CN116821821A - Method and device for determining fault risk of chilled water system and electronic equipment - Google Patents
Method and device for determining fault risk of chilled water system and electronic equipment Download PDFInfo
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Abstract
The application discloses a method and a device for determining fault risk of a chilled water system and electronic equipment, and belongs to the field of fault probability determination. The method for determining the fault risk of the chilled water system comprises the following steps of: constructing a fuzzy fault tree corresponding to the chilled water system, wherein the fuzzy fault tree comprises a top event, an intermediate event and a basic event; acquiring first fault data of the chilled water system based on the fuzzy fault tree, wherein the first fault data represents fuzzy probability distribution of basic events; determining second fault data according to the first fault data, wherein the second fault data represents fuzzy probability distribution of the top event and the middle event; and determining fault risk measurement data of the chilled water system according to the first fault data and the second fault data. In the application, the second fault data can be determined through the collected first fault data, so that the fuzzy probability distribution of fault events in the fuzzy fault tree is obtained, and the effect of fault risk measurement data in the chilled water system is improved.
Description
Technical Field
The present application relates to the field of fault probability measurement, and in particular, to a method and an apparatus for measuring a fault risk of a chilled water system, and an electronic device.
Background
Today, chilled water systems are utility systems used in nuclear power systems, and typically the chilled water systems may cause abnormal operation or direct power failure of equipment due to failure of components, so that it is necessary to detect components in the chilled water system, thereby obtaining the level of possibility of system failure caused by component failure in the system.
In the prior art, in order to obtain relevant data of system faults, a relevant technician generally adopts a reliability analysis method without specific quantification, namely, adopts a definite theory analysis method, wherein the definite theory analysis method is based on a deep defense concept, aims at ensuring three basic safety functions of reactivity control, waste heat discharge and radioactivity containment, adopts a conservative assumption and analysis method aiming at a definite design reference working condition, and meets a set of methods of specific acceptance criteria, and the obtained fault risk measurement data effect is poor due to the fact that the definite theory analysis method without quantitative analysis is adopted.
Disclosure of Invention
The disclosure provides a method, a device, electronic equipment and a storage medium for measuring the fault risk of a chilled water system, so as to solve the problem of poor data effect on the fault risk measurement of the chilled water system.
According to an aspect of the present disclosure, there is provided a method for determining a risk of malfunction of a chilled water system, comprising:
constructing a fuzzy fault tree corresponding to the chilled water system, wherein the fuzzy fault tree comprises a top event, an intermediate event and a basic event;
acquiring first fault data of a chilled water system based on the fuzzy fault tree, wherein the first fault data represents fuzzy probability distribution of the basic event;
determining second fault data from the first fault data, the second fault data representing a fuzzy probability distribution of the top event and the intermediate event;
and determining fault risk measurement data of the chilled water system according to the first fault data and the second fault data.
According to another aspect of the present disclosure, there is provided an apparatus for determining a risk of malfunction of a chilled water system, comprising:
the construction module is used for constructing a fuzzy fault tree corresponding to the chilled water system, wherein the fuzzy fault tree comprises a top event, an intermediate event and a basic event;
the acquisition module is used for acquiring first fault data of the chilled water system based on the fuzzy fault tree, wherein the first fault data represents fuzzy probability distribution of the basic event;
a first determining module for determining second fault data according to the first fault data, wherein the second fault data represents fuzzy probability distribution of the top event and the middle event;
and the second determining module is used for determining fault risk measurement data of the chilled water system according to the first fault data and the second fault data.
According to another aspect of the present disclosure, there is provided an electronic device including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the chilled water system fault risk determination methods provided by the present disclosure.
According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the method of determining a risk of a chilled water system failure provided by the present disclosure.
In the method, firstly, a fuzzy fault tree corresponding to a chilled water system is constructed, fault events in the chilled water system are included in the fuzzy fault tree, the fault events are divided into different layers, second fault data representing top events and intermediate events are determined through first fault data representing basic events, and fault risk measurement data representing the whole chilled water system is determined according to the first fault data and the second fault data. The method can improve the effect of the fault risk measurement data of the chilled water system.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.
