CN110221593A - A kind of three hold the fault mode diagnostic method and system of Water Tank Control System - Google Patents
A kind of three hold the fault mode diagnostic method and system of Water Tank Control System Download PDFInfo
- Publication number
- CN110221593A CN110221593A CN201910654032.6A CN201910654032A CN110221593A CN 110221593 A CN110221593 A CN 110221593A CN 201910654032 A CN201910654032 A CN 201910654032A CN 110221593 A CN110221593 A CN 110221593A
- Authority
- CN
- China
- Prior art keywords
- fault mode
- water tank
- state
- indicate
- hold
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0243—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Testing And Monitoring For Control Systems (AREA)
Abstract
The present invention discloses the fault mode diagnostic method and system that one kind three holds Water Tank Control System, and diagnostic method includes: to model to three appearance high water tank control systems, establishes corresponding stochastic finite state automata；The schema automaton of three appearance water tanks is established according to the finite-state automata；The finite-state automata is synchronous with the schema automaton, obtain the synchronization identifier of three appearance water tanks；Hold the stochastic model diagnostor of water tank based on the synchronous identifier building three；The PA- diagnosticability for the fault mode set that three hold water tank is determined based on the stochastic model diagnostor.The above method in the present invention can be improved the accuracy for the fault mode diagnosis for holding Water Tank Control System to three.
Description
Technical field
The present invention relates to fault diagnosis fields, and the fault mode diagnosis side of Water Tank Control System is held more particularly to one kind three
Method and system.
Background technique
With the fast development of production technology, the equipment in industry also becomes more sophisticated while becoming more intelligent.In reality
In the production and living of border, equipment fault is difficult to avoid, and personnel's operating mistake, ageing equipment, system design are improper etc., all can
Equipment is caused to break down, bring is lost in order to avoid device fails, and fault diagnosis has been increasingly becoming people in recent years
The Important Problems of work one research of intelligence.System can be divided into static system and dynamical system, and the output of static system is with defeated
The variation that enters and change, and the output of dynamical system by input, the factors such as environment, runing time are influenced.Most of system
It is all dynamical system, for the ease of carrying out fault diagnosis to dynamical system, twentieth century end, it is dynamic that brainstrust proposes a kind of simulation
The new system of state system, i.e. discrete event system.Discrete event system is to take out dynamical system under discrete time point
As, and then malfunction elimination and reparation are carried out to system.In order to more accurately simulate real system, the accurate of fault diagnosis is improved
Degree, 2005, brainstrust had also been proposed Stochastic discrete event systems, and many real systems can be by being modeled as Random Discrete
Event system carries out fault diagnosis.
Three appearance high water tank control systems are that very typical teaching experiment is set in the fields such as automatic control, chemical process
Standby, it is also based on one of most typical dynamical system in Model Diagnosis, for many years, three other than it can be used for teaching experiment
Hold the research that water tank is all applied to Troubleshooting Theory.The entirety of industrial many control targets or part can be abstracted into
Three hold the mathematical model of water tank, therefore three hold water tank with very strong representative and industrial background, realize and examine three appearance water tanks
It is disconnected, it can to realize the diagnosis to systems many in industry.Three hold the modeling of water tank and fault diagnosis to dynamic system fault
The research of diagnosis algorithm has important theory significance and practical application value, such as Industrial Boiler, crystallizer liquid level control system, circuit
It is similar all to hold the diagnosis processes of water tank to three for system etc., therefore three appearance water tanks have stronger theoretical property and comprehensive, are failures
Important basic research in diagnosis.And existing method for diagnosing faults, it is unable to complete the mode diagnosticability for holding water tank to three
Determine.
Summary of the invention
The object of the present invention is to provide fault mode diagnostic method and system that one kind three holds Water Tank Control System, raisings pair
Three hold the accuracy of the fault mode diagnosis of Water Tank Control System.
