Fault detection method and device, fault processing method and device, computer equipment and medium

Abstract

The invention relates to the technical field of data processing, in particular to a fault detection method and device, a fault processing method and device, computer equipment and a medium. The method comprises the following steps: analyzing a state information signal of a to-be-analyzed device to obtain a device signal fault level, analyzing a data transmission integrity rate to determine a data transmission fault level, analyzing a data packet loss rate to obtain a network fault level, and determining the fault level of the to-be-analyzed device according to the device signal fault level, the data transmission fault level and the network fault level. And determining the equipment fault level of the equipment. Therefore, multi-dimensional detection is automatically carried out on the fault information of the detection equipment so as to efficiently determine the fault level of the equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly to a fault detection and fault handling method, device, computer device, and medium. Background Art

[0002] The core objective of the acquisition device fault detection method is to quickly identify abnormal device operation and accurately locate the fault cause through multi-dimensional data analysis. With the rapid development of the Internet of Things technology, the device status monitoring system is increasingly widely used in fields such as industrial manufacturing and energy management.

[0003] Currently, most device fault detection methods mainly rely on single-dimensional index analysis. For example, the online status is judged through the device heartbeat signal, or the communication quality is evaluated based on network layer parameters. However, these methods lack a quantitative evaluation of the signal quality continuity, fail to establish a multi-dimensional evaluation system for the transmission process, and have insufficient fault location accuracy.

[0004] Therefore, how to automatically perform multi-dimensional detection on the fault information of the detection device to efficiently determine the device fault level has become an urgent problem to be solved. Summary of the Invention

[0005] Embodiments of the present invention provide a fault detection and fault handling method, device, computer device, and medium to solve the problem of how to automatically perform multi-dimensional detection on the fault information of the detection device to efficiently determine the device fault level.

[0006] In a first aspect, embodiments of the present invention provide a method for detecting faults of an acquisition device, including: Obtain the detection information of the device to be analyzed detected by the detection device in real time, and extract the status signal of the device to be analyzed, the total amount of data transmitted by the device to be analyzed, and the interaction information between the device to be analyzed and the detection device from the detection information; According to the status signal, determine the offline duration of the device to be analyzed, and according to the offline duration, determine the device signal fault level. Calculate the ratio of the total amount of data to a preset amount of data to obtain the data transmission integrity rate, and according to the data transmission integrity rate, determine the data transmission fault level; Input the interaction information into a preset extraction model, and output the round-trip time of the data packet transmission between the detection device and the device to be analyzed, the total amount of received data received by the detection device, and the total amount of data packets sent by the device to be analyzed; According to the round-trip time, determine the information delay time, calculate the ratio of the total amount of received data to the total amount of sent data to obtain the data packet loss rate of the device to be analyzed, and according to the information delay time and the data packet loss rate, determine the network fault level of the device to be analyzed; Determine the device fault level of the device to be analyzed according to the device signal fault level, the data transmission fault level, and the network fault level.

[0007] In a second aspect, an embodiment of the present invention provides a method for processing a collection device fault, including: After the device fault level generated by the method for generating a collection device fault detection is obtained, obtain a historical fault database, and extract the signal fault historical processing operations corresponding to the device signal fault level, the data transmission fault historical processing operations corresponding to the data transmission fault level, and the network fault historical processing operations corresponding to the network fault level from the historical fault database; Perform fault processing on the device to be analyzed according to the signal fault historical processing operation, the data transmission fault historical processing operation, and the network fault historical processing operation.

[0008] In a third aspect, an embodiment of the present invention provides a collection device fault detection device, including: An information extraction module, configured to obtain the detection information of the device to be analyzed detected by the detection device in real time, and extract the status signal of the device to be analyzed, the total amount of data transmitted by the device to be analyzed, and the interaction information between the device to be analyzed and the detection device from the detection information; A fault level determination module, configured to determine the device offline duration of the device to be analyzed according to the status signal, determine the device signal fault level according to the device offline duration, calculate the ratio of the total amount of data to a preset amount of data to obtain a data transmission integrity rate, and determine the data transmission fault level according to the data transmission integrity rate; An interaction information extraction module, configured to input the interaction information into a preset extraction model, and output the round-trip time of data packet transmission between the detection device and the device to be analyzed, the total amount of received data received by the detection device, and the total amount of data packets sent by the device to be analyzed; A network fault determination module, configured to determine the information delay time according to the round-trip time, calculate the ratio of the total amount of received data to the total amount of sent data to obtain the data packet loss rate of the device to be analyzed, and determine the network fault level of the device to be analyzed according to the information delay time and the data packet loss rate; A device fault determination module, configured to determine the device fault level of the device to be analyzed according to the device signal fault level, the data transmission fault level, and the network fault level.

[0009] In a fourth aspect, an embodiment of the present invention provides a collection device fault detection device, including: A historical data processing module, configured to obtain a historical fault database after the device fault level generated by the generating method of the acquisition device fault detection, and extract the signal fault historical processing operations corresponding to the device signal fault level, the data transmission fault historical processing operations corresponding to the data transmission fault level, and the network fault historical processing operations corresponding to the network fault level from the historical fault database; A fault processing module, configured to perform fault processing on the device to be analyzed according to the signal fault historical processing operation, the data transmission fault historical processing operation, and the network fault historical processing operation.

[0010] In a fifth aspect, an embodiment of the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the above-mentioned acquisition device fault detection method or acquisition device fault processing method is implemented.

[0011] In a sixth aspect, an embodiment of the present invention provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the above-mentioned acquisition device fault detection method or acquisition device fault processing method is implemented.

