CN112986722A - Ship shore power fault diagnosis method and device - Google Patents

Ship shore power fault diagnosis method and device Download PDF

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CN112986722A
CN112986722A CN202110126972.5A CN202110126972A CN112986722A CN 112986722 A CN112986722 A CN 112986722A CN 202110126972 A CN202110126972 A CN 202110126972A CN 112986722 A CN112986722 A CN 112986722A
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protection
state
value
fault
shore power
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岳东
刘军
窦春霞
张智俊
丁孝华
李延满
赵景涛
罗剑波
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Nanjing University of Posts and Telecommunications
State Grid Electric Power Research Institute
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State Grid Electric Power Research Institute
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/08—Locating faults in cables, transmission lines, or networks
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/34—Testing dynamo-electric machines
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/40—Testing power supplies
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
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    • G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]

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Abstract

The invention provides a ship shore power fault diagnosis method based on an improved BPSO algorithm, which is technically characterized by comprising the following steps of: the method comprises the following steps: determining a fault occurrence area by comparing ship shore power system diagrams before and after the fault; calculating the fault measure indexes of all original components in the fault occurrence area, analyzing and comparing, and further screening the components to obtain suspicious components which are likely to have faults; inputting the actual state and the expected state of the screened possible fault element into a ship shore power fault diagnosis analysis model to obtain a target function set of the possible fault element; and solving the target function set through an improved binary particle swarm algorithm to obtain the actual state of the element, and comparing the obtained actual state of the element with the alarm state and the expected state respectively to evaluate the fault.

Description

Ship shore power fault diagnosis method and device
Technical Field
The invention relates to a ship shore power fault diagnosis method and device, and belongs to the technical field of ship power fault diagnosis.
Background
Nowadays, ship shipping bears over 80% of the transportation share of global trade by virtue of low cost and huge cargo capacity, and has a very important influence on global trade development and the marine transportation industry. However, during the period when the ship is in the shore, the diesel generator carried by the ship is mainly used for generating electricity for the ship to use. In the process of generating power, a marine diesel generator consumes fuel oil, and generates serious harmful pollutants such as Nitrogen Oxide (NOX), Sulfur Oxide (SOX), Volatile Organic Compounds (VOC), inhalable particulate Pollutants (PM) and the like, thereby not only polluting the environment of a port, but also bringing noise pollution when the marine diesel generator operates, and bringing inconvenience to people living nearby. The ship shore power technology is that when a ship is in shore, a ship generator is stopped, and a shore power supply is used for supplying power. The pollution caused by ship electricity consumption can be effectively reduced, and more attention is paid.
The load capacity of modern ships is increased day by day, the power station structure is complicated day by day, and many special equipment such as fresh-keeping keep-alive equipment, on-board weapons etc. that it adorns simultaneously all have "do not cut off the power supply" demand, therefore the bank power supply just must adopt seamless mode of being incorporated into the power networks for boats and ships power supply. The seamless grid connection must replace the power supply mode of stopping the ship generator first and supplying power to the ship by using an on-shore power supply. The shore/ship grid connection is different from the traditional multi-diesel-generator network connection control. The generator rotor has inertia and has reverse work bearing capacity. The core of the shore-based variable frequency power supply is a high-power IGBT (Insulated Gate Bipolar Transistor), and the small disturbance of the current, voltage and frequency of the ship power station threatens the stability of the variable frequency power supply and the ship generator, and can also cause the damage of the shore/ship power equipment in severe cases. Therefore, in the shore/ship-mounted grid-connected process, the state detection and fault diagnosis of shore equipment and ship-mounted equipment are indispensable.
At present, fault diagnosis methods for power systems include expert systems, artificial neural networks, bayesian networks, petri networks, analytical models, and the like. The traditional analytical model has the advantages of small dimension and quick solution, but the defects of the traditional analytical model are fatal, and multiple solutions or even misunderstandings can occur due to the simple diagnostic rule. The analytic model added with the false action and rejection information of the protection and the breaker has high fault tolerance rate, but has high dimensionality, difficult solution and slow solution.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, provides a ship shore power fault diagnosis method and device, and solves the problems of slow solution and low accuracy of the conventional fault diagnosis method for a power system.
