CN110082103A - A kind of nozzle of steam turbine cut-off shaft system unstability fault early warning method - Google Patents
A kind of nozzle of steam turbine cut-off shaft system unstability fault early warning method Download PDFInfo
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- CN110082103A CN110082103A CN201810387926.9A CN201810387926A CN110082103A CN 110082103 A CN110082103 A CN 110082103A CN 201810387926 A CN201810387926 A CN 201810387926A CN 110082103 A CN110082103 A CN 110082103A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M13/00—Testing of machine parts
- G01M13/02—Gearings; Transmission mechanisms
- G01M13/028—Acoustic or vibration analysis
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M13/00—Testing of machine parts
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Abstract
The present invention discloses a kind of nozzle of steam turbine cut-off shaft system unstability fault early warning method, comprising: adjustment operating states of the units runs unit under single valve mode, acquisition different load, the axis vibration of different main vapour pressure tubine #1~#3 bearings, watt warm data；#1~#3 bearing liner temperature, Shaft chattering fluctuation a reference value and changing value are calculated according to data collected；Establish shaft system fault diagnosis model；According to the shaft system fault diagnosis model customizing shaft train instability fault pre-alarming mechanism built, to judge steam turbine with the presence or absence of shaft train instability failure, the judgment method: if the online monitoring data of unit is more than required early warning value, then it represents that unit has shaft train instability.This method changes the overload alarm mechanism used when traditional shafting stability monitoring, introduces new shaft train instability fault pre-alarming mechanism, realizes accurate warning function of the steam turbine under nozzle governing mode, effectively promotes unit safe running performance.
Description
Technical field
The present invention relates to the dispatching of power netwoks communications field, in particular to a kind of turbine shafting stability diagnosis and on-line monitoring
Method and device.
Background technique
Currently, in face of the energy is increasingly depleted and environmental pollution gets worse the equal Consensus problem of the mankind, large-scale development benefit
The important energy development strategy in various countries is had become with behaves such as the new energy such as wind-powered electricity generation, solar energy, development energy-saving and emission-reduction.Due to firepower
Generate electricity the leading position constituted in China's installation, and therefore, many high-power fired power generating units, which participate in depth peak regulation, becomes imperative,
To stabilize the random fluctuation characteristic of new energy electric power.Also, each power plant not only sufficiently excavates the energy-saving potential of unit, takes various
Ways and means reduce coal consumption for power generation as much as possible, to save cost of electricity-generating, improve the advantage in online competition；Moreover, right
Unit carries out various transformations.In order to improve the economy of unit, steam turbine all uses cut-out governing side when practical stability is run
Formula.But in recent years as the development of high parameter large sized unit is gone into operation, nozzle governing failure is more prominent.Many documents are all
Once the various problems occurred in handoff procedure for unit, such as vibration of high pitch, it is uneven to the active force of high pressure rotor,
The fluctuation of speed is larger etc. to propose relevant solution, and effect highly significant in practical applications；Also there are many researchs
Person's problem larger for Perturbation of Unit Load in single valve/sequence valve handoff procedure, proposes using proper extension valve transfer
The method of time come eliminate unit appearance substantially load fluctuation.However, the high-power vapour of many high parameters being currently running now
Turbine former design pattern since the method for operation deviates, so that various shaft train instability failures are frequently occurred, current most of research
All concentrate on how asking by adjusting the degree of overlapping of each regulating valve, amendment the methods of valve characteristic curve to solve the safety of unit
Topic.And be used to examine the rational online comprehensive estimation method of the high pitch nozzle governing rule of steam turbine, there are no correlations to discuss.