[0012] The beneficial effects of the present invention compared with the prior art are as follows: By obtaining the detection information of the device to be analyzed detected by the detection device in real time, extracting the status signal of the device to be analyzed, the total amount of data transmitted by the device to be analyzed, and the interaction information between the device to be analyzed and the detection device in the detection information, determining the device offline duration of the device to be analyzed according to the status signal, determining the device signal fault level according to the device offline duration, calculating the ratio of the total amount of data to the preset amount of data to obtain the data transmission integrity rate, determining the data transmission fault level according to the data transmission integrity rate, inputting the interaction information into a preset extraction model, outputting the round-trip time of the data packet transmission between the detection device and the device to be analyzed, the total amount of received data received by the detection device, and the total amount of data packets sent by the device to be analyzed, determining the information delay time according to the round-trip time, calculating the ratio of the total amount of received data to the total amount of sent data to obtain the data packet loss rate of the device to be analyzed, determining the network fault level of the device to be analyzed according to the information delay time and the data packet loss rate, and determining the device fault level of the device to be analyzed according to the device signal fault level, the data transmission fault level, and the network fault level. By analyzing the status information number of the device to be analyzed to obtain the device signal fault level, analyzing the data transmission integrity rate to determine the data transmission fault level, analyzing the data packet loss rate to obtain the network fault level, and determining the device fault level of the device according to the device signal fault level, the data transmission fault level, and the network fault level. Automatically perform multi-dimensional detection on the fault information of the detection device to efficiently determine the device fault level. Brief Description of the Drawings

[0013] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments of the present invention. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0014] Figure 1 is a schematic diagram of the application environment of a method for detecting faults in a collection device provided in the first embodiment of the present invention; Figure 2 is a schematic flowchart of a method for detecting faults in a collection device provided in the second embodiment of the present invention; Figure 3 is a schematic flowchart of a method for detecting faults in a collection device provided in the third embodiment of the present invention; Figure 4 is a schematic flowchart of a method for processing faults in a collection device provided in the fourth embodiment of the present invention; Figure 5 is a schematic flowchart of a method for processing faults in a collection device provided in the fifth embodiment of the present invention; Figure 6 is a schematic flowchart of a method for processing faults in a collection device provided in the sixth embodiment of the present invention; Figure 7 is a schematic structural diagram of a device for detecting faults in a collection device provided in the seventh embodiment of the present invention; Figure 8 is a schematic structural diagram of a device for processing faults in a collection device provided in the eighth embodiment of the present invention; Figure 9 is a schematic structural diagram of a computer device provided in the ninth embodiment of the present invention. Detailed Description of the Embodiments

[0015] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0016] Such as Figure 1As shown in the figure, it is a schematic diagram of the application environment of a method for detecting faults in a collection device provided in the first embodiment of the present invention. Among them, the client and the server are connected for communication. Users can provide conditions, requirements, operation instructions, etc. for detecting faults in the collection device to the server by operating the client. The server is used to execute the method for detecting faults in the collection device of the present invention according to the relevant content sent by the client. Among them, the client includes, but is not limited to, various computer devices such as personal computers, laptops, smartphones, tablets, and portable wearable devices. The corresponding computer device of the server can be implemented by an independent server or a server cluster composed of multiple servers.

[0017] As Figure 2 shown in the figure, it is a schematic flowchart of a method for detecting faults in a collection device provided in the second embodiment of the present invention. Among them, this method for detecting faults in the collection device is applied to the Figure 1 server in the figure. This method for detecting faults in the collection device may include the following steps: Step S201, obtain the detection information of the device to be analyzed detected by the detection device in real time, and extract the status signal of the device to be analyzed, the total amount of data transmitted by the device to be analyzed, and the interaction information between the device to be analyzed and the detection device from the detection information.

[0018] Among them, the detection device continuously monitors a specific device to be analyzed. The detection device has a variety of sensors and data collection functions, and can obtain various operation information of the device to be analyzed from different angles. For example, if the device to be analyzed is a machine on an industrial production line, the detection device may monitor the current consumption of the machine through a current sensor and monitor the vibration amplitude of the machine through a vibration sensor.

[0019] Real-time detection is to ensure that the information obtained can accurately reflect the current operating state of the device to be analyzed. Because the state of the device may change at any time, real-time detection allows the server to timely understand the latest situation of the device, so as to quickly respond when the device has an abnormality.

[0020] The detection device will transmit the collected detection information to the server through a certain communication method (such as wired network, wireless network, etc.). After the server receives this information, it has the original data for analyzing the faults of the device to be analyzed.

[0021] The status signal is a kind of information describing the current working state of the device to be analyzed. It can be a simple binary signal (such as the device is turned on or off), or a complex signal containing more status information. For example, for a smart meter, the status signal may include whether the meter is normally powered on, whether it is in the data collection mode, whether there is a fault alarm, etc.

[0022] The status signal can help the server quickly determine whether the device to be analyzed is in a normal working state. If the status signal indicates that the device is in an abnormal state, then the possible problems of the device can be further analyzed in depth. In the subsequent steps, determining the offline duration of the device based on the status signal is also based on an accurate judgment of the device status.

[0023] The total amount of data refers to the sum of the data transmitted by the device to be analyzed within a certain period of time. This amount of data can be the number of bytes, the number of data packets, etc. For example, in a fault detection scenario of a network camera, the total amount of data is the amount of video data transmitted by the camera within a certain period of time.

[0024] The interaction information mainly records the data communication process between the device to be analyzed and the detection device. It includes the sending and receiving times of data packets, the size of data packets, the sequence numbers of data packets, etc. For example, in a detection scenario of an Internet of Things device, the interaction information can show how often the device sends data to the detection device and how much data is sent each time.

