Vibration Analysis Focusing on the Spectrum (Remastered)
Summary
TLDR本视频脚本为观众提供了一次关于振动分析的深入讨论。主讲人介绍了振动监测的基本理论,包括如何测量和分析机器的振动信号,以及如何通过振动的频率和幅度来诊断机器的健康状况。通过案例研究,展示了振动分析在监测和预测机械故障方面的实际应用,强调了识别机器故障信号的重要性,并解释了如何利用这些信号来提高设备的可靠性和性能。
Takeaways
- 📈 振动分析是一种监测机器健康状态的有效工具,通过测量振动信号来识别机器中的潜在问题。
- 🔍 机器通过振动信号而非语言与我们沟通,振动监测可以帮助我们理解机器的运行状况。
- 📊 振动监测可以测量信号的高度和持续时间,从而识别机器中具体部件的问题。
- 🔨 机器的振动可能与电气、机械或过程相关,振动监测能够区分这些不同的信号来源。
- 🌡️ 振动测量需要考虑机器的力和运动,包括机器的对齐情况和振动速率。
- 🔄 机器的不同部件,如叶片、螺丝压缩机或齿轮,会产生独特的“心跳”模式,即振动信号。
- 📉 振动信号的波形复杂,但可以通过傅里叶变换等数学方法简化为频率谱,便于分析。
- 📌 频率谱中的峰值可以指示机器问题的性质,如不平衡、轴承损坏或其他机械故障。
- ⚙️ 振动监测不仅关注振动的幅度,更关注幅度的变化趋势,以识别机器状态的变化。
- 🛠️ 通过案例研究,展示了振动监测在实际应用中如何帮助诊断和修复机器故障。
- 🔧 振动分析需要结合专业知识和经验,以正确解释数据并采取适当的维护措施。
Q & A
振动分析是什么,它在机器监测中扮演什么角色?
-振动分析是一种监测和分析机器振动信号的技术,用于评估机器的运行状况和预测潜在故障。在机器监测中,振动分析帮助我们通过测量和分析振动信号来理解机器的“语言”,从而提前发现问题并采取措施。
为什么机器会产生振动信号?
-机器在运行过程中,由于机械、电气或过程等方面的问题,会产生振动。例如,机器的不对中、轴承损坏或者叶片不平衡等问题都会导致振动,这些振动信号可以被传感器捕捉并分析,以确定机器的健康状况。
振动监测中测量的信号有哪些特点?
-振动监测中测量的信号特点包括信号的高度、持续时间以及频率。信号的高度可以反映振动的强度,持续时间可以帮助我们理解每个事件的长短,而频率则可以揭示机器中哪个部件可能存在问题。
什么是机器的“心跳”信号,它如何帮助我们识别问题?
-机器的“心跳”信号是指机器在正常或异常运行状态下产生的特定频率的振动模式。通过分析这些模式,我们可以识别机器的特定部件是否存在问题,例如齿轮的缺陷、轴承的损坏等,从而实现对机器健康状况的跟踪和诊断。
为什么需要考虑机器的对中和运动对振动监测的影响?
-机器的对中和运动直接影响振动信号的特性。如果机器不对中,会导致额外的力和振动,可能会损坏轴和轴承。了解机器的运动和振动速率有助于我们更准确地诊断问题,比如通过分析振动的频率和幅度来确定故障的类型和位置。
在振动分析中,频率分析的作用是什么?
-频率分析是将复杂的时间波形信号转换为频率域,以揭示信号中不同频率成分的强度。这有助于识别和量化机器中的特定问题,如不平衡、轴承损坏等,因为这些问题会在特定的频率上产生特征峰值。
什么是振动信号中的谐波和边带,它们如何帮助诊断问题?
-谐波是基本频率的整数倍频率,而边带是位于中心频率两侧的等间隔的频率峰值。它们通常与机器中的非线性问题或松动部件有关。通过分析谐波和边带的分布和间距,可以提供关于机器故障性质和位置的重要线索。
为什么振动监测需要定期进行,而不仅仅是在机器启动时?
-定期进行振动监测可以追踪机器的运行趋势和健康状况的变化。机器可能在运行过程中逐渐出现问题,如磨损或损坏,这些问题可能不会立即显现,但通过定期监测可以及时发现并采取措施,避免更严重的故障发生。
在实际案例中,振动监测如何帮助识别和解决轴承问题?
