CN102182671B - State analysis monitoring method of gas compressor - Google Patents
State analysis monitoring method of gas compressor Download PDFInfo
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- CN102182671B CN102182671B CN 201110138460 CN201110138460A CN102182671B CN 102182671 B CN102182671 B CN 102182671B CN 201110138460 CN201110138460 CN 201110138460 CN 201110138460 A CN201110138460 A CN 201110138460A CN 102182671 B CN102182671 B CN 102182671B
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Abstract
The invention discloses a state analysis monitoring system of a gas compressor. The state analysis monitoring system comprises a gas pressure sensor, a temperature sensor, a signal conditioner, an engine oil pressure sensor, a vibration sensor, a vibration meter, a data collection card, a display and a computer. The invention further discloses a state analysis monitoring method of the gas compressor. In the state analysis monitoring method, a gas pressure signal, a temperature signal, an engine oil pressure signal and a vibration signal are input into the computer and are processed through the following steps of: comparing the signals with the upper limits and the lower limits of preset safe values, if the upper limits or the lower limits are exceeded, alarming and starting a failure diagnosis module at the same time; querying a gas compressor state parameter exception and failure mapping table in a failure diagnosis module to determine a corresponding exceptional component type; querying the historical maintenance record of each component in the exceptional component type in a database; calculating service life values of different components corresponding to the exceptional stateparameters; and checking from the component with a minimum service life value to the component with a maximum service life value in sequence until the fault component is found out, thereby finishing the state analysis monitoring.
Description
Technical field
The present invention relates to a kind of electromechanical equipment monitoring analysis field, a kind of state analysis monitoring system and method for gas compressor is provided especially.
Background technique
Gas compressor plays an important role in relating to gas medium and need the chemical process of supercharging.Compressor is carried out working state monitoring help to find incipient fault, bimetry in advance, thereby take measures as early as possible, reduce or avoid production loss.
At present, supervisory system in most use aspect safety, reliability, availability and the economic benefit of gas compressor system is process control machine, the supervisory system of using only plays the demonstration of components of system as directed status information and certain alarm effect mostly, seldom adopts the reliability analysis technology.Technology also fails to take full advantage of the status monitoring signal even the part monitoring system adopts systems reliability analysis, causes well monitoring equipment, can not in time analyze its running state and predict its working life.
Summary of the invention
Goal of the invention: technical problem to be solved by this invention is at the deficiencies in the prior art, a kind of state analysis monitoring system and method for gas compressor are provided, by the signal of gas compressor is analyzed and handled, and utilize reliability engineering to improve Security, reliability and the economic benefit of system.
In order to solve the problems of the technologies described above, the invention discloses a kind of state analysis monitoring system of gas compressor, comprise gas pressure sensor (1), temperature transducer (2), signal conditioner (3), oil pressure sensor (4), vibration transducer (5), vibrometer (6), data collecting card (7), display device (8), computer (9);
Described gas pressure sensor (1), state temperature transducer (2) and oil pressure sensor (4) is connected with described signal conditioner (3) respectively; Described vibration transducer (5) is connected with described vibrometer (6), and described vibrometer (6) and signal conditioner (3) are connected with described data collecting card (7) respectively; Described data collecting card (7) is connected with described computer (9), and described computer (9) is connected with described display device (8).
Among the present invention, the signal that described signal conditioner (3) is used for gas pressure sensor (1), temperature transducer (2) and oil pressure sensor (4) are transmitted amplifies, and is transferred to data collecting card (7).
Among the present invention, described data collecting card (7) is based on PXI (PCI extensions for Instrumentation is towards the PCI expansion of instrument system) bussing technique, and the signal that is used for gathering is converted into electrical signal, is transferred to computer.
Among the present invention, described vibrometer (6) is used for oscillating signal is amplified processing, and is transferred to data collecting card (7).
Among the present invention, described computer (9) is equipped with the LabVIEW platform software.
