Equipment operation data total storage method based on equipment rotating speed monitoring

Abstract

The invention relates to an equipment rotating speed monitoring-based equipment operation data full-amount storage method, which relates to the field of data processing, and comprises the following steps of: constructing a query fault-tolerant condition based on an equipment model of to-be-monitored bit number equipment, a transmission element model list and a transmission element service life list; searching a historical operation sample group meeting a query fault tolerance condition; counting a plurality of control mode starting completion rotation speed characteristic values of the historical operation sample group, setting the minimum value as a rated rotation speed upper limit value, counting a plurality of control mode stopping completion rotation speed characteristic values of the historical operation sample group, and setting the maximum value as a rated rotation speed lower limit value; when the equipment monitoring rotating speed at the first moment falls between the rated rotating speed lower limit value and the rated rotating speed upper limit value, full storage is started, otherwise, interval storage is executed according to a preset period, and the problems that key parameter changes in the equipment starting and stopping process are difficult to accurately capture, data storage efficiency is low, and important information is prone to being missed are solved. And maintenance and analysis are difficult to carry out.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and particularly to a method for full - volume storage of equipment operation data based on equipment rotation speed monitoring. Background Art

[0002] In the fields of industrial Internet and large - scale equipment monitoring, the monitoring of the operation status of equipment is crucial for preventing failures, ensuring production safety, and prolonging the service life of equipment. Equipment is prone to accidents and damage during startup or shutdown, causing significant economic losses on - site. Existing equipment operation data monitoring methods usually adopt the method of storing data at fixed intervals. Although this method is simple and easy to implement, during key processes such as equipment startup or shutdown, due to the limitation of data sampling intervals, important monitoring parameters are often easily missed, making it impossible to accurately judge equipment failures; while if the mode of storing all data is used, it will cause a great waste of server disk space. Moreover, rotating equipment will cause differential changes in the startup cut - off value with the fluctuation of the service state, making it difficult for professionals to accurately judge the operation status and fault conditions of the equipment. Summary of the Invention

[0003] Aiming at the technical problems in the prior art that it is difficult to accurately capture the key parameter changes during equipment startup and shutdown, resulting in low data storage efficiency, easy omission of important information, and difficult maintenance and analysis, the present invention provides a method for full - volume storage of equipment operation data based on equipment rotation speed monitoring to solve these problems.

[0004] The technical solution of the present invention to solve the above - mentioned technical problems is as follows: The present invention provides a method for full - volume storage of equipment operation data based on equipment rotation speed monitoring, including: constructing a query fault - tolerance condition based on the equipment model, transmission element model list, and transmission element service life list of the equipment to be monitored; retrieving a historical operation sample group that meets the query fault - tolerance condition; statistically analyzing the starting - completed rotation speed characteristic values of several control modes in the historical operation sample group, taking the minimum value as the rated rotation speed upper limit value, statistically analyzing the shutdown - completed rotation speed characteristic values of several control modes in the historical operation sample group, taking the maximum value as the rated rotation speed lower limit value; when the equipment monitoring rotation speed at the first moment falls between the rated rotation speed lower limit value and the rated rotation speed upper limit value, start full - volume storage, otherwise, perform interval storage according to a preset period.

[0005] The beneficial effects of the present invention are as follows: By constructing query fault tolerance conditions to retrieve the historical operation sample group and setting the upper and lower limits of the rated speed accordingly, the full-volume data storage within the key speed change range during the startup and shutdown processes of the equipment is achieved, effectively avoiding the omission of important information. Meanwhile, for the non-critical speed change range, interval storage with a preset period is adopted, thereby significantly improving the pertinence and efficiency of data storage. Through intelligent storage, not only can the startup and shutdown states of the equipment be accurately judged, but also the data storage method can be selected according to the actual operation state of the equipment, effectively improving the data storage efficiency and resource utilization rate, and providing strong data support for the fault warning and maintenance of the equipment. Brief Description of the Drawings

[0006] Figure 1 It is a schematic flow chart of the full-volume storage method of equipment operation data based on equipment speed monitoring provided by the present invention.

[0007] Figure 2 It is a schematic flow chart of historical sample retrieval in the full-volume storage method of equipment operation data based on equipment speed monitoring provided by the present invention. Detailed Embodiments

[0008] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts shall fall within the protection scope of the present invention.

[0009] In the description of the present invention, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of the described features. In the description of the present invention, "a plurality" means two or more, unless otherwise specifically defined.

