CN100588965C - Railroad micro-magnetism flaw detector and its defectoscopy - Google Patents
Railroad micro-magnetism flaw detector and its defectoscopy Download PDFInfo
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- CN100588965C CN100588965C CN200710151626A CN200710151626A CN100588965C CN 100588965 C CN100588965 C CN 100588965C CN 200710151626 A CN200710151626 A CN 200710151626A CN 200710151626 A CN200710151626 A CN 200710151626A CN 100588965 C CN100588965 C CN 100588965C
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Abstract
The invention belongs to the safe nondestructive detection technology field, and in particular relates to a railway micro-magnetic flaw detector and an inspection method. A micro-magnetic defect magnetic charge mutation detection principle is adopted by the railway micro-magnetic flaw detector to make the defect detection realized. The railway micro-magnetic flaw detector consists of a magnetic sensor device, a signal preprocessor, an A/D converter and a computer system. The magnetic signals leaked because of defects are detected by the sensing device, converted into electric signals and inputinto the signal preprocessor. The signals are amplified, filtered and purified by the signal preprocessor, transmitted into the A/D converter and are transformed into digital signals. Then, digital filter, signal analysis, defect estimation, defect calculation and display record are implemented on the signals by the computer and are controlled by the computer to detect defects. The flaw inspection method is used for detecting the railway damage defect. The defect detection reliability is two times higher than a traditional nondestructive method. And the working efficiency is improved by fivetimes. At the same time, a worldwide problem that no effective method can be used for turnout inspection at present is solved.
Description
Technical field
The invention belongs to safe nondestructive detection technology field, be specifically related to little magnetic flaw detector of a kind of railway and method of detection thereof.
Background technology
China railways is had higher requirement to the quality and the safe condition of railway track itself along with the needs of speed-raising and heavy duty.At present, ultrasonic testing is adopted in the flaw detection of the routine of railway, and its main disadvantage is body weight big (about 80 kilograms), carries inconvenience, complicated operation (needing 6 people to operate simultaneously), also need constantly apply couplant--and water (also needs add diesel oil season in severe winter in water, with anti-freeze), very loaded down with trivial details; And detection speed is slow, can't detect low, the little defective of resolution of axial flaw; Simultaneously, detect the intellectuality of being unrealized, need manual analysis, judgement; The particularly flaw detection at railway switch position, still blank both at home and abroad so far, because its cross section is irregular, ultrasound wave and other flaw detection modes such as current vortex detection etc. are all powerless, can only lean on artificial hand hammer to strike with visual at present and patrol and examine solution.
Summary of the invention
The objective of the invention is in order to overcome deficiency of the prior art, utilize little magnetic technology, provide small and exquisite, easy to carry, simple to operate, the quick and accurate railway of a kind of volume little magnetic flaw detector, this instrument can detect railway hurt position and degree fast, determines dangerous position.Simultaneously, the present invention also will provide the little magnetic flaw detector of this railway employed method of detection.
Technical scheme of the present invention is as follows: the little magnetic flaw detector of a kind of railway, comprise a magnet sensor arrangement that can move along surface of the work, magnet sensor arrangement is connected with signal preprocessor, signal preprocessor connects A/D converter, and computer system is connected with A/D converter with magnet sensor arrangement respectively.
The little magnetic flaw detector of aforesaid railway, wherein, described magnet sensor arrangement comprises a support, be provided with upper and lower two Magnetic Sensors in the support, constitute complementary differential configuration, two Magnetic Sensors are equipped with magnetic shielding cover outward, and the Magnetic Sensor top of bottom is provided with poly-magnetic sheet, the magnetic shielding cover top of bottom is provided with holddown spring, and the magnetic shielding cover below is provided with aluminium matter alloy covers; Magnetic Sensor connection nonlinearity correction circuit and set, reset circuit.