In order to achieve the purpose, the invention is realized by adopting the following technical scheme:
in a first aspect, the invention provides a ship shore power fault diagnosis method based on an improved BPSO algorithm, which is characterized by comprising the following steps:
determining a fault occurrence area by comparing ship shore power system diagrams before and after the fault;
calculating the fault measure indexes of all original components in the fault occurrence area, analyzing and comparing, and further screening the components to obtain suspicious components which are likely to have faults;
inputting the actual state and the expected state of the screened possible fault element into a ship shore power fault diagnosis analysis model to obtain a target function set of the possible fault element;
and solving the target function set through an improved binary particle swarm algorithm to obtain the actual state of the element, and comparing the obtained actual state of the element with the alarm state and the expected state respectively to evaluate the fault.
Further, the ship shore power fault diagnosis analysis model comprises:
Figure BDA0002923816800000031
in the formula: e (x) represents the value of the objective function, rkmAnd rkm *The actual and expected states of the primary protection represented as a certain element; r iskpAnd rkp *The thief represents the actual and expected state of near backup protection for a certain element; r isksAnd rks *Actual and expected states of far backup protection for the element; ciAnd Ci *Respectively representing the actual and desired states of a certain circuit breaker.
Further, the desired states of the elements include a desired state of main protection, a desired state of near backup protection, a desired state of far backup protection, and a desired state of circuit breaker;
the calculation formula of the expected state of the main protection is as follows:
Figure BDA0002923816800000032
in the formula:
Figure BDA0002923816800000033
indicating the desired state of the main protection, SnIndicates the state of a certain element, SnWhen 0, it means that the element is normal, SnA value of 1 indicates that the element is faulty;
Figure BDA0002923816800000034
then it is the elementWhen the value of the expected state of the main protection associated with the element is 0, the expected state of the protection does not act, otherwise, the expected state of the protection acts;
the calculation formula of the expected state of the near backup protection is as follows:
Figure BDA0002923816800000035
in the formula: r iskmIs a component SnThe main protection actual state of (1) indicates that the protection is not operating when the value is 0 and indicates that the protection is operating when the value is 1,
Figure BDA0002923816800000036
then the element is associated with a near backup protection expected state, when the value is 0, the protection expected state is not action, and when the value is 1, the protection expected state is action;
the calculation formula of the expected state of the far backup protection is as follows:
Figure BDA0002923816800000037
in the formula:
Figure BDA0002923816800000038
is a component SnThe associated far backup protection expected state indicates that the protection expected state does not act when the value is 0, and indicates that the protection expected state acts when the value is 1; z (r)km,Sn) Is composed of
Figure BDA0002923816800000041
S in the protection areanAll closely associated device sets, P ((r)km,SX) To protect
Figure BDA0002923816800000042
Is from the starting point to SXA set of all breaker states on the path;
the calculation formula of the expected state of the circuit breaker is as follows:
Figure BDA0002923816800000043
in the formula: ciAnd
Figure BDA0002923816800000044
the actual state and the expected state of the circuit breaker are obtained, when the value is 0, the circuit breaker state is not disconnected, and when the value is 1, the circuit breaker state is disconnected; r (C)i) The protection sets capable of being opened by the circuit breaker comprise main protection, near backup protection and far backup protection.
Further, the step of determining the fault occurrence region by comparing the ship shore power system diagram before and after the fault specifically includes: constructing a fault information matrix based on the uploaded alarm information, and establishing a section discrimination exclusive or logic by combining a correlation matrix between the switches and the sections; and positioning the fault section through the section discrimination exclusive-OR logic.
Further, the method for calculating the fault test index includes:
failure test index K of elementiThe calculation formula of (2) is as follows:
Ki＝Kr,iKc,i
in the formula, KiIndicates the failure test index, Kr,iThe method comprises the steps of representing a protection alarm relevance index and representing a no-main breaker alarm relevance index; when K isiWhen the value is smaller than the preset value, the element i is a suspicious element, otherwise, the element i is a normal element;
the protection alarm relevance index Kr,iThe expression of (a) is as follows:
Figure BDA0002923816800000045
in the formula: er,0An objective function value assuming no failure; er,iThe objective function value when the element i alone is supposed to fail; n is a radical ofr,iThe protection number associated with element i takes on the following formulaDetermining:
Nr,i＝wmnim+wpnip+wsnis
in the formula: n isim，nip，nisThe number of primary protection, near backup protection and far backup protection associated with the element i respectively; and wm，wp，wsRespectively representing each protection action coefficient;
alarm relevance index K of main-free circuit breakerc,iThe calculation formula of (2) is as follows:
Figure BDA0002923816800000051
in the formula: n iscnm,iAnd ncns,iThe number of non-main breakers associated with the respective element i through main protection and far backup protection; n iscm,iAnd ncs,iThen is the total number of circuit breakers associated by element i through the main protection and far backup protection; n isrm,iAnd nrs,iThe number of primary and far backup protections associated with element i.
