Tobacco equipment monitoring method and device, computer equipment and storage medium

Abstract

The invention relates to a tobacco equipment monitoring method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a target monitoring object from tobacco equipment; and determining target monitoring information of the target monitoring object. And determining a target fault analysis result of the target monitoring object according to the target monitoring information. Wherein the target monitoring information is at least one of current information, vibration information, image information, noise information and position information. Compared with the prior art, the target monitoring object can be flexibly acquired, and the corresponding target monitoring information can be determined according to the target monitoring object. And finally, based on the target monitoring information, the target fault analysis result of the target monitoring object is automatically determined, so that the human input is reduced, and the determined target fault analysis result is more accurate.

Description

Technical Field

[0001] The present application relates to the technical field of tobacco equipment, and in particular to a tobacco equipment monitoring method, device, computer equipment, and storage medium. Background Art

[0002] In the tobacco production process, the stable operation of various tobacco equipment is crucial to ensuring product quality and production efficiency.

[0003] However, traditional tobacco equipment monitoring and fault diagnosis methods have many limitations. Existing monitoring methods often only monitor a single parameter of the equipment (for example, current or temperature), and cannot flexibly and accurately determine the fault monitoring results of tobacco equipment. Summary of the Invention

[0004] Based on this, it is necessary to provide a tobacco equipment monitoring method, device, computer equipment and storage medium that can improve the accuracy of tobacco equipment fault monitoring in response to the above technical problems.

[0005] In a first aspect, the present application provides a tobacco equipment monitoring method. The method comprises:

[0006] Obtaining targeted surveillance subjects from tobacco equipment;

[0007] Determining target monitoring information of a target monitoring object; wherein the target monitoring information is at least one of current information, vibration information, image information, noise information, and position information;

[0008] According to the target monitoring information, the target fault analysis result of the target monitoring object is determined.

[0009] In one embodiment, determining a target fault analysis result of a target monitoring object based on target monitoring information includes:

[0010] Determine preliminary fault analysis results of the target monitoring object based on the target monitoring information;

[0011] If the preliminary fault analysis result indicates that a fault exists, determine the associated monitoring information of the target monitoring object;

[0012] According to the target monitoring information and the associated monitoring information, the target fault analysis result of the target monitoring object is determined.

[0013] In one embodiment, when the preliminary fault analysis result indicates that a fault exists, determining associated monitoring information of the target monitoring object includes:

[0014] If the preliminary fault analysis result indicates that a fault exists, determine the device type corresponding to the target monitoring object;

[0015] Determine the associated monitoring information of the target monitoring object based on the device type.

[0016] In one embodiment, determining a target fault analysis result of a target monitoring object based on the target monitoring information and the associated monitoring information includes:

[0017] Determine the target fault based on the associated monitoring information and the target monitoring information;

[0018] The target fault analysis result of the target monitoring object is determined according to the target fault and the duration of the target fault.

[0019] In one embodiment, determining a target fault analysis result of a target monitoring object according to the target fault and the duration of the target fault includes:

[0020] When the duration exceeds the first time threshold, generating a first fault analysis result according to the target fault; wherein the first fault analysis result includes the target fault and the fault risk;

[0021] When the duration exceeds the second time threshold, generating a second fault analysis result; wherein the second fault analysis result includes the target fault, the fault location and the fault severity level;

[0022] When the duration exceeds a third time threshold, a third fault analysis result is generated; wherein the third fault analysis result includes the target fault and the remaining life of the target monitoring object; the third time threshold is greater than the second time threshold, and the second time threshold is greater than the first time threshold.

[0023] In one embodiment, determining target monitoring information of a target monitoring object includes:

[0024] Determine candidate monitoring information based on the object type of the target monitoring object;

[0025] Determine the indicator priority of candidate monitoring information based on the object type;

[0026] According to the indicator priority, target monitoring information is selected from the candidate monitoring information.

[0027] In a second aspect, the present application also provides a tobacco equipment monitoring device. The device includes:

[0028] An acquisition module, used to acquire a target monitoring object from a tobacco device;

[0029] A first determining module is configured to determine target monitoring information of a target monitoring object; wherein the target monitoring information is at least one of current information, vibration information, image information, noise information, and position information;

[0030] The second determination module is used to determine the target fault analysis result of the target monitoring object according to the target monitoring information.

[0031] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the following steps are performed:

[0032] Obtaining targeted surveillance subjects from tobacco equipment;

[0033] Determining target monitoring information of a target monitoring object; wherein the target monitoring information is at least one of current information, vibration information, image information, noise information, and position information;

[0034] According to the target monitoring information, the target fault analysis result of the target monitoring object is determined.

