed implementation manner

[0020] The embodiments of the present invention will be described below with reference to the accompanying drawings. The examples are illustrations for explaining the present invention, and for the sake of clarity of explanation, omissions and simplifications are appropriately made. The present invention can also be implemented in various other forms. Unless otherwise specifically limited, each component can be either single or multiple.

[0021] When there are multiple components having the same or equivalent functions, sometimes different subscripts are attached to the same reference numeral for explanation. In addition, when it is not necessary to distinguish these multiple components, sometimes the subscripts are omitted for explanation.

[0022] In an embodiment, there may be a case where the processing performed by executing a program is described. Here, while a computer executes a program using a processor (e.g., CPU, GPU) and uses storage resources (e.g., memory), interface devices (e.g., communication ports), etc., the processing determined by the program is performed. Therefore, the entity performing the processing by executing the program can be set as the processor. Similarly, the entity performing the processing by executing the program can also be a controller, device, system, computer, or node having a processor. The entity performing the processing by executing the program only needs to be an arithmetic unit and can include a dedicated circuit for performing specific processing. Here, the so-called dedicated circuit is, for example, an FPGA (Field Programmable Gate Array), an ASIC (Application Specific Integrated Circuit), a CPLD (Complex Programmable Logic Device), etc.

[0023] The program can be installed on the computer from a program source. The program source can be, for example, a program distribution server or a computer-readable storage medium. In the case where the program source is a program distribution server, the program distribution server includes a processor and a storage resource for storing the program to be distributed, and the processor of the program distribution server can distribute the program to be distributed to other computers. In addition, in an embodiment, two or more programs can be implemented as one program, or one program can be implemented as two or more programs.

[0024] An embodiment of the present invention diagnoses the trend of the bearing state by calculating the natural frequency of the structural members of the working equipment and grasping its time-series change. In this embodiment, an escalator is taken as an example of the equipment for illustration. In addition to the escalator, it can also be other passenger conveyors such as moving walkways, and as long as it is an equipment that performs circular operation through a drive unit, it can also be other equipment.

[0025] First, an escalator provided with the bearing diagnosis device according to this embodiment will be described. Figure 1 It is a schematic structural diagram of the escalator 1 of this embodiment. As Figure 1 shown, the escalator 1 of this embodiment includes a frame 2 provided in a building structure (not shown), a control panel 3, a railing part 4, steps 5, guide rails 13, handrails 6, a drive mechanism 7, a transmission chain 8, a step chain 9, a handrail drive device 10, a drive sprocket 11, and a driven sprocket 12.

[0026] On the upper floor side within the frame body 2, a control panel 3, a drive mechanism 7, and a drive sprocket 11 are arranged, and on the lower floor side, a driven sprocket 12 is arranged.

[0027] The drive mechanism 7 is composed of an electric motor and a speed reducer. Electric power is supplied to the electric motor from the control panel 3, and the operation of the electric motor is controlled by the control panel 3. A conveyor belt member 14 is wound around the electric motor and the speed reducer, and the rotational force of the electric motor is transmitted to the speed reducer via the conveyor belt member 14.

[0028] Furthermore, a transmission chain 8 is wound around the speed reducer and the drive sprocket 11, and the driving force of the drive mechanism 7 is transmitted to the drive sprocket 11 via the transmission chain 8, causing the drive sprocket 11 to rotate.

[0029] A pair of step chains 9 are wound around the drive sprocket 11 and the driven sprocket 12. By the rotation of the drive sprocket 11, the driven sprocket 12 and the step chains 9 rotate.

[0030] In addition, a handrail drive chain 15 is wound around the drive sprocket 11. The handrail drive chain 15 is wound around a plurality of transmission pulleys 16 and is wound around the handrail drive device 10.

[0031] A pair of guide rails 13 are arranged in the width direction of the frame body 2, and a plurality of steps 5 are movably supported by the pair of guide rails 13. In addition, the plurality of steps 5 are connected endlessly via a pair of step chains 9, are guided by the guide rails 13 to pass through the going side and the returning side, and perform circular movement between the boarding and alighting openings.

[0032] The railing portion 4 is supported at the upper part of the frame body 2 and is arranged on both sides in the width direction of the frame body 2. An endless handrail 6 is installed on the railing portion 4. The handrail 6 is movably supported on the railing portion 4 and performs circular movement synchronously in the same direction as the plurality of steps 5 by the handrail drive device 10. Thus, in the escalator 1, passengers who board the steps 5 and hold the handrail 6 can be safely transported.

[0033] In addition, both ends of the rotating shafts of the drive sprocket 11 and the driven sprocket 12, which are the drive parts, are supported by bearings (not shown). The bearings are fixed by bearing housings (not shown).

