CN102914427A - Fatigue damage estimating method and monitoring device under multi-axis random load - Google Patents

Abstract

The invention provides a mechanical fatigue damage monitoring device and method under a multi-axis random load, which belong to the field of mechanical fatigue damage monitoring. The device mainly comprises a data collecting system (1), a data processing system (2) and a data monitoring system (3). The data collecting system (1) comprises a mechanical key part A2, a strain sensor A1 and a data transmission line A3; the data processing system (2) comprises a data collecting card B1, an alternating current power supply B2, a USB transmission line B3, a power amplifier B4 and an A/D (Analog to Digital) converter B5; and the data monitoring system (3) comprises a computer C1. According to the invention, as a multi-axis fatigue damage estimating theory based on a critical plane method is applied to a monitoring system, common fatigue damage monitoring problems under the multi-axis load in the actual construction are solved; and as shown by a predication result, the fatigue damage under the multi-axis load can be preferably estimated by using the algorithm.

Description

Method for estimating fatigue damages and monitoring device under a kind of multiaxis random load

Technical field

The present invention is mechanical fatigue damage monitoring device and method under a kind of multiaxis random load, belongs to mechanical fatigue damage monitoring field.

Background technology

Some important spare parts in commission various aerospace flight vehicle, pressure vessel, nuclear power station, generating plant and the daily vehicles can bear the random or random mutual Cyclic Load of complicated multiaxis usually.In long work, mechanical fatigue becomes main failure mode, and the tending to of fatigue break brought heavy economic losses to national product, even goes back entail dangers to personal security.So, operating important spare part is carried out the fatigue damage condition monitoring becomes one of requisite safety guarantee means.

About Fatigue Damage Assessment and monitoring, groundwork concentrates on the single shaft fatigue aspect at present.But engineering structure parts most in the modern industry are all worked under complicated multiaxis loading history, severe environmental conditions, so traditional single shaft fatigue strength theory does not satisfy the engineering requirements such as Grand Equipments strength assessment and life prediction far away.Therefore will meet the damage monitoring that fatigue damage monitoring method under the multiaxis random load of engineering reality is applied to the Grand Equipments key components and parts, be the important development direction of engineering practical structures damage quantitative monitoring technology.

Summary of the invention

Fundamental purpose of the present invention is the current demand for present fatigue monitoring system, has proposed a kind of based on fatigue damage monitoring device and method under the multiaxis random load of strain.The advantage of this device and method is to carry out real-time fatigue damage monitoring to it in the whole process of mechanical key parts operation, notifies its fatigue damage situation at once, to prevent the generation of fatigue break accident.

The technical solution used in the present invention, concrete structure are referring to Fig. 1, and this device mainly comprises data acquisition system (DAS) 1, data handling system 2, data monitoring system 3.It is characterized in that: the data acquisition system (DAS) 1 of this device comprises mechanical key parts A2, strain transducer A1, data line A3; Data handling system 2 comprises data collecting card B1, AC power B2, USB transmission line B3, power amplifier B4, A/D converter B5; Data monitoring system 3 comprises computing machine C1, software monitoring system C2.Software monitoring system C2, concrete structure comprise user log-in block D1, database D 2, real time data display module D3, Fatigue Damage Calculation module D4, historical record preservation and check module D5 referring to Fig. 2; Wherein, strain transducer A1 is affixed on mechanical key parts A2 indentation, there and is connected with power amplifier B4 by data line A3, power amplifier B4 is connected with A/D converter B5, A/D converter B5 is connected with data collecting card B1, data collecting card B1 is connected with computing machine C1 by USB transmission line B3, data collecting card B1 is by AC power B2 power supply, and software monitoring system C2 runs on the computing machine C1, and C3 obtains data by USB port.User log-in block D1, real time data display module D3, Fatigue Damage Calculation module D4, historical record are preserved and are connected with database D 2 respectively with checking module D5, and Fatigue Damage Calculation module D4 preserves with historical record and is connected with checking module D5.

The present invention proposes a kind of advanced person's Multiaxial Fatigue Damage evaluation method in order to solve the problem of Fatigue Damage Assessment under the random multiaxial loading.

