Early warning information processing method and device, equipment and storage medium

Abstract

The embodiment of the invention discloses an early warning information processing method and device, equipment and a storage medium. The method comprises the steps that to-be-processed first early warning information for at least one piece of equipment is determined; based on the first time interval, aggregating the early warning information of the same equipment and the same fault type in the first early warning information, and determining first aggregated information; and under the condition that first historical early warning information with the same equipment and the same fault type as the first aggregation information is queried in the historical fault data, aggregating the first aggregation information with the first historical early warning information based on the first time interval to obtain fault early warning data. According to the invention, through aggregation of the early warning information, the processing efficiency of fault early warning is effectively improved.

Description

Technical Field

[0001] This application relates to, but is not limited to, the field of battery technology, and particularly to a method, apparatus, device, and storage medium for processing early warning information. Background Technology

[0002] With the vigorous promotion of new energy sources, large-scale energy storage systems are being used more and more. Ensuring the safe operation of these systems has become a major challenge in the field. Safe operation requires not only design improvements in individual battery cells and the battery system itself, but also accurate identification and early warning of abnormal battery or cell conditions to enable prompt equipment repair.

[0003] Currently, battery fault warnings are mainly based on data analysis and algorithmic judgment of battery measurement data, such as voltage, current and temperature. The algorithm results are then compared with the set warning thresholds to identify abnormal batteries and report fault warnings.

[0004] However, on the one hand, due to the significant differences in operating conditions of batteries in energy storage systems and the complexity of their electrochemical processes, a large number of redundant warning messages are reported, resulting in duplicate reporting and reducing the efficiency of fault warning processing. On the other hand, for some batteries exhibiting abnormalities, fault warning messages are continuously reported to the battery cloud platform before repairs, leading to an overabundance of fault warning messages and further reducing processing efficiency. Summary of the Invention

[0005] This application provides a method, apparatus, device, and storage medium for processing early warning information, which can improve the processing efficiency of fault early warning.

[0006] The technical solution of this application embodiment is implemented as follows:

[0007] In a first aspect, embodiments of this application provide a method for processing early warning information, the method comprising:

[0008] A first warning message to be processed is identified for at least one device; based on a first time interval, warning messages with the same device and the same fault type in the first warning message are aggregated to determine the first aggregated message; if a first historical warning message with the same device and the same fault type as the first aggregated message is found in the historical fault data, the first aggregated message is aggregated with the first historical warning message based on the first time interval to obtain fault warning data.

[0009] Understandably, on the one hand, the first warning information to be processed indicates an equipment malfunction in the energy storage system. This first warning information may contain multiple warnings for the same fault, meaning there may be redundant warnings. By filtering warnings with the same equipment and fault type, and then aggregating the filtered first warnings based on a first time interval, multiple warnings for the same fault are aggregated to form aggregated information, thus identifying fault warning data. This reduces redundant reporting of warnings and effectively improves the processing efficiency of fault warning information. On the other hand, the first aggregated information is the first aggregated information within the current first preset time period, while historical fault warning data is the fault warning data within the previous first preset time period. If historical fault warning data contains first historical warnings with the same equipment and fault type as the first aggregated information, then the first aggregated information and the first historical warning information are considered duplicate warnings for the same fault. Aggregating warnings for the same fault within different first preset time periods improves the effectiveness of warning information aggregation.

[0010] In some embodiments, the method further includes: determining a first time interval based on real-time usage data of at least one device; the usage data includes at least one of the following: ambient temperature, usage frequency, and charge / discharge cycle.

[0011] Understandably, the aging process of equipment is non-linear and complex, influenced by multiple factors, primarily usage data such as frequency of use, ambient temperature, and charge / discharge cycles. Therefore, determining the first time interval based on usage data and dynamically adjusting it according to the actual condition of the equipment effectively ensures the accuracy of the first time interval.

[0012] In some embodiments, the method further includes: assigning a first weight to different warning messages in the first warning message according to their credibility; the credibility is positively correlated with the first weight; and performing weighted processing on the warning messages corresponding to the first weight to aggregate warning messages of the same device and the same fault type to determine the first aggregated information.

[0013] Understandably, the validity and accuracy of the first warning information are judged based on its credibility. Different first weights are assigned to different warning information based on their credibility levels, so that more credible warning information has higher weights. Thus, the aggregation of different warning information after weighted processing improves the effectiveness of the aggregation.

[0014] In some embodiments, the method further includes: using a time-based aggregation network to aggregate warning information of the same device and the same fault type in the first warning information to determine the first aggregated information.

[0015] Understandably, considering the non-linear aging characteristics of equipment, an aggregation network based on time is used to predict the aging data of the equipment. Based on the prediction results, early warning information of the same equipment and the same fault type in the first early warning information is aggregated to improve the accuracy of the aggregation results.

[0016] In some embodiments, determining the first warning information to be processed for at least one device includes: performing fault correlation analysis on the initial warning information to be processed for at least one device, fusing the warning information that has a correlation in the initial warning information, and determining the first warning information; the fault correlation analysis is used to identify potentially correlated information in the warning information.

[0017] Understandably, by performing fault correlation analysis on the warning information to be processed in advance, and filtering out the warning information that may be related as the first warning information, the effectiveness of the first warning information is ensured, thereby improving the accuracy of aggregation.

[0018] In some embodiments, the method further includes: filtering the initial warning information to be processed from at least one device, removing erroneous warning information, and determining the first warning information.

[0019] It is understandable that the initial warning information to be processed may contain erroneous warnings, for example, warnings caused by noise or false alarms. Therefore, removing erroneous warnings in advance from the initial warning information ensures the effectiveness of the initial warning information, thereby improving the accuracy of the first warning information.

[0020] In some embodiments, the method further includes: processing the initial warning information to be processed based on multi-dimensional attribute information and scene information of at least one device to determine the first warning information.

[0021] Understandably, by using the device's attribute information and scenario information to process the initial warning information to form the first warning information, the accuracy of fault aggregation using the first warning information is improved.

[0022] In some embodiments, the method further includes: performing data cleaning and / or data imputation on the initial warning information to be processed, and determining the first warning information, wherein data cleaning instructs the deletion of duplicate and erroneous warning information in the initial warning information, and data imputation instructs the addition of warning information missing in the initial warning information.

[0023] Understandably, preprocessing the initial warning information removes duplicate and erroneous warnings, eliminating or correcting these issues and ensuring the completeness and accuracy of the warnings. Adding and filling in missing warning information reduces the impact of sparsity in the initial warning data, thereby improving the effectiveness and accuracy of the initial warnings.

[0024] In some embodiments, the multi-dimensional attribute information of at least one device includes the chemical composition and production batch of at least one device; the multi-dimensional scenario information of at least one device includes the usage scenario and operating environment of at least one device; based on the multi-dimensional attribute information and scenario information of at least one device, the initial warning information to be processed is processed to determine the first warning information, including: based on at least one attribute information of at least one device, the warning information with the same attribute information in the initial warning information to be processed is fused to determine the first fused information; based on at least one scenario information of at least one device, the warning information with the same scenario information in the first fused information is fused to determine the first warning information.

[0025] Understandably, by using the device's attribute information and scene information to fuse the initial warning information to be processed into the first warning information, the accuracy of fault aggregation using the first warning information is improved.

[0026] In some embodiments, determining the first warning information to be processed for at least one device includes: when a first preset time period is reached, acquiring incremental data in the fault warning record to obtain the first warning information for at least one device.

[0027] Understandably, using a timed (first preset time period) processing method to read incremental data from the fault warning record reduces data congestion caused by continuous data reading, ensuring data reading throughput and low coupling.

[0028] In some embodiments, based on a first time interval, the early warning information of the same device and the same fault type in the first early warning information is aggregated to determine the first aggregated information, including: determining at least two sets of early warning information of the same device and the same fault type in the first early warning information; if, in each set of early warning information, multiple early warning information that are adjacent in time according to the time sequence are less than the first time interval, the multiple early warning information are aggregated to determine the first aggregated information.

[0029] Understandably, grouping the first warning information based on the principle of similar equipment and fault type increases the convenience of subsequent aggregation and judgment. Within the same group, multiple warning information is aggregated based on a first time interval, that is, multiple warning information belonging to the same fault are aggregated to generate a first aggregated information, reducing the repeated reporting of redundant warning information and effectively improving the efficiency of fault warning.

[0030] In some embodiments, if multiple warning messages in each group of warning messages are adjacent in time and their time intervals are less than a first time interval, then the multiple warning messages are aggregated to determine the first aggregated information, including: if multiple warning messages in each group of warning messages are adjacent in time and their time intervals are less than a first time interval, then the earliest occurrence time, latest end time, and highest fault level among the multiple warning messages are determined as the fault occurrence time, fault end time, and fault level of an aggregated information; until multiple aggregations in each group of warning messages are completed, the first aggregated information is determined.

[0031] It is understandable that the first aggregated information indicates that multiple first warning information entries participating in the aggregation are repeated reports of the same fault. By defining the fault occurrence time of the aggregated information as the earliest occurrence time of the same fault, the fault end time of the aggregated information as the latest end time of the same fault, and the fault level of the aggregated information as the highest fault level of the same fault, it is ensured that the first aggregated information can fully reflect the indication content of multiple warning information entries, thereby improving the accuracy of the first aggregated information.

[0032] In some embodiments, the method further includes: in response to a viewing instruction, displaying fault warning data and a details entry for the first warning information on the fault management interface.

[0033] Understandably, due to the visual design of the fault management interface, while displaying the aggregated fault warning data, it also provides an entry point for details of the first warning information before aggregation, so as to use when viewing the warning information before aggregation. Therefore, it improves the diversity of warning information display before and after aggregation.

[0034] In some embodiments, in response to a viewing instruction, the fault management interface displays fault warning data and a details entry for the first warning information, including: in response to a viewing instruction, the fault management interface displays at least one of the fault information, fault level, fault occurrence time, fault end time, device identifier, and fault status of the fault warning data, and a details entry for the first warning information.

[0035] Understandably, upon receiving the viewing command, the fault management interface displays fault warning data. This interface provides a more intuitive way to obtain fault information, fault level, fault occurrence time, fault end time, device identification, and fault status from the fault warning data, facilitating quick identification of the fault and improving the display effect, intuitiveness, and visibility of the fault warnings. Furthermore, it provides an entry point for details of the initial warning information before aggregation, allowing users to view the warning information before aggregation. Therefore, it enhances the diversity of information displayed before and after aggregation.

