Equipment state determination method and device, nonvolatile storage medium and electronic equipment

Abstract

The invention discloses an equipment state determination method and device, a nonvolatile storage medium and electronic equipment. The method comprises the following steps: establishing an equipment simulation model of the dynamic equipment, and determining an initial vibration threshold value set through the equipment simulation model; collecting vibration data of the moving equipment, and determining whether the moving equipment has a threshold alarm event or not according to the vibration data and the initial vibration threshold value set; according to the vibration data and the initial vibration threshold value set, whether a quick change alarm event exists in the dynamic equipment is determined; according to the change trend of the vibration data, the initial vibration threshold value set and a preset reliability line, determining whether the dynamic equipment has a trend alarm event; and adjusting the initial vibration threshold set according to the threshold alarm event, the quick change alarm event, the trend alarm event and the vibration data of the dynamic equipment to obtain a target vibration threshold set. The technical problem that the running state of the equipment cannot be comprehensively determined due to the fact that the running state of the equipment is detected only through the threshold in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the technical field of Internet of Things, and in particular, to a method and apparatus for determining a device state, a non-volatile storage medium, and an electronic device. Background Art

[0002] Various mechanical equipment used in industrial production processes, such as water pumps, motors, fans, hydraulic presses, etc. During operation, dynamic equipment may experience temperature rise, abnormal vibration, etc. due to the use environment, wear of parts, etc., which may lead to equipment failure, damage, or even accidents.

[0003] In order to improve the reliability and safety of dynamic equipment, it is crucial to carry out preventive maintenance, that is, to detect equipment abnormalities in advance and perform maintenance. Traditional dynamic equipment status determination mostly uses a single static alarm threshold method, which results in an inability to fully determine the operating status of the equipment and poor accuracy.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present application provide a method, apparatus, non-volatile storage medium and electronic device for determining a device status, so as to at least solve the technical problem that the operating status of a device cannot be fully determined due to the prior art only detecting the operating status of the device through a threshold.

[0006] According to one aspect of an embodiment of the present application, a method for determining a device state is provided, including: establishing a device simulation model of a moving device, and determining an initial vibration threshold set through the device simulation model; collecting vibration data of the moving device, and determining whether a threshold alarm event exists for the moving device based on the vibration data and the initial vibration threshold set, wherein the threshold alarm event is used to indicate that the vibration data of the moving device exceeds a threshold in the initial vibration threshold set; determining whether a fast-changing alarm event exists for the moving device based on the vibration data and the initial vibration threshold set, wherein the fast-changing alarm event is used to indicate that the fluctuation of the vibration data of the moving device is abnormal; determining whether a trend alarm event exists for the moving device based on the change trend of the vibration data, the initial vibration threshold set and a preset confidence line, wherein the trend alarm event is used to indicate that the change trend indicator of the vibration data of the moving device is not within the range indicated by the preset confidence line; adjusting the initial vibration threshold set based on the threshold alarm event, the fast-changing alarm event, the trend alarm event and the vibration data of the moving device to obtain a target vibration threshold set; replacing the initial vibration threshold set with the target vibration threshold set, and performing threshold alarm detection, fast-changing alarm detection and trend alarm detection on the moving device based on the target vibration threshold set.

[0007] Optionally, determining whether a fast-changing alarm event occurs in a moving device based on vibration data and an initial vibration threshold set includes: selecting a preset threshold from the initial vibration threshold set; determining a first abnormal data point and a second abnormal data point from the vibration data, wherein both the first abnormal data point and the second abnormal data point are greater than the preset threshold, and the first abnormal data point and the second abnormal data point are two vibration data points collected continuously; determining a deviation value between the first abnormal data point and the second abnormal data point, and determining whether a fast-changing alarm event occurs in the moving device based on the deviation value.

[0008] Optionally, determining whether a fast-changing alarm event exists in the moving device based on the deviation value includes: when the deviation value is not less than a preset deviation value, determining that the moving device has an abnormal vibration behavior; within a preset time period, when the cumulative number of abnormal vibration behaviors of the moving device is not less than a preset number, determining that a fast-changing alarm event exists in the moving device; within a preset time period, when the cumulative number of abnormal vibration behaviors of the moving device is less than a preset number, clearing the cumulative number of abnormal vibration behaviors.

[0009] Optionally, determining whether there is a trend alarm event for the moving device based on the change trend of the vibration data, the initial vibration threshold set and the preset confidence line includes: cleaning the continuously collected vibration data based on the initial vibration threshold to obtain a vibration data sequence, wherein the vibration data sequence includes multiple vibration data points arranged in chronological order of collection time, and the vibration data sequence is a continuously updated sequence; determining a first change trend indicator based on the vibration data sequence, and determining whether there is an abnormality in the vibration data based on the first change trend indicator, wherein the first change trend indicator includes the slope of a fitting curve of the vibration data sequence; determining a first statistical indicator of the vibration data sequence based on the vibration data sequence, the mean and variance of the vibration data sequence, and determining a second statistical indicator based on the inverse sequence of the vibration data sequence, the mean of the inverse sequence and the variance of the inverse sequence; determining a second change trend indicator based on the first statistical indicator and the second statistical indicator, and determining whether there is an abnormality in the vibration data based on the second change trend indicator and the preset confidence line; determining that there is a trend alarm event for the moving device when the first change trend indicator indicates that there is an abnormality in the vibration data and the second change trend indicator and the preset confidence line indicate that there is an abnormality in the vibration data.

[0010] Optionally, determining a second change trend indicator based on the first statistical indicator and the second statistical indicator, and determining whether the vibration data is abnormal based on the second change trend indicator and a preset confidence line includes: determining a first fitting curve of the first statistical indicator, and a second fitting curve of the second statistical indicator; determining the intersection of the first fitting curve and the second fitting curve, wherein the intersection is the second change trend indicator; and determining that the vibration data is abnormal when the intersection is located in the confidence interval indicated by the confidence line.

