Q1, 2013 Persistence Pays Off

Q1, 2013

Persistence Pays Off By Joe Keckeisen Senior Engineer Data Analyst, Predictive Diagnostic Team Johnson Controls Shortly before hurricane Katrina hit the gulf shores of Louisiana and Mississippi in 2005,

residents fled to neighboring cities to seek shelter until the vicious storm blew over. One of

those cities being Houston, Texas saw over 300,000 people searching for a safe place to reside

until safety had been restored in their hometown. One of the larger manufacturers in the

Houston community has several large facilities, one of which had been vacant as a result of an

acquisition of a smaller company. The manufacturer saw the demand for facilities to feed and

house the hurricane victims and offered this facility to FEMA.

Since this facility had been vacant for some time, the HVAC system had only been run

occasionally as a routine maintenance task. Knowing the facility would have a large load as

occupants filled the area, a facility technician at the building had turned on one of the

centrifugal chillers. After several hours of continuous runtime, he noticed the machine as being

excessively noisy from its normal operation. Johnson Controls (JCI) local Houston branch has an

existing contract for several of the manufacturer’s occupied facilities, so they called upon the

branch to look into the problem.

A local Houston branch service technician from Johnson Controls was contacted to perform a

vibration analysis on the chiller. After the measurements were collected, the Predictive

The SKF Analyst Newsletter Q1, 2013 Page 1

Diagnostic Team headquartered in Milwaukee, WI noticed that the data was showing evidence

of a possible electrical related problem.

It was requested to perform some further analysis by collecting motor current signatures. The

POINTS were set up as shown below:


These new signatures had shown that the motor had open or broken rotor bars and should be

repaired to ensure reliability of the cooling system.

The dB difference between the amplitude of the 2x slip sideband to the left of the line frequency

(60Hz) and the amplitude of the line frequency was 35dB.

JCI received the go ahead to make the necessary repairs on the chiller. The motor was sent to

the service company in North Carolina. Once the motor was rebuilt and the chiller was put back

into service another vibration analysis and a motor current signature was collected. To

everyone’s surprise the motor current data did not look much different from before it left to be

rebuilt.


This was taken on the rebuilt motor and the dB difference was 39dB.

As a result of this measurement, the motor rebuild shop was contacted to make them aware of

the problem. The motor rebuild shop brought in a local vibration consultant to verify JCI’s claim

that the rebuilt motor did have broken or cracked rotor bars. Their report contradicted our

reports of having motor problems. Their report indicated problems of refrigerant flow and

possible improper assembly of the chiller. The motor shop also performed their variac test

which measures the current applied to the rotor and then the rotor is rotated to measure any

deviation in current indicating a broken or cracked rotor bar. The results came back within their

tolerance. At this point the motor shop had refused to do further maintenance on the chiller

siding with their vibration consultant and their own variac test.


The Houston branch was at a point where they had to make a decision whether to tear

the chiller down or let it run as is. After a couple of conference calls between the Predictive

Diagnostic Team in Milwaukee, and their local chiller team from the Houston area office, it was

decided to tear the chiller down on JCI’s time. The motor was torn completely down and sent to

a different local motor shop for inspection. Photographs were supplied to the Houston office

which revealed several broken and cracked rotor bars.


These pictures clearly show problems with the motor. Had this motor been left in service, it

would have been a matter of months possibly days before a catastrophic failure would have

occurred and caused some major secondary damage. Once the motor shop was shown the

pictures, they agreed to have the motor rebuilt again. The motor was put back in service and

had yet another vibration analysis and motor current signature performed which was all in

acceptable levels.


Condition monitoring set-up considerations including Acceleration Enveloping and other bearing defect detection methods By Paul Edwards

Bearing analysis has come a long way from the early days of vibration analysis. Many vendors have developed their

own techniques and claim theirs is the best. As there is no independent or common standard such as the International

Standards Organization (ISO) standards for Root Mean Square (RMS) velocity for stating when a bearing is defective it

is down to the individual vendors to provide these limits. The aim of this article is to show that irrespective of what

technique is used bearing defects can be detected. However the article will also show that the level of detection can

vary greatly depending on the type of technique used and will uncover some of the errors that can occur if incorrectly

set up. Most (but not all) of these "special" measurements boil down to one of two techniques:

Sensor resonant technique

Demodulation technique

Because of too much prior art, neither of the two techniques are patented, and are free for any vendor to adopt. Each

vendor adds its own spin (and name) to these techniques. Trying to technically argue that "our technique" is superior to

"their technique" is like trying to argue that "our religion" is better than "their religion" .There are ardent believers and

preachers of both techniques across the industry, and such argument is best avoided.. SKF's view is that all these

measurements work very well in many applications and not at all in some applications especially when it comes to slow

rotational shaft rpm measurements.