[0010] In the description of the present invention, the term "for example" is used to mean "serving as an example, illustration, or explanation". Any embodiment described as "for example" in the present invention is not necessarily construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to implement and use the present invention. In the following description, details are set forth for the purpose of explanation. It should be understood that those of ordinary skill in the art can recognize that the present invention can be implemented without these specific details. In other instances, well-known structures and processes are not elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but rather to be in line with the broadest scope consistent with the principles and features disclosed in the present invention.

[0011] Embodiment:

[0012] As Figure 1 shown, an embodiment of the present invention provides a method for full-volume storage of device operation data based on device speed monitoring, including: S10: Based on the device model, the list of transmission element models, and the list of transmission element service life years of the device to be monitored, construct a query fault tolerance condition.

[0013] S20: Retrieve a historical operation sample group that meets the query fault tolerance condition.

[0014] S30: Statistically calculate the starting completion speed characteristic values of several control modes of the historical operation sample group, take the minimum value, and set it as the rated speed upper limit value. Statistically calculate the stopping completion speed characteristic values of several control modes of the historical operation sample group, take the maximum value, and set it as the rated speed lower limit value.

[0015] S40: When the device monitoring speed at the first moment falls between the rated speed lower limit value and the rated speed upper limit value, start full-volume storage; otherwise, perform interval storage according to a preset period.

[0016] Exemplarily, the bit number to be monitored refers to the specific identifier or number of the device to be monitored. It represents the specific device or a key part of the device that needs to be monitored, and is the basis for rotational speed monitoring, data collection, and analysis. To accurately construct query fault tolerance conditions, focus on the core attributes of the device with the bit number to be monitored, namely the device model, the list of transmission element models, and the list of service life of transmission elements. The device model, as the basic identifier of the device, provides the basic characteristics and performance parameters of the device; the list of transmission element models details the specific models of each transmission component inside the device, and the performance and status of these components are directly related to the overall operation of the device; while the list of service life of transmission elements records the time span since these transmission elements were put into use, which is an important basis for evaluating the aging degree and maintenance requirements of the elements. First, retrieve the historical operation data samples that match the device model in the database, then further screen out the device samples with the same or similar transmission configurations in combination with the list of transmission element models to ensure the consistency of the selected samples with the device to be monitored in terms of the transmission mechanism. Finally, correct the service life of the selected samples considering the influence of the service life of transmission elements, and exclude the performance deviations that may be caused by element aging, so as to construct a set of query conditions that are both accurate and have a certain degree of fault tolerance. This process ensures that the historical data samples closest to the actual operation of the device to be monitored can be obtained in subsequent analysis, providing a solid foundation for the subsequent statistical analysis of the rotational speed characteristic values of the device and the formulation of the full-scale storage strategy.

[0017] After that, for specific monitoring tag numbers, i.e., the devices to be monitored, a series of operations are carried out to determine the upper limit value and the lower limit value of their rated speeds. This process involves retrieving a group of historical operation samples that meet the query fault tolerance conditions. Based on the above, the query fault tolerance conditions are constructed based on the device model, the list of transmission element models, and the list of transmission element service life years, aiming to ensure that the retrieved historical samples have sufficient similarity and comparability with the current monitored device in key features. Then, these groups of historical operation samples are analyzed to statistically obtain the starting completion speed characteristic values and the stopping completion speed characteristic values under different control modes. Specifically, the minimum value of the starting completion speed and the maximum value of the stopping completion speed under each control mode are respectively extracted, and these values are respectively set as the upper limit value and the lower limit value of the rated speed. The core of this process lies in setting reasonable speed thresholds for the current device through the mining and analysis of historical data, so as to accurately identify the starting and stopping processes of the device in subsequent monitoring. The control mode refers to different stages or states during the operation of the device, and each stage has its specific speed characteristics. The starting completion speed characteristic value and the stopping completion speed characteristic value respectively represent the stable speed values reached by the device during the starting process and the stopping process, and these values are of great significance for judging the starting and stopping states of the device. By setting the upper limit value and the lower limit value of the rated speed, it can be ensured that in subsequent monitoring, when the speed of the device falls within this interval, the full-volume storage strategy can be triggered, thereby accurately recording the operation data of the device.