The little magnetic method of detection of a kind of railway, the magnet sensor arrangement of this method by moving along surface of the work measures little magnetic signal of fault leakage, and is converted into electric signal and outputs to signal preprocessor; Signal preprocessor to signal amplify, filtering, purification, become digital signal through A/D converter again, send into computing machine; Computing machine is implemented control to each part mentioned above, simultaneously the signal that receives is carried out digital filtering, signal analysis, defect characteristic extraction, defective differentiation and calculating, displayed record, realizes defects detection such as crackle.
The little magnetic method of detection of aforesaid railway, wherein, this method adopts the variation of little magnetic defective magnetic charge to detect principle, sets up the defective line-charge model, and determines the defect characteristic of magnetic leakage signal to be used to differentiate the existence of defective according to the defective line-charge model.
Compare with traditional ultrasonic inspection method, the invention has the beneficial effects as follows:
1, detection speed is fast.Because it is a kind of passive detection that little magnetic detects, little magnetic signal of fault leakage exists always, and magnetic signal is with light velocity propagation, so Magnetic Sensor obtains signal time and was less than for 0.1 nanosecond; Ultrasonic Detection is a kind of active detecting, and its ripple ratio light velocity is much smaller, and detecting head obtains signal time greater than 4 microseconds.Therefore, little magnetic detection speed is higher 10000 times than Ultrasonic Detection, is suitable for track, track switch flaw detection after train raises speed.
2, detection sensitivity height.Little magnetic sensing device can obtain less than 10
-8The magnetic signal of T is equivalent to 1 micron of width, 50 microns of the degree of depth, long 100 microns the magnetic signal of fault leakage.In the Ultrasonic Detection, distinguishable defective is usually at Φ more than 1 millimeter (comparatively Xian Jin instrument can reach 0.3 millimeter of Φ, but costs an arm and a leg), and therefore, little magnetic detection sensitivity is higher 1000 times than Ultrasonic Detection.
3, good reliability.Little magnetic detection sensitivity height, can reliably be caught at 80 microns of width, 500 microns of the degree of depth, long flaw indication more than 500 microns for size.And compare with Ultrasonic Detection, reliability is high more than 2 times, and, need not add condition, thereby, the labile factor that adds eliminated.
4, characterization processes is easy.Little magnetic detects tested workpieces surface condition requirement low, needn't polish, clean, and need not add couplant, can work under the condition that the iron rust greasy dirt is arranged.
5, little magnetic testing process environmentally safe, and energy-conservation.
6, solve the global problem of railway switch carrying out flaw detection.
7, be portable, the needs that little, in light weight, easy to carry, the suitable especially railway track flow field of volume detects.
8, (one to two people gets final product) simple to operate, criterion objective (detecting the own magnetic field of rail), accurately and reliably, practical.
9, instrument is intelligent, can substitute manual analysis and judge and directly export testing result.
Description of drawings
Fig. 1 is the little magnetic flaw detector theory diagram of railway of the present invention;
Fig. 2 (a) is the structural drawing of the sensor sniffer shown in Fig. 1;
Fig. 2 (b) is Magnetic Sensor nonlinearity correction circuit figure;
Fig. 3 is Magnetic Sensor set, reset circuit figure;
Fig. 4 is the signal preprocessor circuit diagram shown in Fig. 1;
Fig. 5 is the computer system theory of constitution block diagram shown in Fig. 1;
Fig. 6 is signal analysis and processing device computer realization flow figure;
Fig. 7 is a defect characteristic extraction module computer realization process flow diagram;
Fig. 8 is defective classification discrimination module 603 computer realization process flow diagrams;
Fig. 9 is a defective class Modules computer realization process flow diagram;
Figure 10 depth of defect computing module computer realization process flow diagram.
Embodiment
Below in conjunction with accompanying drawing and embodiment the present invention is further described.
Fig. 1 is the little magnetic flaw detector theory diagram of railway of the present invention, comprise magnet sensor arrangement 1, signal preprocessor 2,, A/D converter 3, computer system 4.Magnet sensor arrangement 1 obtains little magnetic signal that tested workpiece, defect leaks along surface of the work scanning, and is converted to electric signal and is transported to signal preprocessor 2; 2 pairs of signals of signal preprocessor amplify, filtering, purification, and signal is sent into A/D converter 3; A/D converter is a digital signal with conversion of signals, and send computer system 4.Control is implemented in 4 pairs of each part mentioned above work of computer system, simultaneously the signal that receives is carried out digital filtering, signal analysis, defect characteristic extraction, defective differentiation, displayed record.