[0011] Optionally, after determining that the vibration data is abnormal based on the second change trend indicator and the preset confidence line, the method further includes: performing local abnormal factor detection on the vibration data sequence to determine a data mutation point in the vibration data sequence.

[0012] Optionally, adjusting the initial vibration threshold set according to the threshold alarm events, fast-changing alarm events, trend alarm events and vibration data of the dynamic device to obtain the target vibration threshold set includes: determining the alarm accuracy of the threshold alarm events, fast-changing alarm events and trend alarm events; adjusting the initial vibration threshold set according to the alarm accuracy, and continuously determining the alarm accuracy of the threshold alarm events, fast-changing alarm events and trend alarm events during the adjustment process until the alarm accuracy of the threshold alarm events, fast-changing alarm events and trend alarm events are all greater than the preset accuracy threshold, and determining the initial vibration threshold set at this time as the target vibration threshold set.

[0013] According to another aspect of an embodiment of the present application, a device for determining a device state is also provided, including: a first processing module, used to establish a device simulation model of a moving device, and determine an initial vibration threshold set through the device simulation model; a second processing module, used to collect vibration data of the moving device, and determine whether a threshold alarm event exists for the moving device based on the vibration data and the initial vibration threshold set, wherein the threshold alarm event is used to indicate that the vibration data of the moving device exceeds a threshold in the initial vibration threshold set; a third processing module, used to determine whether a fast-changing alarm event exists for the moving device based on the vibration data and the initial vibration threshold set, wherein the fast-changing alarm event is used to indicate fluctuations in the vibration data of the moving device Abnormality; a fourth processing module, used to determine whether there is a trend alarm event for the moving device based on the changing trend of the vibration data, the initial vibration threshold set and the preset confidence line, wherein the trend alarm event is used to indicate that the changing trend index of the vibration data of the moving device is not within the range indicated by the preset confidence line; a fifth processing module, used to adjust the initial vibration threshold set according to the threshold alarm event, fast-changing alarm event, trend alarm event and vibration data of the moving device to obtain a target vibration threshold set; a sixth processing module, used to replace the initial vibration threshold set with the target vibration threshold set, and perform threshold alarm detection, fast-changing alarm detection and trend alarm detection on the moving device based on the target vibration threshold set.

[0014] According to another aspect of an embodiment of the present application, a non-volatile storage medium is provided, in which a program is stored, wherein when the program is running, a device where the non-volatile storage medium is located is controlled to execute a device state determination method.

[0015] According to another aspect of an embodiment of the present application, there is also provided an electronic device, including: a memory and a processor, the processor being configured to run a program stored in the memory, wherein the device status determination method is executed when the program is run.

[0016] According to another aspect of an embodiment of the present application, a computer program product is also provided, including a computer program, and when the computer program is executed by a processor, the device status determination method is implemented.

[0017] In an embodiment of the present application, a device simulation model of a moving device is established, and an initial vibration threshold value set is determined through the device simulation model; vibration data of the moving device is collected, and based on the vibration data and the initial vibration threshold value set, it is determined whether a threshold alarm event exists for the moving device, wherein the threshold alarm event is used to indicate that the vibration data of the moving device exceeds a threshold value in the initial vibration threshold value set; based on the vibration data and the initial vibration threshold value set, it is determined whether a fast-changing alarm event exists for the moving device, wherein the fast-changing alarm event is used to indicate that the fluctuation of the vibration data of the moving device is abnormal; based on the changing trend of the vibration data, the initial vibration threshold value set and a preset confidence line, it is determined whether a trend alarm event exists for the moving device, wherein the trend alarm event is used to indicate that the changing trend index of the vibration data of the moving device is not within the preset The range indicated by the confidence line is within the range indicated by the confidence line; the initial vibration threshold value set is adjusted according to the threshold alarm events, fast-changing alarm events, trend alarm events and vibration data of the dynamic equipment to obtain the target vibration threshold value set; the initial vibration threshold value set is replaced by the target vibration threshold value set, and the threshold alarm detection, fast-changing alarm detection and trend alarm detection are performed on the dynamic equipment according to the target vibration threshold value set. The vibration threshold is determined by establishing a simulation equipment model, and the state of the dynamic equipment is determined by threshold alarm detection, fast-changing alarm detection and trend alarm detection, thereby achieving the purpose of accurately monitoring the state of the equipment, thereby realizing the technical effect of comprehensively determining the operating state of the equipment, and further solving the technical problem that the operating state of the equipment cannot be comprehensively determined due to the fact that the existing technology only detects the operating state of the equipment by threshold. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0019] Figure 1 It is a structural schematic diagram of a computer terminal (mobile device) provided according to an embodiment of the present application;

[0020] Figure 2 It is a flowchart of a method for determining a device state provided in an embodiment of the present application;

[0021] Figure 3 It is a schematic diagram of a process of constructing a simulation model of a dynamic device according to an embodiment of the present application;

[0022] Figure 4is a schematic diagram of a fast-changing alarm event determination process provided according to an embodiment of the present application;

[0023] Figure 5 is a schematic diagram of determining a mutation point according to an embodiment of the present application;

[0024] Figure 6 It is a schematic diagram of an overall process of determining a device status according to an embodiment of the present application;

[0025] Figure 7 It is a structural diagram of a device for determining a device state according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0027] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0028] In order to better understand the embodiments of the present application, the technical terms involved in the embodiments of the present application are explained as follows:

[0029] Simulation Model: The use of computer simulation techniques to simulate real-world systems or processes for testing or optimization.

[0030] Measuring point: In the software, it refers to the measuring instrument used to collect and monitor the status of dynamic equipment in industrial scenarios.

[0031] Mechanical properties: refers to the classification of equipment according to different structures and uses.