[0018] Finally, a switching mechanism between full-volume storage and interval storage based on speed is set. When the system monitors the device speed data at the first moment, it will immediately make a speed value judgment, and this judgment is based on the lower limit value of the rated speed and the upper limit value of the rated speed obtained through historical data statistical analysis before. If the currently monitored speed exactly falls within the interval defined by these two thresholds, it means that the device may be in key operation stages such as starting or stopping, so the full-volume storage mode will be immediately started. In the full-volume storage mode, all operation data of the device at this stage will be continuously and exhaustively recorded to ensure the integrity and accuracy of the data for subsequent in-depth analysis and research. However, if the currently monitored speed does not fall within the above interval, that is, the device is in the normal operation state, then in order to save storage space and improve storage efficiency, interval storage will be executed according to the preset cycle. In the interval storage mode, the operation data of the device will be selectively recorded according to the established time interval or data interval, thus ensuring the overall performance and response speed of the system while meeting the data storage requirements. The design of this mechanism aims to balance the relationship between data integrity and storage efficiency to meet the monitoring requirements in different scenarios.

[0019] In a preferred embodiment, when the rotational speed monitored by the device at the first moment falls between the lower limit value and the upper limit value of the rated rotational speed, full-scale storage is started, including: obtaining the rotational speed monitored by the device at the second moment; when the rotational speed monitored by the device at the second moment minus the rotational speed monitored by the device at the first moment is greater than 0, it is regarded as belonging to the start-up process; when the rotational speed monitored by the device at the second moment minus the rotational speed monitored by the device at the first moment is less than 0, it is regarded as belonging to the shutdown process; when belonging to the start-up process or the shutdown process, continue to perform the full-scale storage.

[0020] Specifically, in the initial stage of device operation monitoring, the rotational speed data at the first moment is immediately captured and compared with the preset lower limit value and upper limit value of the rated rotational speed. If the rotational speed data happens to be between these two thresholds, the full-scale storage mode is immediately started to start recording in detail the operation data of the device at this critical stage. Then, continue to monitor and record the rotational speed data at the second moment. By analyzing the difference between the rotational speed data at the first moment and the second moment, the operation state of the device can be intelligently identified. If the rotational speed at the second moment is higher than that at the first moment, that is, the rotational speed increases and the rotational speed difference is greater than 0, it is judged that the device is in the start-up process; on the contrary, if the rotational speed at the second moment is lower than that at the first moment, that is, the rotational speed decreases and the rotational speed difference is less than 0, it is determined that the device is in the shutdown process. In both of these cases, the full-scale storage mode will be maintained to ensure that all operation details of the device during the critical time period of start-up or shutdown can be completely captured and recorded, so as to conduct in-depth analysis on aspects such as the performance, stability and fault warning of the device in the future. This process reflects the sensitive response and accurate identification ability to the change of the device operation state.

[0021] In a preferred embodiment, when the rotational speed monitored by the device at the first moment falls between the lower limit value and the upper limit value of the rated rotational speed, full-scale storage is started, including: obtaining the rotational speed monitored by the device at the second moment at at least 5 time steps until the rotational speed monitored by the device at the Nth moment, constructing the time series data of the rotational speed monitored by the device; through the development trend discriminator, judging the development trend type of the time series data of the rotational speed monitored by the device; when the development trend type belongs to the climbing trend, it is regarded as belonging to the start-up process; when the development trend type belongs to the descending trend, it is regarded as belonging to the shutdown process; when the development trend type belongs to the operation trend, it is regarded as belonging to the operation process; when belonging to the start-up process or the shutdown process, continue to perform the full-scale storage monitoring, and when belonging to the operation process, perform interval storage according to the preset period.

[0022] Optionally, in the full - volume storage mode, the rotational speed data of the device for at least 5 consecutive time steps (i.e., from the second moment to the Nth moment) will be continuously monitored and recorded. These time - series data together constitute the change curve of the device's rotational speed. Subsequently, the built - in trend discriminator will conduct in - depth analysis on this rotational speed time - series data to accurately determine the type of development trend the device is currently in. The trend discriminator is an intelligent component used to determine the type of development trend of the device's monitored rotational speed time - series data. It can intelligently identify the current development trend of the device based on the rotational speed data at consecutive time steps. The discriminator can intelligently identify three main trends: one is the climbing trend, that is, the rotational speed gradually increases, which usually indicates that the device is in the startup process; the second is the descending trend, that is, the rotational speed gradually decreases, which often means that the device is undergoing a shutdown process; the third is the operation trend, that is, the rotational speed fluctuates within a relatively stable range, indicating that the device has entered the normal operation state. Based on the analysis results of the discriminator, the system will make corresponding adjustments to the storage strategy: if it is determined to be in the startup process or shutdown process, continue to maintain the full - volume storage mode to ensure that all operation details of these key stages can be comprehensively captured and recorded; if it is determined to be in the operation process, in order to save storage space and improve efficiency, switch to interval storage according to the preset period. This process design not only reflects the sensitive capture and accurate judgment of the changes in the device's operation state but also ensures the rationality and efficiency of the data storage strategy.