[0025] In step S202, according to the status signal, determine the offline duration of the device to be analyzed. According to the offline duration of the device, determine the device signal fault level. Calculate the ratio of the total amount of data to the preset amount of data to obtain the data transmission integrity rate. According to the data transmission integrity rate, determine the data transmission fault level.

[0026] Optionally, detect the status signal and record the offline status signal when the device is offline.

[0027] Extract the offline duration of the device corresponding to the offline status signal in the detection information.

[0028] According to the offline duration of the device, determine the device signal fault level.

[0029] Among them, the status signal can reflect the current working state of the device to be analyzed and is the key basis for judging whether the device is offline. Usually, the status signal will represent different states of the device in a certain coding or specific identifier. For example, "0" represents the device is offline and "1" represents the device is online.

[0030] The server will continuously monitor the change of the status signal. When the status signal changes from "online" to "offline", the timing starts; when the status signal changes from "offline" to "online" again, the timing stops, and the time interval during this period is the device offline duration. If the device remains in the offline state all the time, the offline duration will continue to accumulate. The device offline duration is an important indicator to measure the severity of the device signal failure. Generally speaking, the longer the offline duration, the greater the possibility of the device signal failure and the higher the failure level. Different offline duration intervals can be preset to correspond to different failure levels. For example, when the offline duration is within 0 - 1 minute, it is determined as a minor failure, which may be caused by temporary network fluctuations or a short device restart. When the offline duration is within 1 - 2 minutes, it is determined as a moderate failure, and there may be minor device hardware failures or unstable network connections. When the offline duration exceeds 2 minutes, it is determined as a severe failure, which may be due to serious problems such as device hardware damage or network interruption.

[0031] The total data volume is the actual data volume transmitted by the device to be analyzed within a certain period of time, while the preset data volume is a standard value preset according to the data volume that should be transmitted under the normal working state of the device. The setting of the preset data volume usually takes into account factors such as the function of the device, the working mode, and the business requirements.

[0032] The calculation formula for the data transmission integrity rate is: data transmission integrity rate = (total data volume / preset data volume) × 100%. For example, if the preset data volume is 1000MB and the actual total data volume is 800MB, then the data transmission integrity rate = (800 / 1000) × 100% = 80%.

[0033] The data transmission integrity rate reflects the integrity of the data during the transmission process. The lower the integrity rate, the more data is lost or not transmitted, and the more serious the data transmission failure. Different failure levels can be divided according to different data transmission integrity rate intervals. For example, when the data transmission integrity rate is within 90% - 100%, it is determined as no failure or a minor failure, and there may be a small amount of data loss, but it does not affect the normal use of the device. When the data transmission integrity rate is within 70% - 90%, it is determined as a moderate failure, with more data loss, which may affect some functions of the device. When the data transmission integrity rate is lower than 70%, it is determined as a severe failure, with a large amount of data loss, and the device may not work properly.

[0034] Step S203, input the interaction information into the preset extraction model, and output the round - trip time of the data packet transmission between the detection device and the device to be analyzed, the total received amount received by the detection device, and the total sent amount of the data packets sent by the device to be analyzed.

[0035] Among them, the preset extraction model is a specially trained algorithm model, including but not limited to, deep learning models, rule-based models, and machine learning models. Its main task is to accurately identify and extract useful key metrics from complex interaction information. This model is like an intelligent data filter that can find the round-trip time, total received volume, and total sent volume we need from a vast amount of raw interaction information.

[0036] In the model training stage, a large amount of historical interaction information data is used as training samples. These data contain interaction information under different network environments and different device states, and at the same time, the corresponding true values such as round-trip time, total received volume, and total sent volume are labeled. Through machine learning or deep learning algorithms, the model learns the mapping relationship between interaction information and these key metrics, so that it can accurately output the required metrics when facing new interaction information.

[0037] The round-trip time refers to the total time it takes for a data packet to be sent from the device to be analyzed to the detection device and then returned from the detection device to the device to be analyzed. It reflects the latency of data transmission between devices and is an important indicator to measure network communication efficiency. The longer the round-trip time, the greater the latency encountered during data transmission, which may indicate problems such as network congestion and slow device processing speed. For example, in a real-time video call scenario, if the round-trip time is too long, it will cause phenomena such as frozen images and delayed sound.

[0038] The total received volume refers to the number of data packets or the number of data bytes actually received by the detection device from the device to be analyzed within a certain period of time. It reflects how much data sent by the device to be analyzed has successfully reached the detection device. By comparing it with the total sent volume of the data packets sent by the device to be analyzed, it is possible to determine whether there is data loss. If the total received volume is much smaller than the total sent volume, it means that packet loss has occurred during data transmission, and the network failure needs to be further investigated. The total sent volume refers to the number of data packets or the number of data bytes sent by the device to be analyzed within the same period of time. It reflects the data sending ability and workload of the device to be analyzed. Combining the total received volume and the round-trip time, the network performance of the device can be comprehensively evaluated. For example, if the total sent volume is large, but the total received volume is small and the round-trip time is long, it may indicate insufficient network bandwidth or network interference.

[0039] For example, if the device to be analyzed is an intelligent camera and the detection device is a regional gateway. The camera continuously sends video data packets to the gateway, and the gateway records the interaction information with the camera. After inputting this interaction information into a preset extraction model, the model outputs a round-trip time of 50 milliseconds, indicating that it takes approximately 50 milliseconds for the data packet to travel from the camera to the gateway and back to the camera; the total number of received packets by the detection device is 1000, and the total number of sent packets by the device to be analyzed is 1020. From this, it can be inferred that approximately 20 packets are lost during transmission, indicating that there may be a minor network fault.

[0040] Step S204: Determine the information delay time based on the round-trip time, calculate the ratio of the total received amount to the total sent amount to obtain the data packet loss rate of the device to be analyzed, and determine the network fault level of the device to be analyzed based on the information delay time and the data packet loss rate.

