CN114638469A - Garbage incinerator fault risk assessment method based on fuzzy Petri network - Google Patents

Garbage incinerator fault risk assessment method based on fuzzy Petri network Download PDF

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CN114638469A
CN114638469A CN202210130607.6A CN202210130607A CN114638469A CN 114638469 A CN114638469 A CN 114638469A CN 202210130607 A CN202210130607 A CN 202210130607A CN 114638469 A CN114638469 A CN 114638469A
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罗小平
李景生
许静姝
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South China University of Technology SCUT
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Abstract

The invention discloses a fuzzy Petri net-based garbage incinerator fault risk assessment method, which comprises the following steps: evaluating the possible fault state risk in the operation process of each subsystem of the garbage incinerator; evaluating the condition events and relative probabilities of occurrence of each fault state; constructing a fuzzy Petri network graph model; generating an input matrix, an output matrix, a library confidence vector and a transition confidence vector by combining the fault state, the fault state possibility, the condition event and the relative probability of the condition event of the garbage incinerator; converting the graph model into a mathematical model and performing iterative operation; finally, the possibility of key faults of the garbage incinerator is obtained. The method overcomes the defect that the conventional risk assessment method is mainly based on qualitative analysis, can quantitatively obtain the possibility of various faults, effectively utilizes the structure of the fuzzy Petri network, considers the concurrent faults among subsystems and improves the reliability of fault diagnosis.

Description

Garbage incinerator fault risk assessment method based on fuzzy Petri network
Technical Field
The invention relates to the field of garbage incineration fault risk assessment, in particular to a garbage incinerator fault risk assessment method based on a fuzzy Petri network
Background
The incineration has the advantages of small occupied area, high treatment efficiency, environmental protection, energy conservation and the like, meanwhile, the components of the household garbage are complex, the operation condition of the garbage incinerator is complex, the fault occurrence process is often uncontrollable, once a fault occurs, the furnace is shut down and the production is stopped if the fault occurs, and explosion and fire disasters occur if the fault occurs, so that the damage to personnel, economy and environment can be brought. The core of the fault risk assessment is that the arrangement of early operation and maintenance can be utilized, the existing resources are combined for integrated utilization, the control of key fault points is realized, and faults are prevented.
Common evaluation methods are: safety checklists, accident tree analysis, pre-hazard analysis, event tree analysis, and risk and operability studies, fault type and impact analysis, fuzzy comprehensive evaluation, exponential evaluation, and the like. Only the accident tree and the event tree analysis can describe the process of simple accidents caused by concurrency, the operating system of the garbage incinerator has typical randomness characteristics, the garbage incinerator is a complex system related to the joint operation of a plurality of devices, the traditional fault risk evaluation method is difficult to realize fine evaluation, the structural elements of the Petri network have strong capability of describing the concurrent events, and the fault evaluation on the garbage incinerator is rarely researched at present by representing the conditions of system change and the system states before and after the change, describing various possible activity states in the system and the interrelation between the change and the change of the activity states.
In the prior art, for example, in a patent application 'power system fault processing method based on a fuzzy fault Petri network' such as Li Ming, a fuzzy Petri network is used for fault diagnosis, a fault cause is divided into completely independent subsystems, and the method is suitable for systems with strong independence of each component part such as a diesel engine and a bearing, but cannot be suitable for nonlinear high-concurrency complex systems such as a garbage incinerator.
Disclosure of Invention
The invention provides a garbage incinerator fault risk assessment method based on a fuzzy Petri network, which utilizes a Petri modeling method, adopts the fuzzy Petri network to describe due to uncertainty of a garbage incinerator fault relation, can well process complex interrelations in the garbage incinerator fault risk assessment, considers influence of the current researched and neglected subsystem fault concurrency on system operation by a model, can carry out nonlinear system risk assessment, and protects driving for safe operation of the garbage incinerator.