[0036] In some embodiments, the method further includes: in response to a trigger operation of the details entry, displaying fault details information of the first warning information and a historical information viewing entry on the fault analysis interface; the fault details information includes: the fault occurrence time and fault level of the first warning information; in response to a selection operation of the first warning information, displaying the selected first warning information in the fault analysis interface according to a first method; in response to a historical information viewing operation, displaying fault parameters under the fault type to which the selected first warning information belongs in the drop-down page of the fault analysis interface.

[0037] Understandably, responding to the details entry in the fault management interface triggers a jump to the fault analysis interface. The fault analysis interface displays the fault occurrence time and fault level of the first warning information contributing to the fault warning data. This allows for a more intuitive view of multiple warning messages with different times and fault levels aggregated within the same reported fault, enhancing the visualization and diversity of fault warnings. By viewing historical information, the dropdown menu in the fault analysis interface displays the fault parameters under the selected first warning information's fault type, facilitating fault cause location and analysis through these parameters. This enhances the effectiveness of providing fault information during the fault warning process.

[0038] In some embodiments, in response to the historical information viewing operation, the fault parameters under the fault type to which the selected first warning information belongs are displayed in the drop-down page of the fault analysis interface, including: in response to the historical information viewing operation, the fault parameters of the same device parameter at different times under the fault type to which the selected first warning information belongs are displayed in the drop-down page of the fault analysis interface.

[0039] Understandably, the dropdown menu in the fault analysis interface displays fault parameters for the first warning information at different times. These different times span from the fault occurrence time to the fault end time of the first warning information, covering the fault parameters for the entire time period of the first warning information. By obtaining fault parameters from different dimensions, the effectiveness and accuracy of fault information provided in fault warnings are improved.

[0040] In some embodiments, based on a first time interval, the first aggregated information and the first historical warning information are aggregated to obtain fault warning data, including: based on the first time interval, the earliest occurrence time, the latest end time and the highest fault level in the first aggregated information and the first historical warning information are determined as the fault occurrence time, fault end time and fault level of the fault warning data.

[0041] Understandably, since the first historical warning information and the first aggregated information are aggregated based on the first time interval, it indicates that the first historical warning information and the first aggregated information are reports of the same fault. The earliest occurrence time and the latest end time of the same fault are taken as the fault duration of the same fault, i.e., the fault duration of the fault warning data. Furthermore, the highest fault level among the first historical warning information and the first aggregated information is taken as the fault level of the same fault. Therefore, the accuracy of the warning time and fault level of the fault warning data is improved.

[0042] Secondly, embodiments of this application provide a processing apparatus for early warning information. The apparatus includes: determining early warning information to be processed for at least one device; and aggregating early warning information with the same battery and the same fault type in the first early warning information based on a first time interval to determine first aggregated information; and if a first historical early warning information with the same device and the same fault type as the first aggregated information is determined from historical fault early warning data, then the first aggregated information is aggregated with the first historical early warning information based on the first time interval to obtain fault early warning data.

[0043] Thirdly, embodiments of this application provide a device for processing early warning information, including a memory and a processor. The memory stores a computer program that can run on the processor, and the processor executes the program to implement the steps in the above-described method.

[0044] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the above-described method. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort, wherein:

[0046] Figure 1 An optional flowchart illustrating a method for processing early warning information provided in an embodiment of this application. Figure 1 ;

[0047] Figure 2 An optional aggregated schematic diagram of a method for processing early warning information provided in an embodiment of this application;

[0048] Figure 3 An optional flowchart illustrating a method for processing early warning information provided in an embodiment of this application. Figure 2 ;

[0049] Figure 4 An optional flowchart illustrating a method for processing early warning information provided in an embodiment of this application. Figure 3 ;

[0050] Figure 5 A schematic diagram of an optional fault analysis page for a method of processing early warning information provided in an embodiment of this application;

[0051] Figure 6 This application provides an embodiment of a method for processing early warning information, illustrating an optional historical information viewing page.

[0052] Figure 7 An optional freeze diagram illustrating a method for processing early warning information provided in an embodiment of this application;

[0053] Figure 8 An optional overdue shutdown diagram for a method of processing early warning information provided in an embodiment of this application;

[0054] Figure 9 An optional structural diagram of a method for processing early warning information provided in an embodiment of this application;

[0055] Figure 10 An exemplary flowchart of a method for processing early warning information provided in this application embodiment;

[0056] Figure 11 This is a schematic diagram of the structure of a warning information processing device provided in an embodiment of this application;

[0057] Figure 12 This is a schematic diagram of the structure of a warning information processing device provided in an embodiment of this application. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application are further described in detail below with reference to the accompanying drawings and embodiments. The described embodiments should not be regarded as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0059] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0060] It should be noted that the terms "first, second, and third" used in the embodiments of this application are merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that "first, second, and third" can be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0061] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which the embodiments of this application pertain. It should also be understood that terms such as those defined in general dictionaries should be understood to have a meaning consistent with their meaning in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0062] This application provides a method for processing early warning information, such as... Figure 1 As shown, the method may include S101 to S103:

[0063] S101. Determine the first warning information to be processed for at least one device.

[0064] In this embodiment of the application, in order to detect whether the equipment is operating normally, the reported or collected measurement point data or equipment data can be detected by the early warning information processing device or the early warning information processing device, i.e., the equipment cloud platform, to determine whether there are hidden dangers, abnormalities or malfunctions in the equipment. This embodiment of the application does not limit the type of equipment.

[0065] It should be noted that the device can be a battery or cell, or a component of a mobile device, etc., and the embodiments of this application are not limited thereto.

[0066] In the following embodiments, the battery in the energy storage system is used as the device, and the battery cloud platform is described as the device cloud platform.

[0067] In this embodiment, when the energy storage system's device detects an abnormal battery condition or triggers a predefined alarm condition, it generates a battery warning message (i.e., alarm data). This warning message is transmitted to the energy storage system's battery cloud platform. The battery cloud platform processes the warning message. The device can be a sensor, monitoring equipment, or a server, etc., and this embodiment does not impose any limitations. The battery cloud platform is the system or server responsible for receiving and processing the warning message.

[0068] It should be noted that the warning information received by the battery cloud platform may include duplicate reports of the same fault, and it is necessary to aggregate the duplicate warning information.

[0069] In this embodiment, the battery cloud platform reads incremental warning information from the fault warning record according to a first preset time period, for use in subsequent data warning processing. That is, the battery cloud platform reads incremental warning information from the fault warning record upon reaching the first preset time period. This incremental warning information is then identified as the first warning information.

[0070] Understandably, using a timed (first preset time period) processing method to read incremental data from the fault warning record reduces data congestion caused by continuous data reading, ensuring data reading throughput and low coupling.

[0071] In this embodiment, the first warning information may include warning information from multiple devices (e.g., a faulty battery) or multiple warning information of different types from the same device. The battery cloud platform obtains the first warning information to be processed for at least one device within a first preset time period by periodically reading the first warning information.

[0072] In some embodiments, the first warning information may include parameters such as fault information, fault level, fault occurrence time, fault end time, and device identifier. The fault information includes a fault code and a fault name. The fault code in the fault information is used to distinguish different fault types; warning information with the same fault code indicates the same fault type. The fault level may include multiple levels and multiple formats.

[0073] For example, fault levels are divided into three categories: alert, moderate, and severe. Fault levels can be represented by L1 for alert, L2 for moderate, and L3 for severe.

[0074] For example, the first preset time period is 3 days. The battery cloud platform retrieves warning information from the fault warning record at 16:00:23 on February 3, 2022 (fault occurrence time). At 16:00:23 on February 6, 2022 (fault end time), the battery cloud platform again retrieves warning information from the fault warning record within the time range of 16:00:23 on February 3, 2022 to 16:00:23 on February 6, 2022, and identifies it as the first warning information. This first warning information may include a warning message with fault code 601, fault name "Component Fault Alarm," fault level "Severe," fault occurrence time 16:00:23 on February 4, 2022, fault end time 17:00:23 on February 4, 2022, and device identifier 00110.

[0075] S102. Based on the first time interval, aggregate the warning information of the same device and the same fault type in the first warning information to determine the first aggregated information.

[0076] In this embodiment, when the battery cloud platform reads the first warning information, it groups warning information with the same device and the same fault type. The battery cloud platform identifies warning information with the same device and the same fault type as aggregation subjects, and each group may contain multiple aggregation subjects. The battery cloud platform uses a first time interval as a criterion for determining whether aggregation subjects can be aggregated. Based on the first time interval, the battery cloud platform aggregates multiple aggregation subjects that meet the aggregation criteria within the same group to form first aggregated information.

[0077] In this embodiment of the application, when multiple aggregated entities meet the first time interval condition, the battery cloud platform considers that the faults belonging to the multiple aggregated entities are the same faults. Therefore, the battery cloud platform will instruct multiple early warning information of the same faults to be aggregated to obtain the first aggregated information.

[0078] It should be noted that the aggregation of multiple warning messages can result in either successful aggregation or failure. In the case of successful aggregation, the first aggregated message is the warning message after successful aggregation; in the case of failure, the first aggregated message is the first warning message that participated in the aggregation.

[0079] In this embodiment, the first time interval is used as a condition for determining whether the aggregation subjects can be aggregated. If the reporting time interval of the early warning information of the aggregation subjects is less than the first time interval, it is considered that the faults belonging to multiple aggregation subjects are the same faults and need to be aggregated to determine one of the aggregation information in the first aggregation information. If the reporting time interval of the early warning information of the aggregation subjects exceeds the first time interval, it is considered that the faults belonging to multiple aggregation subjects are different faults and need not be aggregated. Instead, the multiple aggregation subjects can be directly determined as one of the aggregation information in the first aggregation information.

[0080] It should be noted that the warning reporting time can be either the time the fault occurred or the time the fault ended.

[0081] For example, if the first time interval is 3 days, and there are two warning messages, one reported on 2022-07-12 12:00:20 and the other reported on 2022-07-13 12:00:20, and both warning messages involve the same device and have the same fault type (i.e., they are two aggregated entities), then since the time interval between the two aggregated entities is less than 3 days, they can be aggregated to obtain the first aggregated information.

