CN1430063A - Diagnosing system for abnormity of rotary machine - Google Patents
Diagnosing system for abnormity of rotary machine Download PDFInfo
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- CN1430063A CN1430063A CN 01145404 CN01145404A CN1430063A CN 1430063 A CN1430063 A CN 1430063A CN 01145404 CN01145404 CN 01145404 CN 01145404 A CN01145404 A CN 01145404A CN 1430063 A CN1430063 A CN 1430063A
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Abstract
A system for diagnosing the exception of rotating machine according to its vibration features that the rotation speed fn of said rotating machine is divided by critical speed fc to obtain dimensionless speed fn/fc, which is classified to obtain several diagnosis ranges, the frequency characteristics of each exception in different diagnosis range are digitalized, and the measured vibration data is compared with the said frequency characteristics to diagnose the cause of exception.
Description
Technical field
The present invention is relevant with the abnormity diagnostic system of rotating machinery, specifically with the running speed of rotating machinery critical velocity nondimensionalization, and the dimensionless rotating speed that will obtain thus is decomposed into some diagnostic areas, carry out suitable diagnosis by each diagnostic area, prevent the mistaken diagnosis of abnormal cause thus.
Background technology
Because technical renovation, plant equipment was constantly advanced, high performance in the last few years, and to the social responsibility of these equipment and economy, productive viewpoint, the abnormality diagnostic importance of plant equipment is paid attention to by people day by day.
From this viewpoint, the early stage abnormal vibrations of large rotating machinery is found in people's expectation early.In order to take some countermeasures, people wish to develop effective abnormity diagnosis technology.
Past, Jap.P. spy about the simple diagnostic method of the unusual running of large rotating machine device opens clear 59-94018 communique etc., as shown in Figure 8, it is the detecting signal that obtains from the sensor that is arranged on the rotating machinery, send into signal input part 3, infer 4 couples of vibration data S1 that obtain from signal input part 3 of portion in failure cause and carry out frequency analysis, and compare with the database of fault causual list memory portion 5, the testing result of gained represents that by the result portion 6 demonstrates.
Use said method, be difficult to differentiate the very approaching various abnormal causes of frequency characteristic, in fact nonevent unusual flase drop also might take place sometimes come out.
In addition, when the abnormal vibrations that takes place as autovibration, although the occurrence condition of abnormal vibrations is defined by running speed, when diagnosing with above-mentioned fault causual list, if do not set diagnosis in advance, detect unusual problem in the time of then might appearing at the running speed that can not take place.
Furtherly, when generations such as the axle of generation crackle and asymmetric axle are unusual, if the different symptoms performance can take place in the running speed of rotary machine when the different range of critical velocity, promptly vary in size according to the ratio between rotating machinery revolution and the natural frequency, then abnormal vibrations performance strong or a little less than, therefore the diagnosis of fixing with above-mentioned fault causual list, then unavoidable sometimes mistaken diagnosis.
Summary of the invention
In view of the above problems, problem of the present invention is to provide a kind of diagnostic means of considering the different symptoms that produces because of running speed in order to prevent the mistaken diagnosis between the approximate different abnormal cause of frequency characteristic.
For solving above-mentioned problem, the abnormal cause of rotating machinery is diagnosed in the vibration that takes place when the present invention is turned round by rotating machinery.In this diagnostic system, the rotational speed of above-mentioned rotating machinery is become the dimensionless rotating speed with critical velocity, and this dimensionless rotating speed is divided into several diagnostic areas, to all abnormal causes that above-mentioned rotating machinery took place, by the dimensionless rotating speed that can embody abnormal cause, above-mentioned diagnostic area is classified.
In above-mentioned each diagnostic area, chosen in advance is corresponding to frequency characteristic that above-mentioned abnormal cause took place, vibration data and the above-mentioned selected frequency characteristic surveyed when above-mentioned rotating machinery is turned round compare, with the abnormal cause of diagnosing above-mentioned rotating machinery to be produced.
