Device alarm information generation method and apparatus, device, and medium

Abstract

The application discloses a device alarm information generation method and device, equipment and medium, and relates to the technical field of device state evaluation. The method comprises the following steps: collecting a candidate power value of a target device at at least one candidate travel position in a current time period; determining a candidate abnormality degree of the target device at the candidate travel position according to the candidate power value, a target power abnormality threshold of the candidate travel position, an abnormality degree threshold and an abnormality correction coefficient; wherein the target power abnormality threshold of the candidate travel position is determined according to a device failure rate of a plurality of candidate devices in a historical time period; the candidate devices are of the same type as the target device; determining a target abnormality degree of the target device according to the candidate abnormality degree at each candidate travel position; and determining target alarm information of the target device from a plurality of candidate alarm information according to the target abnormality degree. The technical scheme of the embodiment of the application improves the generation efficiency of the alarm information and the stability of the device operation.

Description

Technical Field

[0001] This invention relates to the field of equipment condition assessment technology, and in particular to a method, apparatus, device and medium for generating equipment alarms. Background Technology

[0002] The transmission components of subway platform screen doors include motors, couplings, reducers, belts, guide rails, and pulleys. Moving parts include the door body, while fixed structures include the door frame. Failure of these components is the main type of failure for platform screen doors, and such failures pose certain safety hazards and impacts on train operation.

[0003] In existing technologies, data-driven prediction models are mainly used to predict the operating status of equipment. This method requires a large amount of data, involves a large workload of sample labeling, and has a high time cost for machine learning. Summary of the Invention

[0004] This invention provides a method, apparatus, device, and medium for generating equipment alarm information, so as to improve the efficiency of alarm information generation and the stability of equipment operation.

[0005] In a first aspect, embodiments of the present invention provide a method for generating device alarm information, the method comprising:

[0006] Collect candidate power values ​​of the target device at at least one candidate travel position within the current time period;

[0007] The candidate anomaly level of the target device at the candidate travel position is determined based on the candidate power value, the target power anomaly threshold at the candidate travel position, and the anomaly degree threshold; wherein, the target power anomaly threshold at the candidate travel position is determined based on the equipment failure rate of multiple candidate devices in a historical time period; the candidate devices and the target device have the same equipment type;

[0008] The target anomaly level of the target device is determined based on the anomaly level of each candidate travel location.

[0009] Based on the degree of anomaly, the target alarm information of the target device is determined from multiple candidate alarm information.

[0010] Secondly, embodiments of the present invention also provide a device for generating device alarm information, the device comprising:

[0011] The power value acquisition module is used to acquire the candidate power value of the target device at at least one candidate travel position within the current time period;

[0012] The candidate anomaly determination module is used to determine the candidate anomaly degree of the target device at the candidate travel position based on the candidate power value, the target power anomaly threshold of the candidate travel position, and the anomaly degree threshold; wherein, the target power anomaly threshold of the candidate travel position is determined based on the equipment failure rate of multiple candidate devices in a historical time period; the candidate devices and the target device have the same equipment type;

[0013] The target anomaly determination module is used to determine the target anomaly degree of the target device based on the candidate anomaly degree at each candidate travel location.

[0014] The alarm information determination module is used to determine the target alarm information of the target device from multiple candidate alarm information based on the degree of target anomaly.

[0015] Thirdly, embodiments of the present invention also provide an electronic device, comprising:

[0016] At least one processor; and

[0017] A memory that is communicatively connected to at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor is able to execute the device alarm information generation method of any embodiment of the present invention.

[0019] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing computer instructions, which are used to cause a processor to execute and implement the device alarm information generation method of any embodiment of the present invention.

[0020] The technical solution of this invention involves collecting candidate power values ​​of a target device at at least one candidate travel position within the current time period; determining the candidate anomaly level of the target device at each candidate travel position based on the candidate power values, a target power anomaly threshold, and an anomaly level threshold; wherein the power anomaly threshold for each candidate travel position is determined based on the device failure rate of multiple candidate devices within a historical time period; the candidate devices and the target device have the same device type; determining the target anomaly level of the target device based on the candidate anomaly levels at each candidate travel position; and determining the target alarm information of the target device from multiple candidate alarm information based on the target anomaly level. This technical solution improves the efficiency of alarm information generation, promptly reminds technicians to handle the target device based on the alarm information, and enhances the stability of device operation.

