CN104931240A - Steel rim fault self-identification method - Google Patents
Steel rim fault self-identification method Download PDFInfo
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- CN104931240A CN104931240A CN201510269109.XA CN201510269109A CN104931240A CN 104931240 A CN104931240 A CN 104931240A CN 201510269109 A CN201510269109 A CN 201510269109A CN 104931240 A CN104931240 A CN 104931240A
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Abstract
The invention discloses a steel rim fault self-identification method comprising the following steps: (1) a signal detection system is arranged on a steel rim body, a signal is transmitted to detect the steel rim in real time, and detection information is sent to a data transmission system; (2) the data transmission system compresses the detection information and then transmits the detection information to a fault location identification system; (3) the fault location identification system extracts a received compression signal, carries out polygonal signal positioning according to the time-domain component of the signal and the distance between signal points, and repeats iterative calculation to obtain the coordinates of the fault point; and (4) the fault location identification system transmits the coordinates of the fault point to a fault size identification system, and the fault size identification system works out the size of a damage index based on a neural network and through data training fitting. By applying the method, the drawbacks in the prior art can be effectively solved, the detection effect is accurate and effective, and the working safety of steel rims is greatly improved.
Description
Technical field
The present invention relates to steel ring self-inspection field, specifically relate to a kind of steel ring fault self-identifying method.
Background technology
Steel ring is one of principal assembly of automobile, there is the features such as turnout is large, Testing index is many, the quality of its quality, will embody a concentrated reflection of on vehicle performance, but for the damage check of steel ring, major part must make product roll off the production line, re-use special measuring tool to detect, labour intensity is large, and efficiency is low, examination rate and accuracy rate also will be subject to the impact of human factor, can produce a lot of inconvenience in real process.
Summary of the invention
In order to overcome the deficiencies in the prior art, the invention provides a kind of steel ring fault self-identifying method, this recognition methods can be applicable in steel ring self-check system, effectively can solve the drawback that prior art exists, and Detection results is precisely effective, and detection efficiency improves greatly.
Technical scheme of the present invention is as follows: a kind of steel ring fault self-identifying method, comprises the following steps:
A, in steel ring main body signalization detection system, described signal detection system is that multi signal detects block, the dispersion distribution in polygon in steel ring main body, multi signal detects block and is located on each summit polygonal, transmit and steel ring main body detected in real time, and Detection Information is sent to data transmission system; Set data transmission system, abort situation recognition system, fault Dimensions recognition system simultaneously;
The signal that b, signal detection system reception steel ring main body reflects also is transferred to data transmission system, and data transmission system is transferred to abort situation recognition system after being compressed by Detection Information;
The compressed signal received extracts by c, abort situation recognition system, according to the distance between the time domain component of signal and signaling point, carries out polygon signal framing, and iteration calculates, and draws the coordinate of trouble spot;
D, abort situation recognition system are by trouble spot coordinates transmission to fault Dimensions recognition system, and fault Dimensions recognition system, based on neural network, by the training matching of data, calculates damage criterion size.
In described step b, data transmission system is by Detection Information input measurement matrix to the compression process of Detection Information, through transmission, reconstruct, obtains reconstruction signal, the final compressed signal obtaining reconstruct;
Compression process formula: y=φ x=φ ψ s=qs; Y is the signal value after compression, is that M × 1 is tieed up, all elements linearly syntagmatic in all measured values and x in y, and x is by compressed signal, and φ is calculation matrix,
φ
ibe 1 × N dimensional vector,
be called sensing matrix; The prerequisite of reconstruct sparse signal meets the equidistant condition of constraint, namely to any K sparse signal c and constant δ
k∈ (0,1), meets: (1-δ
k) || c||
2≤ || qc||
2≤ (1+ δ
k) || c||
2;
Reconstruction step:
E initialization, makes line difference γ
0=y, original matrix φ
0=φ, iterations k=1;
F solves index value λ
k=arg max i=1,2 ... N (< γ
k-1, φ
i>);
G separates minimum 2 and takes advantage of problem s
k=arg min s||y-φ
k||
2obtain new signal s
k;
H calculates new measured value y
k=φ
ks
kand new line difference γ
k=y-y
k;
I iterations R=k+1, if k<K, then returns step f and continues iteration, otherwise return reconstruction signal
In described step C, polygon signal framing process is:
y
i+3＝k
i,i+1(y
i-y
i+1)、x
i+3＝k
i,i+1(x
i-x
i+1)；
Wherein: λ
ifor time domain component (i=1,2,3 of signal ...), V is the velocity of propagation of acoustical signal, magnetic signal,
for previous signal time domain component (i=1,2,3 under corresponding iterations ...),
for the time value that signal under unfaulty conditions is propagated, Lq is distance (q=1,2,3 between signaling point ...), Lq is distance (q=1,2,3 between signaling point ...);
Calculate the k value of any two points, then by y
i+3=k
i, i+1(y
i-y
i+1), x
i+3=k
i, i+1(x
i-x
i+1) calculate the coordinate figure knowing multiple spot, repeat above-mentioned iterative process, the precise positioning to trouble spot can be realized.