Introduction

In these austere times it can be very difficult to justify the expense of setting up and running a condition monitoring

program. An instant return on the investment is not normally possible but expected of those holding the purse strings.

Projected long term savings are often ignored due to short term requirements to reduce costs. Maintenance of critical

assets is carried out according to the maintenance schedule with no account being taken to its running condition.

Planned maintenance can often introduce faults into machinery that was not there before the maintenance was

carried out. A German study from 1972 showed that unnecessary maintenance was the largest cause of gearbox

failure, followed by faults introduced during repairs.

Many long standing condition monitoring programs are also called into question as the data collected is not consistent

and trend graphs show a saw tooth effect which is caused by a process variable and not a change in the machines

vibration characteristics. Common issues found on single speed systems include;

1. Variation in load

2. Change in measurement location

3. Change in transducer


Minimizing the Saw tooth effect

As stated previously the saw tooth effect arises when process changes are made between readings. The 3 discussed

in this article are the most common but there are many other process variables that can affect the data.

Variation in Load

Variation in load can significantly change the vibration signature but is not commonly taken into account when carrying

out routine monitoring. In most modern condition monitoring systems provision is made to allow for process points

(keypad entry) to be set up alongside traditional vibration measurement points. Acceptance criteria (alarm bands) can

then be set around what is and is not an acceptable load variation for condition monitoring data to be collected.

With this set as the first point in the route the data collector will immediately warn the operator if the load is outside the

acceptable variation or whether it acceptable to continue.


Load outside of the acceptable range

Load within the acceptable range

Comparisons between the vibration and load trends can then be made to look for similar patterns indicating that load is

the cause of the increase or decrease.


Change in measurement location

Another common reason for variation in vibration readings is inconsistency in the placement of the vibration transducer.

Even small deviations in placement can result in a change in the level recorded and produce the saw tooth effect in the

trend plots. The pictures below show the results of a simple experiment on a rotor kit. A spectrum was collected from

the kit and shows an overall value of 10.5mm/second with the 1X at 9.81 mm/second. The accelerometer was then

moved 5 mm to the right and the data taken again. The overall vibration now shows as 8.41mm/second, a drop of 2.09

mm/second and the 1 X dropped to 7.75mm/second a change of 2.06mm/second.

Spectrum from a rotor kit

Second Spectrum from a rotor kit

This clearly shows that the vibration levels recorded are very dependant on location. Every effort should be made to

ensure that the transducer is fixed at the same location for repeatability of readings. By far the best solution is to utilize

quick lock connectors fixed to the machine. However this can prove very expensive if your condition monitoring regime

has hundreds of points. In the past, I have used ring binder hole strengtheners to indicate the measurement location.

Change in Transducer

Many condition monitoring systems have a number of instruments which are interchanged on a monthly basis so the

same instrument and standard sensor – normally an accelerometer, may not be used for the readings in subsequent

months. Modern condition monitoring programs allow the user to preset the sensors sensitivity in the point set up and

in most cases a nominal sensitivity of 100mV/g is used by default.


However accelerometer manufacturers provide sensors that have

the sensitivity + / - a certain percentage of the nominal value so

could vary between 5 and 10% of that stated in the setup.

In practice this can affect the values recorded on your data collector. A simple trial was set up using a PCB®394C06

hand held calibration shaker (calibrated at Sira 16th January 2013). The calibrator provides a signal output at 157Hz at

exactly 1g onto this was mounted an accelerometer whose calibration sensitivity was shown on the cal sheet above to

be 92 mV/g. The analyser was set up with a sensitivity of 100 mV/g and a reading taken the spectrum shown in picture

10 shows that the amplitude recorded is 0.818g and not 1g Thus highlighting that the sensitivity is actually 81.8mV/g.