Said system is set above-mentioned diagnostic area because of the running speed of having considered rotating machinery, therefore can prevent that mistaken diagnosis goes out abnormal cause under the running speed that can not take place, thereby realize correct diagnosis.
In the diagnostic area that certain abnormal cause can not take place,, can not be unusual promptly, can find out abnormal cause accurately this reason mistaken diagnosis even if selected frequency characteristic meets with the frequency characteristic of being surveyed.
In addition, the operating frequency of above-mentioned running speed and critical velocity and rotating machinery and natural frequency are synonyms.
The critical velocity on the rank, preferably per 1 rank-3 of quantity of the above-mentioned diagnostic area of cutting apart with nondimensional velocity is more than 4 below 6.Consider that above-mentioned critical velocity gets rank, 1 rank-3, it is to get 3 when following that the quantity of the diagnostic area on every rank is got more than 4 the reason below 6, and abnormality diagnostic precision reduces, and getting more than 7 then, diagnostic method becomes numerous and diverse.
In addition, when only considering the single order critical velocity, the critical velocity that constitutes above-mentioned dimensionless rotating speed has only become an object, and the quantity of above-mentioned diagnostic area is more than 4 below 6.For example, if single order and second order critical velocity are all taken into account, the critical velocity that constitutes above-mentioned dimensionless rotating speed just becomes single order critical velocity and second order critical velocity, as benchmark, be categorized into the diagnostic area below 6 more than 4 respectively, each diagnostic area is synthesized, just obtain the diagnostic area of native system.
Therefore, when the critical velocity of consideration was several, the Volume Composition of above-mentioned diagnostic area can be more than 7.
In general, during rotating machinery generation abnormal vibrations, be can be influential to the distribution of frequency content, can handle abnormal cause by diagnosis based on frequency content orderlyly.Therefore, shown peak frequencies composition among the identification spectrum analysis result, simultaneously, with the rotating speed composition (fn) of rotating machinery and characteristic frequency composition (high frequency, low frequency, 2fn, fn/2, by rotary body and the determined critical velocity fc of bearing etc.) as diagnostic factro, thereby can find out abnormal cause.
In above-mentioned diagnostic area, based on above-mentioned specific rotating speed composition and above-mentioned characteristic frequency composition, the amplitude of above-mentioned characteristic frequency composition and rotating speed composition to be compared than with predefined reference value, the condition of carrying out is distributed.When the selected frequency content of above-mentioned characteristic frequency composition and each abnormal cause all was consistent, this and the selected corresponding abnormal cause of frequency content were just as diagnostic result.
Said reference value and setting value are determined by experimental result in addition, individual settings in above-mentioned diagnostic area.
When having only crest to be the rotating speed composition, only under the situation that the rotating speed composition presents, when for example being abnormal causes such as imbalance, specific is abnormal cause as the spectrum analysis result.
When estimating the accordance of above-mentioned selected frequency, investigate above-mentioned characteristic frequency composition and be among 2fn, fn/2, high frequency, low frequency, fnZg, the fc which, with each corresponding abnormal cause as diagnostic result.At this, fn represents the rotating speed composition of rotating machinery, and Zg represents the gear number of teeth, and fc represents natural frequency.
Preferably the abnormal cause of said frequencies characteristic close is assigned to one group.
Promptly in the particular diagnosis scope of each above-mentioned classification, above-mentioned selected frequency characteristic and the frequency characteristic that records are compared when being consistent, then think unusually by with the above-mentioned chosen corresponding grouping of frequency characteristic in various abnormal causes cause, through accurate diagnosis, from above-mentioned various abnormal causes, further determine real abnormal cause then.
Such as asymmetric axle and crackle, its frequency characteristic is very close, a specific abnormal cause is difficult, but they are regarded as belong to a grouping, when the vibration data that measures and the frequency characteristic of this grouping meet, according to the abnormal cause in the grouping asymmetric axle and crackle are pointed out out as diagnostic result simultaneously, stay possibility for being defined as some abnormal causes through accurate diagnosis later on.