[0035] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the following steps:

[0036] Obtaining targeted surveillance subjects from tobacco equipment;

[0037] Determining target monitoring information of a target monitoring object; wherein the target monitoring information is at least one of current information, vibration information, image information, noise information, and position information;

[0038] According to the target monitoring information, the target fault analysis result of the target monitoring object is determined.

[0039] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the following steps:

[0040] Obtaining targeted surveillance subjects from tobacco equipment;

[0041] Determining target monitoring information of a target monitoring object; wherein the target monitoring information is at least one of current information, vibration information, image information, noise information, and position information;

[0042] According to the target monitoring information, the target fault analysis result of the target monitoring object is determined.

[0043] The above-mentioned tobacco equipment monitoring method, device, computer equipment and storage medium obtain the target monitoring object from the tobacco equipment when there is a need to monitor the tobacco equipment. The target monitoring information of the target monitoring object is determined. Based on the target monitoring information, the target fault analysis result of the target monitoring object is determined. Among them, the target monitoring information is at least one of current information, vibration information, image information, noise information and position information. Compared with the existing technology, the present application can flexibly obtain the target monitoring object and can determine the corresponding target monitoring information based on the target monitoring object. Finally, based on the target monitoring information, the target fault analysis result of the target monitoring object is automatically determined, which not only reduces manpower input, but also makes the target fault analysis result obtained more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 A diagram illustrating the application environment of the tobacco equipment monitoring method provided in this embodiment;

[0045] Figure 2 A schematic flow chart of the first tobacco equipment monitoring method provided in this embodiment;

[0046] Figure 3 A schematic diagram of a process for determining a target fault analysis result of a target monitoring object provided in this embodiment;

[0047] Figure 4 A schematic diagram of another process for determining target fault analysis results of a target monitoring object provided by this embodiment;

[0048] Figure 5 A schematic flow chart of a second tobacco equipment monitoring method provided in this embodiment;

[0049] Figure 6 A structural block diagram of a tobacco equipment monitoring device provided in this embodiment;

[0050] Figure 7 This is a diagram of the internal structure of the computer device provided in this embodiment. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0052] The tobacco equipment monitoring method provided in the embodiment of the present application can be applied to Figure 1In the application environment shown, the diagnostic device 104 obtains a target monitoring object from the tobacco equipment through the sensing device 102. The diagnostic device 104 determines target monitoring information of the target monitoring object; the target monitoring information is at least one of current information, vibration information, image information, noise information, and location information. Based on the target monitoring information, the diagnostic device 104 determines a target fault analysis result for the target monitoring object.

[0053] The diagnostic device can be a control host, a server, or other device with diagnostic capabilities. The server can be a standalone server or a server cluster consisting of multiple servers. The sensing device can be a collector or a monitoring device such as a sensor.

[0054] In one embodiment, Figure 2 As shown, a tobacco equipment monitoring method is provided, which is applied to Figure 1 The diagnostic device in the example is used to illustrate the following steps:

[0055] S201, obtaining a target monitoring object from a tobacco device.

[0056] Tobacco equipment refers to equipment related to tobacco production, such as conveyors, feeders, cutters, and dryers. A target monitoring object refers to the object to be monitored, which can be a piece of tobacco equipment, such as a conveyor or cutter. It can also be a component of tobacco equipment, such as a conveyor motor or a cutter blade.

[0057] As an optional implementation of the embodiment of the present application, in response to a device monitoring request sent by a user via a client, a target monitoring object is obtained from the tobacco device according to the device monitoring request. The device monitoring request carries an object identifier of the target monitoring object. The object identifier is a unique identifier used to represent the identity of the target monitoring object.

[0058] Another optional implementation of the embodiment of the present application is to obtain a target device selected by the user in response to a trigger operation on a tobacco device monitoring control, and use the target device as a target monitoring object.

[0059] Another optional implementation of the present invention is to obtain a target monitoring object from the tobacco equipment based on historical monitoring records. For example, based on historical monitoring records, the equipment or component that has been monitored the most in recent time is selected as the target monitoring object.

[0060] S202: Determine target monitoring information of the target monitoring object.

[0061] The target monitoring information is at least one of current information, vibration information, image information, noise information and position information. The target monitoring information refers to the main monitoring information of the target monitoring object.

[0062] As an optional implementation of the embodiment of the present application, the target monitoring information is determined based on the target monitoring object and the monitoring list, wherein the monitoring list records each monitoring object and the target monitoring information corresponding to each monitoring object.

