CN112990683A - Early warning method for flight guarantee flow node and related equipment - Google Patents
Early warning method for flight guarantee flow node and related equipment Download PDFInfo
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Abstract
The application provides an early warning method and related equipment for flight guarantee process nodes, which can better monitor each guarantee process node of a flight, can perform effective advance prediction and in-flight early warning, avoid the condition of post-processing and provide the operating efficiency of the flight. The method comprises the following steps: configuring a monitoring rule of each flow node in flight guarantee flow nodes; acquiring real-time guarantee data of a target flight, wherein the target flight is a flight to be monitored, and the real-time guarantee data comprises flight dynamics of the target flight and a guarantee process node process corresponding to the target flight; predicting whether a guarantee process node corresponding to the target flight is abnormal according to the monitoring rule of each process node and the real-time guarantee data of the target flight; and when the guarantee process node corresponding to the target flight is abnormal, sending alarm information according to the abnormity of the guarantee process node corresponding to the target flight.
Description
Technical Field
The application relates to the field of aviation, in particular to an early warning method and related equipment for flight guarantee process nodes.
Background
The development of the civil aviation industry in China is normalized, and the service scale is continuously increased. The passenger traffic of airlines rapidly increases year by year, the pressure of flight support is gradually increased, and the flight support relates to more than eighty protection links of internal and external units such as cleaning, on-board object configuration and recovery, load balance, catering, refueling and the like. The normal promotion of each guarantee link is ensured, the normality of flights is further ensured, and the urgency and the necessity of improving the service quality are highlighted.
At present, a large airline company lacks a process management concept in the aspect of flight guarantee monitoring, a guarantee task is not finely split, and three core business flows (airplane guarantee, passenger service and luggage service) are isolated from each other; the monitoring personnel are information processing guide rather than flight on-schedule guide, namely the monitoring personnel can finish processing the information in the system without being responsible for the overall normality of the flight; the flight guarantee fuzzy monitoring can not carry out effective prediction in advance and early warning in advance, and more is post-processing.
Disclosure of Invention
The application provides an early warning method and related equipment for flight guarantee process nodes, which can better monitor each guarantee process node of a flight, can perform effective advance prediction and in-flight early warning, avoid the condition of post-processing and provide the operating efficiency of the flight.
A first aspect of the embodiments of the present application provides an early warning method for flight assurance process nodes, including:
configuring a monitoring rule of each flow node in flight guarantee flow nodes;
acquiring real-time guarantee data of a target flight, wherein the target flight is a flight to be monitored, and the real-time guarantee data comprises flight dynamics of the target flight and a guarantee process node process corresponding to the target flight;
predicting whether a guarantee process node corresponding to the target flight is abnormal according to the monitoring rule of each process node and the real-time guarantee data of the target flight;
and when the guarantee process node corresponding to the target flight is abnormal, sending alarm information according to the abnormity of the guarantee process node corresponding to the target flight.
A second aspect of the embodiments of the present application provides an early warning device for flight assurance process nodes, including:
the configuration unit is used for configuring the monitoring rule of each flow node in the flight guarantee flow nodes;
the system comprises an acquisition unit, a monitoring unit and a processing unit, wherein the acquisition unit is used for acquiring real-time guarantee data of a target flight, the target flight is a flight to be monitored, and the real-time guarantee data comprises flight dynamics of the target flight and a guarantee process node process corresponding to the target flight;
the prediction unit is used for predicting whether the guarantee process node corresponding to the target flight is abnormal according to the monitoring rule of each process node and the real-time guarantee data of the target flight;
and the alarm unit is used for sending alarm information according to the abnormity of the guarantee process node corresponding to the target flight when the guarantee process node corresponding to the target flight is abnormal.
A third aspect of the embodiments of the present application provides a computer device, which includes at least one connected processor and a memory, where the memory is used to store a program code, and the program code is loaded and executed by the processor to implement the steps of the flight assurance process node early warning method according to the first aspect.
A fourth aspect of the present embodiment provides a machine-readable medium, which includes instructions that, when executed on a machine, cause the machine to perform the steps of the flight assurance process node early warning method according to the first aspect.
