Equipment operation status monitoring methods, devices, air conditioning units, equipment and media

Abstract

This application relates to a method, apparatus, air conditioning unit, equipment, and medium for monitoring the operating status of equipment. The method includes: monitoring abnormal operating parameters of a target device based on the current abnormal range and determining the duration corresponding to the abnormal operating parameters; determining a lifespan conversion factor corresponding to the abnormal operating parameters based on the duration corresponding to the abnormal operating parameters; updating the expected lifespan of the target device based on the lifespan conversion factor; and adjusting the abnormal range corresponding to the abnormal operating parameters based on the updated expected lifespan of the target device, so as to continue monitoring the abnormal operating parameters of the target device based on the adjusted abnormal range. This application predicts the expected lifespan of the target device and dynamically adjusts the abnormal range using the expected lifespan, making the abnormal range more closely match the actual operating status of the target device, and synchronizing the time of anomaly detection with the time when the device actually experiences an anomaly.

Description

Technical Field

[0001] This application relates to the field of equipment monitoring technology, and in particular to a method, device, air conditioning unit, equipment and medium for monitoring equipment operating status. Background Technology

[0002] The correlation between abnormal operating parameters and equipment lifespan is widely recognized. Taking air conditioning equipment as an example, if key operating parameters such as high-pressure side pressure, low-pressure side pressure, and exhaust temperature are in an unsuitable state for a long period, it will lead to problems such as accelerated compressor wear and increased risk of refrigerant leakage, resulting in the actual lifespan of the air conditioner being significantly shorter than its design lifespan.

[0003] While those skilled in the art recognize that abnormal operating parameters negatively impact the actual lifespan of equipment, existing technologies monitor these parameters based on static thresholds and issue alarms when abnormalities are detected, allowing users or maintenance personnel to perform maintenance and prevent further damage. However, during the research of this application, it was found that monitoring the equipment's operating status based on static thresholds is largely ineffective in slowing down the equipment's lifespan decline. This is because as equipment ages, the detection of abnormal operating parameters lags behind the actual occurrence of abnormalities, resulting in a delay in equipment maintenance. This delay in maintenance further accelerates the equipment's lifespan decline. Summary of the Invention

[0004] This application provides a method, device, air conditioning unit, equipment, and medium for monitoring equipment operating status, in order to solve the problem that monitoring equipment operating status based on static thresholds has little effect on delaying the process of equipment lifespan degradation.

[0005] To address the aforementioned technical problems, the technical solution of this application is provided through the following embodiments:

[0006] This application provides a method for monitoring the operating status of a device, comprising: monitoring abnormal operating parameters of a target device based on the current abnormal range and determining the duration corresponding to the abnormal operating parameters; determining a lifespan conversion factor corresponding to the abnormal operating parameters based on the duration corresponding to the abnormal operating parameters of the target device; updating the expected lifespan of the target device based on the lifespan conversion factor corresponding to the abnormal operating parameters; and adjusting the abnormal range corresponding to the abnormal operating parameters based on the updated expected lifespan of the target device, so as to continue monitoring the abnormal operating parameters of the target device based on the adjusted abnormal range.

[0007] The step of monitoring abnormal operating parameters of the target device based on the current abnormal range and determining the duration of the abnormal operating parameters includes: for each preset operating parameter, monitoring abnormal values ​​of the operating parameter according to the current abnormal range of the operating parameter, and determining the duration of the abnormal value when the abnormal value is detected to be converted to a normal value; wherein, the operating parameter is determined to be the abnormal operating parameter and the duration of the abnormal value is determined to be the duration of the abnormal operating parameter; or, every preset time period, obtaining the duration of each abnormal value of the operating parameter occurring in the current time period; determining the operating parameter as the abnormal operating parameter, and determining the duration of the abnormal operating parameter according to the duration of each abnormal value.

[0008] The step of determining the lifetime conversion factor corresponding to the abnormal operating parameter based on the duration of the abnormal operating parameter of the target device includes: using a pre-trained lifetime prediction model to determine the lifetime conversion factor corresponding to the abnormal operating parameter based on the duration of the abnormal operating parameter; or, determining the lifetime conversion factor corresponding to the abnormal operating parameter based on the degree of influence mapped by the duration of the abnormal operating parameter.

[0009] Before determining the lifetime conversion factor corresponding to the abnormal operating parameter based on the impact level mapped by the duration of the abnormal operating parameter, the method further includes: acquiring historical operating data of other devices of the same type as the target device; using a pre-trained lifetime mapping model, determining multiple lifetime conversion factors corresponding to the abnormal operating parameter and a correspondence table of duration ranges corresponding to each lifetime conversion factor based on the historical operating data; wherein each duration range maps to an impact level.

[0010] The step of updating the expected service life of the target device based on the service life conversion factor corresponding to the abnormal operating parameters includes: obtaining the most recently updated expected service life of the target device and obtaining the service life decay rate corresponding to the target device; and updating the expected service life of the target device based on the most recently updated expected service life of the target device, the service life decay rate corresponding to the target device, and the service life conversion factor corresponding to the abnormal operating parameters.

[0011] The step of adjusting the abnormal range of the abnormal operating parameters according to the updated expected service life of the target device includes: obtaining the design service life of the target device; determining the service life utilization rate according to the design service life of the target device and the updated expected service life of the target device; and adjusting the current abnormal range of the abnormal operating parameters according to the correction parameter corresponding to the service life utilization rate.

[0012] This application embodiment also provides a device for monitoring the operating status of an equipment, including: a monitoring module, configured to monitor abnormal operating parameters of a target equipment based on the current abnormal range and determine the duration corresponding to the abnormal operating parameters; a determining module, configured to determine a lifespan conversion factor corresponding to the abnormal operating parameters based on the duration corresponding to the abnormal operating parameters of the target equipment; an updating module, configured to update the expected lifespan of the target equipment based on the lifespan conversion factor corresponding to the abnormal operating parameters; and an adjusting module, configured to adjust the abnormal range corresponding to the abnormal operating parameters based on the updated expected lifespan of the target equipment, so as to continue monitoring the abnormal operating parameters of the target equipment based on the adjusted abnormal range.

