NewProductsBearing Diagnostic Edge Application for Industrial IoTPlatforms

Yudai NAKANO*
Takashi HASEBA*
In an effort to realize a smart and efficient factory, IoT-based
condition monitoring systems are attracting attention in recentyears. Rolling bearings are used to support the rotation ofNormal Attention Caution Warning
production equipment. We need to monitor bearing conditions toprevent unplanned downtime due to bearing damage.
NTN bearing diagnostic edge application
NTN has developed a bearing diagnostic edge application forindustrial IoT platforms to monitor bearing conditions using vibration data. In this article, we introduce thefeatures and application examples of the bearing diagnostic edge application.

1. Introduction
There is a rising demand for predictive maintenancefor production equipment, against the backdrop of
manpower reduction and improved productivity atproduction equipment. Manufacturers are preferringto transition to condition-based maintenance from theconventional time-based maintenance implemented
at production sites1).
At the production site, it is necessary to minimize
downtime that occurs due to equipment stoppages
so that productivity can be improved. Therefore, wemust apply monitoring technology that will allow
us to quantitatively understand conditions such as
equipment deterioration and failure, and quickly
detect abnormalities that have occurred so thatmaintenance can be performed.
A method to achieve this is monitoring the conditionof production equipment through the use of anindustrial IoT (Internet of Things) platform.
NTN has developed an edge application forindustrial IoT platforms that can diagnose production
equipment bearings through the use of vibration
data. This paper introduces the features of thisedge application and examples of its application at
production sites.

2. Condition monitoring at the production site
2.1 Industrial IoT platforms
Industrial IoT platforms refer to IoT systeminfrastructure in the industrial sector. In themanufacturing industry, various equipment at theproduction site is connected via a network, and theproduction process is monitored and controlled. This
allows improvements to be made to productivity ateach step of production.

Fig. 1 shows a schematic drawing of an industrial
IoT platform. This schematic drawing shows how theindustrial IoT platform, edge application and IT system
are linked at the production site.
IT system

Edge Application
Data analysis/AI
Industrial IoT Platforms
Data collection, data management and external system linkup

Production site
Machine tool, PLC, sensors, etc.

Fig. 1 Schematic drawing of industrial IoT platform
An industrial IoT platform connects to equipment
at the production site and collects data relating toequipment operation. An edge application receives
the data collected from the industrial IoT platform
and analyzes it. The analysis results processed here
are then sent to the production site equipment andhost IT system. The IT system takes on the role ofcomprehensively managing the various information
for the production site, and systems such as theEnterprise Resource Planning (ERP) system or
Manufacturing Execution System (MES) can be used
for this task.
Using this industrial IoT platform optimizes
management tasks and provides visualization of theproduction site in terms of monitoring the operation* Robotics & Sensing Engineering Dept., Industrial Business Headquarters

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Bearing Diagnostic Edge Application for Industrial IoT Platforms
and conditions of production equipment.
2.2 Monitoring the condition of bearings
Bearings are precision machine parts where highaccuracy and quality are critical for proper function
and long life. They are installed for use on several
types of equipment to support the rotation ofmachinery.
If a bearing is damaged, the equipment must bestopped to perform inspection and repairs, which
lowers productivity. Therefore, it is important tomonitor bearing conditions to perform maintenancework at an appropriate time.
A method of diagnosing the bearing using vibration
data is often used to monitor bearing conditions2).
Table 1 shows the types of bearing diagnosis using
this vibration method. Two types are available todiagnose bearings: simple diagnosis and precision
diagnosis.
Table 1 Types of bearing diagnosis
TypeDiagnosis method

Simplediagnosis• Absolute value determination(Evaluated in line with standards/standard values)• Same type comparison(Evaluated by comparing with the same
type of equipment/machines under thesame conditions)• Trend management(Determine abnormalities by constantly
observing trends)

Precision
diagnosis• Estimates damage positions on bearing
and extent of damage with frequency
analysis (FFT, etc.)*Requires various bearing information

Simple diagnosis monitors changes in thecondition over time and the degree of deviation fromhealthy conditions. Methods include absolute value
determination in line with predetermined criteria
and standards, compariative analysis that involves
comparing the same type of equipment and machines,
and trend management in which constant observation
is implemented. Simple diagnosis is used to properly
understand the bearing condition and create
maintenance plans for equipment based on diagnosis
results, which can prevent such things as unscheduled
equipment stoppages due to bearing damage.
Meanwhile, precision diagnosis is performed whenfurther analysis is required based on the results ofsimple diagnosis. Fast Fourier transform (FFT) andsimilar can be used to analyze the vibration spectrum
to estimate where the bearing is damaged andthe extent of the damage. However, to analyze therelationship between the spectrum and the positionof damage, various bearing factors such as the rolling
element raceway diameter, rolling element diameter,
number of rolling elements, and the contact angle, as54

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well as information about the shaft rotational speed
are required.

3. Bearing diagnostic edge application
As a bearing manufacturer, NTN has developed acondition monitoring system (CMS) for wind turbines
using our knowledge about bearing damage alongwith sensing technology and diagnosis technology
developed over many years and released this forsale as “WindDoctorTM”3). Currently, we are providing
a condition monitoring service using this systemon over 250 wind turbines throughout Japan. This
technology was used to develop a bearing diagnostic
edge application using real-time processing functions
from Edgecross4), which is an industrial IoT platform(hereafter, bearing diagnostic application).
3.1 Features
The main features of the bearing diagnostic
application are shown below.
(1) Realtime diagnosis
The application includes NTN proprietary diagnosis
algorithms to automatically collect vibration data foranalysis and diagnosis purposes. Up to 16 locations
are diagnosed within at least 3 seconds using a single
bearing diagnostic application license. This enables
users to know any changes in the bearing condition
that may appear in a short amount of time and can
detect abnormalities early on.
(2) Automatic threshold generation
Thresholds are automatically generated to identify
the bearing conditions based on learned data. Thiseliminates work to configure thresholds that require
an experienced operator.
(3) Provides diagnosis not limited to certain bearing
numbers
It is not necessary to configure such things as
bearing factors and rotational speed. Therefore, theapplication can be used even if you do not know thenumber of the bearing installed on the equipment or
the rotational speed.
(4) Rating scale for bearing health condition
Diagnosis results display 4 ratings (Normal,Attention, Caution, and Warning) in text and color
on the display screen of the bearing diagnostic
application. Therefore, it is possible to easily know thebearing condition without the operator performing
detailed analysis.