[0063] Another optional implementation method of the embodiment of the present application is to determine the candidate monitoring information based on the object type of the target monitoring object. According to the object type, the indicator priority of the candidate monitoring information is determined. According to the indicator priority, the target monitoring information is selected from the candidate monitoring information. Exemplarily, if the target monitoring object is a conveyor belt motor, the corresponding object type is a motor. The candidate monitoring information of the motor includes vibration information, current information and noise information. If the indicator priority corresponding to the current information in the candidate monitoring information is the highest, the current information is used as the target monitoring information.

[0064] Optionally, in this embodiment, current information values ​​may be obtained using a current sensor. Vibration information values ​​may be obtained using a vibration sensor. Image information may be obtained using a camera. Noise information may be obtained using a sound sensor. Position information may be obtained using a photoelectric sensor, a visual sensor (e.g., a camera), or a proximity sensor.

[0065] S203: Determine a target fault analysis result of the target monitoring object according to the target monitoring information.

[0066] An optional implementation of the embodiment of the present application is to obtain an index value of the target monitoring information, and determine a target fault analysis result of the target object based on a size relationship between the index value and an index threshold.

[0067] Another optional implementation of the present application is to obtain the index value of the target monitoring information, input the target monitoring information and the index value into an intelligent analysis tool, and have the intelligent analysis tool output the target fault analysis result of the target object. The intelligent analysis tool can be a neural network model.

[0068] In this embodiment, when there is a need to monitor tobacco equipment, a target monitoring object is obtained from the tobacco equipment. Target monitoring information of the target monitoring object is determined. Based on the target monitoring information, a target fault analysis result of the target monitoring object is determined. The target monitoring information is at least one of current information, vibration information, image information, noise information, and position information. Compared with the prior art, the present application can flexibly obtain the target monitoring object and can determine the corresponding target monitoring information based on the target monitoring object. Finally, based on the target monitoring information, the target fault analysis result of the target monitoring object is automatically determined, which not only reduces manpower input, but also makes the target fault analysis result obtained more accurate.

[0069] In one embodiment, in order to more quickly determine the target fault analysis results, such as Figure 3 As shown, an optional implementation in S203 includes:

[0070] S301, determining preliminary fault analysis results of the target monitoring object according to the target monitoring information.

[0071] The preliminary fault analysis result refers to the fault analysis result obtained by performing preliminary fault analysis based on the target monitoring information of the target object.

[0072] As an optional implementation of the embodiment of the present application, target monitoring information is input into a fault analysis model, and the fault analysis model outputs a preliminary fault analysis result of the target monitoring object.

[0073] Another optional implementation of the present application is to determine a preliminary fault analysis result for the target monitored object based on the target monitoring information, the information threshold, and the object type of the target monitored object. For example, if the target monitored object is a conveyor belt motor and the target monitoring information is current information, if the current information exceeds the information threshold, the preliminary fault analysis result is that a fault exists; in this case, the fault may be due to overload, motor failure, or transmission component wear, and therefore the preliminary fault analysis result may not be very clear.

[0074] S302: When the preliminary fault analysis result indicates that a fault exists, determine the associated monitoring information of the target monitoring object.

[0075] As an optional implementation of an embodiment of the present application, when the preliminary fault analysis result indicates that a fault exists, the associated monitoring information of the target monitoring object is determined based on the monitoring list; wherein the associated monitoring information corresponding to each monitoring object is recorded in the monitoring list. Exemplarily, the target monitoring information of the motor is current information. The associated monitoring information is vibration information, noise information, image information, and position information. In this embodiment, the information value corresponding to the associated monitoring information of the target monitoring object can be obtained based on the sensor.

[0076] As another optional implementation of the embodiment of the present application, when the preliminary fault analysis result is that a fault exists, the device type corresponding to the target monitoring object is determined. Based on the device type, the associated monitoring information of the target monitoring object is determined. For example, when the preliminary fault analysis result is that a fault exists, if the target monitoring object is a conveyor belt motor and the corresponding device type is a conveying device, the associated monitoring information is image information, vibration information, and noise information. Image information is mainly used to assist in monitoring whether there is an overload. Vibration information and noise information are used to assist in monitoring whether there is a motor fault.

[0077] S303: Determine a target fault analysis result of the target monitoring object according to the target monitoring information and the associated monitoring information.