The invention also discloses a kind of state analysis monitoring method of gas compressor, gas pressure signal, temperature signal, engine oil pressure signal, oscillating signal imported computer, and according to following steps above signal is handled:
Step (1) compares the upper and lower bound of gas pressure signal, temperature signal, engine oil pressure signal, oscillating signal and predefined safety value, as exceeds the upper limit or lower limit is then reported to the police, and starts fault diagnosis module simultaneously;
Step (2) is unusual and fault corresponding tables by the gas compressor status parameter in the inquiry fault diagnosis module, thereby determines corresponding unusual variety of components;
Unusual and the fault corresponding tables of gas compressor status parameter
The historical maintenance record of various parts in database in the unusual variety of components of step (3) inquiry, described historical maintenance record comprises after unusual parts down time deducts its installation brings into use the time, note L is such unusual parts life value, L=S-F is then arranged, wherein S represents parts and brings into use the time, and F represents unusual component settings and uses terminal time;
The life value of the different parts of step (4) computing mode abnormal parameters correspondence; Note, life-span in the step (3) represents that record value actual life of a certain base part (is n as such unit failure number of times, n life value then arranged), life value then is at first to establish this part aging rule according to step (3) life value in this step, then according to this rule by this component life value of computer simulation.
Step (5) is that order checks by the parts of life value minimum to the parts of life value maximum, up to finding trouble unit, finishing stage analysis monitoring.
The computational methods of unusual parts life value comprise the steps: in the inventive method step (4)
Step (41) ordering is carried out ascending order with the number of stoppages n life value of the some unusual parts of step (3) and is sorted;
Step (42) parameter estimation, calculate n life value of the number of stoppages and obey following function parameters estimated value:
Tub curve, tub curve probability density function are f (t)=beta/alpha
βExp (t/ α)
βExp[1-exp (t/ α)
β] parameter alpha and the estimated value of β, wherein, t represents the component life variable, is worth to be L, parameter alpha represents the position, parameter beta represents shape;
Weibull distribution, Weibull distribution probability density function are f (t)=α β t
β-1Exp (α t
β), wherein, variable t represents operating life, parameter alpha represents the position, parameter represents shape;
Linear increment probability density function f (t)=(at+b) exp (1/2at
2-bt), wherein, variable t represents operating life, and parameter a represents the slope of linear function, and parameter b represents intercept;
Exponential distribution, probability density function are that (at), wherein, variable t represents operating life to f (t)=α exp, and parameter alpha represents the position;
Step (43) uses the life value data after n ordering of formula k=1+3.322lgn to divide into groups, and packet count is k;
Step (44) calculated rate:
(the L apart from Δ t=is namely organized at interval between calculating group and the group
a-S
m)/k, wherein, L
aBe the maximum value in life-span, S
mBe minimum value;
Determine each group group limit value, the group limit i.e. the CLV ceiling limit value of each group
Lower limit
To organize to limit to get into and equal lower limit
And less than CLV ceiling limit value
Namely press the semi-closed interval distribute data.
Statistics falls into the frequency Δ r of each group
i, according to life time and each lower class limit value
With less than CLV ceiling limit value
Compare, if life time t
jSatisfy
Frequency Δ r then
i=Δ r
i+ 1, and pass through ω
i=Δ r
i/ n calculated rate ω
i
Step (45) is passed through
Calculate the cumulative frequency of each group, wherein, r
iCumulative frequency when finishing for organizing to i.