With the sensitivity reset to 0.818 mV/g the reading was taken again and this time the recorded amplitude read 1g.


Spectrum of accel with sensitivity set to 100mV/g

Spectrum of accel with sensitivity set to 81.8mV/g

A second trial was then carried out with the sensitivity set to 100mV/g and the output integrated to velocity. This time

two different sensors were used. The first sensor showed an overall vibration of 9.21 mm/second and the second 10

mm/second 8% higher (or lower depending on which one you consider correct!)

Velocity spectrum 1

Velocity spectrum 2


From this we can conclude that swapping sensors and leaving the sensitivity at the default will affect the amplitude of

the captured data. It is also a well known fact that the calibration sensitivity can drift over time especially if the sensors

are not looked after carefully. A regular check of the calibration sensitivity will show if the sensor is still working within

the required band. It is my considered opinion that your accelerometers be set up in your condition monitoring

database and the periodic calibrations entered into the system so a trend can be made of the sensitivity and warnings

set to indicate when a sensor is close or at the point of requiring a full recalibration. This is also true of the cable

assembly where the Bias voltage will indicate problems.

Bearing Analysis

As stated earlier, there are a wide variety of vendors producing condition monitoring and vibration analysis hardware

and software and although the principles remain the same there are usually specific analysis techniques associated

with these especially around bearing analysis. These basically breakdown into two main types:



The following discusses SKF’s enveloping technology

SKF is the largest manufacturer of bearings in the world, and so the applications we are asked to address are many

and varied. So to keep our reputation as a bearing manufacturer, we must use a technique that reliably covers as

many applications as possible. Development of SKF’s implementation of Enveloping (demodulation) was carried out

in a practical research environment. SKF uses the technology of enveloping in their own factories. It was first used in

the 1960’s as a quality tool.

Within the enveloping technique the two main variables are

Band pass filtering. What values of High Pass Filter and Low Pass Filter do you use for the band pass stage?

Detection type. Do you process the Peak or RMS signal?

These choices are key to the effective implementation of the technique in any one application.

SKF's differentiation is the Band Pass Filter bands that we have standardized on and successfully applied over

thousands of machines types and applications across the world for over 20 years. It does not matter what filter values

others vendors do - or do not - use, the key is standardization of the Band Pass Filter's, and their selection guideline,

across a wide range of applications a bearing manufacturer must cover.


In the sensor resonant technique the natural frequency of the accelerometer is used to amplify the tiny signals

generated by the defect. These produce a scalar value only, which may be trended.


This technique does not differentiate between vibration sources. Bearings are not identified nor are bearing

components; only the overall level is shown. The pulses could just as easily come from another source (Gears,

couplings etc)

Common pitfalls of this technique are:

1. Susceptible to background noise influences, Any random noise that occurs in the area of the sensor natural

frequency will enter the ‘amplification effect’.

2. Poor on slow rotating machinery, As speed and energy reduces, the frequency of the ‘overolling’ spike tends to

move outside the area of the sensor natural frequency, and the ‘amplification effect’ is lost.

3. If used as a one-off reading for analysis purposes it can provide wrong information. During the early stages

of a bearing defect the rolling elements pass over the sharp edges of the defect and give of a high pulse of energy.

As the defect progresses the sharp edges will be smoothed away and when the rolling elements pass over it they

now give off lower pulses of energy.

Over rolling defect early stage

Over rolling defect advanced stage

As the energy emitted by the advanced defect is lower the reading could be mistaken for a good bearing.


The Demodulation technique involves using band pass filters and "envelope" signal processing. It is used to EXTRACT

tiny signals generated by the defect from the background vibration. These produce a scalar value and an FFT which

may be trended or used for a one off analysis.

SKF’s implementation of enveloping (gE) was standardizing on 4 band pass filter values across all its instruments:

1. 5 Hz - 100 Hz

2. 50 Hz - 1 kHz

3. 500 Hz - 10 kHz

4. 5 kHz - 40 kHz


SKF’s enveloping technique has proven to be very effective in many applications for SKF over the past 20 years. When

used in a multi-parameter approach with velocity, acceleration and even acoustic emission, there are few applications

it cannot address.

Over the years the gE message has been misused and misinterpreted, and some still say (even in SKF) that the

technique does not work. This is untrue and the reason for such doubt almost certainly lies in the configuration of the

gE measurement.