[0034] Here, the structure of the bearings will be described. Figure 2 It is a cross-sectional view showing the structure of a rolling bearing. As Figure 2As shown in the figure, the bearing includes: an outer ring 17 fixed to a bearing housing; spherical rolling elements 18; a cage 19 that rotatably holds the rolling elements 18; and an inner ring 20 disposed inside the cage 19 and in point contact with the rolling elements 18. A rotating shaft of a driving sprocket 11 or a driven sprocket 12 is inserted inside the inner ring 20, and the rotating shaft and the inner ring 20 are fixed. Therefore, when the rotating shaft rotates, the inner ring 20, the rolling elements 18, and the cage 19, which are structural members of the bearing, also rotate.

[0035] The following describes a bearing diagnostic device for diagnosing the state of a bearing based on each embodiment.

[0036]

Embodiment 1

[0037] Embodiment 1 assumes that: after an operator transports the bearing diagnostic device 30 to an escalator to be diagnosed as needed and sets it up, the diagnosis of the bearing diagnostic device 30 is continued for a certain period, and the diagnosis result is confirmed on-site during the next maintenance. Figure 3 It is a functional block diagram showing the structure of the bearing diagnostic device according to Embodiment 1. As Figure 3 shown, the bearing diagnostic device 30 according to Embodiment 1 includes a sensor module 31 and a control module 32, and the sensor module 31 and the control module 32 are communicably connected via a cable.

[0038] The sensor module 31 is mounted on the bearing housing to which the bearing is fixed, and includes a magnetic sensor 311, a vibration sensor 312, an amplifier filter unit 313, and an ADC (Analog-to-Digital Converter). After the output signal of the magnetic sensor 311 is processed by the amplifier filter unit 313, it is digitized by the ADC 314, and the converted magnetic signal is output to the control module 32 via a cable. On the other hand, after the output signal of the vibration sensor 312 is processed by the amplifier filter unit 313, it is digitized by the ADC 314, and the converted vibration signal is output to the control module 32 via a cable. In addition, the vibration sensor 312 may be any sensor that can detect a vibration signal caused by the rotation of the bearing or a vibration signal mixed in from other power systems, and includes, for example, a piezoelectric element, an acceleration sensor, a sound microphone, etc.

[0039] The control module 32 includes a natural frequency calculation unit 321, a bearing rotation period calculation unit 322, a diagnosis unit 323, a device vibration period calculation unit 324, a vibration level determination unit 325, a scheduling unit 326, a storage unit 327, and an output unit 328. The natural frequency calculation unit 321 calculates the natural frequency of the bearing (such as the inner ring 20, etc.) using the magnetic signal detected by the magnetic sensor 311. The bearing rotation period calculation unit 322 calculates the rotation period of the bearing using the magnetic signal detected by the magnetic sensor 311. The diagnosis unit 323 diagnoses the state of the bearing based on the natural frequency of the bearing. The device vibration period calculation unit 324 calculates the period of normal vibration, i.e., the device vibration period, that is repeatedly generated from parts of the escalator 1 other than the bearing along with the cyclic operation of the steps 5, etc., based on the natural frequency of the inner ring 20. The vibration level determination unit 325 determines whether the vibration signals detected by the vibration sensor 312 other than the vibration signals corresponding to the device vibration period are below a given vibration level. When exceeding the given vibration level, the scheduling unit 326 changes the time period during which the sensor module 31 performs detection. The output unit 328 outputs the diagnosis result of the diagnosis unit 323, etc. The storage unit 327 stores, in addition to the diagnosis result of the diagnosis unit 323, the model information of the escalator 1 to be diagnosed, information related to the specification values of the bearing associated with the model information, etc. In addition, the natural frequency calculation unit 321 calculates the theoretically natural frequency, i.e., the theoretical natural frequency, of each structural component (inner ring 20, rolling element 18, and cage 19) of the bearing based on the specification values stored in the storage unit 327, and stores it in the storage unit 327 as preprocessing for bearing diagnosis.

[0040] Next, a diagnosis method using the bearing diagnosis device 30 according to the present embodiment will be described. Figure 4 It is a flowchart for explaining the bearing diagnosis method.

[0041] When it becomes a pre-specified time period, the magnetic sensor 311 and the vibration sensor 312 of the sensor module 31 detect magnetic signals and vibration signals, and output them to the control module 32 (step S101).