Calculate the distribution function F of tub curve, Weibull distribution, linear increasing function and exponential distribution respectively
i', F
i' the integration of four kinds of distribution density function f (t), 1≤i≤k wherein;
Calculate k F respectively
i, F
iIt is the cumulative frequency of i group; F
iCalculate and to obtain k individual numerical value, i.e. F by obtaining F (t) that the distribution probability functional integration obtains after the parameter estimation
i' and F
iAll there be k;
Calculate D
i=| F
i-F
i' |, get the test statistics D=max (D of K-S
1, D
2..., D
k);
Step (46) model testing is looked into the critical value D of kolmogorov test according to setting confidence level δ (generally getting 0.05,0.01) and a number of stoppages n life value
cTable draws D
c, judge whether top four kinds of distributions exist D＜D
c:
If have only a D value less than a certain critical value D
c, then the corresponding function of this D value is selected function;
If two or more D values are arranged less than a certain critical value D
c, then choosing the less corresponding function of D value is selected function;
If the D value of all four kinds of models is all more than or equal to critical value D
c, directly use mean value method to obtain its life-span average;
Step (47) is by t
i=F
-1(t
i) the i time unusual component life of simulation, wherein 1≤i≤m simulates after m time, and then this moment, equipment or part life were
Be t to its corresponding life-span calculating formula of tub curve
i=α { ln[1-ln[1-U
i]]
1/ βI=1,2 ..., the life-span calculating formula of Weibull distribution correspondence is t
i=[1/ α (ln[1-U
i])]
1/ βI=1,2 ..., the life-span calculating formula of linear increasing function correspondence is
I=1,2 ..., the life-span calculating formula of exponential distribution function correspondence is t
i=1/ α (ln[1-U
i]) i=1,2 ..., U wherein
iGet [0,1] random value;
The critical value D of kolmogorov test
cTable
Beneficial effect: the recording occurring continuously that can realize data according to the present invention, gas compressor is carried out status parameter to be handled and performance evaluation, and the reliability analysis of coupling system key equipment and life prediction, set up the corresponding relation between state signal and the fault, finish safety on line monitoring and trouble analysis to equipment, improve Security, reliability, availability and the economic benefit of gas compressor system.
Description of drawings
Below in conjunction with the drawings and specific embodiments the present invention is done further to specify, above-mentioned and/or otherwise advantage of the present invention will become apparent.
Fig. 1 forms schematic representation for data acquistion system.
Fig. 2 is application software fundamental function sketch.
Embodiment
Present embodiment provides a kind of gas compressor status parameter monitoring system and method, includes gas pressure sensor 1, temperature transducer 2, signal conditioner 3, oil pressure sensor 4, vibration transducer 5, vibrometer 6, PXI data collecting card 7, display device 8, computer 9, printer 10; Wherein gas pressure sensor 1 is connected with signal conditioner 3, temperature transducer 2 and signal conditioner 3, signal conditioner 3 is connected with oil pressure sensor 4, signal conditioner 3 is connected with PXI data collecting card 7, vibration transducer 5 is connected with vibrometer 6, vibrometer 6 is connected with PXI data collecting card 7, and PXI data collecting card 7 is connected with computer 9, and computer 9 is connected with display device 8, printer 10 respectively.Wherein data collecting card is the PXI data collecting card 7 that NI company produces.Gas compressor status monitoring and belief system are carried out the status parameter measurement based on the LabVIEW platform, design the application software that is applicable to native system and possess database and life prediction function.
As shown in Figure 2, temperature signal 11, pressure signal 12, oscillating signal 13, historical maintenance record 14, database 15, life of equipment distributed model 16, life of equipment distributed model 17, predict device life-span 18, state signal analysis and handle 19, fault diagnosis 20; Wherein, temperature signal 11 imports in the database 15, pressure signal 12 imports in the database 15, oscillating signal 13 imports in the database 15, historical maintenance record 14 imports in the database 15, the result of database 15 is for life of equipment distributed model 17 and state signal analysis and processing 18, and in the 17 predict device life-spans 18 of distributed model life of equipment, predict device life-span 18 and state signal analysis and processing 19 are for system fault diagnosis 20.
Signal by gas compressor pressure and temperature monitoring point respective sensor transfers to signal amplifier, and transfer to and carry out data capture in the PXI data collecting card, and corresponding data input computer, find out failure cause by application software analysis state signal, and in conjunction with establishing direct links between fault tree analysis state of the art parameter and the fault mode, by the historical maintenance record of key equipment, and application reliability theory and technology apparatus for establishing degradation model and carry out model testing, by the life prediction of software realization equipment, finally realize the fault diagnosis of gas compressor system.