[0082] S103. If a first historical warning information with the same device and the same fault type as the first aggregated information is found in the historical fault data, the first aggregated information and the first historical warning information are aggregated based on a first time interval to obtain fault warning data.

[0083] In this embodiment, the battery cloud platform reads incremental warning information from the fault warning record every first preset time period. The warning information read within the current first preset time period is determined as the first warning information. First aggregated information is obtained by aggregating the first warning information. The fault warning data determined by the first aggregated information within the previous first preset time period is historical fault warning data. The first aggregated information within the current first preset time period is aggregated and judged with the historical fault warning data to determine the fault warning data.

[0084] The first warning information before aggregation is stored in the fault details table, and the fault warning data after aggregation is stored in the fault result table.

[0085] It should be noted that the warning information generated by the device is transmitted to the battery cloud platform via a communication mechanism. This communication mechanism can be a network connection. Examples include Message Queuing Telemetry Transport (MQTT) or Hypertext Transfer Protocol (HTTP); other proprietary protocols can also be used. Examples include Modbus Communication Protocol or Simple Network Management Protocol (SNMP).

[0086] It should be noted that the fault details table and the fault result table adopt a twin structure design, which can be optimized, expanded or modified independently without affecting each other, facilitating the writing of the first warning information after aggregation.

[0087] For example, a fault details table can be as shown in Table 1, and the fault details table can include field names, comments, and data types.

[0088] Table 1

[0089]

[0090]

[0091] In this embodiment, a first preset time period is set, and incremental warning information is read from the fault warning record using a timed reading method. The fault warning data generated within the first preset time period is stored in the fault result table. Therefore, within the current first preset time period, the fault result table contains multiple historical fault warning data from previous first preset time periods.

[0092] In this embodiment, when the first preset time period is reached, the battery cloud platform reads incremental warning information from the fault warning record and obtains first aggregated information through aggregation rules. After obtaining the first aggregated information, the battery cloud platform queries the historical fault data in the fault result table, that is, the historical fault data within the first preset time period. If there is a first historical warning information with the same battery and the same fault type as the first aggregated information, that is, the first historical warning information and the first aggregated information have an aggregation subject, the battery cloud platform aggregates the aggregation subject based on the judgment condition of the first time interval to form fault warning data.

[0093] It should be noted that the battery cloud platform will aggregate multiple warning messages with the same fault to obtain the first aggregated message. The result of aggregating multiple warning messages can be either successful or unsuccessful. If aggregation is successful, the first aggregated message is the warning message obtained after successful aggregation; if aggregation fails, the first aggregated message is the first warning message that participated in the aggregation.

[0094] In some embodiments, in the aggregation rules defined by the battery cloud platform, the fault occurrence time of the aggregated warning information is the earliest fault occurrence time among multiple aggregation subjects; the fault end time of the aggregated warning information is the latest fault end time among multiple aggregation subjects; and the fault level of the aggregated warning information is the highest fault level among multiple aggregation subjects.

[0095] In this embodiment of the application, if a first historical warning information with the same device and the same fault type as the first aggregated information is determined from the historical fault warning data, then based on the first time interval, the earliest occurrence time of the first aggregated information and the first historical warning information is determined as the fault occurrence time of the fault warning data; the latest end time of the first aggregated information and the first historical warning information is determined as the fault end time of the fault warning data; and the highest fault level of the first aggregated information and the first historical warning information is determined as the fault level of the fault warning data.

[0096] It should be noted that the reporting time of a fault can be either the time the fault occurred or the time the fault ended.

[0097] For example, such as Figure 2 As shown, the fault management interface displays five fault warning data entries. The dropdown menu for the first fault warning data entry, fault code 2402150000606629, shows that the data is aggregated from three entities. The three bars represent these three entities. The first entity reported the fault earliest (2024-02-15 17:01:03); the third entity reported the fault latest (2024-02-19 09:24:08); and the second entity has the highest fault severity level, "Severe" (L3). Therefore, based on the aggregation rules, the fault occurrence time of the aggregated fault warning data is 2024-02-15 17:01:03; the fault end time is 2024-02-19 09:24:08; and the fault severity level is "Severe" (L3).

[0098] Understandably, on the one hand, the first warning information to be processed indicates an equipment malfunction in the energy storage system. This first warning information may contain multiple warnings for the same fault, meaning there may be redundant warnings. By filtering warnings with the same equipment and fault type, and then aggregating the filtered first warnings based on a first time interval, multiple warnings for the same fault are aggregated to form aggregated information, thus identifying fault warning data. This reduces redundant reporting of warnings and effectively improves the processing efficiency of fault warning information. On the other hand, the first aggregated information is the first aggregated information within the current first preset time period, while historical fault warning data is the fault warning data within the previous first preset time period. If historical fault warning data contains first historical warnings with the same equipment and fault type as the first aggregated information, then the first aggregated information and the first historical warning information are considered duplicate warnings for the same fault. Aggregating warnings for the same fault within different first preset time periods improves the effectiveness of warning information aggregation.

[0099] In some embodiments, the method further includes: determining a first time interval based on real-time usage data of at least one device; the usage data includes at least one of the following: ambient temperature, usage frequency, and charge / discharge cycle.

[0100] In this embodiment, the first time interval can be adjusted according to the real-time usage data of the device. In this embodiment, the method of adjusting the first time interval is not limited. The adjustment can be to extend the first time interval as needed or to shorten the first time interval as needed.

[0101] In some embodiments, the adjustment of the first time interval can be achieved using time series analysis, such as neural network analysis methods. Time series analysis is used to predict equipment aging data, thereby adjusting the first time interval.

[0102] In this application embodiment, the real-time usage data of the device is not limited, and can be ambient temperature, usage frequency, or charge / discharge cycle.

[0103] In this embodiment, the first time interval should be continuously adjusted according to the actual aging process of the device. The aging process of the device is non-linear, and this non-linear process is affected by factors such as the ambient temperature, usage frequency, and charge / discharge cycle of the device. Therefore, the first time interval is adjusted based on the real-time usage data of the device.

[0104] Understandably, the aging process of equipment is non-linear and complex, influenced by multiple factors, primarily usage data such as frequency of use, ambient temperature, and charge / discharge cycles. Therefore, determining the first time interval based on usage data and dynamically adjusting it according to the actual condition of the equipment effectively ensures the accuracy of the first time interval.

[0105] In some embodiments, the method further includes: assigning a first weight to different warning messages in the first warning message according to their credibility; the credibility is positively correlated with the first weight; and performing weighted processing on the warning messages corresponding to the first weight to aggregate warning messages of the same device and the same fault type to determine the first aggregated information.

[0106] In this embodiment of the application, the battery cloud platform does not limit the method for judging the credibility of the warning information; in short, it can score the credibility of the warning information.

[0107] In some embodiments, an evaluation model for the credibility of early warning information can be trained based on a battery cloud platform, and the credibility score of the first early warning information can be achieved using the evaluation model.

[0108] In this application embodiment, the method by which the battery cloud platform performs weighted processing on the early warning information is not limited. In some possible embodiments, the battery cloud platform may use a simple weighted summation method or a more complex aggregation algorithm, such as cluster analysis, to calculate the first aggregated information.

[0109] In this embodiment of the application, since the first warning information may be affected by noise, resulting in inaccuracy, before aggregating the warning information of the same device and the same fault type in the first warning information, the battery cloud platform first performs weighted processing on the multiple warning information to be aggregated in the first warning information, assigns higher weight to the more credible warning information to be aggregated, and then aggregates the warning information of the same device and the same fault type in the first warning information according to the first time interval to determine the first aggregated information.

[0110] Understandably, the validity and accuracy of the first warning information are judged based on its credibility. Different first weights are assigned to different warning information based on their credibility levels, so that more credible warning information has higher weights. Thus, the aggregation of different warning information after weighted processing improves the effectiveness of the aggregation.

[0111] In some embodiments, the method further includes: using a time-based aggregation network to aggregate warning information of the same device and the same fault type in the first warning information to determine the first aggregated information.

[0112] In this embodiment, the time aggregation network is not limited, but it is capable of performing time series analysis on the first warning information, such as a neural network model.

[0113] In some embodiments, the battery cloud platform arranges the first warning information in chronological order to form time series data. For each time series data, the battery cloud platform applies an aggregation network model to model it. Based on the characteristics of equipment aging, the battery cloud platform uses the model to predict the warning information of the equipment in the future. By comparing the actual first warning information generated at present, the first warning information that meets the prediction results is aggregated according to the aggregation principle of the same equipment and the same fault type.

[0114] Understandably, the battery cloud platform, taking into account the non-linear aging characteristics of equipment, predicts the aging data of equipment based on a time-based aggregation network. Based on the prediction results, it aggregates warning information for the same equipment and the same fault type in the first warning information, thereby improving the accuracy of the aggregation results.

[0115] In some embodiments, the method further includes: performing fault correlation analysis on the initial warning information to be processed for at least one device, fusing the warning information that has a correlation in the initial warning information to determine the first warning information; the fault correlation analysis is used to identify potentially correlated information in the warning information.

[0116] In this embodiment of the application, there is a fault correlation between the initial warning information to be processed. Based on this, before aggregating the initial warning information to be processed, the battery cloud platform needs to perform fault correlation analysis on the initial warning information to be processed and filter out the warning information that may be correlated as the first warning information.

[0117] In some embodiments, the battery cloud platform first performs fault correlation analysis and processing on the initial warning information to be processed from at least one device, and then fuses the processed information based on the multi-dimensional attribute information and scene information of at least one device to determine the first warning information.

[0118] In some embodiments, the battery cloud platform performs fault correlation analysis and processing on the initial warning information to be processed from at least one device. At the same time, the battery cloud platform fuses the initial warning information to be processed based on the multi-dimensional attribute information and scenario information of at least one device. The battery cloud platform determines the first warning information based on the results of the fault correlation analysis and the fusion results.

[0119] Understandably, by performing fault correlation analysis on the warning information to be processed in advance, and filtering out the warning information that may be related as the first warning information, the effectiveness of the first warning information is ensured, thereby improving the accuracy of aggregation.

