analog.com/en/resources/technical-articles/why-memes-acceler-are-best-choice-for-cbm-apps.html
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`Home / Resource Library / Technical Articles / Why MEMS Accelerometers Are Becoming the Designer's Best Choice for CbM Applications
`
`Why MEMS Accelerometers Are
`Becoming the Designer's Best Choice
`for CbM Applications
`
`by Chris Murphy Feb 12021
`
`_.
`.
`Introduction to Condition-Based Monitoring
`
`The global condition-based monitoring (CbM) market has experienced significant growth
`over the past few years, and this looks set to continue.1 This growth coincides with the
`rapid advancement of MEMS accelerometers for use in vibration sensing applications,
`
`now rivaling the once dominant piezoelectric or PZT accelerometer. There is an increased
`Page 1 of 37
`demand for CbM on lesscritical assets as well as a growing adoption rate of wireless CbM
`systems, and MEMS accelerometers are the keyto this. This article will compare MEMS
`
`accelerometers to piezoelectric accelerometers to highlight justhow far MEMS sensors
`
`[Eada to myanaiog > Share
`dpommanes
`tin
`
`Author's Contact Information
`
`Chris Murphy
`
`M
`
`

`

`EMU)ele Reeliisutd
`
`
`have come in their shortlifetime. Key design considerations for MEMS accelerometersin
`CbM applications will also be discussed with a comparison of five MEMS sensors from
`three different vendors.
`
`Related to this Article
`
`Products
`
`aoOa
`2a]
`oors
`
`)
`
`=7
`
`ADCMXL3021
`PRODUCTION @
`
`Wide Bandwidth, Low
`
`Noise, Triaxial Vibration
`
`Sensor
`
`>
`
`ADXL1002
`RECOMMENDED FOR NEW DESIGNS
`
`@
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`Low Noise,High
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`Frequency +/-50g
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`MEMS Accelerometer
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`>
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`ADXL317
`RECOMMENDED FOR NEW DESIGNS
`
`@
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`3-Axis, +16 g, 125 Digital
`
`Accelerometer
`
`>
`
`The Current State of the Art in Vibration Sensing—MEMSvs. Piezoelectric
`
`Vibration sensors have been used to detect machine health as far back as the 1930s. Even
`
`now vibration analysis is considered the most important modality for predictive
`maintenance (PdM). Piezoelectric accelerometers have been long established as the gold
`
`standard vibration sensor used on the most critical assets to ensure they remain
`
`operational and perform efficiently. Until recently, MEMS accelerometers’ limited
`
`bandwidth, noise performance, and g-range capabilities prevented their use in CbM of
`critical assets. While many high g-range accelerometers are available (designed
`specifically for automotive impact detection), they have very limited noise performance
`and bandwidth, making them unsuitable for CbM. Likewise, some low noise MEMS
`accelerometers (designed specifically to detecttilt) are available but have insufficient
`bandwidth and g-range.
`
`A small number of MEMS manufacturers have beenstriving to overcome the noise,
`
`bandwidth, and g-range shortcomings and as such have produced several medium and
`
`high performance MEMS accelerometers with the latter being comparable to piezoelectric
`
`accelerometers. MEMS sensors are based on a completely different principle of operation
`
`to piezoelectric sensors, and this is where the key differences arise. Figure 1 shows how
`
`MEMS can measure down to dc, allowing measurements from very slow rotating
`
`machinery as well as tilt detection. It is clearly understood that piezoelectric sensors can
`
`offer better noise performance than MEMS at higher frequencies, but at low frequencies
`
`MEMS sensors offer lower noise all the way to dc. Being able to measure these low
`
`Page 2 of 37
`
`

`

`BoMeleealvical
`
`i
`
`-are-best-choice-for-chm-apps.html
`frequenciesis very usetul for wind turbines, and other types of slow rotating machinery
`BFcay Mlees,
`so
`used in metal processing, pulp/paper processing, and food/beverage industries where
`slow rotating speeds of assets below 60 rpm (1Hz) are common.
`
`meme:
`
`— ADXL1002
`
`@
`
`Industry Solutions
`
`Technology Solutions
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`Product Categories
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`Resources
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`*
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`¥
`
`¥
`
`—— Plezo 10 Hz a
`
`Frequency (Hz)
`
`3 ::3
`
`Figure 1. Noise density: MEMSvs. piezoelectric.
`.
`Figure 2 shows that when piezoelectric sensors are exposed to large shock events they
`can saturate, and due to the large RC time constant they can take a long time to settle
`
`
`
`Using MEMS Accelerometers for
`Condition Monitoring
`
`Condition-Based Monitoring
`
`HTML Solutions to Accelerate Industry
`40
`
`back to normal. MEMS, on the other hand, matches the noncontact reference sensor by
`PE4oOiy
`settling back to normal almost instantly. The implications with a piezoelectric sensor
`r=}a=]
`undergoing a severe shock mean there is a risk that valuable information or failures in the
`©(7)
`ng
`asset/process could go undetected, while MEMS sensors will detect impact events and
`Ae
`
`subsequenteventsreliably.
`
`0
`
`Page 3 of 37
`
`