[0041] Among them, in network communication, the round-trip time (RTT) refers to the time elapsed from when a data packet is sent from the sending end until the return data packet is received. Usually, we can approximately consider the round-trip time as a measure of the delay caused by the information transmission in the network. Because the time consumed in the process of the data packet being sent from the device to be analyzed to the detection device and then returned from the detection device to the device to be analyzed is mainly due to delays caused by factors such as network transmission and device processing. Therefore, in this step, the round-trip time obtained in step S203 can be directly determined as the information delay time. For example, if the round-trip time of data packet transmission between the detection device and the device to be analyzed output in step S203 is 80 milliseconds, then the information delay time is 80 milliseconds.

[0042] The data packet loss rate is an important indicator to measure network reliability and reflects the proportion of lost data packets during data transmission. By comparing the total number of sent packets by the device to be analyzed and the total number of received packets by the detection device, we can calculate the number of lost data packets and then obtain the data packet loss rate. The calculation formula is: Data packet loss rate = (Total sent amount - Total received amount) ÷ Total sent amount × 100%. For example, assume that the total number of sent packets by the device to be analyzed obtained in step S203 is 1000, and the total number of received packets by the detection device is 950. Then the data packet loss rate = (1000 - 950) ÷ 1000 × 100% = 5% Information delay time and data packet loss rate are two key indicators for evaluating network performance. Generally speaking, the longer the information delay time and the higher the data packet loss rate, the more serious the network fault. Therefore, the network fault level of the device to be analyzed can be determined according to the threshold ranges of information delay time and data packet loss rate at different preset levels. For example, when the information delay time is between 30 - 60 milliseconds or the data packet loss rate is between 1% - 3%, there may be some minor problems in the network, but it has little impact on general network applications, and it is judged as a first-level fault; when the information delay time is between 60 - 100 milliseconds or the data packet loss rate is between 3% - 5%, the network performance significantly deteriorates, which may affect some applications with high real-time requirements, such as video calls and online games, and it is judged as a second-level fault; when the information delay time is greater than 100 milliseconds or the data packet loss rate is greater than 5%, the network fault is serious, which may cause most network applications to be unable to be used normally, and it is judged as a third-level fault.

[0043] Step S205, determine the device fault level of the device to be analyzed according to the device signal fault level, data transmission fault level, and network fault level.

[0044] Among them, different weights are assigned to the device signal fault level, data transmission fault level, and network fault level, and then the weighted average value is calculated, and the device fault level is determined according to the interval where the average value is located. The setting of the weights needs to consider the influence degree of each factor on the overall operation of the device according to the actual situation.

[0045] For example, the weight of the device signal fault level is 0.3, the weight of the data transmission fault level is 0.3, and the weight of the network fault level is 0.4. The device signal fault level is 2 (medium fault), the data transmission fault level is 3 (severe fault), and the network fault level is 3 (severe fault). Calculate the weighted average value, (2×0.3 + 3×0.3 + 3×0.4) = 2.7; preset the grade interval, 1 - 1.5 is the first level (minor fault), 1.6 - 2.5 is the second level (medium fault), 2.6 - 3.5 is the third level (severe fault), and according to the calculation result of 2.7, it can be determined that the device fault level is the third level (severe fault).

[0046] In the embodiment of the present application, by obtaining the detection information of the device to be analyzed detected by the detection device in real time, extracting the status signal of the device to be analyzed, the total amount of data transmitted by the device to be analyzed, and the interaction information between the device to be analyzed and the detection device from the detection information, determining the offline duration of the device to be analyzed according to the status signal, determining the device signal failure level according to the offline duration of the device, calculating the ratio of the total amount of data to the preset amount of data to obtain the data transmission integrity rate, determining the data transmission failure level according to the data transmission integrity rate, inputting the interaction information into a preset extraction model, outputting the round-trip time of the data packet transmission between the detection device and the device to be analyzed, the total amount of received data received by the detection device, and the total amount of data packets sent by the device to be analyzed, determining the information delay time according to the round-trip time, calculating the ratio of the total amount of received data to the total amount of sent data to obtain the data packet loss rate of the device to be analyzed, determining the network failure level of the device to be analyzed according to the information delay time and the data packet loss rate, and determining the device failure level of the device to be analyzed according to the device signal failure level, the data transmission failure level, and the network failure level. By analyzing the status information signal of the device to be analyzed, the device signal failure level is obtained. By analyzing the data transmission integrity rate, the data transmission failure level is determined. By analyzing the data packet loss rate, the network failure level is obtained. According to the device signal failure level, the data transmission failure level, and the network failure level, the device failure level of the device is determined. Automatically detecting the fault information of the detection device in multiple dimensions to efficiently determine the device failure level.

[0047] As Figure 3 shown, it is a schematic flowchart of a method for detecting faults of a collection device provided in Embodiment 3 of the present invention. After determining the device failure level of the device to be analyzed in step S205, the method for detecting faults of the collection device may further include the following steps: Step S301, obtaining the online status signal corresponding to the device to be analyzed according to the status signal of the device to be analyzed; Step S302, repeatedly executing the step of obtaining the online status signal corresponding to the device to be analyzed according to the status signal of the device to be analyzed until the online status signals of N devices to be analyzed are obtained, where N is an integer greater than zero.

[0048] Step S303, determining the offline devices according to the N online status signals and the preset total number of devices, and obtaining the gateway offline devices under the same gateway according to the offline devices.

[0049] Step S304, obtaining the device location information of the gateway offline device, obtaining the coverage area of the gateway offline device according to the device location information, and determining the gateway device failure level according to the coverage area.