-在实际案例中,通过监测轴承的振动信号,可以发现异常的频率峰值,如谐波和边带,这些特征表明轴承可能存在问题。通过进一步分析这些峰值的频率和间距,可以确定故障的具体类型,如内圈、外圈或滚动元件的损坏,并据此进行维修或更换。
振动监测在旋转设备上的应用有哪些局限性?
-虽然振动监测是一种强大的工具,但它也有局限性。例如,它可能无法检测到所有类型的故障,特别是那些不产生显著振动信号的问题。此外,振动监测需要专业知识来正确解释数据,而且可能需要与其他监测技术结合使用,以获得更全面的机器健康状况评估。
Outlines
🔍 振动分析基础与监测理论
本段介绍了振动分析的基本概念,包括振动监测的目的和基本理论。振动分析可以帮助我们通过测量机器发出的信号来了解其健康状况。机器的信号不是用语言,而是通过振动来表达。振动监测可以测量信号的高度和事件持续时间,以识别机器中有问题的特定组件。此外,还讨论了不同类型的振动源,包括电气、机械和过程振动,并强调了正确准备和放置传感器的重要性。
📊 振动信号的测量与分析
这段内容深入探讨了如何通过振动监测来测量和分析机器的信号。解释了机器的'心跳'如何反映其健康状况,以及如何通过监测这些心跳来跟踪机器的状态。讨论了不同类型的机器组件,如叶片、螺杆压缩机和齿轮,它们如何产生独特的心跳模式。强调了监测这些模式变化的重要性,以及如何通过频率分析来识别机器问题的性质,例如不平衡、冲击事件或轴承损坏。
🌐 振动信号的频率分析
本段讲述了如何将复杂的振动信号转换为更易于分析的频率谱。介绍了通过数学方法将时域信号转换为频域信号的过程,以及如何通过频率谱来识别和诊断机器问题。解释了如何通过观察频率谱中的峰值来识别机器的特定问题,例如不平衡、轴承损坏或其他机械故障。还讨论了如何通过分析频率谱中的谐波和边带来进一步诊断问题。
🛠 振动监测的实际应用案例
这段内容通过实际案例展示了振动监测在工业应用中的重要性。描述了一个锤式磨机轴承的监测案例,说明了如何通过定期的振动测量来跟踪机器的冲击强度和频率变化。通过监测这些变化,可以及时发现问题并在必要时进行维修。案例还展示了如何通过频率谱分析来识别特定问题,例如轴承外圈故障,并采取相应的维修措施。
🔧 振动监测在大型驱动系统中的应用
本段讨论了振动监测在大型驱动系统中的应用,特别是在一个气体循环风扇的电机驱动案例中。描述了如何通过定期监测来识别和诊断问题,例如通过分析振动信号的频率谱来发现谐波和边带,这些特征表明了转子条问题。案例强调了高分辨率测量的重要性,以及如何通过分析数据来确定问题的根本原因,并采取适当的维修措施。
🔄 振动监测的总结与问题解答
最后一段对振动监测的重要性进行了总结,并强调了理解振动信号或'心跳'对于识别和解决问题至关重要。振动监测不仅可以帮助识别机器的多种缺陷,还可以通过分析信号来确定何时采取纠正措施。演讲者感谢听众的时间,并欢迎任何问题,显示了对主题的深入理解和对交流的开放态度。
Mindmap
Keywords
💡振动分析
💡信号
💡故障诊断
💡频率
💡振幅
💡轴承
💡不平衡
💡冲击振动
💡频谱分析
💡案例研究
Highlights
振动分析讨论会旨在提供振动监测的基础知识和视觉洞察。
机器通过振动信号而非语言与我们交流,振动监测可以帮助我们理解机器的健康状况。
振动监测可以测量信号的高度和持续时间,以识别机器中的问题部件。
机器的信号可能与电气、机械或过程振动有关,振动监测可以帮助区分这些问题。
振动监测时,机器的对齐、运动和振动速率是关键考虑因素。
机器的不同部件,如叶片、螺杆压缩机和齿轮,都有其独特的“心跳”模式。
通过监测机器的“心跳”,我们可以跟踪其健康状况并预测潜在问题。
振动分析中,振幅和频率的变化是识别机器问题的关键指标。
通过频谱分析,可以将复杂的时间波形转换为更易解读的频率谱。
频率谱中的峰值可以帮助我们识别机器中的缺陷,如不平衡、轴承问题或齿轮缺陷。
振动信号中的谐波和边带是识别机器问题的重要特征。
案例研究展示了如何通过振动监测数据识别并解决实际的机器问题。
通过长期趋势分析,可以观察到机器振动水平的变化并采取相应的维护措施。
振动监测不仅用于检测问题,还能帮助提高机器的可靠性和性能。
在分析振动数据时,理解机器的运动和振动特性对于诊断问题至关重要。
振动分析是一种有用的工具,可以补充高频方法,以识别旋转设备上的多种缺陷。
理解振动信号的“心跳”是识别问题原因并采取纠正措施的关键。
Transcripts
[Music]
okay and good afternoon everybody
welcome to this very short 30 minute
discussion on vibration analysis
hopefully it gives you a good taster and
a visual insight into vibration
monitoring and hopefully the end we'll
just talk about one or two case studies
so uh we're going to talk about some
theoretical points to start with very
basic hopefully
talk about the signals we measure and
indeed as i say um
some couple of case studies to talk
through so
talk our machines talk
they talk to us but maybe what they
don't speak is uh
english or spanish or german
obviously they speak vibration
when they're not healthy
you know be nice if they actually said
what was wrong with them but sadly
that's not the case
but what they do talk is signals
so with vibration monitoring we can
measure the signals we can measure the
height of the signal
and we can measure the distance the
how long each event takes to understand
which component in the machine is
problematic
so we can narrow it down to a specific
component within the rotating asset
here we have a sensor placed on the
machine the forms of liberation that we
measure at this particular location
could be
electrically related
they could be mechanically related to
different parts of the machine itself in
a mechanical context we'll talk about
those in a moment
and thirdly it could be a process
vibration so whenever we take a
vibration measurement to measure the
health and trying to track the health of
an asset
all of those different considerations
could be measured through the signal and
we can separate them out to understand
which part of the machine is it
processed is it electrical or is the
mechanical problem we're dealing with
i think a key point to think about with
preparations
around this machine i will measure those
forces obviously very exaggerated
but if the machine were misaligned like
this and it's bolted down
actually is trying to do this in real
operation and that's going to destroy
the shaft bearings the chassis and so
forth
so we have to think about the forces and
secondly think about the motion and
indeed the
the rate of the vibration the rate at
which it moves we'll look more in in a
moment about that different parts of the
machine will vibrate the heartbeat the
the heartbeat of the machine here if the
blades the way that liquid cuts through
the system is disturbed maybe the
causation force from
this the vibration signal we see will
produce a different heartbeat to what we
saw before
maybe the loops and screw compressor
there will be a certain number of uh
sorry screws here so we have various
screws on each
shaft there
both screws will produce a unique