`

`
`
`Figure 2. Response to overload: MEMSvs. piezoelectric with laser reference.
`
`Table 1 highlights some more advantages of MEMS accelerometers for CbM applications.2
`
`Piezoelectric accelerometers are less suitable for wireless CbM systems due to a
`
`combination of size, power consumption, and a lack of integrated features, but solutions
`
`do exist with typical consumption in the range of 0.2 mA to 0.5 mA.
`
`Table 1. Comparison of Piezoelectric and MEMS Accelerometers for CbM Applications
`
`Steg
`
`:
`
`Piezoelectric
`Accelerometer
`
`$25 to $500+
`
`<1 LgivHz to
`eo
`50 pgivHz
`
`2.5 kHz to 30
`kHz+
`
`Short to
`medium
`
`$10 to $30
`
`25 uglVHz to
`aN
`
`3 kHz to 20
`
`Medium to long
`
`No
`
`Yes
`
`No
`
`Yes
`
`No
`
`Yes
`
`PoO
`iw2
`1©©
`me
`iM
`i?)
`
`
`
`Page 4 of 37
`
`

`

`
`
`=Oony
`Fe}i}
`oo
`re
`
`y)
`
`2i
`
`Accelerometer
`
`$10 to $30
`
`25 ug/\Hz to
`_—_
`100 po/sHz
`
`3 kHz to 20
`kHz+
`
`Medium to long
`
`Yes
`
`Yes
`
`Yes
`
`MEMS accelerometers also have a self-test feature where the sensor can be verified to be 100%
`
`functional. This could prove useful in safety critical installations where meeting system standards is
`made easier by the ability to verify if a deployed sensoris still functional. In some applications this
`feature is one of the most important as it allows maintenance professionals to know with absolute
`certainty the current state of the asset as well as the accuracy and reliability of what they are
`measuring.
`
`Design Considerations for MEMS Accelerometers in CbM Applications
`
`MEMS accelerometers designed specifically for CbM applications have some different
`characteristics compared to general-purpose accelerometers. In this section wewill
`discuss the key data sheet parameters of MEMS accelerometers suitable for CoM and how
`
`they relate to detecting machine faults. For example, how can we select a sensor with the
`
`correct g-range or noise performanceto detect bearing faults on a 300 kW induction
`
`motor? Table 2 shows a list of the most important specifications for five MEMS
`
`accelerometers targeted at CbM applications. Each specification will be discussed in detail
`
`in the following sections.
`
`Table 2. Comparison of Most Suitable MEMS Accelerometers for CbM
`
`No. Axes
`
`+3 dB Bandwidth
`
`7
`
`11 kHz
`
`3
`
`3
`
`4 kHz
`
`(xy)
`2 kHz (z)
`
`2.9 kHz to 8.5 kHz
`
`Page 5 of 37
`
`

`

`Table 2. Comparison of Most Suitable MEMS Accelerometers for CbM
`bl
`
` Cin br-lar-|loepmelfillic=crell
`
`ler-
`
`
`
`r-cbm-apps.htmlPF
`
`
`
`No. Axes
`
`+3 dB Bandwidth
`
`T1 KHz
`
`Resonance
`
`21 KHz
`
`Noise Density
`
`25 ug/NHz
`
`4 kHz (x, y)
`2 kHz (z)
`
`5.1 kHz (x, y)
`3.1 kHz (z)
`
`2.9 KHz to 8.5 kHz
`
`Notlisted, or up to 7
`kHz
`
`55 wg/VHz(x, y)
`120 ug/VHz(z)
`
`75 ug/NHz to 300 1g/
`VWHz
`
`50g
`
`1%
`
`16 g
`
`1%
`
`2 gto 64g
`
`Notlisted, or up to 2%
`
`-40°C to +125°C
`
`-40°C to +125°C
`
`-40°C to +105°C
`
`Yes
`
`No
`
`No
`
`g-Range
`
`Cross-Axis Sensitivity
`
`Temperature Range
`
`Solutions for Attaching
`MEMS to Machines
`
`Bandwidth
`
`The bandwidth of a vibration sensoris typically linked to the criticality of the assetit will
`
`be monitoring. A critical asset or motor is crucial to keeping a process or larger machine
`
`operational and online. If such an asset were to break down, it would lead to unplanned
`
`downtime and potential loss of revenue. In order to detect and diagnosefaults as early as
`
`possible, and avoid unplanned downtime, it is imperative to have a wide bandwidth and
`
`“[3]o
`Fe}3
`3)i)ir
`
`n
`
`2o
`
`Page 6 of 37
`
`

