Toxic gas sensor fault identification method, device, equipment and medium
Through the automated toxic gas sensor fault identification method, data analysis is performed using pre-trained models, and the problems of high cost and low accuracy of manual inspection in the existing technology are solved, efficient fault identification and early warning are achieved, and equipment losses are reduced .
Patent Information
- Application Number
- CN202411257797.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-09
- Publication Date
- 2024-12-27
Smart Images
Figure CN119207042A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of fault monitoring, and in particular to a method, device, equipment and medium for identifying faults of a toxic gas sensor. Background Art
[0002] In traditional toxic gas alarm systems, fault identification mainly relies on manual inspection and regular maintenance. This approach not only requires a lot of manpower and material resources, but also may result in the failure to find and handle faults in a timely manner due to inadequate inspection or untimely maintenance. Manual inspection and regular maintenance also cannot guarantee accurate identification and location of faults, which may make it difficult to repair the faults. Therefore, how to improve the accuracy and timeliness of toxic gas alarms is an issue that needs to be solved urgently. Summary of the invention
[0003] The embodiments of the present application provide a method, device, equipment and medium for identifying toxic gas sensor faults, thereby solving the technical problems in the prior art of high manpower and material costs and low monitoring accuracy and timeliness in manually inspecting toxic gas alarm systems, thereby achieving the technical effect of reducing fault monitoring costs and improving the accuracy and timeliness of toxic gas alarms.
[0004] In a first aspect, the present application provides a method for identifying a toxic gas sensor fault, the method comprising:
[0005] Acquire actual toxic gas sensor data monitored in real time by multiple toxic gas sensors;
[0006] Inputting actual toxic gas sensor data into a pre-trained toxic gas fault detection model to obtain target toxic gas sensor data with abnormalities;
[0007] When the target toxic gas sensor data meets the alarm pop-up window conditions, the target toxic gas sensor data and the corresponding target sensor position are displayed on the display interface of the target host computer through a pop-up window;
[0008] In response to the user's pop-up window processing instruction corresponding to the target toxic gas sensor data, when the target toxic gas sensor data does not meet the alarm pop-up window conditions, the pop-up window of the target toxic gas sensor data and the corresponding target sensor position on the display interface of the target host computer is eliminated.
[0009] Further, after obtaining actual toxic gas sensor data monitored in real time by multiple toxic gas sensors, the method further includes:
[0010] The actual toxic gas sensor data is input into the pre-trained toxic gas fault detection model to obtain the toxic gas sensors to be observed that may have abnormalities in the future time period;
[0011] When the toxic gas sensor to be observed meets the warning pop-up window condition, the toxic gas sensor to be observed and the corresponding sensor position to be observed are displayed on the display interface of the target host computer through a pop-up window.
[0012] Furthermore, the training method of the toxic gas fault detection model includes:
[0013] Performing data preprocessing operations on historical toxic gas sensor data of multiple toxic gas sensors, the data preprocessing operations including cleaning, denoising, and filling missing values to obtain valid toxic gas sensor data;
[0014] Screen out abnormal toxic gas sensor data from valid toxic gas sensor data, and perform feature extraction on the abnormal toxic gas sensor data;
[0015] Determine the abnormal types corresponding to each abnormal toxic gas sensor data according to the extracted features, and divide the data according to the abnormal types corresponding to each abnormal toxic gas sensor data to obtain multiple different data clusters corresponding to the various abnormal types;
[0016] Perform association rule mining technology analysis on multiple different data clusters to determine the changing patterns of various types of anomalies;
[0017] The target type model is trained according to multiple different data clusters and the changing rules of various abnormal types to obtain a toxic gas fault detection model.
[0018] Furthermore, when the target toxic gas sensor data meets the alarm pop-up window condition, the target toxic gas sensor data and the corresponding target sensor position are displayed on the display interface of the target host computer in a pop-up window manner, including:
[0019] When multiple target toxic gas sensor data meet the alarm pop-up window conditions, the multiple target toxic gas sensor data are sorted in order according to their alarm severity;
[0020] The data of multiple target toxic gas sensors and the corresponding target sensor positions are displayed on the display interface of the target host computer in a pop-up window in sequence and with different background colors.
[0021] Further, in response to a pop-up window processing instruction corresponding to the target toxic gas sensor data from the user, the method includes:
[0022] In response to the user's pop-up processing instructions corresponding to the target toxic gas sensor data, the pop-up processing instructions include user login operation, alarm handling person filling operation, alarm handling time record, alarm handling method record, alarm cause record and fault measures taken record.