The common configuration pitfalls of enveloping lie with incorrect

1. Band pass filter selection

2. FFT maximum frequency and line resolution

3. Detection type and averaging

4. Use of low frequency accelerometers when used on slow rotating shafts

Band Pas filter selection

A common demodulation guideline is that the high pass filter value of the selected band pass filter needs to be at least

10X shaft speed.

Enveloped filter selection

Filter 3 IS the filter used for bearing fault detection (Bearing faults will be detected in other filter bands (Filter 4 at the

very early stages of a fault occurring and filter 2 and 1 when the fault is very well established or almost at the point of

failure)).

Frequency - HzFilter #1 Filter #2 Filter #3 Filter #4

Rolls, Bearings Gears

FFT Spectrum5 kHz - 40 kHz

500 Hz - 10 kHz

50 Hz - 1 kHz

5 Hz - 100 Hz

Enveloping

Detector

Bandpass filter

Accelerometer

Felt

Frequency - HzFilter #1 Filter #2 Filter #3 Filter #4

Rolls, Bearings Gears

FFT Spectrum5 kHz - 40 kHz

500 Hz - 10 kHz

50 Hz - 1 kHz

5 Hz - 100 Hz

Enveloping

Detector

Bandpass filter

Accelerometer

Felt


From the illustration above it can be seen that NO reference is made to shaft speed so filter selection is independent of,

and NOT dependant upon, shaft rpm. Shaft RPM is however VERY important in setting up the envelope collection

correctly, Why?

1. Enveloping requires adequate TIME-LENGTH

2. This is defined by the selected Bandwidth versus the chosen RESOLUTION (LINES).

3. Time-length = Lines / Bandwidth.

4. Frequency (f) = 1/t (where t = time) so t=1/f. Knowing this we can calculate one period of the lowest frequency

of interest.

5. Optimal time-length is 15X the lowest frequency reciprocal that you are interested in. If you do not know the

bearing details use 40% of 1X.

6. The lowest frequency of interest will change with SPEED so the shaft speed needs to be taken into account

when calculating the lowest frequency of interest

7. gE levels will decrease as shaft speed lowers so lower alarm levels are needed

FFT Frequency and lines of resolution

If we look at the example below of a typical deep groove ball bearing running at 1800rpm we can calculate the time

period for one cycle, Time=1/Frequency = 1/11.39 which works out at 0.087 seconds.

If we look at the example again reducing the rotational speed to 50 rpm as shown in the picture below, the calculated

time period for one cycle is now, Time=1/Frequency = 1/0.32 which works out at 3.125 seconds. So for one period of

the fault frequency we have to wait 35 times longer than we do at 1800 rpm.


To obtain the best quality data we should allow the lowest frequency event occur 15 times during our collection period.

In the example at 1800 rpm we need a minimum of 1.305 seconds of data (15 * 0.087) and at 50 rpm we need a

minimum of 46.87 seconds of data (15 * 3.125)

As previously stated at lower shaft rotational speeds the energy given off by the defect is lower so we must adjust our

alarm bands accordingly. The calculation of alert and danger limit levels is based on one of 4 Fmax settings;

40 x N (where N is the running speed)

20 X N (where N is the running speed)

Fixed range of 500Hz

Fixed range of 1000Hz

Below pictures shows the difference in alarm levels from a shaft speed of 3600 to 1200 rpm

The


Fast Fourier Transform (FFT) relies on a signal consistently repeating itself with time and averaging is used for

standard Condition monitoring as it allows the data to become more statistically correct.

However the process of averaging when applied to gE readings actually damages the data – Why?

Bearing defect frequencies can be looked at as random signals in our data block as they do not happen synchronously

with other rotational characteristics.

Averaging exponentially reduces random frequencies with each average so we are potentially exponentially removing

the bearing fault frequencies with every average applied. Bearing showing defect:

In addition to this, the averaging process uses overlapping. This process allows us to reuse a percentage of the last

signal block as the first corresponding percentage the signal in the second data block speeding up data acquisition

50% has become the standard overlap when averaging data.

This reuse of the signal can make the bearing signals appear even more random and removed in the average process

The Fast Fourier Transform (FFT) relies on a signal consistently repeating itself with time.