Use the method for Fatigue Damage Assessment under a kind of multiaxis random load of described device, it is characterized in that, step is as follows:

Step 1): read strain history load blocks of data;

Strain data is by the data collecting card collection and deposit in the computing machine (C1), and when data volume reaches counting of setting in advance, system will read normal strain from database and shearing strain moment point data deposit in respectively in two arrays;

Step 2): calculate equivalent strain Damage Parameter time history;

Normal strain and shearing strain array data are used for calculating equivalent strain Damage Parameter time history according to the moment point order; Equivalent strain Damage Parameter time history is calculated with following Parameter for Multiaxial Fatigue Damage based on critical surface:

$\frac{\mathrm{\&Delta;}{\mathrm{\&epsiv;}}_{\mathrm{eq}}^{\mathrm{cr}}\left(t\right)}{2}=\sqrt{{\mathrm{\&epsiv;}}_n^{*2}+\frac{1}{3}{\left(\frac{\mathrm{\&Delta;}{\mathrm{\&gamma;}}_{\max }}{2}\right)}^2}{|}_{0<t\&le;t_{\mathrm{end}}}$

Wherein, Δ γ _MaxThe maximum shear strain scope on the maximum shear strain scope plane,

The Δ γ on this plane _MaxNormal strain course between turning back a little, the moment point in the corresponding array of t; t _EndThe some finish time in the corresponding array;

Step 3): determine maximum equivalent strain Damage parameter, and calculate the fatigue damage value;

Determine among the whole load piece, the maximal value of equivalent strain Damage Parameter time history, and with this maximum equivalent strain Damage parameter Value substitution following formula calculates the fatigue damage of its generation:

$\frac{{\mathrm{\&Delta;\&epsiv;}}_{\mathrm{eq}}^{\mathrm{cr}}\left(t\right)}{2}{|}_{\max }=\frac{{\mathrm{\&sigma;}}_f^{\&prime;}}{E}{\left(2N_f\right)}^b+{\mathrm{\&epsiv;}}_f^{\&prime;}{\left(2N_f\right)}^c$

Wherein, E is the elastic modulus of material, σ ' _f, ε ' _f, b, c are the fatigue of materials parameters under the single shaft tension and compression, inquiry obtains N by experiment or in the material handbook _fIt is lift cycles;

Step 4): determine in the whole load new for small strain time history load blocks of data;

For a random multiaxial loading piece, if not being completely monotone, whole equivalent strain Damage Parameter time history do not rise, stipulate that then each part that does not rise is defined as inner less strain history load piece;

Step 5): to new less load blocks of data, repeating step 2) to step 4), until can not form the less strain history load blocks of data in new inside;

Step 6): the accumulation of fatigue damage value obtains the fatigue damage of whole load piece;

Use linear damage accumulation rule, the fatigue damage that each little load piece calculates is carried out fatigue damage accumulation, obtain the fatigue damage value of whole load piece; Its formula is expressed as follows:

$D_{\mathrm{tol}}=\underset{i=1}{\overset{\mathrm{<figure-callout\; id="1"\; label="n"\; filenames="HDA00002252787100011.png"\; state="\{\{state\}\}">n</figure-callout>}}{\mathrm{\&Sigma;}}}\frac{1}{{2N}_{\mathrm{fi}}}$

Wherein, D _TolWhich load piece the total impairment value that represents whole load piece, i represent, n represents the little load piece number that whole load piece can be divided,

Represent the impairment value that i the maximum equivalent strain Parameters Calculation in the load piece obtains.

Advantage of the present invention is: 1) system at first is saved in database with the data that USB port gets access to, convenient many computing machines simultaneously from database reading out data carry out remote computation, monitoring; 2) system can extract the data that obtain in the database and automatically carries out fatigue damage accumulation and calculate, and realizes the on-line real time monitoring to fatigue damage; 3) will be applied in the monitoring system based on the Multiaxial Fatigue Damage assessment theory of critical surface method, solve fatigue damage monitoring problem under the multiaxial loading common in the engineering reality, the algorithm that the explanation that predicts the outcome proposes can be assessed the fatigue damage under the multiaxial loading preferably.