In order to realize the purpose of the invention, the invention provides a garbage incinerator fault risk assessment method based on a fuzzy Petri network, which comprises the following steps:
s1: dividing the garbage incinerator into a plurality of subsystems, analyzing the possible fault state of each subsystem, and comprehensively analyzing the possibility of each independent fault state;
s2: analyzing the superior-subordinate relation between fault states in independent subsystems of the garbage incinerator, obtaining the conditional event and dynamic relation of fault occurrence, further constructing the concurrent fault state relation between the subsystems, and evaluating the relative probability of the corresponding fault occurrence conditional event;
s3: aiming at the development state of the failure risk of the garbage incinerator, generating a garbage incinerator failure risk assessment fuzzy Petri network graph model based on the theory of a fuzzy Petri network and in combination with the ' AND ' or ' generation rule in failure analysis;
s4: and converting the generated fuzzy Petri network model into a mathematical model, wherein the probability of the fault occurrence corresponds to the reliability of the library, and the relative probability of the fault occurrence condition event corresponds to the confidence of the transition, and performing iterative operation to obtain the corresponding probability of various fault states of the garbage incinerator after convergence.
Further, the divided subsystems include, but are not limited to, a furnace subsystem, an air supply subsystem and a water supply subsystem.
Further, the fuzzy factors are characterized by fuzzy quantifiers, which include unreal, slightly real, somewhat real, more real, quite real, very real, extremely real, and completely real.
Further, the probability of the fault occurrence and the relative probability of the fault occurrence condition event are obtained by converting fuzzy factor factors of various faults into numerical values through expert system analysis.
Further, the AND, OR or generation rules in the fault analysis correspond to four cases, wherein IF P1AND P2 THEN P3, this structure shows that if two faults happen simultaneously, the transition can be fired to fire the next fault, similar to an AND gate in a fault tree; IF P1THEN P2 OR P3, one fault may cause the other two faults after the fault occurs but it is uncertain which fault occurs; IF P1OR P2 THEN P3, which indicates that IF P can cause secondary failure as long as one of the two failures occurs1The rule THEN P2 AND P3 indicates that the occurrence of one fault will cause the next two faults to occur simultaneously.
Further, the fuzzy Petri network structure consists of three parts, namely a place, a transition and a flow relation. The octave defining a fuzzy Petri net is defined as: FPN ═ (P, T, F, M, I, O, S, L, M), involving concepts including several aspects as follows:
P＝{p1，p2，p3，…，pn}，n>0, representing the garbage incinerator failure library set, represents all system failure risk states that can be estimated.
T＝{t1，t2，t3，…，tm}，m>0, representing a finite fault transition set, representing all events which may occur, and P ≠ T ≠ Φ; p n T ═ phi
F represents a garbage incinerator fault initiation relation, is an ordered even number set of P and T, is a set connecting fault base places and fault transitions and directed relations between the fault transitions and the fault base places, and is (PxT) U (TxP).
And I represents an input matrix of the fault transition T input fault base P, when the fault transition T is input into the fault base P through the fault triggering relation F, the point value is 1, and the point value is 0 if no input exists.
And O represents an output matrix P of the output fault base of the fault transition T, and when the point value of the matrix P of the output fault base of the fault transition T passes through the fault triggering relation F is 1, the point value is 0 if no input exists.
S is the reliability vector of the fault library, corresponding to the probability of occurrence of the fault risk state
L is the confidence vector for the fault transition, corresponding to the relative probability that an event may occur.
M is a marker, M0Is the initial mark of the system, and can use M ═ M1，m2，m3，…，mi}，i>0 describes the distribution of the Token in the system in different states, which indicates whether a fault state is activated.
Further, the mathematical model comprises an input matrix I, an output matrix O, a library confidence vector S and a fault transition confidence matrix L. And generating an input matrix, an output matrix, a library confidence vector and a transition confidence vector by combining the fault state, the fault state possibility, the condition event and the relative probability of the condition event of the garbage incinerator.
Further, the inference algorithm is as follows:
Figure BDA0003502379100000031
in the formula
Figure BDA0003502379100000032
Is an n-dimensional vector. SkElement s in (1)iIs the failure status depot PiFalse confidence at k-th inference. First, let k equal to 0, use S0To obtain S1If S is0≠S1Then let k be k +1, and so on, and repeat the steps until S is obtainedk＝Sk+1And the calculation is finished.
