Elevator fault alarm data graph updating method, elevator fault determining method, device, equipment, medium and program product

Abstract

The invention provides an elevator fault alarm data graph updating method, an elevator fault determining method, device and equipment, a medium and a program product, and can be applied to the technical field of Internet of Things and artificial intelligence. The elevator fault alarm data graph updating method comprises the steps that the data type of real-time data included in elevator real-time data flow is determined; under the condition that the elevator fault alarm data graph does not comprise the real-time data, data nodes corresponding to the real-time data are added to the elevator fault alarm data graph; based on the sequence of the multiple pieces of real-time data in the real-time data flow, a plurality of data nodes in the elevator fault alarm data graph are connected through directed edges, and a data sub-graph corresponding to the real-time data flow is obtained; determining labels of the data sub-graphs based on respective data types of a plurality of pieces of real-time data in the real-time data stream; and adding the data sub-graph to the elevator fault alarm data graph to obtain an updated elevator fault alarm data graph.

Description

Technical Field

[0001] This disclosure relates to the fields of Internet of Things and artificial intelligence, specifically to a method for updating elevator fault alarm data graphs, a method for determining elevator faults, and related devices, equipment, media, and program products. Background Technology

[0002] Currently, elevators are widely used in various locations. However, due to the large number of users, complex environments, and frequent use, various malfunctions are inevitable, reducing elevator operating efficiency and threatening passenger safety in the event of entrapment. Therefore, it is necessary to shorten the elevator malfunction assessment period and respond as quickly as possible after a malfunction occurs to ensure both elevator operating efficiency and safety.

[0003] In the process of implementing this disclosure, the inventors discovered that the prior art has at least the following problems: Since elevator malfunctions are a low-probability event, using IoT devices to monitor the elevator's operation in real time and reporting all data to the cloud storage would result in a large amount of data being stored in the cloud, reducing the utilization rate of computing and storage resources. Furthermore, the data needs to be analyzed in real time by the elevator administrator, resulting in low efficiency in determining elevator malfunctions. Summary of the Invention

[0004] In view of the above problems, this disclosure provides a method for updating elevator fault alarm data graphs, a method for determining elevator faults, an apparatus, equipment, medium, and program product.

[0005] According to a first aspect of this disclosure, a method for updating an elevator fault alarm data graph is provided, comprising: determining the data type of real-time data included in an elevator real-time data stream; adding data nodes corresponding to the real-time data to the elevator fault alarm data graph when the elevator fault alarm data graph does not include real-time data; connecting multiple data nodes in the elevator fault alarm data graph using directed edges based on the order of multiple real-time data in the real-time data stream to obtain a data subgraph corresponding to the real-time data stream; determining the label of the data subgraph based on the respective data types of the multiple real-time data in the real-time data stream; and adding the data subgraph to the elevator fault alarm data graph to obtain an updated elevator fault alarm data graph.

[0006] According to embodiments of this disclosure, determining the data type of real-time data included in a real-time data stream includes: for multiple real-time data in the real-time data stream, determining their data type based on the data content of the real-time data.

[0007] According to embodiments of this disclosure, the data types include fault types for characterizing elevator malfunctions and non-fault types for characterizing normal elevator operation.

[0008] According to embodiments of this disclosure, determining the label of a data sub-graph based on the data types of multiple real-time data in a real-time data stream includes: when the data type of the real-time data at a preset position in the real-time data stream is a fault type, determining the label of the data sub-graph based on the fault category; and when the data type of the real-time data at a preset position in the real-time data stream is a non-fault type, sending the data sub-graph and the real-time data stream to the control terminal, whereby the elevator administrator determines the label of the data sub-graph.

[0009] According to embodiments of this disclosure, the elevator fault alarm data graph update method further includes: adding the label of the data subgraph to the fault list when the label of the data subgraph indicates that the elevator has malfunctioned.

[0010] A second aspect of this disclosure provides a method for determining elevator faults, comprising: receiving a fault data stream characterizing an elevator fault; and determining fault information corresponding to the fault data stream based on an elevator fault alarm data graph.

[0011] According to embodiments of this disclosure, determining fault information corresponding to a fault data stream based on an elevator fault alarm data graph includes: determining multiple real-time data included in the fault data stream; performing fuzzy matching in the elevator fault alarm data graph based on the multiple real-time data and the data order between them, and determining a matching result, wherein the matching result is a data subgraph in the elevator fault alarm data graph; determining a fault index corresponding to the fault data stream based on the labels of the data subgraph; determining the fault location based on real-time data preceding the real-time data whose data type is fault type when the labels of the data subgraph are fault categories; determining fault information based on the fault location and fault type; and determining fault information based on the labels of the data subgraph when the labels of the data subgraph are determined by the elevator administrator.

[0012] According to embodiments of this disclosure, an elevator fault alarm data graph includes multiple data subgraphs, each data subgraph including one or more action subgraphs, wherein each action subgraph represents a continuous action of the elevator, and the action subgraph includes multiple data nodes and directed edges between the multiple data nodes; based on multiple real-time data and the data order between the multiple real-time data, fuzzy matching is performed in the elevator fault alarm data graph to determine the matching result, including: when it is determined that the fault data stream is generated based on a data stream combination instruction, determining the real-time data of the fault type among the multiple real-time data as the matching target; matching the matching target with multiple action subgraphs in the elevator fault alarm data graph to determine the target action subgraph that is successfully matched; determining the data subgraph including the target action subgraph as the matching result; and when it is determined that the fault data stream is generated based on a data stream determination instruction, determining the data subgraph corresponding to the data features as the matching result.

[0013] According to embodiments of this disclosure, the elevator fault determination method further includes: receiving a real-time data stream sent by an IoT terminal; determining data characteristics of the real-time data stream based on the real-time data stream; when the data type of the real-time data in the real-time data stream is a fault type, sending a data stream combination instruction to the IoT terminal, so that after receiving the data stream combination instruction, the IoT terminal generates a fault data stream based on the real-time data of the fault type and the real-time data stream, and returns the fault data stream to the control terminal; and when the data characteristics are consistent with the labels of the data subgraphs in the fault list, sending a data stream determination instruction to the IoT terminal, so that after receiving the data stream determination instruction, the IoT terminal determines the real-time data stream corresponding to the data characteristics consistent with the labels of the data subgraphs in the fault list as the fault data stream, and returns the fault data stream to the control terminal.