[0050] Among them, the monitoring system will collect various status signals of the device to be analyzed in real time, such as the heartbeat packet sent by the device, the connection status of the communication port, the response information returned by the device, etc. Then, these status signals are analyzed according to the pre-set rules. For example, if the device successfully sends a heartbeat packet and returns normal response information within the specified time, it is determined that the online status signal of the device is "online"; otherwise, if no heartbeat packet or abnormal response information is received within a certain time, it is determined to be "offline".

[0051] Among them, the online status signal of the device to be analyzed may be accidental or have errors. Multiple collections (until N online status signals are obtained) can improve the accuracy and reliability of the data and more comprehensively reflect the true operating conditions of the device. After determining the device failure level of the device to be analyzed, the acquisition device will return to the step of obtaining the detection information of the device to be analyzed that is detected by the detection device in real time, and repeat continuously to extract the existence time of the online status signal of the device to be analyzed until N online status signals are collected. Here, N is an integer greater than zero, and its specific value can be determined according to actual needs and data accuracy requirements. For example, N can be 10, 20, etc. The N collected online status signals are comprehensively analyzed. If the online status signal of a certain device is continuously missing or the number of missing times exceeds a certain threshold during these N collection processes, it can be determined that the device is an offline device. After determining all offline devices, according to the association relationship between the device and the gateway, find the offline devices under the same gateway, and these devices are the gateway offline devices.

[0052] Among them, the positioning system of the device or the pre-recorded device installation location information is used to obtain the device location information of the gateway offline device. According to these device location information, determine the geographical area covered by the gateway offline device. Tools such as Geographic Information System (GIS) can be used for area division and calculation. Different gateway device failure levels corresponding to different coverage area sizes are pre-set. For example, when the coverage area is less than a certain area threshold, it is determined as level one (mild failure); when the coverage area is within a certain range, it is determined as level two (moderate failure); when the coverage area exceeds a larger area threshold, it is determined as level three (severe failure).

[0053] In this embodiment, by extending from the individual failure situation of the device to be analyzed to the overall operating conditions of the devices under the same gateway, and then accurately evaluating the failure level of the gateway device, it helps to timely discover and solve potential problems in the network and ensure the stable operation of the network.

[0054] Such as Figure 4As shown in the figure, it is a schematic flowchart of a method for processing faults of a collection device provided in the fourth embodiment of the present invention. After the device fault level generated by the above-mentioned collection device fault detection method, the method for processing faults of the collection device may include the following steps: Step S401, obtain a historical fault database, and extract the signal fault historical processing operations corresponding to the device signal fault level in the historical fault database, the data transmission fault historical processing operations corresponding to the data transmission fault level, and the network fault historical processing operations corresponding to the network fault level.

[0055] Step S402, perform fault processing on the device to be analyzed according to the signal fault historical processing operations, the data transmission fault historical processing operations, and the network fault historical processing operations.

[0056] Among them, first, it is necessary to obtain a historical fault database from a storage device or system. This database may be a local database file or a database system stored on a server, such as MySQL, Oracle, etc. According to the device signal fault level, data transmission fault level, and network fault level of the device to be analyzed, search for the corresponding signal fault historical processing operations, data transmission fault historical processing operations, and network fault historical processing operations in the historical fault database. For example, if the device signal fault level of the device to be analyzed is level two, extract all the processing operation records corresponding to the level two device signal fault level from the database.

[0057] Integrate the signal fault historical processing operations, the data transmission fault historical processing operations, and the network fault historical processing operations to formulate a specific fault processing plan for the device to be analyzed. For example, if the signal fault historical processing operation suggests checking whether the signal source is normal, and the data transmission fault historical processing operation suggests replacing the transmission line, then incorporate these operations into the processing plan. According to the formulated processing plan, perform corresponding fault processing operations on the device to be analyzed. During the execution process, it is necessary to closely monitor the state change of the device and observe whether the fault is resolved.

[0058] After completing the fault processing operation, evaluate the processing effect. It is possible to judge whether the fault has been eliminated by detecting various indicators of the device again, such as device signal strength, data transmission rate, network connectivity, etc. If the fault still exists, it may be necessary to re-examine the historical processing operations or further analyze and process the fault in combination with other methods.

[0059] In this embodiment, the fault processing method through the historical fault database can improve the efficiency and accuracy of fault processing, reduce the device downtime caused by improper fault processing, and also help to continuously accumulate and improve fault processing experience.

[0060] As shown in Figure 5 the figure, it is a schematic flowchart of a method for processing faults of a collection device provided in the fifth embodiment of the present invention. Based on the above fourth embodiment, when processing the device to be analyzed in step S402, the following steps may further be included: Step S501: Analyze whether the device offline duration exceeds a preset offline duration threshold. If it exceeds the preset offline duration threshold, perform the processing operation for device repair faults. If the device offline duration does not exceed the preset offline duration threshold, perform the processing operation for remotely processing faults.

[0061] Step S502: Analyze whether the data transmission integrity rate is lower than a preset data integrity rate threshold. If it is lower than the preset data integrity rate threshold, perform the processing operation for device repair faults. If the data transmission integrity rate is not lower than the preset data integrity rate threshold, perform the processing operation for remotely processing faults.

[0062] Step S503: Add and calculate the information delay time and the data packet loss rate to obtain a network composite value. Analyze whether the network composite value is higher than a preset composite threshold. If it is higher than the preset composite threshold, perform the processing operation for device repair faults. If the network composite value is not higher than the preset composite threshold, perform the processing operation for remotely processing faults.