[0042] Next, the natural frequency calculation unit 321 performs an operation process of high-speed Fourier transform on the magnetic signal detected by the magnetic sensor 311 to obtain the frequency characteristics of the magnetic signal (step S102). Furthermore, the natural frequency calculation unit 321 determines the natural frequency of the bearing by analyzing the frequency characteristics, specifically, determines the natural frequencies of the inner ring 20, the rolling element 18, and the cage 19 (step S103). In addition, in step S103, the bearing rotation period calculation unit 322 calculates the rotation period of the bearing (inner ring 20) based on the analysis result of the frequency characteristics.

[0043] Figure 5This is an example of a peak graph obtained by performing a high-speed Fourier transform on the magnetic signal detected by the magnetic sensor 311 when the bearing is in a normal state, with the horizontal axis representing frequency and the vertical axis representing signal intensity. As Figure 5 shown, it can be seen that the inner ring 20, rolling elements 18, and cage 19 of the bearing during normal operation rotate at their respective determined natural frequencies (0.4 Hz and 0.8 Hz for the inner ring, 1.7 Hz for the rolling elements, and 0.17 Hz for the cage). Additionally, in the Figure 5 example, there are two peaks corresponding to the inner ring, with the fundamental wave at 0.4 Hz and the second harmonic component at 0.8 Hz.

[0044] Next, the diagnostic unit 323 compares the detected natural frequency in step S103 with the theoretical natural frequency calculated during preprocessing (step S104).

[0045] If the natural frequencies of the two do not match, for example, if the difference between the detected natural frequency and the theoretical natural frequency is equal to or greater than a given threshold, the diagnostic unit 323 diagnoses that the bearing is in an abnormal state and registers the detected magnetic signal, detected natural frequency, and detection time together as diagnostic target data in the storage unit 327 (step S105). The diagnostic target data registered in the storage unit 327 is used in trend diagnosis. Additionally, multiple thresholds can be set. For example, if it is equal to or greater than a high threshold, it can be diagnosed as a major failure requiring urgent response; if it is equal to or greater than a low threshold but not equal to or greater than the high threshold, it can be diagnosed as the initial stage of a failure and continuous monitoring is sufficient. Furthermore, it is also possible to determine which part of the bearing has an abnormality based on which of the inner ring 20, rolling elements 18, and cage 19 has a natural frequency equal to or greater than the threshold.

[0046] Here, in addition to detecting the vibration caused by the bearing, the vibration sensor 312 also detects periodic vibrations repeatedly generated from parts of the escalator 1 other than the bearing during the cyclic operation of the escalator 1, as well as vibrations from the external environment including the boarding and alighting of passengers. In particular, since vibrations from the external environment can become noise in the diagnosis of the bearing state by the diagnostic unit 323, it is desirable to use the sensor data when the vibration level of the external environment is low for diagnosis. Therefore, in this embodiment, whenever the vibration level of the external environment is determined, the vibration generated periodically by the escalator 1 itself is first removed (separated) from the vibration signal detected by the vibration sensor 312.

[0047] First, a method for the device vibration period calculation unit 324 to calculate the period of vibration (device vibration period) generated by the cyclic operation of the escalator 1 (device machine) will be described. The rotating shaft of the sprocket of the escalator 1 rotates integrally with the inner ring 20 of the bearing. Therefore, the device vibration period calculation unit 324 uniquely obtains the operating speed of the escalator 1 based on the rotation period of the inner ring 20 determined in step S103. If the operating speed of the escalator 1 is determined, the device vibration period calculation unit 324 calculates the timing (interval) of the vibration periodically generated by the escalator 1 (mainly the vibration when the steps collide with the guide rail 13 during flipping on the outgoing side and the return side) (step S106).

[0048] Next, the vibration level determination unit 325 removes the vibration signal corresponding to the device vibration period from the vibration signals detected by the vibration sensor 312 (step S107).

[0049] After that, the vibration level determination unit 325 uses the data of the vibration signal obtained in step S107 to determine whether it is below a given vibration level (step S108). For example, when there are few passengers and the load on the escalator 1 is small, it is below the given vibration level.

[0050] When it is below the given vibration level, the detected magnetic signal, the detected natural frequency, and the detection time are registered as diagnostic target data in the storage unit 327 together (step S109). The diagnostic target data registered in the storage unit 327 is used in trend diagnosis.

[0051] On the other hand, when it exceeds the given vibration level, the scheduling unit 326 changes the time period for the sensor module to perform detection after the next day (step S110). As a method for changing the time period, for example, it is considered to stagger by 1 hour compared to the current time period, etc.