[0013] This application also provides an air conditioning unit, wherein the air conditioning unit applies the equipment operation status monitoring method described in any of the above claims.

[0014] This application embodiment also provides a device for monitoring device operation status, including: at least one communication interface; at least one bus connected to the at least one communication interface; at least one processor connected to the at least one bus; and at least one memory connected to the at least one bus, wherein the processor is configured to execute a device life prediction program stored in the memory to implement the device operation status monitoring method described in any of the above claims.

[0015] This application also provides a computer-readable storage medium storing computer-executable instructions, which are executed to implement the device operation status monitoring method described in any of the above claims.

[0016] Compared with the prior art, the technical solution provided in this application has the following advantages: The method provided in this application can monitor the abnormal operating parameters of the target device based on the current abnormal range and determine the duration corresponding to the abnormal operating parameters; determine the lifespan conversion factor corresponding to the abnormal operating parameters based on the duration corresponding to the abnormal operating parameters of the target device; update the expected lifespan of the target device based on the lifespan conversion factor corresponding to the abnormal operating parameters; and adjust the abnormal range corresponding to the abnormal operating parameters based on the updated expected lifespan of the target device, so as to continue monitoring the abnormal operating parameters of the target device based on the adjusted abnormal range. Compared with the method of monitoring abnormal operating parameters with a fixed abnormal range, this application embodiment can predict the expected lifespan of the target device based on the duration corresponding to the abnormal operating parameters as the target device is used continuously, and dynamically adjust the abnormal range using the expected lifespan, so that the abnormal range is more in line with the actual usage state of the target device, the detection of abnormal values ​​is more accurate, and the time of detecting abnormality is synchronized with the time when the device actually becomes abnormal, so as to maintain the target device in a timely manner and delay the degradation process of the device's lifespan from the root. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0020] Figure 1 This is a flowchart of a device operation status monitoring method according to an embodiment of this application;

[0021] Figure 2 This is a flowchart of the training steps for a lifetime prediction mode according to an embodiment of this application;

[0022] Figure 3 A flowchart illustrating the steps for determining the expected service life of an air conditioning unit according to an embodiment of this application;

[0023] Figure 4 This is a structural diagram of a device for monitoring the operating status of an equipment according to an embodiment of this application;

[0024] Figure 5 This is a structural diagram of a device for monitoring the operating status of an equipment according to an embodiment of this application. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] The following disclosure provides numerous different embodiments or examples for implementing various structures of this application. To simplify the disclosure, specific examples of components and arrangements are described below. These are merely examples and are not intended to limit the scope of this application. Furthermore, reference numerals and / or letters may be repeated in different examples. Such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed.

[0027] This application provides a method for monitoring the operating status of a device. For example... Figure 1 The diagram shown is a flowchart of a device operation status monitoring method according to an embodiment of this application.

[0028] Step S110: Monitor the abnormal operating parameters of the target device based on the current abnormal range and determine the duration corresponding to the abnormal operating parameters.

[0029] The abnormal range refers to the boundary at which a parameter value used to measure the operation of a device has become abnormal. If the value of an operating parameter falls within this abnormal range, it indicates that the parameter value is abnormal and the operating parameter is considered an abnormal operating parameter. If the value of an operating parameter does not fall within this abnormal range, it indicates that the parameter value is normal and the operating parameter is considered a normal operating parameter.

[0030] Target equipment refers to equipment whose operational status needs to be monitored. Target equipment can be smart home appliances or industrial equipment. For example, types of target equipment include, but are not limited to, air conditioning units, refrigerators, and televisions.

[0031] Abnormal operating parameters refer to operating parameters whose values ​​fall within the abnormal range; that is, operating parameters that exhibit abnormalities.

[0032] Duration refers to the length of time a parameter value (outlier) remains within the abnormal range. In other words, it's the duration for which the running parameter exhibits an abnormality. While the parameter value is allowed to fluctuate within the abnormal range, it must remain within that range at all times.

[0033] Specifically, since the longer the duration of the anomaly, the greater the damage to the equipment's lifespan, and the shorter the duration of the anomaly, the less damage to the equipment's lifespan, the embodiments of this application can provide basic data for subsequent quantitative analysis of the impact of abnormal operating parameters on equipment lifespan by real-time monitoring and recording of abnormal operating parameters and their corresponding duration.

[0034] Furthermore, in this embodiment of the application, after detecting abnormal operating parameters, an alarm message can be sent to a preset terminal device to enable timely operation and maintenance of the target device. The alarm message may carry information about the abnormal operating parameters so that the user can identify the type of abnormal operating parameter.

[0035] Step S120: Determine the lifespan conversion factor corresponding to the abnormal operating parameters based on the duration of the abnormal operating parameters of the target device.

[0036] The lifespan reduction factor is used to quantify the degree of lifespan loss of a target device due to the duration of abnormal operating parameters.

[0037] By determining the lifespan conversion factor, the abstract duration of anomalies can be transformed into lifespan-related loss indicators, thereby establishing a link between abnormal operating parameters and the lifespan of the target equipment.

[0038] Step S130: Update the expected service life of the target device according to the service life conversion factor corresponding to the abnormal operating parameters.

[0039] Expected service life refers to the predicted lifespan of the target equipment.

[0040] The previous estimated service life of the target equipment can be obtained; using the service life conversion factor corresponding to the abnormal operating parameters of this time, the previous estimated service life is corrected to obtain the current estimated service life of the target equipment.

[0041] By using dynamically determined lifespan conversion factors, the design lifespan of the target equipment can be continuously revised, and then the expected lifespan, which is calculated iteratively, can be used to determine a lifespan that is closer to the actual state of the target equipment.

[0042] Step S140: Adjust the abnormal range corresponding to the abnormal operating parameters according to the updated expected service life of the target device, so as to continue monitoring the abnormal operating parameters of the target device based on the adjusted abnormal range.

[0043] The abnormal range includes an upper threshold and / or a lower threshold. The upper threshold refers to the value of a running parameter when it is greater than the upper threshold, and the lower threshold refers to the value of a running parameter when it is less than the lower threshold, and so on.