heartbeat if there's four screws four
heartbeats per rotation
obviously much more detailed here maybe
but in simple terms each gear will have
a certain number of teeth
and this defect on one of the teeth or
all the teeth or some of the teeth
the heartbeat pattern will be distinctly
different again to what we saw before
where the machine was misaligned or
secondly we saw the loops or the blades
on the pump
so you can see there obviously you've
got a certain number of teeth on each
gear that will produce a certain number
of pulsations if it's 20 teeth on this
gear for example 20 pulsations per
rotation
so we can trend we can track that
particular heartbeat and measure the
health
maybe with an imbalance you know the
forces here are more radio again the
force is radial but it's more of
emotional force maybe in this context
with the heartbeat it could produce
another distinct pattern the shutter
speed produces a particular force
maybe in this situation we've got more
of a shock event or an impact event so
it's going to disturb the signal in a
slightly different way to what we've
seen before
maybe with a bearing
you know if if there's a damaged spot on
the bearing it's going to produce a
certain number of pulses impacts per
rotation maybe the next slide we can
count them the defect here is where that
red dot is at 12 o'clock one shot two
three four five six seven eight and a
bit
eight and a bit shocks per rotation not
seven not eight but eight point
something that's uniquely different
that's what we discussed before
maybe we have a defect here on the outer
race we're not going to count them but
again it's going to produce a unique
heartbeat that's different
i guess bringing it into a more complex
machine like a wind turbine we've got
you know a complex array of rotating
components within this system the hub
bearing the gears
the drive shafts for the uh
generator itself an epicycle gearbox
with gears that are traveling around but
each part of that
machine each component produces distinct
unit heartbeats and we can trend and we
can track those heartbeats
and you know assess the health of each
part of that machine
so how does it kind of work well
vibration is kind of a strange thing
people think vibration is going to shake
and everything's going to move quite
dramatically but maybe that's not the
case
if my machine were
out of balance
you know that would cause more uh
emotional force and i would touch the
machine i would feel it's vibrating no
problem obviously i need to quantify
that and measure that
but if i had a bearing problem
that's not actually going to cause the
machine to move and vibrate excessively
it's going to be more localized impacts
shocks
actually due to the bearing that might
be damaged
so that's a different heartbeat inside
maybe the rotor bars they've got a
different heartbeat kind of bring them
all together
you know and it kind of gets a bit
more complicated maybe that's a bit loud
sorry about that
but obviously the heartbeats combined
together we measure these heartbeats
distinctly with our vibration are at key
strategic measurement locations and we
can trend and track
each component within the machine
[Music]
okay
so just a little bit of
theoretical stuff here before we kind of
move forward with some signals and
understand how these heartbeats produce
themselves
and one of the key aspects of the story
with vibration condition monitoring
we're trending and tracking the health
and what's most important obviously is
we measure the amplitude
how good we have all the vibration is or
how large it might be because if our
machine has a problem
the aperture is important but the change
in amplitude is important as well
condition monitoring about looking for
change trend and track the health and
look for change
once that change occurs we can say the
vibration has changed due to what well
that's where we need to understand the
frequency the rate of the heartbeat
you know is it 25 pulses per rotation is
it six pulses per rotation or is it one
pulse per rotation
depending upon what's causing it to
vibrate so the frequency enables enables
us sorry to understand the nature of the
source of what's causing this thing to
vibrate the defect itself is it the
bearing is it the blades is it the
coupling and so forth
and then main understanding how a
machine might move
by understanding the motion would
actually provide us with more diagnostic
information to narrow down the problem
so if we take a look at the basic uh
initial
part of the signal we measure it's the