[0032] Threshold: Indicates that this value is a critical point. When a parameter exceeds the threshold, a corresponding property will change drastically. The alarm after exceeding the limit is divided into 1 to 4 levels, representing the severity of this drastic change, with 4 being the highest and 1 being the lowest.

[0033] Allowable deviation value: indicates that the deviation between two values ​​is within the allowable range.

[0034] MK test: Mann-Kendall rank test method, mainly a method for mutation test of time series.

[0035] Confidence line: In order to judge whether the trend of a time series is significant, a confidence line or significance level line constructed according to statistical analysis methods is often used to judge the significance of the trend.

[0036] Mutation point: In a sequence or process, when a statistical characteristic (distribution type, distribution parameter) changes at a certain point in time due to systematic factors rather than accidental factors, we call this point in time a change point.

[0037] The realization of dynamic equipment status determination technology requires the use of Internet of Things technology, which can be used for various dynamic equipment, including but not limited to industrial machinery, production line equipment, energy equipment, transportation equipment, etc. Traditional dynamic equipment status determination methods mostly use a unified static alarm threshold method or are based on manual judgment, which has the following problems:

[0038] (1) Insufficient sensitivity: Threshold alarm technology can only detect signal out-of-limit conditions. It may not be able to detect short-term abnormal signals or irregular signal changes in a timely manner.

[0039] (2) Large uncertainty: The setting of threshold values ​​needs to rely on manual experience or test results, so there may be errors or uncertainties, resulting in false alarms or missed alarms.

[0040] (3) Limited scope of application: Threshold alarm technology is usually only applicable to the case of a single monitoring signal. For the monitoring of multiple signals or complex signals, more advanced technologies and algorithms are required.

[0041] (4) Lack of adaptability: The threshold value may vary under different operating conditions and therefore needs to be adjusted in a timely manner, but the threshold alarm technology cannot adapt to the changing situation.

[0042] In order to solve the above problems, relevant solutions are provided in the embodiments of the present application, which are described in detail below.

[0043] According to an embodiment of the present application, a method embodiment of a device status determination method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0044] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 1 FIG. 1 shows a hardware structure block diagram of a computer terminal (or mobile device) for implementing a method for determining a device state. Figure 1 As shown, the computer terminal 10 (or mobile device 10) may include one or more (102a, 102b, ..., 102n are used to illustrate) processors 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0045] It should be noted that the one or more processors 102 and / or other data processing circuits described above may generally be referred to herein as "data processing circuits". The data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuit may be a single independent processing module, or may be incorporated in whole or in part into any of the other components in the computer terminal 10 (or mobile device). As described in the embodiments of the present application, the data processing circuit acts as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0046] The memory 104 can be used to store software programs and modules of application software, such as program instructions / data storage devices corresponding to the device state determination method in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, the above-mentioned device state determination method is realized. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the computer terminal 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0047] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the computer terminal 10. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0048] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 10 (or mobile device).

[0049] In the above operating environment, the present application embodiment provides a method for determining the device status, such as Figure 2 As shown, the method comprises the following steps:

[0050] Step S202: establishing a device simulation model for the moving device, and determining an initial vibration threshold set through the device simulation model.

[0051] Optionally, Figure 3 A schematic diagram of a process for constructing a simulation model of a dynamic device is shown in FIG. Figure 3As shown, the equipment parameter information and process condition data are obtained, including but not limited to the equipment speed, model, residual value rate, test data, operation data, maintenance data, etc. These data form the basis for model construction. Next, the mechanical characteristics stage of the equipment is confirmed, that is, the international vibration classification or enterprise vibration standard of the equipment is identified to ensure the versatility and applicability of the model. Subsequently, the above information is input into the equipment simulation model for training, and the equipment simulation model is constructed to simulate the behavior of the equipment under different working conditions. Finally, the vibration standard, parameter information and process condition data of the dynamic equipment are input into the constructed simulation equipment model to obtain the default vibration thresholds generated by the simulation equipment model. These thresholds will be used for subsequent alarm detection.

[0052] Optionally, the equipment simulation model is used to identify the vibration standards of dynamic equipment (including national vibration standards and enterprise vibration standards for dynamic equipment), and determine an initial vibration threshold set based on the vibration standards, parameter information and process condition data, where the vibration threshold includes four levels.

[0053] Optionally, the equipment simulation model determines corresponding initial vibration thresholds for measuring points of the moving equipment, different installation locations of the measuring points, and flexible or rigid foundations.

[0054] Step S204, collecting vibration data of the moving device, and determining whether there is a threshold alarm event for the moving device based on the vibration data and the initial vibration threshold set, wherein the threshold alarm event is used to indicate that the vibration data of the moving device exceeds a threshold in the initial vibration threshold set.

[0055] Optionally, the vibration data of the moving equipment is collected in real time, and the initial vibration threshold set of the equipment simulation model autonomously identifies whether the current vibration value exceeds the limit, wherein the initial vibration threshold set is determined by the equipment simulation model according to the national vibration standard / enterprise vibration standard. When the vibration value exceeds the threshold in the initial vibration threshold set, the threshold alarm of the corresponding level will be triggered according to how many levels of the four vibration thresholds are exceeded.

[0056] Optionally, when a level 2 threshold alarm or above is triggered, fast-changing alarm detection is performed.

[0057] Step S206 , determining whether there is a fast-changing alarm event for the moving device based on the vibration data and the initial vibration threshold set, wherein the fast-changing alarm event is used to indicate abnormal fluctuation of the vibration data of the moving device.