The abnormal cause that past can not be differentiated frequency characteristic is also rigid specific, and the result causes mistaken diagnosis and lost this problem of determining the possibility of real abnormal cause, has improved at all owing to import the notion of packetizing.
The example of above-mentioned grouping is as follows, in the said frequencies analysis result, be that the abnormal cause of feature performance is concentrated into one group with rotating speed composition (fn), with rotating speed frequency multiplication composition (2fn) is that the abnormal cause that feature shows is concentrated into one group, natural frequency composition (fc) with rotating machinery is that the abnormal cause that feature shows is concentrated into one group, with the radio-frequency component is that the abnormal cause that feature shows is concentrated into one group, with the low-frequency component is that the abnormal cause that feature shows is concentrated into one group, is that the abnormal cause that feature shows is concentrated into one group with 1/2 rotating speed composition (fn/2).
In addition, each abnormal cause with above-mentioned packetizing in above-mentioned classified each diagnostic area places in the particular diagnosis scope that can produce abnormal cause, frequency characteristic and the above-mentioned selected frequency characteristic surveyed are compared, when the result meets, can think by this abnormal cause cause unusual, and can not take place in other diagnostic area of this abnormal cause, even frequency characteristic that measures and above-mentioned selected frequency characteristic meet, do not think yet by this abnormal cause cause unusual, thereby prevent the wrong diagnosis under the running speed that abnormal cause can not take place, the situation of the single diagnosis that was decided by the comparison frequency characteristic with the past is compared, and can reduce mistaken diagnosis widely.
Have vibration detecting sensor, will be transformed to the arithmetic processor of vibration data and carry out abnormality diagnostic software with this vibration data from the detection signal that this vibration transducer obtains.
Also has the division that above-mentioned diagnostic area is classified in the above-mentioned software, the diagnosis portion that each diagnostic area is diagnosed and be the grouping portion of a group to the set of the abnormal cause of said frequencies characteristic close.
In addition, the detection signal that obtains from above-mentioned vibration detecting sensor is a vibration data through the arithmetic processor conversion process, and this vibration data can be directly or delivered in the information processing machine that has above-mentioned software by communication network and to diagnose.
As above-mentioned structure, on rotating machinery, load onto above-mentioned vibration detecting sensor, to deliver to that to make it conversion process the above-mentioned arithmetic processor be vibration data from the detection signal that vibration detecting sensor obtains, and these data are delivered in the information processing machine that has above-mentioned software that is connecting and maybe this vibration data is connected with the information processing machine that has above-mentioned software through communication network, then on the information processing machine, can carry out the diagnosis of above-mentioned abnormal cause.
In addition, undertaken in succession, can concentrate supervision to rotating machinery, also can carry out unified concentrated supervision to rotating machinery by special company what a plurality of companies used to what use in a plurality of factories by the above-mentioned above-mentioned intelligence processor that connects through communication network.
Description of drawings
Fig. 1 is about the rotating machinery abnormity diagnostic system figure of the embodiment of the invention 1
The sketch of Fig. 2 rotating machinery
Fig. 3 software sketch
The vibration occurrence scope of Fig. 4 abnormal cause, frequency content and packetizing matrix
Fig. 5 abnormity diagnosis basic flow sheet
The diagnostic flow chart of Fig. 6 fn/fc＜0.4,0.6＜fn/fc≤0.88 diagnostic area
The sketch of the rotating machinery abnormity diagnostic system of Fig. 7 embodiment 2
The sketch of the existing diagnostic method of Fig. 8
Embodiment
Below, with reference to accompanying drawing the embodiment that the present invention was fit to is described.