[0078] Optionally, in this embodiment, the information content corresponding to the target monitoring information (for example, indicator values, pictures or other forms of parameters) and the information content corresponding to the associated monitoring information are input into the intelligent analysis tool, and the intelligent analysis tool outputs the target fault analysis results of the target monitoring object.

[0079] In this embodiment, a preliminary fault analysis result of the target monitoring object is determined based on the target monitoring information. In the case where the preliminary fault analysis result shows that a fault exists, the device type corresponding to the target monitoring object is determined. Based on the device type corresponding to the target monitoring object, the associated monitoring information of the target monitoring object is determined. Based on the target monitoring information and the associated monitoring information, the target fault analysis result of the target monitoring object is determined. In this embodiment, first based on the target monitoring information, when a potential fault is detected in the target monitoring object, the associated monitoring information is determined, and the target fault analysis result is determined based on the target monitoring information and the associated monitoring information; that is, when the preliminary fault analysis result shows that no fault exists, only the target monitoring information needs to be obtained, and no other information needs to be obtained, which not only reduces energy consumption but also reduces the computational burden of the monitoring equipment.

[0080] On the basis of the above embodiment, in order to make the target fault analysis result determined to be more accurate, as shown in FIG. Figure 4 As shown, an optional implementation method for determining a target fault analysis result of a target monitoring object based on the target monitoring information and the associated monitoring information includes:

[0081] S401: Determine a target fault based on associated monitoring information and target monitoring information.

[0082] As an optional implementation method of the embodiment of the present application, the information content corresponding to the target monitoring information (for example, indicator values, pictures or other forms of parameters) and the information content corresponding to the associated monitoring information are input into the intelligent analysis tool, and the intelligent analysis tool outputs the target fault.

[0083] As another optional implementation method of the embodiment of the present application, based on the information content of the target monitoring information, the content change characteristics are determined. Based on the content change characteristics and the information content of the associated monitoring information, the target fault is determined. Example 1, if the target monitoring object is a conveyor belt motor. The target monitoring information is current information. The characteristic of the current information is that the current value will increase for a short time at each specific time interval. The associated monitoring information is vibration information and noise information. The information content of the vibration information is an increase in vibration amplitude. The information content of the noise information is an increase in noise. The target fault can be determined to be wear of transmission parts (for example, bearings or gears). Example 2, as shown in Table 1, during the production process, the motor current of the conveyor belt increased from the original 5.2A to 6.0A, and lasted for a long time. According to the current monitoring technology, the system detected that this change exceeded the set current threshold (5.5A), and there was no obvious change in noise and vibration, then the target fault was overload:

[0084] Table 1

[0085] time Current (A) Preset current threshold (A) Noise changes Vibration changes Diagnosis results 2024-01-01 5.2 5.5 normal normal normal 2024-01-10 5.8 5.5 normal normal Overload warning 2024-01-15 6.0 5.5 normal normal Overload warning

[0086] In Example 3, the target monitoring object is the conveyor belt, and the target monitoring information is image information. When the image information analysis shows that the material is piled up too high, the associated monitoring information is determined to be the material flow rate and conveyor belt speed. Based on the associated monitoring information and the target monitoring information, the method for determining the target fault is shown in Table 2:

[0087] Table 2

[0088] time Material stacking height (mm) Material flow rate (kg / h) Conveyor belt speed (m / s) Diagnosis results 2024-05-08 50 3000 1.2 normal 2024-06-25 70 3500 1.0 Material accumulation 2024-07-02 100 3800 0.8 Material accumulation

[0089] Optionally, the associated monitoring information and target monitoring information may be preprocessed before use. Preprocessing methods include, but are not limited to, data cleaning, filtering, noise reduction, and extraction. For example, for current information, wavelet transform or Kalman filtering may be used to reduce noise on the current signal, and fast Fourier transform may be used to extract characteristic frequencies from the current signal.

[0090] S402: Determine a target fault analysis result of a target monitoring object according to the target fault and the duration of the target fault.

[0091] Optionally, in this embodiment, when the duration exceeds the first time threshold, a first fault analysis result is generated according to the target fault; wherein the first fault analysis result includes the target fault and the fault risk.