Description of drawings

Fig. 1 system construction drawing of the present invention;

Fig. 2 software monitoring system structural drawing;

Among the figure: A1, strain transducer, A2, mechanical key parts, A3, data line, B1, data collecting card, B2, AC power, B3, USB transmission line, C1, computing machine, C2, software monitoring system, D1, user log-in block, D2, database, D3, real time data display module, D4, Fatigue Damage Calculation module, D5, historical record are preserved and are checked module, 1, data acquisition system (DAS), 2, data handling system, 3, data monitoring system.

Embodiment

The concrete structure of present embodiment, referring to Fig. 1, this device mainly comprises data acquisition system (DAS) 1, data handling system 2, data monitoring system 3.Data acquisition system (DAS) 1 comprises mechanical key parts A2, strain transducer A1, data line A3; Data handling system 2 comprises data collecting card B1, AC power B2, USB transmission line B3, power amplifier B4, A/D converter B5; Data monitoring system 3 comprises computing machine C1, software monitoring system C2.Software monitoring system C2, concrete structure is participated in Fig. 2, comprises user log-in block D1, database D 2, real time data display module D3, Fatigue Damage Calculation module D4, historical record preservation and checks module D5; Wherein, strain transducer A1 is affixed on mechanical key parts A2 indentation, there, and be connected with power amplifier B4 by data line A3, power amplifier B4 is connected with A/D converter B5, A/D converter B5 is connected with data collecting card B1, and data collecting card B1 is connected with computing machine C1 by USB transmission line B3, and data collecting card B1 is by AC power B2 power supply, software monitoring system C2 runs on the computing machine C1, and C3 obtains data by USB port.User log-in block D1, real time data display module D3, Fatigue Damage Calculation module D4, historical record are preserved and are connected with database D 2 respectively with checking module D5, and Fatigue Damage Calculation module D4 preserves with historical record and is connected with checking module D5.

Strain signal in the strain transducer A1 collection machinery key components and parts A2 operational process, pass A3 by data line and give power amplifier B4, power amplifier B4 carries out strain signal to be transferred to A/D converter B5 after power amplification is processed, A/D converter B5 is transferred to data collecting card B1 after strain signal being converted to digital signal again, after data collecting card B1 carries out corresponding pre-service with strain signal, B3 sends computing machine C1 to by the USB transmission line, the software monitoring system C2 of the upper operation of computing machine C1 gets access to this strain data by USB port C3 again, then data are carried out respective handling and calculating, realize the fatigue damage monitoring.The data that get access at first are stored in the database D 2, then real time data display module D3 connection data storehouse obtains data and shows, Fatigue Damage Calculation module D4 connection data storehouse obtains data and data is calculated simultaneously, result of calculation and process data can and check that module D5 is stored in database D 2 by the historical record preservation, but historical record preserve with check module also connection data storehouse D2 obtain historical record and check for the user, user log-in block D1 connection data storehouse D2 obtains data and carries out user login validation.

Below in conjunction with instantiation Multiaxial Fatigue Damage computing method content under the random load of the present invention is described in further detail:

Step 1): extract strain history load blocks of data.

For certain aluminum alloy materials, extract altogether 182 data points of normal strain and shearing strain time history load piece, as shown in table 1.

Table 1 normal strain and shearing strain time history load blocks of data

Data point	Normal strain	Shearing strain
			1	-0.00964	0.005758
2	-0.00887	0.005284
			3	-0.00805	0.004736
4	-0.00721	0.004157
			5	-0.00634	0.003575
6	-0.00548	0.00306

7	-0.0046	0.0026
			8	-0.00369	0.001936
9	-0.00273	0.001312
			10	-0.00173	0.000632
11	-0.00068	-1.5E-05
			12	0.000401	-0.00066
13	0.001526	-0.00131
			14	0.002687	-0.00197
15	0.003829	-0.00261
			16	0.005	-0.00325
17	0.006175	-0.00388
			18	0.00737	-0.00452
19	0.0086	-0.00514
			20	0.009629	-0.00571
21	0.009023	-0.00562
			22	0.008324	-0.00515
23	0.007601	-0.00455
			24	0.006831	-0.00391
25	0.006052	-0.00326
			26	0.005267	-0.00284
27	0.00448	-0.00213
			28	0.003692	-0.00133
29	0.002867	-0.00057
			30	0.001995	0.000144
31	0.001095	0.000862
			32	0.000151	0.001608