Embodiment 1
As shown in Figure 1, the abnormity diagnostic system 10 of the rotating machinery in the embodiments of the invention is by being arranged on as the vibration detecting sensor 15 on the rotary machine 14 of diagnosis object, the vibration monitor 16 that is connected with vibration detecting sensor 15, will being transformed to the arithmetic processor 17 of vibration data from the detection signal that vibration monitor 16 comes out and the information processing machine of diagnosing from the vibration data of arithmetic processor 17 12 is constituted.
As shown in Figure 2, the linking part 26 that links up by the motor 23 of turning axle 20, supporting rotating shaft 20 both sides and the bearing 24,25 that makes it to rotate freely, driven in rotation axle 20, an end of turning axle and motor 23 of rotating machinery 14 and be sleeved on turning axle 20 and constitute near the disc- like rotor 21,22 of central parts.
What vibration detecting sensor 15 adopted is non-contact displacement transducer, near the disc- like rotor 21,22 or bearing 24,25 near be mutually an angle of 90 degrees at least two directions vibration detecting sensor 15 is housed, carry out the measurement (vertical direction of only having drawn among the figure) of shaft vibration, perhaps also can on bearing 24,25 places are separated by two directions of an angle of 90 degrees, directly load onto vibration detecting sensor 15 and measure bear vibration.
Have abnormity diagnosis software 30 in the above-mentioned information processing machine 12, as shown in Figure 3, this software 30 is by the approximate abnormal cause of frequency characteristic is summed up the grouping portion 31 that is divided into several groupings in advance, divide the division 32 of diagnostic area by running speed, each diagnostic area is carried out the diagnosis portion 33 of abnormal cause diagnosis forms.
The division 32 of above-mentioned diagnostic area is the parameter of running speed fn (hereinafter to be referred as rotating speed) with the rotating machinery 14 dimensionless rotating speed fn/fc after with critical velocity fc (to call natural frequency in the following text) nondimensionalization as the diagnostic area classification.
To in the division 32 with running speed decision diagnostic area, determine that with nondimensional velocity fn/fc the determining method of diagnostic area describes below.
Resonance about critical velocity, even in fact rotating speed fn is inconsistent with natural frequency fc, but near natural frequency fc, also can produce bigger vibration, consider this point, as long as rotating speed fn reaches in some scopes, that it can be looked is the resonance of critical velocity, and we are decided to be resonance range to this scope of 0.88≤fn/fc≤1.12.
Oil whip is to result from the displacement of turning axle 20 and the inconsistent whirling moment that causes of direction of oil film post-equalization power in the sliding bearing portion 24,25, displacement or distortion along with turning axle, self has produced exciting force turning axle, make the natural frequency of shafting different with rotary shaft rotating speed fn carry out whirling and constantly become big, this is a kind of autovibration.
The characteristic frequency composition is natural frequency ingredient f c, and the direction of whirling is identical with the sense of rotation of turning axle, and its occurrence condition is for when satisfying 2.0≤fn/fc.
When abnormal cause is asymmetric axle, crackle, through frequency analysis as can be known its characteristic frequency composition be 2 times of composition 2fn of rotating speed, but the different frequency characteristic of the scope of rotating speed fn is also different sometimes, and rotating machinery 14 in fact, even under normal condition, also necessarily have the composition 2fn of 2 times of rotating speeds to exist, the difference between these situations is not clear.
Therefore, asymmetric axle, crackle are set up simple and easy mathematical model, to the variation of rotating speed fn and the variation of the vibration frequency composition that causes catch by numeric value analysis, find out 2 times of scopes that composition presents as feature of rotating speed fn, and definite occurrence scope, result of study is definite, and the scope of 0.4≤fn/fc≤0.6 is a unusual occurrence scope of non-axis of symmetry, crackle associated.
In sum, the occurrence scope of conclusion abnormal vibrations can obtain Fig. 4.
At present embodiment, be conceived to the resonance of the critical velocity in the abnormal cause, oil whip, asymmetric axle and crackle are divided into six diagnostic areas as shown in table 1.
