CN101685042B - On-line monitoring method of cold rolled heating furnace roller running state - Google Patents
On-line monitoring method of cold rolled heating furnace roller running state Download PDFInfo
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- CN101685042B CN101685042B CN2008102004694A CN200810200469A CN101685042B CN 101685042 B CN101685042 B CN 101685042B CN 2008102004694 A CN2008102004694 A CN 2008102004694A CN 200810200469 A CN200810200469 A CN 200810200469A CN 101685042 B CN101685042 B CN 101685042B
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Abstract
The invention discloses an on-line monitoring method of cold rolled heating furnace roller running state. The method comprises the following steps: using a vibration sensor to collect vibration signal of the furnace roller and bearing, performing signal reconstruction to the vibration signal to obtain a vibration characteristic signal of the furnace roller and bearing, wherein the characteristic signal comprises the vibration frequency spectrum of each part of the bearing and the rotary frequency of the furnace roller in every frequency multiplication; calculating failure factor of each part of the bearing to compare with a set value and judge bearing failure; calculating total vibration value of the furnace roller, comparing the value with vibration amplitude values of the rotary frequency of the furnace roller in 1 and 2 frequency multiplication to judge whether the furnace roller is abnormal; building vibration waveform aggregate to the original vibration signal to obtain the fractal dimension of furnace roller vibration, obtaining the conclusion that the furnace roller is abnormal when the fractal dimension changes violently; and finally judging whether the furnace roller surface is over abrasion by comparing the basic furnace roller vibration amplitude value with the on-line furnace roller total vibration value.
Description
Technical field
The present invention relates to a kind of on-line monitoring method of cold rolled heating furnace roller running state.
Background technology
Cold rolled heating furnace roller is one of major equipment of rolling mill production line.Heating furnace roller rises sheet billet in the stove and supports and transmitting effect, in case furnace roller breaks down, possibly cause the thin sheet surface scuffing even broken belt occur and the heap steel, causes the production line cancel closedown.
The failure mode of cold rolled heating furnace roller shows as: bearing fault, furnace roller flexural downwarping, local bulge, inner and outer ring cracking, excessive abrasion, the anti-material in furnace roller surface come off and inner chamber scaling etc.These fault in-situs for furnace roller generally adopt the mode that ear is listened, hand is touched; Minority adopts simple instrument to test; Adopt said method can't accurately monitor the running status of furnace roller; So the basic mode that adopts periodic maintenance and correction maintenance, eliminate the defective of furnace roller through the mode of periodic maintenance and correction maintenance, with the normal operation of assurance equipment.
Summary of the invention
Technical matters to be solved by this invention provides a kind of on-line monitoring method of cold rolled heating furnace roller running state; Utilize this method can monitor the running status of furnace roller and bearing in real time; In time find furnace roller and the operating all kinds of defectives of bearing, guaranteed the normal operation of equipment and the quality of producing product.
For solving the problems of the technologies described above, the on-line monitoring method of cold rolled heating furnace roller running state of the present invention comprises furnace roller, rolling bearing and is arranged at the vibration transducer that is used to export furnace roller and bearing vibration signal on the bearing seat that said method comprises the steps:
Step 1, the said vibration transducer output of collection signal Yi are to this original signal Y
iDo spectrum analysis, and make signal reconstruction, extract the characteristic signal of furnace roller and bearing through Hilbert;
Step 2, said bearing fault show that unusual vibration level value has impact, and the impact speed of said each parts of bearing and the relation of rumble spectrum do
Bearing outer ring rumble spectrum: f
O=nf
r(1-dcos α/D)/2 (1)
Bearing inner race rumble spectrum: f
i=nf
r(1+dcos α/D)/2 (2)
Bearing roller rumble spectrum: f
p=f
r(D/d) { 1-[d (cos α)/D]
2}/2 (3)
Retainer rumble spectrum: f
h={ f
i[1-d (cos α)/D] ± f