33	-0.00082	0.002379
			34	-0.00183	0.003159
35	-0.00287	0.003931
			36	-0.00392	0.004686
37	-0.00495	0.005416
			38	-0.00601	0.006156
39	-0.00709	0.006889
			40	-0.00812	0.007616
41	-0.00758	0.007638
			42	-0.00694	0.00709
43	-0.00628	0.006388
			44	-0.0056	0.005638
45	-0.00491	0.004854
			46	-0.00419	0.004064
47	-0.00349	0.003283
			48	-0.00275	0.002576
49	-0.00201	0.001929
			50	-0.00121	0.001083
51	-0.00039	0.000205
			52	0.000461	-0.00065
53	0.001325	-0.00149
			54	0.002243	-0.00231
55	0.003175	-0.00316
			56	0.004122	-0.004
57	0.005092	-0.00484
			58	0.006083	-0.00568

59	0.007088	-0.00653
			60	0.008089	-0.00736
61	0.007745	-0.00749
			62	0.007163	-0.00696
63	0.006558	-0.00624
			64	0.005936	-0.00541
65	0.0053	-0.00455
			66	0.004657	-0.00369
67	0.003999	-0.00284
			68	0.003354	-0.00224
69	0.002707	-0.00127
			70	0.00203	-0.00026
71	0.001311	0.00067
			72	0.000561	0.001574
73	-0.00022	0.002501
			74	-0.00101	0.003456
75	-0.00183	0.004432
			76	-0.00268	0.005397
77	-0.00355	0.00635
			78	-0.0044	0.007288
79	-0.0053	0.008227
			80	-0.00617	0.009164
81	-0.00598	0.009471
			82	-0.00547	0.008957
83	-0.00494	0.008122
			84	-0.00441	0.007182

85	-0.00387	0.006214
			86	-0.0033	0.005234
87	-0.00274	0.004252
			88	-0.00217	0.003271
89	-0.00158	0.002394
			90	-0.00097	0.001528
91	-0.00035	0.000506
			92	0.000309	-0.0006
93	0.000995	-0.00162
			94	0.001696	-0.00263
95	0.002408	-0.00364
			96	0.003154	-0.00469
97	0.003915	-0.00574
			98	0.004688	-0.00678
99	0.005484	-0.00783
			100	0.006294	-0.00887
101	0.006257	-0.0093
			102	0.005808	-0.00883
103	0.005342	-0.00798
			104	0.004865	-0.00698
105	0.004364	-0.00592
			106	0.003865	-0.00486
107	0.003366	-0.0038
			108	0.002855	-0.00274
109	0.002349	-0.00196
			110	0.001852	-0.00082

111	0.00132	0.000404
			112	0.000751	0.001533
113	0.000165	0.002624
			114	-0.00044	0.003736
115	-0.00106	0.004889
			116	-0.00171	0.006057
117	-0.00236	0.007212
			118	-0.00302	0.008359
119	-0.0037	0.009508
			120	-0.00439	0.010647
121	-0.00448	0.011288
			122	-0.0041	0.010883
123	-0.00371	0.009914
			124	-0.00331	0.008792
125	-0.0029	0.007632
			126	-0.00249	0.006462
127	-0.00207	0.005288
			128	-0.00164	0.004112
129	-0.0012	0.002953
			130	-0.00078	0.002063
131	-0.00029	0.000799
			132	0.000198	-0.0005
133	0.000684	-0.00171
			134	0.001193	-0.00291
135	0.001732	-0.00411
			136	0.002292	-0.00535