`

`berame-lur:|eye ene) if
`magnitudes and wide frequencies, as common faults with bearings, gear meshing, and
`
`pump cavitation all occur—or at least can be detected earliest—at higher frequencies
`
`greater than 5 kHz and even up to 20 kHz and beyond. Therefore, it is incumbent on
`
`MEMS sensorsto be able to compete with the de facto vibration sensors used for decades
`in industrial applications: piezoelectric accelerometers. A noise level of less than 100 ug/
`VHz and bandwidth of 5 kHz or greater is considered a high performance MEMS
`accelerometer for CbM. Table 3 categorizes the two most important criteria for
`
`MEMSaccelerometers used in CbM and PdM applications.3
`
`Table 3. MEMS Accelerometer PerformanceCriteria for CbM Applications
`
` MEMS Accelerometer
`
`Performance
`
`a)
`
`4(S)
`w2oO
`aa)
`ue
`
`High
`
`Medium
`
`Low
`
`<100 pg/VHz
`
`>5 kHz
`
`>100 pg/VHz and <1000 pg/VHz
`
`Up to 5 kHz
`
`>1000 ug/VHz
`
`Up to 1 kHz
`
`Not all sensors are required to be ultralow noise or wide bandwidth: there are levels to vibration
`sensing that depend on howcritical it is to keep an asset running. Water cooling pumps in a nuclear
`reactor could be considered extremely critical and, in this case, detecting a fault early is required. This
`means the criticality of the asset to be monitored will generally dictate the level of vibration sensor
`required, which relies on the following criteria.
`
`Fault Detection
`
`To simply detect if vibrations have gone above a threshold or warning level, a low
`
`Page 7 of 37
`
`

`

`'y-mem es-acceler-are-best-choice-for-cbm-apps.html
`performance MEMS accelerometer can be used. This method is typically employed on
`
`analog.com/en/resources/technical-a
`
`meoO
`hyFs}a=
`9ba
`irs
`
`
`
`I7
`
`3)
`
`lower criticality assets.
`
`Fault Diagnosis
`
`To detect and identify the potential source(s) of the fault, a higher level of MEMS
`accelerometer is required along with algorithms.
`
`Fault Prediction
`
`This requires the highest level of MEMS accelerometer performance in order to detect
`
`issues at the earliest possible time and allow algorithms to identify the source of the fault.
`
`This also requires good domain knowledge of the asset.
`
`Fault Prognosis
`
`This is the highest level of PdM requiring the best MEMS accelerometers along with
`
`algorithms, machine learning, etc., as well as expert domain knowledge of the asset. The
`aim of fault prognosis is to have the PdM system make recommendations to prolong the
`
`life of the asset or even optimize the performance ofthe asset.
`
`Keep in mind the performance level of the predictive maintenance sensor used on an
`
`Page 8 of 37
`
`

`

`r-cbm-apps.html
`
`Pleats
`
`2
`
`analog.com/en/resou
`
`chnical-artic
`
`cost of the asset itself.
`
`Table 4 showsthe range of available bandwidths of the MEMS accelerometers most
`
`suitable for CbM. Due to their mechanical nature, various moving silicon elements, and
`
`integrated conditioning electronics, it is not easy to make a wide bandwidth MEMS
`
`accelerometer, especially with low noise. Typically, the mechanical resonanceis several
`
`kHz away from the bandwidth of interest. Recently, several MEMS accelerometers have
`managed to move the usable bandwidth closer to the mechanical resonance with
`enhancedfiltering methods. However, some manufacturersstill choose not to state the
`
`resonant frequencyoftheir vibration sensors, which suggestsit is either very close to the
`
`usable bandwidth or reveals sensitive information on how their part works.
`
`Table 4. Bandwidth and Resonance of MEMS Accelerometers for CbM
`
`High
`
`<100 pg/VHz
`
`>5 kHz
`
`Bandwidth
`
`Resonance
`
`11 kHz
`
`21 kHz
`
`4 kHz/2 kHz
`
`2.9 kHz to 8.5 kHz
`
`51 kHz/3.1 kHz
`
`Notlisted, o
`to7
`TSEC OF UP 12
`kHz
`
`Noise Density
`
`MEMS accelerometer noise comes from several inherent sources such as Tlicker noise,
`Brownian noise, or electronics noise. It is usually expressed in yg/VHz. The noise output
`from a MEMS accelerometer is dependent on the outputfilter settings shown in Table 5.
`
`Some data sheets specify rms noise, but be careful as this will often be over a very small
`
`4ooy
`oa=)o
`auw
`ne
`te
`
`
`
`Page 9 of 37
`
`