o[1+d (cos α)/D] }/2 (4)
In the formula: n is rolling body number, f
rFor bearing inner race, outer ring relative rotation speed frequency, d are that rolling body diameter, D are that pitch diameter, α are contact angle;
Step 3, the setting bearing fault factor, bearing inner race fault factor B
1, bearing outer ring fault factor B
2, bearing roller fault factor B
3, retainer fault factor B
4, then the relation between each unit failure factor of bearing and rumble spectrum is:
B
1＝(A
fi+1/A
fi+U
fi+1/U
fi)/4 (5)
B
2＝(A
fo+1/A
fo+U
fo+1/U
fo)/4 (6)
B
3(A
fp+1/A
fp+U
fp+1/U
fp)/4 (7)
B
4＝(A
fh+1/A
fh+U
fh+1/U
fh)/4 (8)
A in the formula
Fi, U
FiBe respectively bearing inner race rumble spectrum f
iThe vibration amplitude and the f at place
iAt the weighted mean of positive and negative 20% scope internal vibration value, A
Fo, U
F0Be respectively bearing outer ring rumble spectrum f
oThe vibration amplitude and the f at place
oAt the weighted mean of positive and negative 20% scope internal vibration value, A
Fp, U
FpBe bearing roller rumble spectrum f
pThe vibration amplitude and the f at place
pAt the weighted mean of positive and negative 20% scope internal vibration value, A
Fh, U
FhBe retainer rumble spectrum f
hThe vibration amplitude and the f at place
hWeighted mean in positive and negative 20% scope internal vibration value;
The alarming value of step 4, setting bearing inner race, outer ring, rolling body and the retainer fault factor is respectively B
S1, B
S2, B
S3And B
S4, monitoring step three centre bearer fault factor B
1, B
2, B
3And B
4, work as B
1, B
2, B
3And B
4Respectively greater than B
S1, B
S2, B
S3And B
S4The time, on-line monitoring system forecast bearing is unusual;
Step 5, for the original vibration signal Yi of the vibration transducer of gathering through step 1; This Yi is obtained the vibration amplitude component Xi (t) at furnace roller 1 frequency multiplication rotational frequency, 2 frequency multiplication rotational frequencies, 3 frequency multiplication rotational frequencies and 4 frequency multiplication rotational frequency places respectively through vibration frequency specturm analysis FFT conversion; I gets 1,2,3 and 4, and then furnace roller body global vibration value does
Monitor the ratio of X1 (t) and X2 (t) and Ψ (t) respectively, when this ratio greater than 30% the time, on-line monitoring system forecast furnace roller is unusual;
Step 6, for the original vibration signal Y of the vibration transducer of gathering through step 1
i, obtain state vector Y, make up vibrational waveform set A={ a}a=(X
i, Y
i), i=1,2 ..., N;
X wherein
iBe the sampling time, Y
iBe vibration amplitude, N is that sampled data is counted,
Calculate mean value Ave (Y) and the peak-to-peak value PP (Y) of Y, make Topological Mapping A → M, M={m|m=(X
i *, Y
i *), i=1,2 ..., N} is the subclass on unit plane, and A is a vibration signal discrete sampling time series, and M is through the corresponding numerical value after the signal Processing,
X
i *＝X
i/X
N Y
i *＝(Y
i-Ave(Y))/PP(Y)
X in the formula
NRespective value for vibration signal discrete sampling last point
Ave (Y) is vibration sampled data Y
iAverage, Ave (Y)=(Y
1+ Y
2+ ... + Y
i)/N
PP (Y) is vibration sampled data Y
iPeak-to-peak value, PP (Y)=max (Y
i)-min (Y
i)
Adopt the variation of the fractal dimension dw measurement vibrational waveform M of time domain waveform, the length fractal dimension is to the nonlinear vibration waveform with preceding tropism, and the length fractal dimension is for to cover as hypercube one dimension length line segment to vibrational waveform; Among the set M, establishing vibrational waveform length is L, and waveform sampling is counted and is N; The hypercube length of side is ε; Then the capping unit number is L/ ε, gets ε=1/U, U=N-1;
dw＝1+lnL/lnU (10)
Wherein U is that waveform sampling is counted and subtracted 1, adopts above-mentioned formula can calculate the fractal dimension dw of waveform, when acute variation takes place dw, when big hour, thinks that great changes have taken place the time domain waveform of vibration signal in the time of promptly should value, judges that the furnace roller state is unusual;
Step 7, vibration initial testing data or similar furnace roller vibration amplitude C when obtaining the furnace roller replacing
0, being worth with this is benchmark, and with the furnace roller global vibration value Ψ (t) of step 5 gained relatively, establishing furnace roller surface excessive abrasion coefficient is W
W=Ψ (t)/Co (11) then
As w>180% the time, on-line monitoring system forecast furnace roller surface excessive abrasion.