waveform forgive me
with this simulator here i can just
start this machine up and just bear with
me a moment
i can see that this shaft is being
displaced i've got a clock gauge to
visually show you what normally a
vibration sensor would do we might use a
sensor placed on the body of the bearing
it's measuring the the vibration within
that bearing
and just pop that clock gauge back on
again um so obviously if
my my shaft had a fan on it and there's
a heavy spot it's going to cause it to
vibrate at a frequency of once for
rotation due to the heavy spot
if the hairstyle gets related because
products building up on a fan blade
maybe then obviously what will happen is
the amplitude the level of the vibration
will grow and just be steady there i'm
going to weigh that bearing if i'm not
careful just wind that back a bit um
so we can see that the amplitude of the
signal now is grown due to a heavier
mass on the actual fan
maybe that's that's mounted on that
particular shaft
so that's good if the speed changes
if the speed changes then obviously
behind the signal the waves get closer
together so the speed increases but it
takes less time to do one full rotation
less time
so one thing that's very important about
vibration is that we that we measure and
we correlate speed with the signals and
with statistically that's normally quite
a simple task to do so
um
that's a very important point of speed
measure that we need to understand
so what do all those peaks mean kind of
vibration people look at signals and
heartbeats how do they know
you know what the dominant frequency is
where is it coming from within the
machine
in
reality due to the complexity of the
fact i've got electrical vibrations i've
got process vibrations maybe here from
the air going through the ventilation
system i've got mechanical vibrations
inherently in the machine
the waveform is very complicated and
difficult to maybe relate to
but thankfully
there is a way to simplify this to make
what is a complex signal a much more
simplified signal
mathematically it's a very involved
process but thankfully due to uh
technology today
it's actually not that difficult in a
graphical way
and indeed for the analysts to very
quickly interpret the results so here's
my wave
here's the wave if i increase the speed
there just to make it a little bit more
destroying so we're going to speed up
the speed that fan
this wave the right one
of the signal represents one rotation of
the shaft
okay
so obviously as the imbalance grows at a
fixed speed now the speed is now fixed
the imbalance grows or it weakens
because
the shape of the wave
will go all the way
balance
so what do we do well
you know as you saw just now that
waveform is very complex well let's make
it easier
let's ask you this question here's the
wave i'm looking now at that signal i'm
looking 90 degrees at that signal what
do i see the end of the wave
a line a peak
so in simple terms
vibration systems today take the signal
initially like this which is currently
very simple
and they they convert it to a frequency
spectrum by initially i turn that 45
degrees
and then complete the 90 degree rotation
what do we see one single peak what do i
see looking at 90 degrees i see the
weight
so we take the time wave and we convert
it to a frequency
very crisp very sharp way of
presenting the data
this peak here would be
proportional to rotation speed let's
kind of switch it back again
and maybe the bearing here the defect
okay so the bearing's got a
hitted
spawn point on the bearing and in one
rotation there'll be a certain number of
pulsation forces every time a ball
strikes the bearing
count the number of poles is there if
you wish to
higher or lower frequency
higher frequency yeah so the green wave
is the heartbeat of the bearing
let's bring that together just click on
there sorry about that
there we go let's put it 45 degrees what
do we see
two separate peaks one proportional to
rotational speed
the unbalance in the fan and one that
shouldn't be there because there
shouldn't be a problem with the bearing
but it's appeared at i don't know 6.1
times the speed not six not seven but
6.1 times the speed for example
so that's a key difference for the
bearing it's actually not a whole number
so these peaks you know we can we can
separate them from a very complex wave
and trend them discreetly to know what's
wrong
with the machine it was vibrating too
much
so with knowledge
we could look at problems with spectra
and you know this might be a normal
reading there's hardly any other peaks