`

`f-are-best-choice-for-cbm-apps. html
`
`analog.com/en/
`
`relate
`
`(oo
`
`PoO
`a2ae!
`©©ire
`i)
`
`
`
`2(
`
`Table 5. Filter Order Coefficient Used in Calculation of MEMS Accelerometer Noise
`
`|
`
`Filter Order
`
`First
`
`Second
`
`Third
`
`Fourth
`
`Brick Wall
`
`157
`
`1.11
`
`1.05
`
`7.025
`
`1
`
`The output rms noise of a MEMS accelerometer can be determined by the following formula:
`
`Output Noise rms = Noise Density x \Bandwidth x Filter Order
`
`(1)
`
`Once the sensor noise is understood, it is important to match the most suitable sensor to
`
`the machine type, keeping in mind some important questions such as: Will the sensor’s
`
`noise prohibit it from measuring important vibrations, and will the g-range of the sensor be
`
`able to withstand potential fault vibration levels? Luckily, there are standards that can help
`with this such as ISO 10816.
`
`ISO 10816 establishes conditions and procedures for the measurement and evaluation of
`
`vibrations from assets and machines. It defines a vibration severity standard where the
`rms velocity (10 Hz to 1 kHz) of the installed machine's housing is used as a condition
`
`indicator, as shown in Table 6. The measured vibration from the machine is classified
`
`Page 10 of 37
`
`

`

`br Urel(ofeReelfia)
`based on machine size, mounting strategy, and machine class (| = small, Il = medium, Ill =
`large with small foundation, and IV = large with rigid foundation).
`
`Table 6. [SO 10816 Vibration Severity Chart
`
`RMS Vibration
`
`Velocity (mm/s)
`
`0.28
`
`0.45
`
`0.71
`
`1.12
`
`1.8
`
`2.8
`
`45
`
`71
`
`11.2
`
`18
`
`28
`
`45
`
`A
`
`D
`
`A—Recently Commissioned Motor Installation
`B—Unlimited, Satisfactory, Long-Time Operation
`
`A
`
`DB
`
`rloO
`oy2o
`[(a
`re
`A:
`
`Y)
`
`Page 11 of 37
`
`

`

`e-best-choice-for-cbm-apps.html
`
`jie eile
`
`m=
`
`D—Vibration Level That Causes Damage to the Motor
`
`Please note that accelerometers typically output acceleration in g whereas ISO 10816 uses velocity in
`mm/s or in/s. Equation 2 can help us translate accelerations in g to velocity in mm/s. It determinesthat
`at a minimum vibration frequency of 10 Hz, the noise in the acceleration measurement must be less
`than 7.18 mg to detect vibration severity in the good range (A) for a Class 2 machine, per ISO 10816-1
`(VMIN = 1.12 mm/s) as shown in Table 6.4
`
`AnolsE < 27 fiwin * Vin
`
`Avorse = 2x * 10 Hz x Sg x —“S—< 7.18 mg
`
`1.12
`
`9.8 ——
`sec2
`
`Equation 3 offers this in a generic form, along with an example, which estimates the total
`noise associated with an accelerometer with a noise density of 80 ug/VHz, whenusing it
`with a single-pole low-pass filter that has a cutoff frequency of 1000 Hz (f¢ = 1000 Hz). At
`3.17 mg, the accelerometer appears to meet the boundary condition from Equation 2:
`
`aere)o
`Fel=)
`oi)Le
`a7)
`
`
`
`=(
`
`(3)
`
`AnorsE = ND *~+[ fygw] = ND =
`ANOISE = TE x x 1000|=3.17 mg
`
`80
`
`1
`
`Page 12 of 37
`
`