[0044] Expected service life and anomaly range are positively correlated. That is, a shorter expected service life leads to a smaller anomaly range. Anomaly range shrinkage refers to raising the lower threshold and lowering the upper threshold. Further, anomaly range shrinkage refers to using correction parameters to raise the lower threshold and lower the upper threshold. The specific methods for shrinking the anomaly range will be described later and will not be elaborated upon here.

[0045] As the expected service life decreases, the range of anomalies is narrowed because as the target equipment is used continuously, the components in the target equipment become more sensitive to anomalies due to wear and other factors. Anomalies of the same degree will significantly accelerate the wear and tear on the equipment. Therefore, this application embodiment uses a more stringent range of anomalies to identify anomalies by narrowing the range of anomalies, thereby maintaining the operational reliability of the target equipment. It can also reduce the additional load on the target equipment caused by component aging and slow down the rate of life decay of the target equipment.

[0046] In this embodiment, abnormal operating parameters of the target device are monitored based on the current abnormal range, and the duration corresponding to the abnormal operating parameters is determined. A lifespan conversion factor corresponding to the abnormal operating parameters is determined based on the duration of the abnormal operating parameters. The estimated lifespan of the target device is updated based on the lifespan conversion factor. The abnormal range corresponding to the abnormal operating parameters is adjusted based on the updated estimated lifespan of the target device, so that the abnormal operating parameters of the target device can continue to be monitored based on the adjusted abnormal range. Compared to monitoring abnormal operating parameters with a fixed abnormal range, this embodiment can predict the estimated lifespan of the target device based on the duration of the abnormal operating parameters as the target device is used continuously, and dynamically adjust the abnormal range using the estimated lifespan. This makes the abnormal range more closely match the actual usage state of the target device, resulting in more accurate detection of abnormal values. It also synchronizes the time of abnormal detection with the actual time when the device experiences an abnormality, enabling timely maintenance of the target device and slowing down the degradation process of the device's lifespan from the root cause.

[0047] Furthermore, as the target equipment continues to operate, components (such as compressors and bearings) gradually age due to wear, material fatigue, and decreased lubrication performance. These aging issues increase the target equipment's sensitivity to abnormal operating parameters; that is, the same degree of abnormal operating parameters (such as excessive high-pressure side pressure) has a significantly greater impact on the lifespan of aging equipment than on new equipment. For example, the compressor seals of a new air conditioner have good elasticity and can withstand excessive high-pressure side pressure (abnormality) without leakage; however, as the air conditioner ages, the seals harden, and the same excessive high-pressure side pressure may cause rapid refrigerant leakage, significantly shortening its lifespan. In this case, using a static abnormality range, new equipment will not experience lifespan loss due to abnormal operating parameters, but aging equipment may experience lifespan loss due to abnormal operating parameters, resulting in an actual lifespan far below the design value. To address this issue, the embodiments of this application can dynamically adjust the abnormality range, such as gradually reducing the threshold of high-pressure side pressure, thereby identifying abnormal operating parameters through a more stringent threshold, reducing the possibility of aging equipment bearing additional loads, and thus slowing down the process of equipment lifespan decline. For example, at the factory, the threshold value corresponding to the high-pressure side pressure of an air conditioner is 2.5 MPa (the upper limit threshold). At this point, a high-pressure side pressure greater than 2.5 MPa will not damage the equipment temporarily. However, when the lifespan of the air conditioner decreases from 10 years to 5 years, the air conditioner components have aged. If the threshold value of 2.5 MPa is still used to trigger an alarm, it may cause the air conditioner components to be unable to withstand the high pressure, resulting in rapid refrigerant leakage and accelerating the lifespan of the air conditioner. To address this issue, this application embodiment can reduce the threshold value corresponding to the high-pressure side pressure, such as adjusting it from 2.5 MPa to 2.3 MPa. In this way, when the high-pressure side pressure is less than 2.3 MPa, the high-pressure side pressure abnormality can be detected, thereby preventing the compressor of the aging air conditioner from failing prematurely due to long-term high-pressure operation.

[0048] To make the embodiments of this application clearer, the device operation status monitoring method of the embodiments of this application will be further described below.

[0049] In this embodiment of the application, the abnormal operating parameters of the target device can be monitored based on the current abnormal range, and the duration of the abnormal operating parameters can be determined.

[0050] The type of operating parameter to be monitored must be at least one. The specific type of operating parameter can be set according to the device type of the target device.

[0051] For each preset operating parameter, the abnormal value of the operating parameter can be monitored according to the current abnormal range of the operating parameter, and when the abnormal value is detected to be converted into a normal value, the duration of the abnormal value can be determined.

[0052] When the target equipment is an air conditioning unit, the types of operating parameters include, but are not limited to: high-pressure side pressure, low-pressure side pressure, exhaust temperature, exhaust superheat, and noise level. These operating parameters reflect the operating status and working environment of the air conditioning unit. If the parameter values ​​exceed the normal range, it will lead to premature wear of the air conditioning unit's components, performance degradation, or failure, meaning the service life of the air conditioning unit will be reduced more rapidly.

[0053] Specifically, before the target device is first run, an initial abnormal range can be set for each operating parameter. Based on the abnormal range corresponding to the operating parameter, the parameter value is monitored for abnormalities. Subsequently, adjustments are made iteratively based on this initial abnormal range. Specifically, for each operating parameter, when the parameter value is detected to be within its corresponding abnormal range, the operating parameter is determined to be abnormal and can be identified as an abnormal operating parameter. The duration from when the parameter value enters the abnormal range to when the parameter value no longer exists within the abnormal range is recorded and determined as the duration corresponding to the abnormal operating parameter.

[0054] After detecting an abnormal value in the operating parameter and determining the duration of the abnormal value, the duration of the abnormal operating parameter can be determined in real time or periodically. Since there is at least one type of operating parameter, each type of operating parameter can be monitored for abnormal values, and the duration of each abnormal operating parameter can be determined separately.