Fig. 2 (a) is the magnet sensor arrangement structural drawing among Fig. 1, comprise a support 22, be provided with upper and lower two Magnetic Sensor 2B, 2A in the support 22, two Magnetic Sensors are equipped with magnetic shielding cover 26,21 outward, the Magnetic Sensor 2A top of bottom is provided with poly-magnetic sheet 25, magnetic shielding cover 21 tops of bottom are provided with holddown spring 23, and magnetic shielding cover 21 belows are provided with aluminium matter alloy covers 24; Magnetic Sensor connection nonlinearity correction circuit and set, reset circuit, support top is provided with lead-in wire 27.Magnetic Sensor 2A, Magnetic Sensor 2B constitute complementary differential configuration, offset earth magnetism, outside electromagnetic interference and material grains is inhomogeneous, power supply etc. causes interference.
The HM201 that magnetic device in the present embodiment is selected for use is a kind of device that is used to detect corner, and the material leakage field that is used to measure and monitor the growth of standing timber will carry out gamma correction to output characteristics, will carry out set simultaneously, reset to recover detection sensitivity.
Fig. 2 (b) is for being used for the circuit of gamma correction, and it is corresponding with the electric bridge of magnetic resistance to add a Wheatstone bridge, and the variation that makes the Δ R/R of magnetic resistance is about angle θ rotational symmetry, range of linearity of existence in the miter angle scope.In the range of linearity, output voltage is directly proportional with externally-applied magnetic field, i.e. Δ V
Out=SHV
b, wherein S is the sensitivity of magnetoresistive transducer, can reach 3mv/1v/Oe, the range of linearity is within 2Oe.
Fig. 3 is Magnetic Sensor set, reset circuit figure.When Magnetic Sensor is operated in the environment of strongly disturbing external magnetic field effect, apply on its sensitive axes direction to surpass 2 * 10
-4During the magnetic field of T, can upset the polarised direction of the inner magnetic domain of sensor magnetic resistance, change the output characteristics of sensor, make the signal weaker of output, sensitivity reduces adopts set, reset circuit to eliminate the influence in strong jamming magnetic field for this reason, recovers the sensitivity of sensor.
For being used to offset the set-reset circuit in changing environment magnetic field, comprise squarer 31, follower 32, push-pull switching circuit (IRF7105) 36.The square-wave signal that squarer 31 produces 5kHz send follower 32 set control circuits (74HC04), pulse processing circuit (74HC04) 33, phase-adjusting circuit 34, phase inverter (2N3904) 35.Be operated in as Magnetic Sensor in the environment of noisy external magnetic field effect, apply on its sensitive axes direction above 2 * 10
-4During the magnetic field of T, can upset the polarised direction of the inner magnetic domain of sensor magnetic resistance, change the output characteristics of sensor, make the signal weaker of output, sensitivity reduces.For this reason, adopt set-reset electric current band, the influence of disturbing magnetic field, the sensitivity that recovers sensor are eliminated in the magnetic field that produces with certain set-reset electric current.Because the polarity of the output voltage of sensor depends on the polarised direction of inner magnetic domain, so sensor is applied the reset pulse opposite with the set pulse direction, can make the magnetic domain direction counter-rotating, externally show as the reversal of poles of sensor output.The square-wave pulse that is produced by squarer (timer) 31 among the figure send phase-adjusting circuit 34 after pulse processing circuit 33 (A, B, C, D) shaping; If 33A output pulsating wave is for just, the diode of phase-adjusting circuit 34A ends, and sends into 33B after pulse is delayed, send push-pull switching circuit 36 again after 33C and phase inverter 35 carry out the phase place adjustment, makes switching tube 36A conducting; This moment 34B diode current flow, the delayed hardly 34D that just sends into of 33A output pulsating wave, after anti-phase the switching tube 36B of push-pull switching circuit 36 is ended, put reset circuit and enter SM set mode, set current is entered magnetic field by the magnetic field cancellation ring that the electric current band produces.If 33A output pulsating wave is for negative, the diode current flow of 34A, the delayed