Because the on-line monitoring method of cold rolled heating furnace roller running state of the present invention has adopted technique scheme, promptly utilize vibration transducer to detect the vibration signal of furnace roller and rolling bearing, through Hilbert and FFT this vibration signal is made signal reconstruction to obtain the characteristic signal of furnace roller and bear vibration; Comprise the rumble spectrum of each parts of bearing and the rotational frequency of each frequency multiplication of furnace roller; The fault factor of each parts of calculation bearing and with setting value relatively, judge bearing fault with this, calculate furnace roller the global vibration value and with the vibration amplitude component of furnace roller 1 frequency multiplication and 2 frequency multiplication place rotational frequencies relatively; Judge that with this furnace roller is unusual; Through the original vibration signal of gathering, make up the vibrational waveform set, obtain the fractal dimension of furnace roller vibration; When fractal dimension generation acute variation; The unusual conclusion of rod of must coming out of the stove through the stove rod vibration amplitude of benchmark and comparison in line oven rod global vibration value, is judged whether excessive abrasion of stove rod surface; Utilize this method can monitor the running status of furnace roller and bearing in real time, in time find the operating all kinds of defectives of furnace roller and bearing, guaranteed the normal operation of equipment and the quality of producing product.
Description of drawings
The present invention is described in further detail below in conjunction with accompanying drawing and embodiment:
Fig. 1 is the block diagram of cold rolled heating furnace roller running state on-line monitoring method of the present invention.
Embodiment
Core of the present invention has been to propose a kind of method of on-line monitoring roller running state; Through gathering furnace roller and bearing vibration parameter; Characteristic parameter through signal reconstruction acquisition furnace roller state adopts classification indicators to keep watch on the degradation trend of furnace roller and bearing running status, and guiding operation and equipment management personnel are taked counter-measure; Avoid the equipment non-programmed halt that causes because of bearing and furnace roller body fault, support the ordinary production of rolling mill production line.
The failure mode of furnace roller mainly shows as bearing fault, furnace roller flexural downwarping, local bulge, inner and outer ring cracking, excessive abrasion, the anti-material in furnace roller surface comes off and the inner chamber scaling;
Bearing fault shows as usually has impact when unusual vibration level value, each is decreased impact speed and bearing between parameters of operating part and is had certain relation;
Come off and failure mode such as inner chamber scaling to furnace roller flexural downwarping, local bulge, the anti-material in furnace roller surface, can be classified as uneven category in fault diagnosis field.Imbalance is that the center of gravity of stove rod is not on its geometric centre axes; Just receive certain centrifugal force when the stove rod rotates like this, because action of centrifugal force, the stove rod is except rotation; Can be radius also with certain eccentric throw; With the geometric center is the garden heart, does the revolution swing, the energy imbalance of Here it is stove rod.Unbalance vibration has following characteristic: its vibration frequency is consistent with rotating speed, and promptly outstanding corresponding to the vibration amplitude composition under the speed-frequency on the rumble spectrum figure, direction of vibration is for radially, and the vibration phase characteristics are diaxon bearing same-phases.
Furnace roller inner and outer ring cracking is that effect causes because furnace roller outside surface heat-barrier material and furnace roller inner chamber circulation fail to bring into normal play, and its vibration signal is characterized by the time-domain signal instability, little phenomenon when big when vibration values occurs.
Excessive abrasion is meant the furnace roller anti-material excessive wear in surface, if irregular wear, it is inhomogeneous that quality appears in the furnace roller body, and vibration signal shows similar rotor unbalance characteristic.If uniform wear, the uneven characteristic of furnace roller body vibration signal is not obvious, but vibration reference data or the similar furnace roller vibration values of its global vibration value can change with furnace roller the time occurs than big-difference.