[0055] The real-time determination method includes: for each preset operating parameter, based on the current abnormal range corresponding to the operating parameter, monitoring the abnormal value of the operating parameter, and when the abnormal value is detected to be converted into a normal value, determining the duration corresponding to the abnormal value; determining the operating parameter as the abnormal operating parameter and determining the duration corresponding to the abnormal value as the duration corresponding to the abnormal operating parameter.

[0056] For example: if the value of the first operating parameter is greater than the threshold of 5, it is considered an abnormal value. If parameter value 6 is detected to last for 2 seconds and parameter value 7 to last for 3 seconds, and then the parameter value becomes 4, which is a normal value, then the duration corresponding to the first operating parameter is 5 seconds (i.e., 2 + 3 = 5). This real-time determination method can determine the duration corresponding to each abnormal operating parameter detected, determine the lifespan conversion factor based on the duration, and update the estimated lifespan of the target device based on the lifespan conversion factor.

[0057] The periodic determination method includes: for each preset operating parameter, monitoring abnormal values ​​of the operating parameter according to the current abnormal range of the operating parameter, and determining and recording the duration of the abnormal value when the abnormal value is detected to be converted to a normal value; every preset time period, obtaining the duration of each abnormal value of the operating parameter in the current time period; determining the operating parameter as the abnormal operating parameter, and determining the duration of the abnormal operating parameter according to the duration of each abnormal value.

[0058] Furthermore, the sum of the durations corresponding to each of the abnormal values ​​can be determined as the duration corresponding to the abnormal operating parameter; or, the average of the durations corresponding to each of the abnormal values ​​can be determined as the duration corresponding to the abnormal operating parameter.

[0059] For example, if the value of the second operating parameter is greater than 5, it is considered an anomaly. If a value of 7 was observed for 3 seconds, a value of 2 for 5 seconds, a value of 6 for 7 seconds, and a value of 3 for 5 seconds, the duration of each anomaly within 20 seconds is recorded. Since only values ​​7 and 6 can be identified as anomalies, the duration of 3 seconds for value 7 and 7 seconds for value 6 can be recorded. The average of these two durations is 5 seconds (i.e., (3+7)÷2=5). Therefore, the duration of the second operating parameter under anomaly conditions can be determined to be 5 seconds. This periodic determination method allows monitoring of anomaly operating parameters for a period of time. Based on the average duration of each anomaly operating parameter monitored during this period, a lifespan conversion factor is determined, and the estimated lifespan of the target equipment is updated based on this lifespan conversion factor.

[0060] In this embodiment of the application, the lifespan conversion factor corresponding to the abnormal operating parameters of the target device is determined based on the duration of the abnormal operating parameters.

[0061] Furthermore, when the duration of each of the multiple abnormal operating parameters is determined at the same time, a lifetime conversion factor is determined for each abnormal operating parameter. When the duration of each of the multiple abnormal operating parameters is determined at different times, the lifetime conversion factor for each abnormal operating parameter is determined sequentially in chronological order, i.e., the equipment operation status monitoring method of this application embodiment is executed sequentially.

[0062] Specifically, since the duration of outliers varies and their impact on the target equipment differs, the lifespan conversion factor can be different for different durations of the same abnormal operating parameter.

[0063] Taking the types of operating parameters of an air conditioning unit, including high-pressure side pressure (hereinafter referred to as high pressure) and exhaust temperature, as an example:

[0064] Under excessively high voltage conditions, the degree of damage to the target equipment varies depending on the duration of the voltage exposure.

[0065] 1) Short-term excessively high pressure: usually will not cause immediate damage to the air conditioning unit, but will accelerate the aging of the air conditioning unit's components.

[0066] 2) Short- to medium-term excessively high pressure: The compressor and other key components of the air conditioning unit may experience significant wear and performance degradation.

[0067] 3) Prolonged excessively high pressure: The compressor and other key components of the air conditioning unit may suffer irreversible damage, eventually leading to the complete failure of the air conditioner.

[0068] When the exhaust temperature is too high, the degree of damage to the target equipment varies depending on the duration of the high temperature.

[0069] 1) Short-term excessively high exhaust temperature will cause the internal temperature of the air conditioning unit's compressor to rise. The lubricating oil is prone to decomposition and deterioration at high temperatures, which will accelerate the aging and wear of the internal materials of the compressor.

[0070] 2) Prolonged high exhaust temperature will increase internal friction of the compressor, accelerate wear, increase energy consumption, and may cause the compressor to seize up, leading to compressor failure or even damage, and reducing the compressor's lifespan.

[0071] Other types of operating parameters also have varying durations, resulting in different degrees of damage to the target equipment.

[0072] Since the duration of abnormal operating parameters varies, and their impact on the target equipment differs, the lifespan conversion factor can be determined based on the duration of the abnormal operating parameters. Two methods for determining the lifespan conversion factor are provided below.

[0073] Method 1: Using a pre-trained lifetime prediction model, determine the lifetime conversion factor corresponding to the abnormal operating parameters based on the duration of the abnormal operating parameters.

[0074] Furthermore, the lifetime prediction model is used to determine the lifetime reduction factor corresponding to the abnormal operating parameters based on their duration. This lifetime prediction model can be trained using the stochastic gradient descent method. Figure 2 The diagram shown is a flowchart of the training steps for a lifetime prediction mode according to an embodiment of this application.

[0075] Step S210: Obtain historical operating data of the sample equipment under different operating conditions.

[0076] The sample device has the same device type as the target device.

[0077] Step S220: Extract each abnormal operation parameter and the duration corresponding to each abnormal operation parameter from the acquired historical operation data, and use each abnormal operation parameter and its corresponding duration as a training sample.

[0078] Taking air conditioning units as an example, historical operating data includes, but is not limited to, abnormal operating parameters such as high-pressure side pressure, low-pressure side pressure, exhaust temperature, and exhaust superheat, as well as their duration.

[0079] Step S230: Obtain the actual lifespan of each sample device.

[0080] Step S240: Sequentially obtain a training sample.

[0081] Step S250: Input the current training sample into the lifetime prediction model and obtain the lifetime conversion factor output by the lifetime prediction model.