Further, the method for solving the objective function set through the improved binary particle swarm algorithm comprises the following specific steps:
setting improved binary particle swarm algorithm parameters, wherein the improved binary particle swarm algorithm parameters comprise: the number of group individuals, learning factors, inertial weight and maximum iteration times;
randomly initializing the speed and the position of the population according to the dimension of the corresponding matrix, and then preliminarily obtaining a local optimal value and a global optimal value of the population;
comparing the current objective function value with a local optimum value and a global optimum value respectively, and if the local optimum value is less than or equal to the current objective function value, keeping the local optimum value unchanged; if the local optimum value is larger than the current objective function value, updating the local optimum value into the current objective function value; if the global optimum value is less than or equal to the current objective function value, the global optimum value is kept unchanged; if the global optimum value is larger than the current objective function value, updating the global optimum value into the current objective function value;
and when the iteration of the maximum iteration times set by the improved binary particle swarm algorithm is finished, obtaining a global optimal value, namely an optimal target solution.
Further, the method for solving the set of objective functions by the modified binary particle swarm algorithm further includes: the location update function is updated using the following formula:
the Sigmond function is modified as follows:
Figure BDA0002923816800000061
when v isidWhen the content is less than or equal to 0:
Figure BDA0002923816800000062
when v isid>At time 0:
Figure BDA0002923816800000063
in the above formula: s (v)id) For the value of the probability mapping function, vidIs the velocity, x, of the particleidAnd rand () represents a random number between 0-1 for the position of the particle.
Further, the fault evaluation method specifically includes:
comparing the actual state of the element with the alarm information and the expected state respectively, and if the expected state is 0 and the actual state is 1, the protection device is in false operation; if the expected state is 1 and the actual state is 0, the protection device refuses to operate; if the two values are the same, the protection device is correct;
comparing the alarm information with the alarm information, and if the alarm state is 0 and the actual state is 1, the protection device fails to report the information; if the alarm state is 1 and the actual state is 0, the protection device misreads information; if the two are the same, the protection device is correct.
In a second aspect, the present invention provides a ship shore power failure diagnosis apparatus, comprising:
a failure zone determination module: the system is used for determining a fault occurrence area by comparing ship shore power system diagrams before and after the fault;
suspicious element screening module: the failure detection system is used for calculating failure measure indexes of all original elements in the failure occurrence area, analyzing and comparing the failure measure indexes, and further screening elements to obtain suspicious elements which are likely to fail;
an analytical model optimization module: the system comprises a suspected element, a protection and circuit breaker, a corresponding matrix, a ship shore power fault diagnosis and analysis model and a ship shore power fault diagnosis and analysis model, wherein the suspected element and the protection and circuit breaker are associated with the suspected element, the corresponding matrix is established to obtain the corresponding ship shore power fault diagnosis and analysis model, and the ship shore power fault diagnosis and analysis model is optimized by using a binary particle swarm algorithm to obtain the optimized ship shore power fault diagnosis and analysis model;
and a fault evaluation module: and the system is used for calculating and obtaining the actual state of the element through the optimized ship shore power fault diagnosis analysis model, and comparing the obtained actual state of the element with alarm information and an expected state respectively to obtain fault evaluation.
In a third aspect, the present invention provides a ship shore power fault diagnosis apparatus, comprising a processor and a storage medium;
the storage medium is used for storing instructions;
the processor is configured to operate according to the instructions to perform the steps of the above-described method.
Compared with the prior art, the invention has the following beneficial effects:
1. by adopting the staged analytical model, the defects of high dimension and slow solving of the analytical model with protection and misoperation and refusal of the breaker are avoided, and the defect of low solving precision of the traditional analytical model is also overcome;
2. compared with a genetic algorithm and a common particle swarm algorithm, the improved BPSO algorithm can obtain the optimal solution in a shorter time and in a shorter number of iteration steps.
Drawings
FIG. 1 is a fault diagnosis process flow diagram of the present invention;
fig. 2 is a connection structure diagram of a distribution network of ship shore power of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
The first embodiment is as follows:
the embodiment provides a ship shore power fault diagnosis method based on an improved BPSO algorithm, which comprises the following steps:
1) when an offshore ship is connected or uses an onshore power supply and has a fault, a power grid fault positioning method based on a matrix algorithm is used, namely a fault information matrix is constructed based on uploaded alarm information, and a section discrimination exclusive OR logic is established by combining a correlation matrix between a switch and the section, so that the fault section can be positioned quickly finally.