[0092] Optionally, in this embodiment, when the duration exceeds the second time threshold, a second fault analysis result is generated; wherein the second fault analysis result includes the target fault, the fault location and the fault severity level. Specifically, when the duration exceeds the second time threshold, the fault location is determined based on the information characteristics of the target monitoring information and the associated monitoring information. For example, taking the conveyor belt motor as an example, as shown in Table 3, when the vibration signal continues to rise from 0.10mm / s to 0.14mm / s, and the spectrum analysis shows that 1.5 times the fundamental frequency harmonic component appears in the frequency signal, and the noise increases, the duration of these two phenomena exceeds 180S, and the system confirms that the fault type is motor bearing wear. Based on this analysis result, the system can determine that the fault location is the bearing part of the motor and evaluate its fault severity level:

[0093] Table 3

[0094] time Vibration signal (mm / s) Vibration threshold (mm / s) Noise changes Duration threshold Spectrum analysis results Fault Location Failure severity 2024-06-20 0.10 0.08 none none No harmonics normal No trouble 2024-07-03 0.14 0.08 Increase 180S 1.5 times fundamental frequency harmonics Bearing wear Light wear 2024-07-15 0.16 0.08 Increase 180S 2 times fundamental frequency harmonics Bearing damage Moderate damage

[0095] Optionally, in this embodiment, when the duration exceeds the third time threshold, a third fault analysis result is generated; wherein, the third fault analysis result includes the target fault and the remaining life of the target monitoring object. Optionally, in this embodiment, when the duration exceeds the third time threshold, historical monitoring data of all monitoring information of the target monitoring object is obtained, and based on the historical monitoring data of all monitoring information, combined with machine learning methods (such as support vector machine SVM, random forest Random Forest, etc.), the equipment health assessment is performed, and its remaining life is predicted based on the usage trend of the equipment. For example, taking a certain compressor equipment as an example, during the diagnosis process of this equipment, when the duration exceeds the third time threshold, relevant monitoring data of vibration information, temperature information and current information are obtained from the operating data of the past six months, and it is found that the vibration, current and temperature have shown a gradual upward trend. Based on the machine learning algorithm, the historical monitoring data of all monitoring information predicts that its remaining life is 150 days. It is recommended to conduct a comprehensive inspection and maintenance during this period, as shown in Table 4:

[0096] Table 4

[0097] time Temperature (°C) Vibration (mm / s) Current (A) Health score Remaining life prediction (days) 2024-02-10 75 0.08 5.6 98% 240 2024-03-02 78 0.10 6.0 95% 210 2024-03-22 80 0.11 6.2 93% 190 2024-04-06 82 0.12 6.3 90% 170 2024-04-27 85 0.14 6.5 88% 150

[0098] Optionally, in this embodiment, the third time threshold is greater than the second time threshold, and the second time threshold is greater than the first time threshold. Based on different time thresholds, a step-by-step intelligent diagnosis is achieved, which avoids misjudgment due to short-term data anomalies, and can send corresponding fault analysis results at different stages to achieve diagnostic analysis of target monitoring objects at different levels.

[0099] In this embodiment, a step-by-step intelligent diagnostic approach is employed to provide comprehensive and accurate monitoring and diagnostic services for equipment operation. This technology not only enables early fault warning, fault location, and fault severity confirmation, but also provides equipment lifespan prediction and health management through historical data and health monitoring. Through continuous training and optimization, the system can continuously improve diagnostic accuracy, ultimately helping enterprises achieve intelligent maintenance and optimized operation of their equipment.

[0100] In one embodiment, Figure 5 As shown, an optional implementation of the tobacco equipment monitoring method is:

[0101] S501, obtaining a target monitoring object from a tobacco device.

[0102] S502: Determine candidate monitoring information according to the object type of the target monitoring object.

[0103] S503: Determine the indicator priority of the candidate monitoring information according to the object type.

[0104] S504: Select target monitoring information from candidate monitoring information based on the indicator priority, wherein the target monitoring information is at least one of current information, vibration information, image information, noise information, and position information.

[0105] S505: Determine preliminary fault analysis results of the target monitoring object based on the target monitoring information.

[0106] S506: When the preliminary fault analysis result indicates that a fault exists, determine the device type corresponding to the target monitoring object.

[0107] S507: Determine the associated monitoring information of the target monitoring object according to the device type.

[0108] S508: Determine the target fault according to the associated monitoring information and the target monitoring information.

[0109] S509: When the duration exceeds the first time threshold, generate a first fault analysis result according to the target fault, wherein the first fault analysis result includes the target fault and the fault risk.

[0110] S510: If the duration exceeds a second time threshold, generate a second fault analysis result, wherein the second fault analysis result includes the target fault, the fault location, and the fault severity level.

[0111] S511: If the duration exceeds a third time threshold, generate a third fault analysis result, wherein the third fault analysis result includes the target fault and the remaining life of the target monitored object; the third time threshold is greater than the second time threshold, and the second time threshold is greater than the first time threshold.