The invention also discloses a kind of state analysis monitoring method of gas compressor, gas pressure signal, temperature signal, engine oil pressure signal, oscillating signal imported computer, and according to following steps above signal is handled:
Step (1) compares the upper and lower bound of gas pressure signal, temperature signal, engine oil pressure signal, oscillating signal and predefined safety value, as exceeds the upper limit or lower limit is then reported to the police, and starts fault diagnosis module simultaneously;
Step (2) is unusual and fault corresponding tables by the gas compressor status parameter in the inquiry fault diagnosis module, thereby determines corresponding unusual variety of components;
Unusual and the fault corresponding tables of gas compressor status parameter
The historical maintenance record of various parts in database in the unusual variety of components of step (3) inquiry, described historical maintenance record comprises after unusual parts down time deducts its installation brings into use the time, note L is such unusual parts life value, L=S-F is then arranged, wherein S represents parts and brings into use the time, and F represents unusual component settings and uses terminal time;
The life value of the different parts of step (4) computing mode abnormal parameters correspondence; Note, life-span in the step (3) represents that record value actual life of a certain base part (is n as such unit failure number of times, n life value then arranged), life value then is at first to establish this part aging rule according to step (3) life value in this step, then according to this rule by this component life value of computer simulation.
Step (5) is that order checks by the parts of life value minimum to the parts of life value maximum, up to finding trouble unit, finishing stage analysis monitoring.
The computational methods of unusual parts life value comprise the steps: in the inventive method step (4)
Step (41) ordering is carried out ascending order with the number of stoppages n life value of the some unusual parts of step (3) and is sorted;
Step (42) parameter estimation, calculate n life value of the number of stoppages and obey following function parameters estimated value:
Tub curve, tub curve probability density function are f (t)=beta/alpha
βExp (t/ α)
βExp[1-exp (t/ α)
β] parameter alpha and the estimated value of β, wherein, t represents the component life variable, is worth to be L, parameter alpha represents the position, parameter beta represents shape;
Weibull distribution, Weibull distribution probability density function are f (t)=α β t
β-1Exp (α t
β), wherein, variable t represents operating life, parameter alpha represents the position, parameter represents shape;
Linear increment probability density function f (t)=(at+b) exp (1/2at
2-bt), wherein, variable t represents operating life, and parameter a represents the slope of linear function, and parameter b represents intercept;
Exponential distribution, probability density function are that (at), wherein, variable t represents operating life to f (t)=α exp, and parameter alpha represents the position;
Step (43) uses the life value data after n ordering of formula k=1+3.322lgn to divide into groups, and packet count is k;
Step (44) calculated rate:
(the L apart from Δ t=is namely organized at interval between calculating group and the group
a-S
m)/k, wherein, L
aBe the maximum value in life-span, S
mBe minimum value;
Determine each group group limit value, the group limit i.e. the CLV ceiling limit value of each group
Lower limit
To organize to limit to get into and equal lower limit
And less than CLV ceiling limit value
Namely press the semi-closed interval distribute data.
Statistics falls into the frequency Δ r of each group
i, according to life time and each lower class limit value
With less than CLV ceiling limit value
Compare, if life time t
jSatisfy
Frequency Δ r then
i=Δ r
i+ 1, and pass through ω
i=Δ r
i/ n calculated rate ω
i
Step (45) is passed through
Calculate the cumulative frequency of each group, wherein, r
iCumulative frequency when finishing for organizing to i.