2) By calculating the fault measure indexes of all original parts in the fault occurrence area and then analyzing and comparing, elements can be further screened to obtain suspicious elements which are likely to have faults.
3) Establishing an improved ship shore power fault diagnosis analysis model according to the actual value and the fault value of the screened possible fault element; the function is:
Figure BDA0002923816800000081
in the formula: r iskmAnd rkm *The actual and expected states of the primary protection represented as a certain element; r iskpAnd rkp *The thief represents the actual and expected state of near backup protection for a certain element; r isksAnd rks *Actual and expected states of far backup protection for the element; ciAnd Ci *Respectively representing the actual and desired states of a certain circuit breaker.
4) And solving the target function by using an improved binary particle swarm algorithm, and comparing the obtained result with the alarm value and the expected value to obtain accurate fault evaluation.
Calculating the fault test indexes of each element in the step 2) as follows:
(1) the fault test index is divided into two parts, the first type protection alarm correlation index, and the other type protection alarm correlation index is the alarm correlation index without the main breaker.
(2) Alarm relevance index;
when only the protected information is considered, the breaker part in the analytical model in the step 3) is removed, and the expression of the breaker part is changed into that:
Figure BDA0002923816800000091
establishing a protection alarm correlation index, wherein the expression of the protection alarm correlation index is as follows:
Figure BDA0002923816800000092
in the formula: er,0An objective function value assuming no failure; er,iThe objective function value when the element i alone is supposed to fail; n is a radical ofr,iThe value of the protection number associated with element i is determined by the following equation:
Nr,i＝wmnim+wpnip+wsnis
in the formula: n isim，nip，nisThe number of primary, near backup, and far backup protections associated with element i, respectively. And wm，wp，wsAfter consulting the relevant literature, the values are respectively 6, 3 and 2.
(3) Alarm relevance indexes of no main breaker;
the non-main breaker is a breaker which protects alarm triggering but acts, and the set of the breaker is as follows:
Figure BDA0002923816800000093
wherein C is the set of all circuit breakers; cniIs the ith main-free breaker; cniAnd
Figure BDA0002923816800000094
respectively the actual and the desired state of the circuit breaker.
Establishing an alarm relevance index of a non-main breaker;
Figure BDA0002923816800000095
in the formula: n iscnm,iAnd ncns,iThe number of non-main breakers associated with the respective element i through main protection and far backup protection; n iscm,iAnd ncs,iThen is the total number of circuit breakers associated by element i through the main protection and far backup protection; n isrm,iAnd nrs,iThe number of primary and far backup protections associated with element i.
(4) Element failure test index:
correcting the protection alarm relevance index by using the alarm relevance index without the main breaker, wherein the fault test indexes of the elements are as follows:
Ki＝Kr,iKc,i
looking up the relevant data, here we set a threshold value of 0.2, when KiIf the value is less than this, the element i is a normal element, and the other is a normal element.
Calculating the expected states of the protection and the breaker in the steps 2) and 3) as follows:
(1) the desired state of primary protection;
Figure BDA0002923816800000101
in the formula: snIn a state of a certain element, when the state is 0, the element is normal, and when the value is 1, the element is failed;
Figure BDA0002923816800000102
then the desired state of the primary protection associated with that element is a value of 0 and the desired state of the protection is not activeOtherwise, the protection expects a state action.
(2) An expected state of near backup protection;
Figure BDA0002923816800000103
in the formula: r iskmIs a component SnThe value of the main protection actual state of (1) is 0, the protection does not act, and is 1,
Figure BDA0002923816800000104
then the value is 0 for the near backup protection expected state associated with that element, which is inactive, and 1, which is active.
(3) An expected state of far backup protection;
Figure BDA0002923816800000105
in the formula:
Figure BDA0002923816800000106
is a component SnWhen the value of the associated far backup protection expected state is 0, the protection expected state is not operated, and when the value of the protection expected state is 1, the protection expected state is operated; z (r)km,Sn) Is composed of
Figure BDA0002923816800000107
S in the protection areanAll closely associated device sets, P ((r)km,SX) To protect
Figure BDA0002923816800000108
Is from the starting point to SXAll breaker states on the path are aggregated.
