Method and device for determining equipment state

Abstract

The invention discloses a method and a device for determining a device state. A specific embodiment of the method comprises the following steps: acquiring running state data of target equipment; distribution data of a state feature space is determined, and the state feature space represents abnormal state feature data of equipment in the equipment type to which the target equipment belongs; determining the correlation between the operation state data and the distribution data; and determining the operation state of the target equipment according to the correlation. Based on the real-time running state data of the equipment, the current running state of the equipment can be automatically judged through the state feature space, and the timeliness and accuracy of fault analysis and fault positioning are improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of computer technology, specifically to the field of fault analysis technology, and more particularly to a method, apparatus, computer-readable medium, and electronic device for determining a device status. Background Art

[0002] In the sorting system, the status of the sorting equipment, such as equipment failure status, directly affects the efficiency and quality of the sorting process in the field operation. If the sorting equipment fails and is not discovered in time, it will cause the parcels to be sorted to be stranded on the main line, parcel sorting errors and other problems. Therefore, it is very important to monitor the equipment status in real time and respond to equipment abnormalities in a timely manner. In the prior art, the equipment status is generally monitored based on the on-site SCADA (Supervisory Control And Data Acquisition) monitoring or signal lights of the sorting site, and there is a lag in the monitoring of the equipment status and the response to failures. Summary of the invention

[0003] The embodiments of the present application provide a method, an apparatus, a computer-readable medium, and an electronic device for determining a device status.

[0004] In a first aspect, an embodiment of the present application provides a method for determining a device status, including: obtaining operating status data of a target device; determining distribution data of a status feature space, wherein the status feature space characterizes abnormal status feature data of a device in a device type to which the target device belongs; determining a correlation between the operating status data and the distribution data; and determining the operating status of the target device based on the correlation.

[0005] In some examples, the above-mentioned determination of the distribution data of the state feature space includes: determining the distribution mean and distribution variance of the abnormal state feature data in the state feature space by an elliptical envelope algorithm to obtain the distribution data.

[0006] In some examples, before determining the distribution data of the state feature space, the method further includes: obtaining historical abnormal state data of multiple devices in the device type; constructing a state feature space based on the historical abnormal state data in a one-to-one correspondence manner between feature dimensions and abnormal state types corresponding to the historical abnormal state data.

[0007] In some examples, the obtaining of historical abnormal status data of multiple devices in the device type includes: obtaining historical abnormal status data of multiple devices in the device type within a preset time period up to the present.

[0008] In some examples, the determining of the correlation between the operating status data and the distribution data includes: calculating the Mahalanobis distance between the operating status data and the distribution data to determine the correlation.

[0009] In some examples, the above method also includes: in response to determining that the target device is in an abnormal operating state, generating an alarm message corresponding to the target device; based on the subscription information of the mini program in the preset application, pushing the alarm message to the subscription object corresponding to the alarm message.

[0010] In some examples, the above method also includes: determining the distribution position of the target device in the state feature space based on the correlation; and displaying the distribution position and operating status of the target device in the state feature space.

[0011] In a second aspect, an embodiment of the present application provides an apparatus for determining a device status, comprising: an acquisition unit configured to acquire operating status data of a target device; a first determination unit configured to determine distribution data of a state feature space, wherein the state feature space characterizes abnormal state feature data of a device in a device type to which the target device belongs; a second determination unit configured to determine a correlation between the operating status data and the distribution data; and a third determination unit configured to determine the operating status of the target device based on the correlation.

[0012] In some examples, the first determination unit is further configured to: determine the distribution mean and distribution variance of the abnormal state feature data in the state feature space by using an elliptical envelope algorithm to obtain distribution data.

[0013] In some examples, the above-mentioned device also includes: a construction unit, which is configured to: obtain historical abnormal state data of multiple devices in the device type before determining the distribution data of the state feature space; and construct the state feature space based on the historical abnormal state data in a one-to-one correspondence manner between the feature dimensions and the abnormal state types corresponding to the historical abnormal state data.

[0014] In some examples, the construction unit is further configured to: obtain historical abnormal status data of multiple devices of the device type within a preset time period up to the current time.