Calculate the distribution function F of tub curve, Weibull distribution, linear increasing function and exponential distribution respectively
i', F
i' the integration of four kinds of distribution density function f (t), 1≤i≤k wherein;
Calculate k F respectively
i, F
iIt is the cumulative frequency of i group; F
iCalculate and to obtain k individual numerical value, i.e. F by obtaining F (t) that the distribution probability functional integration obtains after the parameter estimation
i' and F
iAll there be k;
Calculate D
i=| F
i-F
i' |, get the test statistics D=max (D of K-S
1, D
2..., D
k);
Step (46) model testing is looked into the critical value D of kolmogorov test according to setting confidence level δ (generally getting 0.05,0.01) and a number of stoppages n life value
cTable draws D
c, judge whether top four kinds of distributions exist D＜D
c:
If have only a D value less than a certain critical value D
c, then the corresponding function of this D value is selected function;
If two or more D values are arranged less than a certain critical value D
c, then choosing the less corresponding function of D value is selected function;
If the D value of all four kinds of models is all more than or equal to critical value D
c, directly use mean value method to obtain its life-span average;
Step (47) is by t
i=F
-1(t
i) the i time unusual component life of simulation, wherein 1≤i≤m simulates after m time, and then this moment, equipment or part life were
Be t to its corresponding life-span calculating formula of tub curve
i=α { ln[1-ln[1-U
i]]
1/ βI=1,2 ..., the life-span calculating formula of Weibull distribution correspondence is t
i=[1/ α (ln[1-U
i])]
1/ βI=1,2 ..., the life-span calculating formula of linear increasing function correspondence is
I=1,2 ..., the life-span calculating formula of exponential distribution function correspondence is t
i=1/ α (ln[1-U
i]) i=1,2 ..., U wherein
iGet [0,1] random value;
The critical value D of kolmogorov test
cTable
Embodiment:
Present embodiment provides the applicable cases of a kind of gas compressor status parameter monitoring system and method, by gas pressure sensor 1 the detected pressures signal is passed to signal conditioner 3, through passing to PXI data collecting card (7) after the signal processing, and it is transferred in the computer, reading one-level outlet valve pressure by the LabVIEW software platform is 0.63 MPa, compare with capping 0.62 MPa, judge that exhaust pressure is higher than normal exhaust pressure, searching the unusual and fault corresponding tables of gas compressor status parameter establishes main incipient fault pattern the outlet valve damage is arranged respectively, Aspirating valves damages, excessive and the pressure gauge fault of piston ring and cylinder gap, at this moment, the application software system prompting occurs unusual and reports to the police, and starts fault diagnosis module simultaneously;
Unusual and the fault corresponding tables of gas compressor status parameter:
From database, inquire about maintenance records such as the excessive and pressure gauge fault of outlet valve, Aspirating valves, piston ring and cylinder gap by software, bring into use time and down time to calculate outlet valve, Aspirating valves, piston ring and excessive and manometric life-span of cylinder gap according to it respectively, see Table 3 (unit: hour), its corresponding number of stoppages n table 3 parts respectively detects the life-span table
| The number of stoppages | Outlet valve | Aspirating valves | Piston ring and cylinder gap | Pressure gauge |
| 1 | 2578 | 4790 | 4829 | 7890 |
| 2 | 590 | 2571 | 763 | 10957 |
| 3 | 4502 | 7725 | 7903 | 6890 |
| 4 | 1793 | 7890 | 6783 | 5372 |
| 5 | 3367 | 13481 | 9903 | 7693 |
| 6 | 2790 | 8902 | 3648 | 8738 |
| 7 | 1680 | 5704 | 6720 | 7383 |
| 8 | 4721 | 4217 | 7374 | 7562 |
| 9 | 1480 | 5820 | 6837 | 5637 |
| 10 | 2092 | 5821 | 9012 | 5694 |
| 11 | 5071 | 6890 | 5378 | 6704 |
| 12 | 2695 | 6093 | 6721 | 3783 |
| 13 | 773 | 8902 | 3264 | 7003 |
| 14 | 1679 | 3680 | 6346 | 4582 |
| 15 | 4903 | 5272 | 3267 | 7904 |
| 16 | 4720 | 6890 | 7413 | 7098 |
| 17 | 1890 | 4270 | 2367 | |
| 18 | 3805 | 9863 | 7893 | |
| 19 | 3407 | 8632 | ||
| 20 | 4704 | |||
| 21 | 3534 | |||
| 22 | 3572 | |||
| 23 | 6730 | |||
| 24 | 3107 |
Be 24,18,19 and 16, lifetime data to outlet valve sorts, obtain 590,773,1480,1659,1680,1793,1890,2092,2578,2695,2790,3072,3107,3367,3407,3534,3805,4321,4502,4704,4720,4903,5071,6730, estimate that the tub curve parameter is 3207.3 for location parameter α, form parameter β is 1.019; Weibull distribution location parameter α is 2515.7, and form parameter β is 1.141; Linear increment parameter a is 0.3271, and parameter b is 0.8352, and exponential distribution is 3508.6;
These data are divided into groups, by k=1+3.322lg24=5.585, then organize number and be approximately 6, the group interval of delta t is 1023, and six intervals are then arranged, and is respectively [590,1613), [1613,2636), [2636,3659), [3659,4682), [4682,5705) and [5705,6730], six interval frequencies are respectively 3,6,7,3,4,1, cumulative frequency F
iBe respectively 0.125,0.375,0.667,0.792,0.958 and 1.
Estimates of parameters according to top four kinds of distributions calculates t
iBe respectively 1613,2636,3659,4682,5705 and 6730 o'clock corresponding distribution functions, the test statistics D that calculates the K-S of tub curve, Weibull distribution, linear increasing function and exponential distribution respectively is respectively 0.431,0.205,0.319 and 0.496.
Given confidence level δ is 0.05, is 24 to look into the critical value D of kolmogorov test by the number of stoppages again
cTable is known D
cBe 0.268 and the test statistics D of K-S compare and know, the test statistics D that has only the K-S of Weibull distribution is 0.205 less than 0.268, judges that thus outlet valve obeys Weibull distribution, and location parameter α is 2515.7, form parameter β is 1.141;
With judging that with quadrat method the life-span of Aspirating valves is distributed as Weibull distribution, Aspirating valves Weibull distribution location parameter α is 4815.7, form parameter β is 1.017, the excessive obedience Weibull distribution of piston ring and cylinder gap, location parameter α is 7018, and form parameter β is 1.062, and pressure gauge is obeyed linear increment, parameter a is 0.2629, and parameter b is 0.7274.
At last by t
i=[1/2517 (ln[1-U
i])]
1/1.141I=1,2 ... simulating 100 its outlet valve life-spans is 2471.4 hours, by t
i=[1/4815.7 (ln[1-U
i])]
1/1.017I=1,2 ... simulating 100 its outlet valve life-spans is 4759.7 hours, by t
i=[1/7018 (ln[1-U
i])]
1/1.062I=1,2 ... simulate 100 its piston rings and cylinder gap and spend greatly 6409.8 hours, by
I=1,2 ... simulate 100 its piston rings and cylinder gap and spend greatly 5381.3 hours, these life values are sorted, by 2471.4＜4759.7＜5381.3＜6409.8, know that the parts that break down are that outlet valve, Aspirating valves, pressure gauge and piston ring and cylinder gap are excessive in proper order, check whether outlet valve breaks down this moment earlier, as do not have fault, then check Aspirating valves, by that analogy, if all do not break down, then consider whether to exist other reason.
Gas compressor status monitoring of the present invention and reliability analysis system and method are gathered dissimilar a plurality of variable data by different sensors and are obtained object information.And the graphic programming controlling method by LabVIEW, physical quantity collections such as the temperature of gas compressor, pressure, vibration can be entered into computer and analyze.By the state signal analyzing failure cause, and in conjunction with the reliability analysis technology of fault tree analysis and the aging of equipment, realize fault diagnosis and improve equipment reliability, availability level.Thereby than traditional gas compressor group monitor supervision platform, more can improve Security and the reliability of system.
The monitoring of gas compressor status parameter is to use sensor that physical quantitys such as the temperature of compressor, pressure, vibration are measured, convert suitable intermediate quantity to, as voltage or electric current, by the process of the demonstration of LabVIEW platform, identification, analysis and trend prediction.The LabVIEW platform is a kind of software platform based on instrument or virtual instrument.By the graphic programming controlling method of LabVIEW, a plurality of variable data collections of physical quantitys such as the temperature of gas compressor, pressure, vibration can be entered into computer and analyze.Data acquistion system need be used suitable sensor and hardware support kit, and will change transmission from the data that sensor obtains by corresponding software.Use the hardware product of NI company, use the LabVIEW development platform, utilize Matlab to handle the ability of complicated algorithm, the application program that meets the demands is developed on fast and high quality ground.Utilize this platform can strengthen the ability of structure science and engineering system, the convenient way that realizes instrument programming and data acquistion system is provided.Can also carry out principle research, design, test and realize instrument system by it, thereby increase work efficiency greatly.