[0058] In the technical solution provided in step S206, determining whether a fast-changing alarm event occurs in a moving device based on vibration data and an initial vibration threshold set includes: selecting a preset threshold from the initial vibration threshold set; determining a first abnormal data point and a second abnormal data point from the vibration data, wherein both the first abnormal data point and the second abnormal data point are greater than the preset threshold, and the first abnormal data point and the second abnormal data point are two vibration data points collected continuously; determining a deviation value between the first abnormal data point and the second abnormal data point, and determining whether a fast-changing alarm event occurs in the moving device based on the deviation value.

[0059] Optionally, determining whether a fast-changing alarm event exists in the moving device based on the deviation value includes: when the deviation value is not less than a preset deviation value, determining that the moving device has an abnormal vibration behavior; within a preset time period, when the cumulative number of abnormal vibration behaviors of the moving device is not less than a preset number, determining that a fast-changing alarm event exists in the moving device; within a preset time period, when the cumulative number of abnormal vibration behaviors of the moving device is less than a preset number, clearing the cumulative number of abnormal vibration behaviors.

[0060] Optionally, Figure 4 The process of determining the fast-changing alarm event is shown in FIG. Figure 4 As shown in the figure, the real-time vibration data uploaded by the sensor is combined with the positive deviation formula to identify whether the equipment has a fast-changing alarm. The positive deviation formula is:

[0061] x% = (v2-v1) / Q*100

[0062] Wherein, x is the deviation value obtained, Q is the standard index value, i.e., the preset threshold value. In the embodiment of the present application, the secondary vibration threshold value is selected as the preset threshold value, (v1, v2) are the vibration index values ​​before and after, i.e., the first abnormal data point and the second abnormal data point. When both the first abnormal data point and the second abnormal data point exceed the preset threshold value and x%>=y%, the device is marked as a vibration abnormality, where y is the preset deviation value, and adaptive adjustment through the simulation model is supported. When the cumulative number of vibration abnormalities does not reach the preset number of times and is interrupted, the number of times is cleared and accumulated again. When the cumulative number of vibration abnormalities reaches the preset number of times, it is determined that there is a fast-changing alarm event in the dynamic device.

[0063] Specifically, the simulation model, as a virtual mapping of the equipment under different working conditions and environmental conditions, dynamically generates vibration thresholds that match the actual operating conditions by inputting parameters that reflect the current state of the equipment (such as temperature, pressure, speed, etc.). When the system detects continuous changes or abnormal trends in vibration data, this information is fed back to the simulation model, and the trained simulation model is analyzed to automatically identify whether these changes are part of normal aging, wear, or working condition adjustment of the equipment. When the model determines that the current preset deviation value y is no longer suitable for the current equipment state, the adjusted deviation value is output. For example, if the equipment has been operating stably at a high vibration level for a long time and has not failed, the preset deviation value y may be gradually relaxed to reduce false alarms; conversely, if an increasing trend in equipment vibration is detected, the preset deviation value y may be tightened to identify potential problems earlier. This adaptive adjustment mechanism ensures the sensitivity and accuracy of the early warning system, enabling it to more accurately adapt to the real state of the equipment changing over time and improve the reliability of maintenance decisions. Through continuous learning and optimization of the simulation model, the adjustment of the preset deviation value y can automatically adapt to the operating environment and health status of the equipment, reducing the need for manual intervention and improving the intelligence level of the early warning system.

[0064] Step S208, determining whether there is a trend alarm event for the moving device based on the change trend of the vibration data, the initial vibration threshold set and the preset confidence line, wherein the trend alarm event is used to indicate that the change trend index of the vibration data of the moving device is not within the range indicated by the preset confidence line.

[0065] Optionally, the vibration data [d1, d2, ..., dn] include vibration-related data such as the pressure on the moving device and the temperature of the moving device.

[0066] In the technical solution provided in step S208, determining whether there is a trend alarm event for the moving device based on the change trend of the vibration data, the initial vibration threshold set and the preset confidence line includes: cleaning the continuously collected vibration data based on the initial vibration threshold to obtain a vibration data sequence, wherein the vibration data sequence includes a plurality of vibration data points arranged in chronological order of collection time, and the vibration data sequence is a continuously updated sequence; determining a first change trend indicator based on the vibration data sequence, and determining whether there is an abnormality in the vibration data based on the first change trend indicator, wherein the first change trend indicator includes the slope of a fitting curve of the vibration data sequence; determining a first statistical indicator of the vibration data sequence based on the vibration data sequence, the mean and variance of the vibration data sequence, and determining a second statistical indicator based on the inverse sequence of the vibration data sequence, the mean of the inverse sequence and the variance of the inverse sequence; determining a second change trend indicator based on the first statistical indicator and the second statistical indicator, and determining whether there is an abnormality in the vibration data based on the second change trend indicator and the preset confidence line; determining whether there is a trend alarm event for the moving device when the first change trend indicator indicates that there is an abnormality in the vibration data and the second change trend indicator and the preset confidence line indicate that there is an abnormality in the vibration data.

[0067] Optionally, the continuously collected vibration data is cleaned according to the initial vibration threshold to obtain the vibration data sequence, including cleaning the data according to the vibration threshold by using a random forest algorithm, and converting the cleaned data [y1, y2, ..., y n ] as a vibration data sequence and scattered on a plane coordinate system.

[0068] Optionally, determining the first change trend indicator according to the vibration data sequence includes:

[0069] According to the least squares formula, calculate the slope b (i.e. the first trend indicator):

[0070]

[0071] in, y is the vibration data, x is the time when the data was collected, i is the value of the i-th vibration, the value range of i is from 1 to n, y i is the value of the i-th vibration data, is the average value of the data collection time, is the average value of the vibration data.

[0072] Optionally, the first change trend indicator is used to represent the overall upward or downward trend of the data, and determining whether there is an abnormality in the vibration data based on the first change trend indicator includes: when the first change trend indicator is negative, determining that there is no abnormality in the vibration data, and when the first change trend indicator is positive, determining that there is an abnormality in the vibration data. It is necessary to further combine the second statistical indicator to determine whether there is a trend alarm event in the dynamic equipment.

