CN102441579B - The on-line monitoring method of hot tandem rolling mill running status - Google Patents
The on-line monitoring method of hot tandem rolling mill running status Download PDFInfo
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- CN102441579B CN102441579B CN201010505291.1A CN201010505291A CN102441579B CN 102441579 B CN102441579 B CN 102441579B CN 201010505291 A CN201010505291 A CN 201010505291A CN 102441579 B CN102441579 B CN 102441579B
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Abstract
The present invention relates to hot tandem rolling mill, be specifically related to a kind of state monitoring method of hot tandem rolling mill.An on-line monitoring method for hot tandem rolling mill running status, it also comprises: step one, utilizes vibrating sensor to gather monitoring point signal; Described collection point is located at reductor shaft bearing, motor bearing seat, AGC oil cylinder, memorial archway top; Step 2, gather hot rolling PLC process variable information, the synchronous acquisition of technical process signal and milling train machinery state quantity signal is realized by OPC mode, and the corresponding index of the acquisition of analytical calculation: the signal of rolling bearing, sliding bearing fault-signal, AGC oil cylinder respective synchronization signal, and memorial archway ftractures or dynamic rate signal; Step 3, utilizes the index that step 2 obtains, and when abnormal signal, provides warning message, instructs operation and equipment management personnel to take counter-measure.The present invention adopts classification indicators to monitor the degradation trend of hot tandem rolling mill running status, supports the normal production of production line.
Description
Technical field
The present invention relates to hot tandem rolling mill, be specifically related to a kind of monitoring method of hot tandem rolling mill.
Background technology
Hot rolling line is the important one-tenth manufacturer of smelter, its current mechanical equipment state detects and mainly contains three kinds of forms: the state that the spot check of first plant maintenance and technical staff carry out according to individual experience judges, i.e. so-called routine diagnosis, its two be utilize with equipment introduce the analytical information that provides of equipment on-line condition diagnosing system judge, i.e. inline diagnosis; It three is in conjunction with the information in above-mentioned one and two, after clear and definite problem points, utilizes offline inspection instrument, records apparatus characteristic amount and analyze, be i.e. off-line accurate diagnosis.Three kind equipment condition managings have common foothold, that is exactly " device status data collection and analysis judgment technology ", namely by gathering which apparatus characteristic parameter, when should gather, and what kind of uses analyze and determination methods, realize the target to equipment state accurate assurance.
Due to the work characteristics of the speed change of equipment of hot rolling, variable load, variable working condition, the impact that milling train stings steel and the generation of throwing steel causes vibration equipment data very large, and the equipment state quality of the main driving motor, reductor, AGC oil cylinder, memorial archway etc. of milling train directly has influence on operational efficiency and the product quality of hot rolling line.
In order to monitor the stability of milling train from hot continuous rolling process, milling equipment state, technique, electrical control process variable signal etc. being integrated in on-line system, being convenient to the integrated management of equipment of hot rolling state and anomaly analysis diagnosis.
The state quality that milling train key equipment comprises the motor, milling train speed reduction gear box, AGC oil cylinder (laying respectively at transmission side and the fore side of milling train), mill housing etc. of main transmission directly has influence on rolling stability; these equipment likely cause stopping accident once break down; therefore need to increase online monitoring point to these equipment; monitor its variation tendency vibrated; the fault that may be able to exist equipment when operation trend changes carries out early warning, and can carry out analyzing and diagnosing.
Summary of the invention
The present invention is intended to solve the problem, and provides the on-line monitoring method of hot tandem rolling mill running status.The present invention adopts classification indicators to monitor the degradation trend of hot tandem rolling mill running status, supports the normal production of production line.
An on-line monitoring method for hot tandem rolling mill running status, it comprises:
Step one, utilizes vibrating sensor to gather monitoring point signal; Described collection point is located at reductor shaft bearing, motor bearing seat, AGC oil cylinder, memorial archway top;
Step 2, gathers hot rolling PLC process variable information, is realized the synchronous acquisition of technical process signal and milling train machinery state quantity signal by OPC mode, and the corresponding index of the acquisition of analytical calculation:
The signal of rolling bearing,
Sliding bearing fault-signal,
AGC oil cylinder respective synchronization signal, and
Memorial archway cracking or dynamic rate signal;
Step 3, utilizes the index that step 2 obtains, and when abnormal signal, provides warning message, instructs operation and equipment management personnel to take counter-measure.