Currently, the monitoring system in unit is also integrated with some parameter real time monitoring functions relevant to shafting failure, such as
To the on-line monitoring of the data such as a watt temperature, axis vibration.But the method for traditional monitoring watt temperature, axis vibration is to establish watt temperature, axis vibration, bear
Variation tendency between the time-domain curve or Wa Wen-load of lotus, axis vibration-load is reported automatically when monitor value is more than setting value
It is alert.But turbine shafting unstability failure not occurs suddenly, all there is certain development trend, and overload alarm mechanism does not have
Have and realizes fault pre-alarming function using this trend.Therefore, existing overload alarm mechanism and on-line monitoring are unfavorable for
The fault diagnosis of turbine shafting destabilization problems easily neglects the potential failure of unit.Inherently consider, to being in nozzle
For steam turbine under shaping modes, shafting unstability is the offset of turbine rotor caused by uneven air-flow power, is generated
Axis vibration, that thus causes lubricating oil unevenly causes a watt warm variation respectively.Control Stage of Steam Turbine generates uneven air-flow power
Two big principal elements are valve opening sequence and valve opening, and the shafting stability problem as caused by valve opening sequencing problem
It can be solved by optimization valve opening sequence.If still there is shaft train instability after optimization, it can determine that the problem by valve
Caused by aperture, therefore, for the Steam Turbine under cut-out governing mode, establishes one kind and be related to uneven air-flow power effect vapour
The early warning mechanism of turbine shaft train instability failure is just particularly important.
Summary of the invention
The main object of the present invention is to propose a kind of diagnosis of turbine shafting stability and on-line monitoring method, it is intended to be overcome
Problem above.
To achieve the above object, a kind of turbine shafting stability diagnosis proposed by the present invention and on-line monitoring method, packet
Include following steps:
S10 adjusts operating states of the units, runs unit under single valve mode, acquisition different load, different main vapour pressures
The axis vibration of tubine #1~#3 bearing, watt warm data, load be chosen for respectively rated load 50%, 60%, 70%,
80%, 90%, 100%, pressure is chosen for the minimum main vapour pressure P allowed under sliding pressure operation mode after governing stageM mono-, it is maximum main
Steam pressure
S20 calculates #1~#3 Shaft chattering fluctuation, bearing liner temperature a reference value S according to S10 data collected0, T0With changing value Δ
S,ΔT；
S30 establishes shaft system fault diagnosis model, including bearing liner temperature diagnostic model, bearing axis vibration diagnostic model；
The shaft system fault diagnosis model customizing shaft train instability fault pre-alarming mechanism that S40 is built according to S30, to judge steam turbine
With the presence or absence of shaft train instability failure, the judgment method: if the online monitoring data of unit is more than early warning value required by S30, then it represents that
There is shaft train instability in unit.
Preferably, the S20 includes:
S201 calculates #1~#3 Shaft chattering fluctuation, bearing liner temperature a reference value S0, T0, calculation formula is as follows:
Wherein, SOne、TOneEach bearing axis vibration for being acquired in respectively S10, watt warm data, i ∈ [1, n]；
S202 calculates #1~#3 Shaft chattering fluctuation, bearing liner temperature variation delta S, Δ T, and calculation formula is as follows:
Wherein, SOne、TOneEach bearing axis vibration for being acquired in respectively S10, watt warm data, i ∈ [1, n]；
S203 judges that unit with the presence or absence of shafting failure, judges base by bearing liner temperature, Shaft chattering fluctuation a reference value and variable quantity
Standard is S0Not higher than 100 μm, T0Not higher than 85 DEG C, after being more than maximum value, can determine that unit, there are shafting failures.
Preferably, the S30 includes:
S301 establishes bearing liner temperature diagnostic model:
S=S0+ΔS+δS
Wherein, S0For Shaft chattering fluctuation a reference value；Δ S is Shaft chattering fluctuation variable quantity；δSIt=10 μm, shakes for diagnostic model bearing
Dynamic allowance.
S302 establishes bearing axis vibration diagnostic model:
T=T0+ΔT+δT
Wherein, T0For bearing liner temperature a reference value；Δ T is bearing liner temperature variable quantity；δTValue range be 3~5 DEG C, to examine
Disconnected model bearing liner temperature allowance.