In summary, it can be seen that, in the embodiment provided by the application, the early warning device for flight guarantee process nodes may first determine the monitoring rule, acquire the real-time guarantee data of the flight, then predict whether the guarantee process node corresponding to the target flight is abnormal according to the monitoring rule and the guarantee data, and send out warning information according to the abnormality when the guarantee process node is abnormal. Therefore, the acquired flight guarantee data which is timely and accurate is combined with the monitoring rule, so that each guarantee flow node of the flight can be better monitored, effective advance prediction and in-flight early warning can be carried out, the condition of post-processing is avoided, and the operation efficiency of the flight is improved.
Drawings
The above and other features, advantages and aspects of various embodiments of the present application will become more apparent from the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and features are not necessarily drawn to scale.
Fig. 1 is a schematic flow chart of an early warning method for flight assurance flow nodes according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of an early warning device of a flight assurance process node according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a machine-readable medium according to an embodiment of the present disclosure;
fig. 4 is a schematic hardware structure diagram of a server according to an embodiment of the present application.
Detailed Description
Embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present application are shown in the drawings, it should be understood that the present application may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present application. It should be understood that the drawings and embodiments of the present application are for illustration purposes only and are not intended to limit the scope of the present application.
The terms "include" and variations thereof as used herein are inclusive and open-ended, i.e., "including but not limited to. The term "based on" is "based, at least in part, on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions for other terms will be given in the following description.
It should be noted that the terms "first", "second", and the like in the present application are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
It is noted that references to "a", "an", and "the" modifications in this application are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that reference to "one or more" unless the context clearly dictates otherwise.
The flight guarantee process node early warning method provided by the present application is described in terms of a flight guarantee process node early warning device, which may be a server or a service unit in the server, and is not particularly limited.
Referring to fig. 1, fig. 1 is a schematic flow chart of an early warning method for flight assurance process nodes according to an embodiment of the present application, including:
101. and configuring a monitoring rule of each flow node in the flight guarantee flow nodes.
In this embodiment, the early warning device of the flight assurance process nodes may configure a monitoring rule of each process node in the flight assurance process nodes, that is, for each assurance process node in the flight assurance process nodes, which assurance process nodes need to be monitored according to actual conditions, start and end times of each assurance process node, and early warning rules of each assurance process node, such as a ferry vehicle, are generally specified to wait under the aircraft in advance by 5 minutes according to the expected change time, an inaccurate point reaches a yellow early warning, a red early warning after 5 minutes, and the like. The flight guarantee process nodes comprise but are not limited to all guarantee links from landing to take-off of all flights of a passenger ladder vehicle, a ferry vehicle, a service airport, a passenger, a baggage, an onboard cleaning, a catering and an oiling, and the like. And the administrator combines the business requirements of the airline company to perform flexible personalized configuration on the acquired guarantee node data. Different monitoring rules are configured for different posts so as to reduce the operation pressure of workers during production peak. In addition, the configuration of the monitoring rule needs to be combined with the responsibility of a post, for example, a certain post only pays attention to the stowage and refueling, and only the monitoring rule of the stowage and refueling link is configured for the post.
It should be noted that each guarantee process node includes different guarantee tasks, and resources required by each guarantee task are different, where the guarantee task type in each guarantee process node may be divided into: basic tasks and trigger tasks; the basic task is a task which is required to be executed by each flight based on a service scene; the triggering tasks are tasks possibly occurring in the flight guarantee process, such as 'reducing passengers and turning over luggage' and 'requiring passengers to temporarily use vehicles'
102. And acquiring real-time guarantee data of the target flight.
In this embodiment, the early warning device of the flight guarantee flow node may obtain real-time guarantee data of a target flight, where the target flight is a flight to be monitored, and the real-time guarantee data includes flight real-time dynamics of the target flight and a guarantee flow node process of the target flight; the guarantee node data of the flight relates to eighty links such as cleaning of flight ground guarantee, configuration and recovery of on-board goods, load balance, catering and refueling, and comprises distribution conditions (receiving personnel and vehicles) of guarantee tasks of guarantee process nodes corresponding to the target flight, data (such as cleaning in-place time, cleaning starting time and cleaning ending time) of guarantee task key nodes and abnormal data reported by production line staff corresponding to the target flight, such as conditions that the in-place on time is influenced by road blockage or vehicle faults and the like when a ferry car goes to the off-board. It will be appreciated that the assurance data also includes which flow node the target flight is at the current time. The production data collected by the system mainly has three sources: the method comprises the following steps that equipment automatically acquires (such as the starting and ending time acquired by an RFID reader-writer, the opening/closing of a cabin door, the opening/closing of a wheel gear and the like through video intelligent analysis); external system sending or active acquisition; and manually reporting in the production line.