[0082] Step S260: Determine the expected service life of the sample device corresponding to the current training sample based on the service life conversion factor output by the service life prediction model.

[0083] Step S270: Determine the loss value of the life prediction model based on the actual and expected lifespan of the sample device corresponding to the training sample.

[0084] Step S280: Determine whether the loss value for the preset number of training iterations has been greater than the loss value threshold. If yes, proceed to step S290; otherwise, adjust the parameters in the lifetime prediction model and jump to step S240.

[0085] Step S290: Determine that the lifetime prediction model has converged.

[0086] Method 2: Determine the lifetime conversion factor corresponding to the abnormal operating parameter based on the impact level mapped by the duration of the abnormal operating parameter.

[0087] The impact level is used to reflect the degree of impact of the duration of abnormal operating parameters on the target equipment.

[0088] Furthermore, for each operating parameter of the target device, a mapping relationship between duration and impact level can be pre-set for each operating parameter, and a lifespan conversion factor can be set for each impact level.

[0089] In other words, the impact levels corresponding to the same duration for different abnormal operating parameters can be the same or different; the lifetime conversion factors corresponding to the same impact level for different abnormal operating parameters can be the same or different. Thus, after determining the duration corresponding to the abnormal operating parameter, the impact level mapped to that duration can be queried, and the lifetime conversion factor corresponding to that impact level can be determined.

[0090] Furthermore, before determining the lifetime conversion factor corresponding to the abnormal operating parameter based on the impact level mapped to the duration of the abnormal operating parameter, historical operating data of other devices of the same type as the target device can be obtained. Using a pre-trained lifetime mapping model, a correspondence table is determined based on the historical operating data for multiple lifetime conversion factors corresponding to the abnormal operating parameter and the duration range corresponding to each lifetime conversion factor; wherein each duration range maps to an impact level. After determining the duration corresponding to the abnormal operating parameter, the lifetime conversion system corresponding to the abnormal operating parameter can be determined by querying the duration range of the abnormal operating parameter within that duration range.

[0091] The lifetime mapping model and the lifetime prediction model can be the same or different models.

[0092] When the lifetime mapping model and the lifetime prediction model are the same, during the training process, the relationship between the duration of the training samples and the lifetime conversion factor output by the model can be determined, and then the correspondence between the lifetime conversion factor and the duration range of abnormal operating parameters can be determined.

[0093] When the lifetime mapping model differs from the lifetime prediction model, during training, the lifetime mapping model can be trained to establish a correspondence between the output lifetime reduction factor and the duration range of abnormal operating parameters based on the input training samples. The training process for the lifetime mapping model can be referenced from that for the lifetime prediction model.

[0094] The following table, using air conditioning unit operating parameters including high pressure, exhaust temperature, and exhaust superheat as examples, describes the correspondence between multiple lifespan conversion factors for abnormal operating parameters and the duration range corresponding to each lifespan conversion factor. The table also reflects the degree of influence set for each duration range.

[0095] Table 1 lists the lifespan conversion factors m corresponding to different duration ranges of excessively high voltage (tp-high), arranged in ascending order of the extreme values ​​of the duration range. It should be understood by those skilled in the art that Table 1 is merely illustrative of embodiments of this application and is not intended to limit the scope of these embodiments.

[0096]

[0097] Table 1

[0098] Table 2 lists the lifespan conversion factors n corresponding to different duration ranges of excessively high exhaust temperatures, arranged in ascending order of the extreme values ​​of the duration range tT-exhaust. Of course, those skilled in the art should understand that Table 2 is merely illustrative of embodiments of this application and is not intended to limit the scope of these embodiments.

[0099]

[0100] Table 2

[0101] Table 3 lists the lifetime conversion factors v corresponding to different duration ranges when the duration t-T_sh of the exhaust superheat is too low, arranged in ascending order of the extreme values ​​of the duration range. Of course, those skilled in the art should know that Table 3 is only for illustrating the embodiments of this application and is not intended to limit the embodiments of this application.

[0102]

[0103] Table 3

[0104] In this embodiment of the application, after determining the lifespan conversion factor corresponding to the abnormal operating parameters, the expected lifespan of the target device can be updated according to the lifespan conversion factor corresponding to the abnormal operating parameters.

[0105] Specifically, the estimated lifespan of the target device can be obtained from the most recent update, and the lifespan decay rate of the target device can be obtained accordingly. Based on the estimated lifespan of the target device from the most recent update, the lifespan decay rate of the target device, and the lifespan conversion factor corresponding to the abnormal operating parameters, the estimated lifespan of the target device can be updated.

[0106] Lifetime decay rate refers to the normal rate at which the lifespan of a target device decays.

[0107] Furthermore, the expected service life of the target device after the most recent update, the life decay rate of the target device, and the life conversion factor corresponding to the abnormal operating parameters can be calculated, and the product can be used to determine the expected service life of the target device after the update.

[0108] Furthermore, after determining the lifetime conversion factors corresponding to multiple abnormal operating parameters, the product of the expected lifetime of the most recent update of the target device, the lifetime decay rate of the target device, and the lifetime conversion factors corresponding to the multiple abnormal operating parameters can be calculated, and the product can be used to determine the expected lifetime of the target device after the update.

[0109] Determining the normal service life of a target device is an iterative update process. The current normal service life of the target device is the product of its previous normal service life and its lifespan decay rate. However, during operation, the target device is affected by multiple factors (e.g., environmental influences, operating parameters), causing its actual service life to deviate from its normal service life. Therefore, this embodiment of the application considers the negative impact of abnormal states during operation on the lifespan of the target device. It uses the duration corresponding to abnormal operating parameters to determine a lifespan reduction factor, and multiplies the normal service life of the target device by this lifespan reduction factor to correct the normal service life of the target device.