[0063] Among them, the time length from the start of device offline to the current moment of the device to be analyzed is recorded by the detection device. Compare the obtained device offline duration with the preset offline duration threshold. For example, the preset offline duration threshold is 2 hours. If the device offline duration is 3 hours, exceeding the threshold, perform the processing operation for device repair faults, such as arranging maintenance personnel to go to the location of the device for inspection; if the device offline duration is 1 hour, not exceeding the threshold, perform the processing operation for remotely processing faults, such as checking the configuration of the device and restarting the device through remote control software.

[0064] Among them, the data transmission integrity rate is calculated by comparing the amount of data sent and the amount of data successfully received. For example, if 1000 data packets are sent and 950 are successfully received, the data transmission integrity rate is 95%.

[0065] Among them, the calculated data transmission integrity rate is compared with the preset data integrity rate threshold. Assume that the preset data integrity rate threshold is 98%. If the data transmission integrity rate is 95%, lower than the threshold, perform the processing operation for device repair faults; if the data transmission integrity rate is 99%, not lower than the threshold, perform the processing operation for remotely processing faults.

[0066] Among them, the information delay time and the data packet loss rate are added for calculation. For example, if the information delay time is 50 milliseconds and the data packet loss rate is 3%, then the network composite value is 50 + 3 = 53 (this is just to illustrate the calculation method, and unit conversion or other processing may be required in actual applications).

[0067] The network composite value is compared with a preset composite threshold. If the preset composite threshold is 55 and the network composite value is 53, which is not higher than the threshold, then the processing operation for remotely handling the fault is executed; if the network composite value is 60, which is higher than the threshold, then the processing operation for device repair fault is executed.

[0068] In this embodiment, through different fault manifestations of the device, a more scientific and appropriate fault handling method is selected to improve the efficiency and accuracy of fault handling.

[0069] As Figure 6 shown, it is a schematic flowchart of a method for handling faults of a collection device provided in Embodiment 6 of the present invention. When performing the processing operation for remotely handling the fault in step S501, the following steps may be included: Step S601, continuously detect the status signals of the device to be analyzed, and combine with the historical fault database to determine abnormal signals.

[0070] Step S602, extract the historical standard data corresponding to the abnormal signals from the historical fault database, and determine the data processing scheme of the device to be analyzed according to the historical standard data.

[0071] Among them, the continuous detection of status signals can utilize monitoring devices or systems to continuously collect various status signals of the device to be analyzed, such as the voltage, current, temperature, signal strength, etc. of the device. These signals can be obtained through sensors, communication interfaces, etc. Combining with the historical fault database to determine abnormal signals, compare the collected status signals with the data in the historical fault database. The historical fault database records the characteristics of various status signals of the device during normal operation and when a fault occurs. By analyzing the difference between the current signal and the historical data, it is judged whether there is an abnormal signal. For example, if the historical data shows that the temperature of the device is between 20 - 30 degrees Celsius during normal operation, and the currently detected temperature is 50 degrees Celsius, then this temperature signal may be an abnormal signal.

[0072] Among them, after an abnormal signal is determined, historical standard data corresponding to the abnormal signal is searched from the historical fault database. This data may include the normal signal range, steps for handling faults, suggestions for adjusting parameters, etc. For example, if the abnormal signal is that the device temperature is too high, the historical standard data may show the normal temperature range and the cooling measures that should be taken, such as adjusting the speed of the cooling fan and checking whether the ventilation opening is blocked. According to the extracted historical standard data and combined with the actual situation of the device to be analyzed, a specific data processing plan is formulated. This plan may include operations such as adjusting the parameters of the device, restarting the device, and updating the software. For example, if the historical standard data indicates that reducing the operating frequency of the device can solve the problem of overheating, then the data processing plan can be to remotely adjust the operating frequency of the device.

[0073] In this embodiment, by utilizing the experience and data of the historical fault database, without on-site maintenance, the faults of the device are identified and solved through remote operation, improving the efficiency and convenience of fault handling.

[0074] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution is prior or posterior. The execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0075] As Figure 7 shown, it is a schematic diagram of a fault detection device for a collection device provided in the seventh embodiment of the present invention. The fault detection device for the collection device corresponds one-to-one with the fault detection method for the collection device in the above embodiment. The fault detection device for the collection device includes an information extraction module 71, a fault level determination module 72, an interaction information extraction module 73, a network fault determination module 74, and a device fault determination module 75. The detailed description of each functional module is as follows: The information extraction module 71 is used to obtain the detection information of the device to be analyzed detected by the detection device in real time, and extract the status signal of the device to be analyzed, the total amount of data transmitted by the device to be analyzed, and the interaction information between the device to be analyzed and the detection device from the detection information; The fault level determination module 72 is used to determine the offline duration of the device to be analyzed according to the status signal, determine the device signal fault level according to the offline duration of the device, calculate the ratio of the total amount of data to the preset amount of data to obtain the data transmission integrity rate, and determine the data transmission fault level according to the data transmission integrity rate; The interaction information extraction module 73 is used to determine the offline duration of the device to be analyzed according to the status signal, determine the device signal fault level according to the offline duration of the device, calculate the ratio of the total amount of data to the preset amount of data to obtain the data transmission integrity rate, and determine the data transmission fault level according to the data transmission integrity rate; A network fault determination module 74, configured to determine an information delay time according to a round-trip time, calculate a ratio of a received total amount to a transmitted total amount to obtain a data packet loss rate of a device to be analyzed, and determine a network fault level of the device to be analyzed according to the information delay time and the data packet loss rate; A device fault determination module 75, configured to determine a device fault level of the device to be analyzed according to a device signal fault level, a data transmission fault level, and a network fault level.

