Real-time control method for power box

Abstract

The present application relates to a real-time control method and apparatus for a power box, and a computer device, a computer-readable storage medium and a computer program product, which can be applied to the technical field of automation. The method comprises: collecting operation data of a power box by means of a plurality of sensors arranged in the power box, wherein the sensors comprise a temperature sensor, a vibration sensor, a current sensor and a voltage sensor; performing feature identification processing on the operation data by means of an intelligent gateway, so as to obtain feature data of the power box; performing state analysis processing on the feature data by means of an Internet of Things platform, so as to obtain a state analysis result of the power box; on the basis of the state analysis result, generating control information for the power box; and on the basis of the control information, controlling the power box. By means of the present method, the efficiency of controlling the power box can be improved.

Description

Real-time control method of power box Technical Field

[0001] This application relates to the field of automation technology, and in particular to a real-time control method, apparatus, computer equipment, computer-readable storage medium, and computer program product for a power box. Background Technology

[0002] With the development of automation technology, intelligent control of industrial equipment has become an important development direction. Power boxes are crucial power transmission devices in many industrial equipment, and how to efficiently control power boxes has become an important research area.

[0003] Traditional technology typically involves manual control of the power box; however, this method requires a significant amount of manual processing time, resulting in low efficiency in power box control. Summary of the Invention

[0004] Therefore, it is necessary to provide a real-time control method, device, computer equipment, computer-readable storage medium, and computer program product for power box that can improve the efficiency of power box control, in order to address the above-mentioned technical problems.

[0005] Firstly, this application provides a real-time control method for a power box. The method includes:

[0006] The power box's operating data is collected by multiple sensors installed inside the power box; the sensors include a temperature sensor, a vibration sensor, a current sensor, and a voltage sensor.

[0007] The power box's feature data is obtained by performing feature recognition processing on the operating data through a smart gateway.

[0008] The power box's status analysis results are obtained by performing state analysis processing on the feature data through an IoT platform.

[0009] Based on the state analysis results, control information for the power box is generated;

[0010] The power box is controlled according to the control information.

[0011] In one embodiment, the step of performing state analysis processing on the feature data through an IoT platform to obtain the state analysis result of the power box includes:

[0012] The fault status analysis model of the IoT platform is used to perform fault status analysis processing on the feature data to obtain the fault status analysis information of the power box.

[0013] Based on the fault status analysis information, the status analysis result of the power box is generated.

[0014] In one embodiment, generating control information for the power unit based on the state analysis results includes:

[0015] According to the preset multi-level early warning mechanism, the state analysis results are processed to identify the early warning level, and the early warning level of the power box is obtained.

[0016] A control command corresponding to the warning level is generated and used as the control information for the power box.

[0017] In one embodiment, controlling the power box according to the control information includes:

[0018] The remote control system sends the control command corresponding to the control information to the control terminal of the power box; the control terminal is used to control the power box according to the control command.

[0019] Receive the execution result corresponding to the control command returned by the control terminal;

[0020] Based on the execution result, the control feedback information of the power box is determined.

[0021] In one embodiment, the step of collecting operating data of the power unit through multiple sensors installed inside the power unit includes:

[0022] Temperature data of the power box is collected by the temperature sensor installed inside the power box;

[0023] Vibration data of the power box is collected by the vibration sensor installed inside the power box;

[0024] The current data of the power box is collected by the current sensor installed inside the power box;

[0025] The voltage data of the power box is collected by the voltage sensor installed inside the power box;

[0026] The temperature data, vibration data, current data, and voltage data are fused together to obtain the operating data of the power box.

[0027] In one embodiment, before performing feature recognition processing on the operating data through a smart gateway to obtain the feature data of the power box, the method further includes:

[0028] The operational data is standardized to obtain standard data corresponding to the operational data.

[0029] The step of performing feature recognition processing on the operating data through a smart gateway to obtain the feature data of the power box includes:

[0030] The standard data is processed by the smart gateway to obtain the feature data of the power box.

[0031] Secondly, this application also provides a real-time control device for a power box. The device includes:

[0032] The data acquisition module is used to collect the operating data of the power box through multiple sensors installed inside the power box; the sensors include a temperature sensor, a vibration sensor, a current sensor, and a voltage sensor.

[0033] The data recognition module is used to perform feature recognition processing on the operating data through the smart gateway to obtain the feature data of the power box;

[0034] The data analysis module is used to perform state analysis processing on the feature data through the Internet of Things platform to obtain the state analysis results of the power box;

[0035] The information generation module is used to generate control information for the power box based on the state analysis results.

[0036] The target control module is used to control the power box according to the control information.

[0037] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0038] The power box's operating data is collected by multiple sensors installed inside the power box; the sensors include a temperature sensor, a vibration sensor, a current sensor, and a voltage sensor.

[0039] The power box's feature data is obtained by performing feature recognition processing on the operating data through a smart gateway.