[0023] Further, in response to the user's pop-up window processing instruction corresponding to the target toxic gas sensor data, when the target toxic gas sensor data does not meet the alarm pop-up window condition, after eliminating the pop-up window of the target toxic gas sensor data and the corresponding target sensor position on the display interface of the target host computer, the method also includes:
[0024] Generate an alarm information disposal record based on the target toxic gas sensor data and its corresponding pop-up window processing instructions and save it in the database.
[0025] Furthermore, when the target toxic gas sensor data meets the alarm pop-up window condition, before displaying the target toxic gas sensor data and the corresponding target sensor position on the display interface of the target host computer by means of a pop-up window, the method further includes:
[0026] Check whether the pop-up function is turned on;
[0027] When the pop-up window function is turned on and the target toxic gas sensor data meets the alarm pop-up window conditions, the target toxic gas sensor data and the corresponding target sensor position are displayed on the display interface of the target host computer through a pop-up window.
[0028] In a second aspect, the present application provides a toxic gas sensor fault identification device, the device comprising:
[0029] A data acquisition module, used to acquire actual toxic gas sensor data monitored in real time by multiple toxic gas sensors;
[0030] The abnormality monitoring module is used to input the actual toxic gas sensor data into the pre-trained toxic gas fault detection model to obtain the target toxic gas sensor data with abnormalities;
[0031] A pop-up window display module is used to display the target toxic gas sensor data and the corresponding target sensor position on the display interface of the target host computer through a pop-up window when the target toxic gas sensor data meets the alarm pop-up window condition;
[0032] A pop-up window elimination module is used to respond to the user's pop-up window processing instructions corresponding to the target toxic gas sensor data. When the target toxic gas sensor data does not meet the alarm pop-up window conditions, the pop-up window of the target toxic gas sensor data and the corresponding target sensor position on the display interface of the target host computer is eliminated.
[0033] Furthermore, the device also includes an abnormality prediction module, which is used to:
[0034] After obtaining actual toxic gas sensor data monitored in real time by multiple toxic gas sensors, the actual toxic gas sensor data is input into a pre-trained toxic gas fault detection model to obtain toxic gas sensors to be observed that may have abnormalities in a future time period;
[0035] When the toxic gas sensor to be observed meets the warning pop-up window condition, the toxic gas sensor to be observed and the corresponding sensor position to be observed are displayed on the display interface of the target host computer through a pop-up window.
[0036] Furthermore, the device also includes a model training module, which is used to:
[0037] Performing data preprocessing operations on historical toxic gas sensor data of multiple toxic gas sensors, the data preprocessing operations including cleaning, denoising, and filling missing values to obtain valid toxic gas sensor data;
[0038] Screen out abnormal toxic gas sensor data from valid toxic gas sensor data, and perform feature extraction on the abnormal toxic gas sensor data;
[0039] Determine the abnormal types corresponding to each abnormal toxic gas sensor data according to the extracted features, and divide the data according to the abnormal types corresponding to each abnormal toxic gas sensor data to obtain multiple different data clusters corresponding to the various abnormal types;
[0040] Perform association rule mining technology analysis on multiple different data clusters to determine the changing patterns of various types of anomalies;
[0041] The target type model is trained according to multiple different data clusters and the changing rules of various abnormal types to obtain a toxic gas fault detection model.
[0042] Furthermore, the pop-up window display module is used to:
[0043] When multiple target toxic gas sensor data meet the alarm pop-up window conditions, the multiple target toxic gas sensor data are sorted in order according to their alarm severity;
[0044] The data of multiple target toxic gas sensors and the corresponding target sensor positions are displayed on the display interface of the target host computer in a pop-up window in sequence and with different background colors.
[0045] Furthermore, the pop-up window elimination module is used to:
[0046] In response to the user's pop-up processing instructions corresponding to the target toxic gas sensor data, the pop-up processing instructions include user login operation, alarm handling person filling operation, alarm handling time record, alarm handling method record, alarm cause record and fault measures taken record.
[0047] Furthermore, the device also includes a data storage module, which is used to:
[0048] Generate an alarm information disposal record based on the target toxic gas sensor data and its corresponding pop-up window processing instructions and save it in the database.