[0021] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart of a device alarm information generation method according to Embodiment 1 of the present invention;

[0024] Figure 2 This is a flowchart of a device alarm information generation method according to Embodiment 2 of the present invention;

[0025] Figure 3 This is a structural diagram of a device alarm information generation apparatus according to Embodiment 3 of the present invention;

[0026] Figure 4 This is a schematic diagram of the structure of an electronic device that implements the device alarm information generation method of this invention. Detailed Implementation

[0027] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0028] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices. In the technical solutions of the embodiments of this invention, the acquisition, storage, and application of candidate power values, etc., all comply with relevant laws and regulations and do not violate public order and good morals.

[0029] Example 1

[0030] Figure 1 This is a flowchart illustrating a device alarm information generation method according to Embodiment 1 of the present invention. This embodiment of the invention is applicable to situations involving the generation of device alarm information. The method can be executed by a device alarm information generation device, which can be implemented in hardware and / or software and can be configured in an electronic device, such as a server.

[0031] See Figure 1 The method for generating device alarm information shown includes:

[0032] S101. Collect the candidate power value of the target device at at least one candidate travel position within the current time period.

[0033] In this embodiment, the target device can be a device whose degree of abnormality is to be determined. The candidate stroke position can be a position within the movement stroke of the target device. The candidate power value can be the power value of the target device's motor when the target device is at the candidate stroke position.

[0034] In one optional embodiment, the target device has at least one motion stroke within the current time period. The voltage and current values ​​of the target device's motor at at least one candidate stroke position in each motion stroke are collected; the power value of the motor at at least one candidate stroke position in each motion stroke is determined based on the voltage and current values; for each candidate stroke position, the average of the power values ​​at that candidate stroke position across all motion strokes is determined as the candidate power value of the target device at that candidate stroke position within the current time period. It should be noted that the candidate stroke positions and the length of the time period can be set independently by those skilled in the art based on actual needs or practical experience, and this invention does not limit them.

[0035] In an optional embodiment, when the target device is operating normally, candidate power values ​​are collected at at least one candidate travel position of the target device within the current time period.

[0036] S102. Determine the candidate anomaly level of the target device at the candidate travel position based on the candidate power value, the target power anomaly threshold and the anomaly level threshold at the candidate travel position; wherein, the target power anomaly threshold at the candidate travel position is determined based on the equipment failure rate of multiple candidate devices in the historical time period; the candidate devices and the target device have the same equipment type.

[0037] In this embodiment, the target power anomaly threshold can be a critical value for anomalies in candidate power values ​​at candidate travel positions. The anomaly severity threshold can be a critical value for target device anomalies. The candidate anomaly severity can be represented numerically, characterizing the anomaly of candidate power values ​​at candidate travel positions; where a smaller candidate anomaly severity value indicates a more anomalous candidate power value at candidate travel positions. The historical time period can be a time period prior to the current time period. For example, if a time period is a natural day, i.e., the length of the time period is 24 hours of the corresponding natural day, and the current time period is January 31, then the historical time period can be 30 time periods from January 1 to January 30. The device failure rate is the probability of a candidate device failing within the historical time period. The candidate device can be a device of the same type as the target device. In an optional embodiment, the target device and the candidate device perform the same motion stroke. The target device includes, but is not limited to, mechanical devices that perform reciprocating motion and mechanical devices that perform repetitive motion. Mechanical devices that perform reciprocating motion can be, for example, automatic doors and air conditioning compressors. Taking an automatic door as an example, a set of adjacent opening and closing movements constitutes one round trip motion. Mechanical devices that perform repetitive movements can be, for example, fans or rotating platforms. Taking a fan as an example, the fan blades rotate continuously during operation, and each rotation of the blades constitutes one round trip motion of the fan blades.