Drawings
The drawings are for a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
FIG. 1 is a flow chart of a method of determining risk of chilled water system failure provided by the present disclosure;
FIG. 2 is a schematic diagram of a chilled water system provided by the present disclosure;
FIG. 3 is a schematic diagram of a fuzzy fault tree provided by the present disclosure;
FIG. 4 is a block diagram of a chilled water system fault risk determination apparatus provided by the present disclosure;
FIG. 5 is another block diagram of a chilled water system fault risk determination apparatus provided by the present disclosure;
FIG. 6 is another block diagram of an apparatus for determining risk of failure of a chilled water system provided by the present disclosure;
FIG. 7 is another block diagram of a chilled water system fault risk determination device provided by the present disclosure;
FIG. 8 is another block diagram of a chilled water system fault risk determination apparatus provided by the present disclosure;
fig. 9 is a block diagram of an electronic device for implementing a chilled water system fault risk determination method in accordance with an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Referring to fig. 1, fig. 1 is a flowchart of a method for determining a risk of failure of a chilled water system provided by the present disclosure, as shown in fig. 1, including the following steps:
and step S101, constructing a fuzzy fault tree corresponding to the chilled water system, wherein the fuzzy fault tree comprises a top event, an intermediate event and a basic event.
The establishment of the fuzzy fault tree can be constructed according to a chilled water system, wherein the events in the fuzzy fault tree correspond to fault events in the chilled water system, and the fuzzy fault tree can comprise top events, middle events and basic events according to the hierarchy or the inclusion relation of the fault events.
It should be noted that, the top event is the top of the fuzzy fault tree, and may be a fault event, for example: taking 'system lost' as the top event of the fuzzy fault tree. Wherein the system loses functionality represented by the chilled water system described above.
In addition, the number of the intermediate events and the basic events and the number of layers of the intermediate events and the basic events in the fuzzy fault tree may be determined according to a rule of fault tree setting construction, wherein the number of the intermediate events and the basic events may be determined according to a division depth and a division breadth of fault events in the chilled water system, and the embodiment of the present application is not limited to the number of the intermediate events and the basic events.
Step S102, first fault data of the chilled water system is obtained based on the fuzzy fault tree, wherein the first fault data represents fuzzy probability distribution of the basic event.
The first fault data represents a fuzzy probability distribution of the basic event, wherein the basic event may be a fault event corresponding to the chilled water system, i.e. the fuzzy probability distribution of the fault event in the chilled water system is obtained.
It should be noted that, the first failure data may be obtained by obtaining related literature data or a part of industry investigation, which is not limited to the embodiment of the present application.
Step S103, determining second fault data according to the first fault data, wherein the second fault data represents fuzzy probability distribution of the top event and the middle event.
And determining the second fault data according to the first fault data, wherein the second fault data can be obtained according to the first fault data and a triangle ambiguity theory, and the triangle ambiguity theory needs to acquire the logic relationship between the basic event and the intermediate event as well as the top event.
In addition, the determination of the second fault data according to the first fault data may be obtained according to other functions, and may represent the logical relationship between the basic event and the intermediate event as well as the top event, which is not limited in this embodiment of the present application.
And step S104, determining fault risk measurement data of the chilled water system according to the first fault data and the second fault data.
The first failure data represents a probability distribution of a blur of the basic event, the second failure data represents a probability distribution of a blur of the intermediate event and the top event, and the probability distribution of a blur of the basic event, the intermediate event, and the top event is obtained by integrating the first failure data and the second failure data, that is, the probability distribution of a blur of all failure events to be acquired in the cooling water system is obtained, and the probability distribution of a blur is used as the failure risk measurement data.
In this embodiment, first, a fuzzy fault tree corresponding to the chilled water system is constructed, the fuzzy fault tree includes fault events in the chilled water system, the fault events are divided into different layers, second fault data representing top events and intermediate events are determined through first fault data representing basic events, and fault risk measurement data representing the whole chilled water system is determined according to the first fault data and the second fault data. The method can improve the effect of the fault risk measurement data of the chilled water system.
As an alternative embodiment, the constructing a fuzzy fault tree corresponding to the chilled water system includes: selecting a system fault event as the top event of the fuzzy fault tree; n system fault events are selected as the intermediate events of the fuzzy fault tree, the intermediate events are set to be M layers, N is an integer greater than 0, and M is a positive integer less than or equal to N; k system fault events are selected as the basic events of the fuzzy fault tree, the basic events are set to be L layers, K is an integer greater than 0, and L is a positive integer less than or equal to K.
The number of layers of the intermediate event and the basic event in the fuzzy fault tree may be set according to a hierarchy or a containing relationship of the fault event, which is not limited in the embodiment of the present application.