[0015] In some examples, the second determination unit is further configured to: calculate the Mahalanobis distance between the operating status data and the distribution data to determine the correlation.

[0016] In some examples, the above-mentioned device also includes: a generation unit, configured to generate an alarm message corresponding to the target device in response to determining that the target device is in an abnormal operating state; a push unit, configured to push the alarm message to the subscription object corresponding to the alarm message based on the subscription information of the mini program in the preset application.

[0017] In some examples, the above-mentioned apparatus also includes: a fourth determination unit, configured to determine the distribution position of the target device in the state feature space based on the correlation; and a display unit, configured to display the distribution position and operating status of the target device in the state feature space.

[0018] In a third aspect, an embodiment of the present application provides a computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, the method described in any implementation manner of the first aspect is implemented.

[0019] In a fourth aspect, an embodiment of the present application provides an electronic device, comprising: one or more processors; a storage device on which one or more programs are stored, and when the one or more programs are executed by one or more processors, the one or more processors implement the method described in any implementation manner of the first aspect.

[0020] The method and apparatus for determining the status of a device provided in an embodiment of the present application obtain the operating status data of the target device; determine the distribution data of the status feature space, wherein the status feature space characterizes the abnormal status feature data of the device in the device type to which the target device belongs; determine the correlation between the operating status data and the distribution data; and determine the operating status of the target device based on the correlation, thereby providing a method capable of determining the operating status of the device, and based on the real-time operating status data of the device, the current operating status of the device can be automatically judged through the status feature space, thereby improving the timeliness and accuracy of fault analysis and fault location. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0022] Figure 1 is an exemplary system architecture diagram in which an embodiment of the present application may be applied;

[0023] Figure 2 is a flow chart of an embodiment of a method for determining a device status according to the present application;

[0024] Figure 3 is a schematic diagram of an application scenario of the method for determining a device state according to this embodiment;

[0025] Figure 4 It is a display effect diagram of the distribution position and operation status in the state feature space according to this application;

[0026] Figure 5 is a flow chart of another embodiment of a method for determining a device state according to the present application;

[0027] Figure 6 is a service block diagram of a method for determining a device status according to the present application;

[0028] Figure 7 is a structural diagram of an embodiment of an apparatus for determining a device state according to the present application;

[0029] Figure 8 It is a structural diagram of a computer system suitable for implementing the embodiments of the present application. DETAILED DESCRIPTION

[0030] The present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the relevant invention, rather than to limit the invention. It should also be noted that, for ease of description, only the parts related to the relevant invention are shown in the accompanying drawings.

[0031] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0032] It should be noted that the collection, collection, updating, analysis, processing, use, transmission, storage and other aspects of user personal information involved in the technical solution of this disclosure are in compliance with the provisions of relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. Necessary measures are taken for user personal information to prevent illegal access to user personal information data and maintain the security of user personal information, network security and national security.

[0033] Figure 1 An exemplary architecture 100 is shown to which the method and apparatus for determining a device status of the present application can be applied.

[0034] like Figure 1 As shown, the system architecture 100 may include terminal devices 101, 102, 103, a network 104 and a server 105. The communication connection between the terminal devices 101, 102, 103 constitutes a topological network, and the network 104 is used to provide a medium for the communication link between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0035] The terminal devices 101, 102, 103 can interact with the server 105 through the network 104 to receive or send data, etc. The terminal devices 101, 102, 103 can be hardware devices or software that support network connection for data interaction and data processing. When the terminal devices 101, 102, 103 are hardware, they can be various electronic devices that support network connection, information acquisition, interaction, display, processing and other functions, including but not limited to sorting equipment, smart phones, tablet computers, e-book readers, laptop portable computers and desktop computers, etc. When the terminal devices 101, 102, 103 are software, they can be installed in the electronic devices listed above. It can be implemented as multiple software or software modules for providing distributed services, for example, or it can be implemented as a single software or software module. No specific limitation is made here.