In addition, be that the quantity of the diagnostic area cut apart of parameter is not limited to above-mentioned 6 with dimensionless rotating speed fn/fc, in the scope below 8 more than 4, be suitable between the decision cut section.
In addition, in the present embodiment, be that diagnostic area has been determined on the basis only with 1 rank critical velocity, 2 rank critical velocitys and 3 rank critical velocitys also to be taken into account determined that diagnostic area is also passable, that classifies with regard to needs thinlyyer.
Table 1
| The reason that scope is cut apart | |
| fn/fc＜0.4 | |
| 0.4≤fn/fc≤0.6 | Characteristic according to asymmetric axle and crackle |
| 0.6＜fn/fc≤0.88 | |
| 0.88≤fn/fc≤1.12 | The resonance range of critical velocity |
| 1.12≤fn/fc＜2.0 | |
| 2.0≤fn/fc | Self-excitation vibrations (with the film shocks difference) |
Below the grouping portion 31 that has compiled the close abnormal cause of frequency characteristic is described.
For example foregoing asymmetric axle and crackle, both characteristic frequency compositions all are 2 times of composition 2fn that show as rotating speed strongly, judge that from frequency characteristic abnormal cause is that non-axis of symmetry or crackle are difficult.
Therefore, as shown in Figure 4, to the approximate abnormal cause of frequency content each all in advance packetizing classified.
Among Fig. 4, synthetic following group.Compile with rotating speed ingredient f n is the abnormal cause group G1 of feature, compile with rotating speed ingredient f n and natural frequency ingredient f c is the abnormal cause group G2 of feature, compile with the natural frequency ingredient f c of rotating machinery 20 is the abnormal cause group G3 of feature, the abnormal cause group G4 that to compile with 2 times of composition 2fn of rotating speed be feature, compiling with the radio-frequency component is the abnormal cause group G5 of feature, compiling with the low-frequency component is the abnormal cause group G6 of feature, compiling with 1/2 rotating speed ingredient f n/2 is the abnormal cause group G7 of feature, and the long-pending fnZg that compiles with rotating speed ingredient f n and gear number of teeth Zg is the groupings such as abnormal cause group G8 of feature.
Just diagnose the diagnostic process of diagnosis portion 33 of the abnormal cause of each abnormal ranges to be illustrated below.
12 pairs of vibration datas that receive from vibration monitoring device 16 of information processing machine carry out frequency analysis, and rotating speed ingredient f n and the characteristic frequency composition of extracting rotating machinery from the result of gained again out are used for diagnosis as diagnostic factro.
Figure 5 shows that an example of diagnostic process.
From the result of frequency analysis, find out amplitude above certain reference value, get the relative ratio of maximum amplitude of this amplitude then, if should just be considered as crest it is picked out than surpassing certain setting value.
Whether there is rotating speed ingredient f n in the above-mentioned crest, if exist then its amplitude is made as An.
Then, look for above-mentioned crest medium speed ingredient f n characteristic frequency composition in addition again.
At this moment the crest that has maximum amplitude beyond the rotating speed ingredient f n as above-mentioned characteristic frequency composition, its amplitude is made as A ".In addition, except that rotating speed ingredient f n, can not find the occasion of characteristic frequency composition, be considered as not having the characteristic frequency composition, diagnosable abnormal cause for grouping G1.
Confirm then whether natural frequency ingredient f c is arranged in above-mentioned each crest, when natural frequency ingredient f c and rotating speed ingredient f n exist simultaneously, be judged to be the abnormal cause of grouping G2; When natural frequency ingredient f c exists, when rotating speed ingredient f n does not exist, be diagnosed as the abnormal cause of grouping G3.
At last, the amplitude of getting above-mentioned characteristic frequency composition and rotating speed ingredient f n is than A, and "/An compares with reference value A1, B; see then whether the corresponding selected in advance frequency content (2fn, fn/2, high frequency, low frequency, fnZg) of above-mentioned characteristic frequency composition and each abnormal cause meets; as meet then with reference to Fig. 4; the abnormal cause by the frequency content that is consistent most of its correspondence is defined as one of the G4-G8 that divides into groups.