[0023] In a preferred embodiment, by using the trend discriminator to determine the type of development trend of the device's monitored rotational speed time - series data, it includes: configuring the rotational speed record time - series data of the device for at least 5 time steps; when the rotational speed at the tail of the device's rotational speed record time - series data minus the rotational speed at the head is greater than 0, and the data at the moment exceeding the preset ratio is in an upward trend, marking the device's rotational speed record time - series data as the climbing trend; when the rotational speed at the tail of the device's rotational speed record time - series data minus the rotational speed at the head is less than 0, and the data at the moment exceeding the preset ratio is in a downward trend, marking the device's rotational speed record time - series data as the descending trend; otherwise, marking the device's rotational speed record time - series data as the operation trend; based on the marked data and the device's rotational speed record time - series data, training the trend discriminator based on machine learning.

[0024] Further, to implement the discrimination function of the development trend discriminator, first, configure the sequential data of the equipment rotation speed record containing at least 5 consecutive time steps as the input. These data form a curve of the equipment rotation speed changing with time, providing a basis for the discriminator to analyze. Next, the discriminator will analyze the sequential data according to specific logical rules. Specifically, it will calculate the difference between the rotation speed at the tail (i.e., the latest moment) and the rotation speed at the head (i.e., the earliest moment) of the sequential data, and judge the development trend of the rotation speed based on this difference and a preset proportional threshold. If the rotation speed at the tail is higher than that at the head, and the moment data exceeding the preset proportion all show an upward trend, then the discriminator will label this sequential data as a climbing trend, which usually means the equipment is in the starting stage. On the contrary, if the rotation speed at the tail is lower than that at the head, and the moment data exceeding the preset proportion all show a downward trend, then the discriminator will label it as a downward trend, which usually indicates that the equipment is shutting down. If neither of the above two situations is satisfied, then the discriminator will default to label it as an operating trend, that is, the equipment is in a normal operating state. To continuously improve the accuracy and generalization ability of the discriminator, based on the above-labeled data and the sequential data of the equipment rotation speed record, machine learning technology is used for training. By continuously iterating and optimizing the model parameters, the discriminator can learn more features and rules about the development trend of the equipment rotation speed, so as to achieve more accurate and reliable discrimination in practical applications. This process not only improves the sensitivity to changes in the equipment operating state, but also provides strong support for subsequent data storage, analysis, and fault warning, etc.

[0025] In a preferred embodiment, based on the equipment model, the list of transmission element models, and the list of service life of transmission elements of the equipment to be monitored, query fault tolerance conditions are constructed, including: when the sample equipment model is inconsistent with the equipment model, it is regarded as not meeting the first fault tolerance condition; when the sample list of transmission element models is inconsistent with the list of transmission element models, it is regarded as not meeting the second fault tolerance condition; a service state deviation function is constructed: ; Where represents the deviation value between the sample list of service life of transmission elements and the list of service life of transmission elements, represents the number of transmission element models, represents the service life of the model transmission element, represents the service life of the sample model transmission element, Service deviation threshold of the model transmission element; when the output value of the service status deviation function is greater than or equal to the deviation threshold, it is considered that the third fault tolerance condition is not met; the first fault tolerance condition, the second fault tolerance condition and the third fault tolerance condition are logically AND configured to obtain the query fault tolerance condition.

[0026] Specifically, when constructing the query fault tolerance condition for the device with the bit number to be monitored, the device model, the list of transmission element models and the list of service years of transmission elements of this device will be referred to first. This process aims to ensure the accuracy and practicality of the query results, and can screen out suitable samples even in the case of incomplete matching. First, check whether the model of the sample device is exactly the same as that of the device to be monitored. If not, it is considered that the first fault tolerance condition is not met, which means that the difference in device models is regarded as an important mismatch factor. Secondly, compare the list of sample transmission element models with the list of transmission element models of the device to be monitored. If there is any inconsistency between the two, that is, the sample is missing or contains transmission element models not listed in the device to be monitored, it is considered that the second fault tolerance condition is not met. This step ensures the consistency of the transmission element models, because different transmission elements may significantly affect the performance and operating status of the device. In addition to model matching, a service status deviation function will be constructed to evaluate the deviation of the service years of transmission elements. This function will calculate the deviation value between the list of service years of sample transmission elements and the list of service years of transmission elements of the device to be monitored, taking into account the number of transmission element models, the difference between the actual service years of each type of transmission element and the sample service years, and the predefined service deviation threshold for each type of transmission element. If the output value of the service status deviation function is greater than or equal to the preset deviation threshold, it is considered that the third fault tolerance condition is not met, indicating that there is a significant inconsistency between the sample and the device to be monitored in terms of the service years of transmission elements. The specific formula of the service status deviation function is: ; where, characterizes the deviation value between the list of service years of sample transmission elements and the list of service years of transmission elements, characterizes the number of transmission element models, characterizes the service years of the model transmission element, characterizes the service years of the sample Service deviation threshold of the model transmission component. Finally, these three fault tolerance conditions are configured with a logical AND, that is, only when all conditions are met, the sample is considered to meet the query fault tolerance conditions. This process ensures that even in the face of incomplete matches, samples that are closest to the device to be monitored in terms of device model, transmission component model, and service life of the transmission component can be screened out, thereby improving the accuracy and practicality of the query results.