[0112] When there is a need to monitor tobacco equipment, the present application obtains a target monitoring object from the tobacco equipment. The target monitoring information of the target monitoring object is determined. Based on the target monitoring information, the target fault analysis result of the target monitoring object is determined. Among them, the target monitoring information is at least one of current information, vibration information, image information, noise information and position information. Compared with the existing technology, the present application can flexibly obtain the target monitoring object and can determine the corresponding target monitoring information based on the target monitoring object. Finally, based on the target monitoring information, the target fault analysis result of the target monitoring object is automatically determined, which not only reduces manpower input, but also makes the target fault analysis result obtained more accurate.

[0113] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0114] Based on the same inventive concept, embodiments of the present application also provide a tobacco equipment monitoring device for implementing the aforementioned tobacco equipment monitoring method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more tobacco equipment monitoring device embodiments provided below can be found in the aforementioned limitations of the tobacco equipment monitoring method and will not be further elaborated here.

[0115] In one embodiment, Figure 6 As shown, a tobacco equipment monitoring device 1 is provided, comprising: an acquisition module 10, a first determination module 20 and a second determination module 30, wherein:

[0116] An acquisition module 10 is used to acquire a target monitoring object from a tobacco device;

[0117] A first determining module 20 is configured to determine target monitoring information of a target monitoring object; wherein the target monitoring information is at least one of current information, vibration information, image information, noise information, and position information;

[0118] The second determining module 30 is configured to determine a target fault analysis result of a target monitoring object according to the target monitoring information.

[0119] In one embodiment, the Figure 6 The second determining module is further specifically configured to:

[0120] Determine preliminary fault analysis results of the target monitoring object based on the target monitoring information;

[0121] If the preliminary fault analysis result indicates that a fault exists, determine the associated monitoring information of the target monitoring object;

[0122] According to the target monitoring information and the associated monitoring information, the target fault analysis result of the target monitoring object is determined.

[0123] In one embodiment, the Figure 6 The second determining module is further specifically configured to:

[0124] If the preliminary fault analysis result indicates that a fault exists, determine the device type corresponding to the target monitoring object;

[0125] Determine the associated monitoring information of the target monitoring object based on the device type.

[0126] In one embodiment, the Figure 6 The second determining module is further specifically configured to:

[0127] Determine the target fault based on the associated monitoring information and the target monitoring information;

[0128] The target fault analysis result of the target monitoring object is determined according to the target fault and the duration of the target fault.

[0129] In one embodiment, the Figure 6 The second determining module is further specifically configured to:

[0130] When the duration exceeds the first time threshold, generating a first fault analysis result according to the target fault; wherein the first fault analysis result includes the target fault and the fault risk;

[0131] When the duration exceeds the second time threshold, generating a second fault analysis result; wherein the second fault analysis result includes the target fault, the fault location and the fault severity level;

[0132] When the duration exceeds a third time threshold, a third fault analysis result is generated; wherein the third fault analysis result includes the target fault and the remaining life of the target monitoring object.

[0133] In one embodiment, the Figure 6 The first determination module is further specifically configured to:

[0134] Determine candidate monitoring information based on the object type of the target monitoring object;

[0135] Determine the indicator priority of candidate monitoring information based on the object type;

[0136] According to the indicator priority, target monitoring information is selected from the candidate monitoring information.

[0137] Each module in the aforementioned tobacco equipment monitoring device may be implemented in whole or in part through software, hardware, or a combination thereof. Each module may be embedded in or independent of a processor within a computer device in the form of hardware, or may be stored in a memory within the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0138] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 7 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. 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 computer program in the non-volatile storage medium. The database of the computer device is used to store tobacco equipment monitoring related data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication 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, a tobacco equipment monitoring method is implemented.

[0139] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0140] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0141] Obtaining targeted surveillance subjects from tobacco equipment;

[0142] Determining target monitoring information of a target monitoring object; wherein the target monitoring information is at least one of current information, vibration information, image information, noise information, and position information;

[0143] According to the target monitoring information, the target fault analysis result of the target monitoring object is determined.

[0144] In one embodiment, when the processor executes the computer program, the processor further implements the following steps: determining a target fault analysis result of a target monitoring object based on the target monitoring information, including:

[0145] Determine preliminary fault analysis results of the target monitoring object based on the target monitoring information;

[0146] If the preliminary fault analysis result indicates that a fault exists, determine the associated monitoring information of the target monitoring object;

[0147] According to the target monitoring information and the associated monitoring information, the target fault analysis result of the target monitoring object is determined.