[0073] Optionally, determining a second change trend indicator based on the first statistical indicator and the second statistical indicator, and determining whether the vibration data is abnormal based on the second change trend indicator and a preset confidence line includes: determining a first fitting curve of the first statistical indicator, and a second fitting curve of the second statistical indicator; determining the intersection of the first fitting curve and the second fitting curve, wherein the intersection is the second change trend indicator; and determining that the vibration data is abnormal when the intersection is located in the confidence interval indicated by the confidence line.

[0074] Optionally, determining a first fitting curve of the first statistical indicator includes: n ] as a time series, construct a set of ordered sequences r i ,i ranges from 1 to n:

[0075]

[0076] Among them, S k It represents the time series data [y1, y2, ..., y k ]’s cumulative sum.

[0077] Using the MK test method, the statistic is defined as:

[0078]

[0079] Among them, E(s k ) is the mean of the cumulative sum, var(s k ) is the variance of the cumulative sum. UF k is the standard normal distribution statistic, i.e. the first statistic indicator. Apply this method to the reverse sequence and repeat the above calculation process, and multiply the calculated value by -1 to obtain the reverse sequence statistic UB k , i.e., the second statistical indicator, fitting the curves of the first statistical indicator and the second statistical indicator with respect to time, i.e., the first fitting curve and the second fitting curve, and determining the intersection of the first fitting curve and the second fitting curve. When the intersection is in the confidence interval indicated by the confidence line, it is determined that the vibration data is abnormal, wherein the value of the confidence line is obtained by calling a preset interface.

[0080] Optionally, after determining that the vibration data is abnormal based on the second change trend indicator and the preset confidence line, the method further includes: performing local abnormal factor detection on the vibration data sequence to determine a data mutation point in the vibration data sequence.

[0081] Optionally, when the first change trend indicator indicates that the vibration data is abnormal and the second change trend indicator and the preset confidence line indicate that the vibration data is abnormal, a local abnormal factor detection algorithm is performed on the intersection of the first fitting curve and the second fitting curve to find and confirm [y1, y2, ..., y n ] in the data mutation point, Figure 5 A schematic diagram of determining a mutation point is shown.

[0082] Step S210, adjusting the initial vibration threshold value set according to the threshold alarm event, the fast-changing alarm event, the trend alarm event and the vibration data of the dynamic device to obtain the target vibration threshold value set.

[0083] In the technical solution provided in step S210, the initial vibration threshold value set is adjusted according to the threshold alarm events, fast-changing alarm events, trend alarm events and vibration data of the dynamic equipment to obtain the target vibration threshold value set, including: determining the alarm accuracy of the threshold alarm events, fast-changing alarm events and trend alarm events; adjusting the initial vibration threshold value set according to the alarm accuracy, and continuously determining the alarm accuracy of the threshold alarm events, fast-changing alarm events and trend alarm events during the adjustment process, until the alarm accuracy of the threshold alarm events, fast-changing alarm events and trend alarm events are all greater than the preset accuracy threshold, and determining the initial vibration threshold value set at this time as the target vibration threshold value set.

[0084] Optionally, Figure 6 An overall flow chart for determining a device state is shown, such as Figure 6As shown, threshold alarm is performed based on the simulation model, fast-changing alarm is performed based on the preset model, and trend alarm is performed based on the trend statistical model. The intelligent model receives these inputs and unifies the inputs in combination with the alarm conclusions for comprehensive analysis. By combining the simulation model with the vibration waveform of the current moving equipment, the initial mechanism inference of the current moving equipment is performed. Combining the alarm conclusions and the knowledge base and case library stored in the intelligent model, the conclusion is given after checking and inference to determine whether to output the final alarm confirmation and whether to adjust the vibration threshold set. At the same time, after the intelligent model gives the alarm conclusion, manual confirmation feedback is performed, and the feedback results are input into the intelligent model as a training set for training. The intelligent module adjusts the thresholds and preset values ​​in the simulation model and the preset model based on the threshold dynamic adaptive technology of historical trends. The design of the intelligent model takes into account the adaptive values ​​in the simulation model and the preset model, and can dynamically adjust the threshold according to the actual operating status of the equipment to improve the accuracy of the alarm. Specifically, the intelligent model first evaluates the accuracy of threshold alarms, fast-changing alarms, and trend alarms, and then adjusts the initial vibration threshold set according to the alarm accuracy until the accuracy of all alarm events reaches the preset accuracy threshold. The vibration threshold set at this time is the "target vibration threshold set" and is used to replace the initial set for more accurate alarm detection. This process enables the system to self-optimize according to the real-time status of the equipment, reduce false alarms and missed alarms, and improve the efficiency and accuracy of equipment maintenance.

[0085] Step S212: Replace the initial vibration threshold set with the target vibration threshold set, and perform threshold alarm detection, fast-changing alarm detection and trend alarm detection on the moving device according to the target vibration threshold set.

[0086] Specifically, the intelligent model receives conclusions from threshold alarms, fast-changing alarms, and trend alarms, which are generated based on the current vibration level of the equipment, short-term changes in vibration values, and changes in long-term vibration trends. The intelligent model first uses the built-in deep learning network and statistical analysis tools, combined with the historical data in the equipment knowledge base and case library, to conduct in-depth anomaly and correlation analysis on the alarm conclusions to identify potential abnormal patterns and subtle changes in equipment status. The intelligent model is based on the evaluation results of the alarm conclusions, changes in equipment operating conditions, historical operating trends, and current health status. The model will continuously monitor the alarm accuracy, and based on the feedback of the accuracy, gradually optimize the vibration threshold set, and replace the initial vibration threshold set with the dynamically optimized target vibration threshold set.