Described steel ring fault self-identifying method, also comprises progressive damage rank evaluation system and residual life Prediction System.
Described progressive damage rank evaluation system receives the damage criterion Size calculation result from fault Dimensions recognition system, passes judgment on compared with the limit discontinuity size corresponding to the type material preset to progressive damage rank.
Described residual life Prediction System receives from the Detection Information of data transmission system and the judged result of progressive damage rank evaluation system, to estimating of crackle Root Stress in steel ring use procedure, and realize estimating of the real-time residual life of crackle component under random load spectrum according to estimating stress.
Described process of estimating is: residual life Prediction System carries out decompress(ion) to signal value, by Time Domain Piecewise to obtain useful time-domain signal, root position is carried out to the calculating of stress, then Integrated comparative preset value carries out residual life and estimates;
Described root position Stress calculation formula is:
in formula, c, M, r are material or steel ring performance parameter, and N is the working time, and A is stress field zone radius, λ
tfor time-domain signal blocks component, v is signal velocity.
Described steel ring fault self-identifying method, also comprises described dangerous working condition real-time alarm system, when progressive damage rank evaluation system judges that damage criterion size exceeds preset value alarm.
Described steel ring fault self-identifying method, also comprises display module, the result of each systems axiol-ogy and calculating is exported.
Described signal detection system can launch sonar, sound wave, the signal such as infrared, and receives the signal reflected.
Described signal detection system is provided with three, is installed on the inner panel of steel ring main body in positive triangle distribution.
Relative to prior art, the present invention has the following advantages and good effect:
1, adopt the steel ring self-inspection recognition system of the method, in steel ring work, damage check can be carried out in real time, decrease the heavy labor detected under needing line, greatly increase work efficiency.
2, in the steel ring course of work, obtain the damage information of steel ring truly, determine online on its basis and show damage position, lesion size, damage rank and concrete surplus working life in real time, realize the warning function of steel ring under dangerous working condition comparatively accurately, thus improve the security of steel ring use.
3, overhaul relative under traditional line, method provided by the invention can ensure the authenticity of floor data in Real-Time Monitoring, thus ensure that the accuracy of monitored damage data, reduce error rate, subsequent treatment is more accurately carried out in time for damage, substantially increase usability and the serviceable life of steel ring, reduce the scrappage of steel ring, save production cost.
Accompanying drawing explanation
Fig. 1 is the information flow direction figure adopting fault finding system of the present invention.
Fig. 2 is the data transmission system information flow direction figure based on compressive sensing theory.
Fig. 3 is the intelligent steel ring survey mass arrangenent diagram based on triangle signal positioning principle.
Fig. 4 is the information flow direction figure based on residual life Prediction System.
Fig. 5 is polygon signal framing method iterative process figure.
Accompanying drawing identifies: the abort situation recognition system that 1-steel ring main body, 2-signal detection system, 3-locate based on triangle signal based on the data transmission system of compressive sensing theory, 4-, 5-are based on fault Dimensions recognition system, 6-progressive damage rank evaluation system, 7-dangerous working condition real-time alarm system, the real-time Prediction System of 8-residual life of neural network.
Embodiment
Below in conjunction with the drawings and specific embodiments, the invention will be further described.