M is a positive integer less than or equal to N, meaning that each layer contains at least one of the above-described intermediate events.
And L is a positive integer less than or equal to K, and each layer at least comprises one basic event.
The construction of the fuzzy fault tree may be determined according to the component structure of the chilled water system, referring to fig. 2, fig. 2 is a structural diagram of the chilled water system, where the chilled water system is mainly composed of three water-cooled chiller units, namely, a water-cooled chiller unit, B water-cooled chiller unit and C water-cooled chiller unit, and the three water-cooled chiller units are commonly connected to the same air-cooled chiller unit, so that the corresponding fuzzy fault tree may be generated by the structure.
Referring to fig. 3, fig. 3 is a fuzzy fault tree generated according to the architecture of the chilled water system in fig. 2, wherein a top event in the fuzzy fault tree may be set as a system loss event, which indicates a functional failure in the chilled water system, and an intermediate event in the fuzzy fault tree may be set as an accident time loss event, a normal operation loss event, an a column failure event, a B column failure event, a C column failure event, an air cooling column failure event, etc. in fig. 3, wherein a normal operation loss event in a second layer in the fuzzy fault tree may indicate a system loss due to a component during operation, and an accident time loss event may indicate a final hot trap loss of the chilled water system or a plant outage.
In addition, numerals 1 to 17 in fig. 3 represent basic events in the above-mentioned chilled water system, and specific fault event names of the above-mentioned basic events may refer to table 1, and table 1 is a basic event table in the above-mentioned chilled water system:
TABLE 1
In this embodiment, the fuzzy fault tree is constructed by the specific component arrangement and the combination relationship between components in the chilled water system, so that the logic relationship between fault events can be obtained through the fuzzy fault tree, thereby improving the effect on the chilled water system fault risk measurement data.
As an optional implementation manner, the acquiring the first fault data of the chilled water system based on the fuzzy fault tree includes: determining the type of the basic event in the fuzzy fault tree; matching corresponding event names according to the types of the basic events; and acquiring the first fault data of the event name, wherein the first fault data represents fuzzy probability distribution of the basic event.
In the determining the basic event type in the fuzzy fault tree, a structure corresponding to the basic event may be determined, where the structure may be represented as being composed of a plurality of components. That is, the process of determining the basic event type in the fuzzy fault tree may be expressed as a process of narrowing the locking range.
After the process of matching the corresponding event names according to the types of the basic events, the fuzzy probability distribution of the corresponding event names is directly obtained, namely the first fault data is obtained.
The event name corresponding to the basic event in the fuzzy fault tree may correspond to the basic event name in table 1, that is, the first fault data may obtain a fuzzy probability distribution corresponding to the basic event name in table 1, see table 2, where table 2 is a fuzzy probability distribution corresponding to the basic event in table 1, and the fuzzy probability distribution of the basic event may be based on a triangle fuzzy number theory, and l, m, and u in table 2 represent parameters in the triangle fuzzy number theory.
In this embodiment, the type of the basic event in the fuzzy fault tree is first determined, and the event name corresponding to the basic event matching is locked according to the type, so that the fuzzy probability distribution representing the basic event can be obtained according to the event name corresponding to the basic event matching, and by this method, the effect on the frozen water system fault risk measurement data can be improved.
TABLE 2
As an alternative embodiment, the determining the second fault data according to the first fault data includes: determining a logic relationship between a fault event corresponding to the first fault data and a fault event corresponding to the second fault data; substituting the first fault data into a logic AND gate operator for quantitative analysis under the logic relation that the fault event corresponding to the first fault data and the fault event corresponding to the second fault data are AND gates, so as to obtain the second fault data; substituting the first fault data into a logic OR operator for quantitative analysis under the logic relation that the fault event corresponding to the first fault data and the fault event corresponding to the second fault data are OR gates, so as to obtain the second fault data.
The fault event corresponding to the first fault data and the fault event corresponding to the second fault data have a certain logic relationship, the fault event corresponding to the first fault data can be interpreted as a branch or a thinned part of the fault event corresponding to the second fault data, and the components in the chilled water system can be arranged in parallel or according to a certain hierarchical relationship, so that the faults of some components can drive the abnormal operation of the related components.