hardly 34B that just sends into of 33A output pulsating wave send push-pull switching circuit 36 again after 34C and phase inverter 35 carry out the phase place adjustment, switching tube 36A is ended; This moment, the diode of 34B ended, and sent into 34D after pulse is delayed and sent push-pull switching circuit 36 after anti-phase, made switching tube 36B conducting, put reset circuit and enter reset mode, by the current reversal of electric current band, the magnetic field of generation makes the characteristic of sensor return to zero point, promptly recovers original sensitivity.Therefore, phase-adjusting circuit 34 makes push-pull switching circuit 36 reliably end at switching tube 36A conducting preceding switch pipe 36B; 36A reliably ends at switching tube 36B conducting preceding switch pipe.The pulsating wave of squarer constantly overturns, and two switching tube 36A, 36B of push-pull switching circuit 36 take turns conducting, and constantly set-reset is eliminated the interference of extraneous variation magnetic field; Set control circuit 32 is to control the work of putting reset circuit by computing machine.Put when resetting when needs, computing machine is exported a pulse, makes 4 ends of squarer 31 put high level, starts timer work, puts to reset; Other times computing machine output low level, the work of sealing squarer 31 is put reset circuit and is in waiting status.
Fig. 4 is a signal pre-processing circuit among Fig. 1.Signal pre-processing circuit comprises pre-service amplifier 41, wave filter 42.
The Signal Pretreatment amplifier comprises amplifier 411, amplifier 412,413,3 amplifiers of amplifier and is made up of INA128, constitutes differential configuration.Wherein amplifier 411 amplifies the signal of being carried by magnetoresistive transducer 2A, for detecting sensor amplifier; Amplifier 412 amplifies the signal of being carried by magnetoresistive transducer 2B, is the reference sensor amplifier; Amplifier 413 is a group amplifier, the flaw indication after the interference that amplification counteracting earth magnetism, outside electromagnetic interference and power supply etc. cause, and full gain is 1～10000.The output limb 6 of amplifier and the resistance R of wave filter 42
1Link to each other.
Wave filter 42 is the low acceptors of an active filter of second order, by resistance R
1, R
2, R
3, R
4, capacitor C
1, C
2Form with operational amplifier OP07.When the detection signal frequency is higher than 10kHz, capacitor C
2Be bordering on short circuit, the circuit no-output; When signal frequency is lower than 10kHz, capacitor C
2Be bordering on open circuit, circuit is equivalent to an in-phase amplifier, and circuit output is lower than the signal of 10kHz, be mainly used in filtering and be higher than the external interference signal of 10kHz, amplify the slow variable signal of output, circuit 3 can be detected change magnetic signal slowly, realize that the magnetic field absolute magnitude detects.The output limb 6 energising resistance R of wave filter
5Link to each other with the A/D converter input port of computing machine.
A/D converter 3 adopts the built-in A/D converter of RM9,12 of conversion resolutions, slewing rate 100K samples/sec.
Fig. 5 is the computer system composition diagram among Fig. 1.Computer system comprises computing machine 51, displayed record device 52, power supply 53, signal analysis and processing device 54.
S3C24lO has the MMU (supporting WinCE, EPOC32 and Linux) that strengthens the ARM system, the instruction and data high-speed cache of 16kB and high speed AMBA bus interface.S3C32410 is usually used in the integrated system of handheld device and common Embedded Application, and embedded functional module is abundant, and interface is complete, mainly comprises as the lower part: lcd controller (STN﹠amp; TFT), NAND Flash bootstrap loading routine, system management (chip selection logic and SIR controller), 3 passage UART, SD master's mouth and multimedia card interface, 2 passage SPI and 2 passage PLL.4 passage DMA, 4 passage PWM clocks, I/O mouth, RTC, 8 path 10 position ADC and touch screen interface, iic bus interface, IIS bus interface are taken high-performance, the low-power consumption microprocessor that the formula intelligence instrument uses, and have USB master's mouth and USB device mouth, be very suitable for just that railroad turnout flaw detection software systems run on the (SuSE) Linux OS of being transplanted on the ARM9 platform.