It should be noted that, in order to realize highly automated flight guarantee data acquisition, the early warning device of the flight guarantee process node interfaces with an Airport Operation Database (AODB), an Airport cooperative decision system (which is dominated by an Airport, and is participated by an airline company, an air traffic control company, a ground service company, and the like, and takes information sharing as a basis and takes cooperative decision as a core operation mechanism), a credit HSD system, a departure system, and advanced technologies such as video Identification, internet of things, bluetooth and Radio Frequency Identification (RFID) are introduced at the same time, so that the automatic data acquisition capability of the early warning device of the flight guarantee process node is further enhanced; simultaneously, for automatic completion guarantee data acquisition, install the RFID label additional for guarantee vehicle resource, install the RFID read write line additional such as machine position, luggage letter sorting mouth, machine position and shelter bridge install the camera additional. Thus, when the early warning device of the flight guarantee process node acquires the real-time guarantee data of the target flight, the early warning device can receive the production data uploaded by the flight guarantee process node device corresponding to the target flight; receiving abnormal data reported by production line staff corresponding to the target flight; that is to say, the early warning device of the flight guarantee process node can automatically acquire production data through hardware equipment, collect data manually reported by the production line, and determine the automatically acquired production data and the manually reported data generated by the production line staff as the real-time guarantee data of the target flight.
It should be noted that the early warning device of the flight safeguard process node may determine the monitoring rule of each process node in the flight safeguard process node through step 101, and may obtain the real-time safeguard data of the target flight through step 102, however, there is no sequential execution order limitation between these two steps, and step 101 may be executed first, step 102 may be executed first, or executed simultaneously, which is not limited specifically.
103. And predicting whether the guaranteed process node corresponding to the target flight is abnormal according to the monitoring rule of each process node and the real-time guarantee data of the target flight, and if so, executing the step 104.
In this embodiment, after the early warning device of the flight guarantee flow node obtains the monitoring rule of each flow node and the real-time guarantee data of the target flight, whether the guarantee flow node corresponding to the target flight is abnormal or not may be predicted according to the monitoring rule of each flow node and the real-time guarantee data of the target flight, and if yes, step 104 is executed. That is to say, the early warning device of the flight guarantee process node may perform data cleaning and formatting on the real-time guarantee data of the target flight to obtain the monitoring data of the first process node currently executed by the target flight, predict whether the guarantee process node corresponding to the target flight is abnormal according to the monitoring data of the first process node and the monitoring data of the target flight, and execute step 104 when it is determined that the guarantee process node corresponding to the target flight is abnormal.
In one embodiment, the guarantee process node corresponding to the target flight includes a first process node currently executed by the target flight and/or a second process node whose association degree with the first process node reaches a preset value after the first process node, and predicting whether the guarantee process node corresponding to the target flight is abnormal according to the monitoring rule of each process node and the monitoring data of the target flight includes:
determining a first monitoring rule corresponding to the first flow node in the monitoring rules of each flow node, and predicting whether the completion of the first flow node is abnormal or not according to the first monitoring rule and the monitoring data of the target flight;
and/or the presence of a gas in the gas,
and determining a second monitoring rule corresponding to the second process node in the monitoring rules of each process node, and predicting whether the second process node is abnormal according to the second monitoring rule and the completion condition of the first process node.