But in some cases faults…..

±_c..can shift with time….or…

±_c..are not guaranteed to repeat.

One long FFT is much better than several quick overlap averages.

Data Block 1 Data Block 2 Data Block 3


3

Amplitude descriptor

The choice of amplitude descriptor (detection type) also has a large effect on the quality of the data. If we look at a

typical data block in the time domain (picture below), we can see some tall peaks due to short duration impacts -

potentially bearing defects?

If we use an RMS amplitude descriptor, then we sum the individual values and reduce the measured level to a much

lower calculated value. Individual peaks would have to grow massively before they have an impact on the RMS value.

If we select to use Peak or Peak-to-Peak then we are still not capturing the data correctly, as these two descriptors are

calculated from the RMS value (Pk =1.414* RMS) (Pk-Pk = 2 *Peak)

The correct way to look at this data is with a TRUE Peak detector as used in the Microlog

Low Frequency accelerometers

For many years now it has been widely accepted that when a shaft is rotating at a low number of revs per minute a low

frequency accelerometer should be used.

FOR BEARING ANALYSIS USING gE MEASUREMENTS THIS IS WRONG!

Band Data

capture range gE Band 3 High pass filter

no signals from within this range are taken into

the gE calculation

Useful range of sensor


Bearing analysis is done with gE band 3 which looks at signals in the 500 Hz to 10 kHz range so the first 500 Hz of the

signal is filtered out. As you can see the maximum useable range at the 3dB point is well below the 10 kHz range of

band 3 so the majority of the energy generated by a bearing defect will not be seen by these accelerometers. The use

of standard accelerometers will still allow us to detect bearing effects using gE band 3 on a shaft that has a very low

(sub 1 rpm) rotational speed.

Case Study - Monitoring of low Speed Slewing Bearings

Objective – to monitor the condition of the slewing bearings

Bearing Geometry

Roller

diameter Number of rollers

Pitch Diameter

Raceway 1 40mm 260 3550mm



Bearing Arrangement


Instrument used was a Microlog CMXA70 in conjunction with a CMSS 2200 (100 mV/g sensitivity) accelerometer

magnetically mounted in the horizontal and vertical direction. 4 areas on the outside of the bearing were cleared of

paint; readings were taken directly under the cranes jib and at 90˚intervals.

The main winch bearing was continually rotated at a speed of 0.317 rpm and data collected over several minutes (in

accordance with the setup described earlier in this paper). Analysis highlighted that although amplitude levels were low

the spectral data showed clearly that bearing fault frequencies that corresponded to the BPFI (ball pass frequency

inner race) were clearly visible.

Spectral analysis of main slewing bearing

Conclusions

With careful attention to detail and by fully understanding the consequences of setting to work any condition monitoring

program will provide an excellent return on investment in preventing catastrophic failure or assisting in the planning of

machine down time.


About the author

Paul Edwards spent 23 years in the British Royal Navy as an electrical engineer on submarines. On these vessels

vibration analysis was carried out on a daily basis, not for machinery health but to reduce radiated noise. His shore

based role was as the Navies senior vibration analyst where he was required to set up and run condition monitoring

programs for new classes of ships and carry out bespoke analysis on an ad hock basis. His skills were utilised during

machinery trials on new build ships to help pinpoint design defects and to improve the reliability of the machinery

onboard. On leaving the Navy he joined SKF and has carried out a number of roles from production test engineer to

consultant and trainer. His present role within the Condition monitoring group as “Mr Microlog” takes him all over the

world where he lectures and supports local SKF teams and customers. His knowledge of the world of noise and

vibration has been transferred into the Microlog range which has greatly increased their features and functionality.


Application Note

Setting up Accelerometers as Assets in SKF @ptitude Analyst

Setting up accelerometers as assets in SKF @ptitude AnalystYou will need:

SKF Microlog Analyzer AX or GX•Portable calibrator•Pen and paper•

Figure 1. The necessities: SKF Microlog, pen and paper, and a portable calibrator.


How to set up the tests in SKF @ptitude AnalystICP and Voltage should be set up as measurements irrespective of having a hand-held calibrator (ICP is a standard accelerometer point with ICP enabled) (Figure 2).

Figure 2. Accelerometer points.

Figure 3. Group Properties window – General tab.