[0120] In some embodiments, the method further includes: filtering the initial warning information to be processed from at least one device, removing erroneous warning information, and determining the first warning information.

[0121] In this embodiment, the filtering method is not limited; in short, any method that can filter out erroneous warning information in the initial warning information is acceptable.

[0122] In some embodiments, the filtering method can be a filtering algorithm based on statistical rules or a filtering algorithm based on a machine learning model.

[0123] In this embodiment of the application, the battery cloud platform filters the initial warning information to be processed for at least one device according to the filtering algorithm, and removes the erroneous warning information in the initial warning information, such as warning information that is inconsistent with the actual situation of the device due to noise or false alarm.

[0124] Understandably, removing erroneous warning messages from the initial warning information to be processed in advance ensures the effectiveness of the initial warning information, thereby improving the accuracy of the first warning message.

[0125] In some embodiments, the method further includes: processing the initial warning information to be processed based on multi-dimensional attribute information and scene information of at least one device to determine the first warning information.

[0126] In the embodiments of this application, the multi-dimensional attribute information of at least one device includes the chemical composition and production batch of at least one device; the multi-dimensional scenario information of at least one device includes the usage scenario and operating environment of at least one device.

[0127] In this embodiment of the application, after determining the warning information to be processed for at least one device, the battery cloud platform processes the warning information to be processed based on multi-dimensional attribute information and scene information, and determines the processed warning information as the first warning information.

[0128] In some embodiments, the warning information to be processed is processed based on multi-dimensional attribute information and scene information of at least one device to determine the first warning information, including: based on at least one attribute information of at least one device, the warning information with the same attribute information in the warning information to be processed is fused to determine the first fused information; based on at least one scene information of at least one device, the warning information with the same scene information in the first fused information is fused to determine the first warning information.

[0129] In this embodiment of the application, the warning information to be processed includes at least one warning information with the same attribute information (chemical composition information and production batch information). The battery cloud platform merges the warning information with the same attribute information. Based on the scene information of the merged warning information, the warning information with the same scene information is merged again. Based on this, the warning information to be processed is merged to obtain at least one first warning information with the same attribute information and scene information.

[0130] Understandably, by using the device's attribute information and scene information to fuse the initial warning information to be processed into the first warning information, the accuracy of fault aggregation using the first warning information is improved.

[0131] In some embodiments, the method further includes: performing data cleaning and / or data imputation on the initial warning information to be processed, and determining the first warning information, wherein data cleaning instructs the deletion of duplicate and erroneous warning information in the initial warning information, and data imputation instructs the addition of warning information missing in the initial warning information.

[0132] In this embodiment of the application, the initial warning information to be processed may contain duplicate warning information or erroneous warning information that is different from the actual situation of the device. The battery cloud platform deletes such warning information.

[0133] In this embodiment of the application, the initial warning information to be processed may be partially missing or insufficient. Therefore, the battery cloud platform fills in the data for such warning information.

[0134] In some embodiments, data cleaning may include eliminating or correcting erroneous, duplicate, and incomplete warning messages to ensure the integrity and accuracy of the initial warning messages to be processed.

[0135] In some embodiments, data imputation can employ interpolation, regression, or machine learning methods to fill in missing early warning information, thereby reducing the impact of sparse early warning information.

[0136] Understandably, preprocessing the initial warning information removes duplicate and erroneous warnings, eliminating or correcting these issues and ensuring the completeness and accuracy of the warnings. Adding and filling in missing warning information reduces the impact of sparsity in the initial warning data, thereby improving the effectiveness and accuracy of the initial warnings.

[0137] In some embodiments, such as Figure 3 As shown, S102 may include S201 to S202:

[0138] S201. Determine at least two sets of warning messages with the same battery and the same fault type in the first warning message.

[0139] In this embodiment, the battery cloud platform queries the first warning information and groups the first warning information with the same device and the same fault type together. Since the first warning information contains warning information for multiple devices, there are at least two groups of warning information in the first warning information.

[0140] It should be noted that the battery cloud platform has aggregation rules. The aggregation subject in the aggregation rules is the first warning information with the same device and the same fault type. The aggregation subject then determines whether to aggregate based on the time interval specified in the aggregation rules.

[0141] In some embodiments, after aggregating multiple first warning messages, the battery cloud platform updates the fault occurrence time, fault end time, and fault level of the aggregated warning messages according to the aggregation rules. The fault occurrence time is the earliest occurrence time among the multiple first warning messages; the fault end time is the latest end time among the multiple first warning messages; and the fault level is the highest fault level among the multiple first warning messages.

[0142] S202. If, in each group of early warning information, multiple early warning information that are adjacent in time and are less than the first time interval, then the multiple early warning information are aggregated to determine the first aggregated information.

[0143] It should be noted that when the battery cloud platform groups the first warning information, within each group, the first warning information is arranged according to the time of fault occurrence. The arrangement of the time of fault occurrence can be in ascending order or in descending order, and this application embodiment does not impose any restrictions.

[0144] In this embodiment, the battery cloud platform defines a first time interval in the aggregation rules, and determines whether the warning information should be aggregated based on the first time interval. Within each group of warning information, the battery cloud platform arranges the first warning information based on the fault occurrence time of the first warning information. Starting from the first warning information in a group, the battery cloud platform sequentially queries the time intervals of multiple warning information with adjacent times. When the time intervals of multiple warning information are less than the first time interval, the battery cloud platform considers the multiple warning information as duplicate reports of the same fault, and aggregates the multiple warning information.

[0145] In other words, in this embodiment, the battery cloud platform queries the warning information in the fault details table and groups the first warning information with the same fault code and the same device code into the same group. The battery cloud platform includes at least one aggregation subject. Within the same group, the aggregation subjects are arranged according to the fault occurrence time. Based on a first time interval, the battery cloud platform aggregates the aggregation subjects according to the aggregation rules, and the aggregated first aggregation information is stored in the fault result table.

[0146] In some embodiments, when the time interval between multiple warning messages is greater than the first time interval, the battery cloud platform treats the multiple warning messages as reports of different faults, and the battery cloud platform does not aggregate the multiple warning messages.

[0147] In this embodiment, if aggregated entities within the same group meet the first time interval (i.e., aggregated entities meeting the first time interval report the same fault), then the aggregated entities are aggregated to form aggregated warning information. If aggregated entities do not meet the first time interval, then the aggregated entities belong to different faults. In this case, the aggregated entities are not aggregated, and the battery cloud platform identifies aggregated entities exceeding the first time interval as new fault reports, forming new warning information. The battery cloud platform displays the warning information through the host computer interface (fault management interface).

[0148] It should be noted that if the difference between the fault end time of a certain aggregated entity and the fault occurrence time of the next aggregated entity is less than a first time interval, then the two aggregated entities meet the first time interval requirement and are aggregated. If the difference between the fault end time of a certain aggregated entity and the fault occurrence time of the next aggregated entity is greater than the first time interval, then the two aggregated entities do not meet the first time interval requirement, and the battery cloud platform does not aggregate them. Furthermore, for the aggregated entity with the later fault occurrence time, the battery cloud platform identifies it as a new fault report.

[0149] It's worth noting that when determining whether an aggregated entity meets the first time interval requirement, the battery cloud platform needs to sequentially traverse the aggregated entities within the same group. The warning information for each aggregated entity includes both the fault occurrence time and the fault end time.

[0150] In this embodiment, the warning information in the fault management interface includes warning information aggregated by the aggregation subject, as well as new warning information. Furthermore, by clicking the details entry of the aggregated warning information in the fault management interface, the warning information of each aggregated subject can be queried.

[0151] Understandably, grouping the first warning information based on the principle of the same battery and the same fault type increases the convenience of subsequent aggregation and judgment. Within the same group, multiple warning information is aggregated based on the first time interval, that is, multiple warning information belonging to the same fault are aggregated to generate a first aggregated information, which reduces the repeated reporting of redundant warning information and effectively improves the efficiency of fault warning.

[0152] In some embodiments, such as Figure 4 As shown, S202 may include S301 and S302:

[0153] S301. If, in each group of early warning information, multiple early warning information that are adjacent in time are less than the first time interval, then the earliest occurrence time, latest end time, and highest fault level among the multiple early warning information are determined as the fault occurrence time, fault end time, and fault level of an aggregated information.

[0154] S302. When all multiple aggregations in each group of early warning information are completed, determine the first aggregated information.

[0155] It should be noted that the first aggregated information is composed of multiple first warning information. The multiple first warning information involved in the first aggregated information are repeated reports of the same fault.

[0156] In this embodiment, the warning information in each group is arranged in ascending or descending order of fault occurrence time. The battery cloud platform queries sequentially, starting from the first or last warning information in the group, checking the time intervals of multiple warning information with adjacent times. If the time interval of adjacent warning information is less than a first time interval, indicating that multiple warning information are repeated reports of the same fault, then the multiple warning information are aggregated. The aggregated result is determined as the first aggregated information. The fault occurrence time of the first aggregated information is the earliest occurrence time among the multiple warning information; the fault end time of the first aggregated information is the latest end time among the multiple warning information; and the fault level of the first aggregated information is the highest fault level among the multiple warning information.

[0157] In this embodiment, the battery cloud platform sequentially queries all warning information within a group, starting with the first warning information. When a warning information matching the aggregation rules is found, it is aggregated. After aggregation, the battery cloud platform continues querying within the group, then combines the aggregated warning information with the currently queried warning information for aggregation judgment. The battery cloud platform can perform multiple aggregations within the same group until all warning information within the group has been queried. At this point, there are no more warning information within the group that can be aggregated. The battery cloud platform determines the warning information generated by aggregation within the same group as a first aggregated information.

[0158] It should be noted that the battery cloud platform can process data in batches across different groups until each group has completed the aggregation process and obtained the first aggregated information.

[0159] It is understandable that the first aggregated information indicates that multiple first warning information entries participating in the aggregation are repeated reports of the same fault. By defining the fault occurrence time of the aggregated information as the earliest occurrence time of the same fault, the fault end time of the aggregated information as the latest end time of the same fault, and the fault level of the aggregated information as the highest fault level of the same fault, it is ensured that the first aggregated information can fully reflect the indication content of multiple warning information entries, thereby improving the accuracy of the first aggregated information.