in the spectrum quite a low level
running speed peak which is very
normal to see at low amplitude happy
days
a heavy mass sticks to the fan up
frequency will grow the amplitude will
grow and we'll know exactly what's
causing our software we click on the pig
and we're told it's once times the
speed we'll see in a moment maybe if two
shafts are not aligned so two shaft
motor pump should be perfectly aligned
but maybe one is shimmed higher than the
other now think about the forces think
about the motion as it rotates one
rotation
one pulse
two pulses
one pulse two pulses so two puppets turn
two postures per rotation producing a
very distinctive characteristic second
peak an imbalance would not underline do
that
it's completely different
so different
parts different defects different
properties show a distinct difference
in the appearance
in the frequency spectrum in the
heartbeat of the machine here there's
obviously several peaks
if we have a problem with a bearing
for example this
this data here is showing me a small 1x
peak that's normal but these bearing
peaks should not be there end off
sadly it's a vibration reading they're
present the damage is done this peak
here is at 3.1 pulses per rotation if i
click on that in my software it would
tell me it's occurring at 3.1 times the
speed
it's three blade it would be a three
times the speed if the blades were
problematic but here it's 3.1
so that's indicating maybe a bearing
okay so the spectrum itself um
what's nice you know one single peak
maybe easier you know i can look at that
i can see one p
the reality is
machines don't produce just few pure
smooth vibrational forces some of them
can be shocked we've spoken about those
some of them might be uh you know
pushing and pulling forces against each
other with two shafts that are fighting
each other so that's going to cause the
data
to distinctly change and there's other
techniques which i'm sorry to say we
don't have time to cover today but you
know there's other supplementary
techniques that do support the analyst
in diagnosing problems
so where the vibration is smooth in
summary what do we see
you know heavy mass rotating around the
rotor you know a strong radial force an
increase in vibration at what frequency
once times the speed
so an imbalance in the system will
actually occur at once times the speed
little else present
that's the main problem
other peaks might mean there's a second
problem
the vibration's going to change it
behavior it's not such a smooth force
you've got two shafts fighting one
another
that'd be bolted down but think about
the stress
of the exhibits on that sheet
so that's going to change the shape of
the spectrum the frequency spectrum
where we see maybe more than just one
peak here we've seen three particular
peaks due to uh
non-linearity's distortion of of the
wave so being nice and smooth it's
distorted that fighting force is causing
that distortion
here with shock i know i always take
that scenario take a slow and throw it
into a pond you kind of get the impact
of the stone and then you get the echo
the ripple
here
shop might be quite small intent shops
here it's maybe quite visually
exaggerated but that will change the
shape of the reading we see the spectrum
the frequency part b
could come from bearings
shock could come from loose
shaft on the bearing so it's working
loose on the shaft that would cause
shock as well
that produces stiffly something uniquely
different
characteristics that we call harmonics
lots of them here we've got seven
typically we see actually a lot more
where something might be loose
harmonics like the echo kind of
scenario are equally spaced peaks
that appear in the spectrum equally
spaced piece so that's you know
distinctly different to what you saw
just now with a smooth vibration where
there was only one single dominant peak
one other factor maybe one step too much
here but let's just scratch the surface
um uh another characteristic in the
reading called sidebands
what's the difference well look at these
gears look at how the teeth that one
part of the rotation come right into the
roof of the teeth then the gap opens
so that means the vibration once the rev
goes strong
goes weak
goes strong
goes weak as it comes deeper into the
root the amplitude that wave and the
signal being produced very strong and
where it separates because there's not
so much force
the strength is
these are equally spaced peaks
either side of central peak
so here we have several peaks equally
spaced either side of the center