In the General tab, in the Group Properties window, enter the factory sensitivity in the Description field (Figure 2). In the Setup tab in the POINT Properties window, the Input mV/EU field should remain at 100 irrespective of the sensitivity of the accel-

erometer (Figure 3).

Note: The Detection setting will depend on what is set on the calibrator.

Figure 4. POINT Properties window – Setup tab.

2 The SKF Analyst Newsletter Q1, 2013 Page 24

Note that voltage is a manual data entry.

Figure 5. DAD/POINT Type Selection window.


Set the overall alarm as an out of window alarm (Figure 7).If you have a handheld calibrator, calibration check can be set up as a third measurement. Note that calibration check is also a manual data

entry (Figure 8).Full scale is dependent on the factory sensitivity (Figure 9).

Figure 7. Alarm Settings window.

Figure 8. DAD/POINT Type Selection window.


3The SKF Analyst Newsletter Q1, 2013 Page 25

Set the overall alarm as an out of window alarm with the alert levels set according to the calibration data sheet for the accelerometer, usu-ally as a =/- % of set sensitivity:

Figure 10. Alarm Settings window – Overall tab.

Route loaded onto instrumentNote: The ICP icon in the toolbar indicates that the ICP supply is on (Figure 11).

From the ICP point, press the shift () and 2 keys. Note down the bios voltage reading when displayed and then press OK to return to the route screen (Figure 12).

Note: If you have a triaxial sensor connected, the bios voltage for channels X, Y and Z will be displayed.

Figure 11. ICP icon indicating that the ICP supply is on. Figure 12. Bios check results.


Applicable to calibration check onlyIf you have a handheld portable calibrator, you can now test the sensitivity of the accelerometer and cable (Figure 13).

Attach the accelerometer to the portable calibrator and switch it on, and then start the route measurement (Figure 14).

Figure 13. Portable calibrator.

Figure 14. Accelerometer attached to the portable calibrator.

Figure 15. Taking the route measurement.


Assessing the accelerometer's actual sensitivityOnce the data has been collected, use the Review function to display the spectrum and use the 7 key to locate the peak.

The amplitude displayed shows the sensitivity of the accelerometer. In this case, it is showing 0.906, so the sensitivity is 90.6mV/g. Note this and return to the route menu.

Manual data entry of bios voltageSelect the voltage reading to display the manual data entry screen, and then press the Manual function key. Use the keypad to enter the value you noted down previously and then press Enter (Figure 17).

The alarm will clear and you can press the Enter button again to return to the route menu (Figure 18).

Figure 16. Review Data screen.

Figure 17. Collecting data screen – with alarm. Figure 18. Collecting data screen – without alarm.


Manual data entry of calibration sensitivitySelect the calibration check reading to display the manual data entry screen and then press the Manual function key.

Use the keypad to enter the value you noted down previously and then press Enter (Figure 19).The alarm will clear and you can press the Enter button again to return to the route menu (Figure 20).

Figure 19. Collecting data screen – with alarm. Figure 20. Collecting data screen – without alarm.

View the trend for the bias voltage or sensitivityWhen finished, upload the data into SKF @ptitude Analyst and view the trend for the bias voltage or sensitivity.

Figure 21. SKF @ptitude Analyst – hierarchy screen.


Configuring your SKF Microlog Analyzer to connect to a Microsoft* Windows 7 operating system By Paul Edwards

Prerequisites To configure your SKF Microlog Analyzer for a USB connection to a Windows 7 operating system, you will need to take a few steps to ensure that the SKF USB Driver and Microsoft Windows Mobile Device Center are installed. Please follow these steps BEFORE connecting your Microlog. First:

Download a free version of Microsoft Windows Mobile Device Center – two options will be available through Microsoft’s download center: 1. Device centre for 32 bit OS 2. Device centre for 64 bit OS .

Run the Window’s Móbile Device Center installation program and follow the on-screen instructions. Once installed, you must configure Mobile Device Centre to communicate through the USB port. To do so, select the File menu’s Connection Settings option and enable the Allow USB connection… option. Second

Download the SKF Microlog Device Driver files from Microlog Driver Installer

Installing the SKF Microlog USB Driver To facilitate communication between the Microlog and a host PC, you must first install specific Windows driver files onto the host PC. Double click the SKF_USB_Driver_Installer_v1.00.8704.msi installer to start the installation.