To achieve the above object, the present invention provides following schemes:
A kind of three hold the fault mode diagnostic method of Water Tank Control System, and the diagnostic method includes:
Three appearance high water tank control systems are modeled, corresponding stochastic finite state automata is established；
The schema automaton of three appearance water tanks is established according to the finite-state automata；
The finite-state automata is synchronous with the schema automaton, obtain the synchronization identifier of three appearance water tanks；
Hold the stochastic model diagnostor of water tank based on the synchronous identifier building three；
The PA- diagnosticability for the fault mode set that three hold water tank is determined based on the stochastic model diagnostor.
Optionally, the finite-state automata is four-tuple G={ X, Σ, p, x0, wherein X indicates state space, Σ
Indicate event sets, p:X × Σ × p × x0→ [0,1] indicates partial status transition probability function, x0Indicate finity state machine
The original state of machine.
Optionally, the schema automaton is four-tuple GΩ={ XΩ,∑Ω,TΩ,x0Ω, F }, wherein XΩIntermediate scheme is certainly
The state set of motivation, ΣΩIndicate the mode event set of initiation failure, TΩThe transfer function of intermediate scheme automatic machine；x0ΩIt is
The original state of schema automaton；F indicates final state set.
Optionally, described that the finite-state automata is synchronous with the schema automaton specifically using following formula:
Wherein, function transv(x, e) indicates the transfer function of automatic machine, x1And x1' it is shape in finite-state automata
State, xΩ1And xΩ1' be schema automaton state SP indicate fault mode set.
Optionally, the described three synchronization identifiers for holding water tank are four-tuple Gsv=(Xsv,Σsv,psv,x0sv), wherein Xsv
=X × XΩIndicate state set, × indicate cartesian product, Σsv=Σ indicates event sets, psv:Xsv×Σsv×psv→[0,
1] the probability transfer function of synchronous identifier, x are indicated0sv∈XsvIndicate the original state of synchronous identifier.
Optionally, the stochastic model diagnostor is hexa-atomic group of Gpd=(Xpd,Σpd,Tpd,x0pd,Φpd,φ0pd), wherein
XpdIndicate logic state set, ΣpdIndicate Observable event, TpdIndicate transfer function, x0pd=((x0sv), { N }) indicate random
The original state of modality diagnostic device, ΦpdIndicate probability transition matrix, φ0pdIndicate the probability matrix of initial function, φ0pd=1.
Optionally, the PA- of the fault mode set that three appearance water tanks are determined based on the stochastic model diagnostor can be examined
Disconnected property specifically includes:
Determine the PA- diagnosticability of each fault mode set；
PA- diagnosticability based on the fault mode set determines that the PA- of the fault mode set of three appearance water tanks can be examined
Disconnected property.
Optionally, the PA- diagnosticability for determining each fault mode set specifically includes:
Judge the fault mode label of the component in the logic state in stochastic model diagnostor whether all comprising SP；
The logic state is that SP- determines that otherwise the logic state is SP- uncertain if all including SP；
Judge whether the corresponding probability of each component is 1；
If the corresponding probability of each component is 1, the component be it is permanent, otherwise the component is of short duration；
It defines in a stochastic finite state automata there are a circulation, if comprising permanent fault Mode S P in circulation
Logic state where component be it is fuzzy, then the fault mode set is not that PA- is diagnosable.
Optionally, the PA- diagnosticability based on the fault mode set determines the three fault mode collection for holding water tank
The PA- diagnosticability of conjunction specifically includes:
Determine the fault mode collective number in system；
If only exist a fault mode set in system, the PA- diagnosticability of system and the fault mode set
PA- diagnosticability it is identical；
If being all and if only if fault mode set all in the system there are when multiple fault mode set in system
When PA- is diagnosable, then the system is PA- diagnosable.
The present invention additionally provides the fault mode diagnostic system that one kind three holds Water Tank Control System, the diagnostic system packets
It includes:
Modeling module establishes corresponding stochastic finite state certainly for modeling to three appearance high water tank control systems
Motivation；
Schema automaton establishes module, and the mode for establishing three appearance water tanks according to the finite-state automata is automatic
Machine；
Synchronization module, for by the finite-state automata it is synchronous with the schema automaton, obtain three appearance water tanks
Synchronous identifier；
Diagnostor establishes module, for holding the stochastic model diagnostor of water tank based on the synchronous identifier building three；
Diagnosticability determining module, for determining the three fault mode set for holding water tank based on the stochastic model diagnostor
PA- diagnosticability.