(4) The desired state of the circuit breaker;
Figure BDA0002923816800000109
in the formula: ciAnd
Figure BDA00029238168000001010
the actual state and the expected state of the circuit breaker are 0, the circuit breaker state is not disconnected, and 1, the circuit breaker state is disconnected. r (C)i) The protection sets capable of being opened by the circuit breaker comprise main protection, near backup protection and far backup protection.
In the step 4), the improved BPSO is used for solving the ship shore power fault diagnosis analysis model, and the specific steps are as follows:
(1) the method comprises the following steps 1 and 2), and can further screen the fault outage area obtained in the step 1) to obtain a suspicious fault element.
(2) And establishing corresponding matrixes of the obtained suspicious fault elements and the protection and circuit breakers related to the elements, and sorting and analyzing the models to obtain corresponding objective functions.
(3) And setting parameters of the improved binary particle swarm algorithm, such as the number of group individuals, learning factors, inertia weight and maximum iteration times.
(4) And (3) randomly initializing the speed and the position of the groups according to the matrix dimension obtained in the step (2), and then substituting the groups into the step (2) to preliminarily obtain the local optimal value and the global optimal value of the groups.
(5) And (3) performing optimization calculation on the objective function in the step (2) by adopting an improved binary particle swarm algorithm, and comparing the calculated result with a local optimal value and a global optimal value for replacement. The location update function is optimized here, and updated using the following formula:
the Sigmond function is modified as follows:
Figure BDA0002923816800000111
when v isidWhen the content is less than or equal to 0:
Figure BDA0002923816800000112
when v isid>At time 0:
Figure BDA0002923816800000113
in the above formula: s (v)id) For the value of the probability mapping function, vidIs the velocity, x, of the particleidIs the position of the particle. And rand () is a random number between 0-1.
(6) After the iteration is finished, the global optimal value is the optimal target solution, namely the fault solution.
The fault evaluation in the step (4) is specifically as follows:
comparing the result obtained in claim 5, i.e. the actual state, with the expected state, and if the expected state is 0 and the actual state is 1, the protection device is malfunction; if the expected state is 1 and the actual state is 0, the protection device refuses to operate; if the two values are the same, it is correct. Comparing the alarm information with the alarm information, and if the alarm state is 0 and the actual state is 1, the protection device fails to report the information; if the alarm state is 1 and the actual state is 0, the protection device misreads information; if they are the same, it is correct.
The technical solution of the present invention will be further described in detail with reference to the accompanying drawings.
The invention takes the system of the contact structure diagram of fig. 2 as a test system, takes a fault case and takes the fault diagnosis processing flow diagram shown in fig. 1 as a description flow to diagnose the fault.
The elements in fig. 2, the circuit breaker, and the protection devices for these elements are first numbered.
As can be seen from fig. 2, the system comprises a shore power supply GB; two onboard generators GB1, GB 2; 4 transformers T1-T4; 1 shipborne substation TB; two main switchboard panels B1, B2; 4 area distribution boards B3-B6; 11 lines L1-L11; 37 protection breakers CB 1-CB 37.
Numbering 25 elements (S)1～C25):GB,G1,G2,B1…B6,T1…TB,L1…L11。
37 breakers are numbered (C)1～C37):C1…C37。
Numbering in 64 protections (R)1～R64): the number of main protections is 25, the number of near backup protections is 25, and the number of far backup protections is 14 because far backup protections are not arranged on bottom-layer elements due to the particularity of ship power. Numbering according to the protection each element has, e.g. B1 has 3 protections, B1m, B1p, B1s, so R10，R11，R12。
When a fault occurs, the received alarm signals are as follows: the protection T1p, B1s, T2m and L5p act, and the circuit breakers CB5, CB3, CB1, CB6, CB7 and CB13 trip. The following are specific diagnostic procedures:
(1) by using the topological diagrams of the power system network before and after the fault, the elements to be subjected to the possible fault in the fault area are B1, B3, B4, T1, T2, L3, L4, L5 and L6. Labeling is performed with the corresponding element state vector S ═ S1,s2,s3,s4,s5,s6,S7,S8,s9](ii) a The breaker state vector associated with these elements is C ═ C1,c2,c3,…c8,…c14]The circuit breakers CB1, CB3, CB4, CB5, CB6, CB7, CB9, CB10, CB11, CB12, CB13, CB14, CB15 and CB16 correspond to the circuit breakers CB1, CB3, CB4, CB5 and CB16 respectively. Similarly, the protection state vector associated with these elements is R ═ R1,r2,r3,…r8,…r23]The corresponding protections are B1m, B1p, B1s, B3m, B3p, B3s, B4m, B4p, B4s, T1m, T1p, T1s, T2m, T2p, T2s, L3m, L3p, L4m, L4p, L5m, L5p, L6m and L6 p.