frequency
so they are spaced by a a delta a
difference in frequency that's known
and they're equally spaced and they're
common
on bearing problems
gear problems
looseness
bearings and gears maybe electrical
problems might be another one as well
where we see that distinct
behavior and again there's some more
side bends
maybe if the defect here think about
this the defect that red dot is inside
the bearing there's a pitted damage spot
when the defect enters the lower part of
the bearing due to gravity the forces
are greater so we get a stronger seat
look then as the debate
out of the load zone towards the top
as we said just a second ago a distinct
pattern suffers but we've got shock as
well
so what do we see shock results in
harmonics equally spaced peaks the
larger ones there in yellow
and side bands where we see equally
spaced peaks around those harmonics
maybe that's one step too far for those
of you that maybe are newer to the
subject but distinctly different
pictures to simplify
okay um
we've got some examples here some case
studies i think i have time to uh
maybe choose there's
probably too many to go through them all
but so i'm just going to go to this
particular one here
so
this is a hammer mill bearing um
on a particular bearing on a motor
there's the actual drive itself so this
mill
crushes or mashes wheat in preparation
for bi-ethanol
fuel reducing process
variable speed motor so it varies in
speed during operation
and monthly vibration measurements were
collected when the plant first started
up in 2010 and continued to monitor this
machine up to present day
on a monthly basis now this trend is a
trend actually of the shock within the
machine the impact force you know the
shocks that might be produced from a bad
bearing well this is the strength of the
shocks where at the baseline the first
measurement taken here which may not
always be the baseline actually
doesn't always mean it's good because
it's the first reading but it's 5g well
that's kind of quite reasonable it's a
p2p
measurement of the shock of
the signal up to 70 g's you can see the
degradation there is up to 70 g's
and then you can see after
repair that the level's returned to
normal afterwards
what's this well this is the frequency
heartbeat
of a particular point on the machine
the motor drive end or motor inboard
bearing here so this is the bearing at
the motor driving and you can see the
heartbeat month on month here
the most recent reading back when the
problem was present being at the back
how the heartbeat has changed
the heartbeat has changed if this was a
problem with balance for example that
was lower down the scale my 1x peak is
this kind of very small peak down here
not of concern but these stronger peaks
here are
you know the main cause
why that trend caused that kind of
degradation
so here we can see the actual uh singles
spectrum the heartbeat the frequency
spectrum from that particular point
and in this case we can clearly see due
to the purple dots there harmonics are
evident within that particular fft sorry
the spectrum itself the frequency
spectrum
equally space peaks clearly evident the
point is
what is the rate of those peaks what is
the spacing between it well the driving
frequency the first one
is at 3.05 times the speed so let's
spread it out to 3.1 times the speed not
three but 3.1 shots per rotation
this particular case the bearing was
known
the bearing was home
we knew it was a six three two two
bearing
and in that case that correlated with
these dotted lines
that match the outer race frequency of
the bearing so we knew exactly that it
was the outer race of the bearing
okay some might think we don't have a
bearing number in all cases not a
problem what else could cause 3.1 shocks
per rotation on a pump motor assembly or
sorry a grinder here and a motor
apart from transmitted vibration
somewhere else perhaps which it wasn't
because it was only present at the motor
electrical vibration
could cause a
strange number here but it wasn't that
it had to be
so we would have known anyway
so there's the actual bearing that was
um taken out it's a very distinct wear
pattern in this bearing as well which
provides the analysts with recorded
information because it's not just about
detecting the problem really conditional
monitoring only trends and tracks of
defect
to improve the actual conditions improve
the reliability we need to ask why what
caused it and what action we're going to
take rather than just say put a new
bearing in
what's caused it let's put that to bed