[0038] Specifically, for each candidate travel position, the power difference between the candidate power value at that candidate travel position and the target power anomaly threshold at that candidate travel position is determined; the power ratio between the power difference and the target power anomaly threshold at that candidate travel position is determined; the power ratio, the anomaly severity threshold, and the anomaly severity correction coefficient are determined to determine the candidate anomaly severity of the target device at that candidate travel position. For example, the candidate anomaly severity can be represented by the following formula:

[0039]

[0040] Among them, Y ip represents the degree of candidate anomaly at candidate route position i; i r represents the candidate power value at candidate stroke position i; i represents the target power anomaly threshold at candidate travel position i; h represents the anomaly degree threshold; k1 represents the anomaly degree correction coefficient.

[0041] S103. Determine the target anomaly level of the target device based on the candidate anomaly level at each candidate travel location.

[0042] In this embodiment, the target anomaly level can be represented numerically to characterize the overall anomaly level of the target device. The smaller the target anomaly level value, the more abnormal the target device. Specifically, the candidate anomaly level with the smallest value among the candidate anomaly levels at each candidate travel position is determined as the target anomaly level of the target device.

[0043] S104. Based on the degree of anomaly of the target, determine the target alarm information of the target device from multiple candidate alarm information.

[0044] In this embodiment, the target alarm information is the alarm information corresponding to the target anomaly level of the target device. Each candidate alarm information corresponds to a different anomaly level value. Based on the correlation between the candidate alarm information and the anomaly level value, and the target anomaly level, the target alarm information for the target device is determined from multiple candidate alarm information. For example, the candidate alarm information includes a first alarm information and a second alarm information, where the anomaly level value corresponding to the first alarm information is less than the anomaly level value corresponding to the second alarm information. If the target anomaly level value is less than or equal to the anomaly level value corresponding to the first alarm information, then the first alarm information is determined as the target alarm information. If the target anomaly level value is greater than the anomaly level value corresponding to the first alarm information and less than or equal to the anomaly level value corresponding to the second alarm information, then the second alarm information is determined as the target alarm information for the target device. If the target anomaly level value is greater than the anomaly level value corresponding to the second alarm information, then no target alarm information is generated for the target device.

[0045] In one optional embodiment, the anomaly threshold is a monthly inspection alarm threshold; candidate alarm information includes monthly inspection alarm information, and at least one of daily and weekly inspection alarm information. The monthly inspection alarm threshold is the critical value for determining monthly inspection alarm information. Monthly inspection alarm information can be used to indicate that the target equipment needs maintenance within one month; weekly inspection alarm information can be used to indicate that the target equipment needs maintenance within one week; and daily inspection alarm information can be used to indicate that the target equipment needs maintenance on the date corresponding to the current time period.

[0046] It is understandable that by adopting the above technical solution to determine the alarm information of the target equipment from the monthly, weekly, and daily inspection alarm information, the effectiveness of equipment maintenance work can be improved, the equipment failure rate can be reduced, and the stable operation of the target equipment can be guaranteed.

[0047] This invention, in its embodiments, collects candidate power values ​​for a target device at at least one candidate travel position within the current time period; determines the candidate anomaly level of the target device at each candidate travel position based on the candidate power values, a target power anomaly threshold, and an anomaly severity threshold; wherein the power anomaly threshold for each candidate travel position is determined based on the device failure rate of multiple candidate devices within a historical time period; the candidate devices and the target device are of the same device type; the target anomaly level of the target device is determined based on the candidate anomaly levels at each candidate travel position; and the target alarm information for the target device is determined from multiple candidate alarm information based on the target anomaly level. By employing the above technical solution, the efficiency of alarm information generation is improved, allowing for timely reminders to technicians to handle the target device based on the alarm information, enhancing the real-time performance of anomaly location and maintenance, and improving the stability of equipment operation.

[0048] Example 2

[0049] Figure 2 This is a flowchart illustrating the generation of device alarm information according to Embodiment 2 of the present invention. Based on the above embodiments, this embodiment adds an operation to determine the target power anomaly threshold at candidate travel positions.

[0050] Furthermore, the method for generating equipment alarm information is further improved by adding the following: "Based on the candidate power value of the candidate device at the candidate travel position in the current time period, the equipment failure rate of multiple candidate devices in the previous historical time period, and the average failure interval of the target device, determine the power anomaly threshold of the candidate travel position in the current time period; and determine the average value between the power anomaly threshold of the candidate travel position in multiple historical time periods and the power anomaly threshold of the candidate travel position in the current time period as the target power anomaly threshold of the candidate travel position."