[0036] The server 105 may be a server that provides various services, for example, a background processing server that automatically determines the current operating state of the device according to the state feature space for the operating state data generated by the terminal devices 101, 102, and 103. As an example, the server 105 may be a cloud server.

[0037] It should be noted that the server can be hardware or software. When the server is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or it can be implemented as a single server. When the server is software, it can be implemented as multiple software or software modules (for example, software or software modules used to provide distributed services), or it can be implemented as a single software or software module. No specific limitation is made here.

[0038] It should also be noted that the method for determining the device status provided in the embodiments of the present application can be executed by the server, or by the terminal device, or by the server and the terminal device in cooperation with each other. Accordingly, the various parts (such as various units) included in the apparatus for determining the device status can be all set in the server, or all set in the terminal device, or can be set in the server and the terminal device respectively.

[0039] It should be understood that Figure 1 The number of terminal devices, networks, and servers in the system architecture is only illustrative. Any number of terminal devices, networks, and servers may be provided as required. When the electronic device on which the method for determining the state of a device is running does not need to perform data transmission with other electronic devices, the system architecture may only include the electronic device (e.g., server or terminal device) on which the method for determining the state of a device is running.

[0040] Continue to refer Figure 2 , a process 200 of an embodiment of a method for determining a device state is shown, comprising the following steps:

[0041] Step 201, obtaining the operating status data of the target device.

[0042] In this embodiment, the execution subject of the method for determining the device status (for example Figure 1 The terminal device or server in the network can obtain the operating status data of the target device remotely or locally through a wired network connection or a wireless network connection.

[0043] The target device may be a machine device that can realize various functions. For example, in the field of logistics sorting, the target device may be a sorting device; in the field of intelligent distribution, the target device may be an intelligent distribution vehicle.

[0044] The above-mentioned execution subject can collect the operation status data of the equipment from the sorting equipment body, and the operation status data covers various types of sorting data and information processing data of the sorting equipment during the sorting process.

[0045] In order to reduce the amount of data processing in the process of determining the status and improve the information processing efficiency of the status determination process, in some optional implementation methods of this embodiment, the above-mentioned execution entity can obtain the original operating status data of the target device, and then filter the original operating status data to obtain operating status data that characterizes the possibility of failure of the target device, so as to further determine the abnormal state of the operating status data through subsequent steps.

[0046] Step 202, determining the distribution data of the state feature space.

[0047] In this embodiment, the execution subject can obtain the distribution data of the state feature space remotely or locally through a wired network connection or a wireless network connection. The state feature space represents the abnormal state feature data of the device in the device type to which the target device belongs.

[0048] As an example, the above-mentioned execution entity can provide services such as data storage and state modeling. Through the data storage service, the abnormal state feature data of all devices in the above-mentioned device types are stored; then, through the state modeling service, the state modeling of the devices in the above-mentioned device types is performed based on the large amount of stored abnormal state feature data to obtain the abnormal state model, that is, the state feature space.

[0049] After the state feature space is obtained, the distribution of various abnormal state feature data in the state feature space can be determined to obtain distribution data.

[0050] In some optional implementations of this embodiment, before executing the above step 202, the above execution subject may construct the state feature space in the following manner:

[0051] First, historical abnormal status data of multiple devices in the device type is obtained.

[0052] In this implementation, the above-mentioned execution entity can collect the initial historical abnormal status data of multiple devices in the device type through the data collection service, and perform data ETL (Extraction-Transformation-Loading) operations on the initial abnormal status data to obtain the historical abnormal status data of multiple devices.

[0053] Second, a state feature space is constructed based on the historical abnormal state data by adopting a one-to-one correspondence between feature dimensions and abnormal state types corresponding to the historical abnormal state data.

[0054] In this implementation, a feature dimension corresponds to an abnormal state in the historical abnormal state data, and the abnormal state data under each abnormal state is represented in the feature dimension corresponding to the abnormal state to construct a state feature space.

[0055] As an example, the abnormal state of the equipment includes three types: fault state, alarm state, and communication interruption state. The above execution subject constructs a three-dimensional feature space based on the duration of the three types of abnormal states. Among them, the first feature dimension represents the duration of the communication interruption state, the second feature dimension represents the duration of the alarm state, and the third feature dimension represents the duration of the fault state.