[0049] Furthermore, the pop-up window display module is used to:
[0050] Check whether the pop-up function is turned on;
[0051] When the pop-up window function is turned on and the target toxic gas sensor data meets the alarm pop-up window conditions, the target toxic gas sensor data and the corresponding target sensor position are displayed on the display interface of the target host computer through a pop-up window.
[0052] In a third aspect, the present application provides an electronic device, including:
[0053] processor;
[0054] a memory for storing processor-executable instructions;
[0055] The processor is configured to execute to implement a toxic gas sensor fault identification method as provided in the first aspect.
[0056] In a fourth aspect, the present application provides a non-temporary computer-readable storage medium. When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to implement a toxic gas sensor fault identification method as provided in the first aspect.
[0057] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
[0058] This embodiment realizes real-time monitoring and data analysis of toxic gas alarms. When the sensor detects an abnormal situation of the toxic gas alarm, the data collector will immediately collect data, process and analyze the data, and accurately identify the fault type and location of the toxic gas alarm, so as to repair and handle it in time, improve the efficiency of fault detection, reduce the cost of manual operation, and be able to warn and predict faults and adapt to complex fault identification. This embodiment obtains data based on multiple toxic gas sensors and analyzes it to quickly and accurately identify the location and possible causes of the fault. This automated method greatly improves the efficiency of fault detection, reduces the error rate, and greatly reduces labor costs and maintenance costs. By tracking and comparing the values of each key part for a long time, early warning and prediction can be achieved before the equipment fails, so that the enterprise has time to prevent or take measures to repair in advance, avoiding or reducing the loss caused by the equipment failure. Therefore, the solution provided by this embodiment can greatly improve the efficiency of fault detection, greatly reduce the cost of manual operation, provide early warning and prediction, and establish a data analysis model to adapt to complex fault identification. BRIEF DESCRIPTION OF THE DRAWINGS
[0059] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.
[0060] Figure 1 A schematic diagram of a flow chart of a method for identifying a toxic gas sensor fault provided in this embodiment;
[0061] Figure 2 A topological diagram of a toxic gas monitoring system provided in this embodiment;
[0062] Figure 3 A schematic diagram of the distribution of multiple toxic gas sensors corresponding to different clients provided in this embodiment;
[0063] Figure 4 A schematic diagram of the structure of a toxic gas sensor fault identification device provided in this embodiment;
[0064] Figure 5 A schematic diagram of the structure of an electronic device provided in this embodiment. DETAILED DESCRIPTION
[0065] The embodiment of the present application provides a method for identifying toxic gas sensor faults, thereby solving the technical problems in the prior art of manual inspection of toxic gas alarm systems, which have high manpower and material costs and low monitoring accuracy and timeliness.
[0066] The technical solution of the embodiment of the present application is to solve the above technical problems, and the overall idea is as follows:
[0067] This embodiment realizes real-time monitoring and data analysis of toxic gas alarms. When the sensor detects an abnormal situation of the toxic gas alarm, the data collector will immediately collect data, process and analyze the data, and accurately identify the fault type and location of the toxic gas alarm, so as to repair and handle it in time, improve the efficiency of fault detection, reduce the cost of manual operation, and be able to warn and predict faults and adapt to complex fault identification. This embodiment obtains data based on multiple toxic gas sensors and analyzes it to quickly and accurately identify the location and possible causes of the fault. This automated method greatly improves the efficiency of fault detection, reduces the error rate, and greatly reduces labor costs and maintenance costs. By tracking and comparing the values of each key part for a long time, early warning and prediction can be achieved before the equipment fails, so that the enterprise has time to prevent or take measures to repair in advance, avoiding or reducing the loss caused by the equipment failure. Therefore, the solution provided by this embodiment can greatly improve the efficiency of fault detection, greatly reduce the cost of manual operation, provide early warning and prediction, and establish a data analysis model to adapt to complex fault identification.
[0068] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.
[0069] First of all, the term "and / or" in this article is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.
[0070] This embodiment provides Figure 1 A method for identifying a toxic gas sensor fault is shown, and the method includes steps S11 to S14.