137	0.002849	-0.0066
			138	0.003414	-0.00784
139	0.004003	-0.00908
			140	0.004598	-0.01032
141	0.004837	-0.01121
			142	0.004679	-0.01122
143	0.004497	-0.01086
			144	0.0043	-0.01035
145	0.004103	-0.0098
			146	0.003906	-0.00923
147	0.003701	-0.00865
			148	0.003487	-0.00807
149	0.00328	-0.00749
			150	0.003066	-0.0069
151	0.00285	-0.00632
			152	0.002632	-0.00574
153	0.002418	-0.00516
			154	0.002196	-0.00457
155	0.00197	-0.00399
			156	0.001748	-0.0034
157	0.001523	-0.00285
			158	0.001298	-0.00247
159	0.001063	-0.00189
			160	0.000827	-0.00121
161	0.000849	-0.00129
			162	0.000582	-0.00064

163	0.000108	-0.00017
			164	-0.00037	0.000192
165	-0.00087	0.000521
			166	-0.00136	0.000838
167	-0.00186	0.001167
			168	-0.00238	0.001504
169	-0.0029	0.001843
			170	-0.00343	0.00218
171	-0.00398	0.002508
			172	-0.00451	0.002826
173	-0.00506	0.003148
			174	-0.00563	0.003475
175	-0.00622	0.0038
			176	-0.00683	0.004126
177	-0.00744	0.004443
			178	-0.00806	0.004755
179	-0.00868	0.005063
			180	-0.00931	0.005364
181	-0.00995	0.005668
			182	-0.01036	0.005917

Step 2): calculate equivalent strain Damage Parameter time history.

According to the data point order, calculate shearing strain and normal strain on each plane with following formula and normal strain and shearing strain time history.

${\mathrm{\&epsiv;}}_{\mathrm{\&theta;}}=\frac{1-v}{2}{\mathrm{\&epsiv;}}_x+\frac{1+\mathrm{<figure-callout\; id="2"\; label="v"\; filenames="HDA00002252787100011.png"\; state="\{\{state\}\}">v</figure-callout>}}{2}{\mathrm{\&epsiv;}}_x\cos \left(2\mathrm{\&theta;}\right)+\frac{{\mathrm{\&gamma;}}_{\mathrm{<figure-callout\; id="2"\; label="xy"\; filenames="HDA00002252787100011.png"\; state="\{\{state\}\}">xy</figure-callout>}}}{2}\sin \left(2\mathrm{\&theta;}\right)$

$\frac{{\mathrm{\&gamma;}}_{\mathrm{\&theta;}}}{2}=\frac{(1+v){\mathrm{\&epsiv;}}_x}{2}\sin \left(2\mathrm{\&theta;}\right)-\frac{{\mathrm{\&gamma;}}_{\mathrm{<figure-callout\; id="2"\; label="xy"\; filenames="HDA00002252787100011.png"\; state="\{\{state\}\}">xy</figure-callout>}}}{2}\cos \left(2\mathrm{\&theta;}\right)$

Wherein, v is Poisson ratio (approximate value 0.4),

And ε _θShearing strain and the normal strain on the difference angle θ plane.ε in the formula _xThe data of the 1st row in the corresponding table 1, γ _XyThe data of the 2nd row so just obtain 182 in the corresponding table 1

And ε _θBy these 182

And ε _θObtain 182 equivalent strain Damage Parameter time histories.Then calculating equivalent strain Damage Parameter time history joins with following Multiaxial Fatigue Damage based on critical surface:

$\frac{{\mathrm{\&Delta;\&epsiv;}}_{\mathrm{eq}}^{\mathrm{cr}}\left(t\right)}{2}=\sqrt{{\mathrm{\&epsiv;}}_n^{*2}+\frac{1}{3}{\left(\frac{\mathrm{\&Delta;}{\mathrm{\&gamma;}}_{\max }}{2}\right)}^2}{|}_{0<t\&le;t_{\mathrm{end}}}$

Wherein, Δ γ _MaxThe maximum shear strain scope on the maximum shear strain scope plane,

The Δ γ on this plane _MaxNormal strain course between turning back a little, the moment point in the corresponding array of t.t _EndThe some finish time in the corresponding array;

As shown in table 2 for 182 data point result of calculations in the case.

Table 2 equivalent strain parameter time history

Step 3): determine maximum equivalent strain Damage parameter, and calculate the fatigue damage value.