[0110] For example: the high pressure of the air conditioning unit is higher than the normal high pressure range and lasts for a duration t1∈(0, a1); simultaneously, the exhaust temperature of the air conditioning unit is higher than its normal value and lasts for a duration t2∈(b1, b2), while all other operating parameters are within the normal operating range. In this case, the expected service life of the air conditioning unit is T_use = L_life × s × m1 × v2. Where L_life is the previously determined expected service life, s is the lifespan decay rate corresponding to the air conditioning unit, m1 is the lifespan reduction factor corresponding to the high pressure, and v2 is the lifespan reduction factor corresponding to the exhaust temperature; s, m1, and v2 are all less than 1. Figure 3 This is a flowchart illustrating the steps for determining the expected service life of an air conditioning unit according to an embodiment of this application.

[0111] Step S310: The air conditioning unit starts running.

[0112] Step S320: Monitor whether any of the operating parameters of the air conditioning unit are abnormal; if so, proceed to steps S331 to S332; if not, proceed to step S360 every preset update time period.

[0113] Step S331: Determine that the high voltage P-high is greater than the high voltage threshold P-high-limit and has lasted for the first duration.

[0114] Step S341: Query the lifetime conversion factor m1 corresponding to the first duration, and jump to step S350.

[0115] Step S332: Determine that the exhaust temperature T-exhaust is less than the exhaust temperature threshold T-exhaust-limit and has lasted for a second duration.

[0116] Step S342: Query the lifetime conversion factor v2 corresponding to the second duration, then proceed to step S350. In this example, it is assumed that the determination time for both durations is the same.

[0117] In this example, only the high pressure (P-high) and exhaust temperature (T-exhaust) were detected to be abnormal, so only these two abnormal operating parameters are shown in the figure; other operating parameters are not shown in the figure.

[0118] Step S350, update the estimated lifetime T_use = the previously determined estimated lifetime L_life × lifetime decay rate s × m1 × v2.

[0119] Step S360, update the estimated lifespan T_use = the previously determined estimated lifespan L_life × lifespan decay rate s.

[0120] Since the target device will lose lifespan with use even if no abnormal operating parameters are sent during operation, the expected lifespan of the target device can be updated every preset update time period using the most recent updated expected lifespan L_life and lifespan decay rate s. That is: the updated expected lifespan T_use = L_life × s.

[0121] In this embodiment of the application, after updating the expected lifespan of the target device, the abnormal range corresponding to the abnormal operating parameters can be adjusted according to the updated expected lifespan of the target device, so as to continue monitoring the abnormal operating parameters of the target device based on the adjusted abnormal range.

[0122] The abnormal range corresponding to the abnormal operating parameters can be adjusted once after each update of the expected lifespan of the target device; or, at each preset adjustment interval, the abnormal range corresponding to the abnormal operating parameters can be adjusted once based on the most recently updated expected lifespan in the current adjustment interval.

[0123] Specifically, the design service life of the target device can be obtained; the service life utilization rate can be determined based on the design service life of the target device and the updated expected service life of the target device; and the abnormal range corresponding to the abnormal operating parameters can be adjusted according to the correction parameters corresponding to the abnormal operating parameters under the service life utilization rate.

[0124] Life utilization rate refers to the relative proportion of current lifespan consumed.

[0125] Correction parameters are numerical values ​​used to correct for extreme values ​​within an abnormal range.

[0126] Furthermore, the ratio of the updated expected service life of the target device to its designed service life can be calculated, and this ratio can be used to determine the service life utilization rate. The correction parameters corresponding to the abnormal operating parameters within the correction parameter range of this service life utilization rate can be determined. Based on the current endpoint of the abnormal range of the target device and the correction parameter, a new endpoint value can be determined. Specifically, a calculation method can be pre-set for each endpoint of the abnormal range, and the endpoint of the abnormal range and the correction parameter can be calculated according to this calculation method to obtain the new endpoint value.

[0127] Furthermore, multiple ranges of correction parameters with consecutive endpoints can be pre-defined, with each range corresponding to a correction parameter. The correction parameter can be the smallest endpoint of its corresponding range.

[0128] For example, as shown in Table 4, the correction parameters corresponding to abnormal operating parameters are given for the lifetime utilization rate within different correction parameter ranges. Of course, those skilled in the art should understand that Table 4 is only used to illustrate embodiments of this application and is not intended to limit the embodiments of this application.

[0129]

[0130] Table 4

[0131] Among them, P-high-limit, T-exhaust-limit, and T_sh-limit2 are the maximum values, and T_sh-limit1 is the minimum value. That is to say, high pressure P-high < P-high-limit, exhaust temperature T-exhaust < T-exhaust-limit, and T_sh-limit1 < exhaust temperature T_sh < T_sh-limit2 are all abnormal operating parameters. After determining the correction parameters, the current end value can be multiplied or divided by the correction parameters according to the calculation method shown in Table 4 to determine the new end value and obtain the new abnormal range. For example, when d1 ≤ f < 1, based on the new abnormal range, high pressure P-high < P-high-limit × d1, exhaust temperature T-exhaust < T-exhaust-limit × d1, and T_sh-limit1 ÷ d1 < exhaust temperature T_sh < T_sh-limit2 × d1 can be identified as abnormal operating parameters.

[0132] Furthermore, the correction parameter range of the initial state can be preset; the number of changes in the expected service life of the target device can be recorded; and each time the number of changes in the expected service life reaches a preset number, the values ​​at each end of the correction parameter range can be reduced by a preset gradient value.

[0133] The range of the initial state correction parameters can be empirical values ​​or values ​​obtained through experiments.

[0134] The number of changes in expected service life refers to the number of times the target equipment decreases from its designed service life. Each decrease can be counted once.

[0135] The preset number of times can be an empirical value or a value obtained through experiments. For example, for every reduction in the expected service life, the values ​​at each end of the correction parameter range are reduced by one according to this gradient value.

[0136] The gradient value can be an empirical value or a value obtained through experiments.

[0137] In this embodiment of the application, the expected lifespan of the target device and its abnormal operating parameters and their corresponding duration can be sent to a preset terminal device.

[0138] Furthermore, to facilitate users' understanding of the target device's status, the system can send the estimated lifespan of the target device, which was last determined within the current sending time period, as well as all abnormal operating parameters detected within the current sending time period and their corresponding durations, to the preset terminal device at preset sending time intervals.