The algorithm introduces two operators
Figure BDA0003502379100000035
And
Figure BDA0003502379100000033
the meaning of these two matrix operators is explained below. :
Figure BDA0003502379100000036
where A, B, C are all m n matrices, then cij＝max(aij,bij)，i＝1，2，…， m，j＝1，2，…，n。
Figure BDA0003502379100000034
Wherein A, B, C are m × p, p × n, m × n matrices, respectively, then cij＝max(aik·bkj)， i＝1，2，…，m，j＝1，2，…，n。
Further, after step S4, the method further includes: and comparing the probability of the fault state of the subsystem of the garbage incinerator with the final fault reliability value obtained by iterative algorithm operation, sequencing the fault occurrence probability, analyzing key fault points, combing key fault links and giving suggestions to daily operation and maintenance of the garbage incinerator.
Compared with the prior art, the invention can realize the following beneficial effects:
1. the invention constructs a garbage incinerator fault model with strict logic by using a fuzzy Petri network model, visually represents the fault and fault occurrence relation of each subsystem, and simultaneously solves the problem of nonlinear complex system fault diagnosis of the garbage incinerator by using the structural advantages of the fuzzy Petri network and taking the fault concurrency condition among the subsystems into consideration compared with the prior method, thereby being an effective quantitative risk assessment method, and being capable of providing feasible operation and maintenance for the daily operation of the garbage incinerator and maintaining the safe and effective work of the system.
2. According to the method, the risk assessment of the garbage incinerator is realized by utilizing the characteristics of the fuzzy Petri network, and the risk assessment method has the capability of describing concurrent faults and solves the problem of assessing the concurrent faults.
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Fig. 1 is a schematic flow chart of an evaluation method according to an embodiment of the present invention.
Fig. 2 is a schematic view of a garbage incinerator failure risk assessment model according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of concurrent faults between a furnace system and a blast system according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of a concurrent failure between a water supply system and a wind supply system according to an embodiment of the present invention.
Detailed Description
The following detailed description will be provided for the purpose of the present invention with reference to the accompanying drawings and specific embodiments, which are not repeated herein, but the embodiments of the present invention are not limited to the following embodiments, and other embodiments obtained by persons skilled in the art without making creative work based on the embodiments of the present invention are within the protection scope of the present invention.
In order to facilitate understanding of the embodiment of the invention, fig. 1 shows an overall logic framework of the invention, wherein the process of building a Petri net based on mutual relationship identification and solving are key points of the embodiment of the invention, a set of garbage incinerator operation logic is established through analysis of a garbage incinerator system, as shown in fig. 1, the garbage incinerator is divided into a plurality of subsystems, the possible fault state of each subsystem is analyzed, and the possibility of each independent fault is evaluated through comprehensive analysis results.
Specifically, the invention provides a fuzzy Petri net-based garbage incinerator fault risk assessment method, which comprises the following steps:
step 1: according to the operating hierarchical logic of the garbage incinerator, the system faults of the garbage incinerator are analyzed, if a blower belongs to an air supply system, the air supply system belongs to the whole garbage incinerator, the garbage incinerator is divided into a plurality of subsystems, fault states which may occur in each subsystem are analyzed, and the possibility of occurrence of each independent fault state is comprehensively analyzed.
In some embodiments of the invention, the division of the waste incinerator into a plurality of subsystems is based on the relative independence of the operation of each subsystem but is more dependent on expert experience.
In some embodiments of the invention, the failure of the garbage incinerator is divided into three subsystems, including a hearth failure, an air supply failure and a water supply failure, and then the failure state of each independent subsystem is refined.
Step 2: analyzing the superior-inferior relation between the fault states in each independent subsystem of the garbage incinerator to obtain the conditional event and dynamic relation of the fault occurrence, further constructing the concurrent fault state relation between the subsystems, and evaluating the relative probability of the corresponding fault occurrence conditional event.
The step is mainly to clear the cause and effect combing of the faults obtained in the previous step, and besides the fault relation in subsystems, the concurrent faults among subsystems need to be concerned, for example, in some embodiments of the invention, the blockage of the fire grate of the garbage incinerator can cause abnormal temperature of a hearth, the blockage of the fire grate of the garbage incinerator belongs to the hearth fault, but the blockage of the fire grate can also cause primary air faults below the fire grate, and can be divided into the category of air supply faults. The risk assessment is carried out based on the fuzzy Petri network, the high-concurrency model has high concurrency processing capacity, and the generated model can be used for carrying out fault diagnosis on a nonlinear complex system such as a garbage incinerator.