In the case that the chilled water system structure corresponds to fig. 2, see table 3, where table 3 is a data graph corresponding to the second fault data, and table 3 shows a fuzzy probability distribution of the intermediate event and the top event, where a system failure event is a top event of a fuzzy fault tree, and a column a failure event, an air cooling machine failure event, an air cooling column failure event, a normal operation failure event, and an accident failure event are intermediate events of the fuzzy fault tree.
TABLE 3 Table 3
In this embodiment, according to determining a logic relationship between a fault event corresponding to the first fault data and a fault event corresponding to the second fault data, the logic relationship may correspondingly generate a logic and gate operator and a logic or gate operator, and according to the determined logic relationship, bring the first fault data into the corresponding logic and gate operator and logic or gate operator, and perform quantitative analysis, to obtain the second fault data. The fuzzy probability distribution of the intermediate event and the top event can be obtained by the method, so that the effect of measuring the data of the fault risk of the chilled water system is improved.
As an alternative embodiment, the logical and gate operator is determined by the following formula:
wherein ,representing a logical AND gate operator, l AND 、m AND 、u AND Respectively representing parameters in triangle fuzzy number under AND gate logic relationship, +.>Representing the sum of probability values of n events occurring in the case of a logical AND gate, +.>Respectively represent l AND 、m AND 、u AND The sum of the accumulation of n events.
The logical OR gate operator is determined by the following formula:
wherein ,representing logical OR gate operator, l OR 、m OR 、u OR Respectively representing parameters in triangle ambiguity number under OR gate logic relationship, +.>Representing the sum of probability values of occurrence of n events in the case of a logical or gate,respectively indicate->The sum of the accumulation of n events.
The logical AND gate operator and the logical OR gate operator can be obtained according to a triangle fuzzy number theory, wherein the triangle fuzzy number theory can be expressed by the following formula:
wherein, let U be the domain of an object, then a fuzzy number is set on the domain of UDefined as a membership function expressed by the above formula, mapping the elements in U to [0,1 ]]The real number in (1) is marked as +.> wherein ,/>Expressed as the degree to which the element x in the universe U belongs to the fuzzy set a, simply referred to as the degree of membership to a. And->The greater the degree to which x belongs to A, the stronger the degree to which x belongs to A, and if the membership function for a fuzzy number consists of a linear function, it can be expressed by the following formula:
wherein m is calledIs l+u is +.>The membership function of which is shown in FIG. 1, such ambiguities are called triangular ambiguities, noted +.>
It should be noted that, the logical AND gate operator in the conventional fault tree can be expressed asqi is expressed as a probability value of occurrence of an event i, and a logical AND gate operator which can obtain fuzzy processing by combining a triangle fuzzy number theory is as follows:
whereas logical OR operators in a conventional fault tree can be represented asThe logical OR gate operator which can obtain fuzzy processing by combining the triangle fuzzy number theory is as follows:
in this embodiment, according to the determined logical and gate operator and logical or gate operator, the corresponding first fault data is substituted to obtain the probability distribution of ambiguity of the intermediate event and the top event, so as to obtain the probability distribution of all ambiguity corresponding to the fault event in the chilled water system, and further improve the effect on the chilled water system fault risk measurement data.
As an alternative embodiment, after said determining fault risk measurement data of said chilled water system from said first fault data and said second fault data, said method further comprises: and determining a configuration result of the chilled water system according to the risk measurement data, wherein the configuration result is used for configuring at least one integral component in the chilled water system.
In this embodiment, after the first failure data and the second failure data are obtained and the first failure data and the second failure data are integrated to obtain the failure risk measurement data, the probability of occurrence of a failure after each component combination is determined according to the failure risk measurement data, and the overall components of the chilled water system are configured by selecting an optimal scheme according to the comparison of different component combinations, thereby improving the stability of the chilled water system during operation.
Referring to fig. 4, fig. 4 is a device for determining a risk of a chilled water system failure provided by the present disclosure, and as shown in fig. 4, the device 400 for determining a risk of a chilled water system failure includes:
a construction module 401, configured to construct a fuzzy fault tree corresponding to the chilled water system, where the fuzzy fault tree includes a top event, an intermediate event, and a base event;
an acquisition module 402, configured to acquire first fault data of a chilled water system based on the fuzzy fault tree, where the first fault data represents a fuzzy probability distribution of the basic event;
a first determining module 403, configured to determine second fault data according to the first fault data, where the second fault data represents a fuzzy probability distribution of the top event and the middle event;
a second determining module 404 is configured to determine fault risk measurement data of the chilled water system according to the first fault data and the second fault data.