[0071] Step S11, obtaining actual toxic gas sensor data monitored in real time by multiple toxic gas sensors;
[0072] Step S12, inputting actual toxic gas sensor data into a pre-trained toxic gas fault detection model to obtain target toxic gas sensor data with abnormalities;
[0073] Step S13, when the target toxic gas sensor data meets the alarm pop-up window condition, the target toxic gas sensor data and the corresponding target sensor position are displayed on the display interface of the target host computer in a pop-up window manner;
[0074] Step S14, in response to the user's pop-up window processing instruction corresponding to the target toxic gas sensor data, when the target toxic gas sensor data does not meet the alarm pop-up window condition, eliminate the pop-up window of the target toxic gas sensor data and the corresponding target sensor position on the display interface of the target host computer.
[0075] The toxic gas sensor fault identification method provided in this embodiment is applicable to a gas monitoring system where a large number of toxic gas sensors are located. The method can be executed by a host computer, for example Figure 2 The monitoring server, operation station, ERP / MES server, etc. shown in the figure.
[0076] Regarding step S11, actual toxic gas sensor data monitored in real time by multiple toxic gas sensors is acquired.
[0077] Sensor technology is the physical basis of fault identification. There are many types of sensors, such as temperature, pressure, humidity, speed, position, vibration, noise and other sensors. These sensors can effectively monitor the working conditions of the equipment for fault identification. In this embodiment, toxic gas sensors are mainly used. Toxic gas sensors are also divided into many different types and can monitor different types of toxic gases. The types of multiple toxic gas sensors in this embodiment can be the same or different, and can be set according to actual conditions.
[0078] Some sensors may be affected by other factors in the environment, resulting in false alarms or missed alarms. In addition, the stability of the sensor is also a problem. For example, during long-term operation, the sensor may age and drift, affecting the accuracy of monitoring. Therefore, it is necessary to identify the actual toxic gas sensor data monitored in real time and filter out the actual toxic gas sensor data that may represent abnormalities.
[0079] like Figure 2 As shown in the figure, each acquisition node is the distribution position of each toxic gas sensor in the topology diagram. Each toxic gas sensor can transmit the actual toxic gas sensor data collected to the IoT gateway through the relay device, or directly transmit the actual toxic gas sensor data collected to the IoT gateway. The IoT gateway transmits the actual toxic gas sensor data to the LAN device via Ethernet, and the LAN device forwards the actual toxic gas sensor data to the monitoring server, operation station, and ERP / MES server.
[0080] Figure 2The network communication technology involved in the architecture is the bridge for fault identification, which determines the actual application scope of the fault identification method. This technology includes the compilation technology of various network communication protocols, the planning technology of network topology structure, and the technology for improving data transmission rate. Network communication technology enables the fault identification method to be implemented in large-scale applications.
[0081] During data transmission and storage, effective network security protection measures are taken, such as data encryption, access control, firewalls, etc., to ensure the security and integrity of data. At the same time, the system is regularly scanned and repaired for security vulnerabilities to prevent hacker attacks and malware intrusions.
[0082] Regarding step S12, the actual toxic gas sensor data is input into the pre-trained toxic gas fault detection model to obtain the target toxic gas sensor data with abnormalities.
[0083] The training method of the toxic gas fault detection model includes steps S121 to S125.
[0084] Step S121, performing data preprocessing operations on historical toxic gas sensor data of multiple toxic gas sensors, the data preprocessing operations including cleaning, denoising, and filling missing values to obtain effective toxic gas sensor data and improve data quality and availability.
[0085] Data processing is an intermediary operation for fault identification. It includes operations such as the collection, cleaning, organization, storage, conversion, analysis, and clarification of results of large amounts of data. Data processing technology mainly focuses on how to process large amounts of data at high speed and high precision while saving hardware resources as much as possible.
[0086] Step S122, screening out abnormal toxic gas sensor data from valid toxic gas sensor data, and performing feature extraction on the abnormal toxic gas sensor data.
[0087] Extract fault-related features from the preprocessed data, including numerical features, time series features, etc. For example, you can extract features such as the maximum value, minimum value, and average value of sensor data, as well as features such as the operating time and number of alarms of device status data.
[0088] Step S123, determining the abnormal types corresponding to each abnormal toxic gas sensor data according to the extracted features, and dividing the data according to the abnormal types corresponding to each abnormal toxic gas sensor data to obtain multiple different data clusters corresponding to the various abnormal types.
[0089] Cluster analysis technology is used to divide equipment operation data into different clusters, each cluster represents an equipment operation state or fault type. By observing abnormal clusters or outliers, possible fault locations and types can be determined.
[0090] Step S124, performing association rule mining technology analysis on multiple different data clusters to determine the changing rules of various abnormal types.