[0139] The sending period can be determined according to requirements. For example, the sending period can be one month.

[0140] In this embodiment, a preset alarm message can be issued each time abnormal operating parameters are detected. The alarm message includes information about the abnormal operating parameters. This allows the user to promptly perform operation and maintenance on the target device after seeing the alarm message.

[0141] The static threshold monitoring method, which monitors operating parameters for anomalies by pre-setting fixed abnormal ranges, has significant technical limitations. As equipment ages, fixed thresholds fail to reflect the actual operating status. When persistent parameter deviations occur due to environmental factors or component aging, only passive monitoring of abnormal states is possible, without establishing a quantitative correlation between parameter anomalies and lifespan deterioration. This leads to equipment maintenance often lagging behind the actual lifespan decline process. This technological gap makes equipment susceptible to irreversible lifespan loss due to the cumulative effect of parameter anomalies during operation, severely impacting user experience and equipment economics. To address this issue, this application's embodiments monitor abnormal operating parameters and determine their duration. This allows for the determination of a lifespan conversion factor corresponding to the abnormal operating parameters. The expected lifespan of the target device is then updated based on this conversion factor. Finally, the currently used device monitoring parameters (abnormal range) are adjusted based on the updated expected lifespan of the target device. In this way, a connection is established between abnormal operating parameters, expected lifespan, and device monitoring parameters. Based on this connection, a dynamic adjustment mechanism for the target device is implemented. The abnormal range always closely matches the actual state of the target device, making parameter anomaly monitoring more real-time and accurate, and avoiding the problem of equipment maintenance lagging behind the actual lifespan degradation process.

[0142] This application also provides a device for monitoring the operating status of equipment. For example... Figure 4 The diagram shown is a structural diagram of a device for monitoring the operating status of an equipment according to an embodiment of this application.

[0143] The equipment operation status monitoring device includes:

[0144] The monitoring module 410 is used to monitor the abnormal operating parameters of the target device based on the current abnormal range and determine the duration of the abnormal operating parameters.

[0145] The determining module 420 is used to determine the lifespan conversion factor corresponding to the abnormal operating parameters based on the duration of the abnormal operating parameters of the target device.

[0146] The update module 430 is used to update the expected service life of the target device according to the service life conversion factor corresponding to the abnormal operating parameters.

[0147] The adjustment module 440 is used to adjust the abnormal range corresponding to the abnormal operating parameters according to the updated expected service life of the target device, so as to continue to monitor the abnormal operating parameters of the target device based on the adjusted abnormal range.

[0148] The functions of the apparatus described in this application embodiment have been described in the above method embodiments. Therefore, for any parts not detailed in the description of this embodiment, please refer to the relevant descriptions in the foregoing embodiments, which will not be repeated here.

[0149] This application also provides a device for monitoring the operating status of an equipment, such as... Figure 5 The diagram shown is a structural diagram of a device for monitoring device operation status according to an embodiment of this application.

[0150] The device operation status monitoring equipment includes: a processor 510, a communication interface 520, a memory 530, and a communication bus 540. Among them, the processor 510, the communication interface 520, and the memory 530 communicate with each other through the communication bus 540.

[0151] Memory 530 is used to store computer programs.

[0152] In one embodiment of this application, when the processor 510 executes the program stored in the memory 530, it implements the device operation status monitoring method provided in any of the foregoing method embodiments, including: monitoring abnormal operating parameters of a target device based on the current abnormal range and determining the duration corresponding to the abnormal operating parameters; determining a lifespan conversion factor corresponding to the abnormal operating parameters based on the duration corresponding to the abnormal operating parameters of the target device; updating the expected lifespan corresponding to the target device based on the lifespan conversion factor corresponding to the abnormal operating parameters; and adjusting the abnormal range corresponding to the abnormal operating parameters based on the updated expected lifespan corresponding to the target device, so as to continue monitoring the abnormal operating parameters of the target device based on the adjusted abnormal range.

[0153] The step of monitoring abnormal operating parameters of the target device based on the current abnormal range and determining the duration of the abnormal operating parameters includes: for each preset operating parameter, monitoring abnormal values ​​of the operating parameter according to the current abnormal range of the operating parameter, and determining the duration of the abnormal value when the abnormal value is detected to be converted to a normal value; wherein, the operating parameter is determined to be the abnormal operating parameter and the duration of the abnormal value is determined to be the duration of the abnormal operating parameter; or, every preset time period, obtaining the duration of each abnormal value of the operating parameter occurring in the current time period; determining the operating parameter as the abnormal operating parameter, and determining the duration of the abnormal operating parameter according to the duration of each abnormal value.

[0154] The step of determining the lifetime conversion factor corresponding to the abnormal operating parameter based on the duration of the abnormal operating parameter of the target device includes: using a pre-trained lifetime prediction model to determine the lifetime conversion factor corresponding to the abnormal operating parameter based on the duration of the abnormal operating parameter; or, determining the lifetime conversion factor corresponding to the abnormal operating parameter based on the degree of influence mapped by the duration of the abnormal operating parameter.

[0155] Before determining the lifetime conversion factor corresponding to the abnormal operating parameter based on the impact level mapped by the duration of the abnormal operating parameter, the method further includes: acquiring historical operating data of other devices of the same type as the target device; using a pre-trained lifetime mapping model, determining multiple lifetime conversion factors corresponding to the abnormal operating parameter and a correspondence table of duration ranges corresponding to each lifetime conversion factor based on the historical operating data; wherein each duration range maps to an impact level.

[0156] The step of updating the expected service life of the target device based on the service life conversion factor corresponding to the abnormal operating parameters includes: obtaining the most recently updated expected service life of the target device and obtaining the service life decay rate corresponding to the target device; and updating the expected service life of the target device based on the most recently updated expected service life of the target device, the service life decay rate corresponding to the target device, and the service life conversion factor corresponding to the abnormal operating parameters.

[0157] The step of adjusting the abnormal range of the abnormal operating parameters according to the updated expected service life of the target device includes: obtaining the design service life of the target device; determining the service life utilization rate according to the design service life of the target device and the updated expected service life of the target device; and adjusting the current abnormal range of the abnormal operating parameters according to the correction parameter corresponding to the service life utilization rate.