The specific embodiment provided according to the present invention, the invention discloses following technical effects:
By modeling to three appearance high water tank control systems, establish corresponding has at random for the above method in the present invention
Limit state automata；The schema automaton of three appearance water tanks is established according to the finite-state automata；Certainly by the finite state
Motivation is synchronous with the schema automaton, obtains the synchronization identifier of three appearance water tanks；Held based on the synchronous identifier building three
The stochastic model diagnostor of water tank；Determine that the PA- for the fault mode set that three hold water tank can based on the stochastic model diagnostor
It is diagnostic, substantially increase the accuracy for the fault mode diagnosis for holding Water Tank Control System to three.
Detailed description of the invention
It in order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, below will be to institute in embodiment
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the invention
Example, for those of ordinary skill in the art, without any creative labor, can also be according to these attached drawings
Obtain other attached drawings.
Fig. 1 is that the embodiment of the present invention three holds high water tank control system model schematic diagram；
Fig. 2 is the fault mode diagnostic method flow chart that the embodiment of the present invention three holds Water Tank Control System；
Fig. 3 is that the embodiment of the present invention three holds the corresponding stochastic finite state automata of high water tank control system；
Fig. 4 is the corresponding schema automaton of fault mode of embodiment of the present invention set { POFF, Decrease }；
Fig. 5 is the corresponding mode of fault mode of embodiment of the present invention set { PON, V4OFF, V5OFF, V6OFF, V3OFF }
Automatic machine；
Fig. 6 is the stochastic finite state automata and schema automaton that the embodiment of the present invention three holds high water tank control system
GΩ1Synchronization identifier Gsv1；
Fig. 7 is the stochastic finite state automata and schema automaton that the embodiment of the present invention three holds high water tank control system
GΩ2Synchronization identifier Gsv2；
Fig. 8 is the synchronous identifier G of stochastic model of the embodiment of the present inventionsv1Corresponding stochastic model diagnostor Gpd1；
Fig. 9 is the synchronous identifier G of stochastic model of the embodiment of the present inventionsv2Corresponding stochastic model diagnostor Gpd2；
Figure 10 is the fault mode diagnostic system structural schematic diagram that the embodiment of the present invention three holds Water Tank Control System.
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 embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
The object of the present invention is to provide fault mode diagnostic method and system that one kind three holds Water Tank Control System, raisings pair
Three hold the accuracy of the fault mode diagnosis of Water Tank Control System.
In order to make the foregoing objectives, features and advantages of the present invention clearer and more comprehensible, with reference to the accompanying drawing and specific real
Applying mode, the present invention is described in further detail.
Fig. 1 is that the embodiment of the present invention three holds high water tank control system model schematic diagram, as shown in Figure 1, the present invention simulates
Three hold high water tanks control by three glass containers (T1, T2, T3), seven valves (V0, V1, V2, V3, V4, V5, V6), one
A booster pump (Pump1) and a tank composition.Three appearance high water tank control systems are a closed systems, and working principle is such as
Under: firstly, water is added into tank, then opens booster pump Pump1 and V0, inject water into T1, then sequentially open V1, V2,
V3, water flow are circulated back in tank by V3, and V4, V5, V6 can be used for adjusting the water in glass container, pass through following for water flow
The switch of ring and V1-V6 valve controls the liquid levels of three appearance water tanks.
The following steps, specific flow chart are broadly divided into the judgement of the PA- diagnosticability of three appearance high water tank control systems
It is as shown in Figure 2:
The diagnostic method includes:
Step 101: three appearance high water tank control systems being modeled, corresponding stochastic finite state automata is established.
Wherein, the finite-state automata is four-tuple G={ X, Σ, p, x0, wherein X indicates state space, Σ table
Show event sets, p:X × Σ × p × x0→ [0,1] indicates partial status transition probability function, x0Indicate finite-state automata
Original state.