[0014] A fourth aspect of this disclosure provides an elevator fault determination apparatus, comprising:

[0015] The data stream receiving module is used to receive fault data streams that indicate elevator malfunctions.

[0016] The information determination module is used to determine the fault information corresponding to the fault data stream based on the elevator fault alarm data graph.

[0017] A fifth aspect of this disclosure provides an electronic device comprising: one or more processors; and a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the method described above.

[0018] A sixth aspect of this disclosure also provides a computer-readable storage medium having a computer program or instructions stored thereon, which, when executed by a processor, implement the steps of the above-described method.

[0019] The seventh aspect of this disclosure also provides a computer program product, including a computer program or instructions that, when executed by a processor, implement the steps of the above-described method.

[0020] According to embodiments of this disclosure, by matching the real-time collected fault data stream when an elevator malfunctions with the elevator fault alarm data graph, fault information can be quickly determined based on the matching results. This allows for rapid fault location and repair, improving elevator safety and operational efficiency. Since the possible causes of elevator malfunctions are limited, updating the elevator fault alarm data graph by adding nodes and connecting them with directed edges avoids the problem of excessively long matching times caused by an overly large directed graph, improving matching efficiency and storage resource utilization. Furthermore, since only the fault data stream is processed, the server does not need to process large amounts of unnecessary data streams from normal elevator operation, reducing server computational pressure and improving computational resource utilization. Attached Figure Description

[0021] The foregoing contents, as well as other objects, features, and advantages of this disclosure, will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0022] Figure 1 The illustration schematically depicts an application scenario of an elevator fault alarm data graph update method, an elevator fault determination method, an apparatus, a device, a medium, and a program product according to embodiments of the present disclosure.

[0023] Figure 2 A flowchart illustrating an elevator fault alarm data graph update method according to an embodiment of the present disclosure is shown schematically.

[0024] Figure 3 The illustration shows a schematic diagram of an elevator fault alarm data graph update method according to an embodiment of the present disclosure.

[0025] Figure 4 A flowchart illustrating an elevator fault determination method according to an embodiment of the present disclosure is shown schematically.

[0026] Figure 5 This schematic diagram illustrates a structural block diagram of an elevator fault alarm data graph updating device according to an embodiment of the present disclosure;

[0027] Figure 6 A schematic block diagram of an elevator fault determination device according to an embodiment of the present disclosure is shown; and

[0028] Figure 7 A block diagram schematically illustrates an electronic device suitable for implementing an elevator fault alarm data map update method and an elevator fault determination method according to embodiments of the present disclosure. Detailed Implementation

[0029] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0030] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0031] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0032] When using expressions such as "at least one of A, B, and C", they should generally be interpreted in accordance with the meaning that is commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B, and C, etc.).

[0033] In the technical solution disclosed herein, the user information (including but not limited to user personal information, user image information, user device information, such as location information) and data (including but not limited to data used for analysis, stored data, and displayed data) involved are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of related data all comply with relevant laws, regulations, and standards, necessary confidentiality measures have been taken, and they do not violate public order and good morals. Corresponding operation entry points are provided for users to choose to authorize or refuse.

[0034] In scenarios involving automated decision-making using personal information, the methods, devices, and systems provided in this disclosure all offer users corresponding entry points for choosing to agree to or reject the automated decision-making results. If the user chooses to reject, the process proceeds to the expert decision-making stage. Here, "automated decision-making" refers to the activity of automatically analyzing and evaluating an individual's behavioral habits, interests, or economic, health, and credit status through computer programs, and then making a decision. Here, "expert decision-making" refers to the activity of making decisions by personnel who specialize in a particular field, possess specialized experience, knowledge, and skills, and have reached a certain level of professional expertise.

[0035] This disclosure provides an elevator fault determination method, comprising: receiving a fault data stream representing an elevator fault sent by an Internet of Things (IoT) terminal; determining a fault index corresponding to the fault data stream based on the fault data stream and an elevator fault alarm data graph; and determining fault information based on the fault index; wherein the elevator fault alarm data graph is determined by the following steps: determining the data type of real-time data included in the real-time data stream sent by the IoT terminal, wherein the real-time data stream includes multiple real-time data; adding data nodes corresponding to the real-time data to the elevator fault alarm data graph when the elevator fault alarm data graph does not include real-time data; connecting multiple data nodes in the elevator fault alarm data graph using directed edges based on the order of multiple real-time data in the real-time data stream to obtain a data subgraph corresponding to the real-time data stream; and determining the label of the data subgraph based on the data type of each of the multiple real-time data in the real-time data stream.

[0036] Figure 1 The illustration schematically depicts an application scenario of an elevator fault alarm data graph update method, an elevator fault determination method, an apparatus, a device, a medium, and a program product according to embodiments of the present disclosure.

[0037] like Figure 1 As shown, application scenario 100 according to this embodiment may include terminal devices 101 and 102, elevator 103, network 104, server 105, and database 106. Network 104 serves as a medium for providing communication links between terminal devices 101 and 102, elevator 103, server 105, and database 106. Network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0038] Users can use terminal devices 101 and 102 to interact with the elevator 103, server 105, and database 106 via network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101 and 102 for querying elevator fault determination results.

[0039] Terminal devices 101 and 102 can be various electronic devices with displays and support web browsing, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0040] The elevator 103 can be connected to an Internet of Things (IoT) device, which can monitor the data stream generated during the operation of the elevator 103 in real time.

[0041] Server 105 can be a server that provides various services, such as a back-end management server that supports the elevator fault determination method performed by users using terminal devices 101 and 102 (this is just an example). The back-end management server can analyze and process the received fault data stream and other data, and feed the processing results back to the terminal devices.

[0042] Database 106 can be a database used to store a list of faults, and it can be a relational database or a non-relational database.

[0043] It should be noted that the elevator fault alarm data graph update method and elevator fault determination method provided in this embodiment can generally be executed by server 105. Correspondingly, the elevator fault alarm data graph update device and elevator fault determination device provided in this embodiment can generally be located in server 105. The elevator fault alarm data graph update method and elevator fault determination method provided in this embodiment can also be executed by a server or server cluster that is different from server 105 and capable of communicating with terminal devices 101, 102, elevator 103, and / or server 105 and / or database 106. Correspondingly, the elevator fault alarm data graph update device and elevator fault determination device provided in this embodiment can also be located in a server or server cluster that is different from server 105 and capable of communicating with terminal devices 101, 102, elevator 103, and / or server 105 and / or database 106.