[0091] Association rule mining technology is used to analyze the association relationship between equipment operation data to discover the rules and trends hidden in the data. By setting appropriate support and confidence thresholds, it is possible to identify whether there are association rules related to faults in abnormal toxic gas sensor data.
[0092] Step S125 , training the target type model according to the multiple different data clusters and the changing rules of various abnormal types to obtain a toxic gas fault detection model.
[0093] The toxic gas fault detection model integrates several aspects such as fault identification model, fault analysis method, fault prediction, and fault decision method. There are many specific fault identification models, such as neural network, fuzzy logic, expert system, hidden Markov model, etc. These models use extracted features and historical fault data, based on specific mathematical models, machine learning, deep learning and other algorithms, to discover the rules and trends in the data through training models, and automatically identify possible fault points and types, and build a model that can automatically identify toxic gas alarm faults. Select the appropriate model according to the specific situation of the problem, such as support vector machine (SVM), neural network (NN), decision tree (DT), etc.
[0094] In addition, the toxic gas fault detection model uses the prediction function of data mining technology, such as regression analysis, time series analysis, etc., to predict the equipment operation data. By comparing the difference between actual data and predicted data, abnormal changes are found and potential fault risks are warned.
[0095] A large number of toxic gas sensors generate a large amount of data, which needs to be processed and analyzed in a timely manner. The toxic gas fault detection model provided in this embodiment not only processes and analyzes the data, focusing on the surface features of the data, but also identifies the deep information behind the data to predict future data, which reduces the probability of misjudgment or omission of faults and improves the accuracy of automatic fault identification.
[0096] In a complex system of multiple toxic gas sensors, the failure of one toxic gas sensor may affect the normal operation of other toxic gas sensors, or even cause the entire system to fail. The existing technology lacks comprehensive fault diagnosis capabilities and cannot detect and solve such problems in a timely manner. The toxic gas fault detection model provided in this embodiment not only focuses on the failure of a single toxic gas sensor, but also focuses on the correlation and interactivity between the detection points of multiple toxic gas sensors.
[0097] The toxic gas fault detection model provided in this embodiment is trained based on the collected historical fault data, and the model parameters are adjusted to improve the accuracy and generalization ability of the model. By real-time monitoring of equipment operation data, the trained model is used to classify and predict the data, and possible fault points and types are automatically identified.
[0098] Regarding step S13, when the target toxic gas sensor data meets the alarm pop-up window condition, the target toxic gas sensor data and the corresponding target sensor position are displayed on the display interface of the target host computer in a pop-up window manner.
[0099] First, check whether the pop-up function is in the on state; when the pop-up function is in the on state and the target toxic gas sensor data meets the alarm pop-up condition, the target toxic gas sensor data and the corresponding target sensor position are displayed on the display interface of the target host computer through a pop-up window.
[0100] Enable the pop-up window function for alarm points and alarm hosts. When the host enables the pop-up window function, all points under the host will enable the function by default, and you can reverse the selection. The alarm value must reach the alarm value preset in the pop-up window, and the alarm threshold of the pop-up window can be customized.
[0101] The pop-up processing instructions include user login operation, alarm handling person filling operation, alarm handling time record, alarm handling method record, alarm cause record and fault measures taken record.
[0102] like Figure 3As shown, different users use different clients (such as client 1, 2, and 3) to log in to the corresponding system. Different clients correspond to different lower computers, and each lower computer manages a part of toxic gas sensors. The PC terminal that needs to pop up is bound to the role. When a user role meets the management authority of the host point, a pop-up window will be displayed on the PC terminal logged in by the user under the role when the pop-up window condition is met. When there is gas alarm information within the system scope under the jurisdiction of the user's authority, the alarm information will pop up and display at the specified position of the system interface after meeting the alarm pop-up window condition, and an "alarm disposal" button will be attached after each gas alarm record. The user can enter the disposal interface of the alarm information by clicking the button. The alarm information disposal interface will be accompanied by some information that cannot be changed, including: login user information alarm information, etc. The alarm disposal interface can display the information that needs to be filled in, such as the alarm disposal person, alarm disposal time, alarm disposal method, alarm cause, measures taken, etc. When the user has completed filling in, an alarm information disposal record will be generated and saved in the database.