Three hold in the corresponding stochastic finite state automata of high water tank control system, state space X=C0, C1, C2,
C3, C4, C5, C6, C7, C8, C9, C10, C11, C12, C13 }, event sets be Σ=Increase, Decrease, PON,
POFF,V0ON,V1ON,V2ON,V3ON,V4ON,V5ON,V6ON,V0OFF,V1OFF,V2OFF,V3OFF,V4OFF,V5OFF,
V6OFF }, wherein Increase and Decrease, which is respectively indicated, fills the water into tank and discharges water from tank, and PON indicates to open
Corresponding valve is opened in booster pump, POFF expression closing booster pump, V1ON, V2ON, V3ON, V4ON, V5ON, V6ON expression,
Corresponding valve is closed in V0OFF, V1OFF, V2OFF, V3OFF, V4OFF, V5OFF, V6OFF expression.It is considerable in event sets
Survey event sets Σ0=Increase, Decrease, PON, POFF, V0ON, V1ON, V2ON, V3ON, V4ON, V5ON,
V6ON }, unobservable event sets Σu0={ V0OFF, V1OFF, V2OFF, V3OFF, V4OFF, V5OFF, V6OFF }, by event
{ POFF, Decrease } and { PON, V4OFF, V5OFF, V6OFF, V3OFF } in set is defined as two fault mode set,
That is POFF, Decrease, PON, V4OFF, V5OFF, V6OFF, V3OFF are normal conditions, but as { POFF, Decrease }
Or { PON, V4OFF, V5OFF, V6OFF, V3OFF }, simultaneously when occurring, system enters fault mode state.
As shown in figure 3, Fig. 3 is that the corresponding stochastic finite state of the appearance high water tank control system of the embodiment of the present invention three is automatic
Machine, in the automatic machine, C0 is the original state of system, anhydrous in tank at this time, is infused by Increase event to tank
Water, then system reaches state C1 from state C0, i.e. C1 indicates that reservoir has water, and system, which operates normally, then recycles shape in C3-C12
In state, C2 is the fault mode state that system passes through that fault mode set { POFF, Decrease } enters, and C13 is that system passes through
Another fault mode state that fault mode set { PON, V4OFF, V5OFF, V6OFF, V3OFF } enters.
Step 102: the schema automaton of three appearance water tanks is established according to the finite-state automata.
Wherein, the schema automaton is four-tuple GΩ={ XΩ,∑Ω,TΩ,x0Ω, F }, wherein XΩIntermediate scheme is automatic
The state set of machine, ΣΩIndicate the mode event set of initiation failure, TΩThe transfer function of intermediate scheme automatic machine；x0ΩIt is mould
The original state of formula automatic machine；F indicates final state set.
Specifically, can establish three appearance water box liquids by the characteristic of schema automaton and the fault mode set of system
The schema automaton of level controlling system.Figure three show the corresponding schema automaton of fault mode set { POFF, Decrease }
GΩ1, figure four show the corresponding schema automaton G of fault mode set { PON, V4OFF, V5OFF, V6OFF, V3OFF }Ω2。
Step 103: the finite-state automata is synchronous with the schema automaton, it obtains the synchronous of three appearance water tanks and knows
Other device.
The finite-state automata is synchronous with the schema automaton specifically using following formula:
Wherein, function transv(x, e) indicates the transfer function of automatic machine, x1And x1' it is shape in finite-state automata
State, xΩ1And xΩ1' be schema automaton state, SP indicate fault mode set.
The described three synchronization identifiers for holding water tank are four-tuple Gsv=(Xsv,Σsv,psv,x0sv), wherein Xsv=X × XΩ
Indicate state set, × indicate cartesian product, Σsv=Σ indicates event sets, psv:Xsv×Σsv×psv→ [0,1] indicates same
Walk the probability transfer function of identifier, x0sv∈XsvIndicate the original state of synchronous identifier.
As shown in Figure 6 and Figure 7, Fig. 6 shows the stochastic finite state automata and mode of three appearance high water tank control systems
Automatic machine GΩ1Synchronization identifier Gsv1.Fig. 7 shows the stochastic finite state automata and mould of three appearance high water tank control systems
Formula automatic machine GΩ2Synchronization identifier Gsv2.Wherein state is by by the state of stochastic finite state automata and schema automaton
Carry out what cartesian product operated；The calculating of transition probability is based on formula
In Fig. 6, { C2, P12It is a fault mode state, { C13, P2 in Fig. 75It is a fault mode state.