[0158] This application also provides a computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the steps of the device operation status monitoring method provided in any of the foregoing method embodiments. Since the device operation status monitoring method has been described in detail above, any omissions or deficiencies in this embodiment can be found in the relevant descriptions in the foregoing embodiments, and will not be repeated here.

[0159] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0160] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented using software plus a general-purpose hardware platform, or of course, using hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0161] It should be understood that the terminology used herein is for the purpose of describing particular exemplary embodiments only and is not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “described” as used herein may also include the plural forms. The terms “comprising,” “including,” “containing,” and “having” are inclusive and therefore indicate the presence of the stated features, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, elements, components, and / or combinations thereof. The method steps, processes, and operations described herein are not construed as requiring them to be performed in a particular order described or illustrated unless the order of performance is explicitly indicated. It should also be understood that additional or alternative steps may be used.

[0162] The above description is merely a specific embodiment of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for monitoring the operating status of equipment, characterized in that, include: Based on the current anomaly range, monitor the abnormal operating parameters of the target device and determine the duration of the abnormal operating parameters. Based on the duration of the abnormal operating parameters of the target device, determine the lifespan conversion factor corresponding to the abnormal operating parameters; The expected service life of the target device is updated based on the service life conversion factor corresponding to the abnormal operating parameters. Based on the updated expected lifespan of the target device, the abnormal range corresponding to the abnormal operating parameters is adjusted so that the abnormal operating parameters of the target device can continue to be monitored based on the adjusted abnormal range. The step of monitoring abnormal operating parameters of the target device based on the current abnormal range and determining the duration of the abnormal operating parameters includes: for each preset operating parameter, monitoring abnormal values ​​of the operating parameter according to the current abnormal range of the operating parameter, and determining the duration of the abnormal value when the abnormal value is detected to be converted to a normal value; wherein, the operating parameter is determined to be the abnormal operating parameter and the duration of the abnormal value is determined to be the duration of the abnormal operating parameter; or, every preset time period, obtaining the duration of each abnormal value of the operating parameter occurring in the current time period; determining the operating parameter as the abnormal operating parameter, and determining the duration of the abnormal operating parameter according to the duration of each abnormal value.

2. The method according to claim 1, characterized in that, The step of determining the lifetime conversion factor corresponding to the abnormal operating parameters based on the duration of the abnormal operating parameters of the target device includes: Using a pre-trained lifetime prediction model, the lifetime reduction factor corresponding to the abnormal operating parameter is determined based on the duration of the abnormal operating parameter; or, Based on the degree of impact mapped by the duration of the abnormal operating parameters, the lifetime conversion factor corresponding to the abnormal operating parameters is determined.

3. The method according to claim 2, characterized in that, Before determining the lifetime conversion factor corresponding to the abnormal operating parameter based on the impact level mapped by the duration of the abnormal operating parameter, the method further includes: Obtain historical operating data of other devices of the same device type as the target device; Using a pre-trained lifetime mapping model, based on the historical operating data, a correspondence table is determined for multiple lifetime conversion factors corresponding to the abnormal operating parameters and the duration range corresponding to each lifetime conversion factor; wherein, each duration range maps to an impact level.

4. The method according to claim 1, characterized in that, The step of updating the expected service life of the target device based on the service life conversion factor corresponding to the abnormal operating parameters includes: Obtain the estimated lifespan of the target device from the most recent update and obtain the lifespan decay rate of the target device; The expected lifespan of the target device is updated based on the most recently updated estimated lifespan of the target device, the lifespan decay rate of the target device, and the lifespan conversion factor corresponding to the abnormal operating parameters.

5. The method according to claim 1, characterized in that, The step of adjusting the abnormal range corresponding to the abnormal operating parameters based on the updated expected lifespan of the target device includes: Obtain the design service life of the target device; The lifespan utilization rate is determined based on the design lifespan of the target equipment and the expected lifespan of the target equipment after its upgrade. Based on the correction parameter corresponding to the abnormal operating parameter under the service life rate, adjust the current abnormal range corresponding to the abnormal operating parameter.

6. A device for monitoring the operating status of equipment, characterized in that, include: A monitoring module is used to monitor abnormal operating parameters of a target device based on the current abnormal range and determine the duration corresponding to the abnormal operating parameters. The step of monitoring abnormal operating parameters of the target device based on the current abnormal range and determining the duration corresponding to the abnormal operating parameters includes: for each preset operating parameter, monitoring abnormal values ​​of the operating parameter according to the current abnormal range of the operating parameter, and determining the duration corresponding to the abnormal value when the abnormal value is detected to have changed to a normal value; wherein, the operating parameter is determined to be the abnormal operating parameter and the duration corresponding to the abnormal value is determined to be the duration corresponding to the abnormal operating parameter; or, every preset time period, acquiring the duration corresponding to each abnormal value of the operating parameter occurring within the current time period; determining the operating parameter as the abnormal operating parameter, and determining the duration corresponding to the abnormal operating parameter based on the duration corresponding to each abnormal value. The determination module is used to determine the lifespan conversion factor corresponding to the abnormal operating parameters based on the duration of the abnormal operating parameters of the target device. The update module is used to update the expected service life of the target device according to the service life conversion factor corresponding to the abnormal operating parameters; The adjustment module is used to adjust the abnormal range corresponding to the abnormal operating parameters according to the updated expected service life of the target device, so as to continue monitoring the abnormal operating parameters of the target device based on the adjusted abnormal range.

7. An air conditioning unit, characterized in that, The air conditioning unit uses the equipment operation status monitoring method according to any one of claims 1-5.

8. A device for monitoring the operating status of equipment, characterized in that, include: At least one communication interface; At least one bus connected to the at least one communication interface; At least one processor connected to the at least one bus; At least one memory connected to the at least one bus, wherein the processor is configured to execute a device lifetime prediction program stored in the memory to implement the device operating status monitoring method according to any one of claims 1-5.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which are executed to implement the device operation status monitoring method according to any one of claims 1-5.

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