[0044] It should be understood that Figure 1 The number of terminal devices, elevators, networks, servers, and databases shown is merely illustrative. Depending on implementation needs, any number of terminal devices, elevators, networks, servers, and databases can be included.

[0045] The following will be based on Figure 1 The described scene, through Figures 2-3 The elevator fault alarm data graph update method of the disclosed embodiments is described in detail.

[0046] Figure 2 A flowchart illustrating an elevator fault alarm data graph update method according to an embodiment of the present disclosure is shown.

[0047] like Figure 2As shown, the elevator fault alarm data graph update method of this embodiment includes operations S210 to S250.

[0048] In operation S210, the data type of the real-time data included in the elevator real-time data stream is determined.

[0049] When operating S220, if the elevator fault alarm data graph does not include real-time data, add the data node corresponding to the real-time data to the elevator fault alarm data graph.

[0050] In operation S230, based on the order of multiple real-time data in the real-time data stream, directed edges are used to connect multiple data nodes in the elevator fault alarm data graph to obtain a data subgraph corresponding to the real-time data stream.

[0051] In operation S240, the labels of the data subgraphs are determined based on the data types of multiple real-time data in the real-time data stream.

[0052] In operation S250, the data subgraph is added to the elevator fault alarm data graph to obtain the updated elevator fault alarm data graph.

[0053] According to embodiments of this disclosure, the data types of real-time data included in the real-time data stream sent by the IoT terminal are determined, wherein the real-time data stream includes multiple real-time data; when the elevator fault alarm data graph does not include real-time data, data nodes corresponding to the real-time data are added to the elevator fault alarm data graph; based on the order of the multiple real-time data in the real-time data stream, the multiple data nodes in the elevator fault alarm data graph are connected using directed edges to obtain a data subgraph corresponding to the real-time data stream; based on the data types of the multiple real-time data in the real-time data stream, the labels of the data subgraphs are determined.

[0054] According to embodiments of this disclosure, an IoT terminal can monitor the elevator's operation in real time and acquire the real-time data stream generated during elevator operation. The server determines the multiple real-time data included in the real-time data stream and judges whether the elevator fault alarm data graph includes the multiple real-time data in the real-time data stream. If the elevator fault alarm data graph does not include real-time data, a data node corresponding to the real-time data is created and added to the elevator fault alarm data graph.

[0055] According to embodiments of this disclosure, a label for a data subgraph is determined based on the data types of multiple real-time data in a real-time data stream. Specifically, when the data types of the multiple real-time data in the real-time data stream all represent normal elevator operation, the label of the data subgraph represents normal elevator operation. When the multiple real-time data in the real-time data stream include real-time data whose data type represents an elevator malfunction, the label of the data subgraph can be determined based on the fault type corresponding to the real-time data representing the elevator malfunction. For example, when the real-time data stream includes a power outage fault code, the label of the data subgraph corresponding to that real-time data stream can be determined as a power outage fault.

[0056] According to embodiments of this disclosure, since the possible causes of elevator malfunctions are limited, updating the elevator malfunction alarm data graph by adding nodes and connecting them with directed edges avoids the problem of excessively long matching times caused by an overly large directed graph, thus improving matching efficiency and storage resource utilization. Furthermore, since only fault data streams are processed, the server does not need to process large amounts of unnecessary data streams from normal elevator operation, reducing server computational pressure and improving computational resource utilization.

[0057] According to embodiments of this disclosure, determining the data type of real-time data included in a real-time data stream includes: for multiple real-time data in the real-time data stream, determining their data type based on the data content of the real-time data.

[0058] According to embodiments of this disclosure, multiple real-time data points included in the real-time data stream are determined based on the real-time data stream, and the data content of each of the multiple real-time data points is determined. Based on the data content of each of the multiple real-time data points and the correspondence between the multiple data content points and data types, the data type of each of the multiple real-time data points is determined. The correspondence between the multiple data content points and data types can be pre-configured; for example, the data type of real-time data points where the data content is the start of transportation indicates normal elevator operation, the data type of real-time data points where the data content is at floor position 3 indicates normal elevator operation, and the data type of real-time data points where the data content is a power outage fault code indicates an elevator malfunction.

[0059] According to embodiments of this disclosure, the data type of real-time data is determined based on the data content of multiple real-time data in a real-time data stream. By classifying the data content, the label of the data sub-graph can be quickly determined by the data type, thereby improving the construction efficiency of elevator fault alarm data graphs.

[0060] According to embodiments of this disclosure, the data types include fault types for characterizing elevator malfunctions and non-fault types for characterizing normal elevator operation.

[0061] According to embodiments of this disclosure, based on the order of multiple real-time data in a real-time data stream, multiple data nodes in an elevator fault alarm data graph are connected using directed edges to obtain a data subgraph corresponding to the real-time data stream. This includes: determining the data order of multiple real-time data based on the real-time data stream; connecting multiple data nodes in the elevator fault alarm data graph using directed edges based on the data order, wherein a directed edge points from one data node to the next adjacent data node; and determining the data subgraph corresponding to the real-time data stream based on the data nodes corresponding to each of the multiple real-time data in the real-time data stream and the directed edges between the multiple data nodes.

[0062] According to embodiments of this disclosure, the real-time data stream is decoded to determine the data order of multiple real-time data. Following the data order of the multiple real-time data in the real-time data stream, multiple data nodes in the elevator fault alarm data graph are connected using multiple directed edges. The directed edges point from the first detected real-time data in the real-time data stream to the next detected real-time data. After the connections are completed, a simple graph without isolated points is obtained, i.e., a data subgraph corresponding to the real-time data stream.

[0063] According to embodiments of this disclosure, data nodes are connected in the order of data using directed edges to obtain a data subgraph. This ensures that the order of data nodes in the data subgraph is the same as that of real-time data in the real-time data stream, thereby ensuring successful matching between the fault data stream and the elevator fault alarm data graph. This avoids constructing multiple data subgraphs and improves the efficiency of elevator fault determination.

[0064] Figure 3 The illustration shows a schematic diagram of an elevator fault alarm data graph update method according to an embodiment of the present disclosure.