The on-line monitoring method of cold rolled heating furnace roller running state of the present invention comprises furnace roller, rolling bearing and is arranged at the vibration transducer that is used to export furnace roller and bearing vibration signal on the bearing seat that as shown in Figure 1, said method comprises the steps:
Step 1, the said vibration transducer output of collection signal Yi are to this original signal Y
iDo spectrum analysis, and make signal reconstruction, extract the characteristic signal of furnace roller and bearing through Hilbert;
Step 2, said bearing fault show that unusual vibration level value has impact, and the impact speed of said each parts of bearing and the relation of rumble spectrum do
Bearing outer ring rumble spectrum: f
0=nf
r(1-dcos α/D)/2 (1)
Bearing inner race rumble spectrum: f
i=nf
r(1+dcos α/D)/2 (2)
Bearing roller rumble spectrum: f
p=f
r(D/d) { 1-[d (cos)/D]
2}/2 (3)
Retainer rumble spectrum: f
h={ f
i[1-d (cos)/D] ± f
o[1+d (cosa)/D] }/2 (4)
In the formula: n is rolling body number, f
rFor bearing inner race, outer ring relative rotation speed frequency, d are that rolling body diameter, D are that pitch diameter, α are contact angle;
In step 3, the rolling bearing, early stage fault because the impact signal energy is low, usually be submerged in the ground unrest, field measurement fault-signal research shows; From vibration envelope spectrogram; Can see the failure-frequency of bearing outer ring, but except the failure-frequency of bearing, same much other failure-frequencies that exist; The highest spectral line is not the bearing fault frequency, and can not draw bearing problem is the conclusion of main vibration source; Therefore, adopt bearing characteristic frequency amplitude tracking method to confirm the bearing fault factor, realize the in-service monitoring of bearing fault; The frequency band of choosing each component feature frequency of bearing carries out computing as monitoring target with the vibration peak at characteristic frequency place and the frequency spectrum weighted value in the selected frequency band;
Set the bearing fault factor, bearing inner race fault factor B
1, bearing outer ring fault factor B
2, bearing roller fault factor B
3, retainer fault factor B
4, then the relation between each unit failure factor of bearing and rumble spectrum is:
B
1＝(A
fi+1/A
fi+U
fi+1/U
fi)/4 (5)
B
2＝(A
fo+1/A
fo+U
fo+1/U
fo)/4 (6)
B
3＝(A
fp+1/A
fp+U
fp+1/U
fp)/4 (7)
B
4＝(A
fh+1/A
fh+U
fh+1/U
fh)/4 (8)
A in the formula
Fi, U
FiBe respectively bearing inner race rumble spectrum f
iThe vibration amplitude and the f at place
iAt the weighted mean of positive and negative 20% scope internal vibration value, A
Fo, U
F0Be respectively bearing outer ring rumble spectrum f
oThe vibration amplitude and the f at place
oAt the weighted mean of positive and negative 20% scope internal vibration value, A
Fp, U
FpBe bearing roller rumble spectrum f
pThe vibration amplitude and the f at place
pAt the weighted mean of positive and negative 20% scope internal vibration value, A
Fh, U
FhBe retainer rumble spectrum f
hThe vibration amplitude and the f at place
hWeighted mean in positive and negative 20% scope internal vibration value;
The alarming value of step 4, setting bearing inner race, outer ring, rolling body and the retainer fault factor is respectively B
S1, B
S2, B
S3And B
S4, monitoring step three centre bearer fault factor B
1, B
2, B
3And B
4, work as B
1, B
2, B
3And B
4Respectively greater than B
S1, B
S2, B
S3And B
S4The time, on-line monitoring system forecast bearing is unusual;
Step 5, the unbalanced monitoring of stove rod body; Original vibration signal Yi for the vibration transducer of gathering through step 1; This Yi is obtained the vibration amplitude component Xi (t) at furnace roller 1 frequency multiplication rotational frequency, 2 frequency multiplication rotational frequencies, 3 frequency multiplication rotational frequencies and 4 frequency multiplication rotational frequency places respectively through vibration frequency specturm analysis FFT conversion; I gets 1,2,3 and 4, and then furnace roller body global vibration value does
Monitor the ratio of X1 (t) and X2 (t) and Ψ (t) respectively, when this ratio greater than 30% the time, on-line monitoring system forecast furnace roller balance is unusual;
The monitoring of step 6, stove rod inner and outer ring cracking is for the original vibration signal Y of the vibration transducer of gathering through step 1
i, obtain state vector Y, make up the vibrational waveform set
A＝{a}a＝(X
i，Y
i)，i＝1，2，……，N；
X wherein
iBe the sampling time, Y
iBe vibration amplitude, N is that sampled data is counted,
Calculate mean value Ave (Y) and the peak-to-peak value PP (Y) of Y, make Topological Mapping A → M, M={m|m=(X
i *, Y