In addition, said reference value A1, B are determined by experimental result, press the individual settings respectively of diagnostic area shown in the table 1.
Below diagnostic method is as shown in Figure 5 set respectively by above-mentioned each diagnostic area, Figure 6 shows that a wherein example.
The explanation of the diagnostic sequence of above-mentioned diagnostic process and Fig. 5 is basic identical, but separately is diagnostic process its characteristics by each diagnostic area.For example vibrate occurrence scope limited " with resonance of critical velocity " among Fig. 4, fn/fc＜0.4 beyond its occurrence scope, 0.6 in the diagnostic area of＜fn/fc≤0.88, in its diagnostic process Fig. 6, even satisfy this condition of fi=fc " with the resonance of critical velocity " this mistaken diagnosis can not appear yet.
This that is to say, above-mentioned abnormity diagnostic system 10, with the rotating speed fn nondimensionalization of natural frequency fc with rotating machinery, fn/fc is as shown in table 1 with diagnostic area with the dimensionless rotating speed, separate by occasion, so just can prevent under the running speed that can not take place mistaken diagnosis effectively abnormal cause.
In addition, as shown in Figure 4, the abnormal cause that frequency content is close is divided into grouping G1-G8, when the frequency content of the vibration data that records meets frequency content fn/2, fn, 2fn, fc, high frequency, low frequency, the fnZg of above-mentioned certain grouping, abnormal cause in the grouping (during such as 2fn, two kinds in asymmetric axle and crackle are possible) proposes simultaneously as diagnostic result, so can mistaken diagnosis, leave the possibility of further finding out the specific exceptions reason.
Embodiment 2
As shown in Figure 7, vibration detecting sensor 15, vibration monitoring device 16 and the arithmetic processor 17 that is provided with in the location of rotating machinery is referred to as strong point machine group 11.For example, each the strong point machine group 11-1 ∽ x that disperses in each factory is coupled together with communication network 13.Then, simultaneously communication network 13 is coupled together, the management strong point 18 of the information processing machine 12-1 ∽ Y that has abnormity diagnosis software 30 is set again, to manage strong point 18 and couple together with above-mentioned communication network, the vibration data that sends from strong point machine group 11 is delivered to management strong point 18 by communication network 13 like this.
Said structure is arranged at the vibration data that the strong point machine group 11 at factory rotating machinery place sends, and by network 13, the information processing machine 12-1 ∽ Y that can be used on the management strong point 18 of distant location monitors.
In addition, even above-mentioned strong point machine group 11 is dispersed in each factory, concentrate the information processing machine 12-1 ∽ Y that is arranged at a place can carry out unified monitoring by communication network 13 usefulness.
And the also vibration data that the strong point machine group 11-1 ∽ X that is arranged at each company can be sent is delivered to the management strong point 18 of the remote management company of being separated by by communication network 13, can monitor by information processing machine 12-1 ∽ Y.
The effect of invention
More than explanation clearly illustrates that the present invention take the dimensionless rotating speed as parameter, diagnoses by each diagnostic area, can prevent under running speed that can not abnormal making correct diagnosis become possibility to the mistaken diagnosis of abnormal cause.
In addition, because with regard to above-mentioned all abnormal causes and the selected prior packetizing of frequency characteristic, when the vibration data that records and a certain grouped frequency characteristic conforms, if each abnormal cause in this grouping is prompted out as diagnostic result simultaneously, then be later accurate diagnosis, and then for determining that real abnormal cause provides possibility.
The detection signal that occurs from the vibration detecting sensor that is arranged on the rotating machinery is delivered to above-mentioned calculation process carry out delivering to the information processing machine as vibration data after the conversion process, can on this information processing machine, can carry out the diagnosis of above-mentioned abnormal cause thus. Remote monitoring can be realized by above-mentioned information processing machine is connected with communication network in addition, and in the situation of above-mentioned vibration detecting sensor and the dispersion of calculation process means, also unified supervision can be realized.