And 3, step 3: aiming at the development state of the failure risk of the garbage incinerator, a garbage incinerator failure risk assessment fuzzy Petri network graph model is generated based on the theory of a fuzzy Petri network and in combination with the ' AND ' or ' generation rule in failure analysis.
In some embodiments of the present invention, the AND, OR or generation rules in the fault analysis in this step correspond to four cases, wherein the IF P1AND P2 THEN P3, this structure shows that if two faults happen simultaneously, the transition can be fired to fire the next fault, similar to an AND gate in a fault tree; IF P1THEN P2 OR P3, one fault may cause the other two faults after occurring but it is uncertain which fault occurs; IF P1OR P2 THEN P3, which indicates that IF P can cause secondary failure as long as one of the two failures occurs1The rule THEN P2 AND P3 indicates that the occurrence of a fault will cause the next two causesThe barrier occurs simultaneously. The resulting blurred Petri is shown in FIG. 2. Table 2 shows the corresponding failure status for each bank. To illustrate the concurrency of faults in the system, FIG. 3 shows the concurrency of faults between two subsystems of a hearth system and an air supply system, and the concurrency of faults is P3Grate clogging and P14Fuel supply faults, which essentially belong to the furnace system, but also cause air supply faults; FIG. 4 shows a concurrent fault between the air supply system and the water supply system, where the concurrent fault is P8And P16The transition involved is T7、T8，T14、T15The consideration of the concurrent faults benefits from the mechanism structure of the fuzzy Petri net and is related to the consideration of the concurrent faults before construction.
TABLE 2
Figure BDA0003502379100000061
And 4, step 4: and converting the generated fuzzy Petri network model into a mathematical model according to an algorithm, wherein the probability of the fault occurrence corresponds to the reliability of the database, the relative probability of the fault occurrence condition event corresponds to the confidence of the transition, iterative operation is carried out by using the algorithm, and the probability of the fault occurrence of various faults of the garbage incinerator can be obtained after convergence.
In some embodiments of the present invention, the probability of the occurrence of the fault and the relative probability of the occurrence condition event of the fault are obtained by converting fuzzy factors of various types of faults into numerical values through expert system analysis.
The probability of fault occurrence and the relative probability of fault occurrence condition events are obtained by converting fuzzy factors of various faults into numerical values through expert system analysis, and the specific corresponding relation is shown in table 1. (fuzzy quantifier is a method for quantifying fuzzy expression in expert system evaluation, namely, asking experts in the field to evaluate various faults, providing fuzzy quantifier and comparison table, and scoring the probability of initial fault occurrence and the relative probability of fault occurrence condition events by referring to the table by the experts)
TABLE 1
Figure BDA0003502379100000062
Figure BDA0003502379100000071
In the present invention, step 4 comprises the following substeps:
step 4.1: a mathematical concept is defined for a fuzzy Petri network graph model for fault risk assessment, and the fuzzy Petri network structure comprises a place, a transition and a flow relation. The octave defining a fuzzy Petri net is defined as: FPN ═ (P, T, F, M, I, O, S, L, M), involving concepts including several aspects as follows:
P＝{p1，p2，p3，…，pn}，n>0, representing the garbage incinerator fault library set, representing all system fault risk states which can be estimated; p is a radical ofnThe nth failure risk state is shown, and n is the number of failure risk states.
T＝{t1，t2，t3，…，tm}，m>0, representing a finite fault transition set, representing all events which may occur, and P ≠ T ≠ Φ; p and T is phi; t is tmThe m-th fault occurrence condition event is shown, and m represents the number of fault occurrence condition events.
F represents the fault triggering relation of the garbage incinerator, is an ordered even number set of P and T, is a set connecting fault libraries and fault transitions and directed relations between the fault transitions and the fault libraries, and is (PxT) U (TxP).
M is a marker, M0Is the initial mark of the system, and can use M ═ M1，m2，m3，…，mn}，i>0 describes the distribution of the Token in the system in different states, which indicates whether a fault state is activated. m isnThe initial condition of the corresponding nth fault state library is shown, and the initial condition is 1 when the fault state library is activated and 0 when the fault state library is not activated.