As can be seen from Table 2, its maximum equivalent strain Damage Parameter

Be 0.0107.This value substitution following formula is calculated the fatigue damage of its generation:

$\frac{{\mathrm{\&Delta;\&epsiv;}}_{\mathrm{eq}}^{\mathrm{cr}}\left(t\right)}{2}{|}_{\max }=\frac{{\mathrm{\&sigma;}}_f^{\&prime;}}{E}{\left(2N_f\right)}^b+{\mathrm{\&epsiv;}}_f^{\&prime;}{\left(2N_f\right)}^c$

Wherein, E is the elastic modulus of material, σ ' _f, ε ' _f, b, c are the fatigue of materials parameters under the single shaft tension and compression, can by experiment or inquire about in the material handbook and obtain N _fIt is lift cycles.

For at aluminum alloy materials, the tired parameter of its uniaxial material can be inquired about in the material handbook, and its Query Result is shown in Table 3.

Tired parameter under certain aluminum alloy materials single-axle load of table 3

Then find the solution top formula, just can find the solution and draw N _fValue.

Step 4): determine in the whole load new for small strain time history load blocks of data.

For the whole equivalent strain Damage Parameter time history in the table 2, can find that data point 22 to the value between the data point 34 and data point 42 to the value between the data point 182 remains unchanged.The two blocks of data point that then these two data is not increased is divided into two strain history load pieces that new inside is less.

Step 5): to new less load blocks of data, repeating step 2) to step 4), until can not form the less strain history load blocks of data in new inside.

Only come the brief description repetitive process with data point 22 to data point 34.Data point 22 is to having 11 data between the data point 34.Repeating step 2) obtains 11

And ε _θ, ε wherein _xThe 1st columns strong point 22 is to 11 data between the data point 34, γ in the corresponding table 1 _XyThe data point 22 of the 2nd row is to 11 data between the data point 34 in the corresponding table 1.By these 11

And ε _θObtain 11 equivalent strain Damage Parameter time histories.At this moment data are 11 new equivalent strain Damage Parameter time histories that are different from table 2 data, then determine new maximum equivalent strain Damage parameter

Obtain the new N of another one _fValue.

Search again after the same method whether to form the less strain history load blocks of data in new inside, until can not form the less strain history load blocks of data in new inside.

Data point 42 to data point 182 also obtains a N successively _fValue.Search again after the same method whether to form the less strain history load blocks of data in new inside, until can not form the less strain history load blocks of data in new inside.

Whole loading spectrum forms 8 load pieces, thereby can obtain 8 impairment value N _f

Step 6): the accumulation of fatigue damage value obtains the fatigue damage of whole load piece.

Use linear damage accumulation rule, the fatigue damage value that each little load piece calculates is carried out damage accumulation, thereby obtain the fatigue damage value of whole load piece.Its formula is expressed as follows:

$D_{\mathrm{tol}}=\underset{i=1}{\overset{\mathrm{<figure-callout\; id="1"\; label="n"\; filenames="HDA00002252787100011.png"\; state="\{\{state\}\}">n</figure-callout>}}{\mathrm{\&Sigma;}}}\frac{1}{{2N}_{\mathrm{fi}}}$

Wherein, D _TolWhich load piece the total impairment value that represents whole load piece, i represent, n represents the little load piece number that whole load piece can be divided,

Represent the impairment value that i the maximum equivalent strain Parameters Calculation in the load piece obtains.

Be 8 for this load piece i.

Test findings demonstration, this material move 116 fatigure failures occur under the effect of this load piece, namely the fatigue damage value of this piece is 0.00862, and the damage result of the algorithm accumulation of proposition is 0.0098, and the life-span of its estimation is 102.The algorithm that the explanation that predicts the outcome proposes can be assessed the fatigue damage under the multiaxial loading preferably.

This advantage of system is: 1) system at first is saved in database with the data that USB port gets access to, convenient many computing machines simultaneously from database reading out data carry out remote computation, monitoring; 2) system can extract the data that obtain in the database and automatically carries out fatigue damage accumulation and calculate, and realizes the on-line real time monitoring to fatigue damage; 3) will be applied in the monitoring system based on the Multiaxial Fatigue Damage assessment theory of critical surface method, solved fatigue damage monitoring problem under the multiaxial loading common in the engineering reality.