The explanation of symbol
10, the abnormity diagnostic system of rotating machinery
11, strong point machine group
12, information processing machine
13, communication network
14, rotating machinery
18, management strong point
20, rotating shaft
21,22, disc-like rotor
23, motor
24,25, bearing portion
G1 ∽ G8 grouping
Fn, rotating speed composition
Fc, proper vibration composition
Fn/fc, nondimensional velocity
The amplitude of An, rotating speed composition
A ", the amplitude of characteristic frequency composition
Claims (6)
1. the abnormity diagnostic system of a rotating machinery, the unusual reason of rotating machinery is diagnosed in the vibration that takes place when turning round according to rotating machinery, it is characterized in that, be the dimensionless rotating speed with the rotational speed of described rotating machinery with the critical velocity switching; And this dimensionless rotating speed is divided into several diagnostic areas; All abnormal causes that described rotating machinery took place, classify in described diagnostic area by the dimensionless rotating speed that abnormal cause occurs; In described each diagnostic area, the frequency characteristic that chosen in advance produces corresponding to described abnormal cause, measured vibration data and described selected frequency characteristic compared when described rotating machinery was turned round, with the abnormal cause of diagnosing described rotating machinery to be produced.
2. the abnormity diagnostic system of rotating machinery as claimed in claim 1, its further feature be, the number of the diagnostic area of cutting apart with described dimensionless rotating speed is divided into more than 4 below 6 by the every rank of critical velocity, rank, 1 rank-3.
3. the abnormity diagnostic system of rotating machinery as claimed in claim 1 or 2, its further feature is, by the selected frequency characteristic of described abnormal cause by, the rotating speed composition (fn) of the rotating machinery of extracting out from the frequency analysis result and characteristic frequency composition (high frequency, low frequency, 2fn, fn/2, by determined critical velocity fc such as rotary body and bearing etc.) are formed.
4. as claim 1,2 or 3 described rotating machinery abnormity diagnostic systems, its further feature is that described frequency characteristic is divided into groups by approximate abnormal cause; Described selected frequency characteristic and practical frequency characteristic are compared, when meeting, think by corresponding in the described selected frequency characteristic grouping that abnormal cause caused was unusual, then by accurate diagnosis, determine the specific exceptions reason in the described grouping.
5. as claim 1,2 or 3 described rotating machinery abnormity diagnostic systems, its further feature is, has vibration detecting sensor, will detect the detection signal that sensor obtains from this vibration and be transformed to the arithmetic processor of vibration data and carry out abnormality diagnostic software with this vibration data; Described software also has the grouping portion that the diagnosis portion that diagnoses to the division of described diagnostic area classification, by each diagnostic area and the abnormal cause that described frequency characteristic is approximate gather.
6. the abnormity diagnostic system of rotating machinery as claimed in claim 5, its further feature is, the detection signal that obtains from described vibration detecting sensor is for conversion into vibration data by computational processor, and this vibration data directly or deliver to the information processing machine with described software by communication network and diagnose.
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| Application Number | Priority Date | Filing Date | Title |
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| CNB011454040A CN1308692C (en) | 2001-12-31 | 2001-12-31 | Diagnosing system for abnormity of rotary machine |
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|---|---|---|---|
| CNB011454040A CN1308692C (en) | 2001-12-31 | 2001-12-31 | Diagnosing system for abnormity of rotary machine |
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| CN1308692C CN1308692C (en) | 2007-04-04 |
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| DE69837847T2 (en) * | 1998-03-16 | 2008-02-07 | Central Japan Railway Co., Nagoya | DEVICE FOR TESTING MAIN MOTOR BEARINGS IN RAIL VEHICLES |
| CN2337548Y (en) * | 1998-07-15 | 1999-09-08 | 中国航空工业总公司第六○八研究所 | Vibration and resonance demodulation fault detector |
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