The invention also discloses a kind of diagnosis of turbine shafting stability and on-Line Monitor Devices, for realizing above-mentioned side
Method comprising:
Acquisition module runs unit under single valve mode for adjusting operating states of the units, acquisition different load, no
Axis vibration, watt warm data with main vapour pressure tubine #1~#3 bearing, load be chosen for respectively rated load 50%,
60%, 70%, 80%, 90%, 100%, pressure is chosen under sliding pressure operation mode the minimum main vapour pressure allowed after governing stage
PM mono-, maximum main vapour pressure
Computing module, for calculating #1~#3 bearing liner temperature, Shaft chattering fluctuation benchmark according to acquisition module data collected
Value S0, T0With changing value Δ S, Δ T；
Modeling module is examined for establishing shaft system fault diagnosis model including bearing liner temperature diagnostic model, the vibration of bearing axis
Disconnected model；
Judgment module, the shaft system fault diagnosis model customizing shaft train instability fault pre-alarming machine for being built according to modeling module
System, to judge steam turbine with the presence or absence of shaft train instability failure, the judgment method: if the online monitoring data of unit is more than S30 institute
Seek early warning value, then it represents that unit has shaft train instability.
Preferably, the computing module includes:
Reference cell, for calculating #1~#3 Shaft chattering fluctuation, bearing liner temperature a reference value S0, T0, calculation formula is as follows:
Wherein, SOne、TOneEach bearing axis vibration for being acquired in respectively S10, watt warm data, i ∈ [1, n]；
Change unit, for calculating #1~#3 Shaft chattering fluctuation, bearing liner temperature variation delta S, Δ T, calculation formula is as follows:
Wherein, SOne、TOneEach bearing axis vibration for being acquired in respectively S10, watt warm data, i ∈ [1, n],
Initial decision unit, for judging unit with the presence or absence of axis by bearing liner temperature, Shaft chattering fluctuation a reference value and variable quantity
It is failure, judges benchmark for S0Not higher than 100 μm, T0Not higher than 85 DEG C, after being more than maximum value, can determine that unit, there are shaftings
Failure.
Preferably, the modeling module includes:
Bearing liner temperature diagnosis unit, for establishing bearing liner temperature diagnostic model:
S=S0+ΔS+δS
Wherein, S0For Shaft chattering fluctuation a reference value；Δ S is Shaft chattering fluctuation variable quantity；δSIt=10 μm, shakes for diagnostic model bearing
Dynamic allowance.
Bearing axis vibration diagnosis unit, for establishing bearing axis vibration diagnostic model:
T=T0+ΔT+δT
Wherein, T0For bearing liner temperature a reference value；Δ T is bearing liner temperature variable quantity；δTValue range be 3~5 DEG C, to examine
Disconnected model bearing liner temperature allowance.
It is weaker in order to solve malfunction monitoring ability existing for existing unit axis stability on-line monitoring method, cause
Failure is unable to monitor, thus the problem of extreme influence peak load regulation flexibility, so proposing a kind of turbine shafting stability
Diagnosis and on-line monitoring method, method of the invention change the monitoring mechanism of traditional turbine shafting unstability failure, utilize list
Safe operation data under valve mode establish fault diagnosis model, realize the fault pre-alarming to turbine shafting destabilization problems.?
Data acquisition phase, it is contemplated that the instable factors such as unit different load, different main vapour pressures, using the data as calculating base
Plinth fluctuates reference values X calculating0It embodies caused by the instable factors such as device characteristics and the steam quality of steam turbine armature spindle itself
Fluctuation.When realizing the fault pre-alarming function under nozzle governing mode, the principal element imbalance gas of generation unstability failure
Stream masterpiece is emphasis factor, is produced by the pattern differentials between fluctuating change amount Δ X and single valve mode/nozzle governing both modes
Raw fluctuation empirical value δ embodies.Wherein, when calculating fluctuation a reference value and variable quantity, unit can be judged by calculating data
Itself whether there is shafting failure problems.