[0103] In addition, the content of the pop-up window can also include information such as alarm time, alarm point, personnel to be handled, handling process, "alarm handling" function button, etc. The pop-up window can also set an uninterrupted alarm output sound, and the color of the window header flashes to highlight the fault alarm and improve the timeliness of user fault discovery. When a terminal has multiple pop-up windows, only one pop-up window will pop up, and multiple pop-up window information will be displayed in separate lines.
[0104] When multiple target toxic gas sensor data meet the alarm pop-up conditions, the multiple target toxic gas sensor data are sorted in order according to the severity of the alarm. Multiple target toxic gas sensor data and the corresponding target sensor positions are displayed in the display interface of the target host computer in a pop-up window in order and with different background colors. For example, green means that the alarm record has been handled, yellow means that the alarm record has not been handled, and red means the most serious fault. For gas alarm information that needs to be handled, filter according to the conditions, and display the alarm information that meets the conditions in a pop-up window, focusing on reminding the post operators to increase the efficiency of alarm handling.
[0105] Regarding step S14, in response to the user's pop-up window processing instruction corresponding to the target toxic gas sensor data, when the target toxic gas sensor data does not meet the alarm pop-up window conditions, the pop-up window of the target toxic gas sensor data and the corresponding target sensor position on the display interface of the target host computer is eliminated.
[0106] In the pop-up window, all alarm information is handled and the pop-up window disappears after the alarm handling record is submitted. In addition, the alarm information handling record is generated according to the target toxic gas sensor data and its corresponding pop-up window processing instructions and saved in the database. A fault database is established in the system, and common fault types, fault causes, maintenance methods and other information are stored in the database to facilitate maintenance personnel to quickly find and solve problems.
[0107] After executing step S11, steps S21 and S22 may also be executed.
[0108] Step S21, inputting actual toxic gas sensor data into a pre-trained toxic gas fault detection model to obtain toxic gas sensors to be observed that may have abnormalities in a future time period;
[0109] Step S23, when the toxic gas sensor to be observed meets the warning pop-up window condition, the toxic gas sensor to be observed and the corresponding sensor position to be observed are displayed on the display interface of the target host computer in a pop-up window manner.
[0110] By monitoring the equipment operation data in real time, the trained model is used to classify and predict the data, automatically identifying possible fault points and types. When abnormal data is found or there is a large difference between the predicted results and the actual results, the system can automatically issue an early warning signal to remind relevant personnel to handle and repair in time.
[0111] In summary, this embodiment realizes real-time monitoring and data analysis of toxic gas alarms. When the sensor detects an abnormal situation of the toxic gas alarm, the data collector will immediately collect data, process and analyze the data, and accurately identify the fault type and location of the toxic gas alarm, so as to repair and handle it in time, improve the efficiency of fault detection, reduce the cost of manual operation, and be able to warn and predict faults and adapt to complex fault identification. This embodiment obtains data based on multiple toxic gas sensors and analyzes it to quickly and accurately identify the location and possible causes of the fault. This automated method greatly improves the efficiency of fault detection, reduces the error rate, and greatly reduces labor costs and maintenance costs. By tracking and comparing the values of each key part for a long time, early warning and prediction can be achieved before the equipment fails, so that the enterprise has time to prevent or take measures to repair in advance, avoiding or reducing the loss caused by the equipment failure. Therefore, the solution provided by this embodiment can greatly improve the efficiency of fault detection, greatly reduce the cost of manual operation, provide early warning and prediction, and establish a data analysis model to adapt to complex fault identification.
[0112] Based on the same inventive concept, this embodiment provides Figure 4 A toxic gas sensor fault identification device is shown, the device comprising:
[0113] A data acquisition module 41 is used to acquire actual toxic gas sensor data monitored in real time by multiple toxic gas sensors;
[0114] The abnormality monitoring module 42 is used to input the actual toxic gas sensor data into the pre-trained toxic gas fault detection model to obtain the target toxic gas sensor data with abnormalities;
[0115] A pop-up window display module 43 is used to display the target toxic gas sensor data and the corresponding target sensor position on the display interface of the target host computer in a pop-up window manner when the target toxic gas sensor data meets the alarm pop-up window condition;
[0116] The pop-up window elimination module 44 is used to respond to the user's pop-up window processing instruction corresponding to the target toxic gas sensor data. When the target toxic gas sensor data does not meet the alarm pop-up window conditions, the pop-up window of the target toxic gas sensor data and the corresponding target sensor position on the display interface of the target host computer is eliminated.