i *), i=1,2 ..., N} is the subclass on unit plane, and A is a vibration signal discrete sampling time series, and M is through the corresponding numerical value after the signal Processing,
X
i *＝X
i/X
N Y
i *＝(Y
i-Ave(Y))/PP(Y)
X in the formula
NRespective value for vibration signal discrete sampling last point
Ave (Y) is vibration sampled data Y
iAverage, Ave (Y)=(Y
1+ Y
2+ ... + Y
i)/N
PP (Y) is vibration sampled data Y
iPeak-to-peak value, PP (Y)=max (Y
i)-min (Y
i)
Adopt the variation of the fractal dimension dw measurement vibrational waveform M of time domain waveform, the length fractal dimension is to the nonlinear vibration waveform with preceding tropism, and the length fractal dimension is for to cover as hypercube one dimension length line segment to vibrational waveform; Among the set M, establishing vibrational waveform length is L, and waveform sampling is counted and is N; The hypercube length of side is ε; Then the capping unit number is L/, gets ε=1/U, U=N-1;
dw＝1+lnL/lnU (10)
Wherein U is that waveform sampling is counted and subtracted 1, adopts above-mentioned formula can calculate the fractal dimension dw of waveform, when acute variation takes place dw, when big hour, thinks that great changes have taken place the time domain waveform of vibration signal in the time of promptly should value, judges that the furnace roller state is unusual;
The monitoring of step 7, stove rod excessive abrasion, vibration initial testing data or similar furnace roller vibration amplitude C when obtaining the furnace roller replacing
0, being worth with this is benchmark, and with the furnace roller global vibration value Ψ (t) of step 5 gained relatively, establishing furnace roller surface excessive abrasion coefficient is W
W=Ψ (t)/Co (11) then
As w>180% the time, on-line monitoring system forecast furnace roller surface excessive abrasion.
The on-line monitoring method of cold rolled heating furnace roller running state of the present invention utilizes vibration transducer to detect the vibration signal of furnace roller and rolling bearing; Through Hilbert and FFT this vibration signal is made signal reconstruction to obtain the characteristic signal of furnace roller and bear vibration, comprises the rumble spectrum of each parts of bearing and the rotational frequency of each frequency multiplication of furnace roller, the fault factor of each parts of calculation bearing and with setting value relatively; Judge bearing fault with this; Calculate furnace roller the global vibration value and with the vibration amplitude component of furnace roller 1 frequency multiplication and 2 frequency multiplication place rotational frequencies relatively, judge that with this furnace roller is unusual, through the original vibration signal of gathering; The set of structure vibrational waveform; Obtain the fractal dimension of furnace roller vibration, when fractal dimension generation acute variation, the unusual conclusion of rod of must coming out of the stove; Stove rod vibration amplitude through benchmark and comparison in line oven rod global vibration value are judged whether excessive abrasion of stove rod surface; Utilize this method can monitor the running status of furnace roller and bearing in real time, in time find the operating all kinds of defectives of furnace roller and bearing, guaranteed the normal operation of equipment and the quality of producing product.
Claims (1)
1. the on-line monitoring method of a cold rolled heating furnace roller running state comprises furnace roller, rolling bearing and is arranged at the vibration transducer that is used to export furnace roller and bearing vibration signal on the bearing seat, it is characterized in that said method comprises the steps:
Step 1, the said vibration transducer output of collection signal Yi are to this original signal Y
iDo spectrum analysis, and make signal reconstruction, extract the characteristic signal of furnace roller and bearing through Hilbert;
Step 2, said bearing fault show that unusual vibration level value has impact, and the impact speed of said each parts of bearing and the relation of rumble spectrum do
Bearing outer ring rumble spectrum: f
0=nf
r(1-dcos α/D)/2 (1)
Bearing inner race rumble spectrum: f
i=nf
r(1+dcos α/D)/2 (2)
Bearing roller rumble spectrum: f
p=f
r(D/d) { 1-[d (cos α)/D]
2}/2 (3)
Retainer rumble spectrum: f
h={ f
i[1-d (cos α)/D] ± f
0[1+d (cos α)/D] }/2 (4)
In the formula: n is rolling body number, f
rFor bearing inner race, outer ring relative rotation speed frequency, d are that rolling body diameter, D are that pitch diameter, α are contact angle;
Step 3, the setting bearing fault factor, bearing inner race fault factor B
1, bearing outer ring fault factor B
2, bearing roller fault factor B
3, retainer fault factor B