The invention has the benefit that
A kind of nozzle of steam turbine cut-off shaft system unstability fault early warning method of the invention, using when turbine single-valve mode not
Operation data under same load, different main vapour pressures establishes the fault diagnosis model under nozzle governing mode, at runtime not
Airflow balancing power considers other secondary instable factors as main instable factor simultaneously.This method changes traditional
The overload alarm mechanism that shafting stability uses when monitoring, introduces new shaft train instability fault pre-alarming mechanism.This method can
It realizes accurate warning function of the steam turbine under nozzle governing mode, effectively promotes unit safe running performance.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with
The structure shown according to these attached drawings obtains other attached drawings.
Fig. 1 is the flow diagram of the diagnosis of turbine shafting stability and on-line monitoring method of the invention；
Fig. 2 is unit sliding pressure operation curve graph；
Fig. 3 is the axis vibration axis vibration time-domain diagram in one embodiment of the invention actual motion state；
Fig. 4 is axis vibration-valve bit instruction figure in one embodiment of the invention actual motion state；
Fig. 5 is the law curve figure that the unit bearing shell random groups main valve bit instruction of one embodiment of the invention changes,
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiment is only a part of the embodiments of the present invention, instead of all the embodiments.Base
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts it is all its
His embodiment, shall fall within the protection scope of the present invention.
It is to be appreciated that if relating to directionality instruction (such as up, down, left, right, before and after ...) in the embodiment of the present invention,
Then directionality instruction be only used for explain under a certain particular pose (as shown in the picture) between each component relative positional relationship,
Motion conditions etc., if the particular pose changes, directionality instruction is also correspondingly changed correspondingly.
In addition, being somebody's turn to do " first ", " second " etc. if relating to the description of " first ", " second " etc. in the embodiment of the present invention
Description be used for description purposes only, be not understood to indicate or imply its relative importance or implicitly indicate indicated skill
The quantity of art feature." first " is defined as a result, the feature of " second " can explicitly or implicitly include at least one spy
Sign.It in addition, the technical solution between each embodiment can be combined with each other, but must be with those of ordinary skill in the art's energy
It is enough realize based on, will be understood that the knot of this technical solution when conflicting or cannot achieve when occurs in the combination of technical solution
Conjunction is not present, also not the present invention claims protection scope within.
As shown in Figs. 1-5, a kind of turbine shafting stability diagnosis proposed by the present invention and on-line monitoring method, including such as
Lower step:
S10 adjusts operating states of the units, runs unit under single valve mode, acquisition different load, different main vapour pressures
The axis vibration of tubine #1~#3 bearing, watt warm data, load be chosen for respectively rated load 50%, 60%, 70%,
80%, 90%, 100%, pressure is chosen for the minimum main vapour pressure P allowed under sliding pressure operation mode after governing stageM mono-, it is maximum main
Steam pressure
S20 calculates #1~#3 Shaft chattering fluctuation, bearing liner temperature a reference value S according to S10 data collected0, T0With changing value Δ
S,ΔT；
S30 establishes shaft system fault diagnosis model, including bearing liner temperature diagnostic model, bearing axis vibration diagnostic model；
The shaft system fault diagnosis model customizing shaft train instability fault pre-alarming mechanism that S40 is built according to S30, to judge steam turbine
With the presence or absence of shaft train instability failure, the judgment method: if the online monitoring data of unit is more than early warning value required by S30, then it represents that
There is shaft train instability in unit.
Preferably, the S20 includes:
S201 calculates #1~#3 Shaft chattering fluctuation, bearing liner temperature a reference value S0, T0, calculation formula is as follows:
Wherein, SOne、TOneEach bearing axis vibration for being acquired in respectively S10, watt warm data, i ∈ [1, n]；
S202 calculates #1~#3 Shaft chattering fluctuation, bearing liner temperature variation delta S, Δ T, and calculation formula is as follows:
Wherein, SOne、TOneEach bearing axis vibration for being acquired in respectively S10, watt warm data, i ∈ [1, n]；
S203 judges that unit with the presence or absence of shafting failure, judges base by bearing liner temperature, Shaft chattering fluctuation a reference value and variable quantity
Standard is S0Not higher than 100 μm, T0Not higher than 85 DEG C, after being more than maximum value, can determine that unit, there are shafting failures.