[0052] Figure 6 It is a flowchart showing a method for diagnosing the trend of the bearing state. As Figure 6 shown, in the trend diagnosis in this embodiment, first, the diagnosis unit 323 extracts the diagnostic target data for the same time period from the storage unit 327 (step 201). Next, the diagnosis unit 323 calculates the difference between the detected natural frequency and the theoretical natural frequency (step S202). Here, the diagnosis unit 323 determines whether the days when this difference is above a given threshold value occur continuously (step S203). When it does not occur continuously, the diagnosis result is displayed through the output unit (step S204). On the other hand, when it occurs continuously, after performing an abnormality diagnosis (step S205), the diagnosis result is displayed through the output unit 328 (step S204).

[0053] Thus, according to this embodiment, since the detection of the sensor module 31 is performed only during a time period when the influence of external noise below a given vibration level is small, continuous and high-quality data that lasts for a certain number of days can be obtained even in a restricted power supply environment. In addition, by grasping the time-series change of the detection natural frequency of the bearing, for example, long-term trend diagnosis can be performed according to the situation where the bearing temporarily deviates from the normal range (the difference between the detection natural frequency and the theoretical natural frequency is less than a given threshold) and then returns to the normal range again. Furthermore, in this embodiment, even if the operation schedule of the escalator 1 cannot be obtained, the time period with a large influence of external noise can be automatically avoided, and high-precision diagnosis using data during a time period with few passengers can be achieved.

[0054]

Embodiment 2

[0055] Embodiment 2 assumes that after a bearing diagnosis device (mainly the sensor module 31) is installed in a passenger conveyor (such as an escalator) to be diagnosed, the result of continuous diagnosis for a certain period is confirmed using a monitoring server 51 communicatively connected to the bearing diagnosis device at a monitoring center. Figure 7 It is a functional block diagram showing the structure of the passenger conveyor diagnosis system according to Embodiment 2. As Figure 7 shown, the passenger conveyor diagnosis system according to Embodiment 2 includes: a passenger conveyor 41; and a monitoring server 51 used by a monitoring center or the like as a base for remotely monitoring the state of the passenger conveyor. In addition, the monitoring server 51 can be a monitoring server used by a management room of a building or other facilities where the passenger conveyor 41 is installed.

[0056] As described above, the passenger conveyor 41 includes: steps 5 that circulate between boarding and alighting openings; an endless step chain 9 connected to the steps 5; a drive unit that drives the step chain 9; a bearing that supports the rotating shaft of the drive unit; a sensor module 31; and a control module 32. The sensor module 31 is composed of a magnetic sensor 311, a vibration sensor 312, etc. in the same manner as in Embodiment 1, but the control module 32 is different from that in Embodiment 1 and is composed of a communication unit 43 for connecting to the monitoring server 51 via a communication line.

[0057] In addition to having a communication unit 329 for connecting to the passenger conveyor 41 via a communication line, the monitoring server 51 also has a natural frequency calculation unit 321, a bearing rotation period calculation unit 322, a diagnosis unit 323, an equipment vibration period calculation unit 324, a vibration level determination unit 325, a scheduling unit 326, an output unit 328, and a storage unit 327 in the same manner as the control module 32 in Embodiment 1.

[0058] According to this embodiment, signals from the magnetic sensor 311 and the vibration sensor 312 provided in the passenger conveyor 41 are sent to the monitoring server 51, and the diagnosis of the bearing and the confirmation of its result can be confirmed on the monitoring server 51. Therefore, it is easy to establish an implementation plan for maintenance including the timing of the next inspection, and it is possible to prevent unnecessary trips to the installation site of the passenger conveyor 41. In addition, a part of the functions of the monitoring server 51 can be mounted on the control module 32.

[0059]

Embodiment 3

[0060] Embodiment 3 assumes that a bearing diagnosis device is pre-mounted on the passenger conveyor to be diagnosed. In the passenger conveyor, the bearing diagnosis device 30 according to Embodiment 1 can be permanently installed, or only the sensor module 31 can be mainly permanently installed as in Embodiment 2. In the former case, the operator can confirm the diagnosis result at the installation site of the passenger conveyor using the output unit 328 of the control module 32 of the bearing diagnosis device 30. In the latter case, the monitor can confirm the diagnosis result at the monitoring center using the monitoring server 51 communicatively connected to the communication unit 329 of the control module 32. In either case, there is an advantage that there is no need to perform operations for installing the sensor module 31 or removing the sensor module 31 on the passenger conveyor.

[0061] The present invention is not limited to the foregoing embodiments, and various modifications can be made. The foregoing embodiments are illustrated for easy understanding of the present invention, but are not necessarily limited to having all the structures described. In addition, a part of the structure of one embodiment can be replaced with the structure of another embodiment, and in addition, the structure of another embodiment can be added to the structure of one embodiment. In addition, addition, deletion, or replacement of other structures can be made to a part of the structure of each embodiment.