Step 104: holding the stochastic model diagnostor of water tank based on the synchronous identifier building three.
The stochastic model diagnostor is hexa-atomic group of Gpd=(Xpd,Σpd,Tpd,x0pd,Φpd,φ0pd), wherein XpdIt indicates
Logic state set, ΣpdIndicate Observable event, TpdIndicate transfer function, x0pd=((x0sv), { N }) indicate that stochastic model is examined
The original state of disconnected device, ΦpdIndicate probability transition matrix, φ0pdIndicate the probability matrix of initial function, φ0pd=1.
Fig. 8 is the synchronous identifier G of stochastic modelsv1Corresponding stochastic model diagnostor, Fig. 9 are the synchronous identification of stochastic model
Device Gsv2Corresponding stochastic model diagnostor.
Wherein each rectangle indicates a logic state, and include in logic state is component.Due to stochastic model
Do not include unobservable event in diagnostor, so Fig. 8 and Fig. 9 all removes unobservable event, and uses the tired side multiplied
Method calculates new probability.
{ C0, P1 in Fig. 60Corresponding diagram 8 x0, due to P10It is non-fault mode state, so x0Faulty tag be
{ N }, sequentially { C1, P10, { C2, P11, { C2, P12, { C3, P11, { C4, P11, { C5, P11, { C6, P11, { C7, P11,
{C8,P11, { C9, P11, { C10, P11, { C11, P11, { C12, P11, { C13, P11Respectively correspond state x1-x14.Wherein
{C2,P12, i.e. x3It is fault mode state, therefore x3Faulty tag be SP1.The corresponding matrix of event indicates in logic state
The probability of component conversion, such as logic state { (x1,{N}),(x2, { N }) } pass through event Decrease to logic state { (x3,
{SP1), in Fig. 6, x1({C1,P10) arrive x3({C2,P12) probability be 0.3, x2({C2,P11) arrive x3Probability be 1,
So the first row first row of homography is 0.3, the second row first row is 1.
The construction method of Fig. 9 is identical as Fig. 8, state { C0, P2 in Fig. 60, { C1, P20, { C2, P20, { C3, P21,
{C4,P21, { C5, P21, { C6, P22, { C7, P22, { C8, P22, { C9, P23, { C10, P23, { C11, P23, C12,
P24, { C13, P25, { C3, P24, { C4, P24, { C5, P24, { C6, P24, { C7, P24, { C8, P24, { C9, P24,
{C10,P24, { C11, P24Respectively correspond state x ' in Fig. 90-x’20。
Step 105: determining that the PA- for the fault mode set that three hold water tank is diagnosable based on the stochastic model diagnostor
Property.
Wherein, PA- diagnosticability is defined as:
In one stochastic finite state automata G, living, prefix closure language L is about Pj and transition probability of mapping
Set is PA- diagnosable, and if only if
Pr (t:D (st)=0 | t ∈ L/s ∧ | t |=n < τ) }
Wherein, diagnosticability conditional function is defined as follows:
Path s is the path in G, and is a failure path (set of Ψ (L) expression failure path), and mode is automatic
The sequence of events of machine, t are the subsequent paths of any sufficiently long s,Indicate the collection of event composition all in ω
It closes, Pr (t) indicates the probability in path, and L is PA- diagnosable, and the probability and if only if t is less than τ.
In Fig. 8, only logic state { (x3,{SP1) include permanent mode fault and in the circulating cycle, the logic state
It is a SP1The logic state determined, therefore fault mode set { POFF, Decrease } is PA- diagnosable.In Fig. 9,
Logic state { (x '10,{N}),(x’12,{N}),(x’13,{SP2) and { x '13,{SP2Be present in circulation and include forever
Long mode fault, however { (x '10,{N}),(x’12,{N}),(x’13,{SP2) it is a SP2Uncertain logic state,
Therefore, fault mode set { PON, V4OFF, V5OFF, V6OFF, V3OFF } is not that PA- is diagnosable.