[0051] It should be noted that for parts not described in detail in the embodiments of the present invention, please refer to the descriptions in other embodiments.

[0052] See Figure 2 The method for generating device alarm information shown includes:

[0053] S201. Collect the candidate power value of the target device at at least one candidate travel position within the current time period.

[0054] S202. Based on the candidate power value of the candidate device at the candidate travel position in the current time period, the equipment failure rate of multiple candidate devices in the previous historical time period of the current time period, and the average failure interval of the target device, determine the power anomaly threshold of the candidate travel position in the current time period.

[0055] In this embodiment, the mean time between failures (MTBF) of the target device can be a target value that the target device is required to meet during its production design. In an optional embodiment, the candidate device and the target device are of the same type and have the same MTBF. The previous historical time period of the current time period is the adjacent historical time period of the previous time period. For example, if a time period is one calendar day, and the current time period is January 31, then the previous historical time period of the current time period is January 30.

[0056] Optionally, based on the candidate power value of the candidate device at the candidate travel position in the current time period, the equipment failure rate of multiple candidate devices in the previous historical time period of the current time period, and the average fault interval of the target device, the power anomaly threshold of the candidate travel position in the current time period is determined, including: determining the maintenance ratio coefficient in the current time period based on the average fault interval of the target device and the equipment failure rate of multiple candidate devices in the previous historical time period of the current time period; sorting the candidate power values ​​of each candidate device in the current time period, and selecting the candidate power value at the position corresponding to the maintenance ratio coefficient as the power anomaly threshold of the candidate travel position in the current time period.

[0057] The maintenance ratio coefficient can be used to characterize the proportion of candidate equipment requiring maintenance to the total number of candidate equipment. A larger maintenance ratio coefficient indicates a larger number of equipment requiring maintenance, more ineffective maintenance of candidate equipment without abnormalities, and lower effectiveness of maintenance work on each candidate equipment. Conversely, a smaller maintenance ratio coefficient indicates a smaller number of equipment requiring maintenance, fewer ineffective maintenance of candidate equipment without abnormalities, and higher effectiveness of maintenance work on each candidate equipment. In one optional implementation, the maintenance ratio coefficient is expressed as a percentage. In a specific implementation, the candidate power values ​​of each candidate equipment in the current time period are sorted in descending order to determine the percentage order of each candidate power value in the sorting; the candidate power value closest to the percentage corresponding to the maintenance ratio coefficient is selected as the power anomaly threshold for the candidate travel position in the current time period.

[0058] It is understandable that by adopting the above technical solution, the maintenance ratio coefficient in the current time period is determined, and the power anomaly threshold of the candidate travel position in the current time period is determined by the maintenance ratio coefficient in the current time period. The power anomaly threshold can be adjusted according to the maintenance ratio coefficient, and the target anomaly degree of the target equipment can be adjusted by adjusting the power anomaly threshold. This avoids generating incorrect target alarm information for the target equipment when it is operating normally, which would cause the target equipment to need maintenance and increase the number of unnecessary maintenance equipment. It can effectively improve the accuracy of the target anomaly degree, the effectiveness of the target alarm information, and the effectiveness of the number of maintenance equipment determined based on the target alarm information.

[0059] In an optional embodiment, determining the maintenance ratio coefficient in the current time period based on the mean time between failures of the target device and the failure rates of multiple candidate devices in the previous historical time period of the current time period includes: determining the product between the mean time between failures of the target device and the failure rates of multiple candidate devices in the previous historical time period of the current time period; determining the ratio between the maintenance ratio correction coefficient and the product; and determining the sum of the ratio and the preset maintenance ratio as the maintenance ratio coefficient in the current time period.

[0060] The maintenance ratio correction factor can be a factor used to adjust the maintenance ratio coefficient. The preset maintenance ratio and the maintenance ratio correction factor can be set independently by technical personnel based on actual needs or practical experience. For example, the maintenance ratio coefficient can be expressed by the following formula:

[0061]

[0062] Where M represents the maintenance ratio coefficient; m represents the preset maintenance ratio; k2 represents the maintenance ratio correction coefficient; T represents the mean time between failures; and e represents the equipment failure rate.