The on-line monitoring method of described hot tandem rolling mill running status, in described step 2, the frequency spectrum weighted value in the vibration peak at characteristic frequency place and selected frequency band, using the frequency band near bearing features frequency as monitoring target, is carried out computing by the signal of rolling bearing.If the bearing fault factor is: bearing inner race fault compression B
1, bearing outer ring fault compression B
2, bearing roller fault compression B
3, retainer fault compression B
4:
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)
Wherein A
fi, U
fibe respectively rumble spectrum upper bearing (metal) inner ring f
ithe vibration amplitude at place and the weighted average of selected frequency band internal vibration value.A
fo, U
fObe respectively outer ring characteristic frequency f
othe vibration amplitude at place and the weighted average of selected frequency band internal vibration value; A
fp, U
fpfor rolling element characteristic frequency f on rumble spectrum figure
pthe vibration amplitude at place and the weighted average of selected frequency band internal vibration value; f
ah, U
fhfor rumble spectrum figure holder frequency f
hthe vibration amplitude at place and the weighted average of selected frequency band internal vibration value.
The on-line monitoring method of described hot tandem rolling mill running status, described step 2 sliding bearing fault-signal is the original vibration signal extracting bearing block acquisition, is transformed into through vibration frequency specturm analysis FFT the vibration amplitude component A that rotating speed frequency multiplication is 1-9 frequency multiplication place
i(f), the sliding bearing fault-signal reconstructed after being superposed by inverse, sliding bearing failure coefficient J algorithm is such as formula (9):
i＝1，2，----，9。
The on-line monitoring method of described hot tandem rolling mill running status, the frequency response of oil cylinder adopts frequency spectrum analysis method, if the maximum spectrum peak frequency of frequency spectrum of transmission side (DS side) and fore side (OS side) is respectively f
dSand f
oS, when two side cylinder synchronisms are good, f
dSand f
oSdiffer very little; Work as f
dSand f
oSlevy difference larger time represent AGC cylinder action occur inconsistent, on time-domain signal show two oil cylinder vibrational waveforms cycle difference larger.
AGC oil cylinder response synchronism fault compression U adopts f
oSand f
oSthe vibration amplitude A that place is corresponding
oS, frequency f
dSand f
dSthe vibration amplitude A that place is corresponding
dScalculate by formula (10), evaluate the waveform indicator difference of two AGC oil cylinder frequency spectrums.
U＝abs(A
DS*f
DS-A
OS*f
OS)/(A
OS*f
OS)(10)
Wherein abs (A
dS* f
dS-A
oS* f
oS) represent A
dS* f
dS-A
oS* f
oSresult of calculation take absolute value.
The on-line monitoring method of described hot tandem rolling mill running status, in described step 2, the signal of memorial archway cracking adopts ratio in judgement method, chooses historical vibration amplitude C when vibration basic data when memorial archway puts into operation or rolling same specification variety steel
0as benchmark, the global vibration value that on-line monitoring system detects is C
1
Memorial archway cracking or rigidity failure coefficient W are:
W＝C
1/Co(11)
The on-line monitoring method of described hot tandem rolling mill running status, index and the alert if of described step 3 comprise: the alarming value B of the setting bearing component failure factor
sk(k=1,2,3,4), the bearing fault factor B at each characteristic frequency place
k(k=1,2,3,4), work as B
k> B
sktime, on-line monitoring system forecast bearing is abnormal; Sliding bearing failure coefficient J, as J > 40%, on-line system is reported to the police; AGC oil cylinder response synchronism failure coefficient U, as U > 20%, on-line system is reported to the police; W > 150% alarm is worked as with memorial archway cracking or rigidity fault.
The present invention proposes the on-line monitoring solution of hot continuous rolling Experimental Rolling Mill running status, vibration acceleration sensor is adopted to realize the signals collecting of rolling mill vibration, obtained the characteristic parameter of milling equipment state by signal reconstruction, realize the on-line monitoring of rolling mill body running status;
The hook achieving hot tandem rolling mill state and technique amount PLC joins, and meets equipment state and the corresponding of parameters of technique process and synchronous acquisition, is successfully applied to on-line monitoring system;
Propose the method utilizing classification indicators technology to hold the state degradation trend of hot tandem rolling mill, when monitoring index of classifying is abnormal, on-line system provides warning message, instructs related personnel to take counter-measure.
Accompanying drawing explanation
Below in conjunction with drawings and embodiments, the present invention is described in further detail:
Fig. 1 is that continous hot rolling facility running status line monitor signal of the present invention flows to schematic diagram;
Fig. 2 is hot tandem rolling mill online monitoring data flow diagram of the present invention.