Due to three hold high water tank control systems in exist can not be PA- diagnosable fault mode set PON, V4OFF,
V5OFF, V6OFF, V3OFF }, therefore three appearance high water tank control systems are not that PA- is diagnosable.
Figure 10 is the fault mode diagnostic system structural schematic diagram that the embodiment of the present invention three holds Water Tank Control System, such as Figure 10
Shown, the diagnostic system includes:
Modeling module 201 establishes corresponding stochastic finite state for modeling to three appearance high water tank control systems
Automatic machine；
Schema automaton establishes module 202, for establishing the mode of three appearance water tanks according to the finite-state automata certainly
Motivation；
Synchronization module 203, for by the finite-state automata it is synchronous with the schema automaton, obtain three appearance water tanks
Synchronization identifier；
Diagnostor establishes module 204, for holding the stochastic model diagnostor of water tank based on the synchronous identifier building three；
Diagnosticability determining module 205, for determining three fault modes for holding water tank based on the stochastic model diagnostor
The PA- diagnosticability of set.
Each embodiment in this specification is described in a progressive manner, the highlights of each of the examples are with other
The difference of embodiment, the same or similar parts in each embodiment may refer to each other.
Used herein a specific example illustrates the principle and implementation of the invention, and above embodiments are said
It is bright to be merely used to help understand method and its core concept of the invention；At the same time, for those skilled in the art, foundation
Thought of the invention, there will be changes in the specific implementation manner and application range.In conclusion the content of the present specification is not
It is interpreted as limitation of the present invention.
Claims (10)
1. the fault mode diagnostic method that one kind three holds Water Tank Control System, which is characterized in that the diagnostic method includes:
Three appearance high water tank control systems are modeled, corresponding stochastic finite state automata is established；
The schema automaton of three appearance water tanks is established according to the finite-state automata；
The finite-state automata is synchronous with the schema automaton, obtain the synchronization identifier of three appearance water tanks；
Hold the stochastic model diagnostor of water tank based on the synchronous identifier building three；
The PA- diagnosticability for the fault mode set that three hold water tank is determined based on the stochastic model diagnostor.
2. according to claim 1 three hold the fault mode diagnostic method of Water Tank Control System, which is characterized in that described to have
Limiting state automata is four-tuple G={ X, Σ, p, x0, wherein X indicates that state space, Σ indicate event sets, p:X × Σ
×p×x0→ [0,1] indicates partial status transition probability function, x0Indicate the original state of finite-state automata.
3. according to claim 1 three hold the fault mode diagnostic method of Water Tank Control System, which is characterized in that the mould
Formula automatic machine is four-tuple, GΩ={ XΩ,∑Ω,TΩ,x0Ω, F } wherein, XΩThe state set of intermediate scheme automatic machine, ΣΩIt indicates
Cause the mode event set of failure, TΩThe transfer function of intermediate scheme automatic machine；x0ΩIt is the original state of schema automaton；F
Indicate final state set.
4. according to claim 1 three hold the fault mode diagnostic method of Water Tank Control System, which is characterized in that described to incite somebody to action
The finite-state automata is synchronous with the schema automaton specifically to use following formula:
Wherein, function transv(x, e) indicates the transfer function of automatic machine, x1And x1' it is state in finite-state automata,
xΩ1And xΩ1' be schema automaton state, SP indicate fault mode set.
5. according to claim 1 three hold the fault mode diagnostic method of Water Tank Control System, which is characterized in that described three
The synchronization identifier for holding water tank is four-tuple Gsv=(Xsv,Σsv,psv,x0sv), wherein Xsv=X × XΩIndicate state set, ×
Indicate cartesian product, Σsv=Σ indicates event sets, psv:Xsv×Σsv×psv→ [0,1] indicates the probability of synchronous identifier
Transfer function, x0sv∈XsvIndicate the original state of synchronous identifier.