I represents an input matrix of a fault transition T input fault base P, the matrix dimension is n multiplied by m, n represents the number of fault risk states, m represents the number of fault occurrence condition events, when the fault transition T is input into the fault base P through a fault triggering relation F, the point value is 1, no input is 0, and the input matrix I is generated according to the relation.
And O represents an output matrix of the fault transition T output fault base P, the matrix dimension is n multiplied by m, n represents the number of fault risk states, m represents the number of fault occurrence condition events, when the fault transition T outputs the fault base P through the fault triggering relation F, the matrix point value is 1, and if no output exists, the matrix point value is 0, and the output matrix O is generated according to the relation.
S is the confidence vector of the fault bank, S ═ S1，s2，s3，…，sn)，snThe probability of occurrence of the nth fault risk state is represented, n represents the number of the fault risk states, the initial probabilities of other faults are temporarily set to be zero except the probability of occurrence of the initial fault is obtained through evaluation of an expert system, and the final value is obtained through iterative operation.
L is the confidence diagonal matrix of the fault transition, L ═ diag (L)1，l2，l3，…，lm) Wherein l ismAnd the relative probability of the mth fault occurrence condition event is shown, m represents the number of the fault occurrence condition events, and the numerical values are obtained by the evaluation of an expert system.
Step 4.2: the concept and definition are utilized to convert the garbage incinerator fault risk assessment fuzzy Petri network model into a mathematical model, and the mathematical model comprises the steps of generating an input matrix I, an output matrix O, a library confidence vector S and a fault transition confidence matrix L.
In some embodiments of the present invention, the initial value is:
S0＝(0.34,0.31,0.5,0.31,0.3,0.1,0.5,0.5,0.12,0.33,0.45,0.16,0,0,0,0,0,0,0,0)T，S0indicating the likelihood of the occurrence of the initial fault risk condition.
L0＝diag(0.95,0.8,0.8,0.85,0.75,0.85,0.9,0.9,0.95,0.9,0.8,0.9,0.8,0.9,0.95,0.9,0.8,0.95,0.9,0.9)， L0Representing the relative probability of an initial fault condition event.
Step 4.3: and (4) carrying out iterative operation by using an algorithm, and obtaining the corresponding possibility of various fault states of the garbage incinerator after convergence.
In some embodiments of the present invention, the iterative algorithm is:
Figure BDA0003502379100000081
in the formula
Figure BDA0003502379100000082
εn＝(1,1,…,1)TIs an n-dimensional vector, SkThe element in (1) is a fault status library piFalse confidence at k-th inference. First, let k equal to 0, use S0To obtain S1If S is0≠S1Then let k be k +1, and so on, and repeat the steps until S is obtainedk＝Sk+1And the calculation is finished.
In some embodiments of the invention, the iterative process is:
S0＝(0.34,0.31,0.5,0.31,0.3,0.1,0.5,0.5,0.12,0.33,0.45,0.16,0,0,0,0,0,0,0,0)T
L0＝diag(0.95,0.8,0.8,0.85,0.75,0.85,0.9,0.9,0.95,0.9,0.8,0.9,0.8,0.9,0.95,0.9,0.8,0.95,0.9,0.9)
S1＝(0.34,0.31,0.5,0.31,0.3,0.1,0.5,0.5,0.12,0.33,0.45,0.16,0.29,0.4,0.4,0.45,0,0.26,0.41,0)T
S2＝(0.34,0.31,0.5,0.31,0.3,0.1,0.5,0.5,0.12,0.33,0.45,0.16,0.29,0.4,0.4,0.45,0.36,0.41,0.43,0.9) T
S3＝(0.34,0.31,0.5,0.31,0.3,0.1,0.5,0.5,0.12,0.33,0.45,0.16,0.29,0.4,0.4,0.45,0.36,0.41,0.43,0.38 )T
S4＝(0.34,0.31,0.5,0.31,0.3,0.1,0.5,0.5,0.12,0.33,0.45,0.16,0.29,0.4,0.4,0.45,0.36,0.41,0.43,0.38 )T
S4＝S3and after reasoning is finished, obtaining a reasoning result, namely obtaining the corresponding possibility of various fault states of the garbage incinerator.