Attention

Fig. 2 Device configuration for bearing diagnostic applicationPC

Edgecross

PLC

Attention

Fig. 3 Coolant pump diagnosis process

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Bearing Diagnostic Edge Application for Industrial IoT Platforms
3.2 Usage configuration
The devices required to use the bearing diagnostic
application are a PC installed with Windows operating
system, a vibration sensor, and a data logger.
Edgecross basic software and the bearing diagnostic
application can be used after installing them onto thePC (Fig. 2).
The bearing diagnostic application can also run
in standalone mode for convenience of use at theproduction site.

4. Example of application on coolant
pumpsThis section introduces an example of using
the bearing diagnostic application to monitor theconditions of a coolant pump at the production site.
4.1 Challenges of inspection work
If a coolant pump that supplies coolant toequipment fails, it will lead to production linestoppages. To mitigate this type of situation, operators
either regularly perform inspection work on theequipment or perform such work depending on thesituation. However, this inspection work relies on theexperience of the operator so there are times when an
operator may fail to notice a problem with the coolant
pump. To prevent this type of situation, it is necessary
to evaluate the bearing conditions automatically andquantitatively (whether damage has occurred and its
extent, etc.) based on the operational status of thecoolant pump expressed in a numerical format.
4.2 Introducing the bearing diagnostic application
Fig. 3 shows the device configuration andmeasurement/diagnosis procedure for this example.
The bearing diagnostic application is organized suchthat it links to the coolant pump control PLC and thedisplay via Edgecross. Operation information such as
the rotational speed, pressure and temperature aredisplayed on the coolant pump control panel display
in addition to diagnosis results from the bearing
diagnostic application.
In this example, operators receive information about
the coolant pump operational status at the same time
the bearing conditions are checked, which reduces
the amount of inspection work the operator must
do. Furthermore, the bearing diagnostic application
constantly monitors the bearing conditions, enabling
any bearing abnormalities or development of damage
to be quantitatively evaluated. If any signs of damage
are discovered on the bearing, control is switched
to lower the load on the coolant pump based on
the diagnosis results, which is expected to delay theprogress of damage on the bearing.

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5. Proof of concept build support service
When introducing the system to the production site,
proof of concept (PoC) is performed to validate theeffectiveness of introducing the system in advance.
Sensors and equipment used for the PoC step are
prepared by the user. However, when introducing thebearing diagnostic application, users were unable toprepare equipment such as vibration sensors and dataloggers, and it was sometimes difficult to implement
PoC. Due to this fact, NTN provides a “PoC build
support service”5) in collaboration with EdgecrossConsortium4), in which the user can borrow a setof the devices that need to be prepared. They areborrowed for a fixed period at no cost to the user.
Fig. 4 shows a flowchart up to the point of starting
PoC operation for the PoC build support service.
This service includes an interview concerning what
equipment needs to be diagnosed and any issues
to address, followed by a decision on the PoC
implementation details and NTN work support details.
For users who are concerned about how to set up thedevices, NTN also helps set up peripheral devices andconfigure the bearing diagnostic application.
This service has been favorably received by users
who have used it, describing how they were able toquickly start PoC and were able to understand how
it operates. Even after the PoC build support service
ended, many users continued to use the bearing
diagnostic application.

Apply for the proof of concept build
support service

Interview held about requirements
and issues (Web)Loan of PoC Kit, assistance to set
up at production site

Start PoC operation
Fig. 4 PoC build support service flowchart

6. Summary
This paper introduced the bearing diagnostic edgeapplication used for industrial IoT platforms. It also
showed the introduction of the bearing diagnostic
edge application at a production site using an
example of application on cooling pumps. The bearing
diagnostic edge application is not limited to theexample shown in this paper and is used by a varietyof users. We will continue to develop products withenhanced functionality in the future, provide service
solutions that meet the needs of our users, andcontribute towards improving productivity in eachindustry.
References1) METI, The State of Government Initiatives for
Promoting Smart Security, (December 2020)
https://www.meti.go.jp/policy/safety_security/industrial_safety/smart_industrial_safety_
symposium/images/meti_goto.pdf
2) ISO 20816-1:2016, Mechanical vibration- Measurement and evaluation of machine
vibration - Part 1.
3) Makoto Miyazaki, Wataru Hatakeyama,
Application of Condition Monitoring System forWind Turbines, NTN TECHNICAL REVIEW, No.86,(2018) 40-44.
4) Edgecross Consortium, Edgecross Consortium
Official Homepage.
https://www.edgecross.org/ja/
5) Edgecross Consortium, PoC Build Support
Service, Edgecross Consortium OfficialHomepage.
https://www.edgecross.org/ja/dounyu_kentou/poc.html

Photo of authors

Yudai NAKANOTakashi HASEBA

Robotics & Sensing
Engineering Dept.,
Industrial Business
Headquarters

Robotics & Sensing
Engineering Dept.,
Industrial Business
Headquarters

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