[0087] Through the above steps, it is possible to quickly identify trend change points and realize comprehensive equipment status determination by combining dynamic thresholds with trends. Compared with the prior art, the equipment simulation model of the embodiment of the present application combines international standards and operating condition inputs to dynamically generate vibration thresholds; secondly, by effectively filtering abnormal or irregular signal data, the warning accuracy of the model is enhanced; at the same time, the inventive method has strong versatility and universality, and can perform early warning identification and classification on most dynamic equipment. Based on the mechanical characteristics of different dynamic equipment, according to international standards and input operating condition changes, a self-adjustable dynamic threshold method is provided. At the same time, according to trend anomaly monitoring algorithms such as isolated forests and MK tests, abnormal data can be effectively filtered, and trend change points can be quickly identified, realizing comprehensive dynamic equipment status determination and alarm by combining dynamic thresholds with trends.

[0088] The present application provides a device for determining a device state. Figure 7 is a schematic diagram of the structure of the device, such as Figure 7 As shown, the device includes: a first processing module 70, which is used to establish an equipment simulation model of the moving equipment and determine the initial vibration threshold set through the equipment simulation model; a second processing module 72, which is used to collect vibration data of the moving equipment and determine whether there is a threshold alarm event for the moving equipment based on the vibration data and the initial vibration threshold set, wherein the threshold alarm event is used to indicate that the vibration data of the moving equipment exceeds the threshold in the initial vibration threshold set; a third processing module 74, which is used to determine whether there is a fast-changing alarm event for the moving equipment based on the vibration data and the initial vibration threshold set, wherein the fast-changing alarm event is used to indicate that the vibration data of the moving equipment has an abnormal fluctuation; a fourth processing module 76, Used to determine whether there is a trend alarm event for the moving device based on the changing trend of the vibration data, the initial vibration threshold set and the preset confidence line, wherein the trend alarm event is used to indicate that the changing trend index of the vibration data of the moving device is not within the range indicated by the preset confidence line; the fifth processing module 78 is used to adjust the initial vibration threshold set according to the threshold alarm event, fast-changing alarm event, trend alarm event and vibration data of the moving device to obtain the target vibration threshold set; the sixth processing module 710 is used to replace the initial vibration threshold set with the target vibration threshold set, and perform threshold alarm detection, fast-changing alarm detection and trend alarm detection on the moving device based on the target vibration threshold set.

[0089] In some embodiments of the present application, the third processing module 74 determines whether a fast-changing alarm event occurs in the moving device based on the vibration data and the initial vibration threshold set, including: selecting a preset threshold from the initial vibration threshold set; determining a first abnormal data point and a second abnormal data point from the vibration data, wherein the first abnormal data point and the second abnormal data point are both greater than the preset threshold, and the first abnormal data point and the second abnormal data point are two vibration data points collected continuously; determining a deviation value between the first abnormal data point and the second abnormal data point, and determining whether a fast-changing alarm event occurs in the moving device based on the deviation value.

[0090] In some embodiments of the present application, the third processing module 74 determines whether there is a fast-changing alarm event in the moving device based on the deviation value, including: when the deviation value is not less than the preset deviation value, determining that the moving device has an abnormal vibration behavior; within a preset time period, when the cumulative number of abnormal vibration behaviors of the moving device is not less than the preset number, determining that there is a fast-changing alarm event in the moving device; within the preset time period, when the cumulative number of abnormal vibration behaviors of the moving device is less than the preset number, clearing the cumulative number of abnormal vibration behaviors.

[0091] In some embodiments of the present application, the fourth processing module 76 determines whether there is a trend alarm event for the dynamic device based on the change trend of the vibration data, the initial vibration threshold set and the preset confidence line, including: cleaning the continuously collected vibration data according to the initial vibration threshold to obtain a vibration data sequence, wherein the vibration data sequence includes multiple vibration data points arranged in chronological order of collection time, and the vibration data sequence is a continuously updated sequence; determining a first change trend indicator according to the vibration data sequence, and determining whether there is an abnormality in the vibration data according to the first change trend indicator, wherein the first change trend indicator includes the slope of the fitting curve of the vibration data sequence; determining a first statistical indicator of the vibration data sequence according to the vibration data sequence, the mean and variance of the vibration data sequence, and determining a second statistical indicator according to the inverse sequence of the vibration data sequence, the mean of the inverse sequence and the variance of the inverse sequence; determining a second change trend indicator according to the first statistical indicator and the second statistical indicator, and determining whether there is an abnormality in the vibration data according to the second change trend indicator and the preset confidence line; determining that there is a trend alarm event for the dynamic device when the first change trend indicator indicates that there is an abnormality in the vibration data and the second change trend indicator and the preset confidence line indicate that there is an abnormality in the vibration data.

[0092] In some embodiments of the present application, the fourth processing module 76 determines the second change trend indicator based on the first statistical indicator and the second statistical indicator, and determines whether the vibration data is abnormal based on the second change trend indicator and the preset confidence line, including: determining a first fitting curve of the first statistical indicator, and a second fitting curve of the second statistical indicator; determining the intersection of the first fitting curve and the second fitting curve, wherein the intersection is the second change trend indicator; and when the intersection is located in the confidence interval indicated by the confidence line, determining that the vibration data is abnormal.

[0093] In some embodiments of the present application, after the fourth processing module 76 determines that the vibration data is abnormal based on the second change trend indicator and the preset confidence line, the method further includes: performing local abnormal factor detection on the vibration data sequence to determine the data mutation point in the vibration data sequence.

[0094] In some embodiments of the present application, the fifth processing module 78 adjusts the initial vibration threshold set according to the threshold alarm events, fast-changing alarm events, trend alarm events and vibration data of the dynamic device to obtain the target vibration threshold set, including: determining the alarm accuracy of the threshold alarm events, fast-changing alarm events and trend alarm events; adjusting the initial vibration threshold set according to the alarm accuracy, and continuously determining the alarm accuracy of the threshold alarm events, fast-changing alarm events and trend alarm events during the adjustment process, until the alarm accuracy of the threshold alarm events, fast-changing alarm events and trend alarm events are all greater than the preset accuracy threshold, and determining the initial vibration threshold set at this time as the target vibration threshold set.