Optionally, as shown in fig. 5, the building unit 401 includes:
a first selection unit 4011 for selecting a system fault event as the top event of the fuzzy fault tree;
a second selection unit 4012, configured to select N system fault events as the intermediate events of the fuzzy fault tree, and set the intermediate events as M layers, where N is an integer greater than 0, and M is a positive integer less than or equal to N;
a third selecting unit 4013, configured to select K system fault events as the basic events of the fuzzy fault tree, where K is an integer greater than 0 and L is a positive integer less than or equal to K, where the basic events are set as L layers.
Optionally, as shown in fig. 6, the obtaining module 402 includes:
a first determining unit 4021 configured to determine a type of the basic event in the fuzzy fault tree;
a first matching unit 4022, configured to match corresponding event names according to the type of the basic event;
the first obtaining unit 4023 is configured to obtain the first fault data of the event name, where the first fault data represents a probability distribution of ambiguity of the basic event.
Optionally, as shown in fig. 7, the first determining module 403 includes:
a second determining unit 4031, configured to determine a logical relationship between a fault event corresponding to the first fault data and a fault event corresponding to the second fault data;
a first generating unit 4032, configured to, when a fault event corresponding to the first fault data and a fault event corresponding to the second fault data are logical relationships of and gates, substitute the first fault data into a logical and gate operator for quantitative analysis, so as to obtain the second fault data;
and a second generating unit 4033, configured to, under a logical relationship that a fault event corresponding to the first fault data and a fault event corresponding to the second fault data are or gates, substitute the first fault data into a logical or gate operator for quantitative analysis, so as to obtain the second fault data.
Optionally, the logical AND gate operator is determined by the following formula:
wherein ,representing a logical AND gate operator, l AND 、m AND 、u AND Respectively representing parameters in triangle fuzzy number under AND gate logic relationship, +.>Representing the sum of probability values of n events occurring in the case of a logical AND gate, +.>Respectively indicate->The sum of the accumulation of n events.
The logical OR gate operator is determined by the following formula:
wherein ,representing logical OR gate operator, l OR 、m OR 、u OR Respectively representing parameters in triangle ambiguity number under OR gate logic relationship, +.>Representing the sum of probability values of occurrence of n events in the case of a logical or gate,respectively indicate->The sum of the accumulation of n events.
Optionally, as shown in fig. 8, the apparatus 400 further includes:
a third determining module 405 is configured to determine a configuration result of the chilled water system according to the risk measurement data, where the configuration result is used to configure at least one integral component in the chilled water system.
According to an embodiment of the disclosure, the disclosure further provides an electronic device, a readable storage medium.
Fig. 9 shows a schematic block diagram of an example electronic device 900 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 9, the apparatus 900 includes a computing unit 901 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 902 or a computer program loaded from a storage unit 908 into a Random Access Memory (RAM) 903. In the RAM 903, various programs and data required for the operation of the device 900 can also be stored. The computing unit 901, the ROM 902, and the RAM 903 are connected to each other by a bus 904. An input/output (I/O) interface 905 is also connected to the bus 904.
Various components in device 900 are connected to I/O interface 905, including: an input unit 906 such as a keyboard, a mouse, or the like; an output unit 907 such as various types of displays, speakers, and the like; a storage unit 908 such as a magnetic disk, an optical disk, or the like; and a communication unit 909 such as a network card, modem, wireless communication transceiver, or the like. The communication unit 909 allows the device 900 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunications networks.
The computing unit 901 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 901 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 901 performs the respective methods and processes described above, such as a method of determining the risk of a chilled water system failure. For example, in some embodiments, the method of determining the risk of a chilled water system failure may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as the storage unit 908. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 900 via the ROM 902 and/or the communication unit 909. When the computer program is loaded into the RAM 903 and executed by the computing unit 901, one or more steps of the above-described chilled water system fault risk determination method may be performed. Alternatively, in other embodiments, the computing unit 901 may be configured to perform the method of determining the risk of a chilled water system failure by any other suitable means (e.g. by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.
The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server incorporating a blockchain.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel, sequentially, or in a different order, provided that the desired results of the disclosed aspects are achieved, and are not limited herein.
The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.