(2) And (3) further screening the elements obtained in the step (1) by calculating the fault test indexes of the elements:
a) firstly, calculating a protection alarm correlation index:
the protection alarm relevance index has the following expression:
Figure BDA0002923816800000131
Er,iand Er,0Using the formula:
Figure BDA0002923816800000132
Figure BDA0002923816800000133
and (4) calculating.
Nr,iUsing the formula: n is a radical ofr,i＝wmnim+wpnip+wsnisAnd (4) calculating.
Assuming that none of the elements in the vector of step 1 has failed, the element states are all 0, and E is obtained in the carry-inr,0Equal to 14, then sequentially taking B1 as possible failure, i.e. state 1, the rest as no failure, state 0, results in: er＝[23,25,25,9,8,25,25,11,25]It is reacted with Nr,iK is obtained by calculation in the index of the brought-in protection alarm association systemr＝[0.81,1,1-0.45,-0.55,1,1,-0.27,1]。
b) Calculating the alarm index of the main-free breaker:
the alarm relevance index of the no main breaker has the following expression:
Figure BDA0002923816800000134
since the case has no main breaker 0, K isc＝[1,1,1,1,1,1,1,1,1]。
c) Calculating a component fault test index:
the component failure test index has the following expression:
Ki＝Kr,iKc,i
subjecting K obtained in steps a) and b)r,iKc,iSubstituted and available K ═ 0.81,1,1-0.45, -0.55,1,1, -0.27,1]Here we set a threshold of 0.2, below which we are suspected faulty elements, otherwise we are not, so we can go to suspected faulty elements T1, T2, L5.
(3) And (3) establishing a fault hypothesis X by using the elements obtained in the step 2 and the associated protection and circuit breaker, wherein the fault hypothesis X is { T1, T2, L5, B1s, T1m, T1p, T2m, T2p, T2s, L5m, L5p, CB1, CB3, CB4, CB5, CB6, CB7, CB13 and CB14 }.
The objective function is:
Figure BDA0002923816800000141
solving the objective function by adopting an improved binary particle swarm algorithm, initializing some parameters of the algorithm: the population number is 20, the maximum iteration number is 100, the learning factors are 1.5 and 2.5, and the inertial weight is 0.5.
The position updating formula in the particle swarm algorithm is improved, and when iterative computation is carried out, the improved position updating formula is used for computation, and the formula is as follows:
the Sigmond function is modified as follows:
Figure BDA0002923816800000142
when v isidWhen the content is less than or equal to 0:
Figure BDA0002923816800000143
when v isid>At time 0:
Figure BDA0002923816800000144
in the above formula: s (v)id) For the value of the probability mapping function, vidIs the velocity, x, of the particleidAnd rand () is a random number between 0-1 for the position of the particle.
The improved binary particle swarm algorithm can reach an optimal solution by only iterating 5 steps, wherein E (X) is 5, and the fault hypothesis that E (X) is 5 is X [1,1,1,1,0,1,1,0,0,0,1,1,1,0 ].
(4) Analyzing results;
comparing the actual state with the alarm state and the expected state, the elements that may result in a fault are transformers T1, T2, line L5, with specific fault details: when the transformer T1 fails, the main protection T1m refuses to operate, the near backup protection T1p operates, the circuit breakers CB5 and CB4 are cut off, but the CB4 refuses to operate, the second backup protection B1s provided by the upper layer bus B1 operates, and the circuit breakers CB1, CB3 and CB6 are cut off; when the transformer T2 fails, the main protection T2m acts to cut off the CB6 and the CB 7; when a fault occurs on the line L5, the main protection L5m refuses to operate, the near backup half kettle L5p operates, and the CB13 and the CB14 are cut off, but the CB14 information is reported in a missing way.
Example two:
the embodiment provides a ship shore power fault diagnosis device, the device includes:
a failure zone determination module: the system is used for determining a fault occurrence area by comparing ship shore power system diagrams before and after the fault;
suspicious element screening module: the failure detection system is used for calculating failure measure indexes of all original elements in the failure occurrence area, analyzing and comparing the failure measure indexes, and further screening elements to obtain suspicious elements which are likely to fail;
an analytical model optimization module: the system comprises a suspected element, a protection and circuit breaker, a corresponding matrix, a ship shore power fault diagnosis and analysis model and a ship shore power fault diagnosis and analysis model, wherein the suspected element and the protection and circuit breaker are associated with the suspected element, the corresponding matrix is established to obtain the corresponding ship shore power fault diagnosis and analysis model, and the ship shore power fault diagnosis and analysis model is optimized by using a binary particle swarm algorithm to obtain the optimized ship shore power fault diagnosis and analysis model;
and a fault evaluation module: and the system is used for calculating and obtaining the actual state of the element through the optimized ship shore power fault diagnosis analysis model, and comparing the obtained actual state of the element with alarm information and an expected state respectively to obtain fault evaluation.