In this embodiment, the safeguard flow node corresponding to the target flight includes a first flow node and/or a second flow node that is currently executed, where the second flow node is a flow node after the first flow node is executed, and a degree of association between the second flow node and the first flow node reaches a preset value, the flight safeguard flow node early warning device may first determine a first monitoring rule corresponding to the first flow node and/or a second monitoring rule corresponding to the second flow node from the monitoring rules of each flow node, and then predict whether completion of the first flow node is abnormal based on the first monitoring rule and the monitoring data of the target flight, for example, the first monitoring rule specifies that a safeguard task in the first flow node needs to be completed within 20 minutes, and regarding the current time, the safeguard task in the first flow node has been executed for more than 20 minutes, if the completion of the first flow node is abnormal, executing step 104; the early warning device of the flight guarantee process node can also predict whether the second process node is abnormal or not based on the second monitoring rule and the completion condition of the first process node. The guarantee tasks have clear relevance or context, when the pre-task is abnormal, the pre-task possibly affects the post-link, and the early warning prompt can be given in time based on the actual running condition, for example, the execution time of the guarantee task of the first flow node needs 20 minutes, the current time is already executed for 19 minutes, the completion condition of the guarantee task of the first flow node is less than half, at this moment, the fact that the guarantee task of the second flow node is abnormal can be predicted, and the early warning prompt can be given in advance.
104. And sending alarm information according to the abnormity of the guarantee process node corresponding to the target flight.
In this embodiment, when the early warning device of the flight guarantee flow node determines that the guarantee flow node corresponding to the target flight is abnormal, alarm information may be sent according to the abnormality of the guarantee flow node corresponding to the target flight; for example, if the guarantee process node is a first process node and is overtime, an alarm message indicating that the first process node is overtime may be sent, the alarm message may further include specific overtime information, and if the first process node has a second process node whose association degree reaches a preset value, an alarm message corresponding to the second process node may also be sent. The alarm information comprises alarm information such as single guarantee task early warning, associated guarantee task early warning, ground guarantee delay early warning, station crossing time shortage early warning, transfer connection time shortage early warning, flight delay early warning and the like, and can be sent out according to actual conditions.
In one embodiment, the early warning device of the flight guarantee process node visually displays the completion condition of the first process node in a Gantt chart mode according to the monitoring data of the first process node and the first monitoring rule;
when the first process node is abnormal, determining the abnormal level of the first process node according to a first monitoring rule;
and visually displaying the abnormal condition of the first flow node in a Gantt chart mode based on the abnormal grade of the first flow node and the abnormal visual display rule.
In this embodiment, the early warning device of the flight assurance process node may visually display the completion condition of the first process node (the completion condition of the first process node refers to a completion condition between the time when the assurance task of the first process node is issued and the time when the assurance task of the first process node is completed) according to the monitoring data of the first process node and the first monitoring rule, that is, the early warning device of the flight assurance process node may obtain real-time data of a flight and visually display the completion condition of the assurance task of each process node of the flight from the time when the assurance task is issued to the time when the assurance task is completed, so that a user can conveniently manage and control the flight; in addition, when the abnormal condition occurs to the process node, the abnormal level of the process node can be determined according to the monitoring rule, and then the abnormal condition of the process node is visually displayed according to the abnormal level of the process node and the abnormal visual display rule. For example, the guarantee task of the first flow node is distributed to a certain employee, the first monitoring rule specifies a task starting time, a task execution time, a task ending time and a specific early warning rule, the early warning rule can be that, for example, 10 minutes before the task is started do not reach the site, the warning level 1, 5 minutes before the task is started do not reach the site, the warning level 2, the task is started do not reach the site, the warning level 3, and the early warning device of the flight guarantee flow node can visually display the completion condition of the first flow node in a gantt chart form according to the monitoring data of the first flow node and the first monitoring rule, for example, the employee sends out warning information and performs warning level 1 display on the gantt chart if the completion condition of the first flow node does not reach the site yet 10 minutes before the guarantee task of the first flow node is started. It is understood that the anomaly visualization display rule may be, for example, a color that distinguishes alarm level 1 to alarm level 3, for example, alarm level 1 is green, alarm level 2 is yellow, and alarm level 3 is red, or may be other rules, for example, a font size, without limitation.