`

` as IX,
`
`
`
`a&e
`
`y
`=
`2
`
`55
`
`25
`
`120
`
`75
`
`110
`
`130
`
`130
`
`4000
`
`10,000
`
`2000
`
`6300
`
`6300
`
`|
`4200
`
`2900
`
`4.4
`
`3.1
`
`6.7
`
`75
`
`10.9
`
`10.6
`
`8.8
`
`Pass
`
`Pass
`
`Pass
`
`Pass
`
`Pass
`
`Pass
`
`Pass
`
`Pass
`
`Fail
`
`Fail
`
`Fail
`
`,
`Fail
`
`Fail
`
`Pass
`
`Pass
`
`Pass
`
`Fail
`
`Fail
`
`.
`Fail
`
`Fail
`
`Pass
`
`Pass
`
`Pass
`
`Pass
`
`Pass
`
`Pass
`
`Pass
`
`Pass
`
`ADXL1002
`
`ADXL317 [Z]
`
`MEMSB [X
`
`Y] x,
`
`MEMS B [Z]
`
`MEMS C1
`Ix, Y]
`
`—_
`
` analog.com/en/resources/technical-articles/why-memes-acceler-are-best-choice-for-cbm-apps.him
`Table 7 showsthe prescribedvibration levels for eachclass of machine from a known
`good state to dangerousfaultlevel vibrations and the corresponding minimum noise a
`MEMS accelerometer requires to detect known good vibrations in region A (Class | at 4.5
`mg, ClassII at 7.2 mg, ClassIll at 11.5 mg, and Class IV at 17.9 mq).
`
`
`
`Table 7. Noise Comparison of MEMS Accelerometers for CbM as per ISO 10816 Vibration
`Severity Standards
`
`UAPAreelal Mewim meeeetry
`
`Page 13 of 37
`
`

`

`
`300
`8200
`34.0
`Fail
`Fail
`Fail
`Fail
`
`emes-acceler-
`
`-he
`
`L
`-cbm-apps.html
`
`analog.com/en,
`
`/technical-a
`
`MEMS C2
`
`— oF
`
`— ee
`
`300
`
`300
`
`8500
`
`5600
`
`34.7
`
`28.1
`
`Fail
`
`Fail
`
`Fail
`
`Fail
`
`Fail
`
`Fail
`
`Fail
`
`Fail
`
`This data suggests that MEMS C2, MEMS C1, MEMS B, and ADXL317 (z-axis) are not suited for use on
`machines wherea noise level below 0.71 mm/s or 4.5 mgis required to detect a known good level of
`vibration (A). MEMS B, MEMS C2, and MEMS C1arenot suited for use on machines requiring noise
`below 1.12 mm/s or 7.2 mg. MEMS C2 do not have sufficient noise performance, for use on any class of
`machine shown, to detect known good vibration severity levels (A).
`
`Please note that all sensor noise values reported in Table 7 are for full bandwidth
`
`measurements even though ISO 10816 is only concerned with bandwidths up to 1 kHz. It is
`
`assumedthat if a vibration sensor has a wider bandwidth this will typically be used in
`
`order to not only detect vibration severity but also to diagnose any potential faults at
`
`higher frequencies. With the bandwidthlimited to 1 kHz MEMS C1 fails Class | noise levels
`
`while MEMS C2 only passes on Class IV.
`
`g-Range
`
`This tells us the acceptable range of accelerations that a sensor can reliably detect while
`
`guaranteeing the data sheet performance. Anyone who has ever tested a +2 g sensor will
`
`have been able to generate more than 2 g while shaking the sensorin their hand. Most
`
`MEMS accelerometers, especially analog output, have some headroom due to mechanical
`elements and signal conditioning electronics. For CbM typical g-range requirementsstart
`
`xois
`reiS
`oore
`eS
`7)
`
`
`
`Page 14 of 37
`
`

`

`analog.com/en
`
`g for use on industrial gearboxes, compressors, medium and high voltage induction
`
`motors, etc.
`
`When measuring vibrations, it is important to understand the relationship between
`
`acceleration, velocity, and displacement.If a vibration, measured on one axis, causes 250
`
`nm of displacement while vibrating at 1 KHz, the generated peak acceleration will be
`ApK(250 nm, 1 kHz) = 1g. For the same displacement at 10 KHz, the peak acceleration will
`now be Ap (250 nm, 10 KHz) = 100 g.
`
`==
`ee Direction of
`
`Q
`
`re ~
` we i owEE= 43°
`Linear Vibration
`onasDox
`
`!j
`
`
`
`ai
`
`tp)
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`aeoa
`Fe}i]
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`Le
`
`A,,(D,,.f) = 4= 1? =f» D,
`alt)=A,, = sindw, = t)
`
`Avg=
`vz
`f= Wy
`¥2n
`
`D,,...Peak Displacement
`Apy--Peak Acceleration
`a(t)...Instant Acceleration
`
`Figure 3. The relationship between acceleration, velocity, displacement, and g-range.5
`
`It is vitally important to understand the potential vibrations that can occur in your asset
`
`before selecting a vibration sensor. Some motor manufacturers will provide such
`
`Page 15 of 37
`
`