6. it is according to claim 1 three hold Water Tank Control System fault mode diagnostic method, which is characterized in that it is described with
Machine modality diagnostic device is hexa-atomic group of Gpd=(Xpd,Σpd,Tpd,x0pd,Φpd,φ0pd), wherein XpdIndicate logic state set,
ΣpdIndicate Observable event, TpdIndicate transfer function, x0pd=((x0sv), { N }) indicate stochastic model diagnostor initial shape
State, ΦpdIndicate probability transition matrix, φ0pdIndicate the probability matrix of initial function, φ0pd=1.
7. according to claim 1 three hold the fault mode diagnostic method of Water Tank Control System, which is characterized in that the base
Determine that the PA- diagnosticability of the fault mode set of three appearance water tanks specifically includes in the stochastic model diagnostor:
Determine the PA- diagnosticability of each fault mode set；
PA- diagnosticability based on the fault mode set determines the PA- diagnosticability for the fault mode set that three hold water tank.
8. according to claim 7 three hold the fault mode diagnostic method of Water Tank Control System, which is characterized in that described to sentence
The PA- diagnosticability of each fixed fault mode set specifically includes:
Judge the fault mode label of the component in the logic state in stochastic model diagnostor whether all comprising SP；
The logic state is that SP- determines that otherwise the logic state is SP- uncertain if all including SP；
Judge whether the corresponding probability of each component is 1；
If the corresponding probability of each component is 1, the component be it is permanent, otherwise the component is of short duration；
It defines in a stochastic finite state automata there are a circulation, if in circulation including the component of permanent fault Mode S P
The logic state at place be it is fuzzy, then the fault mode set is not that PA- is diagnosable.
9. according to claim 7 three hold the fault mode diagnostic method of Water Tank Control System, which is characterized in that the base
Determine that the PA- diagnosticability of the fault mode set of three appearance water tanks is specifically wrapped in the PA- diagnosticability of the fault mode set
It includes:
Determine the fault mode collective number in system；
If only exist a fault mode set in system, the PA- of the PA- diagnosticability of system and the fault mode set
Diagnosticability is identical；
If there are when multiple fault mode set in system, and if only if fault mode set all in the system be all PA-
When diagnosable, then the system is PA- diagnosable.
10. the fault mode diagnostic system that one kind three holds Water Tank Control System, which is characterized in that the diagnostic system includes:
Modeling module establishes corresponding stochastic finite state automata for modeling to three appearance high water tank control systems；
Schema automaton establishes module, for establishing the schema automaton of three appearance water tanks according to the finite-state automata；
Synchronization module, for by the finite-state automata it is synchronous with the schema automaton, obtain the synchronization of three appearance water tanks
Identifier；
Diagnostor establishes module, for holding the stochastic model diagnostor of water tank based on the synchronous identifier building three；
Diagnosticability determining module, for the fault mode set based on three appearance water tanks of stochastic model diagnostor judgement
PA- diagnosticability.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910654032.6A CN110221593B (en) | 2019-07-19 | 2019-07-19 | Fault mode diagnosis method and system for three-tank control system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910654032.6A CN110221593B (en) | 2019-07-19 | 2019-07-19 | Fault mode diagnosis method and system for three-tank control system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110221593A true CN110221593A (en) | 2019-09-10 |
| CN110221593B CN110221593B (en) | 2021-05-04 |
Family
ID=67812587
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910654032.6A Active CN110221593B (en) | 2019-07-19 | 2019-07-19 | Fault mode diagnosis method and system for three-tank control system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110221593B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109725528A (en) * | 2018-11-13 | 2019-05-07 | 广东工业大学 | The failure predictability detection method and failure predictor of discrete event system |
| CN114268557A (en) * | 2021-12-17 | 2022-04-01 | 中国农业银行股份有限公司 | Fault detection method, device, equipment and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2013071931A1 (en) * | 2011-11-15 | 2013-05-23 | Kk-Electronic A/S | A system and method for identifying suggestions to remedy wind turbine faults |