[0065] like Figure 3 As shown, the updated elevator fault alarm data diagram includes the original elevator fault alarm data diagram 301 and the newly added data sub-diagram 302. The original elevator fault alarm data diagram 301 includes four data sub-diagrams, including X0-X... 01 -X 021 -X 03 -X 04 -X 05 X0-X 01 -X 022 -X 03 -X 04 -X 05 X1-X 11 -X 12 -X 13 -X 141 and X1-X 11 -X 12 -X13 -X 142 -X 15 Each data subgraph is formed by connecting multiple data nodes with directed edges. Each data node represents a real-time data point in the real-time data stream. For example, X0 can represent the start of a shipment, X... 05 This can represent power outage fault codes. Following the data order of the real-time data stream, directed edges are used to connect the data nodes X2 and X... corresponding to the real-time data included in the real-time data stream. 21 and X 22 Connect to obtain the data subgraph X2-X 21 -X 22 The newly added data sub-graph 302 is then added to the elevator fault alarm data graph, completing the update of the elevator fault alarm data graph.

[0066] According to embodiments of this disclosure, the data types include fault types for characterizing elevator malfunctions and non-fault types for characterizing normal elevator operation.

[0067] According to embodiments of this disclosure, the data types include fault types characterizing elevator malfunctions and non-fault types characterizing normal elevator operation. The different data types of real-time data lead to different methods for determining the labels of the corresponding data subgraphs.

[0068] According to embodiments of this disclosure, determining the label of a data sub-graph based on the data types of multiple real-time data in a real-time data stream includes: when the data type of the real-time data at a preset position in the real-time data stream is a fault type, determining the label of the data sub-graph based on the fault category; and when the data type of the real-time data at a preset position in the real-time data stream is a non-fault type, sending the data sub-graph and the real-time data stream to the control terminal, whereby the elevator administrator determines the label of the data sub-graph.

[0069] According to an embodiment of this disclosure, if the data type of the real-time data at a preset position in the real-time data stream is a fault type, and the elevator has experienced a fault of that type, then the label of the data sub-graph can be determined based on the fault category. The fault category includes various faults that the elevator may experience, such as power outage faults, door opening faults, and abnormal positions. The preset position can be the last position in the real-time data stream.

[0070] According to embodiments of this disclosure, when the data type of real-time data at a preset location in the real-time data stream is a non-fault type, the fault that the elevator has not malfunctioned or that has occurred cannot be reflected in the real-time data. For example, if the elevator repeatedly opens and closes its doors, preventing passengers from riding the elevator normally, the opening and closing of the doors are non-fault type real-time data. The label of the data subgraph cannot be determined by the data type of the real-time data. The elevator administrator needs to determine the label of the data subgraph based on the real-time data stream and the actual operation of the elevator.

[0071] According to embodiments of this disclosure, for different data types of real-time data at preset locations in the real-time data stream, different methods are used to determine the labels of the data subgraphs. This allows elevator administrators to determine the labels of the data subgraphs by judging the actual operation of the elevator when the real-time data does not indicate an elevator malfunction. This avoids situations where the real-time data does not indicate an elevator malfunction, leading to incorrect data subgraph labels.

[0072] According to embodiments of this disclosure, the elevator alarm data graph update method further includes: adding the label of the data subgraph to the fault list when the label of the data subgraph indicates that the elevator has malfunctioned.

[0073] According to embodiments of this disclosure, when the label of the data subgraph indicates that the elevator has malfunctioned, the label of the data subgraph is added to the fault list. This enables IoT devices to successfully match the data subgraph label in the fault list when they detect the same fault data stream again, thereby determining that the elevator has malfunctioned. The fault list is a data structure that can be updated and queried in real time. For example, the fault list can be stored in a database, and the label of the data subgraph can be added to the fault list at any time using the Insert clause.

[0074] According to embodiments of this disclosure, when the label of the data subgraph indicates that the elevator has malfunctioned, adding the label of the data subgraph to the fault list can avoid adding the labels of all real-time data streams to the fault list, thereby reducing the number of data streams processed by the server and alleviating the computational pressure on the server.

[0075] Figure 4 A flowchart illustrating an elevator fault determination method according to an embodiment of the present disclosure is shown schematically.

[0076] like Figure 4 As shown, the elevator fault determination method in this embodiment includes operations S410 to S420.

[0077] In operation S410, a fault data stream indicating a fault in the elevator is received.

[0078] In operation S420, based on the elevator fault alarm data graph, the fault information corresponding to the fault data stream is determined.

[0079] According to an embodiment of this disclosure, the server receives a fault data stream indicating that the elevator has malfunctioned, sent by an IoT terminal. The IoT terminal can monitor the elevator's operation in real time and acquire the data stream generated during the elevator's operation. When the elevator's data stream indicates that the elevator has malfunctioned, the corresponding fault data stream is sent to the server.

[0080] According to embodiments of this disclosure, the fault data stream includes multiple data generated during elevator operation arranged in chronological order, where one or more data represent an elevator malfunction. Based on the fault data stream and an elevator fault alarm data graph, a fault index corresponding to the fault data stream is determined. The elevator fault alarm data graph is a directed graph, where each node corresponds to the data content of a data generated during elevator operation, such as "transport start," "floor position 3," or "power outage fault code." Directed edges in the elevator fault alarm data graph represent the sequential order of data in the data stream. For example, a directed edge (u, v) represents a data stream in the elevator fault alarm data graph where the data corresponding to node u was received first, followed by the data corresponding to node v. Therefore, the elevator fault alarm data graph is used to match the fault data stream, and the fault index corresponding to the fault data stream is determined based on the matching result. Based on the fault index, fault information such as the location of the fault and the type causing it can be determined, enabling rapid fault location and repair.

[0081] According to embodiments of this disclosure, by matching the fault data stream collected in real time when an elevator malfunctions with the elevator fault alarm data graph, fault information can be quickly determined based on the matching results, so as to quickly locate and repair the fault based on the fault information, thereby improving the safety and operating efficiency of the elevator.

[0082] According to embodiments of this disclosure, determining a fault index corresponding to the fault data stream based on a fault data stream and an elevator fault alarm data graph includes: determining multiple real-time data included in the fault data stream; performing fuzzy matching in the elevator fault alarm data graph based on the multiple real-time data and the data order between the multiple real-time data to determine a matching result, wherein the matching result is a data subgraph in the elevator fault alarm data graph; determining a fault index corresponding to the fault data stream based on the labels of the data subgraph; determining the fault location based on real-time data preceding real-time data of the fault type when the label of the data subgraph is a fault category; determining fault information based on the fault location and fault type; and determining fault information based on the labels of the data subgraph when the labels of the data subgraph are determined by the elevator administrator.