[0117] Furthermore, the device also includes an abnormality prediction module, which is used to:
[0118] After obtaining actual toxic gas sensor data monitored in real time by multiple toxic gas sensors, the actual toxic gas sensor data is input into a pre-trained toxic gas fault detection model to obtain toxic gas sensors to be observed that may have abnormalities in a future time period;
[0119] When the toxic gas sensor to be observed meets the warning pop-up window condition, the toxic gas sensor to be observed and the corresponding sensor position to be observed are displayed on the display interface of the target host computer through a pop-up window.
[0120] Furthermore, the device also includes a model training module, which is used to:
[0121] Performing data preprocessing operations on historical toxic gas sensor data of multiple toxic gas sensors, the data preprocessing operations including cleaning, denoising, and filling missing values to obtain valid toxic gas sensor data;
[0122] Screen out abnormal toxic gas sensor data from valid toxic gas sensor data, and perform feature extraction on the abnormal toxic gas sensor data;
[0123] Determine the abnormal types corresponding to each abnormal toxic gas sensor data according to the extracted features, and divide the data according to the abnormal types corresponding to each abnormal toxic gas sensor data to obtain multiple different data clusters corresponding to the various abnormal types;
[0124] Perform association rule mining technology analysis on multiple different data clusters to determine the changing patterns of various types of anomalies;
[0125] The target type model is trained according to multiple different data clusters and the changing rules of various abnormal types to obtain a toxic gas fault detection model.
[0126] Furthermore, the pop-up window display module 43 is used to:
[0127] When multiple target toxic gas sensor data meet the alarm pop-up window conditions, the multiple target toxic gas sensor data are sorted in order according to their alarm severity;
[0128] The data of multiple target toxic gas sensors and the corresponding target sensor positions are displayed on the display interface of the target host computer in a pop-up window in sequence and with different background colors.
[0129] Furthermore, the pop-up window elimination module 44 is used to:
[0130] In response to the user's pop-up processing instructions corresponding to the target toxic gas sensor data, the pop-up processing instructions include user login operation, alarm handling person filling operation, alarm handling time record, alarm handling method record, alarm cause record and fault measures taken record.
[0131] Furthermore, the device also includes a data storage module, which is used to:
[0132] Generate an alarm information disposal record based on the target toxic gas sensor data and its corresponding pop-up window processing instructions and save it in the database.
[0133] Furthermore, the pop-up window display module 43 is used to:
[0134] Check whether the pop-up function is turned on;
[0135] When the pop-up window function is turned on and the target toxic gas sensor data meets the alarm pop-up window conditions, the target toxic gas sensor data and the corresponding target sensor position are displayed on the display interface of the target host computer through a pop-up window.
[0136] Based on the same inventive concept, this embodiment provides Figure 5 An electronic device as shown includes:
[0137] Processor 51;
[0138] A memory 52 for storing instructions executable by the processor 51;
[0139] The processor 51 is configured to execute to implement a toxic gas sensor fault identification method as provided above.
[0140] Based on the same inventive concept, this embodiment provides a non-temporary computer-readable storage medium. When the instructions in the storage medium are executed by the processor 51 of the electronic device, the electronic device can implement a toxic gas sensor fault identification method as provided above.
[0141] Since the electronic device introduced in this embodiment is an electronic device used to implement the information processing method in the embodiment of the present application, based on the information processing method introduced in the embodiment of the present application, a person skilled in the art can understand the specific implementation of the electronic device of the present embodiment and its various variations, so how the electronic device implements the method in the embodiment of the present application is not described in detail here. As long as a person skilled in the art implements the electronic device used by the information processing method in the embodiment of the present application, it belongs to the scope of protection of this application.
[0142] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0143] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.
[0144] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.
[0145] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.
[0146] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.
[0147] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.
Claims
1. A method for identifying a toxic gas sensor fault, characterized in that: The method comprises: Acquire actual toxic gas sensor data monitored in real time by multiple toxic gas sensors; Inputting the actual toxic gas sensor data into a pre-trained toxic gas fault detection model to obtain target toxic gas sensor data with abnormalities; When the target toxic gas sensor data meets the alarm pop-up window condition, the target toxic gas sensor data and the corresponding target sensor position are displayed on the display interface of the target host computer in a pop-up window manner; In response to a pop-up window processing instruction corresponding to the target toxic gas sensor data from the user, when the target toxic gas sensor data does not meet the alarm pop-up window condition, the pop-up window of the target toxic gas sensor data and the corresponding target sensor position on the display interface of the target host computer is eliminated.