When installation is complete, click Close

Connecting the Microlog Connect the Microlog Analyzer to the PC using the supplied USB communications cable. When the Found New Hardware Wizard appears on the PC, press cancel. Then, on the PC, run the driver installer located at Start/All Programs/SKF/USB Driver/Install. Follow the on screen instructions to install the new USB drivers. When the following message appears select Install the driver software anyway (Win 7)


http://www.skf.com/group/products/condition-monitoring/condition-monitoring-product-support/condition-monitoring-product-downloads/skf-microlog-analyzer-series/index.html

Turn the Microlog on and connect the Microlog to the host PC using the CMAC 5095 USB/Power Splitter Cable or by placing the unit on the docking station. Windows Mobile Device Center should automatically start, which indicates that the device is connected. At this point, you will have two options: Set up the device or Connect without setting up your device (Strongly recommended).


What to do if you connected your Microlog Analyzer to a PC before installing the drivers and the Mobile Device Center Software? If you have previously connected the Microlog Analyzer to your Windows PC before installing the Microlog drivers, the Driver Software Installation will likely report a failure and the drivers will not install (The reason why this may happen is due to your PC’s default setting to search for Windows updates for the driver). Close both screens and proceed to the next step.

Reconnect your Microlog Analyzer to the PC. In the Device Manager screen, under the Other devices category, you will find the SKF USB device with a yellow exclamation mark. Right click SKF USB and select Uninstall device.

Once uninstalled, disconnect the Microlog, reboot the PC, and start the procedure from the beginning of this tutorial. •Windows is a registered trademark of Microsoft Corporation in the United States and other countries.


2013 ‘Q1 SKF Microlog Analyzer Newsletter | 1

Stay informed with SMS Text messages or Simple Mail Transfer Protocol (SMTP) from @ptitude Analyst

By Robert Kaufman

The SKF @ptitude Analyst V7.0 software release has a great text and email feature that can

simplify the sharing of time sensitive information. The Simple Mail Transfer Protocol (SMTP)

is an Internet standard for email transmission across the Internet. It can operate within a

secure corporate environment to email just to employees within your company or across the

Internet using almost any common email service.

Once setup, this feature allows user to send or schedule notifications, email any generated

report, and configure the Scheduler application to perform actions in response to changes in

alarm conditions.

SMS (text) messages include the description of the alarm condition change in plain text, but

without the attached report. Email and SMS messages can be sent to an individual person,

or to groups of people. The email message format includes an HTML report along with

a .PDF attachment so that even members of your team without access to an account in the

SKF @ptitude Analyst software can receive timely and actionable information - that they can

open on almost any device.

The setup of your SKF @ptitude Analyst V7.0 SMTP connections are very easy to perform

provided that you can get some very basic SMTP server information from your company’s IT

provider.

In this article, I will focus on setting up the system to send messages within a corporate

network. This will allow you to access the corporate mail services from within any of your

company sites as long as they are within your companies firewall, or by connecting through

the approved VPN mechanism to the corporate network. This point is very important. If

the client application is located outside the company’s network, any attempts to connect to

the SMTP server using the SKF @ptitude Analyst Configuration Tool, or any attempts to

send messages using the application through the SKF SMTP server, will fail.



SMTP settings for @ptitude Analyst e-mail and text messaging are first configured in the SKF

@ptitude Analyst Configuration Tool. To access the configuration settings, follow the instructions

below:

1. Go to Start > Programs > SKF @ptitude Monitoring Suite > Admin Tools > SKF @ptitude

Analyst Configuration Tool.

2. Click on the SMTP Settings link in the left panel. [Figure 1.1]

Figure 1.1. Configure SMTP Settings in the Configuration Tool

In the right panel, input your company’s specific SMTP Settings as follows in blue:

Name: This name will appear in some e-mail clients receiving messages from @Analyst as the name of

the message sender. The Configuration Tool requires that this field be filled in. It can’t be left empty:



Enter any name as desired

Server Address: This text value contains the network address of the SMTP server that the @ptitude

Analyst application should use to send e-mail messages. Depending on the environment where the

software is being installed, this server may be either an internal location within an organization’s private

network, or a publicized public location for an external provider of e-mail service such as Google Gmail

or Yahoo Mail. The address may be specified as either a domain name such as smtp.gmail.com, or as a

valid IP address such as 74.125.137.109. The Configuration Tool requires that this field be filled in as

well.