[0160] In some embodiments, the method may further include: in response to a viewing instruction, displaying fault warning data and a details entry for the first warning information on the fault management interface.

[0161] In this embodiment of the application, the battery cloud platform responds to the viewing command and displays at least one of the following in the fault management interface: fault information, fault level, fault occurrence time, fault end time, device identifier, and fault status, as well as a details entry for the first warning information.

[0162] In this embodiment, for the visualization of early warning information, after the early warning information is aggregated to form fault early warning data, the battery cloud platform can respond to the viewing operation and display the fault early warning data in the fault management interface. The fault early warning interface can be graphical or textual, displaying at least one of the following: fault information, fault level, fault occurrence time, fault end time, device identifier, and fault status, as well as a details entry for the first early warning information. Furthermore, within the fault management interface, any fault early warning data can also display a details entry for the first early warning information, which is used to view multiple first early warning information items participating in the fault early warning data aggregation. The details entry can be displayed as an icon or as text; this embodiment does not impose specific limitations on the display method of the details entry.

[0163] For example, the fault management interface of the battery cloud platform, such as Figure 2 As shown, the fault management interface includes condition controls for fault number, fault code, fault name, fault level, fault occurrence time, fault confirmation time, fault end time, device type, device number, fault status, and operation. One fault warning data point in the fault management interface is as follows: fault number 2402150000606629, fault code 602, fault name "Battery Abuse Alarm," fault level L3-Severe, fault occurrence time 2024-02-15 17:01:03, fault end time 2024-02-19 19:24:08, device type "VIN," device number 42892240500241, fault status "Active_Unconfirmed," and operation "View Details" (i.e., the details entry). The fault management interface displays five fault warning data points, each containing a details entry point. These details entry points are used to view multiple first-level warning messages that are included in the fault warning data aggregation.

[0164] It should be noted that the battery cloud platform obtains first aggregated information by aggregating the first early warning information, and then obtains fault early warning data based on the first aggregated information. That is, the fault early warning data is obtained by the participation of multiple first early warning information.

[0165] Understandably, on the one hand, the first warning message indicates an equipment malfunction in the energy storage system. This first warning message may contain multiple warnings for the same fault, meaning there may be redundant warnings. By filtering warnings with the same equipment and fault type, and then aggregating them based on a first time interval, multiple warnings for the same fault are aggregated to form aggregated information, thus identifying the fault warning data. This reduces redundant reporting of warnings and effectively improves the processing efficiency of fault warning information. On the other hand, due to the visual design of the fault management interface, while displaying the aggregated fault warning data, it also provides an entry point for details of the first warning information before aggregation, allowing users to view the warning information before aggregation. Therefore, it improves the diversity of information displayed before and after aggregation.

[0166] In some embodiments, the method may further include S401 to S403:

[0167] S401. In response to the trigger operation of the details entry, the fault details information of the first warning information and the access to view historical information are displayed on the fault analysis interface; the fault details information includes: the fault occurrence time and fault level of the first warning information.

[0168] In some embodiments, the fault management interface displays fault warning data and detailed entry points for first warning information. Accessing these detailed entry points allows the display of multiple first warning messages that participate in the aggregation of fault warning data. The battery cloud platform can respond to triggering operations on the detailed entry points of any fault warning data.

[0169] In this embodiment, when it is necessary to view multiple first warning messages participating in the fault warning data aggregation, the battery cloud platform responds to the trigger operation of the details entry, jumping from the fault management interface to the fault analysis interface. The fault analysis interface displays the fault details of the first warning messages and access points for viewing historical information. The fault details of the first warning messages can be displayed in a table or graphical format; this embodiment does not limit the display method of the fault details.

[0170] In this embodiment, the fault details information may include: the fault occurrence time and fault level of the first warning information. Historical information refers to the fault parameters of the first warning information at different historical times.

[0171] It should be noted that the start time at different historical moments is the time when the first warning information failure occurred, and the end time at different historical moments is the time when the first warning information failure ended.

[0172] For example, in response to a trigger operation at the details entry point, the battery cloud platform redirects from the fault management interface to the fault analysis interface. For instance... Figure 5 As shown, the fault analysis interface includes a fault cause (excessive differential pressure warning) control, a first warning information control, and a historical information viewing control (entry point for viewing historical information). The first warning information control displays the fault reporting times for the following dates: 2023-06-11 04:35:28, 2023-06-11 04:35:58, 2023-06-11 04:50:13, 2023-06-11 07:20:29, 2023-06-11 07:51:12, 2023-06-11 08:30:23, 2023-06-11 14:00:58, 2023-06-11 14:02:39, 2023-06-11 15:18:48, 2023-06-11 17:07:14, 2023-06-11 The fault levels (L3-Severe, L2-Moderate, L1-Alert) of the 11 first warning messages at 21:01:36 are displayed. The first warning message control is shown as a bar chart, with each bar corresponding to each aggregated first warning message. By selecting first warning message 611 and selecting the "View Historical Information" control, detailed information of the first warning messages (multiple warning messages) before aggregation can be displayed.

[0173] S402. In response to the selection operation of the first warning information, the selected first warning information is displayed on the fault analysis interface in the first manner.

[0174] In this embodiment of the application, the fault analysis interface includes multiple first warning messages. The battery cloud platform can respond to the selection operation of any first warning message. When the battery cloud platform receives the selection operation instruction of the first warning message, it displays the selected first warning message in the fault analysis interface in a first manner.

[0175] It should be noted that the first method can be either highlighting or selecting, and the embodiments of this application do not limit the type of the first method.

[0176] For example, such as Figure 6 As shown, in the first warning information control of the fault analysis interface, clicking the bar for the first warning information with a fault occurrence time of 2023-06-11 21:01:36 will display a dashed frame outside the bar, indicating that the warning information has been selected. The battery cloud platform responds to the selection of the first warning information and displays the fault parameters of the selected first warning information.

[0177] S403. In response to the historical information viewing operation, the fault parameters under the fault type of the selected first warning information are displayed in the drop-down page of the fault analysis interface.

[0178] In this embodiment, in response to the historical information viewing operation, the battery cloud platform displays another drop-down page below the fault analysis interface. This drop-down page displays the fault parameters of the first warning information at different times. The time span for each "different time" is from the fault occurrence time to the fault end time of the first warning information, covering the fault parameters for the entire time period of the first warning information. The fault parameters are different dimensions of the same device parameters at different times.

[0179] It should be noted that the display method of the fault parameters under the fault type to which the first warning information belongs can be a data table or a diagram. This application embodiment does not make specific limitations.

[0180] Understandably, responding to the details entry in the fault management interface triggers a jump to the fault analysis interface. The fault analysis interface displays the fault occurrence time and fault level of the first warning information contributing to the fault warning data. This allows for a more intuitive view of multiple warning messages with different times and fault levels aggregated within the same reported fault, enhancing the visualization and diversity of fault warnings. By viewing historical information, the dropdown menu in the fault analysis interface displays the fault parameters under the selected first warning information's fault type, facilitating fault cause location and analysis through these parameters. This enhances the effectiveness of providing fault information during the fault warning process.

[0181] In some embodiments of this application, in response to the historical information viewing operation, the drop-down page of the fault analysis interface displays different dimensions of the fault parameters of the same device at different times under the fault type to which the selected first warning information belongs.

[0182] For example, as shown in Figure 6, in the historical information viewing control of the fault analysis interface, by selecting the first warning information with a fault occurrence time of 2023-06-11 21:01:36, a drop-down page appears on the fault analysis page. The drop-down page displays the voltage of the warning information with a fault occurrence time of 2023-06-11 21:01:36 at different times under three sampling methods. The voltage of the warning information at different times under the three sampling methods corresponds to three curves. Among them, the display range of different times is from 2023-09-26 22:27:44 to 2023-09-26 22:42:14; the voltage display range is 4211 to 4380, and the voltage unit is millivolts (mV); the three sampling methods are the maximum voltage (voltage max), the average voltage (voltage mean), and the minimum voltage (voltage min), respectively.

[0183] Understandably, the dropdown menu in the fault analysis interface displays fault parameters for the first warning information at different times. These different times span from the fault occurrence time to the fault end time of the first warning information, covering the fault parameters for the entire time period of the first warning information. By obtaining fault parameters from different dimensions, the effectiveness and accuracy of fault information provided in fault warnings are improved.

[0184] In some embodiments, if there is no first historical warning information with the same battery and the same fault type as the first aggregated information from the historical fault warning data, then the first aggregated information is determined as fault warning data.

[0185] In this embodiment, if there is no first historical warning information with the same battery and fault type as the first aggregated information in the historical fault warning data, that is, if the first aggregated information and the first historical warning information indicate different faults, the battery cloud platform does not aggregate the first aggregated information and the first historical warning information. Since there is no fault in the historical fault warning data that is the same as the fault indicated by the first aggregated information, the battery cloud platform uses the first aggregated information as fault warning data.

[0186] It is understandable that there is no first historical warning information with the same equipment and the same fault type as the first aggregated information in the historical fault warning data. That is, the first aggregated information and the first historical warning information are different fault warnings. Determining fault warning data for different fault warnings improves the effectiveness of the warning information.

[0187] In some embodiments, if, in each group of warning information, the time interval between two adjacent warning information messages exceeds a first time interval according to the time sequence, then the second warning information message that caused the earliest failure in the pair of warning information messages is frozen, and the third warning information message that caused the latest failure in the pair of warning information messages is determined as an aggregated information message in the first aggregated information message.

[0188] In this embodiment, the warning information is arranged in ascending order of occurrence time within each group. The warning information includes the fault occurrence time and fault end time. The battery cloud platform queries the fault occurrence time and fault end time of two adjacent warning information within the same group. Among the two warning information, the one with the earliest fault occurrence time is the second warning information, and the one with the latest fault occurrence time is the third warning information. If the fault end time of the second warning information and the fault occurrence time of the third warning information exceed a first time interval, the battery cloud platform freezes the second warning information, meaning it does not participate in aggregation. The battery cloud platform then determines the third warning information as an aggregated information, which can participate in the aggregation of the first aggregated information.