Wherein, two operators are introduced into the iterative algorithm
Figure BDA0003502379100000084
And
Figure BDA0003502379100000083
the meaning of these two matrix operators is explained below:
Figure BDA0003502379100000092
where A, B, C are all m n matrices, then cij＝max(aij,bij)，i＝1，2，…， m，j＝1，2，…，n。aijI.e. the corresponding value of the ith row and jth column of the A matrix, bijI.e. the corresponding value of the ith row and the jth column of the B matrix)
Figure BDA0003502379100000091
Wherein A, B, C are m × p, p × n, m × n matrices, respectively, then cij＝max(aik·bkj)， i＝1，2，…，m，j＝1，2，…，n，aikI.e. the corresponding value of the ith row and the kth column of the A matrix, bkjI.e. the corresponding value of the kth row and jth column of the B matrix.
And 5: and comparing the probability of the fault state of the subsystem of the garbage incinerator according to the final fault reliability value obtained by iterative algorithm operation, sequencing the probability of the fault occurrence, generating a key fault point, and obtaining a key fault link. And advices are given to the daily operation and maintenance of the garbage incinerator.
As can be seen from the calculation results, in the backward calculation, the confidence of the combustion temperature abnormality which indirectly causes the garbage incinerator accident is 0.29, the confidence of the fuel supply failure is 0.4, the confidence of the primary air failure is 0.4, and the confidence of the overfire air failure is 0.45, and as the failure which directly causes the garbage incinerator accident, the confidence of the furnace failure is 0.36, the confidence of the air supply failure is 0.41, and the confidence of the water supply failure is 0.43, so in order to ensure the safe and stable operation of the garbage incinerator, the boiler feed water needs to be well maintained. And reverse reasoning can be carried out by utilizing the result, if the water supply fault is the key fault point in the direct fault of the garbage incinerator and has the highest confidence coefficient, the reverse reasoning in the water supply fault causes that the maximum probability of the water supply fault is that the confidence coefficient of the water pump fault is 0.45, so that the key fault link of the garbage incinerator is the water pump fault → the water supply fault → the garbage incinerator fault, and the operation of the water pump and the water supply system is focused in the daily management of the garbage incinerator.
The method provided by the embodiment of the invention overcomes the defect that the existing risk assessment method is mainly based on qualitative analysis, can quantitatively obtain the occurrence probability of various faults, effectively utilizes the structure of the fuzzy Petri network, considers the concurrent faults among subsystems, improves the reliability of fault diagnosis, can help operation and maintenance personnel of the garbage incinerator to locate key fault points in advance, purposefully develop daily work, prevent the sudden failure of the garbage incinerator, and prolong the service life of the garbage incinerator.
The foregoing represents only one embodiment of the present application, which is described in more detail and specific, but the present invention is not limited to the best mode described above. It should be noted that the structural changes made under the teaching of the present invention, without obvious innovation, have the same or similar technical solutions as the present invention, and are within the protection scope of the present invention.

Claims (10)

1. A garbage incinerator fault risk assessment method based on a fuzzy Petri net is characterized by comprising the following steps:
s1: dividing the garbage incinerator into a plurality of subsystems, analyzing the possible fault state of each subsystem, and comprehensively analyzing the possibility of each independent fault state;
s2: analyzing the superior-inferior relation between fault states in independent subsystems of the garbage incinerator, obtaining the conditional event and dynamic relation of fault occurrence, further constructing the concurrent fault state relation between the subsystems, and evaluating the relative probability of the corresponding fault occurrence conditional event;
s3: aiming at the development state of the failure risk of the garbage incinerator, generating a garbage incinerator failure risk assessment fuzzy Petri network graph model based on the theory of a fuzzy Petri network and in combination with the ' AND ' or ' generation rule in failure analysis;
s4: and converting the generated fuzzy Petri network model into a mathematical model, wherein the probability of the fault occurrence corresponds to the reliability of the library, and the relative probability of the fault occurrence condition event corresponds to the confidence of the transition, and performing iterative operation to obtain the corresponding probability of various fault states of the garbage incinerator after convergence.