It should be noted that, the early warning device for the flight guarantee process node may show, in addition to the early warning information of the guarantee process node on the gantt chart, other information of the guarantee process node, such as basic information of the guarantee process node, task allocation information, and task execution conditions, in the gantt chart, which is not limited specifically. In addition, the basic guarantee task is directly rendered on the Gantt chart for display, the trigger task is rendered on the Gantt chart in real time in different colors different from the basic task when the system generates the trigger task, and color change prompt is carried out on the guarantee flow node along with the progress of the guarantee task in the process of flight guarantee if the condition specified by the monitoring rule is triggered.
In summary, it can be seen that, in the embodiment provided by the application, the early warning device for flight guarantee process nodes may first determine the monitoring rule, acquire the real-time guarantee data of the flight, then predict whether the guarantee process node corresponding to the target flight is abnormal according to the monitoring rule and the guarantee data, and send out warning information according to the abnormality when the guarantee process node is abnormal. Therefore, the acquired flight guarantee data which is timely and accurate is combined with the monitoring rule, so that each guarantee flow node of the flight can be better monitored, effective advance prediction and in-flight early warning can be carried out, the condition of post-processing is avoided, and the operation efficiency of the flight is improved.
It is to be understood that the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The names of messages or information exchanged between a plurality of devices in the embodiments of the present application are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
Although the operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous.
It should be understood that the various steps recited in the method embodiments of the present application may be performed in a different order and/or in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present application is not limited in this respect.
Additionally, the present application may also be written with computer program code for performing the operations of the present application in one or more programming languages, including, but not limited to, an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The present application is described above from the perspective of the flight support process node early warning method, and is described below from the perspective of the flight support process node early warning device.
Referring to fig. 2, fig. 2 is a schematic view of a virtual structure of an early warning device for flight assurance process nodes according to an embodiment of the present application, where the early warning device 200 for flight assurance process nodes includes:
a configuration unit 201, configured to configure a monitoring rule of each flow node in flight guarantee flow nodes;
an obtaining unit 202, configured to obtain real-time guarantee data of a target flight, where the target flight is a flight to be monitored, and the real-time guarantee data includes flight dynamics of the target flight and a guarantee process node process corresponding to the target flight;
the predicting unit 203 is configured to predict whether a guarantee process node corresponding to the target flight is abnormal according to the monitoring rule of each process node and the real-time guarantee data of the target flight;
and the alarm unit 204 is configured to send alarm information according to the abnormality of the guarantee process node corresponding to the target flight when the guarantee process node corresponding to the target flight is abnormal.
In a possible implementation manner, the apparatus further includes:
the data processing unit 205 is configured to perform data cleaning and formatting on the real-time guarantee data of the target flight, so as to obtain monitoring data of a first flow node currently executed by the target flight;
the prediction unit 203 is specifically configured to:
and predicting whether the guarantee process node corresponding to the target flight is abnormal according to the monitoring rule of each process node and the monitoring data of the target flight.
In a possible implementation manner, the guarantee process node corresponding to the target flight includes a first process node currently executed by the target flight and/or a second process node after the first process node and having a degree of association with the first process node reaching a preset value, and the predicting unit 203 predicts whether the guarantee process node corresponding to the target flight is abnormal according to the monitoring rule of each process node and the monitoring data of the target flight includes:
determining a first monitoring rule corresponding to the first process node in the monitoring rules of each process node, and predicting whether the completion of the first process node is abnormal or not according to the first monitoring rule and the monitoring data of the target flight;
and/or the presence of a gas in the gas,
and determining a second monitoring rule corresponding to the second process node in the monitoring rules of each process node, and predicting whether the second process node is abnormal according to the second monitoring rule and the completion condition of the first process node.
In a possible implementation manner, the apparatus further includes:
a presentation unit 206, the presentation unit 206 being configured to:
visually displaying the completion condition of the first flow node in a Gantt chart mode according to the monitoring data of the first flow node and the first monitoring rule;
when the first flow node is abnormal, determining the abnormal level of the first flow node according to the first monitoring rule;
and visually displaying the abnormal condition of the first flow node in a Gantt chart mode based on the abnormal grade of the first flow node and an abnormal visual display rule.
In a possible implementation manner, the obtaining unit 202 is specifically configured to:
collecting production data reported by flight guarantee process node equipment corresponding to the target flight;
receiving abnormal data reported by production line staff corresponding to the target flight;
and determining the production data and the abnormal data as real-time guarantee data of the target flight.