[0148] In one embodiment, when the processor executes the computer program, the processor further implements the following steps: when the preliminary fault analysis result indicates that a fault exists, determining associated monitoring information of the target monitoring object, including:

[0149] If the preliminary fault analysis result indicates that a fault exists, determine the device type corresponding to the target monitoring object;

[0150] Determine the associated monitoring information of the target monitoring object based on the device type.

[0151] In one embodiment, when the processor executes the computer program, the processor further implements the following steps: determining a target fault analysis result of the target monitoring object based on the target monitoring information and the associated monitoring information, including:

[0152] Determine the target fault based on the associated monitoring information and the target monitoring information;

[0153] The target fault analysis result of the target monitoring object is determined according to the target fault and the duration of the target fault.

[0154] In one embodiment, when the processor executes the computer program, the processor further implements the following steps: determining a target fault analysis result of a target monitoring object according to the target fault and the duration of the target fault, including:

[0155] When the duration exceeds the first time threshold, generating a first fault analysis result according to the target fault; wherein the first fault analysis result includes the target fault and the fault risk;

[0156] When the duration exceeds the second time threshold, generating a second fault analysis result; wherein the second fault analysis result includes the target fault, the fault location and the fault severity level;

[0157] When the duration exceeds a third time threshold, a third fault analysis result is generated; wherein the third fault analysis result includes the target fault and the remaining life of the target monitoring object.

[0158] In one embodiment, when the processor executes the computer program, the processor further implements the following steps: determining target monitoring information of the target monitoring object, including:

[0159] Determine candidate monitoring information based on the object type of the target monitoring object;

[0160] Determine the indicator priority of candidate monitoring information based on the object type;

[0161] According to the indicator priority, target monitoring information is selected from the candidate monitoring information.

[0162] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0163] Obtaining targeted surveillance subjects from tobacco equipment;

[0164] Determining target monitoring information of a target monitoring object; wherein the target monitoring information is at least one of current information, vibration information, image information, noise information, and position information;

[0165] According to the target monitoring information, the target fault analysis result of the target monitoring object is determined.

[0166] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: determining a target fault analysis result of a target monitoring object based on the target monitoring information, including:

[0167] Determine preliminary fault analysis results of the target monitoring object based on the target monitoring information;

[0168] If the preliminary fault analysis result indicates that a fault exists, determine the associated monitoring information of the target monitoring object;

[0169] According to the target monitoring information and the associated monitoring information, the target fault analysis result of the target monitoring object is determined.

[0170] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: when the preliminary fault analysis result indicates that a fault exists, determining associated monitoring information of the target monitoring object, including:

[0171] If the preliminary fault analysis result indicates that a fault exists, determine the device type corresponding to the target monitoring object;

[0172] Determine the associated monitoring information of the target monitoring object based on the device type.

[0173] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: determining a target fault analysis result of the target monitoring object based on the target monitoring information and the associated monitoring information, including:

[0174] Determine the target fault based on the associated monitoring information and the target monitoring information;

[0175] The target fault analysis result of the target monitoring object is determined according to the target fault and the duration of the target fault.

[0176] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: determining a target fault analysis result of a target monitoring object according to the target fault and the duration of the target fault, including:

[0177] When the duration exceeds the first time threshold, generating a first fault analysis result according to the target fault; wherein the first fault analysis result includes the target fault and the fault risk;

[0178] When the duration exceeds the second time threshold, generating a second fault analysis result; wherein the second fault analysis result includes the target fault, the fault location and the fault severity level;

[0179] When the duration exceeds a third time threshold, a third fault analysis result is generated; wherein the third fault analysis result includes the target fault and the remaining life of the target monitoring object.

[0180] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: determining target monitoring information of the target monitoring object, including:

[0181] Determine candidate monitoring information based on the object type of the target monitoring object;

[0182] Determine the indicator priority of candidate monitoring information based on the object type;

[0183] According to the indicator priority, target monitoring information is selected from the candidate monitoring information.

[0184] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0185] Obtaining targeted surveillance subjects from tobacco equipment;

[0186] Determining target monitoring information of a target monitoring object; wherein the target monitoring information is at least one of current information, vibration information, image information, noise information, and position information;

[0187] According to the target monitoring information, the target fault analysis result of the target monitoring object is determined.

[0188] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: determining a target fault analysis result of a target monitoring object based on the target monitoring information, including:

[0189] Determine preliminary fault analysis results of the target monitoring object based on the target monitoring information;

[0190] If the preliminary fault analysis result indicates that a fault exists, determine the associated monitoring information of the target monitoring object;

[0191] According to the target monitoring information and the associated monitoring information, the target fault analysis result of the target monitoring object is determined.