[0083] According to embodiments of this disclosure, multiple real-time data included in the fault data stream are determined. Based on the multiple real-time data and the data order among the multiple real-time data, fuzzy matching is performed in the elevator fault alarm data graph to determine the matching result, wherein the matching result is a data subgraph in the elevator fault alarm data graph.

[0084] According to embodiments of this disclosure, since elevators can experience various malfunctions, the malfunction index corresponding to the malfunction data stream is determined by the malfunction type. The malfunction type is only related to real-time data with a malfunction data type and is unrelated to other real-time data. That is, in the malfunction data stream, the real-time data stream during the normal operation period of the elevator is unrelated to the malfunction type of the elevator. Therefore, the malfunction index corresponding to the malfunction data stream can be determined by fuzzy matching. Fuzzy matching is a data matching technique. As long as the real-time data with a malfunction data type in the malfunction data stream matches the malfunction type corresponding to the data node at a preset position in the data subgraph, the matching result can be determined.

[0085] According to embodiments of this disclosure, a fault index corresponding to a faulty data stream is determined based on the labels of a data subgraph. The fault type can be determined according to the fault type corresponding to the label of the data subgraph, and the location where the fault occurs can be determined according to the real-time data of the non-fault type that precedes the real-time data of the fault type in the faulty data stream, thereby determining the fault index corresponding to the faulty data stream.

[0086] According to embodiments of this disclosure, when the label of the data subgraph is a fault category, the fault location is determined based on real-time data of non-fault types preceding real-time data of the fault type. For example, if the real-time data of the non-fault type preceding the power outage fault code is floor 5, the fault type can be determined to be a power outage fault, and the fault occurred on the 5th floor. Based on the fault location and fault type, fault information is determined.

[0087] According to embodiments of this disclosure, when the labels of the data sub-map are determined by the elevator administrator, the labels of the data sub-map include the fault type and fault location, so fault information can be determined based on the labels of the data sub-map.

[0088] According to embodiments of this disclosure, when the labels of the data subgraphs are determined by the elevator administrator, the fault type can be determined based on the labels of the data subgraphs, and the fault location can be determined based on the real-time data of the most recently represented location. For example, if the action subgraph after the data node at floor position 6 in the data subgraph represents the elevator repeatedly opening and closing the door, the fault type can be determined to be a door opening and closing fault, and the fault location is floor 6. Based on the fault location and fault type, the fault information is determined.

[0089] According to embodiments of this disclosure, based on fault data streams and elevator fault alarm data maps, fuzzy matching is used to determine the fault index corresponding to the fault data stream. This allows for rapid determination of the elevator fault index corresponding to the fault data stream based on historical data from the elevator fault alarm data map, thereby enabling rapid fault repair and improving the efficiency of elevator fault identification. Different methods are used to determine fault information for fault category labels and labels determined by the elevator administrator, completing the location of the elevator fault and determining its type. Based on the fault type, the appropriate repair methods are determined, and fault repair is performed based on the fault location, ensuring a rapid response to elevator faults and improving elevator safety and operational efficiency.

[0090] According to embodiments of this disclosure, an elevator fault alarm data graph includes multiple data subgraphs, each data subgraph including one or more action subgraphs, wherein each action subgraph represents a continuous action of the elevator, and the action subgraph includes multiple data nodes and directed edges between the multiple data nodes; based on multiple real-time data and the data order between the multiple real-time data, fuzzy matching is performed in the elevator fault alarm data graph to determine the matching result, including: when it is determined that the fault data stream is generated based on a data stream combination instruction, determining the real-time data of the fault type among the multiple real-time data as the matching target; matching the matching target with multiple action subgraphs in the elevator fault alarm data graph to determine the target action subgraph that is successfully matched; determining the data subgraph including the target action subgraph as the matching result; and when it is determined that the fault data stream is generated based on a data stream determination instruction, determining the data subgraph corresponding to the data features as the matching result.

[0091] According to embodiments of this disclosure, the elevator fault alarm data graph includes multiple data subgraphs, each data subgraph including one or more action subgraphs, wherein each action subgraph is used to represent a continuous action of the elevator, and the action subgraph includes multiple data nodes and directed edges between the multiple data nodes.

[0092] For example, the three data nodes in the data subgraph represent floor positions 2, 3, and 4, respectively. The directed edges between these three data nodes can be used as an action subgraph to represent the action of the elevator moving from the second floor to the fourth floor. Figure 3 X in 01 -X 021 -X 03 -X 04 and X 01 -X 022 -X 03 -X 04 These can be two different action subgraphs.

[0093] According to embodiments of this disclosure, when it is determined that the fault data stream is generated based on data stream combination instructions, real-time data of the fault type among multiple real-time data are identified as matching targets, such as elevator door opening fault. The matching targets are then matched with multiple action subgraphs in the elevator fault alarm data graph to determine the successfully matched target action subgraph. Wherein, when the matching target is elevator door opening fault, the label of the successfully matched target action subgraph indicates that the elevator has experienced a door opening fault.

[0094] According to the embodiments of this disclosure, when the fault data stream is determined to be generated based on the data stream determination instruction, it is impossible to match it using real-time data of the fault type. However, the label of the data subgraph is determined based on the data characteristics of the fault data stream. Therefore, there is a data subgraph in the elevator fault alarm data graph that corresponds to the data characteristics, and the data subgraph that corresponds to the data characteristics can be determined as the matching result.

[0095] According to embodiments of this disclosure, fuzzy matching can cover more elevator faults corresponding to fault data streams without adding too many data subgraphs to the elevator fault alarm data graph, reducing storage resource consumption and improving resource utilization. Furthermore, by avoiding data redundancy in the elevator fault alarm data graph, matching efficiency can be improved, accelerating the determination of elevator faults and thus speeding up the repair of elevator faults and improving safety.