In summary, it can be seen that, in the embodiment provided by the application, the early warning device for flight guarantee process nodes may first determine the monitoring rule, acquire the real-time guarantee data of the flight, then predict whether the guarantee process node corresponding to the target flight is abnormal according to the monitoring rule and the guarantee data, and send out warning information according to the abnormality when the guarantee process node is abnormal. Therefore, the acquired flight guarantee data which is timely and accurate is combined with the monitoring rule, so that each guarantee flow node of the flight can be better monitored, effective advance prediction and in-flight early warning can be carried out, the condition of post-processing is avoided, and the operation efficiency of the flight is improved.
It should be noted that the units described in the embodiments of the present application may be implemented by software, and may also be implemented by hardware. Here, the name of the unit does not constitute a limitation of the unit itself in some cases, and for example, the acquisition unit may also be described as "a unit that acquires credential information of a target user".
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
Referring to fig. 3, fig. 3 is a schematic diagram of an embodiment of a machine-readable medium according to the present invention.
As shown in fig. 3, the embodiment provides a machine-readable medium 300, on which a computer program 311 is stored, and when executed by a processor, the computer program 311 implements the steps of the method for early warning of flight assurance process nodes described above in fig. 1.
In the context of this application, a machine-readable medium may be any 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. A 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.
It should be noted that the machine-readable medium described above in this application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having 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. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device.
Referring to fig. 4, fig. 4 is a schematic diagram of a hardware structure of a server according to an embodiment of the present disclosure, where the server 400 may have a relatively large difference due to different configurations or performances, and may include one or more Central Processing Units (CPUs) 422 (e.g., one or more processors) and a memory 432, and one or more storage media 430 (e.g., one or more mass storage devices) storing an application 440 or data 444. Wherein the memory 432 and storage medium 430 may be transient or persistent storage. The program stored on the storage medium 430 may include one or more modules (not shown), each of which may include a series of instruction operations for the server. Still further, the central processor 422 may be arranged to communicate with the storage medium 430, and execute a series of instruction operations in the storage medium 430 on the server 400.
The server 400 may also include one or more power supplies 426, one or more wired or wireless network interfaces 450, one or more input-output interfaces 458, and/or one or more operating systems 441, such as Windows Server, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, and so forth.
The steps performed by the early warning device of the flight assurance process node in the above embodiment may be based on the server structure shown in fig. 4.
It should be further noted that, according to an embodiment of the present application, the process of the flight assurance process node early warning method described in the flow diagram in fig. 1 above may be implemented as a computer software program. For example, embodiments of the present application include a computer program product comprising a computer program carried on a non-transitory computer readable medium, the computer program containing program code for performing the method illustrated in the flow chart diagram of fig. 2 described above.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.
While several specific implementation details are included in the above discussion, these should not be construed as limitations on the scope of the application. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.
The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the disclosure herein is not limited to the particular combination of features described above, but also encompasses other arrangements formed by any combination of the above features or their equivalents without departing from the spirit of the disclosure. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.
Claims (10)
1. An early warning method for flight guarantee process nodes is characterized by comprising the following steps:
configuring a monitoring rule of each flow node in flight guarantee flow nodes;
acquiring real-time guarantee data of a target flight, wherein the target flight is a flight to be monitored, and the real-time guarantee data comprises flight dynamics of the target flight and a guarantee process node process corresponding to the target flight;
predicting whether a guarantee process node corresponding to the target flight is abnormal according to the monitoring rule of each process node and the real-time guarantee data of the target flight;
and when the guarantee process node corresponding to the target flight is abnormal, sending alarm information according to the abnormity of the guarantee process node corresponding to the target flight.
2. The method of claim 1, further comprising:
performing data cleaning and formatting processing on the real-time guarantee data of the target flight to obtain monitoring data of a first process node currently executed by the target flight;
the predicting whether the guarantee process node corresponding to the target flight is abnormal according to the monitoring rule of each process node and the real-time guarantee data of the target flight comprises the following steps:
and predicting whether the guarantee process node corresponding to the target flight is abnormal according to the monitoring rule of each process node and the monitoring data of the target flight.