[0027] In a preferred embodiment, as Figure 2 shown, retrieving a historical operation sample group that meets the query fault tolerance conditions includes: retrieving a first historical operation sample set that meets the query fault tolerance conditions in the first control mode, where any historical operation sample in the first historical operation sample set has a first transmission component service life record list; updating the query fault tolerance conditions based on the transmission component service life record list, traversing the first historical operation sample set to retrieve a second historical operation sample set that meets the updated query fault tolerance conditions; adding the first historical operation sample set and the second historical operation sample set into the historical operation sample group; until the retrieval is completed in the th control mode, and outputting the historical operation sample group, where represents the total number of control modes.

[0028] Preferably, after constructing the query fault tolerance conditions for the device to be monitored at the tag position, the retrieval process of the historical operation sample group is started. This process aims to screen out a sample set that is closest to the device to be monitored in key features from a large amount of historical data for subsequent analysis and reference. First, retrieve the historical operation samples in the first control mode and screen out the first historical operation sample set that meets the initial query fault tolerance conditions. Each historical operation sample in these sample sets contains a detailed transmission component service life record list, which details the service life of each transmission component and is an important basis for updating the query fault tolerance conditions subsequently. Then, update the initial query fault tolerance conditions based on these transmission component service life record lists. The purpose of the update is to further refine the screening criteria to further screen out samples that are more in line with the current state of the device to be monitored from the first historical operation sample set. After the update is completed, traverse the first historical operation sample set to retrieve the second historical operation sample set that meets the updated query fault tolerance conditions. Then, merge the first historical operation sample set and the second historical operation sample set to jointly form a part of the historical operation sample group in the current control mode. This process ensures that even in the face of complex and changeable device states, the true state of the device to be monitored can be gradually approximated through gradually refined screening criteria. Repeat the above steps until all The historical operation samples under all control modes have been retrieved. During this process, the query fault tolerance conditions are continuously updated according to new information to ensure that the selected sample set can comprehensively and accurately reflect the operation status of the device to be monitored under different control modes. Finally, a set containing the historical operation samples under all control modes, namely the historical operation sample group, is output, providing strong data support for subsequent analysis and research.

[0029] In a preferred embodiment, several starting completion speed characteristic values of the historical operation sample group are statistically analyzed, and the minimum value is taken and set as the rated speed upper limit value, including: grouping the second historical operation sample set according to the first historical operation sample set to obtain multiple groups of second historical operation samples; traversing the multiple groups of second historical operation samples for starting completion speed central tendency analysis to obtain multiple starting completion speed central values of the second historical operation samples; performing central tendency analysis on the multiple starting completion speed central values of the second historical operation samples and the starting completion speed values of the first historical operation samples in the first historical operation sample set to obtain the starting completion speed characteristic value of the first control mode, and adding it to the several starting completion speed characteristic values.