Preferably, the S30 includes:
S301 establishes bearing liner temperature diagnostic model:
S=S0+ΔS+δS
Wherein, S0For Shaft chattering fluctuation a reference value；Δ S is Shaft chattering fluctuation variable quantity；δSIt=10 μm, shakes for diagnostic model bearing
Dynamic allowance.
S302 establishes bearing axis vibration diagnostic model:
T=T0+ΔT+δT
Wherein, T0For bearing liner temperature a reference value；Δ T is bearing liner temperature variable quantity；δTValue range be 3~5 DEG C, to examine
Disconnected model bearing liner temperature allowance.
The invention also discloses a kind of diagnosis of turbine shafting stability and on-Line Monitor Devices, for realizing above-mentioned side
Method comprising:
Acquisition module runs unit under single valve mode for adjusting operating states of the units, acquisition different load, no
Axis vibration, watt warm data with main vapour pressure tubine #1~#3 bearing, load be chosen for respectively rated load 50%,
60%, 70%, 80%, 90%, 100%, pressure is chosen under sliding pressure operation mode the minimum main vapour pressure allowed after governing stage
PM mono-, maximum main vapour pressure
Computing module, for calculating #1~#3 bearing liner temperature, Shaft chattering fluctuation benchmark according to acquisition module data collected
Value X0With changing value Δ X；
Modeling module is examined for establishing shaft system fault diagnosis model including bearing liner temperature diagnostic model, the vibration of bearing axis
Disconnected model；
Judgment module, the shaft system fault diagnosis model customizing shaft train instability fault pre-alarming machine for being built according to modeling module
System, to judge steam turbine with the presence or absence of shaft train instability failure, the judgment method: if the online monitoring data of unit is more than S30 institute
Seek early warning value, then it represents that unit has shaft train instability.
Preferably, the computing module includes:
Reference cell calculates #1~#3 Shaft chattering fluctuation, bearing liner temperature a reference value S0, T0, calculation formula is as follows:
Wherein, SOne、TOneEach bearing axis vibration for being acquired in respectively S10, watt warm data, i ∈ [1, n]；
Change unit calculates #1~#3 Shaft chattering fluctuation, bearing liner temperature variation delta S, Δ T, and calculation formula is as follows:
Wherein, SOne、TOneEach bearing axis vibration for being acquired in respectively S10, watt warm data, i ∈ [1, n],
Initial decision unit, for judging unit with the presence or absence of axis by bearing liner temperature, Shaft chattering fluctuation a reference value and variable quantity
It is failure, judges benchmark for S0Not higher than 100 μm, T0Not higher than 85 DEG C, after being more than maximum value, can determine that unit, there are shaftings
Failure.
Preferably, the modeling module includes:
Bearing liner temperature diagnosis unit, for establishing bearing liner temperature diagnostic model:
S=S0+ΔS+δS
Wherein, S0For Shaft chattering fluctuation a reference value；Δ S is Shaft chattering fluctuation variable quantity；δSIt=10 μm, shakes for diagnostic model bearing
Dynamic allowance.
Bearing axis vibration diagnosis unit, for establishing bearing axis vibration diagnostic model:
T=T0+ΔT+δT
Wherein, T0For bearing liner temperature a reference value；Δ T is bearing liner temperature variable quantity；δTValue range be 3~5 DEG C, to examine
Disconnected model bearing liner temperature allowance.