[0096] According to embodiments of this disclosure, the elevator fault determination method further includes: receiving a real-time data stream sent by an IoT terminal; determining data characteristics of the real-time data stream based on the real-time data stream; when the data type of the real-time data in the real-time data stream is a fault type, sending a data stream combination instruction to the IoT terminal, so that after receiving the data stream combination instruction, the IoT terminal generates a fault data stream based on the real-time data of the fault type and the real-time data stream, and returns the fault data stream to the control terminal; and when the data characteristics are consistent with the labels of the data subgraphs in the fault list, sending a data stream determination instruction to the IoT terminal, so that after receiving the data stream determination instruction, the IoT terminal determines the real-time data stream corresponding to the data characteristics consistent with the labels of the data subgraphs in the fault list as the fault data stream, and returns the fault data stream to the control terminal.

[0097] According to embodiments of this disclosure, a server can accept real-time data streams sent by IoT terminals and determine the data characteristics of the real-time data streams. The data characteristics of the real-time data streams can be determined by the data types of the real-time data included in the real-time data streams and can be used to characterize the characteristics of multiple real-time data, wherein the multiple real-time data can be multiple real-time data in the real-time data streams.

[0098] According to embodiments of this disclosure, when the data type of the real-time data in the real-time data stream is fault type, a data stream combination instruction is sent to the IoT terminal. Upon receiving the data stream combination instruction, the IoT terminal generates a fault data stream based on the real-time data of the fault type and the real-time data stream, and returns the fault data stream to the control terminal. The fault data stream can be obtained by combining multiple real-time data of the fault type from the real-time data stream that occurred a predetermined time prior to the fault type. For example, the real-time data of the fault type within the first five minutes of the real-time data stream can be combined in data order. The predetermined time can be set according to actual needs. For example, if the preset position is the last position, the predetermined time can be three minutes or five minutes before the fault type's real-time data. If the preset position is not the last position, it can be three minutes before the fault type's real-time data to two minutes after the last position.

[0099] According to embodiments of this disclosure, since the labels of the data subgraphs in the fault list indicate that the real-time data stream corresponding to the data subgraph represents a fault in the elevator, when the data characteristics of the real-time data stream are consistent with the labels of the data subgraphs in the fault list, it can be determined that the real-time data stream represents a fault in the elevator. Therefore, a data stream determination instruction can be sent to the IoT terminal so that after receiving the data stream determination instruction, the IoT terminal determines the real-time data stream corresponding to the data characteristics consistent with the labels of the data subgraphs in the fault list as the fault data stream and returns the fault data stream to the control terminal.

[0100] According to embodiments of this disclosure, different instructions are sent to the real-time data stream corresponding to the data subgraph included in the elevator fault alarm data graph and the real-time data stream corresponding to the data subgraph not included in the elevator fault alarm data graph, so that the IoT terminal can determine the fault data stream and push the fault data stream to the server for subsequent processing. This can ensure that all faults occurring in the elevator are analyzed and processed, avoiding omissions.

[0101] For example, the current elevator fault alarm data graph is as follows: Figure 3 The fault data stream includes data Y0-Y1-Y2-Y3-Y4-Y5-Y6, where Y0 is floor position 7, Y1 is floor position 6, Y2 is floor position 5, Y3 is floor position 4, Y4 is floor position 3, Y5 is the door opening code, and Y6 is the power outage fault code. Y0-Y1-Y2-Y3-Y4 correspond to an action subgraph representing the elevator moving from floor 7 to floor 3; Y5 corresponds to an action subgraph representing the elevator door opening; and Y6 corresponds to an action subgraph representing a power outage. Since the real-time fault type data is Y5 and Y6, the matching targets are Y5 and Y6. Using the matching targets... Figure 3Matching is performed to obtain the target action subgraph X. 142 and X 15 Then the matching result can be determined as the data subgraph X1-X 11 -X 12 -X 13 -X 142 -X 15 Based on the labels of this data subgraph, the cause of the fault can be determined to be a power outage during the door opening process. Based on other real-time data before the real-time data of the fault type, the fault location is determined to be the 3rd floor. Thus, the fault information is determined to be that the elevator experienced a power outage during the door opening process on the 3rd floor.

[0102] Based on the above-mentioned elevator fault alarm data graph update method, this disclosure also provides an elevator fault alarm data graph update device, which will be described below in conjunction with... Figure 5 The device is described in detail.

[0103] Figure 5 A schematic block diagram of an elevator fault alarm data graph update device according to an embodiment of the present disclosure is shown.

[0104] like Figure 5 As shown, the elevator fault alarm data graph update device 500 of this embodiment includes a type determination module 510, a node addition module 520, a node connection module 530, a tag determination module 540, and a data graph update module 550.

[0105] The type determination module 510 is used to determine the data type of the real-time data included in the elevator real-time data stream. In one embodiment, the type determination module 510 can be used to perform the operation S210 described above, which will not be repeated here.

[0106] The node adding module 520 is used to add data nodes corresponding to the real-time data to the elevator fault alarm data graph when the real-time data is not included in the elevator fault alarm data graph. In one embodiment, the node adding module 520 can be used to perform the operation S220 described above, which will not be repeated here.

[0107] The node connection module 530 is used to connect multiple data nodes in the elevator fault alarm data graph using directed edges based on the order of multiple real-time data in the real-time data stream, to obtain a data subgraph corresponding to the real-time data stream. In one embodiment, the node connection module 530 can be used to perform the operation S230 described above, which will not be repeated here.

[0108] The label determination module 540 is used to determine the label of the data subgraph based on the data types of the various real-time data in the real-time data stream. In one embodiment, the label determination module 540 can be used to perform the operation S240 described above, which will not be repeated here.

[0109] The data graph update module 550 is used to add the data subgraph to the elevator fault alarm data graph to obtain an updated elevator fault alarm data graph. In one embodiment, the data graph update module 550 can be used to perform the operation S250 described above, which will not be repeated here.

[0110] According to embodiments of this disclosure, the type determination module 510 includes a type determination unit.

[0111] The type determination unit is used to determine the data type of multiple real-time data in a real-time data stream based on the data content of the real-time data.

[0112] According to embodiments of this disclosure, the data types include fault types for characterizing elevator malfunctions and non-fault types for characterizing normal elevator operation.

[0113] According to embodiments of this disclosure, the label determination module includes a first label determination unit and a second label determination unit.

[0114] The first label determination unit is used to determine the label of the data subgraph based on the fault type when the data type of the real-time data at a preset position in the real-time data stream is a fault type.