[0095] It should be noted that the various modules in the above-mentioned device status determination device can be program modules (for example, a set of program instructions that implement a certain specific function) or hardware modules. For the latter, it can be expressed in the following forms, but is not limited to this: the expression form of each of the above-mentioned modules is a processor, or the functions of each of the above-mentioned modules are implemented by a processor.

[0096] The embodiment of the present application provides a non-volatile storage medium, in which a program is stored, wherein when the program is running, the device where the non-volatile storage medium is located is controlled to execute the following device status determination method: establish a device simulation model of the moving device, and determine an initial vibration threshold set through the device simulation model; collect vibration data of the moving device, and determine whether there is a threshold alarm event for the moving device based on the vibration data and the initial vibration threshold set, wherein the threshold alarm event is used to indicate that the vibration data of the moving device exceeds a threshold in the initial vibration threshold set; determine whether there is a fast-changing alarm event for the moving device based on the vibration data and the initial vibration threshold set, wherein the fast-changing alarm event The change alarm event is used to indicate the abnormal fluctuation of the vibration data of the moving equipment; according to the change trend of the vibration data, the initial vibration threshold set and the preset confidence line, it is determined whether there is a trend alarm event for the moving equipment, wherein the trend alarm event is used to indicate that the change trend index of the vibration data of the moving equipment is not within the range indicated by the preset confidence line; the initial vibration threshold set is adjusted according to the threshold alarm event, fast change alarm event, trend alarm event and vibration data of the moving equipment to obtain the target vibration threshold set; the initial vibration threshold set is replaced with the target vibration threshold set, and the threshold alarm detection, fast change alarm detection and trend alarm detection are performed on the moving equipment according to the target vibration threshold set.

[0097] An embodiment of the present application provides an electronic device, including: a memory and a processor, the processor is used to run a program stored in the memory, wherein the following device status determination method is executed when the program is run: establishing a device simulation model of a moving device, and determining an initial vibration threshold set through the device simulation model; collecting vibration data of the moving device, and determining whether there is a threshold alarm event for the moving device based on the vibration data and the initial vibration threshold set, wherein the threshold alarm event is used to indicate that the vibration data of the moving device exceeds the threshold in the initial vibration threshold set; determining whether there is a fast-changing alarm event for the moving device based on the vibration data and the initial vibration threshold set, wherein the fast-changing alarm event is used to indicate that the fluctuation of the vibration data of the moving device is abnormal; determining whether there is a trend alarm event for the moving device based on the change trend of the vibration data, the initial vibration threshold set and a preset confidence line, wherein the trend alarm event is used to indicate that the change trend indicator of the vibration data of the moving device is not within the range indicated by the preset confidence line; adjusting the initial vibration threshold set based on the threshold alarm event, the fast-changing alarm event, the trend alarm event and the vibration data of the moving device to obtain a target vibration threshold set; replacing the initial vibration threshold set with the target vibration threshold set, and performing threshold alarm detection, fast-changing alarm detection and trend alarm detection on the moving device based on the target vibration threshold set.

[0098] The embodiment of the present application provides a computer program product, including a computer program, which implements the following device status determination method when executed by a processor: establish a device simulation model of a moving device, and determine an initial vibration threshold set through the device simulation model; collect vibration data of the moving device, and determine whether there is a threshold alarm event for the moving device based on the vibration data and the initial vibration threshold set, wherein the threshold alarm event is used to indicate that the vibration data of the moving device exceeds the threshold in the initial vibration threshold set; determine whether there is a fast-changing alarm event for the moving device based on the vibration data and the initial vibration threshold set, wherein the fast-changing alarm event is used to indicate that the fluctuation of the vibration data of the moving device is abnormal; determine whether there is a trend alarm event for the moving device based on the change trend of the vibration data, the initial vibration threshold set and a preset confidence line, wherein the trend alarm event is used to indicate that the change trend indicator of the vibration data of the moving device is not within the range indicated by the preset confidence line; adjust the initial vibration threshold set based on the threshold alarm event, the fast-changing alarm event, the trend alarm event and the vibration data of the moving device to obtain a target vibration threshold set; replace the initial vibration threshold set with the target vibration threshold set, and perform threshold alarm detection, fast-changing alarm detection and trend alarm detection on the moving device based on the target vibration threshold set.

[0099] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0100] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0101] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0102] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0103] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the relevant technology or all or part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk, etc. Various media that can store program codes.

[0104] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for determining a device state, characterized in that: include: Establishing a device simulation model of the moving device, and determining an initial vibration threshold set through the device simulation model; Collecting vibration data of the moving device, and determining whether a threshold alarm event occurs for the moving device based on the vibration data and the initial vibration threshold set, wherein the threshold alarm event is used to indicate that the vibration data of the moving device exceeds a threshold in the initial vibration threshold set; Determining whether there is a fast-changing alarm event for the moving device according to the vibration data and the initial vibration threshold set, wherein the fast-changing alarm event is used to indicate abnormal fluctuation of the vibration data of the moving device; Determine whether there is a trend alarm event for the moving device according to the change trend of the vibration data, the initial vibration threshold set and the preset confidence line, wherein the trend alarm event is used to indicate that the change trend index of the vibration data of the moving device is not within the range indicated by the preset confidence line; Adjusting the initial vibration threshold value set according to the threshold alarm event, the fast-changing alarm event, the trend alarm event and the vibration data of the moving device to obtain a target vibration threshold value set; The initial vibration threshold set is replaced by the target vibration threshold set, and threshold alarm detection, fast-changing alarm detection and trend alarm detection are performed on the moving device according to the target vibration threshold set.