Embodiment 1:
As Figure 1-Figure 5, a kind of steel ring fault self-identifying method, comprises the following steps:
A, in steel ring main body 1 signalization detection system 2, described signal detection system 2 is multi signal detection block, the dispersion distribution in polygon in steel ring main body 1, multi signal detects block and is located on each summit polygonal, transmit and steel ring main body 1 detected in real time, and Detection Information is sent to data transmission system 3; Set data transmission system 3, abort situation recognition system 4, fault Dimensions recognition system 5 simultaneously;
B, signal detection system 2 receive signal that steel ring main body 1 reflects and are transferred to data transmission system 3, and data transmission system 3 is transferred to abort situation recognition system 4 after being compressed by Detection Information;
The compressed signal received extracts by c, abort situation recognition system 4, according to the distance between the time domain component of signal and signaling point, carries out polygon signal framing, and iteration calculates, and draws the coordinate of trouble spot;
D, abort situation recognition system 4 are by trouble spot coordinates transmission to fault Dimensions recognition system 5, and fault Dimensions recognition system 5, based on neural network, by the training matching of data, calculates damage criterion size.
In described step b, the compression process of data transmission system 3 pairs of Detection Information is by Detection Information input measurement matrix, through transmission, reconstruct, obtains reconstruction signal, the final compressed signal obtaining reconstruct;
Compression process formula: y=φ x=φ ψ s=qs; Y is the signal value after compression, is that M × 1 is tieed up, all elements linearly syntagmatic in all measured values and x in y, and x is by compressed signal, and φ is calculation matrix,
φ
ibe 1 × N dimensional vector,
be called sensing matrix; The prerequisite of reconstruct sparse signal meets the equidistant condition of constraint, namely to any K sparse signal c and constant δ
k∈ (0,1), meets: (1-δ
k) || c
2≤ || qc||
2≤ (1+ δ
k) || c||
2;
Reconstruction step:
E initialization, makes line difference γ
0=y, original matrix φ
0=φ, iterations k=1;
F solves index value λ
k=arg max i=1,2 ... N (< γ
k-1, φ
i>);
G separates minimum 2 and takes advantage of problem s
k=arg min s||y-φ
k||
2obtain new signal s
k;
H calculates new measured value y
k=φ
ks
kand new line difference γ
k=y-y
k;
I iterations R=k+1, if k<K, then returns step f and continues iteration, otherwise return reconstruction signal
In described step c, polygon signal framing process is:
y
i+3＝k
i,i+1(y
i-y
i+1)、x
i+3＝k
i,i+1(x
i-x
i+1)；
Wherein: λ
ifor time domain component (i=1,2,3 of signal ...), v is the velocity of propagation of acoustical signal, magnetic signal,
for previous signal time domain component (i=1,2,3 under corresponding iterations ...),
for the time value that signal under unfaulty conditions is propagated, Lq is distance (q=1,2,3 between signaling point ...), Lq is distance (q=1,2,3 between signaling point ...);
Calculate the k value of any two points, then by y
i+3=k
i, i+1(y
i-y
i+1), x
i+3=k
i, i+1(x
i-x
i+1) calculate the coordinate figure knowing multiple spot, repeat above-mentioned iterative process, the precise positioning to trouble spot can be realized.
Described steel ring fault self-identifying method, also comprises progressive damage rank evaluation system 6 and residual life Prediction System 8.
Described progressive damage rank evaluation system 6 receives the damage criterion Size calculation result from fault Dimensions recognition system 5, passes judgment on compared with the limit discontinuity size corresponding to the type material preset to progressive damage rank.
Described residual life Prediction System 8 receives the judged result of Detection Information from data transmission system 3 and progressive damage rank evaluation system 6, to estimating of crackle Root Stress in steel ring use procedure, and realize estimating of the real-time residual life of crackle component under random load spectrum according to estimating stress.
Described process of estimating is: residual life Prediction System 8 pairs of signal values carry out decompress(ion), by Time Domain Piecewise to obtain useful time-domain signal, root position are carried out to the calculating of stress, then Integrated comparative preset value carries out residual life and estimates;
Described root position Stress calculation formula is:
in formula, c, M, r are material or steel ring performance parameter, and N is the working time, and A is stress field zone radius, λ
tfor time-domain signal blocks component, v is signal velocity.
Described steel ring fault self-identifying method, also comprises described dangerous working condition real-time alarm system 7, when progressive damage rank evaluation system 6 judges that damage criterion size exceeds preset value alarm.
Described steel ring fault self-identifying method, also comprises display module, the result of each systems axiol-ogy and calculating is exported.
Described signal detection system 2 can launch sonar, sound wave, the signal such as infrared, and receives the signal reflected.
Described signal detection system 2 is provided with three, is installed on the inner panel of steel ring main body 1 in positive triangle distribution.
Relative to prior art, the present invention has the following advantages and good effect:
1, adopt the steel ring self-inspection recognition system of the method, in steel ring work, damage check can be carried out in real time, decrease the heavy labor detected under needing line, greatly increase work efficiency.
2, in the steel ring course of work, obtain the damage information of steel ring truly, determine online on its basis and show damage position, lesion size, damage rank and concrete surplus working life in real time, realize the warning function of steel ring under dangerous working condition comparatively accurately, thus improve the security of steel ring use.
3, overhaul relative under traditional line, method provided by the invention can ensure the authenticity of floor data in Real-Time Monitoring, thus ensure that the accuracy of monitored damage data, reduce error rate, subsequent treatment is more accurately carried out in time for damage, substantially increase usability and the serviceable life of steel ring, reduce the scrappage of steel ring, save production cost.
Claims (9)
1. a steel ring fault self-identifying method, is characterized in that comprising the following steps:
A, in the upper signalization detection system (2) of steel ring main body (1), described signal detection system (2) is multi signal detection block, in the upper dispersion distribution in polygon of steel ring main body (1), multi signal detects block and is located on each summit polygonal, transmit and steel ring main body (1) detected in real time, and Detection Information is sent to data transmission system (3); Set data transmission system (3), abort situation recognition system (4), fault Dimensions recognition system (5) simultaneously;
The signal that b, signal detection system (2) reception steel ring main body (1) reflect also is transferred to data transmission system (3), and data transmission system (3) is transferred to abort situation recognition system (4) after being compressed by Detection Information;
The compressed signal received extracts by c, abort situation recognition system (4), according to the distance between the time domain component of signal and signaling point, carries out polygon signal framing, and iteration calculates, and draws the coordinate of trouble spot;
D, abort situation recognition system (4) are by trouble spot coordinates transmission to fault Dimensions recognition system (5), and fault Dimensions recognition system (5), based on neural network, by the training matching of data, calculates damage criterion size.
2. steel ring fault self-identifying method according to claim 1, is characterized in that:
In described step b, data transmission system (3) is by Detection Information input measurement matrix to the compression process of Detection Information, through transmission, reconstruct, obtains reconstruction signal, the final compressed signal obtaining reconstruct;
Compression process formula: y=φ x=φ ψ s=qs; Y is the signal value after compression, is that M × 1 is tieed up, all elements linearly syntagmatic in all measured values and x in y, and x is by compressed signal, and φ is calculation matrix,
φ
ibe 1 × N dimensional vector,
be called sensing matrix; The prerequisite of reconstruct sparse signal meets the equidistant condition of constraint, namely to any K sparse signal c and constant δ
k ∈(0,1), meets: (1-δ
k) || c
2||≤|| qc||
2≤ (1+ δ
k) || c||
2;
Reconstruction step:
E initialization, makes line difference γ
0=y, original matrix φ
0=φ, iterations k=1;
F solves index value λ
k=arg max i=1,2 ... N (< γ
k-1, φ
i>);
G separates minimum 2 and takes advantage of problem s
k=arg min s || y-φ
k||
2obtain new signal s
k;
H calculates new measured value y
k=φ
ks
kand new line difference γ
k=y-y
k;
I iterations R=k+1, if k<K, then returns step f and continues iteration, otherwise return reconstruction signal
3. steel ring fault self-identifying method according to claim 1, it is characterized in that: in described step c, polygon signal framing process is:
y
i+3=k
i, i+1(y
i-y
i+1), x
i+3=k
i, i+1(x
i-x
i+1);
Wherein: λ
ifor time domain component (i=1,2,3 of signal ...), V is the velocity of propagation of acoustical signal, magnetic signal,
for previous signal time domain component (i=1,2,3 under corresponding iterations ...),
for the time value that signal under unfaulty conditions is propagated, Lq is distance (q=1,2,3 between signaling point ...), Lq is distance (q=1,2,3 between signaling point ...);
Calculate the k value of any two points, then by y
i+3=k
i, i+1(y
i-y
i+1), x
i+3=k
i, i+1(x
i-x
i+1) calculate the coordinate figure knowing multiple spot, repeat above-mentioned iterative process, the precise positioning to trouble spot can be realized.
4. steel ring fault self-identifying method according to claim 1, is characterized in that: also comprise progressive damage rank evaluation system (6) and residual life Prediction System (8);
Described progressive damage rank evaluation system (6) receives the damage criterion Size calculation result from fault Dimensions recognition system (5), passes judgment on compared with the limit discontinuity size corresponding to the type material preset to progressive damage rank;
Described residual life Prediction System (8) receives from the Detection Information of data transmission system (3) and the judged result of progressive damage rank evaluation system (6), crackle Root Stress in steel ring use procedure is estimated, and realizes estimating of the real-time residual life of crackle component under random load spectrum according to estimating stress.
5. steel ring fault self-identifying method according to claim 4, it is characterized in that: described process of estimating is: residual life Prediction System (8) carries out decompress(ion) to signal value, by Time Domain Piecewise to obtain useful time-domain signal, root position is carried out to the calculating of stress, then Integrated comparative preset value carries out residual life and estimates;
Described root position Stress calculation formula is:
in formula, c, M, r are material or steel ring performance parameter, and N is the working time, and A is stress field zone radius, λ
tfor time-domain signal blocks component, v is signal velocity.
6. steel ring fault self-identifying method according to claim 4, it is characterized in that: also comprise described dangerous working condition real-time alarm system (7), when progressive damage rank evaluation system (6) judges that damage criterion size exceeds preset value alarm.
7., according to the steel ring fault self-identifying method of claim 1-6 described in any one, it is characterized in that: also comprise display module, the result of each systems axiol-ogy and calculating is exported.
8. steel ring fault self-identifying method according to claim 1, is characterized in that: described signal detection system (2) can launch sonar, sound wave, the signal such as infrared, and receives the signal reflected.
9. steel ring fault self-identifying method according to claim 1, is characterized in that: described signal detection system (2) is provided with three, is installed on the inner panel of steel ring main body (1) in positive triangle distribution.
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|---|---|---|---|
| CN201510269109.XA CN104931240B (en) | 2015-05-25 | 2015-05-25 | A kind of steel ring failure self-identifying method |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510269109.XA CN104931240B (en) | 2015-05-25 | 2015-05-25 | A kind of steel ring failure self-identifying method |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB2456821A (en) * | 2008-01-28 | 2009-07-29 | Stephen Davidson | Determining power output from a crank drive by measuring reaction force at the support bearing housing and angular velocity |
| CN102706572A (en) * | 2012-06-25 | 2012-10-03 | 北京海冬青机电设备有限公司 | Fault diagnosis and rehabilitation center for train wheel sets |
| DE102012015654A1 (en) * | 2012-08-09 | 2014-05-15 | Imo Holding Gmbh | Method and device for detecting and monitoring the state of assemblies and components. |
| US20140132740A1 (en) * | 2012-11-15 | 2014-05-15 | Android Industries Llc | System and Method for Determining Uniformity of a Tire |
| CN104537241A (en) * | 2014-12-30 | 2015-04-22 | 广西科技大学 | Wheel rim fatigue analysis method |
-
2015
- 2015-05-25 CN CN201510269109.XA patent/CN104931240B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB2456821A (en) * | 2008-01-28 | 2009-07-29 | Stephen Davidson | Determining power output from a crank drive by measuring reaction force at the support bearing housing and angular velocity |
| CN102706572A (en) * | 2012-06-25 | 2012-10-03 | 北京海冬青机电设备有限公司 | Fault diagnosis and rehabilitation center for train wheel sets |
| DE102012015654A1 (en) * | 2012-08-09 | 2014-05-15 | Imo Holding Gmbh | Method and device for detecting and monitoring the state of assemblies and components. |
| US20140132740A1 (en) * | 2012-11-15 | 2014-05-15 | Android Industries Llc | System and Method for Determining Uniformity of a Tire |
| CN104537241A (en) * | 2014-12-30 | 2015-04-22 | 广西科技大学 | Wheel rim fatigue analysis method |
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| CN104931240B (en) | 2017-09-01 |
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Effective date of registration: 20221205 Address after: No. 66, Liugong Avenue, Liuzhou City, Guangxi Zhuang Autonomous Region, 545027 Patentee after: LIUZHOU TITAN YUXIANG WHEEL CO.,LTD. Address before: 545006 268 East Ring Road, Central District, Liuzhou, the Guangxi Zhuang Autonomous Region Patentee before: GUANGXI University OF SCIENCE AND TECHNOLOGY |
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Address after: No. 66, Liugong Avenue, Liuzhou, Guangxi 545000 Patentee after: Guangxi Titan Yuxiang Steel Ring Co.,Ltd. Address before: No. 66, Liugong Avenue, Liuzhou City, Guangxi Zhuang Autonomous Region, 545027 Patentee before: LIUZHOU TITAN YUXIANG WHEEL CO.,LTD. |
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