Claims (2)

1. fatigue damage monitoring device under the multiaxis random load, this device mainly comprises data acquisition system (DAS) (1), data handling system (2), data monitoring system (3), it is characterized in that: the data acquisition system (DAS) of this device (1) comprises mechanical key parts (A2), strain transducer (A1), data line (A3), data handling system (2) comprises data collecting card (B1), AC power (B2), USB transmission line (B3), and data monitoring system (3) comprises computing machine (C1), software monitoring system (C2); Wherein, strain transducer (A1) is affixed on mechanical key parts (A2) key position, and be connected with power amplifier (B4) by data line (A3), power amplifier (B4) is connected with A/D converter (B5), A/D converter (B5) is connected with data collecting card (B1), data collecting card (B1) is connected with computing machine (C1) by USB transmission line (B3), data collecting card (B1) is by AC power (B2) power supply, software monitoring system (C2) runs on the computing machine (C1), and (C3) obtains data by USB port.

2. application rights requires the method for Fatigue Damage Assessment under a kind of multiaxis random load of 1 described device, it is characterized in that, step is as follows:

Step 1): read strain history load blocks of data;

Strain data is by the data collecting card collection and deposit in the computing machine (C1), and when data volume reaches counting of setting in advance, system will read normal strain from database and shearing strain moment point data deposit in respectively in two arrays;

Step 2): calculate equivalent strain Damage Parameter time history;

Normal strain and shearing strain array data are used for calculating equivalent strain Damage Parameter time history according to the moment point order; Equivalent strain Damage Parameter time history is calculated with following Parameter for Multiaxial Fatigue Damage based on critical surface:

$\frac{\mathrm{\&Delta;}{\mathrm{\&epsiv;}}_{\mathrm{eq}}^{\mathrm{cr}}\left(t\right)}{2}=\sqrt{{\mathrm{\&epsiv;}}_n^{*2}+\frac{1}{3}{\left(\frac{{\mathrm{\&Delta;\&gamma;}}_{\max }}{2}\right)}^2}{|}_{0<t\&le;t_{\mathrm{end}}}$

Wherein, Δ γ _MaxThe maximum shear strain scope on the maximum shear strain scope plane,

The Δ γ on this plane _MaxNormal strain course between turning back a little, the moment point in the corresponding array of t; t _EndThe some finish time in the corresponding array;

Step 3): determine maximum equivalent strain Damage parameter, and calculate the fatigue damage value;

Determine among the whole load piece, the maximal value of equivalent strain Damage Parameter time history, and with this maximum equivalent strain Damage parameter

Value substitution following formula calculates the fatigue damage of its generation:

$\frac{{\mathrm{\&Delta;\&epsiv;}}_{\mathrm{eq}}^{\mathrm{cr}}\left(t\right)}{2}{|}_{\max }=\frac{{\mathrm{\&sigma;}}_f^{\&prime;}}{E}{\left(2N_f\right)}^b+{\mathrm{\&epsiv;}}_f^{\&prime;}{\left(2N_f\right)}^c$

Wherein, E is the elastic modulus of material, σ ' _f, ε ' _f, b, c are the fatigue of materials parameters under the single shaft tension and compression, inquiry obtains N by experiment or in the material handbook _fIt is lift cycles;

Step 4): determine in the whole load new for small strain time history load blocks of data;

For a random multiaxial loading piece, if not being completely monotone, whole equivalent strain Damage Parameter time history do not rise, stipulate that then each part that does not rise is defined as inner less strain history load piece;

Step 5): to new less load blocks of data, repeating step 2) to step 4), until can not form the less strain history load blocks of data in new inside;

Step 6): the accumulation of fatigue damage value obtains the fatigue damage of whole load piece;

Use linear damage accumulation rule, the fatigue damage that each little load piece calculates is carried out fatigue damage accumulation, obtain the fatigue damage value of whole load piece; Its formula is expressed as follows:

$D_{\mathrm{tol}}=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}\frac{1}{2N_{\mathrm{fi}}}$

Wherein, D _TolWhich load piece the total impairment value that represents whole load piece, i represent, n represents the little load piece number that whole load piece can be divided,

Represent the impairment value that i the maximum equivalent strain Parameters Calculation in the load piece obtains.

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