2. The device status determination method according to claim 1, characterized in that: Determining whether the moving device has a fast-changing alarm event according to the vibration data and the initial vibration threshold set includes: Selecting a preset threshold from the initial vibration threshold set; Determine a first abnormal data point and a second abnormal data point from the vibration data, wherein the first abnormal data point and the second abnormal data point are both greater than the preset threshold, and the first abnormal data point and the second abnormal data point are two vibration data points collected continuously; A deviation value between the first abnormal data point and the second abnormal data point is determined, and whether a fast-changing alarm event occurs for the moving device is determined based on the deviation value.

3. The device status determination method according to claim 2, characterized in that: Determining whether the moving device has a fast-changing alarm event according to the deviation value includes: When the deviation value is not less than a preset deviation value, determining that the moving device has an abnormal vibration behavior; When the cumulative number of abnormal vibration behaviors of the moving device is not less than a preset number within a preset time period, it is determined that a fast-changing alarm event occurs in the moving device; In the preset time period, when the accumulated number of abnormal vibration behaviors of the moving device is less than the preset number, the accumulated number of abnormal vibration behaviors is cleared.

4. The device status determination method according to claim 1, characterized in that: Determining whether there is a trend alarm event for the moving device based on the change trend of the vibration data, the initial vibration threshold set and the preset confidence line includes: Cleaning the continuously collected vibration data according to the initial vibration threshold to obtain a vibration data sequence, wherein the vibration data sequence includes a plurality of vibration data points arranged in chronological order of collection time, and the vibration data sequence is a continuously updated sequence; Determine a first change trend indicator according to the vibration data sequence, and determine whether the vibration data is abnormal according to the first change trend indicator, wherein the first change trend indicator includes a slope of a fitting curve of the vibration data sequence; Determine a first statistical indicator of the vibration data sequence according to the vibration data sequence, the mean and the variance of the vibration data sequence, and determine a second statistical indicator according to an inverse sequence of the vibration data sequence, the mean of the inverse sequence and the variance of the inverse sequence; Determine a second change trend indicator according to the first statistical indicator and the second statistical indicator, and determine whether the vibration data is abnormal according to the second change trend indicator and the preset confidence line; When the first change trend indicator indicates that the vibration data is abnormal and the second change trend indicator and the preset confidence line indicate that the vibration data is abnormal, it is determined that a trend alarm event exists in the moving device.

5. The device status determination method according to claim 4, characterized in that: Determining a second change trend indicator according to the first statistical indicator and the second statistical indicator, and determining whether the vibration data is abnormal according to the second change trend indicator and the preset confidence line includes: Determine a first fitting curve of the first statistical indicator and a second fitting curve of the second statistical indicator; Determine an intersection point of the first fitting curve and the second fitting curve, wherein the intersection point is the second change trend indicator; When the intersection point is located in the confidence interval indicated by the confidence line, it is determined that an abnormality exists in the vibration data.

6. The device status determination method according to claim 4, characterized in that: After determining that the vibration data is abnormal according to the second change trend indicator and the preset confidence line, the method further includes: A local abnormal factor detection is performed on the vibration data sequence to determine a data mutation point in the vibration data sequence.

7. The device status determination method according to claim 1, characterized in that: The initial vibration threshold set is adjusted according to the threshold alarm event, the fast-changing alarm event, the trend alarm event and the vibration data of the moving device to obtain a target vibration threshold set, including: Determine the alarm accuracy of each of the threshold alarm event, the fast-changing alarm event, and the trend alarm event; The initial vibration threshold set is adjusted according to the alarm accuracy, and the alarm accuracy of the threshold alarm event, the fast-changing alarm event and the trend alarm event are continuously determined during the adjustment process until the alarm accuracy of the threshold alarm event, the fast-changing alarm event and the trend alarm event are all greater than a preset accuracy threshold, and the initial vibration threshold set at this time is determined to be the target vibration threshold set.

8. A device for determining a device state, characterized in that: include: A first processing module is used to establish a device simulation model of the moving device and determine an initial vibration threshold set through the device simulation model; a second processing module, configured to collect vibration data of the moving device, and determine whether a threshold alarm event occurs for the moving device based on the vibration data and the initial vibration threshold set, wherein the threshold alarm event is used to indicate that the vibration data of the moving device exceeds a threshold in the initial vibration threshold set; A third processing module is used to determine whether there is a fast-changing alarm event for the moving device based on the vibration data and the initial vibration threshold set, wherein the fast-changing alarm event is used to indicate abnormal fluctuation of the vibration data of the moving device; a fourth processing module, configured to determine whether a trend alarm event exists for the moving device according to the change trend of the vibration data, the initial vibration threshold set and a preset confidence line, wherein the trend alarm event is used to indicate that the change trend index of the vibration data of the moving device is not within the range indicated by the preset confidence line; A fifth processing module, configured to adjust the initial vibration threshold value set according to the threshold alarm event, the fast-changing alarm event, the trend alarm event and the vibration data of the moving device to obtain a target vibration threshold value set; The sixth processing module is used to replace the initial vibration threshold set with the target vibration threshold set, and perform threshold alarm detection, fast-changing alarm detection and trend alarm detection on the moving device according to the target vibration threshold set.

9. A non-volatile storage medium, characterized in that: The non-volatile storage medium stores a program, wherein when the program is executed, the device where the non-volatile storage medium is located is controlled to execute the device status determination method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: include: A memory and a processor, wherein the processor is used to run a program stored in the memory, wherein the device status determination method according to any one of claims 1 to 7 is executed when the program is run.

11. A computer program product, characterized in that The invention comprises a computer program, which implements the device state determination method according to any one of claims 1 to 7 when being executed by a processor.

Images