[0115] The second tag determination unit is used to send the data sub-graph and real-time data stream to the control terminal when the data type of the real-time data at the preset position of the real-time data stream is a non-fault type, so that the elevator administrator can determine the tag of the data sub-graph.

[0116] According to embodiments of this disclosure, the elevator fault alarm data graph update device 500 further includes a tag adding module.

[0117] The labeling module is used to add labels from a data subgraph to the fault list when the labels in the data subgraph represent elevator malfunctions.

[0118] Based on the above-described elevator fault determination method, this disclosure also provides an elevator fault determination device. The following will be combined with... Figure 6 The device is described in detail.

[0119] Figure 6 A schematic block diagram of an elevator fault determination device according to an embodiment of the present disclosure is shown.

[0120] like Figure 6As shown, the elevator fault determination device 600 of this embodiment includes a data stream receiving module 610 and an information determination module 620.

[0121] The data stream receiving module 610 is used to receive fault data streams indicating that the elevator has malfunctioned, sent by the IoT terminal. In one embodiment, the data stream receiving module 610 can be used to perform the operation S410 described above, which will not be repeated here.

[0122] The information determination module 620 is used to determine the fault information corresponding to the fault data stream based on the elevator fault alarm data graph. In one embodiment, the information determination module 620 can be used to perform the operation S420 described above, which will not be repeated here.

[0123] According to embodiments of this disclosure, the information determination module 430 includes a fault data determination unit, a matching determination unit, an index determination unit, a location determination unit, a first information determination unit, and a second information determination unit.

[0124] The fault data determination unit is used to determine multiple real-time data included in the fault data stream.

[0125] The matching determination unit is used to perform fuzzy matching in the elevator fault alarm data graph based on multiple real-time data and the data order between the multiple real-time data, and determine the matching result, wherein the matching result is a data subgraph in the elevator fault alarm data graph.

[0126] The index determination unit is used to determine the fault index corresponding to the faulty data stream based on the labels of the data subgraph.

[0127] The location determination unit is used to determine the fault location based on real-time data prior to real-time data of the fault type, when the label of the data subgraph is fault category.

[0128] The first information determination unit is used to determine fault information based on the fault location and fault type.

[0129] The second information determination unit is used to determine fault information based on the labels of the data sub-map when the labels of the data sub-map are determined by the elevator administrator.

[0130] According to embodiments of this disclosure, the elevator fault alarm data graph includes multiple data subgraphs, each data subgraph including one or more action subgraphs, wherein each action subgraph is used to represent a continuous action of the elevator, and the action subgraph includes multiple data nodes and directed edges between the multiple data nodes; the matching determination unit includes a target determination subunit, a subgraph determination subunit, a result determination subunit, and a matching determination subunit.

[0131] The target determination subunit is used to determine the real-time data of the fault type from multiple real-time data sources as the matching target when the fault data stream is generated based on the data stream combination instruction.

[0132] The subgraph determination sub-unit is used to match the target action with multiple action subgraphs in the elevator fault alarm data graph to determine the target action subgraph that is successfully matched.

[0133] The result determination subunit is used to determine the data subgraph, including the target action subgraph, as the matching result.

[0134] The matching determination subunit is used to determine the data subgraph corresponding to the data characteristics as the matching result when the fault data stream is determined based on the data stream determination instruction.

[0135] According to embodiments of this disclosure, the elevator fault determination device 600 further includes a real-time data stream receiving module, a feature determination module, a data combination module, and a data determination module.

[0136] The real-time data stream receiving module is used to receive real-time data streams sent by IoT terminals.

[0137] The feature determination module is used to determine the data features of the real-time data stream based on the real-time data stream.

[0138] The data combination module is used to send a data stream combination instruction to the IoT terminal when the data type of the real-time data in the real-time data stream is fault type. After receiving the data stream combination instruction, the IoT terminal generates a fault data stream based on the real-time data of the fault type and the real-time data stream, and returns the fault data stream to the control terminal.

[0139] The data determination module is used to send a data flow determination instruction to the IoT terminal when the data characteristics match the labels of the data subgraphs in the fault list. After receiving the data flow determination instruction, the IoT terminal determines the real-time data flow corresponding to the data characteristics that match the labels of the data subgraphs in the fault list as the fault data flow and returns the fault data flow to the control terminal.

[0140] According to embodiments of this disclosure, any and multiple modules among the type determination module 510, node addition module 520, node connection module 530, tag determination module 540, data graph update module 550, data stream receiving module 610, and information determination module 620 can be combined into one module, or any one of these modules can be split into multiple modules. Alternatively, at least some of the functions of one or more of these modules can be combined with at least some of the functions of other modules and implemented in one module. According to embodiments of this disclosure, at least one of the type determination module 510, node addition module 520, node connection module 530, tag determination module 540, data graph update module 550, data stream receiving module 610, and information determination module 620 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), programmable logic array (PLA), system-on-a-chip, system-on-a-substrate, system-on-package, application-specific integrated circuit (ASIC), or any other reasonable method of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three methods. Alternatively, at least one of the type determination module 510, node addition module 520, node connection module 530, tag determination module 540, data graph update module 550, data stream receiving module 610, and information determination module 620 can be at least partially implemented as a computer program module, which, when run, can perform corresponding functions.

[0141] Figure 7 A block diagram schematically illustrates an electronic device suitable for implementing an elevator fault alarm data map update method and an elevator fault determination method according to embodiments of the present disclosure.

[0142] like Figure 7 As shown, an electronic device 700 according to an embodiment of the present disclosure includes a processor 701, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage portion 708 into a random access memory (RAM) 703. The processor 701 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 701 may also include onboard memory for caching purposes. The processor 701 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0143] RAM 703 stores various programs and data required for the operation of electronic device 700. Processor 701, ROM 702, and RAM 703 are interconnected via bus 704. Processor 701 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 702 and / or RAM 703. It should be noted that the programs may also be stored in one or more memories other than ROM 702 and RAM 703. Processor 701 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in said one or more memories.

[0144] According to embodiments of this disclosure, the electronic device 700 may further include an input / output (I / O) interface 705, which is also connected to a bus 704. The electronic device 700 may also include one or more of the following components connected to the I / O interface 705: an input section 706 including a keyboard, mouse, etc.; an output section 707 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN card, modem, etc. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as needed. A removable medium 711, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 710 as needed so that computer programs read from it can be installed into the storage section 708 as needed.