4, then the relation between each unit failure factor of bearing and rumble spectrum is:
B
1＝(A
fi+1/A
fi+U
fi+1/U
fi)/4 (5)
B
2＝(A
f0+1/A
f0+U
f0+1/U
f0)/4 (6)
B
3＝(A
fp+1/A
fp+U
fp+1/U
fp)/4 (7)
B
4＝(A
fh+1/A
fh+U
fh+1/U
fh)/4 (8)
A in the formula
Fi, U
FiBe respectively bearing inner race rumble spectrum f
iThe vibration amplitude and the f at place
iAt the weighted mean of positive and negative 20% scope internal vibration value, A
Fo, U
F0Be respectively bearing outer ring rumble spectrum f
oThe vibration amplitude and the f at place
oAt the weighted mean of positive and negative 20% scope internal vibration value, A
Fp, U
FpBe bearing roller rumble spectrum f
pThe vibration amplitude and the f at place
pAt the weighted mean of positive and negative 20% scope internal vibration value, A
Fh, U
FhBe retainer rumble spectrum f
hThe vibration amplitude and the f at place
hWeighted mean in positive and negative 20% scope internal vibration value;
The alarming value of step 4, setting bearing inner race, outer ring, rolling body and the retainer fault factor is respectively B
S1, B
S2, B
S3And B
S4, monitoring step three centre bearer fault factor B
1, B
2, B
3And B
4, work as B
1, B
2, B
3And B
4Respectively greater than B
S1, B
S2, B
S3And B
S4The time, on-line monitoring system forecast bearing is unusual;
Step 5, for the original vibration signal Yi of the vibration transducer of gathering through step 1; This Yi is obtained the vibration amplitude component Xi (t) at furnace roller 1 frequency multiplication rotational frequency, 2 frequency multiplication rotational frequencies, 3 frequency multiplication rotational frequencies and 4 frequency multiplication rotational frequency places respectively through vibration frequency specturm analysis FFT conversion; I gets 1,2,3 and 4, and then furnace roller body global vibration value does
Monitor the ratio of X1 (t) and X2 (t) and Ψ (t) respectively, when this ratio greater than 30% the time, on-line monitoring system forecast furnace roller is unusual;
Step 6, for the original vibration signal Y of the vibration transducer of gathering through step 1
i, obtain state vector Y, make up vibrational waveform set A={ a}a=(X
i, Y
i), i=1,2 ..., N;
X wherein
iBe the sampling time, Y
iBe vibration amplitude, N is that sampled data is counted,
Calculate mean value Ave (Y) and the peak-to-peak value PP (Y) of Y, make Topological Mapping A → M, M={m|m=(X
i *, Y
i *), i=1,2 ..., N} is the subclass on unit plane, and A is a vibration signal discrete sampling time series, and M is through the corresponding numerical value after the signal Processing,
X
i *＝X
i/X
NY
i *＝(Y
i-Ave(Y))/PP(Y)
X in the formula
NRespective value for vibration signal discrete sampling last point
Ave (Y) is vibration sampled data Y
iAverage, Ave (Y)=(Y
1+ Y
2+ ... + Y
i)/N
PP (Y) is vibration sampled data Y
iPeak-to-peak value, PP (Y)=max (Y
i)-min (Y
i)
Adopt the variation of the fractal dimension dw measurement vibrational waveform M of time domain waveform, the length fractal dimension is to the nonlinear vibration waveform with preceding tropism, and the length fractal dimension is for to cover as hypercube one dimension length line segment to vibrational waveform; Among the set M, establishing vibrational waveform length is L, and waveform sampling is counted and is N; The hypercube length of side is ε; Then the capping unit number is L/ ε, gets ε=1/U, U=N-1;
dw＝1+1nL/1nU(10)
Wherein U is that waveform sampling is counted and subtracted 1, adopts above-mentioned formula can calculate the fractal dimension dw of waveform, when acute variation takes place dw, when big hour, thinks that great changes have taken place the time domain waveform of vibration signal in the time of promptly should value, judges that the furnace roller state is unusual;
Step 7, vibration initial testing data or similar furnace roller vibration amplitude C when obtaining the furnace roller replacing
0, being worth with this is benchmark, and with the furnace roller global vibration value Ψ (t) of step 5 gained relatively, establishing furnace roller surface excessive abrasion coefficient is W
W=Ψ (t)/Co (11) then
As w>180% the time, on-line monitoring system forecast furnace roller surface excessive abrasion.
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| CN2008102004694A CN101685042B (en) | 2008-09-25 | 2008-09-25 | On-line monitoring method of cold rolled heating furnace roller running state |
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|---|---|---|---|
| CN2008102004694A CN101685042B (en) | 2008-09-25 | 2008-09-25 | On-line monitoring method of cold rolled heating furnace roller running state |
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| CN101685042B true CN101685042B (en) | 2012-04-04 |
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