2. The method for assessing the risk of failure of the garbage incinerator based on the fuzzy Petri net, as claimed in claim 1, wherein the divided subsystems include but are not limited to a furnace subsystem, an air supply subsystem and a water supply subsystem.
3. The method for assessing the risk of failure of the garbage incinerator based on the fuzzy Petri net as claimed in claim 1, wherein said probability of failure occurrence and the relative probability of the condition event of failure occurrence are obtained by converting fuzzy factors of various types of failures into numerical values through expert system analysis.
4. The method for assessing the risk of failure of the garbage incinerator based on the fuzzy Petri net as claimed in claim 3, wherein said fuzzy factors are characterized by fuzzy quantifiers, and said fuzzy quantifiers include unreal, very slightly real, somewhat real, more real, quite real, very real, extreme real and complete real.
5. A die-based according to claim 1The method for evaluating the risk of the failure of the garbage incinerator based on the Petri network is characterized in that the AND, OR or generation rules in the failure analysis in the step S2 correspond to four conditions, wherein IF P1AND P2 THEN P3, this configuration indicates that if two faults occur simultaneously, a transition can be fired to fire the next fault; IF P1THEN P2 OR P3, one fault may cause the other two faults after the fault occurs but it is uncertain which fault occurs; IF P1OR P2 THEN P3, which indicates that IF P can cause secondary failure as long as one of the two failures occurs1The rule THEN P2 AND P3 indicates that the occurrence of one fault will cause the next two faults to occur simultaneously.
6. The method for assessing the risk of failure of a garbage incinerator based on fuzzy Petri Net as claimed in claim 1, wherein step S4 includes the sub-steps of:
s4.1: the fuzzy Petri network graph model aiming at fault risk assessment defines a mathematical concept, wherein the fuzzy Petri network structure comprises a custody, a transition and a flow relation, and an octave group defining a fuzzy Petri network is defined as follows: FPN is (P, T, F, M, I, O, S, L, M), P represents a garbage incinerator fault library set, T represents a finite fault transition set, F represents a garbage incinerator fault triggering relation and is an ordered even number set of P and T, M is a mark, I represents an input matrix of a fault transition T input fault library P, O represents an output matrix of a fault transition T output fault library P, S is a reliability vector of a fault library, and L is a confidence diagonal matrix of the fault transition;
s4.2: converting the garbage incinerator fault risk assessment fuzzy Petri network model into a mathematical model, wherein the mathematical model comprises an input matrix, an output matrix, a library credibility vector and a fault transition confidence diagonal matrix;
s4.3: and (4) carrying out iterative operation by using an algorithm, and obtaining the corresponding possibility of various fault states of the garbage incinerator after convergence.
7. The method for evaluating the risk of the failure of the garbage incinerator based on the fuzzy Petri net according to claim 6, characterized in that in the reliability vector of the failure library, the initial probability of other failures is temporarily set to zero except the probability of the initial failure is evaluated by an expert system, and the final value is obtained by iterative operation.
8. The method for assessing the risk of failure of the garbage incinerator based on the fuzzy Petri net as claimed in claim 6, wherein the numerical values in the confidence diagonal matrix of the failure transition are all evaluated by an expert system.
9. The method for assessing the risk of failure of the garbage incinerator based on the fuzzy Petri net as claimed in claim 6, wherein an inference algorithm is adopted for iteration, and the inference algorithm is as follows:
Figure FDA0003502379090000021
in the formula
Figure FDA0003502379090000022
εnIs an n-dimensional vector, T is transposed, SkThe element in (B) is fault status place PiFalse confidence at k-th inference ≦ The
Figure FDA0003502379090000023
Are operators;
first, let k equal to 0, use S0To obtain S1If S is0≠S1Then let k be k +1, and so on, and repeat the steps until S is obtainedk＝Sk+1And the calculation is finished.
10. The method for assessing the risk of failure of a garbage incinerator based on fuzzy Petri net according to any one of claims 1-9, further comprising after step S4:
s5: and (4) comparing the probability of the fault state of the subsystem of the garbage incinerator according to the final fault reliability value obtained by iterative algorithm convergence, sequencing the fault occurrence probability, analyzing key fault points and combing key fault links.
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