Displayed record device 52 is made up of display and storer.Display is PLANAR-EL320 * 256-FD7, wide temperature (25 ℃～+ 65 ℃), and colored the demonstration, various data, chart intuitive display are understood, under high light, can normally show.
Computing machine is mainly used in and extracts the crack information feature, and the differentiation defective is crackle, cut, spot corrosion etc., calculates flaw size, interface setting and system's control.
The signal analysis and processing device 54 of computing machine comprises data acquisition module, defect characteristic extraction module, defective classification discrimination module, depth of defect computing module, record display module, and data acquisition module is finished the data input.The computer realization flow process of signal analysis and processing device comprises the data of gathering is carried out defect characteristic extraction step 601 as shown in Figure 6, defective discriminating step 602, and depth of defect calculates and length estimation steps 603, and displayed record step 604.
Fig. 7 is a defect characteristic extraction module computer realization process flow diagram.After step 701 beginning, step 702 is with data file numbering, No. 0, step 703 read data files; In step 704 with No. 0 file data filtering.
Filtering utilization smooth estimated method the steps include:
(1) by data sequence { X
iA structure new data sequence { X ' }.Method be from get the X} every adjacent 5 figure places median constitutes { X ' }, promptly get X1, X2, X3, X4, the median X3 of X5 (is designated as X '
3), the rest may be inferred, gets last figure place always, and obviously the item number of X ' lacks four than former sequence.
(2) from { X ' }, get every adjacent three-figure median and constitute new data sequence { X " }.
(3) last data sequence
(4) Analysis of X-X " ', whether check has | x
i-x " '
i|＞k (predetermined value), if any then replacing x with an interpolate value
i
At step 704 sectioning search signal amplitude of variation maximum point, differentiate the amplitude standard 706 with defective and weigh each amplitude peak point, satisfactoryly be designated as the anticipation point 707.
At the railway material, through repeatedly experiment, defective amplitude standard is:
Crackle is (105～1123) point, can be expressed as U=-0.01u
3+ 6.1u
2-18u+130
Hole is (315～836) point, can be expressed as U=0.22u
3-3.2u
2+ 49u+260
Spot corrosion is (207～321) point, can be expressed as U=0.1u
3+ 4.1u
2-16u+230
Cut is (287～568) point, can be expressed as U=0.11u
3-2.31u
2+ 28u+30
Decision rule is: all amplitudes more than or equal to 105 can be used as defective amplitude characteristic criterion.
After the data processing of each data file is intact, at step 709 record, and in 710 reading and recording data, ask for each anticipation in step 711 and put two sorrowful each changes in amplitude gradient of 10, whether and it is maximum continuously to analyze gradients 712, and has positive and negative peak, satisfactoryly is judged to defective and record 713.
At the railway material, through repeatedly experiment, defective gradient standard is:
Crackle is (45～97), can be expressed as G=0.078g
2+ 3.4g+41
Hole is (27～37), can be expressed as G=0.0178g
2+ 5.4g+11
Spot corrosion is (18～26), can be expressed as G=0.011g
2+ 1.4g+61
Cut is (13～21), can be expressed as G=0.008g
2+ 7.4g+8
Decision rule is: all gradients more than or equal to 18 all can be used as defective gradient characteristic criterion.
After the data processing of each data file is intact, finish in step 718.
Fig. 8 is a defective discrimination module computer realization process flow diagram.Flow process after step 801 beginning, the defective data of step 802 reading and recording, and carry out defective by step 803,804 amplitude characteristic function, gradient fundamental function and differentiate all defectives that is that meets two function requirements, the incongruent deletion; What belong to defective carries out record 806.Because crackle is that the amplitude starting point is minimum in the defective, cut gradient start minimum, therefore the gradient function with crackle amplitude function, cut serves as according to differentiating.
The pattern of differentiating the defective classification is:
If x
j∈ R
n(j=1,2 ..., n) be n characteristic parameter of corresponding j defective; P
i∈ R
m(i=1,2 ..., be corresponding i kind defective classification master pattern m), L is a pattern undetermined, as to any ε＞0, satisfies
||L
j(X)-P
i(X)||＜ε
L then
jBe pattern P
iP in the formula
iFor: amplitude 105, gradient 13.Be the signal amplitude of variation greater than 105, gradient greater than 13 all can be judged to defective.
Fig. 9 is a defective classification discrimination module computer realization process flow diagram.After step 901 beginning, step 902 reading and recording defective data carries out the defective classification 903 and differentiates, all meet classification amplitude characteristic function, the requirement of gradient fundamental function can be classified as certain class defective, incongruent, be designated as new model, determine by artificial again.After defective data is handled, at step 908 record.
The pattern of differentiating the defective classification is:
If x
j∈ R
n(j=1,2 ..., n) be n characteristic parameter of corresponding j defective; P
i∈ R
m(i=1,2 ..., be corresponding i kind defective classification master pattern m), L is a pattern undetermined, as to any ε＞0, satisfies
||L
j(X)-P
i(X)||＜ε
L then
jBe pattern P
iP in the formula
iFor:
Crackle: amplitude U=-0.01u
3+ 6.1u
2-18u+130, gradient G=0.078g
2+ 3.4g+41;
Hole: U=0.22u
3-3.2u
2+ 49u+260, gradient G=0.0178g
2+ 5.4g+11;
Spot corrosion: U=0.1u
3+ 4.1u
2-16u+230, gradient G=0.011g
2+ 1.4g+61);
Cut: U=0.11u
3-2.31u
2+ 28u+30, gradient G=0.008g
2+ 7.4g+8.
Figure 10 is a depth of defect computing module computer realization process flow diagram.After step 1001 beginning, 1002 read defect parameters, and in step 1003 parameter substitution formula are calculated:
d＝KH
m
D is the degree of depth in the formula, and K is a coefficient, and Hm is an amplitude peak.
At the railway material, through repeatedly experiment, K=31.
Until all defect parameters are handled, finish in step 1006.
Claims (6)
1. little magnetic flaw detector of railway, comprise a magnet sensor arrangement that can move along surface of the work, magnet sensor arrangement is connected with signal preprocessor, signal preprocessor connects A/D converter, computer system is connected with A/D converter with magnet sensor arrangement respectively, it is characterized in that: described magnet sensor arrangement comprises a support (22), support is provided with in (22), following two Magnetic Sensor (2B, 2A), constitute complementary differential configuration, two Magnetic Sensors are equipped with magnetic shielding cover (21 outward, 26), the Magnetic Sensor of bottom (2A) top is provided with poly-magnetic sheet (25), the magnetic shielding cover of bottom (21) top is provided with holddown spring (23), and magnetic shielding cover (21) below is provided with aluminium matter alloy covers (24); Magnetic Sensor connection nonlinearity correction circuit and set, reset circuit.
2. little magnetic method of detection of railway, the magnet sensor arrangement of this method by moving along surface of the work measures little magnetic signal of fault leakage, and is converted into electric signal and outputs to signal preprocessor; Signal preprocessor to signal amplify, filtering, purification, become digital signal through A/D converter again, send into computing machine; Computing machine is implemented control to each part mentioned above, simultaneously the signal that receives is carried out digital filtering, signal analysis, defect characteristic extraction, defective differentiation and calculating, displayed record, the realization crack defect detects, it is characterized in that: this method adopts little magnetic defective magnetic charge variation to detect principle, set up the defective line-charge model, and determine the defect characteristic of magnetic leakage signal to be used to differentiate the existence of defective according to the defective line-charge model.
3. the little magnetic method of detection of railway as claimed in claim 2 is characterized in that: defect characteristic extracts by computer system and carries out, and the amplitude standard of differentiating defective at the railway material behavior is:
Crackle is (105～1123) point, can be expressed as U=-0.01u
3+ 6.1u
2-18u+130
Hole is (315～836) point, can be expressed as U=0.22u
3-3.2u
2+ 49u+260
Spot corrosion is (207～321) point, can be expressed as U=0.1u
3+ 4.1u
2-16u+230
Cut is (287～568) point, can be expressed as U=0.11u
3-2.31u
2+ 28u+30
Defective amplitude decision rule is: all more than or equal to 105 all can be judged to the defective amplitude characteristic;
Differentiating defective gradient standard is:
Crackle is (45～97), can be expressed as G=0.078g
2+ 3.4g+41
Hole is (27～37), can be expressed as G=0.0178g
2+ 5.4g+11
Spot corrosion is (18～26), can be expressed as G=0.011g
2+ 1.4g+61
Cut is (13～21), can be expressed as G=0.008g
2+ 7.4g+8
Defective gradient decision rule is: all gradients more than or equal to 18 and have a positive negative peak all can be judged to defective gradient feature.
4. the little magnetic method of detection of railway as claimed in claim 2 is characterized in that: defective is differentiated by the computer system execution, and at the railway material behavior, the defective decision rule is:
As wait to declare to detect in the data and have defective, then signal characteristic meets simultaneously: 1. defective amplitude decision rule; 2. defective gradient decision rule, because crackle is that the amplitude starting point is minimum in the defective, therefore cut gradient start minimum, serves as according to differentiating with the gradient function of crackle amplitude function, cut
Differentiating defect mode is:
If x
j∈ R
n(j=1,2 ..., n) be n characteristic parameter of corresponding j defective; P
i∈ R
m(i=1,2 ..., be corresponding i kind defective classification master pattern m), L is a pattern undetermined, as to any ε＞0, satisfies
||L
j(X)-P
i(X)||＜ε
L then
jBe pattern P
i, P in the formula
iBe amplitude 105, gradient 13, promptly the signal amplitude of variation is greater than 105, gradient greater than 13 all can be judged to defective.
5. the little magnetic method of detection of railway as claimed in claim 2 is characterized in that: the defective classification is differentiated by the computer system execution, and at the railway material behavior, defective classification decision rule is:
If x
j∈ R
n(j=1,2 ..., n) be n characteristic parameter of corresponding j defective; P
i∈ R
m(i=1,2 ..., be corresponding i kind defective classification master pattern m), L is a pattern undetermined, as to any ε＞0, satisfies
||L
j(X)-P
i(X)||＜ε
L then
jBe pattern P
i, P in the formula
iFor
Crackle: amplitude U=-0.01u
3+ 6.1u
2-18u+130, gradient G=0.078g
2+ 3.4g+41;
Hole: amplitude U=0.22u
3-3.2u
2+ 49u+260, gradient G=0.0178g
2+ 5.4g+11;
Spot corrosion: amplitude U=0.1u
3+ 4.1u
2-16u+230, gradient G=0.011g
2+ 1.4g+61;
Cut: amplitude U=0.11u
3-2.31u
2+ 28u+30, gradient G=0.008g
2+ 7.4g+8.
6. the little magnetic method of detection of railway as claimed in claim 2 is characterized in that: depth of defect calculates by computer system and carries out, and at the railway material behavior, depth of defect calculates according to formula:
d＝KH
m
D is the degree of depth in the formula, and K is a coefficient, H
mBe amplitude peak,
At railway material, K=31.
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|---|---|---|---|
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| CN108802172A (en) * | 2018-07-24 | 2018-11-13 | 烟台大学 | The method and system of inner defect depth in a kind of determining magnetic material |
| CN108873087A (en) * | 2018-09-29 | 2018-11-23 | 重庆天箭惯性科技股份有限公司 | Rotary body geomagnetic sensor noiselike signal processing circuit |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104007173A (en) * | 2013-02-27 | 2014-08-27 | 上海宝钢工业技术服务有限公司 | Magnetic flux leakage detection device for nondestructive detection of ferromagnetic material |
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|---|---|
| CN101122579A (en) | 2008-02-13 |
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