[0030] Exemplarily, in order to determine the upper limit value of the rated speed of the device, the second historical operation sample set is grouped according to the first historical operation sample set. The purpose of this is to analyze the starting completion speed characteristics between different samples at a finer granularity level. Each group of the second historical operation samples is divided based on its similarity to a certain sample in the first historical operation sample set. This similarity may be reflected in multiple dimensions such as device model, transmission element model, or service life. Next, traverse these grouped second historical operation samples and perform a central tendency analysis on the starting completion speed of each group. This step aims to extract the central point of the starting completion speed in each group of samples, that is, the value that best represents the starting completion speed level of this group of samples, namely the central value of the starting completion speed of the second historical operation samples. Through this analysis, the general characteristics of the device's starting completion speed under different groupings can be captured. Subsequently, these central values of the starting completion speed of the second historical operation samples are merged with the starting completion speed values of each sample in the first historical operation sample set, and a central tendency analysis is performed again. The purpose of this analysis is to obtain the overall characteristic value of the device's starting completion speed in the first control mode, which can comprehensively reflect the general level of the device's starting completion speed in this control mode. Add this characteristic value to the set of starting completion speed characteristic values of several control modes for subsequent comparison and analysis. Through the above process, a set containing the starting completion speed characteristic values of the device under multiple control modes can be gradually constructed. Finally, select the minimum value from this set and set it as the upper limit value of the rated speed of the device. The logic behind this setting is that among all control modes, the lowest value of the device's starting completion speed represents its performance under the most adverse conditions. Therefore, setting this value as the upper limit value of the rated speed can ensure that the device will not exceed the upper limit of its design performance under any control mode.

[0031] In a preferred embodiment, to statistically obtain the starting completion speed characteristic values of several control modes of the historical operation sample group and take the minimum value as the upper limit value of the rated speed, it includes: obtaining an initial upper limit value of the rated speed; when the minimum value of the starting completion speed characteristic values of several control modes is less than or equal to the initial upper limit value of the rated speed, setting the initial upper limit value of the rated speed as the upper limit value of the rated speed; when the minimum value of the starting completion speed characteristic values of several control modes is greater than the initial upper limit value of the rated speed, setting the minimum value as the upper limit value of the rated speed.

[0032] Preferably, after obtaining the starting completion speed characteristic values under several control modes through statistics, an initial rated speed upper limit value is preset, which may be determined based on factors such as the design specifications of the equipment, historical operation experience, or industry standards. The setting of the initial value aims to provide a reference point for subsequent adjustments. Subsequently, the minimum value among these starting completion speed characteristic values of the control modes is compared with the initial rated speed upper limit value. The purpose of this step is to identify the lowest stable speed level that the equipment can reach after starting under all control modes and compare it with the preset rated speed upper limit value to ensure that the setting of the rated value is neither too conservative (restricting the normal performance of the equipment) nor too loose (possibly causing the equipment to exceed the safe operating range under extreme conditions). If the minimum value among the starting completion speed characteristic values of several control modes is less than or equal to the initial rated speed upper limit value, it indicates that the preset rated value is already loose enough to cover the lowest stable speed of the equipment under all control modes. Therefore, keep the initial rated speed upper limit value unchanged and use it as the final rated speed upper limit value. However, if the minimum value among the starting completion speed characteristic values of several control modes is greater than the initial rated speed upper limit value, it means that the preset rated value is too conservative and cannot reflect the actual performance of the equipment under some control modes. In this case, set the minimum value as the new rated speed upper limit value to ensure that the setting of the rated value is closer to the actual operating condition of the equipment. Through the above process, the rated speed upper limit value of the equipment can be dynamically adjusted and determined based on the data in the historical operation sample group, providing strong support for the safe operation and performance optimization of the equipment.

[0033] In a preferred embodiment, the maximum value of the shutdown completion speed characteristic values of several control modes of the historical operation sample group is statistically obtained and set as the rated speed lower limit value, including: obtaining an initial rated speed lower limit value; when the maximum value of the shutdown completion speed characteristic values of several control modes is greater than or equal to the initial rated speed lower limit value, setting the initial rated speed lower limit value as the rated speed lower limit value; when the maximum value of the shutdown completion speed characteristic values of several control modes is less than the initial rated speed lower limit value, setting the maximum value as the rated speed lower limit value.

[0034] Specifically, when determining the lower limit value of the rated speed of the equipment, it is necessary to statistically obtain the shutdown completion speed characteristic values under each control mode from the historical operation sample group. These characteristic values represent the level at which the speed of the equipment gradually decreases and finally stabilizes during the shutdown process under different control modes, and are an important basis for evaluating the shutdown performance of the equipment and determining the safe speed range. Before starting the statistics, an initial lower limit value of the rated speed is preset. This value is usually obtained based on the design specifications of the equipment, safety operation requirements, and analysis of historical operation data, aiming to ensure that the equipment will not cause safety problems due to too low speed during the shutdown process. Next, a comparative analysis is carried out on the shutdown completion speed characteristic values of each control mode statistically obtained, and the maximum value among them is extracted. This maximum value represents the highest stable level that the speed of the equipment may reach after shutdown under all control modes. Subsequently, this maximum value is compared with the preset initial lower limit value of the rated speed. If the maximum value is greater than or equal to the initial lower limit value of the rated speed, it indicates that the preset rated lower limit value is already loose enough to cover the highest shutdown completion speed of the equipment under all control modes. In this case, the initial lower limit value of the rated speed remains unchanged and is used as the final lower limit value of the rated speed. However, if the maximum value is less than the initial lower limit value of the rated speed, this means that the preset rated lower limit value is too conservative and may limit the normal shutdown process of the equipment under certain control modes. In order to be closer to the actual operating conditions of the equipment, the system will set this maximum value as the new lower limit value of the rated speed. Through the above process, the lower limit value of the rated speed of the equipment can be dynamically adjusted and determined based on the data in the historical operation sample group, so as to ensure that the equipment can maintain a safe and reasonable speed range during the shutdown process, providing a strong guarantee for the stable operation and extended service life of the equipment.