Example three:
the embodiment of the invention also provides a ship shore power fault diagnosis device, which comprises a processor and a storage medium;
the storage medium is used for storing instructions;
the processor is configured to operate in accordance with the instructions to perform the steps of the method of embodiment one.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.

Claims (10)

1. A ship shore power fault diagnosis method is characterized by comprising the following steps:
determining a fault occurrence area by comparing ship shore power system diagrams before and after the fault;
calculating the fault measure indexes of all original components in the fault occurrence area, analyzing and comparing, and further screening the components to obtain suspicious components which are likely to have faults;
inputting the actual state and the expected state of the screened possible fault element into a ship shore power fault diagnosis analysis model to obtain a target function set of the possible fault element;
and solving the target function set through an improved binary particle swarm algorithm to obtain the actual state of the element, and comparing the obtained actual state of the element with the alarm state and the expected state respectively to evaluate the fault.
2. The ship shore power fault diagnosis method according to claim 1, wherein the ship shore power fault diagnosis analysis model includes:
Figure FDA0002923816790000011
in the formula: e (x) represents the value of the objective function, rkmAnd rkm *The actual and expected states of the primary protection represented as a certain element; r iskpAnd rkp *The thief represents the actual and expected state of near backup protection for a certain element; r isksAnd rks *Actual and expected states of far backup protection for the element; ciAnd Ci *Respectively representing the actual and desired states of a certain circuit breaker.
3. The marine shore power failure diagnostic method of claim 2, wherein the desired states of the components include a desired state of main protection, a desired state of near backup protection, a desired state of far backup protection, and a desired state of circuit breaker;
the calculation formula of the expected state of the main protection is as follows:
Figure FDA0002923816790000021
in the formula:
Figure FDA0002923816790000022
indicating the desired state of the main protection, SnIndicates the state of a certain element, SnWhen 0, it means that the element is normal, SnA value of 1 indicates that the element is faulty;
Figure FDA0002923816790000023
if the value is 0, the protection expected state does not act, otherwise, the protection expected state acts;
the calculation formula of the expected state of the near backup protection is as follows:
Figure FDA0002923816790000024
in the formula: r iskmIs a component SnThe main protection actual state of (1) indicates that the protection is not operating when the value is 0 and indicates that the protection is operating when the value is 1,
Figure FDA0002923816790000025
then the element is associated with a near backup protection expected state, when the value is 0, the protection expected state is not action, and when the value is 1, the protection expected state is action;
the calculation formula of the expected state of the far backup protection is as follows:
Figure FDA0002923816790000026
in the formula:
Figure FDA0002923816790000027
is a component SnThe associated far backup protection expected state indicates that the protection expected state does not act when the value is 0, and indicates that the protection expected state acts when the value is 1; z (r)km,Sn) Is composed of
Figure FDA0002923816790000028
S in the protection areanAll closely associated device sets, P ((r)km,SX) To protect
Figure FDA0002923816790000029
Is from the starting point to SXA set of all breaker states on the path;
the calculation formula of the expected state of the circuit breaker is as follows:
Figure FDA00029238167900000210
in the formula: ciAnd
Figure FDA00029238167900000211
the actual state and the expected state of the circuit breaker are obtained, when the value is 0, the circuit breaker state is not disconnected, and when the value is 1, the circuit breaker state is disconnected; r (C)i) The protection sets capable of being opened by the circuit breaker comprise main protection, near backup protection and far backup protection.
4. The ship shore power fault diagnosis method according to claim 3, wherein the determining the fault occurrence region by comparing the ship shore power system diagrams before and after the fault specifically comprises: constructing a fault information matrix based on the uploaded alarm information, and establishing a section discrimination exclusive or logic by combining a correlation matrix between the switches and the sections; and positioning the fault section through the section discrimination exclusive-OR logic.