[0145] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0146] According to embodiments of this disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this disclosure, the computer-readable storage medium may include ROM 702 and / or RAM 703 and / or one or more memories other than ROM 702 and RAM 703 described above.

[0147] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code is used to cause the computer system to implement the methods provided in the embodiments of this disclosure.

[0148] When the computer program is executed by the processor 701, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0149] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 709, and / or installed from a removable medium 711. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0150] In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 709, and / or installed from the removable medium 711. When the computer program is executed by the processor 701, it performs the functions defined in the system of this disclosure embodiment. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0151] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0152] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0153] Those skilled in the art will understand that the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. In particular, the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0154] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. The scope of this disclosure is defined by the appended claims and their equivalents. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. A method for updating elevator fault alarm data graphs, characterized in that, The method includes: Determine the data type of the real-time data included in the elevator real-time data stream; If the elevator fault alarm data graph does not include the real-time data, the data node corresponding to the real-time data will be added to the elevator fault alarm data graph. Based on the order of multiple real-time data in the real-time data stream, multiple data nodes in the elevator fault alarm data graph are connected by directed edges to obtain a data subgraph corresponding to the real-time data stream. Based on the data types of the various real-time data in the real-time data stream, the labels of the data subgraphs are determined; and The data subgraph is added to the elevator fault alarm data graph to obtain the updated elevator fault alarm data graph.

2. The method according to claim 1, characterized in that, Determining the data type of the real-time data included in the real-time data stream includes: For multiple real-time data points in the real-time data stream, their data types are determined based on the data content of the real-time data.

3. The method according to claim 2, characterized in that, The data types include fault types used to characterize elevator malfunctions and non-fault types used to characterize normal elevator operation.

4. The method according to claim 3, characterized in that, Determining the label of the data subgraph based on the data types of the multiple real-time data in the real-time data stream includes: When the data type of the real-time data at a preset position in the real-time data stream is the fault type, the label of the data subgraph is determined based on the fault category; and If the data type of the real-time data at the preset position of the real-time data stream is the non-fault type, the data sub-graph and the real-time data stream are sent to the control terminal, whereby the elevator administrator determines the label of the data sub-graph.

5. The method according to claim 4, characterized in that, The method further includes: If the label of the data subgraph indicates that the elevator has malfunctioned, the label of the data subgraph is added to the fault list.

6. A method for determining elevator faults, characterized in that, The method includes: Receive fault data streams indicating elevator malfunctions; and Based on the elevator fault alarm data graph, fault information corresponding to the fault data stream is determined, wherein the elevator fault alarm data graph is determined by the method according to any one of claims 1 to 5.

7. The method according to claim 6, characterized in that, The step of determining the fault information corresponding to the fault data stream based on the elevator fault alarm data graph includes: Identify the multiple real-time data included in the fault data stream; Based on the multiple real-time data and the data order among the multiple real-time data, fuzzy matching is performed in the elevator fault alarm data graph to determine the matching result, wherein the matching result is a data subgraph in the elevator fault alarm data graph; Based on the labels of the data subgraph, determine the fault index corresponding to the fault data stream; When the label of the data subgraph is the fault category, the fault location is determined based on the real-time data prior to the real-time data of the fault type. Based on the fault location and the fault type, the fault information is determined; and When the labels of the data subgraph are determined by the elevator administrator, the fault information is determined based on the labels of the data subgraph.

8. The method according to claim 7, characterized in that, The elevator fault alarm data graph includes multiple data subgraphs, each of which includes one or more action subgraphs. Each action subgraph is used to represent a continuous action of the elevator, and the action subgraph includes multiple data nodes and directed edges between the multiple data nodes. The step of performing fuzzy matching on the elevator fault alarm data graph based on the multiple real-time data and the data order among the multiple real-time data to determine the matching result includes: If it is determined that the fault data stream is generated based on the data stream combination instruction, the real-time data whose data type is fault type among the multiple real-time data is determined as the matching target; The target action is matched with multiple action subgraphs in the elevator fault alarm data graph to determine the successfully matched target action subgraph. The data subgraph including the target action subgraph is determined as the matching result; and When it is determined that the faulty data stream was generated based on the data stream determination instruction, the data subgraph corresponding to the data feature is determined as the matching result.

9. The method according to any one of claims 6 to 8, characterized in that, The method further includes: Receive the real-time data stream sent by the IoT terminal; Based on the real-time data stream, determine the data characteristics of the real-time data stream; When the data type of the real-time data in the real-time data stream is the fault type, a data stream combination instruction is sent to the IoT terminal, so that after receiving the data stream combination instruction, the IoT terminal generates the fault data stream based on the real-time data of the fault type and the real-time data stream, and returns the fault data stream to the control terminal; and If the data feature matches the label of the data subgraph in the fault list, a data stream determination instruction is sent to the IoT terminal, so that after receiving the data stream determination instruction, the IoT terminal determines the real-time data stream corresponding to the data feature that matches the label of the data subgraph in the fault list as the fault data stream, and returns the fault data stream to the control terminal.

10. An elevator fault alarm data graph updating device, characterized in that, The device includes: The type determination module is used to determine the data type of the real-time data included in the elevator real-time data stream; The node adding module is used to add data nodes corresponding to the real-time data to the elevator fault alarm data graph when the real-time data is not included in the elevator fault alarm data graph. The node connection module is used to connect multiple data nodes in the elevator fault alarm data graph based on the order of multiple real-time data in the real-time data stream using directed edges to obtain a data subgraph corresponding to the real-time data stream. A label determination module is used to determine the label of the data subgraph based on the data type of each of the multiple real-time data in the real-time data stream; and The data graph update module is used to add the data subgraph to the elevator fault alarm data graph to obtain the updated elevator fault alarm data graph.

11. An elevator fault determination device, characterized in that, The device includes: The data stream receiving module is used to receive fault data streams that indicate elevator malfunctions. The information determination module is used to determine the fault information corresponding to the fault data stream based on the elevator fault alarm data graph.

12. An electronic device, comprising: One or more processors; Memory, used to store one or more computer programs. The characteristic feature is that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 9.

13. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When the computer program or instructions are executed by a processor, they implement the steps of the method according to any one of claims 1 to 9.

14. A computer program product comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by a processor, they implement the steps of the method according to any one of claims 1 to 9.

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