[0035] The full-volume storage method of equipment operation data based on equipment speed monitoring provided by the embodiments of the present invention has at least the following technical effects: 1. By comprehensively considering multi-dimensional information such as the equipment model of the equipment to be monitored, the list of transmission element models, and the list of transmission element service life, refined query fault tolerance conditions are constructed. This multi-dimensional consideration method not only improves the accuracy of historical operation sample retrieval but also can effectively cope with various complex situations that occur during the actual operation of the equipment. By introducing the service state deviation function, the matching requirements for the service life of transmission elements are further refined, making the retrieved historical operation samples closer to the actual state of the equipment to be monitored and providing strong data support for subsequent analysis and decision-making.

[0036] 2. Dynamically adjust the data storage strategy according to the relationship between the real-time monitored rotation speed of the device and the preset upper and lower limits of the rated rotation speed. When the monitored rotation speed of the device is between the upper and lower limits of the rated rotation speed, the system starts full-volume storage to capture the key data changes during the startup and shutdown processes of the device. When the monitored rotation speed of the device exceeds this range, interval storage is performed according to the preset period to reduce the redundancy and cost of data storage while ensuring data integrity. This dynamically adjusted storage strategy not only improves the efficiency of data storage but also helps to detect the abnormal operating state of the device in a timely manner.

[0037] 3. A development trend discriminator is introduced to further refine the applicable scenarios of full-volume storage and interval storage by intelligently identifying the development trend of the time-series data of the device's monitored rotation speed. During the startup and shutdown processes, since the rotation speed of the device changes violently, full-volume storage is required to capture this key data. During the operation process, the rotation speed of the device is relatively stable, so interval storage can be performed according to the preset period. This storage optimization strategy based on development trend discrimination not only improves the pertinence of data storage but also helps to reduce unnecessary data storage overhead and enhance the overall efficiency of data storage.

[0038] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for storing the entire amount of equipment operation data based on equipment speed monitoring, characterized in that: include: Construct query fault tolerance conditions based on the equipment model, transmission component model list and transmission component service life list of the equipment with the bit number to be monitored; Retrieving a historical running sample group that meets the query fault tolerance condition; Counting the speed characteristic values ​​of several control modes starting up and completing the historical operation sample group, taking the minimum value, and setting it as the upper limit of the rated speed; counting the speed characteristic values ​​of several control modes stopping and completing the historical operation sample group, taking the maximum value, and setting it as the lower limit of the rated speed; When the device monitors the rotation speed at the first moment and it falls between the lower limit value of the rated rotation speed and the upper limit value of the rated rotation speed, full storage is started, otherwise, interval storage is performed according to a preset period.

2. The method according to claim 1, characterized in that When the speed monitored by the device at the first moment falls between the lower limit of the rated speed and the upper limit of the rated speed, full storage is started, including: Get the monitoring speed of the device at the second moment; When the speed monitored by the device at the second moment minus the speed monitored by the device at the first moment is greater than 0, it is considered to be in the startup process; When the speed monitored by the device at the second moment minus the speed monitored by the device at the first moment is less than 0, it is considered to be in the shutdown process; When it belongs to the startup process or the shutdown process, the full storage continues to be executed.

3. The method according to claim 2, characterized in that When the speed monitored by the device at the first moment falls between the lower limit of the rated speed and the upper limit of the rated speed, full storage is started, including: Obtain the device monitoring speed at the second moment of at least 5 time steps until the device monitoring speed at the Nth moment, and construct the device monitoring speed time series data; Determine the development trend type of the speed time series data monitored by the device through a development trend discriminator; When the development trend type belongs to an upward trend, it is considered to be in the start-up process; When the development trend type is a downward trend, it is considered to be a shutdown process; When the development trend type belongs to the operation trend, it is considered to belong to the operation process; When it belongs to the startup process or the shutdown process, the full storage monitoring continues to be performed; when it belongs to the operation process, interval storage is performed according to a preset period.