`

`
`
`discussed in the “Noise Density” section.
`
`When selecting a MEMS accelerometer for use with a machine covered under ISO 10816,
`
`we can follow some easy steps to determine if the g-range is accept-able for use.
`
`Equation 4 presents a specific example, which determines that measuring unacceptable
`vibration severity on a Class IV asset, per ISO 10816-1 (Vyyax= 28 mm/sec), at a
`frequency of 1000 Hz (fyyax) will require a measurement range ofat least +25.3 g.4
`
`Apgak > 2 xm x 1000 Hz x 2025mxo (4)
`
`Apgak > 2 XX fy x Vegax
`
`Apgak > 25.3 g
`sec
`
`028
`
`]
`
`It should be noted that these fault classes do not consider a MEMS sensor's ability to
`withstand base load vibration. Typically, a sensor with a smaller g-range or full-scale
`range will be less resistant to wear and tear of its mechanical elements. Also, with a
`
`smaller full-scale range it is easier for vibrations of interest to be masked by baseline
`vibrations.
`
`Table 8 shows ISO 10816 vibration severity charts both in mm/s and g for each class of
`
`asset. A range of MEMS accelerometers suitable for use in CbM applications are
`
`compared. +16 g of g-range is not enough for use on Class Ill and Class IV assets, but it is
`
`acceptable for Class | and ClassIl. The only two sensors with sufficient g-range are
`ADXL1002 and MEMS C2.
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`Cin bertesTurl(efeReal aiT
`Low g-range MEMS accelerometers for CbM (<+16 g) are limited to use on Class | and
`Class II machines, per ISO 10816, as the maximum vibration severity for Class Ill and Class
`IV machines exceeds +16 g. This means that noise performance in low g-range MEMS
`
`accelerometers for CbM becomes even more important to ensure they can be used on
`
`Class | and Class || machines, as discussed in the “Noise Density” section.
`
`Table 8. Comparison of MEMS Accelerometer g-Range for Use with Class | through Class
`IV Motors
`
`
`
`ADXL1002
`
`ADXL317
`
`MEMS B
`
`MEMS C1
`
`MEMS C2
`
`50 g
`
`16 g
`
`16 g
`
`16 g
`
`64g
`
`Pass
`
`Pass
`
`Pass
`
`Pass
`
`Pass
`
`dahil f
`
`Pass
`
`Pass
`
`Pass
`
`Pass
`
`Pass
`
`Pass
`
`Pass
`
`Fail
`
`Fail
`
`Fail
`
`Fail
`
`Fail
`
`Fail
`
`Pass
`
`Pass
`
`When selecting a MEMS accelerometer for use in CbM applications, you must refer to the asset
`manufacturer's specifications to find potential fault vibration severity information, perform your own
`tests, and/or refer to standards such as ISO 10816. By combining the information from Table 7 and
`Table 8, itis clear that the majority of CoM MEMS accelerometers on the marketfail to meet the criteria
`outlined in ISO 10816 in terms of noise performance to measure known good vibration severity levels
`and g-range to detect potential faults per class of motor. The only sensorthat has sufficient noise
`performance and g-range is the ADXL1002, one of a family of sensors from Analog Devices designed
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`accelerometers for CbM need to be classified based on this evidence, and this Is shown in Table 9.
`Noise and bandwidth are considered the highest importance, hence the weighting. g-range is next,
`followed by temperature range and cross-axis sensitivity.
`
`Table 9. Decision Matrix for Choosing the Best MEMS Accelerometer for PdM Based on Key
`
`nei eiSci 8
`
`
`
`[weight]
`
`+3 dB
`
`Bandwidth [5]
`
`Noise Density
`[4]
`
`g-Range [3]
`
`Temperature
`Range [2]
`
`Cross-Axis
`sib
`Is
`Sensitivity [1]
`
`il
`
`1
`
`2
`
`1
`
`dl
`
`5
`
`2
`
`3
`
`1
`
`1
`
`3
`
`3
`
`3
`
`1
`
`S
`
`4
`
`4
`
`3
`
`9
`
`2
`
`2
`
`5
`
`1
`
`9
`
`Z
`
`Total
`
`Rank
`
`18
`
`First
`
`45
`
`A3
`
`Fourth
`
`Third
`
`51
`
`Fifth
`
`42
`
`Second
`
`ADXL1002 is a clear leader in terms of performance and sois classified as the highest performance
`MEMS accelerometer in CbM applications. All other sensors, while still offering excellent performance,
`are classified as medium performance CoM accelerometers given the gaps in performance.
`
`Temperature
`
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`eler-are-best-choice-for-cbm-apps.html
`There are several specifications to consider when it comes to temperature performance of
`MEMSaccelerometers. Table 10 shows some veryinteresting comparisons between key
`temperature related data sheet specifications. Clearly there is a significant range in terms
`
`of the numbers, but what doesthis translate to in terms of performance? A review of the
`most commonapplications for CbM (oil and gas, metal processing, food and beverage,
`and power generation) shows that potential temperatures on assets can easily exceed
`105°C due to factors, such as overdriving the load capabilities, leading to excess current
`being drawn, contamination (dust, debris) raising the internal temperature of a motor and
`
`preventing it from cooling, and even creating vibrations that can generate excess heat.