Detailed description of the invention
The present invention proposes the on-line monitoring solution of hot tandem rolling mill running status, vibration acceleration sensor is adopted to realize the vibration signals collecting of the key equipments such as rolling mill reduction gears, motor, AGC oil cylinder and mill housing, the characteristic parameter of milling equipment state is obtained by signal reconstruction, the process data of synchronous acquisition milling train PLC, realizes the on-line monitoring of rolling state simultaneously; Fig. 1 is that the signal of hot tandem rolling mill on-line monitoring flows to schematic diagram.
The signal extraction of rolling bearing and fault monitoring
In rolling bearing, in earlier stage, fault is low due to impact signal energy, is usually submerged in ambient noise.The research of field measurement fault-signal shows, from vibration envelope spectrogram, the failure-frequency of outer race can be seen, but except the failure-frequency of bearing, same existence other failure-frequency a lot, the highest spectral line is not bearing fault frequency, can not lower bearing problem be the conclusion of main vibration source.
Choose frequency band near bearing characteristic frequency as monitoring target, the frequency spectrum weighted value in the vibration peak at characteristic frequency place and selected frequency band is carried out computing.If the bearing fault factor is: bearing inner race fault compression B
1, bearing outer ring fault compression B
2, bearing roller fault compression B
3, retainer fault compression B
4.
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)
Wherein A
fi, U
fibe respectively rumble spectrum upper bearing (metal) inner ring f
ithe vibration amplitude at place and the weighted average of selected frequency band internal vibration value.A
fo, U
fObe respectively outer ring characteristic frequency f
othe vibration amplitude at place and the weighted average of selected frequency band internal vibration value; A
fp, U
fpfor rolling element characteristic frequency f on rumble spectrum figure
pthe vibration amplitude at place and the weighted average of selected frequency band internal vibration value; A
fh, U
fhfor rumble spectrum figure holder frequency f
hthe vibration amplitude at place and the weighted average of selected frequency band internal vibration value.
The alarming value B of the setting bearing component failure factor
sk(k=1,2,3,4), monitor the bearing fault factor B at each characteristic frequency place
k(k=1,2,3,4).Work as B
k> B
sktime, on-line monitoring system forecast bearing is abnormal.
Sliding bearing fault-signal extracts
For the original vibration signal that bearing block obtains, speed-frequency (1 frequency multiplication) is transformed into through vibration frequency specturm analysis FFT, 2 times of speed-frequencies (2 frequency multiplication), the vibration amplitude component A at 3 times of speed-frequencies (3 frequency multiplication) and 4 times of speed-frequencies (4 frequency multiplication), 5 times of speed-frequencies (5 frequency multiplication), 6 times of speed-frequencies (6 frequency multiplication), 7 times of speed-frequencies (7 frequency multiplication), 8 times of speed-frequencies (4 frequency multiplication) and 9 times of speed-frequency (9 frequency multiplication) places
i(f) (i=1,2,----, 9), the sliding bearing fault-signal reconstructed after being superposed by inverse, sliding bearing failure coefficient J algorithm is such as formula (9):
Monitoring sliding bearing failure coefficient J, as J > 40%, on-line system is reported to the police.AGC oil cylinder response synchronism fault
AGC oil cylinder is all furnished with vibrating sensor, and the frequency response analyzing two AGC oil cylinders adopts frequency spectrum analysis method, if the maximum spectrum peak frequency of frequency spectrum of transmission side (DS side) and fore side (OS side) is respectively f
dSand f
oS, when two side cylinder synchronisms are good, f
dSand f
oSdiffer very little; Work as f
dSand f
oSlevy difference larger time represent AGC cylinder action occur inconsistent, on time-domain signal show two oil cylinder vibrational waveforms cycle difference larger.
AGC oil cylinder response synchronism fault compression U adopts f
oSand f
oSthe vibration amplitude A that place is corresponding
oS, frequency f
dSand f
dSthe vibration amplitude A that place is corresponding
dScalculate by formula (10), evaluate the waveform indicator difference of two AGC oil cylinder frequency spectrums.
U＝abs(A
DS*f
DS-A
OS*f
OS)/(A
OS*f
OS)(10)
Wherein abs (A
dS* f
dS-A
oS* f
oS) represent A
dS* f
dS-A
oS* f
oSresult of calculation take absolute value.
Monitoring AGC oil cylinder response synchronism failure coefficient U, as U > 20%, on-line system is reported to the police.