[0056] In this implementation, a state feature space is constructed by using a one-to-one correspondence between feature dimensions and abnormal state types corresponding to historical abnormal state data, thereby improving the accuracy and expressiveness of features in the state feature space.

[0057] In some optional implementations of this embodiment, the execution subject may perform step 202 in the following manner: determine the distribution mean and distribution variance of the abnormal state feature data in the state feature space by using an elliptical envelope algorithm to obtain distribution data.

[0058] The specific calculation process of the Elliptic Envelopes algorithm includes:

[0059] 1. Perform feature scaling, normalization and other preprocessing on the original abnormal state feature data in the state feature space to ensure that the proportions between the features are consistent.

[0060] 2. Calculate the covariance matrix of the data points, which describes the correlation between different features of the data points. The data points are the data points corresponding to the duration of each abnormal state.

[0061] 3. Use the covariance matrix to calculate the ellipse of the state feature space. The ellipse consists of a center point, a major axis, and a minor axis, and can be used to describe the distribution shape of data points in a high-dimensional space.

[0062] 4. Calculate the distribution mean of the state feature space. The center point of the ellipse is the distribution mean, which represents the position of the entire data set in the feature space.

[0063] 5. Calculate the distribution variance of the state feature space based on the major and minor axes of the ellipse. The ratio of the major axis to the minor axis describes the degree of dispersion of the data points among the features, which can be used to estimate the variance of the distribution.

[0064] In this implementation, a specific method for determining the distribution data of a state feature space is provided, thereby improving the accuracy of the obtained distribution data.

[0065] Step 203: Determine the correlation between the operating status data and the distribution data.

[0066] In this embodiment, the execution entity may determine the correlation between the running status data and the distribution data.

[0067] As an example, the execution subject may determine the correlation between the running status data and the distribution data by calculating the cosine similarity, Euclidean distance, Manhattan distance or Pearson correlation coefficient between the running status data and the distribution data.

[0068] In some optional implementations of this embodiment, the execution subject may perform step 203 in the following manner: calculating the Mahalanobis distance between the running status data and the distribution data to determine the correlation.

[0069] As an example, the above execution subject can perform the calculation process of the Mahalanobis distance in the following manner:

[0070] 1. Standardized data: Subtract the means of the two characteristic data, the operating status data and the distribution data, respectively, and then divide them by their standard deviations, so that their data distribution has a mean of 0 and a standard deviation of 1.

[0071] 2. Calculate the covariance matrix: Use the standardized data to calculate the covariance matrix. The covariance matrix is ​​an n×n matrix, where n is the dimension of the feature data. The elements of the covariance matrix represent the covariance between different features.

[0072] 3. Calculate the inverse covariance matrix: Use the inverse matrix of the covariance matrix to calculate the inverse covariance matrix. The inverse covariance matrix is ​​an n×n matrix, where n is the dimension of the feature data. The elements of the inverse covariance matrix represent the correlation coefficients between different features.

[0073] 4. Calculate Mahalanobis distance: Use the elements of the inverse covariance matrix to calculate the Mahalanobis distance between two feature data. The calculation formula of Mahalanobis distance is:

[0074] Mahalanobis distance=(x1-x2) T ×inv(C)×(x1-x2)

[0075] Among them, x1 and x2 represent the vectors of two feature data, namely, the operating status data and the distribution data, respectively, C is the covariance matrix, and inv(C) is the inverse covariance matrix.

[0076] It can be understood that the smaller the Mahalanobis distance value is, the greater the correlation between the operating status data and the distribution data is.

[0077] In this implementation, the correlation between the operating status data and the distribution data is determined by means of the Mahalanobis distance, thereby improving the accuracy of the determined correlation data.

[0078] Continue to see Figure 3 , Figure 3 FIG. 3 is a schematic diagram 300 of an application scenario of the method for determining the device status according to this embodiment. Figure 3 In the application scenario, multiple sorting devices 301 in the sorting system are performing the sorting operation of the parcels. For each sorting device 301 in the sorting system, its own operating status data is transmitted to the server 302 in real time. The server 302 determines the distribution data of the state feature space, wherein the state feature space represents the abnormal state feature data of the device in the device type to which the target device belongs. After receiving the operating status data of the sorting device, the correlation between the operating status data and the distribution data is determined; then, according to the correlation, the operating status of the target device is determined.

[0079] The method provided by the above-mentioned embodiment of the present application obtains the operating status data of the target device; determines the distribution data of the state feature space, wherein the state feature space characterizes the abnormal state feature data of the device in the device type to which the target device belongs; determines the correlation between the operating status data and the distribution data; and determines the operating status of the target device based on the correlation, thereby providing a method for determining the operating status of the device. Based on the real-time operating status data of the device, the current operating status of the device can be automatically judged through the state feature space, thereby improving the timeliness and accuracy of fault analysis and fault location.

[0080] In some optional implementations of this embodiment, the above-mentioned execution entity may also perform the following operations: first, in response to determining that the target device is in an abnormal operating state, generate an alarm message corresponding to the target device; then, based on the subscription information of the mini-program in the preset application, push the alarm message to the subscription object corresponding to the alarm message.

[0081] The preset application may be any application with a real-time communication function. As an example, the preset application is WeChat.

[0082] In this implementation, the alarm information pushed to the subscribed object may include information such as the name, location, and abnormal state type of the target device, so that the subscribed object can find the target device in time and locate the fault.

[0083] In some optional implementations of this embodiment, the above-mentioned execution subject may also perform the following operations: determine the distribution position of the target device in the state feature space based on the correlation; and display the distribution position and operating status of the target device in the state feature space.

[0084] refer to Figure 4 , showing the display effect diagram of the distribution position and the operating state in the state feature space. Among them, the first feature dimension 401 represents the duration of the communication interruption state, the second feature dimension 402 represents the duration of the alarm state, and the third feature dimension 403 represents the duration of the fault state.

[0085] In the effect diagram, a scatter plot is generally used to represent the distribution position and abnormality score of each device in the state feature space, so as to more intuitively display the device status. In order to further improve the intuitiveness of the effect diagram, different colored dots can be used to distinguish between normal and abnormal devices. For devices in abnormal states, different colored dots can be used to distinguish devices with different abnormalities.

[0086] In this implementation, the distribution location and operation status of the target device are displayed in the state feature space by means of effect diagrams, thereby improving the intuitiveness of information display and the user experience.

[0087] Continue to refer Figure 5 , shows a schematic process 500 of another embodiment of a method for determining a device state according to the present application, comprising the following steps:

[0088] Step 501, obtaining the operating status data of the target device.

[0089] Step 502: determine the distribution mean and distribution variance of the abnormal state feature data in the state feature space by using an elliptical envelope algorithm to obtain distribution data.

[0090] The state feature space represents abnormal state feature data of a device in the device type to which the target device belongs.

[0091] Step 503, calculating the Mahalanobis distance between the running status data and the distribution data to determine the correlation.

[0092] Step 504: Determine the operating status of the target device based on the correlation.

[0093] Step 505: In response to determining that the target device is in an abnormal operating state, generate an alarm message corresponding to the target device.

[0094] Step 506: Based on the subscription information of the mini-program in the preset application, the alarm message is pushed to the subscription object corresponding to the alarm message.

[0095] Step 507: Determine the distribution position of the target device in the state feature space according to the correlation.

[0096] Step 508: Display the distribution location and operation status of the target device in the state feature space.

[0097] It can be seen from this embodiment that Figure 2 Compared with the corresponding embodiments, process 500 of the method for determining the device status in this embodiment specifically illustrates the correlation determination process, the alarm information generation and push process, and the abnormal device display process in the status feature space, further improving the timeliness and accuracy of fault analysis and fault location, as well as the timeliness of information push and the intuitiveness of effect display.

[0098] Continue to refer Figure 6 In order to further illustrate the method for determining the device status in the present application, the following systematic example is given:

[0099] A data collection service 601 , a data ETL service 602 , a data processing service 603 , an alarm service 604 and a small program service 605 are provided for determining the device status.

[0100] For data collection services, equipment status characteristic data is collected from the sorting equipment itself, and the status characteristic data covers various types of sorting data collection and processing.

[0101] For data ETL services, we provide services for data cleaning and storing in ES (Elasticsearch) index library. At the same time, we perform feature analysis based on the state model (state feature space) generated by historical abnormal state data, realize fault identification, fault analysis and fault location functions, and provide customers with comprehensive and accurate fault diagnosis functions.

[0102] For data processing services, we provide services such as storage of historical abnormal status data and status modeling to better understand the value hidden behind the data, discover possible problems with the equipment, and provide data-supported optimization solutions.

[0103] For the alarm service, a service that processes alarm content according to the alarm template is provided. It is necessary to configure the recipient's WeChat account to push the device failure alarm information so that the recipient can respond in time. The recipient must subscribe to the device failure alarm message in the mini program to receive the alarm message.

[0104] For WeChat mini programs, the WeChat mini program used to display device status information and fault information makes it convenient for users to quickly obtain device status information and handle faults, and provides timely and effective responses and solutions.

[0105] Continue to refer Figure 7 As an implementation of the methods shown in the above figures, the present application provides an embodiment of a device for determining a device state. Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0106] like Figure 7 As shown, the device 700 for determining the device status includes: an acquisition unit 701, configured to acquire the operating status data of the target device; a first determination unit 702, configured to determine the distribution data of the state feature space, wherein the state feature space characterizes the abnormal state feature data of the device in the device type to which the target device belongs; a second determination unit 702, configured to determine the correlation between the operating status data and the distribution data; and a third determination unit 704, configured to determine the operating status of the target device based on the correlation.

[0107] In some optional implementations of this embodiment, the first determining unit 702 is further configured to: determine the distribution mean and distribution variance of the abnormal state feature data in the state feature space by using an elliptical envelope algorithm to obtain distribution data.

[0108] In some optional implementations of the present embodiment, the above-mentioned device also includes: a construction unit (not shown in the figure), which is configured to: before determining the distribution data of the state feature space, obtain historical abnormal state data of multiple devices in the device type; and construct a state feature space based on the historical abnormal state data in a one-to-one correspondence manner between feature dimensions and abnormal state types corresponding to the historical abnormal state data.

[0109] In some optional implementations of this embodiment, the above-mentioned construction unit (not shown in the figure) is further configured to: obtain historical abnormal status data of multiple devices in the device type within a preset time period up to the current time.

[0110] In some optional implementations of this embodiment, the second determining unit 703 is further configured to: calculate the Mahalanobis distance between the operating status data and the distribution data to determine the correlation.

[0111] In some optional implementations of this embodiment, the above-mentioned device also includes: a generation unit (not shown in the figure), configured to generate an alarm message corresponding to the target device in response to determining that the target device is in an abnormal operating state; a push unit (not shown in the figure), configured to push the alarm message to the subscription object corresponding to the alarm message based on the subscription information of the mini program in the preset application.

[0112] In some optional implementations of this embodiment, the above-mentioned device also includes: a fourth determination unit (not shown in the figure), configured to determine the distribution position of the target device in the state feature space based on the correlation; a display unit (not shown in the figure), configured to display the distribution position and operating status of the target device in the state feature space.

[0113] In this embodiment, an acquisition unit in a device for determining the status of a device acquires operating status data of a target device; a first determination unit determines distribution data of a status feature space, wherein the status feature space characterizes abnormal status feature data of a device in a device type to which the target device belongs; a second determination unit determines the correlation between the operating status data and the distribution data; a third determination unit determines the operating status of the target device based on the correlation, thereby providing a device capable of determining the operating status of a device, which can automatically identify the current operating status of the device through the status feature space based on the real-time operating status data of the device, thereby improving the timeliness and accuracy of fault analysis and fault location.

[0114] Reference below Figure 8 , which shows a device suitable for implementing the embodiments of the present application (eg Figure 1 Schematic diagram of the structure of a computer system 800 of the devices 101, 102, 103, 105 shown. Figure 8 The device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0115] like Figure 8As shown, the computer system 800 includes a processor (e.g., CPU, central processing unit) 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage part 808 into a random access memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the system 800 are also stored. The processor 801, ROM 802, and RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0116] The following components are connected to the I / O interface 805: an input section 806 including a keyboard, a mouse, etc.; an output section 807 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 808 including a hard disk, etc.; and a communication section 809 including a network interface card such as a LAN card, a modem, etc. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the I / O interface 805 as needed. A removable medium 811, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 810 as needed, so that a computer program read therefrom is installed into the storage section 808 as needed.

[0117] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication part 809, and / or installed from a removable medium 811. When the computer program is executed by the processor 801, the above-mentioned functions defined in the method of the present application are executed.

[0118] It should be noted that the computer-readable medium of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0119] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the client computer, partially on the client computer, as a separate software package, partially on the client computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the client computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0120] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the device, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0121] The units involved in the embodiments described in the present application may be implemented by software or by hardware. The described units may also be set in a processor, for example, may be described as: a processor, comprising an acquisition unit, a first determination unit, a second determination unit, and a third determination unit. Among them, the names of these units do not constitute a limitation on the unit itself under certain circumstances. For example, the first determination unit may also be described as "a unit for determining the distribution data of a state feature space, wherein the state feature space characterizes the abnormal state feature data of a device in a device type to which the target device belongs".

[0122] As another aspect, the present application also provides a computer-readable medium, which may be included in the device described in the above embodiment; or may exist independently without being assembled into the device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by the device, the computer device: obtains the operating status data of the target device; determines the distribution data of the state feature space, wherein the state feature space characterizes the abnormal state feature data of the device in the device type to which the target device belongs; determines the correlation between the operating status data and the distribution data; and determines the operating status of the target device based on the correlation.

[0123] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above invention concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other to form a technical solution.

Claims

1. A method for determining a device status, comprising: Obtain the operating status data of the target device; Determine distribution data of a state feature space, wherein the state feature space represents abnormal state feature data of a device in a device type to which the target device belongs; determining a correlation between the operating status data and the distribution data; The operating status of the target device is determined according to the correlation.

2. The method according to claim 1, wherein: The distribution data of the determined state feature space includes: The distribution data is obtained by determining the distribution mean and distribution variance of the abnormal state feature data in the state feature space through an elliptical envelope algorithm.

3. The method according to claim 1, wherein: Before determining the distribution data of the state feature space, the method further includes: Acquire historical abnormal status data of multiple devices of the device type; The state feature space is constructed based on the historical abnormal state data in a one-to-one correspondence manner between feature dimensions and abnormal state types corresponding to the historical abnormal state data.

4. The method according to claim 3, wherein: The acquiring of historical abnormal status data of the plurality of devices of the device type comprises: The historical abnormal status data of the plurality of devices of the device type within a preset time period up to the present is obtained.

5. The method according to claim 1, wherein: The determining the correlation between the operating status data and the distribution data comprises: The Mahalanobis distance between the operating status data and the distribution data is calculated to determine the correlation.

6. The method according to claim 1, wherein: Also includes: In response to determining that the target device is in an abnormal operating state, generating an alarm message corresponding to the target device; Based on the subscription information of the mini-program in the preset application, the alarm message is pushed to the subscription object corresponding to the alarm message.

7. The method according to claim 1, wherein: Also includes: Determining, according to the correlation, a distribution position of the target device in the state feature space; In the state feature space, the distribution location and the operating state of the target device are displayed.

8. An apparatus for determining a state of a device, comprising: an acquisition unit, configured to acquire operation status data of a target device; A first determining unit is configured to determine distribution data of a state feature space, wherein the state feature space represents abnormal state feature data of a device in a device type to which the target device belongs; a second determining unit configured to determine a correlation between the operating status data and the distribution data; The third determining unit is configured to determine the operating status of the target device according to the correlation.

9. A computer readable medium having a computer program stored thereon, wherein: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

10. An electronic device comprising: one or more processors; a storage device having one or more programs stored thereon, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 7.

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