`
`External factors, such as potential gas or steam leaks, can also play a part in selecting a
`
`sensor. Piezoelectric manufacturers appear to favor a maximum temperature range of
`120°C for most of their general-purpose vibration sensors with some application specific
`sensors having 150°C maximum operating temperature. A survey of high frequency
`sensors (up to 10 kHz and greater)showed that 74% of sensors had a maximum operating
`temperature range below 125°C, with 24% below or equal to 80°C. There are some
`
`special-purpose piezoelectric sensors that can withstand 200°C and higher just like there
`
`are special-purpose MEMS accelerometers that can work up to 175°C, but this article is
`
`not focused on sensors for very specific applications.
`
`Table 10. Temperature Performance Comparison of MEMS Accelerometers for CbM
`
`Parameter [weight]
`
`|
`
`Temperature Range
`
`-40°C to +125°C
`
`—40°C to #125°C
`
`~40°C to +105°C
`
`Sensitivity Change
`
`0 g Bias Error
`
`45%
`
`+10%
`
`+2.5% (x, y) 4.5% (z)
`
`=1% to +4.35%
`
`49%
`
`£0.1% to +1%
`
`8
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`
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`temperature defines how the sensor's sensitivity changes over temperature.It is not uncommonto see
`piezoelectric accelerometers with scale factor error over temperature up to 20%, which could lead to
`significant drift, although 5% is more typical. Such errors require calibration during production. MEMS
`accelerometer scale factor or sensitivity error over temperature is excellent due to being trimmed
`electrically during production, resulting in sensors that do not drift over temperature. As an example, if
`the ADXL1002 was exposed to a temperature change from 25°C to 85°C, the sensitivity (40 mV/g)
`would change by 0.03%/°C x 60 = 1.8%, which means the sensitivity change over 60°C is within 39.28
`mV/g to 40.72 mV/g. This shows that for MEMS accelerometers the sensitivity is quite stable vs.
`temperature change. For most applications, temperature compensation for sensitivity is not required.
`
`Zero g offset is the output of the accelerometer when no acceleration is applied. Ideally
`
`this should be zero, but due to inherent imperfections within the MEMSsensor we see a dc
`
`offset. In most cases, maintenance professionals are primarily concerned with dynamic
`data (ac output from the accelerometer) such as deviations from baselines or trending
`away from an operating normal. For this reason, zero g offset is not a prime concern when
`
`using MEMS accelerometers for CbM. Zero g offset can be easily calibrated out of
`
`measurements, and most high performance digital sensors will provide registers to
`
`perform this action with ease. Where dc or tilt detection is of interest, zero g offset over
`
`temperature can also be calibrated out. The smaller the operating temperature range, the
`easier this will be.
`
`Numberof Axes
`
`MEMS accelerometers are available in single, dual, and triaxial versions. Unlike
`
`piezoelectric accelerometers, there is no real size difference between single and triaxial
`
`MEMS accelerometers. Smaller size is one of the key advantages of MEM Sover
`
`piezoelectric, along with much lower power consumption and higher levels of integration.
`
`With 3-axis piezoelectric accelerometers there are some clear disadvantages—such as
`
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`
`
`
`accelerometers, size, and accuracy—but one of
`
`the main drivers for using triaxia
`
`piezoelectric accelerometers is to allow easier collection of data for portable vibration
`readers. Instead of having to prepare three sites (single-axis sensors) then take three
`
`separate readings, one triaxial sensor can do this alone. For assets with restricted access,
`
`this can be a major advantage. Also, when measuring vibrations in multiple directions, it
`
`can be important to maintain phase relations between axes andatriaxial device will
`
`
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`ensure this. For complex vibration analysis it is important to see events on all axes with no
`
`phase mismatch as this could lead to misinterpretation of events.
`
`With a triaxial piezoelectric sensor measuring vibration in the x, y, and z directions it is
`possible to measure the tangential motion/vibration of the axis of rotation. Many
`
`mechanical forces generated by rotating machines—soft footing, for example—produce
`such tangential motions of the casing. This is not possible to detect with a single-axis
`piezoelectric sensor. With single-axis MEMS accelerometers, it may be possible to detect
`
`such events because the dc content of the measured signal corresponds totilt, assuming
`
`the resulting rocking of the asset occursin the sensitive axis.
`
`Vibration excitation is often directional, depending on the fault, such as a spall on an outer