[0076] Optionally, the acquisition device fault detection device further includes: An online signal extraction module, configured to obtain an online status signal corresponding to the device to be analyzed according to a status signal of the device to be analyzed; A return execution module, configured to, after determining the device fault level of the device to be analyzed, return to execute the step of obtaining the detection information of the device to be analyzed detected by the detection device in real time and extracting the existence time of the online status signal of the device to be analyzed in the detection information until N online status signals of the device to be analyzed are obtained, where N is an integer greater than zero; An offline device determination module, configured to determine an offline device according to the N online status signals and a preset total number of devices, and obtain a gateway offline device under the same gateway according to the offline device; A coverage area determination module, configured to obtain device location information of the gateway offline device, obtain a coverage area of the gateway offline device according to the device location information, and determine a gateway device fault level according to the coverage area.

[0077] Optionally, the above device fault determination module 75 further includes: An offline signal recording unit, configured to detect a status signal and record an offline status signal when the device is offline; An offline duration determination unit, configured to extract the device offline duration corresponding to the offline status signal in the detection information; A signal level determination unit, configured to determine a device signal fault level according to the device offline duration.

[0078] As Figure 8 shown, it is a schematic diagram of an acquisition device fault processing device provided in Embodiment 8 of the present invention, and the acquisition device fault processing device corresponds one-to-one to the acquisition device fault processing method in the above embodiment. The acquisition device fault processing device includes a historical data processing module 81 and a fault processing module 82. The detailed description of each functional module is as follows: The historical data processing module 81 is used to obtain the historical fault database after the device fault level generated by the generating method of the acquisition device fault detection, and extract the signal fault historical processing operations corresponding to the device signal fault level, the data transmission fault historical processing operations corresponding to the data transmission fault level, and the network fault historical processing operations corresponding to the network fault level from the historical fault database; The fault processing module 82 is used to perform fault processing on the device to be analyzed according to the signal fault historical processing operation, the data transmission fault historical processing operation, and the network fault historical processing operation.

[0079] Optionally, the above acquisition device fault processing module 82 further includes: The offline threshold judgment unit is used to analyze whether the device offline duration exceeds the preset offline duration threshold. If it exceeds the preset offline duration threshold, the processing operation of the device maintenance fault is executed. If the device offline duration does not exceed the preset offline duration threshold, the processing operation of the remote processing fault is executed; The transmission threshold judgment unit is used to analyze whether the data transmission integrity rate is lower than the preset data integrity rate threshold. If it is lower than the preset data integrity rate threshold, the processing operation of the device maintenance fault is executed. If the data transmission integrity rate is not lower than the preset data integrity rate threshold, the processing operation of the remote processing fault is executed; The composite threshold judgment unit is used to add and calculate the information delay time and the data packet loss rate to obtain a network composite value, and analyze whether the network composite value is higher than the preset composite threshold. If it is higher than the preset composite threshold, the processing operation of the device maintenance fault is executed. If the network composite value is not higher than the preset composite threshold, the processing operation of the remote processing fault is executed.

[0080] For the specific limitations of the acquisition device fault detection device and the acquisition device fault processing device, reference can be made to the limitations of the acquisition device fault detection method and the acquisition device fault processing method in the above text, which will not be elaborated here. Each module in the above acquisition device fault detection device and acquisition device fault processing device can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor in the computer device in hardware form or independent of it, or stored in the memory in the computer device in software form, so that the processor can call and execute the operations corresponding to the above modules.

[0081] Such as Figure 9As shown in the figure, it is a schematic structural diagram of a computer device provided in the ninth embodiment of the present invention. The computer device includes a processor, a memory, a network interface, and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements a method for detecting faults in a collection device and a method for handling faults in a collection device.

[0082] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the method for detecting faults in a collection device in the above embodiment, for example Figures 2 to 3 As shown. When the processor executes the computer program, it implements the method for handling faults in a collection device in the above embodiment, for example Figures 4 to 6 As shown, to avoid repetition, it will not be elaborated here. Or, when the processor executes the computer program, it implements the functions of each module / unit in this embodiment of the collection device fault detection device, for example Figure 7 The functions of the information extraction module 71, the fault level determination module 72, the interaction information extraction module 73, the network fault determination module 74, and the device fault determination module 75 shown, or, when the processor executes the computer program, it implements the functions of each module / unit in this embodiment of the collection device fault handling device, for example Figure 8 The functions of the historical data processing module 81 and the fault handling module 82 shown. To avoid repetition, it will not be elaborated here.

[0083] In one embodiment, a computer-readable storage medium is provided. A computer program is stored on the computer-readable storage medium. When the computer program is executed by the processor, it implements the method for detecting faults in a collection device in the above embodiment, as Figures 2 to 5 Shown. To avoid repetition, it will not be elaborated here. When the computer program is executed by the processor, it implements the method for handling faults in a collection device in the above embodiment, as Figure 6 Shown. To avoid repetition, it will not be elaborated here. Or, when the computer program is executed by the processor, it implements the functions of each module / unit in the above embodiment of the collection device fault detection device, for example Figure 7The functions of the information extraction module 71, the fault level determination module 72, the interaction information extraction module 73, the network fault determination module 74, and the device fault determination module 75 shown are not described again here to avoid repetition. Alternatively, when the computer program is executed by a processor, it implements the functions of the various modules / units in the above embodiment of the acquisition device fault processing device. For example Figure 8 The functions of the historical data processing module 81 and the fault processing module 82 shown are not described again here to avoid repetition. The computer-readable storage medium may be non-volatile or volatile.

[0084] Those of ordinary skill in the art can understand that all or part of the processes in the above method embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above method embodiments. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0085] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules as needed, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above.