Specific practical operation example；
Step 1: adjustment operating states of the units runs unit under single valve mode.Acquire different load, different main vapour
The axis vibration of pressure tubine #1~#3 bearing, watt warm data, load be chosen for respectively rated load 50%, 60%, 70%,
80%, 90%, 100%.Pressure is chosen for the minimum main vapour pressure P allowed under sliding pressure operation mode after governing stageM mono-, it is maximum main
Steam pressureAs shown in table 1, table 2；
Table 1#1~#3 bear vibration data acquisition tables
Table 2#1~#3 bearing liner temperature data acquisition tables
Step 2: #1~#3 bearing liner temperature, Shaft chattering fluctuation reference values X are calculated by the data acquired in step 10 (X0Respectively
Indicate axis vibration a reference value S0With a watt warm a reference value T0) and changing value Δ X (Δ X respectively indicate axis vibration variation delta S and Wa Wen variation
Measure Δ T), specific steps are as follows:
Step 2 one: #1~#3 Shaft chattering fluctuation, bearing liner temperature a reference value S are calculated0, T0, calculation formula is as follows:
Wherein, SOne、TOneEach bearing axis vibration for respectively being acquired in step 1, watt warm data.The value of i is 1,2,3 ...
n。
Step 2 two: calculating #1~#3 Shaft chattering fluctuation, bearing liner temperature variation delta S, Δ T, and calculation formula is as follows:
Step 2 three: judge that unit with the presence or absence of shafting failure, is sentenced by bearing liner temperature, Shaft chattering fluctuation a reference value and variable quantity
Disconnected benchmark is S0Not higher than 100 μm, T0Not higher than 85 DEG C, after being more than maximum value, can determine that unit, there are shafting failures.
Step 3: establishing shaft system fault diagnosis model, specific steps are as follows:
Step 3 one: bearing liner temperature diagnostic model is established:
S=S0+ΔS+δS
Wherein, S0For Shaft chattering fluctuation a reference value；Δ S is Shaft chattering fluctuation variable quantity；δSIt=10 μm, shakes for diagnostic model bearing
Dynamic allowance.
Step 3 two: bearing axis vibration diagnostic model is established:
T=T0+ΔT+δT
Wherein, T0For bearing liner temperature a reference value；Δ T is bearing liner temperature variable quantity；δTValue range be 3~5 DEG C, to examine
Disconnected model bearing liner temperature allowance.
Step 4: the model foundation shaft train instability fault pre-alarming mechanism as set by step 3 judges steam turbine with the presence or absence of axis
It is unstability failure, judgment method are as follows: whether the operational monitoring data (Wa Wen of corresponding shaft bearing, axis vibration data) of the corresponding bearing of unit
More than early warning value required by step 3, indicate that unit has shaft train instability more than early warning value.
The fault identification precision of nozzle governing shaft train instability failure can be improved in this implementation, improves the safe operation of unit
Energy.Validity and the practical engineering application value of actual test verification experimental verification this method.This method is in view of unit is in single valve
The influence of uneven air-flow power shaft stability under operating status, uneven air-flow after comprehensively considering a variety of instable factors
Masterpiece is that emphasis factor establishes fault diagnosis model.By the model realization to the warning function of shaft system of unit failure.
Present embodiment effect:
Present embodiment proposes a kind of diagnosis of turbine shafting stability and on-line monitoring method, changes traditional steamer
Arbor system failure overload alarm mechanism introduces early warning mechanism, improves fault diagnosis precision, facilitates the safety and stability fortune of unit
Simultaneously, in order to protrude the practical application value of this method, the present invention gives optimization case to row.
Fault pre-alarming function may be implemented in present embodiment, while can also be examined by calculated result in data processing link
Steam turbine rotor shaft itself is measured with the presence or absence of failure.The validity and Practical Project of actual test verification experimental verification this method are answered
With value:
(1) this method has comprehensively considered the shaft train instability factor under a variety of nozzle governing modes, is based on single valve into vapour mode
Calculating data consider each influence factor for leading to turbine shafting destabilization problems comprehensively, and the uneven gas of prominent concern
Flow the effect of power.The conclusion that different step obtains can be used for directly judging to cause the concrete reason of failure.
(2) the introduced early warning mechanism of this method can be integrated into unit on-line monitoring system, realize on-line early warning function
Energy.Therefore, there is great practical extending application value.