| CN108458885A (en) * | 2017-11-30 | 2018-08-28 | 镇江赛尔尼柯自动化有限公司 | Ship Remote Fault Diagnosis and Decision-making support system |
| CN108805256A (en) * | 2018-08-07 | 2018-11-13 | 南京工业大学 | Photovoltaic module method for diagnosing faults based on cuckoo algorithm and BP neural network |
| CN109507526A (en) * | 2018-10-29 | 2019-03-22 | 山东大学 | Fault Diagnosis Method for Distribution Networks based on synchronous phasor measurement and covariance matrix theory |
| CN109977581A (en) * | 2019-04-04 | 2019-07-05 | 长春理工大学 | A kind of Stochastic discrete event systems mode diagnosticability determination method |
-
2019
- 2019-07-19 CN CN201910654032.6A patent/CN110221593B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2013071931A1 (en) * | 2011-11-15 | 2013-05-23 | Kk-Electronic A/S | A system and method for identifying suggestions to remedy wind turbine faults |
| CN108458885A (en) * | 2017-11-30 | 2018-08-28 | 镇江赛尔尼柯自动化有限公司 | Ship Remote Fault Diagnosis and Decision-making support system |
| CN108805256A (en) * | 2018-08-07 | 2018-11-13 | 南京工业大学 | Photovoltaic module method for diagnosing faults based on cuckoo algorithm and BP neural network |
| CN109507526A (en) * | 2018-10-29 | 2019-03-22 | 山东大学 | Fault Diagnosis Method for Distribution Networks based on synchronous phasor measurement and covariance matrix theory |
| CN109977581A (en) * | 2019-04-04 | 2019-07-05 | 长春理工大学 | A kind of Stochastic discrete event systems mode diagnosticability determination method |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109725528A (en) * | 2018-11-13 | 2019-05-07 | 广东工业大学 | The failure predictability detection method and failure predictor of discrete event system |
| CN114268557A (en) * | 2021-12-17 | 2022-04-01 | 中国农业银行股份有限公司 | Fault detection method, device, equipment and storage medium |
| CN114268557B (en) * | 2021-12-17 | 2023-10-03 | 中国农业银行股份有限公司 | Fault detection method, device, equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110221593B (en) | 2021-05-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Rudie et al. | Minimal communication in a distributed discrete-event system | |
| Benveniste et al. | Diagnosis of asynchronous discrete-event systems: a net unfolding approach | |
| Sampath et al. | Active diagnosis of discrete-event systems | |
| Ploennigs et al. | Adapting semantic sensor networks for smart building diagnosis | |
| Carvalho et al. | Generalized robust diagnosability of discrete event systems | |
| CN101657766A (en) | Be used for the online fault detect of distributed factory control systems and avoid framework | |
| CN110221593A (en) | A kind of three hold the fault mode diagnostic method and system of Water Tank Control System | |
| CN105426680A (en) | Characteristic configuration-based fault tree generation method | |
| CN104142451B (en) | Secondary circuit simulated failure investigation Simulation Methods and system in power system | |
| CN109977581A (en) | A kind of Stochastic discrete event systems mode diagnosticability determination method | |
| CN107450517A (en) | A kind of safe diagnosability determination method of Stochastic discrete event systems and system | |
| Cabral et al. | Online fault diagnosis of modular discrete-event systems | |
| Fanti et al. | Fault diagnosis and identification of discrete event systems using Petri nets | |
| CN108768750A (en) | Communication network failure localization method and device | |
| CN103761387A (en) | Formal verification method for sequencing specification of FPGA (field programmable gate array) combinatorial logic system | |
| CN102253663B (en) | Leakage fault diagnose method and system thereof for networked three-container water tank system | |
| Garcia et al. | Centralized modular diagnosis and the phenomenon of coupling | |
| Schumann et al. | Diagnosis of discrete-event systems using binary decision diagrams | |
| Daigle et al. | Improving multiple fault diagnosability using possible conflicts | |
| Liu et al. | Diagnosis of labeled time petri nets using time interval splitting | |
| Ye et al. | Diagnosability analysis of discrete event systems with autonomous components | |
| CN108920939A (en) | Information security method of discrimination, system and relevant apparatus based on Learner diagnosis device | |
| Schmidt et al. | Active diagnosis of deterministic I/O automata | |
| CN104808645A (en) | Discrete event system fault diagnosis method | |
| Subramanian et al. | Qualitative multiple-fault diagnosis of continuous dynamic systems using behavioral modes |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |