Device monitoring method, device and storage medium based on vector coordinates

Abstract

The present invention relates to the field of equipment monitoring, and discloses an equipment monitoring method, equipment and storage medium based on vector coordinates. The method comprises: obtaining N coordinate data of the monitored equipment, wherein N is a positive integer greater than 2; based on the N coordinate data, generating N‑1 vector coordinates and the motion speed corresponding to the N‑1 vector coordinates; judging whether the N‑1 vector coordinates deviate from the preset route range; when they do not deviate from the preset route range, judging whether the motion speed corresponding to the N‑1 vector coordinates has data exceeding the preset speed threshold; when it does not exist, generating visualization data, and sending the visualization data to the preset management port; when it exists, sending speed warning information to the preset management port. In the embodiment of the present invention, the monitoring accuracy of the motion state of the equipment is improved, and the user's grasp of the motion state of the equipment is enhanced by using the visualization data of the vector motion.

Description

Technical Field

[0001] The present invention relates to the field of equipment monitoring, and in particular to an equipment monitoring method, equipment and storage medium based on vector coordinates. Background Art

[0002] With the rapid development of IoT technology, the intelligence level of industrial equipment has been continuously improved, which has not only changed the production mode, but also greatly improved production efficiency and safety. The application scenarios of IoT technology continue to expand, and the internal driving force of the market has promoted the rapid development of IoT. Equipment manufacturers, Internet companies, and operators have deployed IoT on a large scale to promote the integration and development of IoT with artificial intelligence, edge computing and other technologies. Smart grids, smart cities, intelligent platforms and other industry applications have become key scenarios for global IoT applications.

[0003] The development trend of the Internet of Things shows that this field will continue to make progress, not only on the technical level, but also have a profound impact on the social level. As the architecture becomes more flexible, ultra-low power consumption becomes the norm, the network security of endpoint devices becomes increasingly important, and supervision becomes more stringent, the application of the Internet of Things will become more extensive and mature. However, although the Internet of Things technology has made significant progress in basic positioning functions, in terms of dynamic monitoring and early warning systems, the monitoring of the movement status of devices is inaccurate, and misjudgment of device movement monitoring often occurs. Therefore, in view of the technical problem that the existing technology cannot accurately monitor the movement status of devices in the state of the Internet of Things, a new technology is needed to solve the current problem. Summary of the invention

[0004] The main purpose of the present invention is to solve the technical problem of inaccurate monitoring of the motion state of a device in the state of the Internet of Things in the prior art.

[0005] A first aspect of the present invention provides a device monitoring method based on vector coordinates, the device monitoring method based on vector coordinates comprising:

[0006] Obtaining N coordinate data of the monitored device, where N is a positive integer greater than 2;

[0007] Based on the N coordinate data, generate N-1 vector coordinates corresponding to the monitored device and movement speeds corresponding to the N-1 vector coordinates;

[0008] Determine whether the N-1 vector coordinates deviate from the preset route range;

[0009] When N-1 of the vector coordinates deviate from the preset route range, route warning information is sent to the preset management port;

[0010] When the N-1 vector coordinates do not deviate from the preset route range, it is determined whether there is data of the movement speed corresponding to the N-1 vector coordinates exceeding the preset speed threshold;

[0011] When there is no data exceeding the preset speed threshold, generating visualization data according to the N-1 vector coordinates, and sending the visualization data to the preset management port;

[0012] When there is data exceeding the preset speed threshold, a speed warning message is sent to the preset management port.

[0013] Optionally, in a first implementation of the first aspect of the present invention, the determining whether the N-1 vector coordinates deviate from a preset route range includes:

[0014] Determine whether there is data of the lateral offset of the N-1 vector coordinates exceeding the preset route range;

[0015] When there is data of lateral deviation exceeding the preset route range, the lateral range of N-1 vector coordinates deviating from the route range is determined;

[0016] When there is no data of the lateral offset exceeding the preset route range, it is determined whether there is data of the longitudinal offset of the N-1 vector coordinates exceeding the preset route range;

[0017] When there is data of longitudinal offset exceeding the preset route range, the longitudinal range of N-1 vector coordinates deviating from the route range is determined;

[0018] When there is no data of the longitudinal offset exceeding the preset route range, it is determined that the N-1 vector coordinates do not deviate from the route range.

[0019] Optionally, in a second implementation of the first aspect of the present invention, determining the lateral range of the N-1 vector coordinates that deviate from the route range includes:

[0020] Calculate the maximum lateral difference of N-1 vector coordinates from the lateral range;

[0021] In the lateral range, searching for the lateral range length corresponding to the maximum lateral difference;

[0022] Based on the lateral range length and the maximum lateral difference, a lateral deviation rate is calculated, and the lateral deviation rate is determined as a deviation state of N-1 of the vector coordinates deviating from the lateral range.

[0023] Optionally, in a third implementation of the first aspect of the present invention, determining the longitudinal range of the N-1 vector coordinates deviating from the route range includes:

[0024] Calculate the maximum longitudinal difference of N-1 vector coordinates from the longitudinal range;

[0025] In the longitudinal range, searching for the longitudinal range length corresponding to the maximum longitudinal difference;

[0026] Based on the longitudinal range length and the maximum longitudinal difference, a longitudinal deviation rate is calculated, and the longitudinal deviation rate is determined as a deviation state of N-1 of the vector coordinates deviating from the longitudinal range.

[0027] Optionally, in a fourth implementation of the first aspect of the present invention, generating N-1 vector coordinates corresponding to the monitored device and the movement speed corresponding to the vector coordinates based on the N coordinate data includes:

[0028] According to the collection time corresponding to the N coordinate data, the N coordinate data are subtracted to generate N-1 vector coordinates corresponding to the monitored device;

[0029] Based on the time sequence, subtract the acquisition time corresponding to the N coordinate data to generate the movement duration corresponding to the N-1 vector coordinates;

[0030] The movement speeds corresponding to the N-1 vector coordinates are calculated according to the movement durations corresponding to the N-1 vector coordinates.

[0031] Optionally, in a fifth implementation of the first aspect of the present invention, acquiring N coordinate data of the monitored device includes:

[0032] Based on the preset navigation system and the acquisition cycle, the real-time coordinates of the monitored device are acquired at intervals to obtain N coordinate data of the monitored device.

[0033] Optionally, in a sixth implementation of the first aspect of the present invention, after generating visualization data according to the N-1 vector coordinates and sending the visualization data to a preset management port, the method further includes:

[0034] Receive visual adjustment instructions;

[0035] Based on the visualization adjustment instruction, the route range is modified to obtain a new route range.

[0036] Optionally, in a seventh implementation manner of the first aspect of the present invention, generating visualization data according to the N-1 vector coordinates includes:

[0037] Based on the time sequence, calculate the angle data between the N-1 vector coordinates to generate a trajectory angle set;

[0038] Extracting the trajectory angle from the trajectory angle set;

[0039] Determining whether the trajectory angle is greater than a preset angle threshold;

[0040] When it is greater than a preset angle threshold, the two vector coordinates corresponding to the trajectory angle are smoothed to obtain two smoothed vector coordinates, and the two smoothed vector coordinates are written into a preset visualization coordinate set;

[0041] When it is not greater than a preset angle threshold, the two vector coordinates corresponding to the trajectory angle are written into a preset visualization coordinate set, and it is determined whether the trajectory angle set is an empty set;

[0042] When the set is not empty, re-extracting the trajectory angle in the trajectory angle set;

[0043] When it is an empty set, visualization data of the corresponding motion trajectory of the monitored device is generated according to the visualization coordinate set.

[0044] A second aspect of the present invention provides a device monitoring device based on vector coordinates, comprising: a memory and at least one processor, wherein instructions are stored in the memory, and the memory and the at least one processor are interconnected via lines; the at least one processor calls the instructions in the memory so that the device monitoring device based on vector coordinates executes the above-mentioned device monitoring method based on vector coordinates.

[0045] A third aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned device monitoring method based on vector coordinates.

[0046] In an embodiment of the present invention, by proposing a trajectory vector of a monitoring device, the operating status of the monitored device is generated by real-time analysis based on the monitoring data pushed by a detection device, whether the device exceeds a pre-specified vector range is analyzed based on the trajectory vector of the device, and whether the speed corresponding to the trajectory vector of the device meets a pre-specified speed threshold is analyzed, and the motion state of the device is monitored in real time using vector motion data, thereby improving the monitoring accuracy of the motion state of the device, and enhancing the user's understanding of the motion state of the device using visual data of vector motion. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A schematic diagram of an embodiment of a device monitoring method based on vector coordinates in an embodiment of the present invention;

[0048] Figure 2 1 is a schematic diagram of an embodiment of step 102 of the device monitoring method based on vector coordinates in an embodiment of the present invention;

[0049] Figure 3 A schematic diagram of vector coordinates and route ranges of a device monitoring method based on vector coordinates in an embodiment of the present invention;

[0050] Figure 4 1 is a schematic diagram of an embodiment of step 103 of the device monitoring method based on vector coordinates in an embodiment of the present invention;

[0051] Figure 5 Schematic diagram of an embodiment of a device monitoring device based on vector coordinates in an embodiment of the present invention. DETAILED DESCRIPTION

[0052] The embodiments of the present invention provide a device monitoring method, a device and a storage medium based on vector coordinates.

[0053] The embodiments disclosed in the present invention will be described in more detail below with reference to the accompanying drawings. Although certain embodiments disclosed in the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present invention. It should be understood that the drawings and embodiments disclosed in the present invention are only for exemplary purposes and are not intended to limit the scope of protection disclosed in the present invention.

[0054] In the description of the embodiments disclosed in the present invention, the term "including" and similar terms should be understood as open inclusion, that is, "including but not limited to". The term "based on" should be understood as "based at least in part on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The terms "first", "second", etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0055] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 , an embodiment of the device monitoring method based on vector coordinates in an embodiment of the present invention includes:

[0056] 101. Obtain N coordinate data of the monitored device, where N is a positive integer greater than 2;

[0057] In this embodiment, a real-time positioning device is installed on the monitored device, and multiple addresses are reported by the real-time positioning device. The reporting time interval between each address can be the same duration, or can be set to a specified duration of segmentation, such as the first 50 vectors as duration A, the first 50-150 vectors as duration B, and more than 150 sorted vectors as duration C. The number of coordinates collected by the monitored device should be at least 2, so that the vector data of the monitored device can be calculated using at least two coordinate data.

[0058] Specifically, step 101 includes the following specific implementation methods:

[0059] 1011. Based on a preset navigation system and a collection period, real-time coordinates of the monitored device are acquired at intervals to obtain N coordinate data of the monitored device.

[0060] In step 1011, use the GPS positioning and navigation system or the Beidou positioning and navigation system, set the collection period to 2 seconds, use the positioning system to obtain the real-time coordinate data of the monitoring device once every 2 seconds, and continuously obtain the coordinate data of the monitored device. A total of 800 coordinate data can be obtained.

[0061] 102. Based on the N coordinate data, generate N-1 vector coordinates corresponding to the monitored device and movement speeds corresponding to the N-1 vector coordinates;

[0062] In this embodiment, the first coordinate data is subtracted from the second coordinate data to generate the first vector coordinate. The second coordinate data is subtracted from the third coordinate data to generate the second vector coordinate data. And so on, N-1 vector coordinates are generated. And since there is a timestamp corresponding to the coordinate data in the process of uploading the coordinate data, the motion duration corresponding to each vector coordinate is obtained by subtracting the timestamp of the coordinate data source of the vector coordinate, and the motion speed corresponding to the N-1 vector coordinates can be obtained by multiplying the length of the vector coordinate by the motion duration.

[0063] See also Figure 2 , Figure 2 This is a schematic diagram of an embodiment of step 102 of the device monitoring method based on vector coordinates in an embodiment of the present invention. Step 102 includes the following specific implementation methods:

[0064] 1021. According to the collection time corresponding to the N coordinate data, subtract the N coordinate data to generate N-1 vector coordinates corresponding to the monitored device;

[0065] 1022. Based on the time sequence, subtract the acquisition times corresponding to the N coordinate data to generate movement durations corresponding to N-1 vector coordinates;

[0066] 1023. Calculate the movement speeds corresponding to the N-1 vector coordinates according to the movement durations corresponding to the N-1 vector coordinates.

[0067] In steps 1021-1023, first, according to the order of collection time, the coordinate data x with later collection time is collected. j Subtract the coordinate data x collected earlier j-1 , where x j is the jth coordinate data, j is an integer from 2, ..., N. According to the above logic, we can get the vector coordinate y j-1 =x j -x j-1 , j = 2, 3, ..., N, y j-1 is the j-1th vector coordinate, and there are a total of N-1 vector coordinates {y1, y2, ...., y N-2 ,y N-1}.

[0068] The later time t j Subtract the time t before the acquisition time j-1 , where t j is the jth acquisition time, j is an integer from 2, ..., N. According to the above logic, the exercise duration T is obtained j-1 =t j -t j-1 , j = 2, 3, ..., N, T j-1 is the j-1th movement duration, with a total of N-1 vector coordinates {y1, y2, ...., y N-2 ,y N-1} corresponding to the N-1 exercise durations {T1, T2, ...., T N-2 , T N-1}.

[0069] Finally, calculate the vector lengths of the N-1 vector coordinates {|y1|, |y2|, ...., |y N-2 |,|y N-1 |}, through the vector length {|y1|,|y2|,....,|y N-2 |,|y N-1 |} and N-1 exercise durations {T1, T2, ...., T N-2 , T N-1}, and obtain the motion speeds corresponding to the N-1 vector coordinates {|y1| / T1, |y2| / T2, ...., |y N-2 | / T N-2 ,|y N-1 | / T N-1}, there are a total of N-1 movement speeds.

[0070] 103. Determine whether the N-1 vector coordinates deviate from the preset route range;

[0071] In this example, see Figure 3 , Figure 3 FIG. 1 is a schematic diagram of vector coordinates and route ranges of a device monitoring method based on vector coordinates in an embodiment of the present invention. Figure 3 The coordinate data of the device are x1, x2, x3, x4, x5, x6, x7, x8, x9, etc., totaling 8 vector coordinates x2-x1, x3-x2, x4-x3, x5-x4, x6-x5, x7-x6, x8-x7, x9-x8, etc. A route range R is set in the figure to limit the movement of the vector coordinates within a reasonable range. It is judged whether the 8 vector coordinates exceed the route range R, so as to further judge the subsequent processing process.

[0072] See also Figure 4 , Figure 4 This is a schematic diagram of an embodiment of step 103 of the device monitoring method based on vector coordinates in an embodiment of the present invention. Step 103 includes the following specific implementation methods:

[0073] 1031. Determine whether the lateral offsets of the N-1 vector coordinates contain data exceeding the preset route range;

[0074] 1032. When there is data of lateral offset exceeding the preset route range, determine the lateral range of N-1 vector coordinates deviating from the route range;

[0075] 1033. When there is no data of the lateral offset exceeding the preset route range, it is determined whether there is data of the longitudinal offset of the N-1 vector coordinates exceeding the preset route range;

[0076] 1034. When there is data of a longitudinal offset exceeding a preset route range, determine the longitudinal ranges of N-1 vector coordinates that deviate from the route range;

[0077] 1035. When there is no data of the longitudinal offset exceeding the preset route range, it is determined that the N-1 vector coordinates do not deviate from the route range.

[0078] In steps 1031-1035, the lateral offset of the entire vector coordinate is divided into interval data of the route range in the constrained route to determine whether there is data with a lateral offset exceeding the preset route range in the multiple intervals divided vertically. When there is data with a lateral offset exceeding the preset route range, the lateral range of N-1 vector coordinates deviating from the route range is determined.

[0079] When there is no data of lateral offset exceeding the preset route range, the interval data of the lateral segmentation route range is used to analyze whether the longitudinal offset exceeds the preset route range. When there is data of longitudinal offset exceeding the preset route range, the longitudinal range of the N-1 vector coordinates deviating from the route range is determined. When there is no data of longitudinal offset exceeding the preset route range, it is determined that the N-1 vector coordinates do not deviate from the route range.

[0080] Specifically, step 1032 includes the following specific implementations:

[0081] 10321. Calculate the maximum lateral difference of the N-1 vector coordinates from the lateral range;

[0082] 10322. In the horizontal range, retrieve the horizontal range length corresponding to the maximum horizontal difference;

[0083] 10323. Based on the lateral range length and the maximum lateral difference, calculate the lateral deviation rate, and determine the lateral deviation rate as the deviation state of N-1 vector coordinates deviating from the lateral range.

[0084] In steps 10321-10323, the maximum lateral difference in the lateral data of the deviation from the route range is calculated in the N-1 and vector coordinate data. The maximum lateral difference is 15. If the maximum lateral difference perpendicular to the lateral range is 80, it means that the lateral deviation rate is 15 / 80=18.75%. The lateral deviation rate of 18.75% is determined as the deviation state of the N-1 vector coordinates deviating from the lateral range. The deviation state is used as the reporting data to remind the user, and the user is notified of the current state of the monitored device. For example Figure 3 When vector x6-x5 exceeds the maximum lateral difference of the route range R when running, as well as the deviation rate of the lateral range length of x6-x5 perpendicular to the route range R, the deviation rate is determined as the deviation state of the vector coordinates deviating from the lateral range, and the user is notified so that the user can interfere with the monitored device in time.

[0085] Specifically, step 1034 includes the following specific implementation methods:

[0086] 10341. Calculate the maximum longitudinal difference of the N-1 vector coordinates deviating from the longitudinal range;

[0087] 10342. In the longitudinal range, retrieve the longitudinal range length corresponding to the maximum longitudinal difference;

[0088] 10343. Based on the length of the longitudinal range and the maximum longitudinal difference, calculate the longitudinal deviation rate, and determine the longitudinal deviation rate as the deviation state of N-1 vector coordinates deviating from the longitudinal range.

[0089] In steps 10341-13043, the maximum longitudinal difference in the longitudinal data of the deviation route range is calculated in the N-1 and vector coordinate data. The maximum longitudinal difference is 80. If the maximum longitudinal difference perpendicular to the longitudinal range is 40, it means that the longitudinal deviation rate is 80 / 40=200%. The longitudinal deviation rate of 200% is determined as the deviation state of the N-1 vector coordinates deviating from the longitudinal range. The deviation state is used as the reporting data to remind the user, and the user is notified of the current state of the monitored device. For example Figure 3 When vector x6-x5 exceeds the maximum longitudinal difference of the route range R when running, as well as the deviation rate of the longitudinal range length of x6-x5 perpendicular to the route range R, the deviation rate is determined as the deviation state of the vector coordinates deviating from the longitudinal range, and the user is notified so that the user can interfere with the monitored device in time.

[0090] 104. When N-1 of the vector coordinates deviate from the preset route range, route warning information is sent to the preset management port;

[0091] In this embodiment, when N-1 vector coordinates deviate from the preset route range, the lateral deviation rate and the longitudinal deviation rate are sent to the management port as warning information, so that the user can intervene in the monitored equipment in time based on the route warning information.

[0092] 105. When the N-1 vector coordinates do not deviate from the preset route range, determine whether there is data of the movement speed corresponding to the N-1 vector coordinates exceeding the preset speed threshold;

[0093] In this embodiment, the motion speeds corresponding to the N-1 vector coordinates {|y1| / T1, |y2| / T2, ...., |y N-2 | / T N-2 ,|y N-1 | / T N-1}Whether there is a speed exceeding the speed threshold S, where S is an arbitrary constant.

[0094] 106. When there is no data exceeding the preset speed threshold, generating visualization data according to the N-1 vector coordinates, and sending the visualization data to a preset management port;

[0095] In this embodiment, the N-1 vector coordinates are sorted according to the route to generate relevant visualization data, and the visualization data is smoothed to obtain smoothed visualization data. The smoothed visualization data is sent to the preset management port so that the user can preview the monitored device in time.

[0096] Specifically, step 106 includes the following specific implementation methods:

[0097] 1061. Calculate the angle data between the N-1 vector coordinates based on the time sequence to generate a trajectory angle set;

[0098] 1062. Extracting a trajectory angle from the trajectory angle set;

[0099] 1063. Determine whether the trajectory angle is greater than a preset angle threshold;

[0100] 1064. When the angle is greater than a preset angle threshold, smoothing is performed on the two vector coordinates corresponding to the trajectory angle to obtain two smoothed vector coordinates, and the two smoothed vector coordinates are written into a preset visualization coordinate set;

[0101] 1065. When the angle is not greater than the preset angle threshold, the two vector coordinates corresponding to the trajectory angle are written into a preset visualization coordinate set, and it is determined whether the trajectory angle set is an empty set;

[0102] 1066. When the set is not empty, re-extracting the trajectory angle from the trajectory angle set;

[0103] 1067. When it is an empty set, generating visualization data of the corresponding motion trajectory of the monitored device according to the visualization coordinate set.

[0104] In steps 1061-1067, N-1 vector coordinates {y1, y2, ...., y N-2 ,y N-1}, calculate in sequence<y1,y2> ,<y2,y3> ,..., <y N-2 ,y N-1 >The trajectory angle, we get {<y1,y2> ,<y2,y3> ,..., <y N-2 ,y N-1 >}Trajectory angle set. Extract the trajectory angles in the trajectory angle set one by one and judge <y N-2 ,y N-1 >Whether the track angle is greater than the preset angle threshold. If it is greater than the angle threshold, it means that the track is too sharp and not smooth enough. <y N-2 ,y N-1 >y corresponding to the trajectory angle N-2 ,y N-1 The vector coordinates are smoothed to obtain two smoothed vector coordinates y ， N-2 ,y ， N-1 , and y ， N-2 ,y ， N-1 Write to the preset visualization coordinate set. If <y N-2 ,yN-1 >If the trajectory angle is not greater than the preset angle threshold, it means that the trajectory is relatively smooth, then y N-2 ,y N-1 Write into the preset visualization coordinate set, and then determine whether the trajectory angle set has been extracted as an empty set. If it is not an empty set, continue to extract the trajectory angles in the trajectory angle set. If it is an empty set, it means that the trajectory angle set has extracted all trajectory angles, then generate visualization data of the corresponding motion trajectory of the monitored device based on the smoothed coordinate data in the visualization coordinate set.

[0105] Furthermore, after step 106, the following specific implementations are also included:

[0106] 1068. Receive visualization adjustment instructions;

[0107] 1069. Based on the visualization adjustment instruction, modify the route range to obtain a new route range.

[0108] In steps 1068-1069, if Figure 3 As shown, after receiving the visualization adjustment instruction, the route range R is adjusted to obtain a new route range so that the user can readjust the range restriction conditions for the monitored device.

[0109] 107. When there is data exceeding a preset speed threshold, a speed warning message is sent to a preset management port.

[0110] In this embodiment, the information that the monitored device exceeds the speed is provided to the user so that the user can intervene in the monitored device and correct the motion state of the monitored device.

[0111] In the embodiment of the present invention, by proposing the trajectory vector of the monitoring device, the operating status of the monitored device is generated in real time according to the monitoring data pushed by the detection device, and the device is analyzed based on the trajectory vector of the device to see whether it exceeds the pre-specified vector range, and whether the speed corresponding to the trajectory vector of the device meets the pre-specified speed threshold. The motion state of the device is monitored in real time based on the vector motion data, which improves the monitoring accuracy of the motion state of the device, and enhances the user's understanding of the motion state of the device by using the visualized data of the vector motion.

[0112] Figure 51 is a schematic diagram of the structure of a device monitoring device based on vector coordinates provided by an embodiment of the present invention. The device monitoring device 500 based on vector coordinates may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 510 (for example, one or more processors) and a memory 520, and one or more storage media 530 (for example, one or more mass storage devices) storing application programs 533 or data 532. Among them, the memory 520 and the storage medium 530 may be short-term storage or permanent storage. The program stored in the storage medium 530 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the device monitoring device 500 based on vector coordinates. Furthermore, the processor 510 may be configured to communicate with the storage medium 530 to execute a series of instruction operations in the storage medium 530 on the device monitoring device 500 based on vector coordinates.

[0113] The device monitoring device 500 based on vector coordinates may also include one or more power supplies 540, one or more wired or wireless network interfaces 550, one or more input and output interfaces 560, and / or one or more operating systems 531, such as Windows Serve, Mac OS X, Unix, Linux, Free BSD, etc. It will be appreciated by those skilled in the art that Figure 5 The illustrated structure of the device monitoring apparatus based on vector coordinates does not constitute a limitation on the device monitoring apparatus based on vector coordinates, and may include more or less components than illustrated, or a combination of certain components, or a different arrangement of components.

[0114] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the device monitoring method based on vector coordinates.

[0115] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, 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 foregoing.

[0116] In addition, although each operation is described in a specific order, this should be understood as requiring such operation to be performed in the specific order shown or in a sequential order, or requiring that all illustrated operations should be performed to obtain desired results. Under certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although some specific implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Some features described in the context of a separate embodiment can also be implemented in a single implementation in combination. On the contrary, the various features described in the context of a single implementation can also be implemented in multiple implementations individually or in any suitable sub-combination mode.

[0117] Although the subject matter has been described in language specific to structural features and / or methodological logical actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. On the contrary, the specific features and actions described above are merely example forms of implementing the claims.

Claims

1. A device monitoring method based on vector coordinates, characterized in that: Includes steps: Obtaining N coordinate data of the monitored device, where N is a positive integer greater than 2; Based on the N coordinate data, generate N-1 vector coordinates corresponding to the monitored device and movement speeds corresponding to the N-1 vector coordinates; Determine whether the N-1 vector coordinates deviate from the preset route range; When N-1 of the vector coordinates deviate from the preset route range, route warning information is sent to the preset management port; When the N-1 vector coordinates do not deviate from the preset route range, it is determined whether there is data of the movement speed corresponding to the N-1 vector coordinates exceeding the preset speed threshold; When there is no data exceeding the preset speed threshold, generating visualization data according to the N-1 vector coordinates, and sending the visualization data to the preset management port; When there is data exceeding the preset speed threshold, a speed warning message is sent to the preset management port.

2. The device monitoring method based on vector coordinates according to claim 1, characterized in that: The determining whether the N-1 vector coordinates deviate from the preset route range comprises: Determine whether there is data of the lateral offset of the N-1 vector coordinates exceeding the preset route range; When there is data of lateral deviation exceeding the preset route range, the lateral range of N-1 vector coordinates deviating from the route range is determined; When there is no data of the lateral offset exceeding the preset route range, it is determined whether there is data of the longitudinal offset of the N-1 vector coordinates exceeding the preset route range; When there is data of longitudinal offset exceeding the preset route range, the longitudinal range of N-1 vector coordinates deviating from the route range is determined; When there is no data of the longitudinal offset exceeding the preset route range, it is determined that the N-1 vector coordinates do not deviate from the route range.