Beneficial effects of the present invention are verified using following embodiment:
Embodiment one:
By step 1 to step 3 data acquisition and processing, Fig. 3 is the axis vibration in embodiment actual motion state
Status monitoring figure is traditional axis vibration versus time curve figure, it can be found that traditional monitoring means is from the figure
To the simple on-line monitoring of axis vibration data, effective data can not be provided for shaft train instability failure, and monitoring data are not advised
Rule property, can not find potential failure from figure, can only remind operation people by means of overload alarm mechanism after the failure occurred
There are unstability failures for member's steam turbine bearing.Fig. 4 is the axis vibration state diagram in embodiment actual motion state, is main valve bit instruction-
Axis vibration figure, changes plan and intuitively illustrates the law curve of unit bearing shell random groups main valve bit instruction variation.In nozzle governing mode
When operation, when main valve bit instruction is smaller (unlatching of lofty tone door section), unit bearing shell vibration is in maximum rating, shakes at this time to bearing shell
It is dynamic that play a major role is uneven air-flow power.With the increase (high pitch gradually standard-sized sheet) of main valve bit instruction, the vibration of unit bearing shell
Dynamic to be gradually reduced, the function and effect of uneven air-flow power also gradually weaken.According to above-mentioned test as a result, showing by means of novel
Fault diagnosis model shaft train instability fault pre-alarming function under nozzle governing mode may be implemented.More influence factors, differentiation are important
The comprehensive analysis of degree can obtain regular conclusion from Basic monitoring data, realize to turbine shafting unstability failure
Detection, warning function.Acquisition data based on single valve mode can provide mould to diagnostic model is established under nozzle governing mode
Shape parameter, and failure can be whether there is by these parameter detecting steam turbine equipments itself.In addition, being proposed for this method is pre-
Alert mechanism can realize the on-line early warning function of shaft system of unit unstability failure with the existing on-line monitoring Platform integration of steam turbine, right
The promotion that Turbine Safety influences performance is very helpful.This method can be effectively improved the mistake of the shafting under nozzle governing mode
Steady malfunction monitoring mechanism, has great practical extending application value.
It is obvious to a person skilled in the art that invention is not limited to the details of the above exemplary embodiments, Er Qie
In the case where without departing substantially from spirit or essential attributes of the invention, the present invention can be realized in other specific forms.Therefore, no matter
From the point of view of which point, the present embodiments are to be considered as illustrative and not restrictive, and the scope of the present invention is by appended power
Benefit requires rather than above description limits, it is intended that all by what is fallen within the meaning and scope of the equivalent elements of the claims
Variation is included within the present invention.
Claims (6)
1. a kind of nozzle of steam turbine cut-off shaft system unstability fault early warning method, which comprises the steps of:
S10 adjusts operating states of the units, runs unit under single valve mode, vapour under acquisition different load, different main vapour pressures
The axis vibration of turbine #1~#3 bearing, watt warm data, load be chosen for respectively rated load 50%, 60%, 70%, 80%,
90%, 100%, pressure is chosen under sliding pressure operation mode the minimum main vapour pressure allowed, maximum main vapour pressure after governing stage；
S20 calculates #1~#3 bearing liner temperature, Shaft chattering fluctuation reference values X according to S10 data collected0With changing value Δ X；
S30 establishes shaft system fault diagnosis model, including bearing liner temperature diagnostic model, bearing axis vibration diagnostic model；
The shaft system fault diagnosis model customizing shaft train instability fault pre-alarming mechanism that S40 is built according to S30, whether to judge steam turbine
There are shaft train instability failure, the judgment methods: if the online monitoring data of unit is more than early warning value required by S30, then it represents that unit
There are problems that shaft train instability.
2. nozzle of steam turbine cut-off shaft as described in claim 1 system unstability fault early warning method, which is characterized in that 20 packet
It includes:
S201 calculates #1~#3 Shaft chattering fluctuation, bearing liner temperature a reference value S0, T0, calculation formula is as follows:
Wherein, Si、TiEach bearing axis vibration for being acquired in respectively S10, watt warm data, i ∈ [1, n]；
S202 calculates #1~#3 Shaft chattering fluctuation, bearing liner temperature variation delta S, Δ T, and calculation formula is as follows:
Wherein, Si、TiEach bearing axis vibration for being acquired in respectively S10, watt warm data, i ∈ [1, n]；
S203 judges that unit with the presence or absence of shafting failure, judges that benchmark is by bearing liner temperature, Shaft chattering fluctuation a reference value and variable quantity
Δ S is not higher than 100 μm, and Δ T is not higher than 85 DEG C, and after being more than maximum value, can determine that unit, there are shafting failures.