[0063] It is understandable that by adopting the above technical solution, the accuracy of the maintenance ratio coefficient can be improved, thereby improving the accuracy of the power anomaly threshold of the candidate travel position in the current time period determined based on the maintenance ratio coefficient, and further improving the accuracy of the target power anomaly threshold of the candidate travel position.

[0064] The technical solution of this invention performs dynamic threshold self-learning by using the candidate power data of the target device and candidate devices of the same type. This avoids the high workload caused by acquiring and labeling fault samples in the prior art, improves the efficiency of alarm information generation, and enhances the applicability to mechanical transmission equipment.

[0065] S203. The average value between the power anomaly threshold corresponding to the candidate travel position in multiple historical time periods and the power anomaly threshold of the candidate travel position in the current time period is determined as the target power anomaly threshold of the candidate travel position.

[0066] S204. Determine the candidate anomaly level of the target device at the candidate travel position based on the candidate power value, the target power anomaly threshold, and the anomaly level threshold at the candidate travel position; wherein, the power anomaly threshold at the candidate travel position is determined based on the equipment failure rate of multiple candidate devices in a historical time period; the candidate devices and the target device have the same equipment type.

[0067] S205. Determine the target anomaly level of the target device based on the candidate anomaly level at each candidate travel location.

[0068] S206. Based on the degree of anomaly of the target, determine the target alarm information of the target device from multiple candidate alarm information.

[0069] This invention determines the power anomaly threshold of a candidate travel position in the current time period based on the candidate power value of a candidate device at a candidate travel position in the current time period, the device failure rate of multiple candidate devices in the previous historical time period, and the average fault interval of the target device. The average power anomaly threshold between the candidate travel position's corresponding power anomaly thresholds in multiple historical time periods and the candidate travel position's power anomaly threshold in the current time period is then determined as the target power anomaly threshold for the candidate travel position. By employing this technical solution, the accuracy of the target power anomaly threshold is improved, thereby enhancing the accuracy of determining the candidate anomaly degree at each candidate travel position based on the target power anomaly threshold.

[0070] Example 3

[0071] Figure 3 This is a schematic diagram of a device alarm information generation apparatus according to Embodiment 3 of the present invention. This embodiment of the present invention is applicable to situations involving the generation of device alarm information. The apparatus can perform device alarm information generation and can be implemented in hardware and / or software. The apparatus can be configured in electronic devices, such as servers.

[0072] See Figure 3 The device alarm information generation apparatus shown includes: a power value acquisition module 301, a candidate anomaly degree determination module 302, a target anomaly degree determination module 303, and an alarm information determination module 304, wherein...

[0073] The power value acquisition module 301 is used to acquire the candidate power value of the target device at at least one candidate travel position within the current time period;

[0074] The candidate anomaly determination module 302 is used to determine the candidate anomaly degree of the target device at the candidate travel position based on the candidate power value, the target power anomaly threshold of the candidate travel position, and the anomaly degree threshold; wherein, the target power anomaly threshold of the candidate travel position is determined based on the equipment failure rate of multiple candidate devices in a historical time period; the candidate devices and the target device have the same equipment type;

[0075] The target anomaly determination module 303 is used to determine the target anomaly degree of the target device based on the candidate anomaly degree at each candidate travel position;

[0076] The alarm information determination module 304 is used to determine the target alarm information of the target device from multiple candidate alarm information based on the degree of target anomaly.

[0077] This invention employs a power value acquisition module to acquire candidate power values ​​of a target device at at least one candidate travel position within the current time period; a candidate anomaly determination module to determine the candidate anomaly degree of the target device at each candidate travel position based on the candidate power values, a target power anomaly threshold at the candidate travel position, and an anomaly degree threshold; wherein the power anomaly threshold at the candidate travel position is determined based on the device failure rate of multiple candidate devices within a historical time period; and the candidate devices and the target device are of the same device type; a target anomaly degree determination module to determine the target anomaly degree of the target device based on the candidate anomaly degree at each candidate travel position; and an alarm information determination module to determine the target alarm information of the target device from multiple candidate alarm information based on the target anomaly degree. By adopting the above technical solution, the efficiency of alarm information generation is improved, allowing for timely reminders to technicians to handle the target device based on the alarm information, thereby improving the stability of equipment operation.