Memorial archway cracking or dynamic rate fault
The monitoring of memorial archway cracking adopts ratio in judgement method, chooses historical vibration amplitude C when vibration basic data when memorial archway puts into operation or rolling same specification variety steel
0as benchmark, the vibration values that on-line monitoring system detects is C
1.
Memorial archway cracking or rigidity failure coefficient W are:
W＝C
1/Co(11)
When W > 150% alarm.
PLC parameters of technique process is monitored
Technical process signal is from basic automatization or PLC, and as speed, electric current, load, roll-force etc., realized the synchronous acquisition of technical process signal and milling train machinery state quantity signal by OPC mode, its data flow diagram as shown in Figure 2.
To rectify a deviation pinch roll velocity feedback and be given as example, the method for such parameter of on-line monitoring is described.
On-line system obtains correction pinch roll speed feedback value and set-point, by calculating feedback and given difference, when difference is greater than a upper limit or is less than a lower limit, can think correction pinch roll velocity anomaly, on-line system alert notices that correction pinch roll velocity deviation transfinites, and should adjust.
Propose the method utilizing classification indicators to monitor hot rolling mill state degradation trend, when classification indicators are abnormal, on-line system provides warning message, instructs operation and equipment management personnel to take counter-measure.
Hot tandem rolling mill on-line monitoring classification indicators are as follows:
● rolling bearing fault monitors index: bearing component failure factor B
k(k=1,2,3,4);
● motor sliding bearing failure coefficient J: the ratio of the vibration amplitude on 5 frequency multiplication to 9 frequency multiplication place vibration signals spectrograph figure of monitoring reconstruction signal and the vibration amplitude on 1 frequency multiplication to 4 frequency multiplication place vibration signals spectrograph figure;
● during AGC oil cylinder response synchronism fault compression U:U > 20%, on-line system is reported to the police;
● historical vibration magnitude references when vibration basic data when memorial archway cracking or dynamic rate failure coefficient W:W and memorial archway put into operation or rolling same specification variety steel compares judgement.
Claims (5)
1. an on-line monitoring method for hot tandem rolling mill running status, is characterized in that, it comprises:
Step one, utilizes vibrating sensor to gather monitoring point signal; Monitoring point is located at reductor shaft bearing, motor bearing seat, AGC oil cylinder and memorial archway top;
Step 2, gathers hot rolling PLC process variable information, is realized the synchronous acquisition of technical process signal and milling train machinery state quantity signal by OPC mode, and the corresponding index of the acquisition of analytical calculation:
The signal of rolling bearing,
Sliding bearing fault-signal, described sliding bearing fault-signal is the original vibration signal extracting bearing block acquisition, is transformed into through vibration frequency specturm analysis FFT the vibration amplitude component A that rotating speed frequency multiplication is 1-9 frequency multiplication place
i(f), the sliding bearing fault-signal reconstructed after being superposed by inverse, sliding bearing failure coefficient J algorithm is such as formula (9):
i＝1，2，----，9；
AGC oil cylinder respective synchronization signal, and
Memorial archway cracking or dynamic rate signal;
Step 3, utilizes the index that step 2 obtains, and when abnormal signal, provides warning message, instructs operation and equipment management personnel to take counter-measure.
2. the on-line monitoring method of hot tandem rolling mill running status according to claim 1, it is characterized in that, in described step 2, frequency spectrum weighted value in the vibration peak at characteristic frequency place and selected frequency band, using the frequency band near bearing features frequency as monitoring target, is carried out computing by the signal of rolling bearing; If the bearing fault factor is: bearing inner race fault compression B
1, bearing outer ring fault compression B
2, bearing roller fault compression B
3, retainer fault compression B
4:
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)
Wherein A
fi, U
fibe respectively rumble spectrum upper bearing (metal) inner ring f
ithe vibration amplitude at place and the weighted average of selected frequency band internal vibration value; A
fo, U
f0be respectively outer ring characteristic frequency f
othe vibration amplitude at place and the weighted average of selected frequency band internal vibration value; A
fp, U
fpbe respectively rolling element characteristic frequency f on rumble spectrum figure
pthe vibration amplitude at place and the weighted average of selected frequency band internal vibration value; A
fh, U
fhbe respectively rumble spectrum figure holder frequency f
hthe vibration amplitude at place and the weighted average of selected frequency band internal vibration value.