3. nozzle of steam turbine cut-off shaft as described in claim 1 system unstability fault early warning method, which is characterized in that the S30
Include:
S301 establishes bearing liner temperature diagnostic model:
S=S0+ΔS+δS
Wherein, S0For Shaft chattering fluctuation a reference value；Δ S is Shaft chattering fluctuation variable quantity；δS=10 μm, be that diagnostic model bear vibration is abundant
Amount.
S302 establishes bearing axis vibration diagnostic model:
T=T0+ΔT+δT
Wherein, T0For bearing liner temperature a reference value；Δ T is bearing liner temperature variable quantity；δTValue range be 3~5 DEG C, for diagnose mould
Type bearing liner temperature allowance.
4. a kind of nozzle of steam turbine cut-off shaft system unstability fault pre-alarming device characterized by comprising
Acquisition module runs unit under single valve mode, acquisition different load, different masters for adjusting operating states of the units
The axis vibration of steam pressure tubine #1~#3 bearing, watt warm data, load be chosen for respectively rated load 50%, 60%,
70%, 80%, 90%, 100%, pressure is chosen under sliding pressure operation mode the minimum main vapour pressure allowed, maximum after governing stage
Main vapour pressure；
Computing module, for calculating #1~#3 Shaft chattering fluctuation, bearing liner temperature a reference value S according to acquisition module data collected0,
T0With changing value Δ S, Δ T；
Modeling module, for establishing shaft system fault diagnosis model, including bearing liner temperature diagnostic model, bearing axis vibration diagnosis mould
Type；
Judgment module, the shaft system fault diagnosis model customizing shaft train instability fault pre-alarming mechanism for being built according to modeling module,
To judge steam turbine with the presence or absence of shaft train instability failure, the judgment method: if the online monitoring data of unit is more than pre- required by S30
Alert value, then it represents that unit has shaft train instability.
5. nozzle of steam turbine cut-off shaft as described in claim 1 system unstability fault pre-alarming device, which is characterized in that the calculating
Module includes:
Reference cell, for calculating #1~#3 Shaft chattering fluctuation, bearing liner temperature a reference value S0, T0, calculation formula is as follows:
Wherein, Si、TiEach bearing axis vibration for being acquired in respectively S10, watt warm data, i ∈ [1, n]；
Change unit, for calculating #1~#3 bearing liner temperature, Shaft chattering fluctuation variation delta S, Δ T, calculation formula is as follows:
Wherein, Si、TiEach bearing axis vibration for being acquired in respectively S10, watt warm data, i ∈ [1, n],
Initial decision unit, for judging unit with the presence or absence of shafting event by bearing liner temperature, Shaft chattering fluctuation a reference value and variable quantity
Barrier, judges benchmark for S0Not higher than 100 μm, T0Not higher than 85 DEG C, after being more than maximum value, can determine that unit, there are shafting failures.
6. nozzle of steam turbine cut-off shaft as described in claim 1 system unstability fault early warning method, which is characterized in that the modeling
Module includes:
Bearing liner temperature diagnosis unit, for establishing bearing liner temperature diagnostic model:
S=S0+ΔS+δS
Wherein, S0For Shaft chattering fluctuation a reference value；Δ S is Shaft chattering fluctuation variable quantity；δS=10 μm, be that diagnostic model bear vibration is abundant
Amount.
Bearing axis vibration diagnosis unit, for establishing bearing axis vibration diagnostic model:
T=T0+ΔT+δT
Wherein, T0For bearing liner temperature a reference value；Δ T is bearing liner temperature variable quantity；δTValue range be 3~5 DEG C, for diagnose mould
Type bearing liner temperature allowance.
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