[0078] Optionally, the device may also include:

[0079] The first threshold determination module is used to determine the power anomaly threshold of the candidate travel position in the current time period based on the candidate power value of the candidate device at the candidate travel position in the current time period, the equipment failure rate of multiple candidate devices in the previous historical time period of the current time period, and the average failure interval of the target device.

[0080] The second threshold determination module is used to determine the target power anomaly threshold of the candidate travel position as the average value between the power anomaly threshold corresponding to the candidate travel position in multiple historical periods and the power anomaly threshold of the candidate travel position in the current time period.

[0081] Optionally, the first threshold determination module includes:

[0082] The reliability determination unit is used to determine the maintenance ratio coefficient in the current time period based on the mean time between failures of the target equipment and the equipment failure rate of multiple candidate equipment in the previous historical time period of the current time period.

[0083] The threshold determination unit is used to sort the candidate power values ​​of each candidate device in the current time period, and select the candidate power value at the position corresponding to the maintenance ratio coefficient as the power anomaly threshold of the candidate travel position in the current time period.

[0084] Optional, reliability determination unit, specifically used for:

[0085] Determine the product of the mean time between failures of the target device and the device failure rate of multiple candidate devices in the previous historical time period of the current time period;

[0086] Determine the ratio between the maintenance ratio correction factor and the product;

[0087] The sum of the ratio and the preset maintenance ratio is determined as the maintenance ratio coefficient in the current time period.

[0088] Optionally, in this device, the anomaly threshold is the monthly inspection alarm threshold; the candidate alarm information includes monthly inspection alarm information, and at least one of daily inspection alarm information and weekly inspection alarm information.

[0089] Optionally, in this device, the target device and the candidate device perform the same motion stroke.

[0090] Optionally, the target device in the apparatus includes a mechanical device that performs reciprocating motion.

[0091] The device alarm information generation apparatus provided in this embodiment of the invention can execute the device alarm information generation method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the device alarm information generation method.

[0092] Example 4

[0093] Figure 4A schematic diagram of an electronic device 410 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0094] like Figure 4 As shown, the electronic device 410 includes at least one processor 411 and a memory, such as a read-only memory (ROM) 412 or a random access memory (RAM) 413, communicatively connected to the at least one processor 411. The memory stores computer programs executable by the at least one processor. The processor 411 can perform various appropriate actions and processes based on the computer program stored in the ROM 412 or loaded from storage unit 418 into the RAM 413. The RAM 413 may also store various programs and data required for the operation of the electronic device 410. The processor 411, ROM 412, and RAM 413 are interconnected via a bus 414. An input / output (I / O) interface 415 is also connected to the bus 414.

[0095] Multiple components in electronic device 410 are connected to I / O interface 415, including: input unit 416, such as keyboard, mouse, etc.; output unit 417, such as various types of displays, speakers, etc.; storage unit 418, such as disk, optical disk, etc.; and communication unit 419, such as network card, modem, wireless transceiver, etc. Communication unit 419 allows electronic device 410 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0096] Processor 411 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 411 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 411 performs the various methods and processes described above, such as the device alarm information generation method.

[0097] In some embodiments, the device alarm information generation method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 418. In some embodiments, part or all of the computer program may be loaded into and / or installed on electronic device 410 via ROM 412 and / or communication unit 419. When the computer program is loaded into RAM 413 and executed by processor 411, one or more steps of the device alarm information generation method described above may be performed. Alternatively, in other embodiments, processor 411 may be configured to perform the device alarm information generation method by any other suitable means (e.g., by means of firmware).