Claims (10)
1. A method for determining risk of failure in a chilled water system, comprising:
constructing a fuzzy fault tree corresponding to the chilled water system, wherein the fuzzy fault tree comprises a top event, an intermediate event and a basic event;
acquiring first fault data of a chilled water system based on the fuzzy fault tree, wherein the first fault data represents fuzzy probability distribution of the basic event;
determining second fault data from the first fault data, the second fault data representing a fuzzy probability distribution of the top event and the intermediate event;
and determining fault risk measurement data of the chilled water system according to the first fault data and the second fault data.
2. The method according to claim 1, wherein the constructing a fuzzy fault tree corresponding to the chilled water system comprises:
selecting a system fault event as the top event of the fuzzy fault tree;
n system fault events are selected as the intermediate events of the fuzzy fault tree, the intermediate events are set to be M layers, N is an integer greater than 0, and M is a positive integer less than or equal to N;
k system fault events are selected as the basic events of the fuzzy fault tree, the basic events are set to be L layers, K is an integer greater than 0, and L is a positive integer less than or equal to K.
3. The method according to claim 1, wherein the acquiring first fault data of the chilled water system based on the fuzzy fault tree comprises:
determining the type of the basic event in the fuzzy fault tree;
matching corresponding event names according to the types of the basic events;
and acquiring the first fault data of the event name, wherein the first fault data represents fuzzy probability distribution of the basic event.
4. The method of claim 1, wherein determining second fault data from the first fault data comprises:
determining a logic relationship between a fault event corresponding to the first fault data and a fault event corresponding to the second fault data;
substituting the first fault data into a logic AND gate operator for quantitative analysis under the logic relation that the fault event corresponding to the first fault data and the fault event corresponding to the second fault data are AND gates, so as to obtain the second fault data;
substituting the first fault data into a logic OR operator for quantitative analysis under the logic relation that the fault event corresponding to the first fault data and the fault event corresponding to the second fault data are OR gates, so as to obtain the second fault data.
5. The assay of claim 4 wherein the logical and gate operator is determined by the following formula:
wherein ,representing a logical AND gate operator, l AND 、m AND 、u AND Respectively representing parameters in triangle fuzzy number under AND gate logic relationship, +.>Representing the sum of probability values of n events occurring in the case of a logical AND gate, +.>Respectively represent l AND 、m AND 、u AND The sum of the accumulation of n events.
The logical OR gate operator is determined by the following formula:
wherein ,representing logical OR gate operator, l OR 、m OR 、u OR Respectively representing parameters in triangle ambiguity number under OR gate logic relationship, +.>Representing the sum of probability values of occurrence of n events in the case of a logical or gate,respectively represent l OR 、m OR 、u OR The sum of the accumulation of n events.
6. The assay method of claim 1, wherein after said determining fault risk measurement data for the chilled water system from the first fault data and the second fault data, the method further comprises:
and determining a configuration result of the chilled water system according to the risk measurement data, wherein the configuration result is used for configuring at least one integral component in the chilled water system.
7. A chilled water system fault risk determination device, comprising:
the construction module is used for constructing a fuzzy fault tree corresponding to the chilled water system, wherein the fuzzy fault tree comprises a top event, an intermediate event and a basic event;
the acquisition module is used for acquiring first fault data of the chilled water system based on the fuzzy fault tree, wherein the first fault data represents fuzzy probability distribution of the basic event;
a first determining module for determining second fault data according to the first fault data, wherein the second fault data represents fuzzy probability distribution of the top event and the middle event;
and the second determining module is used for determining fault risk measurement data of the chilled water system according to the first fault data and the second fault data.
8. The chilled water system fault risk determination device according to claim 7, wherein the construction unit comprises:
a first selection unit configured to select a system failure event as the top event of the fuzzy failure tree;
a second selection unit, configured to select N system fault events as the intermediate events of the fuzzy fault tree, and set the intermediate events as M layers, where N is an integer greater than 0, and M is a positive integer less than or equal to N;
and the third selection unit is used for selecting K system fault events as the basic events of the fuzzy fault tree, wherein the basic events are set into L layers, K is an integer greater than 0, and L is a positive integer less than or equal to K.
9. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 6.
10. A non-transitory computer readable storage medium storing computer instructions, wherein the computer instructions are for causing the computer to perform the method of any one of claims 1 to 6.
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| CN202210271692.8A CN116821821A (en) | 2022-03-18 | 2022-03-18 | Method and device for determining fault risk of chilled water system and electronic equipment |
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