as well as obviously install a new
bearing
and i think since that time
after replacing them that's continued to
trend
quite happily to present day
so let's check the time yet so i've got
uh maybe more time for one more
um slight different twist of the tail
here actually um
this
problem um
is maybe not quite as common on general
plant but on certainly larger drives it
has a place where it could occur this is
more maybe common for a larger drive
not small sort of 1.5 kilowatts but
large machines
this is a motor driving uh centrifugal
fan it's a gas recycle fan you've got
your motor obviously with your two
plumber block cooper bearings here and
then your coupling is just under this
guard here
so again this machine i believe has been
trended periodically since 1999
on a monthly basis when the client runs
during their operational
a little season there about the machine
315 kilowatts 1500 rpm less slip
so my general vibration trend according
to an iso standard actually was well
within a tolerance
but because
it's important not just to trend
the general level of vibration perhaps
different parts of the vibration either
different heartbeats you can trend them
independently
this particular trend segment here
obviously violated an alarm
drilling down slightly deeper into the
data you can see the degradation this is
one particular point again this is on
the motor non-drive end so this
particular measurement was taken at an
android
the most recently
reading taken at the time this was a
problem is at the back and you can see
the visual picture there has changed
uh where you see obviously more activity
at the back harmonics
so there they are in a bit more detail
zoomed in there if you like and just
taking that one spectrum out
but
upon further investigation
we took a higher resolution measurement
like on your digital camera you take
more pixels if we take more lines we get
clearer sharper crisper peaks
and it revealed actually that we had
harmonics
equally spaced peaks
and
equally spaced peaks either side of the
central peak so we had harmonics and we
had cybex
which fits with what we discussed before
we had both
and you can see here this is the signal
in raw form very complicated very
difficult to relate to but the picture
is it goes strong it goes weak it goes
strong it goes weak the amplitude's
changing that's why they're sideways
the harmonics are there due to
distortion
zoomed in a bit more around those main
peaks there
and understanding the spacing of the
sidebands was the final part of the
jigsaw so the spacing between the
central peak and the peaks basically
equally
the difference the delta frequency was
the key
the spacing was 42 cycles per minute or
0.7 hertz
and then with some known mathematics
that to be focused where today deals
with this for you anyway but
mathematically this tied down
to a rotor bar problem
not a bearing problem
not a balance problem not relying on the
problem but a rotor bar problem
and thankfully the frustration can be we
don't always get the feedback but we got
feedback on this from the actual company
they they took it on board they planned
the repair centered away to the remote
repair shop and that is the damage
of the broken bar
that caused that distinct particular
harpy we knew it wasn't the bearings we
knew it wasn't the fan we knew it wasn't
the cutting it was down in this case
it's the actual rotor bars
okay so just some uh just getting on my
time there just
give me a skip to the end of that the
other time for another one
so
in summary
vibration is a useful tool on generally
rotating equipment
it's fair to say supplemented maybe by
high frequency methods it has
a wide variety of different defects on
rotating plant
and understanding the actual signals the
heartbeat is the key to understanding
what's causing the problem
and then judgments can be made as to
when you're going to do your corrective
action
so happy days i can't believe i've kept
that within the 30 minutes to be honest
but
it's gone so quickly but
for myself personally that's a thank you
but i welcome any questions
تصفح المزيد من مقاطع الفيديو ذات الصلة
Vibration Analysis for beginners 5 (Rules for evaluating machine vibration, Signal path from sensor)
How to become an expert in Vibration Analysis
Electric motors faults, analysis and predictive maintenance 1.
Psychology of Computing: Crash Course Computer Science #38
Natural Language Processing: Crash Course Computer Science #36
On-Site Balancing Guide (balancing preparation, procedure, advices)
5.0 / 5 (0 votes)