The invention provides a kind of state analysis monitoring system of gas compressor and thinking and the method for method; method and the approach of this technological scheme of specific implementation are a lot; the above only is preferred implementation of the present invention; should be understood that; for those skilled in the art; under the prerequisite that does not break away from the principle of the invention, can also make some improvements and modifications, these improvements and modifications also should be considered as protection scope of the present invention.In the present embodiment not clear and definite each constituent element all available prior art realized.
Claims (5)
1. the state analysis monitoring method of a gas compressor, it is characterized in that, comprise gas pressure sensor (1), temperature transducer (2), signal conditioner (3), oil pressure sensor (4), vibration transducer (5), vibrometer (6), data collecting card (7), display device (8) and computer (9);
Described gas pressure sensor (1), described temperature transducer (2) and oil pressure sensor (4) are connected with described signal conditioner (3) respectively; Described vibration transducer (5) is connected with described vibrometer (6), and described vibrometer (6) and signal conditioner (3) are connected with described data collecting card (7) respectively; Described data collecting card (7) is connected with described computer (9), and described computer (9) is connected with described display device (8);
Gas pressure signal, temperature signal, engine oil pressure signal, oscillating signal are imported computer, and according to following steps above signal are handled:
Step (1) compares the upper and lower bound of gas pressure signal, temperature signal, engine oil pressure signal, oscillating signal and predefined safety value, as exceeds the upper limit or lower limit is then reported to the police, and starts fault diagnosis module simultaneously;
Step (2) is unusual and fault corresponding tables by the gas compressor status parameter of inquiry in the fault diagnosis module, thereby determines corresponding unusual variety of components, wherein, the gas compressor status parameter unusually and the fault corresponding tables be:
；
The historical maintenance record of various parts in database in the unusual variety of components of step (3) inquiry, and note L is such unusual parts value actual life, L=F-S is then arranged, wherein S represents parts and brings into use the time, F represents unusual component settings and uses terminal time, such unit failure number of times is n, and n life value then arranged;
Step (4) is at first established this part aging rule according to step (3) value actual life, then according to this rule by this component life value of computer simulation:
Step (5) is that order checks by the parts of life value minimum to the parts of life value maximum, up to finding trouble unit, finishing stage analysis monitoring.
2. the state analysis monitoring method of a kind of gas compressor according to claim 1, it is characterized in that, the signal that described signal conditioner (3) is used for gas pressure sensor (1), temperature transducer (2) and oil pressure sensor (4) are transmitted amplifies, and is transferred to data collecting card (7).
3. the state analysis monitoring method of a kind of gas compressor according to claim 1 is characterized in that, described data collecting card (7) is based on the PX bussing technique, and the signal that is used for gathering is converted into electrical signal, is transferred to computer.
4. the state analysis monitoring method of a kind of gas compressor according to claim 1 is characterized in that, described vibrometer (6) is used for oscillating signal is amplified processing, and is transferred to data collecting card (7).
5. the state analysis monitoring method of a kind of gas compressor according to claim 1 is characterized in that, described computer (9) is equipped with the LabVIEW platform software.
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| CN102494762A (en) * | 2011-12-19 | 2012-06-13 | 湖南工业大学 | Vibration testing system of cooling tower based on labview platform |
| CN103306964A (en) * | 2012-03-12 | 2013-09-18 | 上海斯可络压缩机有限公司 | Fault detection device |
| CN102926983A (en) * | 2012-11-06 | 2013-02-13 | 昆山北极光电子科技有限公司 | State inspection system for compressor unit |
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