3. The method according to claim 2, wherein the guaranteed flow node corresponding to the target flight includes a first flow node currently executed by the target flight and/or a second flow node after the first flow node and having a degree of association with the first flow node reaching a preset value, and the predicting whether the guaranteed flow node corresponding to the target flight is abnormal according to the monitoring rule of each flow node and the monitoring data of the target flight includes:
determining a first monitoring rule corresponding to the first process node in the monitoring rules of each process node, and predicting whether the completion of the first process node is abnormal or not according to the first monitoring rule and the monitoring data of the target flight;
and/or the presence of a gas in the gas,
and determining a second monitoring rule corresponding to the second process node in the monitoring rules of each process node, and predicting whether the second process node is abnormal according to the second monitoring rule and the completion condition of the first process node.
4. The method of claim 3, further comprising:
visually displaying the completion condition of the first flow node in a Gantt chart mode according to the monitoring data of the first flow node and the first monitoring rule;
when the first flow node is abnormal, determining the abnormal level of the first flow node according to the first monitoring rule;
and visually displaying the abnormal condition of the first flow node in a Gantt chart mode based on the abnormal grade of the first flow node and an abnormal visual display rule.
5. The method of any of claims 1 to 4, wherein the obtaining real-time support data for the target flight comprises:
collecting production data reported by flight guarantee process node equipment corresponding to the target flight;
receiving abnormal data reported by production line staff corresponding to the target flight;
and determining the production data and the abnormal data as real-time guarantee data of the target flight.
6. The utility model provides a flight guarantee flow node's early warning device which characterized in that includes:
the configuration unit is used for configuring the monitoring rule of each flow node in the flight guarantee flow nodes;
the system comprises an acquisition unit, a monitoring unit and a processing unit, wherein the acquisition unit is used for acquiring real-time guarantee data of a target flight, the target flight is a flight to be monitored, and the real-time guarantee data comprises flight dynamics of the target flight and a guarantee process node process corresponding to the target flight;
the prediction unit is used for predicting whether the guarantee process node corresponding to the target flight is abnormal according to the monitoring rule of each process node and the real-time guarantee data of the target flight;
and the alarm unit is used for sending alarm information according to the abnormity of the guarantee process node corresponding to the target flight when the guarantee process node corresponding to the target flight is abnormal.
7. The apparatus of claim 6, further comprising:
the data processing unit is used for carrying out data cleaning and formatting processing on the real-time guarantee data of the target flight to obtain monitoring data of a first flow node currently executed by the target flight;
the prediction unit is specifically configured to:
and predicting whether the guarantee process node corresponding to the target flight is abnormal according to the monitoring rule of each process node and the monitoring data of the target flight.
8. The apparatus according to claim 7, wherein the guaranteed flow node corresponding to the target flight includes a first flow node currently executed by the target flight and/or a second flow node after the first flow node and having a degree of association with the first flow node reaching a preset value, and the predicting unit predicts whether the guaranteed flow node corresponding to the target flight is abnormal according to the monitoring rule of each flow node and the monitoring data of the target flight includes:
determining a first monitoring rule corresponding to the first process node in the monitoring rules of each process node, and predicting whether the completion of the first process node is abnormal or not according to the first monitoring rule and the monitoring data of the target flight;
and/or the presence of a gas in the gas,
and determining a second monitoring rule corresponding to the second process node in the monitoring rules of each process node, and predicting whether the second process node is abnormal according to the second monitoring rule and the completion condition of the first process node.
9. The apparatus of claim 8, further comprising:
a presentation unit for:
visually displaying the completion condition of the first flow node in a Gantt chart mode according to the monitoring data of the first flow node and the first monitoring rule;
when the first flow node is abnormal, determining the abnormal level of the first flow node according to the first monitoring rule;
and visually displaying the abnormal condition of the first flow node in a Gantt chart mode based on the abnormal grade of the first flow node and an abnormal visual display rule.
10. A machine-readable medium comprising instructions which, when executed on a machine, cause the machine to perform the steps of the flight assurance process node forewarning method of any of claims 1 to 5.
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