`bearing race, mechanical looseness, misalignment, or a bad gear tooth. The direction of
`the fault vibration is not always predictable, so one can't know which direction—axial,
`
`radial, or tangentialtthe vibration will travel. There also can be more than one fault
`
`causing abnormal vibrations. One study focused on demonstrating the potential for
`
`improved diagnostic capability when usingtriaxial piezoelectric sensors vs. single axis
`
`radial and axial sensors.6 The study revealed that single-axis accelerometers can miss the
`
`diagnosis of nearly 50% of the mechanical faults outlined previously if sensors are only
`placedradially or tangentially as shown in Figure 4. Seeing as the direction of the fault
`vibration is the issue, adding more sensors on the sameaxis will not solve this problem.
`Adding an axial accelerometer improved fault detection to almost 70%. Adding one more
`
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`3 analogcom/en/res
`axial sensor increased the detection to 80%. This shows that the extra diagnostic
`
`information from different axes can lead to better fault detection, but not that this must be
`
`done with a triaxial sensor. This study found that having data for all three axes was
`
`redundant in many cases butstill recommended measuring on three axes if possible.
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`Tangential
`
`Axial
`
`Figure 4. Motor vibration axes.
`
`While having more data is always beneficial, it is not always required, especially in
`
`wireless systems where measuring or transmitting redundant data can shorten the life of
`
`the battery. Proper placement of sensors whether they be single, dual, or triaxial is critical
`
`but according to the above research, based on wired piezoelectric sensors, triaxial
`
`sensors should be used whenever possible.
`
`For MEMS accelerometers, any existing triaxial sensors have reduced performance
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`compared to piezoelectric sensors, so the likelihood is that they will not be able to detect
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`as many faults. Furthermore, the z-axis in most triaxial MEMS accelerometers has lower
`
`performance in noise, bandwidth, or both, as shown in Table 11, possibly weakening the
`
`potential added value of extra axes reported by studies based on triaxial piezoelectric
`
`accelerometers. In some cases, all axes will have different performance in terms of noise
`
`and/or bandwidth, the two most important specitications for CbM.
`
`Table 11. Variation in Noise and Bandwidth from Axis to Axis for MEMS Accelerometers for
`
`Bandwidth X
`
`11 KHz
`
`Bandwidth Y
`
`Bandwidth Z
`
`Noise X
`
`Noise Y¥
`
`Noise Z
`
`a
`25 ug/vHz
`
`4 kHz
`
`4 kHz
`
`2 kHz
`
`—
`55 ug/vHz
`
`—
`55 yg/VHz
`
`4.2 KHz to 8.2 kHz
`
`4.2 KHz to 8.5 KHz
`
`2.9 KHz to 6.3 kHz
`
`75
`
`ug/VHz to 300
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`120 ug/Hz
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`110 ygIVHz to 300 pg!
`VHz
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`The implications of this mismatch in terms of noise and/or bandwidth performance first appears to
`somewhat negate the advantages of having extra axes (y, z) in one place on an asset. This is well
`understood by designers familiar with MEMS sensors, but a few things need to be considered. MEMS
`triaxial accelerometers can be orders of magnitude lower in cost with comparable performance to
`piezoelectric accelerometers and far smaller, so more sensors can be placed, even in wireless
`
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`installations on less critical assets. This provides more diagnostic insights into the general operation of
`the asset.
`
`Cross-Axis Sensitivity
`
`Cross-axis sensitivity (CAS) refers to how much output is seen on one axis when
`acceleration is imposed on a different axis, typically expressed as a percentage. For
`
`piezoelectric accelerometers, which are predominantly single axis, this will be given as
`transverse sensitivity, which describes the sensitivity to any motion not on the same axis it
`was designed to measure on. For a triaxial accelerometer experiencing acceleration only
`
`on its y-axis, some acceleration will be measured on the x and z axes due to CAS. Figure 5
`shows a CAS of 1% as the y (or z) axis experiences 1.5 g of acceleration; this is also
`observed on the x-axis as 15 mg or 1% of 1.5 g. This phenomenon also affects single-axis
`MEMS accelerometers. The lower this percentage, the more accurate and reliable is the
`vibration data that can be measured and used to detect faults, anomalies, and drifting
`
`trend lines.
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`X-AxisResponse(9)
`
`
`
`Acceleration on Y- or Z-Axis(g)
`
`Figure 5. Cross-axis sensitivity observed on the x-axis of a 3-