[0189] It should be noted that the third warning information, as an aggregated information, participates in the aggregation judgment according to the aggregation rules. After the aggregation judgment, the third warning information may meet the aggregation rules and can be aggregated with other aggregation entities to form the first aggregated information; the third warning information may also not meet the aggregation rules and cannot be aggregated with other aggregation entities.

[0190] In some embodiments, the battery cloud platform displays the frozen second warning information on the fault information details page. The warning information displayed on the fault information details page includes the frozen second warning information and the first aggregated information. On the fault information details page, the fault code of the frozen second warning information is different from that of the first aggregated information.

[0191] For example, such as Figure 7 As shown, the fault management interface contains warning messages with fault codes 2210060000000001 and 2210000000000002. The warning message with fault code 2210060000000001 has a fault start time of 2022-10-06 09:28:53, a fault end time of 2022-10-07 13:29:53, a fault code of 601, a fault level of critical (L3), a fault name of component fault alarm, and an equipment code of 1110. The warning message with fault code 2210000000000002 has a fault start time of 2022-10-10 14:28:53, a fault end time of 2022-10-10 13:29:53, a fault code of 601, a fault level of severe (L3), a fault name of component fault alarm, and a device code of 1110.

[0192] The warning messages with fault codes 2210060000000001 and 2210000000000002 share the same fault code (601) and device code (1110). Therefore, these two warning messages with fault codes 2210060000000001 and 2210000000000002 belong to two different aggregate entities. The fault end time of the aggregate entity with fault code 2210060000000001 was 13:29:53 on 2022-10-07. Until 14:28:53 on 2022-10-10, the battery cloud platform received a fault report from the aggregate entity with fault code 2210000000000002. Since the time interval between 2022-10-07 13:29:53 and 2022-10-10 14:28:53 exceeds the first time interval (3 days), the two aggregation subjects belong to different fault reports, and the aggregation subjects will not aggregate.

[0193] Understandably, after the first time interval, the second warning information that failed earliest among the two warning information pairs is frozen, and the failure end time of the frozen second warning information is no longer updated. Only the failure end time of the unfrozen third warning information is queried and updated, which improves resource utilization and thus improves warning efficiency.

[0194] In some embodiments, the method further includes S501 and S502:

[0195] S501. If, after the second preset time period, the fault warning data is frozen and the fault status of the fault warning data is the first preset status, then the fault warning data is determined to be an overdue warning information; the first preset status indicates that the fault warning data is in a pending state.

[0196] S502. Close the system for overdue warning information.

[0197] It should be noted that the fault status of the fault warning data may include at least one of a first preset status, a second preset status, and a third preset status. The first preset status is an active status, indicating that the fault to which the fault warning data belongs is pending processing; the second preset status is a cleared unconfirmed status, indicating that the fault to which the fault warning data belongs has not been processed and will no longer be processed; the third preset status is a cleared confirmed status, indicating that the fault to which the fault warning data belongs has been processed and will no longer be processed.

[0198] In this embodiment, the second preset time period is the waiting time for the fault warning data. If the frozen fault warning data remains unprocessed after the second preset time period, the battery cloud platform determines that the fault warning data is an overdue warning message. The battery cloud platform then closes the overdue warning message.

[0199] Understandably, frozen fault warning data with a fault status of the first preset state indicates that the fault to which the warning data belongs is in a pending state. After a second preset time period, if the frozen fault warning data with a fault status of the first preset state is still in a pending state, it is considered that the fault to which the warning data belongs has not been processed for a long time. As the warning system continuously reports new fault warning information, overdue warning information is closed, reducing the complexity of warning information and improving the manageability of warning information.

[0200] The battery cloud platform's measures for closing expired warning messages are as follows:

[0201] In response to the command to close the overdue warning information, the battery cloud platform updates the fault status of the overdue warning information from the first preset status to the second preset status on the fault management interface. The second preset status is "cleared but not confirmed", indicating that the overdue warning information is closed.

[0202] In some embodiments, the fault status of the fault warning data may include: activation confirmed, activation unconfirmed, clear confirmed, and clear unconfirmed. The activation confirmed and activation unconfirmed statuses indicate that the warning result is pending processing; the clear confirmed status indicates that the warning result has been processed and can be closed; and the clear unconfirmed status indicates that the warning result has not been processed and can be closed.

[0203] It should be noted that the first preset state can be either an activated and confirmed state or an activated but unconfirmed state; the second preset state is to clear the unconfirmed state.

[0204] Understandably, in the fault management interface, disabling overdue warning information and displaying an update of the fault status of the overdue warning information—from a first preset status to a second preset status—indicates that the overdue warning information is disabled. This provides a clear and intuitive view of the warning information's closure status, improving its visibility in different scenarios. Simultaneously, it allows for other operations and processing based on the updated fault status, thereby enhancing the manageability of the warning information.

[0205] In some embodiments, the method further includes S601 and S602:

[0206] S601. After generating fault warning data, continuously monitor the equipment indicated by the fault warning data;

[0207] S602. If the parameters indicated by the first warning information of the device return to normal, in the fault management interface, the fault status of the fault warning data is updated from the first preset status to the third preset status. The third preset status indicates that the fault warning data is in a cleared state.

[0208] In this embodiment, after the device generates fault warning data, the battery cloud platform continuously monitors the device's status. The device may be in a continuous fault state, in which case the device's parameters are fault parameters; the device may also recover to normal operation after maintenance, in which case the device's parameters are normal parameters. If the battery cloud platform detects that the device's parameters have recovered from fault parameters to normal parameters, i.e., the device's fault has been resolved, then in the fault management interface, the battery cloud platform updates the fault status of the fault warning data from the first preset status to the third preset status, i.e., the battery cloud platform cancels the fault warning data generated by the device.

[0209] For example, such as Figure 8 As shown, the fault management interface contains six overdue warning messages with fault codes 2309300080348519, 2309300080347369, 2309300080349462, 2309300080337556, 2309300080348373, and 2309300080337567. The battery cloud platform updates the fault status of these six overdue warning messages in the fault status control, changing the condition control of the fault status from active (first preset status) to cleared_unconfirmed status (third preset status). The cleared_unconfirmed status indicates that the overdue warning message is now closed.

[0210] Understandably, the return of equipment parameters to normal indicates that the equipment malfunction has been resolved. Clearing fault warning data for equipment that has returned to normal improves the timeliness and accuracy of fault warnings.

[0211] The following describes the processing method of the above-mentioned warning information in conjunction with an application embodiment of a battery cloud platform. However, it is worth noting that this embodiment is only for better illustration of this application and does not constitute an improper limitation of this application.

[0212] In this embodiment, the battery cloud platform serves as a system for processing early warning information, and the device is the battery within the energy storage system. The flowchart illustrating the implementation of fault aggregation within the battery cloud platform is as follows: Figure 9 As shown:

[0213] The battery cloud platform acts as a data receiver, receiving alarm data in case of battery abnormalities. After analysis and processing, the alarm data enters the alarm center backend of the cloud platform. Through the data receiving and storage module, rule engine processing module, and alarm push unit in the alarm center backend, the battery cloud platform's fault warnings are aggregated, and the aggregated alarm information is pushed to the customer system.

[0214] The battery cloud platform includes: an algorithm results unit, an analysis center unit, a reporting unit, and an alarm center backend. The algorithm results unit is used to send algorithm results to the alarm center backend; the analysis center unit and the reporting unit are used to send alarm information to the alarm center backend.

[0215] The alarm center backend includes: a data receiving and storage module, a rule engine processing module, and an alarm push unit.

[0216] The data receiving and storage module includes: a Kafka1 unit, a Kafka2 unit, a rule unit, a NiFi unit, a Hive fault details table unit, and a MySQL fault result table. Algorithm results are sent from the Kafka1 unit to the rule unit; the rule unit sends alarm events to the Kafka2 unit; the Kafka2 unit sends the alarm events to the Hive fault details table unit via the NiFi unit, and simultaneously sends the alarm events to the data receiving and storage module. The data receiving and storage module processes the data in the algorithm results, generates alarm events, and sends these alarm events to both the Hive fault details table unit and the data receiving and storage module.

[0217] The rules engine processing module includes a Flink alarm aggregation unit and a Kafka3 unit. The Flink alarm aggregation unit sends alarm information to both the Kafka unit and the MySQL fault result table unit. The rules engine processing module aggregates alarm events according to the rules engine to generate alarm information.

[0218] The alarm push unit is used to push alarm information to the customer's system.

[0219] The alarm center page sends information to the MySQL fault result table, Hive fault detail table, and knowledge base via the alarm front-end API unit to confirm fault handling and manually configure constant parameters. From the customer system, information is sent to the MySQL fault result table via the alarm OpenAPI unit for alarm cancellation. The system configuration page sends information to the push aggregation rule unit via the alarm aggregation configuration unit, which then sends the information to the Flink alarm aggregation unit to push the defined fault aggregation rules. The system configuration page also sends information to the push configuration unit via the alarm push configuration unit, which in turn sends messages to the alarm push unit to push other rules besides fault aggregation rules, such as subscription and suppression rules.

[0220] This application provides a method for processing early warning information, which may include steps S1001 to S1006:

[0221] S1001, The device collects the first early warning information.

[0222] In some embodiments of this application, when a battery malfunctions, the device generates a first warning message upon detecting an abnormal battery condition or triggering a predefined warning condition. The first warning message is transmitted to the battery cloud platform, and the algorithm result unit of the battery cloud platform transmits the result to the warning center backend for issuing the warning.

[0223] It should be noted that the first warning information may include parameters such as fault level, fault occurrence time, fault end time, and equipment identification.

[0224] For example, the device can be a sensor, a monitoring device, or a server; this application embodiment does not impose any limitations.

[0225] S1002, the battery cloud platform receives and stores the first warning information.

[0226] It should be noted that after receiving the first warning information from the device, the battery cloud platform analyzes and processes it, including verifying data integrity, extracting key information, and storing the data for subsequent processing.

[0227] In some embodiments of this application, the first warning information is transmitted to the data receiving and storage module of the warning center backend through the algorithm result unit of the battery cloud platform for verification, extraction, and storage. Specifically, the first warning information before aggregation is stored in the fault details table, and the aggregated fault warning data is stored in the fault result table.

[0228] S1003, rule engine processing of the battery cloud platform.

[0229] It should be noted that the rule engine is a component used to define and execute rules, and is used to process and analyze the first warning information.