3. The device monitoring method based on vector coordinates according to claim 2, characterized in that: Determining the lateral range of the N-1 vector coordinates deviating from the route range includes: Calculate the maximum lateral difference of N-1 vector coordinates from the lateral range; In the lateral range, searching for the lateral range length corresponding to the maximum lateral difference; Based on the lateral range length and the maximum lateral difference, a lateral deviation rate is calculated, and the lateral deviation rate is determined as a deviation state of N-1 of the vector coordinates deviating from the lateral range.

4. The device monitoring method based on vector coordinates according to any one of claims 2 or 3, characterized in that: Determining the longitudinal range of the N-1 vector coordinates deviating from the route range includes: Calculate the maximum longitudinal difference of N-1 vector coordinates from the longitudinal range; In the longitudinal range, searching for the longitudinal range length corresponding to the maximum longitudinal difference; Based on the longitudinal range length and the maximum longitudinal difference, a longitudinal deviation rate is calculated, and the longitudinal deviation rate is determined as a deviation state of N-1 of the vector coordinates deviating from the longitudinal range.

5. The device monitoring method based on vector coordinates according to claim 1, characterized in that: The generating, based on the N coordinate data, N-1 vector coordinates corresponding to the monitored device and the movement speed corresponding to the vector coordinates comprises: According to the collection time corresponding to the N coordinate data, the N coordinate data are subtracted to generate N-1 vector coordinates corresponding to the monitored device; Based on the time sequence, subtract the acquisition time corresponding to the N coordinate data to generate the movement duration corresponding to the N-1 vector coordinates; The movement speeds corresponding to the N-1 vector coordinates are calculated according to the movement durations corresponding to the N-1 vector coordinates.

6. The device monitoring method based on vector coordinates according to claim 1, characterized in that: The obtaining of N coordinate data of the monitored device includes: Based on the preset navigation system and the acquisition cycle, the real-time coordinates of the monitored device are acquired at intervals to obtain N coordinate data of the monitored device.

7. The device monitoring method based on vector coordinates according to claim 1, characterized in that: After generating visualization data according to the N-1 vector coordinates and sending the visualization data to the preset management port, the method further includes: Receive visual adjustment instructions; Based on the visualization adjustment instruction, the route range is modified to obtain a new route range.

8. The device monitoring method based on vector coordinates according to claim 1, characterized in that: Generating visualization data according to the N-1 vector coordinates includes: Based on the time sequence, calculate the angle data between the N-1 vector coordinates to generate a trajectory angle set; Extracting the trajectory angle from the trajectory angle set; Determining whether the trajectory angle is greater than a preset angle threshold; When it is greater than a preset angle threshold, the two vector coordinates corresponding to the trajectory angle are smoothed to obtain two smoothed vector coordinates, and the two smoothed vector coordinates are written into a preset visualization coordinate set; When it is not greater than a preset angle threshold, the two vector coordinates corresponding to the trajectory angle are written into a preset visualization coordinate set, and it is determined whether the trajectory angle set is an empty set; When the set is not empty, re-extracting the trajectory angle in the trajectory angle set; When it is an empty set, visualization data of the corresponding motion trajectory of the monitored device is generated according to the visualization coordinate set.

9. A device monitoring device based on vector coordinates, characterized in that: The device monitoring device based on vector coordinates comprises: a memory and at least one processor, the memory stores instructions, and the memory and the at least one processor are interconnected via a line; The at least one processor calls the instructions in the memory to enable the vector coordinate-based device monitoring device to execute the vector coordinate-based device monitoring method according to any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the device monitoring method based on vector coordinates as described in any one of claims 1 to 8 is implemented.

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