Type in the name of your server

Port: Contains the port number associated with enabling clients to access the SMTP server described

above. The right port number to use depends on how an SMTP server has been set up by its owner,

and will often be publicized for the benefit of authorized users. The Configuration Tool requires that this

field be filled in with a non-empty numeric integer value:

Type in the port number provided to you by your IT support; example: 25

From: This text value contains an e-mail address that may appear in some e-mail clients as the

originating address for messages that are sent from the SKF @ptitude Analyst application. The

Configuration Tool requires that this field be filled in with a non-empty numeric integer value:

Enter any syntactically correct e-mail address

User Name: Contains the user or login name part of the authentication credentials used by many

SMTP service providers to ensure that their services are only being used by authorized users. This field

is required to be filled in by the Configuration Tool only if the “Requires authentication” checkbox is

enabled:



(Leave this blank for internal mail setup)

User Password: Contains the password part of the authentication credentials used by many SMTP

service providers to ensure that their services are only being used by authorized users. This field is

required to be filled in by the Configuration Tool only if the “Requires authentication” checkbox is

enabled:

(Leave this blank)

Requires authentication: Authentication usually consists of a login name and password combination.

When this box is checked, the SKF @ptitude Analyst application will provide the user name and

password described above as credentials to the SMTP server for authentication purposes:

(Leave this box unchecked)

Use secure connection: This box must be checked if the SMTP server uses standard encryption

protocols to protect the security of sensitive information being passed over the network:

(Leave this box unchecked)

Click the Test button once complete and a dialog box will display asking for an e-mail address. Input the

email address where the test notification will be sent to. For simplicity, I used my own corporate email

message and then clicked send. Once you confirm that you received the message, continue to the

steps below:



A confirmation dialog will appear. Press OK. [Figure 1.2]

Filling in these simple steps will allow you to configure all of the mail and SMS (text) messaging options.

Once the system is configured, you can then setup your contacts directly from within the SKF @ptitude

Analyst application by selecting

Customize > Contact Information



Why/When should you use a Bump Test? By Barrie Rodgers

When impacted, an object's natural or resonant frequencies are excited. A spectrum that is taken

while the object is vibrating (due to the impact) shows spectral peaks that identify the object's

natural frequencies.

Vibration forces transmitted by rotating machines often excite natural resonance in attached

structures. Whenever such structural resonance appears, vibration responses are amplified and

can result in fatigue failures. Structural resonances can also mask the cause of a machine's

vibration, making it difficult to implement corrective machine maintenance. A bump test is carried

out to determine if resonance is responsible for high noise or vibration levels.

Bump tests identify the machine’s resonance frequencies and provide a maintenance engineer

the opportunity to change the resonance frequency so as to reduce or eliminate damaging

vibration

Instrument settings for the bump test in the Microlog Analyzer series of instruments are similar to

that of the Analyzer module itself. The difference is that the signal involved is not steady state and

its magnitude will vary; therefore input amplifier auto ranging cannot be used. The expected input

range has to be set manually.

The magnitude of the signal will depend on;

• the frequency response of the structure

• the force being applied (how hard it is being hit)

• the mass of the hammer being used (how big the hammer is)

• the sensitivity of the accelerometer

Therefore estimation has to be made of the expected full scale range of the signal in transducer

units. (The range options change based on the transducer type selected). You must hit the

structure or machine with enough force each time to get the instrument to trigger, but yet not hit it

too hard and get a signal lover load. Natural frequencies of a system cannot be eliminated, but

can be shifted to some other frequency by various methods such as bracing or gussets to the

structure. Another alternative is to change the speed of the machine to move the drive

frequencies away from the natural frequency. Other corrective methods include isolation

methods or damping materials.



The Bump Test module allows two types of averaging to take place;

Exponential is a continuously moving average and Peak Hold holds the highest spectral peaks

that are measured during the test.

0.1 0.2 0.5 1 2 5 10 20 50 100

g

second0 40

+50g

-50g

Expected size of impact?


Date post:	31-Jan-2017
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