Claims

1. A bearing diagnosis device, having a magnetic sensor and a vibration sensor, and diagnosing the state of a bearing of a rotating shaft of a drive unit that causes a device machine to operate in a cycle, wherein the bearing diagnosis device is characterized by comprising: A bearing rotation period calculation unit that calculates a rotation period of the bearing using a magnetic signal detected by the magnetic sensor; A natural frequency calculation unit that calculates a natural frequency of the bearing using a magnetic signal detected by the magnetic sensor; A diagnosis unit that diagnoses the state of the bearing based on the natural frequency of the bearing; A device vibration period calculation unit that calculates a period of vibration that is repeatedly generated from the device machine other than the bearing along with the cycle operation, that is, a device vibration period, based on the rotation period of the bearing; A vibration level determination unit that determines whether a vibration signal other than a vibration signal corresponding to the device vibration period among vibration signals detected by the vibration sensor is below a given vibration level; and A scheduling unit that, when exceeding the given vibration level, determines that a period during which the magnetic sensor performs detection is a period with a high vibration level in the external environment, and changes the period during which the magnetic sensor performs detection.

2. The bearing diagnosis device according to claim 1, wherein The bearing has: an inner ring, rolling elements, a retainer that holds the rolling elements, and an outer ring, The natural frequency calculation unit calculates a theoretically natural frequency, that is, a theoretical natural frequency, of at least one of the inner ring, the rolling elements, and the retainer using a specification value of the bearing, The diagnosis unit diagnoses the state of the bearing by comparing a detected natural frequency calculated using a magnetic signal detected by the magnetic sensor with the theoretical natural frequency.

3. The bearing diagnosis device according to claim 2, wherein The magnetic sensor and the vibration sensor detect the magnetic signal and the vibration signal for a certain number of days in the same period, The diagnosis unit determines whether days in which a difference between the detected natural frequency and the theoretical natural frequency becomes equal to or greater than a given threshold are consecutive.

4. A passenger conveyor, characterized in that, Comprising: Steps that move in a cycle between boarding and alighting openings; An endless chain that is connected to the steps; A drive unit that drives the chain; and The bearing diagnosis device according to claim 1, which diagnoses the state of a bearing that supports a rotating shaft of the drive unit.

5. A passenger conveyor diagnosis system, comprising: A passenger conveyor; and A monitoring server that is connected to the passenger conveyor via a communication line and diagnoses the passenger conveyor, The passenger conveyor diagnosis system is characterized in that The passenger conveyor has: Steps that move in a cycle between boarding and alighting openings; An endless chain that is connected to the steps; A drive unit that drives the chain; A bearing that supports a rotating shaft of the drive unit; A magnetic sensor; and A vibration sensor, The monitoring server has: A bearing rotation period calculation unit that calculates a rotation period of the bearing using a magnetic signal detected by the magnetic sensor; A natural frequency calculation unit that calculates a natural frequency of the bearing using a magnetic signal detected by the magnetic sensor; A diagnosis unit that diagnoses the state of the bearing based on the natural frequency of the bearing; A device vibration period calculation unit that calculates the period of vibration, i.e., the device vibration period, that is repeatedly generated from the passenger conveyor other than the bearing along with the cyclic movement of the steps based on the rotation period of the bearing; A vibration level determination unit that determines whether a vibration signal other than the vibration signal corresponding to the device vibration period among the vibration signals detected by the vibration sensor is below a given vibration level; and A scheduling unit that, when the given vibration level is exceeded, determines that the period during which the magnetic sensor performs detection is a period with a high vibration level in the external environment and changes the period during which the magnetic sensor performs detection.

6. A bearing diagnosis method for diagnosing the state of a bearing that supports a rotating shaft of a drive unit that causes a device machine to operate cyclically, The bearing diagnosis method is characterized by comprising the following steps: A step of calculating the rotation period and natural frequency of the bearing using the magnetic signal detected by the magnetic sensor; A diagnosis step of diagnosing the state of the bearing based on the natural frequency of the bearing; A step of calculating the period of vibration, i.e., the device vibration period, that is repeatedly generated from the device machine other than the bearing along with the cyclic operation based on the rotation period of the bearing; A step of determining whether a vibration signal other than the vibration signal corresponding to the device vibration period among the vibration signals detected by the vibration sensor is below a given vibration level; and A step of, when the given vibration level is exceeded, determining that the period during which the magnetic sensor performs detection is a period with a high vibration level in the external environment and changing the period during which the magnetic sensor performs detection.

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