[0098] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0099] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0100] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0101] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0102] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0103] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0104] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0105] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for generating equipment alarm information, characterized in that, The method includes: Collect candidate power values ​​of the target device at at least one candidate travel position within the current time period; Based on the candidate power value, the target power anomaly threshold at the candidate travel position, and the anomaly degree threshold, the candidate anomaly degree of the target device at the candidate travel position is determined; wherein, the target power anomaly threshold at the candidate travel position is determined based on the device failure rate of multiple candidate devices within a historical time period; the candidate devices are of the same type as the target device; The target anomaly degree of the target device is determined based on the candidate anomaly degree at each of the candidate travel locations; Based on the degree of anomaly of the target, the target alarm information of the target device is determined from multiple candidate alarm information; The target power anomaly threshold for the candidate travel location is determined in the following manner: Based on the candidate power value of the candidate device at the candidate travel position in the current time period, the device failure rate of multiple candidate devices in the previous historical time period of the current time period, and the average failure interval of the target device, the power anomaly threshold of the candidate travel position in the current time period is determined. The target power anomaly threshold for the candidate travel location is determined by averaging the power anomaly thresholds corresponding to the candidate travel location in multiple historical time periods and the power anomaly threshold for the candidate travel location in the current time period.

2. The method according to claim 1, characterized in that, The step of determining the power anomaly threshold of the candidate travel position in the current time period based on the candidate power value of the candidate device at the candidate travel position in the current time period, the device failure rate of multiple candidate devices in the previous historical time period of the current time period, and the average failure interval of the target device includes: Based on the mean time between failures of the target equipment and the equipment failure rates of multiple candidate equipment in the previous historical time period of the current time period, determine the maintenance ratio coefficient in the current time period. The candidate power values ​​of each candidate device in the current time period are sorted, and the candidate power value at the position corresponding to the maintenance ratio coefficient is selected as the power anomaly threshold of the candidate travel position in the current time period. Specifically, the candidate power values ​​of each candidate device in the current time period are sorted, and the candidate power value at the position corresponding to the maintenance ratio coefficient is selected as the power anomaly threshold of the candidate travel position in the current time period, including: Sort the candidate power values ​​of each candidate device in the current time period in descending order to determine the percentage order of each candidate power value in the sorting. The candidate power value that is closest to the percentage corresponding to the maintenance ratio coefficient is selected as the power anomaly threshold of the candidate travel position in the current time period.

3. The method according to claim 2, characterized in that, The step of determining the maintenance ratio coefficient in the current time period based on the mean time between failures of the target equipment and the equipment failure rate of multiple candidate equipment in the previous historical time period includes: Determine the product of the mean time between failures of the target device and the device failure rate of multiple candidate devices in the previous historical time period of the current time period; Determine the ratio between the maintenance ratio correction factor and the product; The sum of the ratio and the preset maintenance ratio is determined as the maintenance ratio coefficient in the current time period.

4. The method according to claim 1, characterized in that, The anomaly threshold is the monthly alarm threshold; candidate alarm information includes monthly alarm information, and at least one of daily alarm information and weekly alarm information.

5. The method according to claim 1, characterized in that, The target device and the candidate device perform the same motion stroke.

6. The method according to claim 5, characterized in that, The target equipment includes: mechanical equipment that performs reciprocating motion.

7. A device alarm generation apparatus, characterized in that, The device includes: The power value acquisition module is used to acquire the candidate power value of the target device at at least one candidate travel position within the current time period; The candidate anomaly degree determination module is used to determine the candidate anomaly degree of the target device at the candidate travel position based on the candidate power value, the target power anomaly threshold of the candidate travel position, and the anomaly degree threshold; wherein, the power anomaly threshold of the candidate travel position is determined based on the equipment failure rate of multiple candidate devices in a historical time period; the candidate devices are of the same type as the target device; The target anomaly degree determination module is used to determine the target anomaly degree of the target device based on the candidate anomaly degree at each of the candidate travel positions; The alarm information determination module is used to determine the target alarm information of the target device from multiple candidate alarm information based on the degree of target anomaly. The device further includes: The first threshold determination module is used to determine the power anomaly threshold of the candidate travel position in the current time period based on the candidate power value of the candidate device at the candidate travel position in the current time period, the device failure rate of multiple candidate devices in the previous historical time period of the current time period, and the average failure interval time of the target device. The second threshold determination module is used to determine the target power anomaly threshold of the candidate travel position as the average value between the power anomaly threshold corresponding to the candidate travel position in multiple historical time periods and the power anomaly threshold of the candidate travel position in the current time period.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the device alarm information generation method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that are used to cause a processor to execute the device alarm information generation method according to any one of claims 1-6.

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