[0192] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: when the preliminary fault analysis result indicates that a fault exists, determining associated monitoring information of the target monitoring object, including:

[0193] If the preliminary fault analysis result indicates that a fault exists, determine the device type corresponding to the target monitoring object;

[0194] Determine the associated monitoring information of the target monitoring object based on the device type.

[0195] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: determining a target fault analysis result of the target monitoring object based on the target monitoring information and the associated monitoring information, including:

[0196] Determine the target fault based on the associated monitoring information and the target monitoring information;

[0197] The target fault analysis result of the target monitoring object is determined according to the target fault and the duration of the target fault.

[0198] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: determining a target fault analysis result of a target monitoring object according to the target fault and the duration of the target fault, including:

[0199] When the duration exceeds the first time threshold, generating a first fault analysis result according to the target fault; wherein the first fault analysis result includes the target fault and the fault risk;

[0200] When the duration exceeds the second time threshold, generating a second fault analysis result; wherein the second fault analysis result includes the target fault, the fault location and the fault severity level;

[0201] When the duration exceeds a third time threshold, a third fault analysis result is generated; wherein the third fault analysis result includes the target fault and the remaining life of the target monitoring object.

[0202] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: determining target monitoring information of the target monitoring object, including:

[0203] Determine candidate monitoring information based on the object type of the target monitoring object;

[0204] Determine the indicator priority of candidate monitoring information based on the object type;

[0205] According to the indicator priority, target monitoring information is selected from the candidate monitoring information.

[0206] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the 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-mentioned embodiments. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), data processing logic devices based on quantum computing, and the like.

[0207] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0208] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A tobacco equipment monitoring method, characterized in that: The method comprises: Obtaining targeted surveillance subjects from tobacco equipment; Determining target monitoring information of the target monitoring object; wherein the target monitoring information is at least one of current information, vibration information, image information, noise information and position information; A target fault analysis result of the target monitoring object is determined based on the target monitoring information.

2. The method according to claim 1, characterized in that Determining a target fault analysis result of the target monitoring object according to the target monitoring information includes: Determining preliminary fault analysis results of the target monitoring object based on the target monitoring information; If the preliminary fault analysis result indicates that a fault exists, determining associated monitoring information of the target monitoring object; A target fault analysis result of the target monitoring object is determined according to the target monitoring information and the associated monitoring information.

3. The method according to claim 2, characterized in that When the preliminary fault analysis result indicates that a fault exists, determining the associated monitoring information of the target monitoring object includes: If the preliminary fault analysis result indicates that a fault exists, determining the device type corresponding to the target monitoring object; Determine the associated monitoring information of the target monitoring object according to the device type.

4. The method according to claim 2, characterized in that The determining, based on the target monitoring information and the associated monitoring information, a target fault analysis result of the target monitoring object includes: determining a target fault according to the associated monitoring information and the target monitoring information; A target fault analysis result of the target monitoring object is determined according to the target fault and the duration of the target fault.

5. The method according to claim 4, characterized in that The determining, based on the target fault and the duration of the target fault, a target fault analysis result of the target monitoring object includes: When the duration exceeds a first time threshold, generating a first fault analysis result according to the target fault; wherein the first fault analysis result includes the target fault and the fault risk; When the duration exceeds a second time threshold, generating a second fault analysis result; wherein the second fault analysis result includes a target fault, a fault location, and a fault severity level; When the duration exceeds a third time threshold, a third fault analysis result is generated; wherein, the third fault analysis result includes the target fault and the remaining life of the target monitoring object; the third time threshold is greater than the second time threshold, and the second time threshold is greater than the first time threshold.

6. The method according to claim 1, characterized in that The determining of target monitoring information of the target monitoring object includes: Determining candidate monitoring information according to the object type of the target monitoring object; Determining the indicator priority of the candidate monitoring information according to the object type; Select target monitoring information from the candidate monitoring information according to the indicator priority.

7. A tobacco equipment monitoring device, characterized in that: include: An acquisition module, used to acquire a target monitoring object from a tobacco device; A first determining module is configured to determine target monitoring information of the target monitoring object; wherein the target monitoring information is at least one of current information, vibration information, image information, noise information, and position information; The second determining module is used to determine the target fault analysis result of the target monitoring object according to the target monitoring information.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the tobacco device monitoring method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the tobacco device monitoring method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the tobacco equipment monitoring method according to any one of claims 1 to 6 are implemented.

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