3. the on-line monitoring method of hot tandem rolling mill running status according to claim 1, is characterized in that, the frequency response of AGC oil cylinder adopts frequency spectrum analysis method, if the maximum spectrum peak frequency of the frequency spectrum of transmission side and fore side is respectively f
dSand f
oS, when both sides AGC oil cylinder synchronism is good, f
dSand f
oSdiffer very little; Work as f
dSand f
oSlevy difference larger time represent AGC cylinder action occur inconsistent, on time-domain signal show two AGC oil cylinder vibrational waveforms cycle difference larger;
AGC oil cylinder response synchronism fault compression U adopts f
oSand f
oSthe vibration amplitude A that place is corresponding
oS, frequency f
dSand f
dSthe vibration amplitude A that place is corresponding
dScalculate by formula (10), evaluate the waveform indicator difference of two AGC oil cylinder frequency spectrums:
U＝abs(A
DS*f
DS-A
OS*f
OS)/(A
OS*f
OS)(10)
Wherein abs (A
dS* f
dS-A
oS* f
oS) represent A
dS* f
dS-A
oS* f
oSresult of calculation take absolute value.
4. the on-line monitoring method of hot tandem rolling mill running status according to claim 1, it is characterized in that, in described step 2, the signal of memorial archway cracking adopts ratio in judgement method, chooses historical vibration amplitude C when vibration basic data when memorial archway puts into operation or rolling same specification variety steel
0as benchmark, the global vibration value that on-line monitoring system detects is C
1,
Memorial archway cracking or rigidity failure coefficient W are:
W＝C
1/Co(11)。
5. the on-line monitoring method of hot tandem rolling mill running status according to claim 1, is characterized in that, index and the alert if of described step 3 comprise: the alarming value B of the setting bearing component failure factor
sk(k=1,2,3,4), the bearing fault factor B at each characteristic frequency place
k(k=1,2,3,4), work as B
k> B
sktime, on-line monitoring system forecast bearing is abnormal; Sliding bearing failure coefficient J, as J > 40%, on-line system is reported to the police; AGC oil cylinder response synchronism fault compression U, as U > 20%, on-line system is reported to the police; With memorial archway cracking or rigidity failure coefficient W, report to the police online as W > 150%.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102006047718A1 (en) * | 2006-10-09 | 2008-04-17 | Siemens Ag | Method for tracking the physical condition of a hot plate or hot strip as part of the control of a plate rolling mill for processing a hot plate or hot strip |
| CN101226102A (en) * | 2007-01-15 | 2008-07-23 | 新疆风能有限责任公司 | Method of diagnosis of varying load mechanical failure |
| CN201179527Y (en) * | 2007-12-04 | 2009-01-14 | 上海宝钢工业检测公司 | Continuous rolling mill strip steel vibrating vein monitoring early warning apparatus |
| CN201311360Y (en) * | 2008-06-20 | 2009-09-16 | 四川恒达电子科技有限公司 | Vibrating online monitoring failure diagnostic device |
| CN101685042A (en) * | 2008-09-25 | 2010-03-31 | 上海宝钢工业检测公司 | On-line monitoring method of cold rolled heating furnace roller running state |
| CN101829689A (en) * | 2010-03-31 | 2010-09-15 | 北京科技大学 | Drift fault recognition method of hot-rolling strip steel based on sound signals |
-
2010
- 2010-10-13 CN CN201010505291.1A patent/CN102441579B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102006047718A1 (en) * | 2006-10-09 | 2008-04-17 | Siemens Ag | Method for tracking the physical condition of a hot plate or hot strip as part of the control of a plate rolling mill for processing a hot plate or hot strip |
| CN101226102A (en) * | 2007-01-15 | 2008-07-23 | 新疆风能有限责任公司 | Method of diagnosis of varying load mechanical failure |
| CN201179527Y (en) * | 2007-12-04 | 2009-01-14 | 上海宝钢工业检测公司 | Continuous rolling mill strip steel vibrating vein monitoring early warning apparatus |
| CN201311360Y (en) * | 2008-06-20 | 2009-09-16 | 四川恒达电子科技有限公司 | Vibrating online monitoring failure diagnostic device |
| CN101685042A (en) * | 2008-09-25 | 2010-03-31 | 上海宝钢工业检测公司 | On-line monitoring method of cold rolled heating furnace roller running state |
| CN101829689A (en) * | 2010-03-31 | 2010-09-15 | 北京科技大学 | Drift fault recognition method of hot-rolling strip steel based on sound signals |
Non-Patent Citations (1)
| Title |
|---|
| 轧机设备的在线监测和故障诊断系统;王新彦;《中国优秀博硕士学位论文全文数据库(硕士) 信息科技辑》;20061115(第11期);第I140-356页 * |
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