2. The method according to claim 1, characterized in that After acquiring actual toxic gas sensor data monitored in real time by a plurality of toxic gas sensors, the method further includes: Inputting the actual toxic gas sensor data into the pre-trained toxic gas fault detection model to obtain toxic gas sensors to be observed that may have abnormalities in a future time period; When the toxic gas sensor to be observed meets the early warning pop-up window condition, the toxic gas sensor to be observed and the corresponding sensor position to be observed are displayed on the display interface of the target host computer in a pop-up window manner.
3. The method according to claim 1, characterized in that The training method of the toxic gas fault detection model includes: Performing data preprocessing operations on the historical toxic gas sensor data of the plurality of toxic gas sensors, wherein the data preprocessing operations include cleaning, denoising, and filling missing values to obtain valid toxic gas sensor data; Screening out abnormal toxic gas sensor data from the valid toxic gas sensor data, and performing feature extraction on the abnormal toxic gas sensor data; Determine the abnormal types corresponding to each of the abnormal toxic gas sensor data according to the extracted features, and classify the data according to the abnormal types corresponding to each of the abnormal toxic gas sensor data to obtain a plurality of different data clusters corresponding to the various abnormal types; Perform association rule mining technology analysis on multiple different data clusters to determine the changing patterns of various types of anomalies; The target type model is trained according to a plurality of different data clusters and the changing rules of various abnormal types to obtain the toxic gas fault detection model.
4. The method according to claim 1, characterized in that When the target toxic gas sensor data meets the alarm pop-up window condition, the target toxic gas sensor data and the corresponding target sensor position are displayed on the display interface of the target host computer in a pop-up window manner, including: When multiple target toxic gas sensor data satisfy the alarm pop-up window condition, the multiple target toxic gas sensor data are sorted in order according to their alarm severity; The target toxic gas sensor data and the corresponding target sensor positions are displayed on the display interface of the target host computer in a pop-up window in the order and with different background colors.
5. The method according to claim 1, characterized in that The pop-up window processing instruction corresponding to the target toxic gas sensor data in response to the user includes: In response to the pop-up window processing instruction corresponding to the target toxic gas sensor data by the user, the pop-up window processing instruction includes user login operation, alarm handling person filling operation, alarm handling time record, alarm handling method record, alarm cause record and fault measures taken record.
6. The method according to claim 1, characterized in that In response to a pop-up window processing instruction corresponding to the target toxic gas sensor data by the user, when the target toxic gas sensor data does not meet the alarm pop-up window condition, after eliminating the pop-up window of the target toxic gas sensor data and the corresponding target sensor position on the display interface of the target host computer, the method further includes: An alarm information handling record is generated according to the target toxic gas sensor data and the corresponding pop-up window processing instruction, and is stored in a database.
7. The method according to claim 1, characterized in that When the target toxic gas sensor data meets the alarm pop-up window condition, before displaying the target toxic gas sensor data and the corresponding target sensor position on the display interface of the target host computer in a pop-up window manner, the method further includes: Check whether the pop-up function is turned on; When the pop-up window function is turned on and the target toxic gas sensor data meets the alarm pop-up window condition, the target toxic gas sensor data and the corresponding target sensor position are displayed on the display interface of the target host computer in a pop-up window manner.
8. A toxic gas sensor fault identification device, characterized in that: The device comprises: A data acquisition module, used to acquire actual toxic gas sensor data monitored in real time by multiple toxic gas sensors; An abnormality monitoring module, used for inputting the actual toxic gas sensor data into a pre-trained toxic gas fault detection model to obtain target toxic gas sensor data with abnormalities; A pop-up window display module is used to display the target toxic gas sensor data and the corresponding target sensor position on the display interface of the target host computer through a pop-up window when the target toxic gas sensor data meets the alarm pop-up window condition; A pop-up window elimination module is used to respond to a user's pop-up window processing instruction corresponding to the target toxic gas sensor data. When the target toxic gas sensor data does not meet the alarm pop-up window condition, the pop-up window of the target toxic gas sensor data and the corresponding target sensor position on the display interface of the target host computer is eliminated.
9. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute to implement a toxic gas sensor fault identification method as described in any one of claims 1 to 7.
10. A non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to implement a toxic gas sensor fault identification method as described in any one of claims 1 to 7.