5. The ship shore power fault diagnosis method according to claim 4, wherein the method for calculating the fault test index includes:
failure test index K of elementiThe calculation formula of (2) is as follows:
Ki＝Kr，iKc，i
in the formula, KiIndicates the failure test index, Kr，iThe method comprises the steps of representing a protection alarm relevance index and representing a no-main breaker alarm relevance index; when K isiWhen the value is smaller than the preset value, the element i is a suspicious element, otherwise, the element i is a normal element;
the protection alarm relevance index Kr，iThe expression of (a) is as follows:
Figure FDA0002923816790000031
in the formula: er，0An objective function value assuming no failure; er，iThe objective function value when the element i alone is supposed to fail; n is a radical ofr，iThe value of the protection number associated with element i is determined by the following equation:
Nr，i＝wmnim+wpnip+wsnis
in the formula: n isim，nip，nisThe number of primary protection, near backup protection and far backup protection associated with the element i respectively; and wm，wp，wsRespectively representing each protection action coefficient;
alarm relevance index K of main-free circuit breakerc，iThe calculation formula of (2) is as follows:
Figure FDA0002923816790000032
in the formula: n iscnm，iAnd ncns，iThe number of non-main breakers associated with the respective element i through main protection and far backup protection; n iscm，iAnd ncs，iThen is the total number of circuit breakers associated by element i through the main protection and far backup protection; n isrm，iAnd nrs，iThe number of primary and far backup protections associated with element i.
6. The ship shore power fault diagnosis method of claim 5, wherein said method for solving said set of objective functions by modified binary particle swarm optimization comprises the following steps:
setting improved binary particle swarm algorithm parameters, wherein the improved binary particle swarm algorithm parameters comprise: the number of group individuals, learning factors, inertial weight and maximum iteration times;
randomly initializing the speed and the position of the population according to the dimension of the corresponding matrix, and then preliminarily obtaining a local optimal value and a global optimal value of the population;
comparing the current objective function value with a local optimal value and a global optimal value respectively; if the local optimal value is less than or equal to the current objective function value, the local optimal value is kept unchanged; if the local optimum value is larger than the current objective function value, updating the local optimum value into the current objective function value;
if the global optimum value is less than or equal to the current objective function value, the global optimum value is kept unchanged; if the global optimum value is larger than the current objective function value, updating the global optimum value into the current objective function value;
and when the iteration of the maximum iteration times set by the improved binary particle swarm algorithm is finished, obtaining a global optimal value, namely an optimal target solution.
7. The marine shore power fault diagnosis method of claim 6, wherein said method of solving said set of objective functions by modified binary particle swarm optimization further comprises: the location update function is updated using the following formula:
the Sigmond function is modified as follows:
Figure FDA0002923816790000041
when v isidWhen the content is less than or equal to 0:
Figure FDA0002923816790000042
when v isid>At time 0:
Figure FDA0002923816790000043
in the above formula: s (v)id) For the value of the probability mapping function, vidIs the velocity, x, of the particleidAnd rand () represents a random number between 0-1 for the position of the particle.
8. The ship shore power fault diagnosis method according to claim 4, wherein the fault evaluation method specifically comprises:
comparing the actual state of the element with the alarm information and the expected state respectively, and if the expected state is 0 and the actual state is 1, the protection device is in false operation; if the expected state is 1 and the actual state is 0, the protection device refuses to operate; if the two values are the same, the protection device is correct;
comparing the alarm information with the alarm information, and if the alarm state is 0 and the actual state is 1, the protection device fails to report the information; if the alarm state is 1 and the actual state is 0, the protection device misreads information; if the two are the same, the protection device is correct.
9. A ship shore power failure diagnosis apparatus, characterized by comprising:
a failure zone determination module: the system is used for determining a fault occurrence area by comparing ship shore power system diagrams before and after the fault;
suspicious element screening module: the failure detection system is used for calculating failure measure indexes of all original elements in the failure occurrence area, analyzing and comparing the failure measure indexes, and further screening elements to obtain suspicious elements which are likely to fail;
an analytic model solving module: inputting the actual state and the expected state of the screened possible fault element into a ship shore power fault diagnosis analysis model to obtain a target function set of the possible fault element;
and a fault evaluation module: and solving the target function set through an improved binary particle swarm algorithm to obtain the actual state of the element, and comparing the obtained actual state of the element with the alarm state and the expected state respectively to evaluate the fault.
10. A ship shore power fault diagnosis device is characterized by comprising a processor and a storage medium;
the storage medium is used for storing instructions;
the processor is configured to operate in accordance with the instructions to perform the steps of the method according to any one of claims 1 to 8.
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