[0230] In some embodiments of this application, the battery cloud platform includes a rule engine processing module, which aggregates the first warning information to generate first aggregated information. The rule engine processing module defines the aggregation subject and aggregation rules, and the first warning information is aggregated according to the rule engine.

[0231] It should be noted that the rule engine may also include a data processing module, which is used to preprocess the first warning information before it is aggregated. The purpose of preprocessing is to ensure the consistency and accuracy of the first warning information.

[0232] The rule engine processing of the battery cloud platform may include S1031 to S1036, such as... Figure 10 As shown.

[0233] S1031. Query the first warning information in the fault details table.

[0234] It should be noted that the first warning information is stored in the fault details table, which is located in the data receiving and storage module of the warning center's backend.

[0235] In this embodiment, the battery cloud platform queries the first warning information in the fault details table based on the time increment. The time increment is the ascending order of the fault occurrence time of the warning information. The battery cloud platform sequentially traverses the first warning information according to the ascending order of the fault occurrence time.

[0236] It should be noted that the first warning information in the fault details table is queried based on the time increment, in preparation for the aggregation of subsequent warning information.

[0237] S1032. Grouping based on the aggregation subject, and aggregating the first warning information within each group based on the aggregation rules.

[0238] It should be noted that the rule engine defines an aggregation subject, which is the first warning message with the same fault code and the same device code.

[0239] In this embodiment of the application, an aggregation rule is defined in the battery cloud platform. The aggregation rule can define a first time interval. Based on the first time interval, it is determined whether the aggregation subject in each group is reporting the same fault or reporting a new fault.

[0240] In this embodiment of the application, when the aggregating entities aggregate into first aggregated information, they need to update the first aggregated information according to the aggregation rules. In the aggregation rules, the failure occurrence time of the first aggregated information is the earliest failure occurrence time among the aggregated entities; the failure end time of the first aggregated information is the latest failure end time among the aggregated entities; and the failure level of the first aggregated information is the highest failure level among the aggregated entities.

[0241] S1033. Check if there is a first warning message for the same aggregated subject in the fault result table. If there is, proceed to S1034; otherwise, proceed to S1035.

[0242] In this embodiment, the battery cloud platform employs a timed processing method for a large volume of warning information. The battery cloud platform defines a first preset time period, and the timed task manager starts a timed task every first preset time period to read incremental warning information from the fault details table. Incremental warning information consists of warning information reported within the first preset time period. First aggregated information is obtained by aggregating the incremental warning information.

[0243] In this embodiment of the application, the battery cloud platform queries the historical fault warning data in the fault result table to determine whether there is a first historical warning information in the historical fault warning data that has the same aggregation subject as the first aggregation information.

[0244] S1034. Do the aggregation subjects in the fault details table and fault result table meet the aggregation rules? If yes, proceed to S1036; otherwise, proceed to S1035.

[0245] In this embodiment, the battery cloud platform queries historical fault warning data in the fault result table to determine if there is a first historical warning message with the same aggregation subject as the first aggregated information. This warning message is then identified as the first historical warning message. The battery cloud platform determines whether the time interval between the first historical warning message and the first aggregated information is less than a first time interval. If the time interval is less than the first time interval, the first historical warning message and the first aggregated information conform to the aggregation rule; if the time interval is greater than the first time interval, the first historical warning message and the first aggregated information do not conform to the aggregation rule.

[0246] S1036. Aggregate the aggregated entities in the fault details table and the fault result table.

[0247] In this embodiment of the application, if the battery cloud platform determines that the first historical warning information and the first aggregated information meet the aggregation rules, then the first aggregated information in the fault details table and the first historical warning information in the fault result table are aggregated.

[0248] S1035. Insert the warning information from the fault details table into the fault result table.

[0249] In this embodiment of the application, if the battery cloud platform determines that the first historical warning information and the first aggregated information do not conform to the aggregation rules, that is, the first aggregated information in the fault details table and the first historical warning information in the fault result table belong to different fault reports, the first aggregated information in the fault details table is inserted into the fault result table as a newly added warning result in the fault result table.

[0250] It should be noted that the first aggregated information in the fault details table and the first historical warning information in the fault results table belong to different fault reports. Furthermore, there are no other historical warning information in the fault results table that share the same aggregation subject as the first aggregated information. Therefore, there are no fault reports in the fault results table that are identical to the first aggregated information.

[0251] S1004. Generate and push early warning notifications.

[0252] It should be noted that the early warning information is aggregated to generate fault early warning data. The fault early warning data includes relevant information from the aggregated early warning information, such as the fault occurrence time, fault end time, fault level, and fault status.

[0253] In this embodiment, after the early warning information is aggregated to generate fault early warning data, the battery cloud platform can generate an early warning notification based on the fault early warning data, and set the early warning level and associate it with other relevant information. The early warning level can be, for example, urgent, severe, or warning; this embodiment does not impose any limitations.

[0254] In this embodiment, the generated early warning notification is pushed to a predetermined target. This allows relevant personnel to receive the early warning notification in a timely manner and take appropriate measures for troubleshooting or emergency response.

[0255] For example, the predetermined target can be the mobile phone of the maintenance personnel, or it can be a workstation, email or other communication channel. This application embodiment does not impose any restrictions.

[0256] S1005. Lifting and updating early warning results.

[0257] In this embodiment, after the warning result is generated, the battery cloud platform continuously monitors the status of the faulty battery corresponding to the warning result. When the fault parameters of the faulty battery are detected to return to normal, the battery cloud platform will update the fault status of the warning result in the fault management interface from the active state to the cleared state. That is, the warning result is cleared.

[0258] It should be noted that when the fault status of the warning result is active, it indicates that the warning result is pending processing; when the fault status of the warning result is cleared, it indicates that the warning result does not need to be processed.

[0259] S1006. Closure of warning results after the expiration period.

[0260] In this embodiment of the application, an overdue shutdown time can be preset. For fault warning data that has been frozen and has reached the overdue shutdown time but has not been closed, the battery cloud platform can shut it down overdue.

[0261] In this embodiment, the battery cloud platform closes the expired fault warning data by updating the fault status of the fault warning data awaiting closure in the fault management interface to a newly cleared, unconfirmed status. This completes the closure of the expired fault warning data.

[0262] In this embodiment, the first early warning information indicates an equipment malfunction in the energy storage system. The first early warning information may contain multiple warnings for the same fault, meaning there may be redundant warnings. By filtering warnings with the same equipment and fault type, and then aggregating the filtered first early warning information based on a first time interval, multiple warnings for the same fault are aggregated to determine the fault warning data. This reduces the repeated reporting of redundant warnings and effectively improves the processing efficiency of fault warnings.

[0263] This application provides a warning information processing device 1100, such as... Figure 11 As shown, the device includes:

[0264] The determination module 1101 is used to determine the first warning information to be processed for at least one device.

[0265] The aggregation module 1102 is used to aggregate warning information with the same device and the same fault type in the first warning information based on a first time interval to determine the first aggregated information; and, when a first historical warning information with the same device and the same fault type as the first aggregated information is found in the historical fault data, the first aggregated information is aggregated with the first historical warning information based on the first time interval to obtain fault warning data.

[0266] In some embodiments, the determining module 1101 is further configured to determine a first time interval based on real-time usage data of at least one device.

[0267] In some embodiments, the determining module 1101 is further configured to assign a first weight to different warning messages in the first warning message according to the credibility of the warning message.

[0268] The aggregation module 1102 is also used to perform weighted processing on the corresponding early warning information based on the first weight, so as to aggregate early warning information of the same device and the same fault type and determine the first aggregated information.

[0269] In some embodiments, the aggregation module 1102 is further configured to use a time-based aggregation network to aggregate warning information of the same device and the same fault type in the first warning information to determine the first aggregated information.

[0270] In some embodiments, the warning information processing device 1100 further includes a fusion module 1103, which is used to perform fault correlation analysis on the initial warning information to be processed for at least one device, fuse the warning information that has a correlation in the initial warning information, and determine the first warning information.

[0271] In some embodiments, the warning information processing device 1100 further includes a filtering module 1104, which is used to filter the initial warning information to be processed from at least one device, remove erroneous warning information, and determine the first warning information.

[0272] In some embodiments, the determining module 1101 is further configured to process the initial warning information to be processed based on the multi-dimensional attribute information and scene information of at least one device, and determine the first warning information.

[0273] In some embodiments, the fusion module 1103 is further configured to fuse warning information with the same attribute information in the initial warning information to be processed based on at least one attribute information of at least one device to determine first fused information; and to fuse warning information with the same scene information in the first fused information based on at least one scene information of at least one device to determine first warning information.

[0274] In some embodiments, the determining module 1101 is further configured to perform data cleaning and / or data filling on the initial warning information to be processed, and to determine the first warning information.

[0275] In some embodiments, the determining module 1101 is further configured to acquire incremental data in the fault warning record when a first preset time period is reached, and obtain first warning information for at least one device.

[0276] In some embodiments, the determining module 1101 is further configured to determine at least two sets of warning messages with the same device and the same fault type in the first warning message.

[0277] The aggregation module 1102 is also used to aggregate multiple early warning messages in each group of early warning messages if, in chronological order, multiple early warning messages that are adjacent in time are less than a first time interval, and to determine the first aggregated information.

[0278] In some embodiments, the determining module 1101 is further configured to: if, in each group of warning information, multiple warning information that are adjacent in time according to time sequence are less than a first time interval, determine the earliest occurrence time, latest end time, and highest fault level among the multiple warning information as the fault occurrence time, fault end time, and fault level of an aggregated information; and determine the first aggregated information until multiple aggregations in each group of warning information are completed.

[0279] In some embodiments, the warning information processing device 1100 further includes a display module 1105, which is used to display fault warning data and a details entry of the first warning information on the fault management interface in response to a viewing command.

[0280] In some embodiments, the display module 1105 is further configured to, in response to a viewing instruction, display at least one of the fault information, fault level, fault occurrence time, fault end time, device identifier, and fault status of the fault warning data, as well as a details entry for the first warning information, on the fault management interface.