[0086] The above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for detecting faults in a collection device, characterized in that: include: Acquire detection information of the device to be analyzed detected by the detection device in real time, and extract the status signal of the device to be analyzed, the total amount of data transmitted by the device to be analyzed, and the interaction information between the device to be analyzed and the detection device from the detection information; Determine the offline duration of the device to be analyzed according to the status signal, determine the device signal fault level according to the offline duration of the device, calculate the ratio of the total amount of data to the preset amount of data to obtain the data transmission completeness rate, and determine the data transmission fault level according to the data transmission completeness rate; Input the interaction information into a preset extraction model, and output the round-trip time of data packet transmission between the detection device and the device to be analyzed, the total amount of data received by the detection device, and the total amount of data packets sent by the device to be analyzed; Determine the information delay time according to the round-trip time, calculate the ratio of the total amount received to the total amount sent to obtain the data packet loss rate of the device to be analyzed, and determine the network fault level of the device to be analyzed according to the information delay time and the data packet loss rate; The device fault level of the device to be analyzed is determined according to the device signal fault level, the data transmission fault level, and the network fault level.

2. The acquisition equipment fault detection method according to claim 1, characterized in that: After determining the device fault level of the device to be analyzed, the method further includes: Obtaining an online status signal corresponding to the device to be analyzed according to the status signal of the device to be analyzed; The step of obtaining the online status signal corresponding to the device to be analyzed according to the status signal of the device to be analyzed is executed cyclically until N online status signals of the device to be analyzed are obtained, where N is an integer greater than zero; Determine an offline device according to the N online status signals and a preset total number of devices, and obtain a gateway offline device under the same gateway according to the offline device; The device location information of the gateway offline device is obtained, the coverage area of ​​the gateway offline device is obtained according to the device location information, and the fault level of the gateway device is determined according to the coverage area.

3. The acquisition equipment fault detection method according to claim 1, characterized in that: The step of determining the offline duration of the device to be analyzed according to the status signal, and determining the device signal fault level according to the offline duration of the device, includes: Detecting the status signal and recording the offline status signal when the device is offline; Extracting the offline time of the device corresponding to the offline status signal in the detection information; The device signal failure level is determined according to the offline time of the device.

4. A method for handling acquisition equipment failure, characterized in that: include: After the device fault level is generated based on the generation method of the acquisition device fault detection according to claims 1 to 3, a historical fault database is obtained, and the signal fault history processing operations corresponding to the device signal fault level, the data transmission fault history processing operations corresponding to the data transmission fault level, and the network fault history processing operations corresponding to the network fault level in the historical fault database are extracted; According to the signal fault history processing operation, the data transmission fault history processing operation, and the network fault history processing operation, fault processing is performed on the device to be analyzed.

5. The method for handling data acquisition equipment failure according to claim 4, characterized in that: The performing fault processing on the device to be analyzed includes: Analyze whether the offline time of the device exceeds a preset offline time threshold, if so, perform a device maintenance fault processing operation, if not, perform a remote fault processing operation; Analyze whether the data transmission integrity rate is lower than a preset data integrity rate threshold, if it is lower than the preset data integrity rate threshold, execute the equipment maintenance fault processing operation, if the data transmission integrity rate is lower than the preset data integrity rate threshold, execute the remote processing fault processing operation; The information delay time and the data packet loss rate are added to obtain a network composite value, and the network composite value is analyzed to see whether it is higher than a preset composite threshold value. If it is higher than the preset composite threshold value, the equipment maintenance fault processing operation is executed; if the network composite value is not higher than the preset composite threshold value, the remote processing fault processing operation is executed.

6. The acquisition equipment failure processing method according to claim 5, characterized in that: The performing of the remote processing fault processing operation includes: Continuously detecting the status signal of the device to be analyzed, and determining abnormal signals in combination with the historical fault database; The historical standard data corresponding to the abnormal signal in the historical fault database is extracted, and a data processing scheme for the device to be analyzed is determined according to the historical standard data.

7. A collection equipment fault detection device, characterized in that: include: An information extraction module is used to obtain detection information of the device to be analyzed detected by the detection device in real time, and extract the status signal of the device to be analyzed, the total amount of data transmitted by the device to be analyzed, and the interaction information between the device to be analyzed and the detection device from the detection information; A fault level determination module is used to determine the offline duration of the device to be analyzed according to the status signal, determine the device signal fault level according to the offline duration of the device, calculate the ratio of the total amount of data to the preset amount of data to obtain the data transmission completeness rate, and determine the data transmission fault level according to the data transmission completeness rate; An interactive information extraction module is used to determine the offline duration of the device to be analyzed according to the status signal, determine the device signal fault level according to the device offline duration, calculate the ratio of the total amount of data to the preset amount of data to obtain the data transmission completeness rate, and determine the data transmission fault level according to the data transmission completeness rate; A network fault determination module, configured to determine the information delay time according to the round trip time, calculate the ratio of the total amount received to the total amount sent to obtain the data packet loss rate of the device to be analyzed, and determine the network fault level of the device to be analyzed according to the information delay time and the data packet loss rate; The device fault determination module is used to determine the device fault level of the device to be analyzed according to the device signal fault level, the data transmission fault level, and the network fault level.

8. A collection equipment fault processing device, characterized in that: include: A historical data processing module, for obtaining a historical fault database after the device fault level is generated based on the generation method of the acquisition device fault detection according to claims 1 to 3, and extracting the signal fault history processing operations corresponding to the device signal fault level, the data transmission fault history processing operations corresponding to the data transmission fault level, and the network fault history processing operations corresponding to the network fault level from the historical fault database; The fault processing module is used to perform fault processing on the device to be analyzed according to the signal fault history processing operation, the data transmission fault history processing operation, and the network fault history processing operation.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the acquisition device fault detection method described in any one of claims 1 to 3 or the acquisition device fault processing method described in any one of claims 4 to 6 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the acquisition device fault detection method described in any one of claims 1 to 3 or the acquisition device fault processing method described in any one of claims 4 to 6 is implemented.

Images