4. The method according to claim 3, characterized in that The development trend type of the speed time series data monitored by the device is determined by the development trend discriminator, including: Configure the equipment speed record time series data with at least 5 time steps; When the tail speed minus the head speed of the equipment speed recording time series data is greater than 0, and the data at the time exceeding the preset ratio is in an upward trend, the equipment speed recording time series data is marked as a climbing trend; When the tail speed minus the head speed of the device speed recording time series data is less than 0, and the data exceeding the preset ratio is in a downward trend, the device speed recording time series data is marked as a downward trend; Otherwise, the time series data of the equipment speed record is marked as an operation trend; The development trend discriminator is trained based on machine learning according to the identification data and the time series data of the equipment rotation speed record.

5. The method according to claim 1, characterized in that Based on the equipment model, transmission component model list and transmission component service life list of the equipment with the tag number to be monitored, build the query fault tolerance conditions, including: When the sample device model is inconsistent with the device model, it is deemed that the first fault tolerance condition is not met; When the sample transmission element model list is inconsistent with the transmission element model list, it is deemed that the second fault tolerance condition is not met; Construct the service status deviation function: ； in, Characterizes the deviation between the service life list of the sample transmission components and the service life list of the transmission components, Characterize the number of transmission component models, Characterization Model Transmission component service life, Characterization Sample Model Transmission component service life, Characterize the predefined Model transmission component service deviation threshold; When the output value of the service status deviation function is greater than or equal to the deviation threshold, it is deemed that the third fault tolerance condition is not met; Perform a logical AND configuration on the first fault-tolerant condition, the second fault-tolerant condition, and the third fault-tolerant condition to obtain the query fault-tolerant condition.

6. The method according to claim 1, characterized in that Retrieving a historical running sample group that meets the query fault tolerance condition includes: Retrieving a first set of historical operation samples under a first control mode that meets the query fault tolerance condition, wherein any one of the historical operation samples in the first set of historical operation samples has a service life record list of a first transmission element; Based on the service life record list of the transmission element, the query fault tolerance condition is updated, and the first historical operation sample set is traversed to retrieve a second historical operation sample set that meets the updated query fault tolerance condition; Adding the first historical operation sample set and the second historical operation sample set into the historical operation sample group; Until the The retrieval is completed in the control mode, and the historical operation sample group is output, wherein: Characterizes the total number of control modes.

7. The method according to claim 6, characterized in that The speed characteristic values ​​of several control mode startup completions of the historical operation sample group are counted, and the minimum value is taken as the rated speed upper limit value, including: According to the first historical operation sample set, grouping the second historical operation sample set to obtain multiple groups of second historical operation samples; Traversing the plurality of groups of second historical operation samples to perform a concentrated trend analysis of the startup completion speed, and obtaining a plurality of concentrated values ​​of the startup completion speed of the second historical operation samples; A central trend analysis is performed on the multiple second historical operation sample startup completion speed concentrated values ​​and the first historical operation sample startup completion speed value of the first historical operation sample set to obtain a first control mode startup completion speed characteristic value, which is added to the several control mode startup completion speed characteristic values.

8. The method according to claim 1, characterized in that The speed characteristic values ​​of several control mode startup completions of the historical operation sample group are counted, and the minimum value is taken as the rated speed upper limit value, including: Obtain the initial rated speed upper limit value; When the minimum value of the speed characteristic values ​​after the start-up of a plurality of control modes is less than or equal to the initial rated speed upper limit value, the initial rated speed upper limit value is set as the rated speed upper limit value; When the minimum value of the speed characteristic values ​​after the start-up of several control modes is greater than the initial rated speed upper limit value, the minimum value is set to the rated speed upper limit value.

9. The method according to claim 1, characterized in that The characteristic values ​​of the shutdown completion speed of several control modes of the historical operation sample group are counted, and the maximum value is taken and set as the lower limit of the rated speed, including: Obtain the initial rated speed lower limit value; When the maximum value of the speed characteristic values ​​of the plurality of control mode shutdown completions is greater than or equal to the initial rated speed lower limit value, the initial rated speed lower limit value is set as the rated speed lower limit value; When the maximum value of the speed characteristic values ​​of the shutdown completion of several control modes is less than the initial rated speed lower limit value, the maximum value is set to the rated speed lower limit value.

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