[0281] In some embodiments, the display module 1105 is further configured to, in response to the triggering operation of the details entry, display the fault details information of the first warning information and the viewing entry of historical information in the fault analysis interface; and, in response to the selection operation of the first warning information, display the selected first warning information in the fault analysis interface according to a first method; and, in response to the viewing operation of historical information, display the fault parameters under the fault type to which the selected first warning information belongs in the drop-down page of the fault analysis interface.

[0282] In some embodiments, the display module 1105 is also configured to, in response to the historical information viewing operation, display different dimensions of the fault parameters of the same device parameter at different times in the drop-down page of the fault analysis interface under the fault type to which the selected first warning information belongs.

[0283] In some embodiments, the determining module 1101 is further configured to determine the earliest occurrence time, latest end time, and highest fault level in the first aggregated information and the first historical warning information as the fault occurrence time, fault end time, and fault level of the fault warning data based on the first time interval.

[0284] In some embodiments, the determining module 1101 is further configured to, if in each group of warning information, the time interval between two pairs of warning information that are adjacent in time exceeds a first time interval, freeze the second warning information that has the earliest failure in the pair of warning information, and determine the third warning information that has the latest failure in the pair of warning information as an aggregate information in the first aggregate information.

[0285] Understandably, on the one hand, the pending early warning information indicates equipment malfunctions in the energy storage system. This pending information may contain multiple warnings for the same fault, meaning there may be redundant warnings. By fusing warnings with similar attributes and scenario information, a first warning is obtained. Then, warnings with the same equipment and fault type are filtered, and aggregated based on a first time interval. This aggregating multiple warnings for the same fault forms aggregated information, thus identifying fault warning data and reducing redundant reporting, effectively improving processing efficiency. On the other hand, the visual design of the fault management interface displays both the aggregated fault warning data and details of the initial first warning information (before aggregation), enhancing the diversity of information displayed before and after aggregation.

[0286] The descriptions of the apparatus embodiments above are similar to those of the method embodiments above, and have similar beneficial effects. In some embodiments, the functions or modules included in the apparatus provided in this application can be used to perform the methods described in the method embodiments above. For technical details not disclosed in the apparatus embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0287] It should be noted that, in the embodiments of this application, if the above methods are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to related technologies, can be embodied in the form of software products. These software products are stored in a storage medium and include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), magnetic disks, or optical disks. Thus, the embodiments of this application are not limited to any specific hardware, software, or firmware, or any combination of hardware, software, and firmware.

[0288] This application provides a device for processing early warning information, such as... Figure 12 As shown, the hardware entity of the warning information processing device 1200 includes a processor 1201 and a memory 1203. The memory stores a computer program that can run on the processor. When the processor executes the program, it implements the steps in the warning information processing method.

[0289] It should be noted that the processor 1201 typically controls the overall operation of the warning information processing device 1200. The memory 1203 is configured to store instructions and applications executable by the processor 1201, and can also cache data to be processed or already processed (e.g., image data, audio data, voice communication data, and video communication data) in the processor 1201 and various modules of the warning information processing device 1200. This can be implemented using flash memory or random access memory (RAM). The warning information processing device may also include a communication interface 1202; the communication interface 1202 enables the warning information processing device to communicate with other terminals or servers via a network. Data can be transferred between the processor 1201, the communication interface 1202, and the memory 1203 via a bus 1204.

[0290] Based on the foregoing embodiments, the modules and units included in the warning information processing device provided in this application embodiment can be implemented by a processor in a computer device; of course, they can also be implemented by specific logic circuits; in the implementation process, the processor can be a central processing unit (CPU), a microprocessor unit (MPU), a digital signal processor (DSP), or a field programmable gate array (FPGA), etc.

[0291] This application provides a computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements all the steps of the method for processing early warning information. The computer-readable storage medium can be transient or non-transient.

[0292] The above are merely embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for processing early warning information, characterized in that, The method includes: Identify the first warning information to be processed for at least one device; Based on a first time interval, the warning information with the same device and the same fault type in the first warning information is aggregated to determine the first aggregated information; If a first historical warning message with the same device and the same fault type as the first aggregated information is found in the historical fault data, the first aggregated information and the first historical warning message are aggregated based on the first time interval to obtain the fault warning data.

2. The method according to claim 1, characterized in that, The method further includes: The first time interval is determined based on real-time usage data from at least one device; the usage data includes at least one of the following: ambient temperature, usage frequency, and charge / discharge cycle.

3. The method according to claim 1, characterized in that, The method further includes: Based on the credibility of the early warning information, different early warning information in the first early warning information are assigned their own first weights; the credibility is positively correlated with the first weight. Based on the first weight, the corresponding early warning information is weighted and processed to aggregate early warning information of the same device and the same fault type, and the first aggregated information is determined.

4. The method according to claim 1, characterized in that, The method further includes: A time-based aggregation network is used to aggregate warning information with the same device and the same fault type in the first warning information to determine the first aggregated information.

5. The method according to any one of claims 1 to 4, characterized in that, The determination of the first warning information to be processed for at least one device includes: A fault correlation analysis is performed on the initial warning information to be processed for the at least one device, and the warning information with correlation in the initial warning information is merged to determine the first warning information; the fault correlation analysis is used to identify potentially correlated information in the warning information.

6. The method according to any one of claims 1 to 4, characterized in that, The determination of the first warning information to be processed for at least one device includes: The initial warning information to be processed from the at least one device is filtered to remove erroneous warning information, and the first warning information is determined.

7. The method according to any one of claims 1 to 4, characterized in that, The determination of the first warning information to be processed for at least one device includes: Based on at least one of the attribute information and scene information of the at least one device, the initial warning information to be processed is processed to determine the first warning information.

8. The method according to claim 7, characterized in that, The process of processing the initial warning information to be processed based on at least one of the attribute information and scene information of the at least one device to determine the first warning information includes: Based on at least one of the attribute information and scene information of the least one device, the warning information with the same attribute information and / or the same scene information in the initial warning information to be processed is fused to determine the first warning information; The attribute information of the at least one device includes the chemical composition and production batch of the at least one device; the scenario information of the at least one device includes the usage scenario and operating environment of the at least one device.

9. The method according to any one of claims 1 to 4, characterized in that, The determination of the first warning information to be processed for at least one device includes: Data cleaning and / or data imputation are performed on the initial warning information to be processed to determine the first warning information; wherein, the data cleaning indicates the deletion of duplicate warning information and erroneous warning information in the initial warning information, and the data imputation indicates the addition or correction of erroneous warning information for the missing warning information in the initial warning information.

10. The method according to any one of claims 1 to 9, characterized in that, The determination of the first warning information to be processed for at least one device includes: Upon reaching the first preset time period, incremental data is acquired from the fault warning record to obtain the first warning information for the at least one device.

11. The method according to any one of claims 1 to 10, characterized in that, The step of aggregating warning information with the same device and the same fault type in the first warning information based on a first time interval to determine the first aggregated information includes: Identify at least two sets of warning messages that contain the same equipment and the same fault type in the first warning message; If, in each group of warning messages, multiple warning messages that are adjacent in time and are less than the first time interval, then the multiple warning messages are aggregated to determine the first aggregated message.

12. The method according to claim 11, characterized in that, If, in each group of early warning information, multiple early warning information messages that are adjacent in time and shorter than the first time interval are in chronological order, then the multiple early warning information messages are aggregated to determine the first aggregated information, including: If, in each group of early warning information, multiple early warning information that are adjacent in time are less than the first time interval, then the earliest occurrence time, latest end time, and highest fault level among the multiple early warning information are determined as the fault occurrence time, fault end time, and fault level of an aggregated information. The first aggregated information is determined when all multiple aggregations in each group of early warning information are completed.

13. The method according to any one of claims 1 to 12, characterized in that, The method further includes: In response to the viewing command, the fault warning data and the details entry of the first warning information are displayed on the fault management interface.

14. The method according to claim 13, characterized in that, In response to the viewing command, the fault management interface displays the fault warning data and a details entry for the first warning information, including: In response to the viewing command, the fault management interface displays at least one of the following: fault information, fault level, fault occurrence time, fault end time, device identifier, and fault status of the fault warning data, as well as a details entry for the first warning information.

15. The method according to claim 13 or 14, characterized in that, The method further includes: In response to the triggering operation of the details entry, the fault details information of the first warning information and the historical information viewing entry are displayed on the fault analysis interface; the fault details information includes: the fault occurrence time and fault level of the first warning information; In response to the selection operation of the first warning information, the selected first warning information is displayed on the fault analysis interface in a first manner; In response to the historical information viewing operation, the fault parameters of the selected first warning information under the fault type are displayed in the drop-down page of the fault analysis interface.

16. The method according to claim 15, characterized in that, In response to the historical information viewing operation, the drop-down page of the fault analysis interface displays the fault parameters under the selected fault type of the first warning information, including: In response to the historical information viewing operation, the drop-down page of the fault analysis interface displays different dimensions of the fault parameters of the same device at different times under the fault type to which the selected first warning information belongs.

17. The method according to any one of claims 1 to 16, characterized in that, The step of aggregating the first aggregated information with the first historical early warning information based on the first time interval to obtain the fault early warning data includes: Based on the first time interval, the earliest occurrence time, latest end time, and highest fault level in the first aggregated information and the first historical early warning information are determined as the fault occurrence time, fault end time, and fault level of the fault early warning data.

18. The method according to claim 11, characterized in that, The method further includes: If, in each group of warning information, the time interval between any two adjacent warning information exceeds the first time interval, then the second warning information that caused the earliest failure in the pair of warning information is frozen, and the third warning information that caused the latest failure in the pair of warning information is determined as one of the aggregated information in the first aggregated information.

19. A device for processing early warning information, characterized in that, The device includes: A determination module is used to determine the first warning information to be processed for at least one device; The aggregation module is used to aggregate warning information with the same device and the same fault type in the first warning information based on a first time interval to determine the first aggregated information; and, when a first historical warning information with the same device and the same fault type as the first aggregated information is found in the historical fault data, the first aggregated information is aggregated with the first historical warning information based on the first time interval to obtain the fault warning data.

20. A device for processing early warning information, characterized in that, It includes a memory and a processor, the memory storing a computer program that can run on the processor, the processor executing the program to implement the steps of the method according to any one of claims 1 to 18.

21. A computer storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program performs the steps of the method according to any one of claims 1 to 18.

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