[0040] The power box's status analysis results are obtained by performing state analysis processing on the feature data through an IoT platform.

[0041] Based on the state analysis results, control information for the power box is generated;

[0042] The power box is controlled according to the control information.

[0043] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0044] The power box's operating data is collected by multiple sensors installed inside the power box; the sensors include a temperature sensor, a vibration sensor, a current sensor, and a voltage sensor.

[0045] The power box's feature data is obtained by performing feature recognition processing on the operating data through a smart gateway.

[0046] The power box's status analysis results are obtained by performing state analysis processing on the feature data through an IoT platform.

[0047] Based on the state analysis results, control information for the power box is generated;

[0048] The power box is controlled according to the control information.

[0049] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0050] The power box's operating data is collected by multiple sensors installed inside the power box; the sensors include a temperature sensor, a vibration sensor, a current sensor, and a voltage sensor.

[0051] The power box's feature data is obtained by performing feature recognition processing on the operating data through a smart gateway.

[0052] The power box's status analysis results are obtained by performing state analysis processing on the feature data through an IoT platform.

[0053] Based on the state analysis results, control information for the power box is generated;

[0054] The power box is controlled according to the control information.

[0055] The aforementioned real-time control method, device, computer equipment, computer-readable storage medium, and computer program product for the power box collects operating data from the power box using multiple sensors installed within it. These sensors include temperature sensors, vibration sensors, current sensors, and voltage sensors. A smart gateway performs feature recognition processing on the operating data to obtain characteristic data of the power box. An IoT platform performs state analysis processing on the characteristic data to obtain a state analysis result for the power box. Based on the state analysis result, control information for the power box is generated. The power box is then controlled according to the control information. This solution achieves comprehensive monitoring of the power box's operating status by installing temperature, vibration, current, and voltage sensors within the power box; extracts characteristic data through feature recognition processing of the operating data using a smart gateway; performs state analysis processing on the characteristic data through an IoT platform to achieve intelligent judgment of the power box's status; and finally, automatically generates and executes control information based on the analysis results, effectively reducing manual intervention. This automated monitoring, analysis, and control process improves the efficiency and accuracy of power box control. Attached Figure Description

[0056] To more clearly illustrate the technical solutions in the embodiments or related technologies of this application, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0057] Figure 1 is a flowchart illustrating a real-time control method for a power box in one embodiment;

[0058] Figure 2 is a schematic diagram of the architecture of a real-time control method for the power box in one embodiment;

[0059] Figure 3 is a functional structure diagram of a real-time control method for a power box in one embodiment;

[0060] Figure 4 is a structural block diagram of the power box real-time control device in one embodiment;

[0061] Figure 5 is an internal structure diagram of a computer device in one embodiment. Detailed Implementation

[0062] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0063] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0064] In an exemplary embodiment, as shown in Figure 1, a real-time control method for a power box is provided. This embodiment illustrates the application of this method to an intelligent power box real-time management platform (such as a terminal, or a terminal equipped with an intelligent power box real-time management platform). It is understood that this method can also be applied to a server, or to a system including a terminal and a server, and is implemented through interaction between the terminal and the server. The terminal can be, but is not limited to, various personal computers, laptops, smartphones, tablets, etc.; the server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. In this embodiment, the method includes the following steps:

[0065] Step S101: Collect operating data of the power box by using multiple sensors installed inside the power box; the sensors include a temperature sensor, a vibration sensor, a current sensor, and a voltage sensor.

[0066] Step S102: The operating data is processed by the intelligent gateway to obtain the characteristic data of the power box.

[0067] Step S103: The feature data is processed by the Internet of Things platform to obtain the state analysis results of the power box.

[0068] Step S104: Based on the state analysis results, generate control information for the power box.

[0069] Step S105: Control the power box according to the control information.

[0070] Among them, the power box can be equipment in the field of industrial automation and intelligent management. For example, the power box can be industrial equipment that requires real-time monitoring, fault diagnosis and intelligent maintenance.

[0071] Among them, the sensor can be a data acquisition device used to collect power box operation data. For example, the sensor can be a device that can achieve high-precision data acquisition and support multi-parameter monitoring.

[0072] Among them, the temperature sensor can be a sensor used to detect the temperature of the power box. For example, the temperature sensor can be a device deployed in a key part inside the power box to collect temperature data in real time.

[0073] Among them, the vibration sensor can be a sensor used to detect the vibration of the power box. For example, the vibration sensor can be a device deployed in a key part inside the power box to collect vibration data in real time.

[0074] Among them, the current sensor can be a sensor used to detect the current of the power box. For example, the current sensor can be a device deployed in a key part inside the power box to collect current data in real time.

[0075] Among them, the voltage sensor can be a sensor used to detect the voltage of the power box. For example, the voltage sensor can be a device deployed in a key part inside the power box to collect voltage data in real time.

[0076] Among them, a smart gateway can be a data processing device with edge computing capabilities. For example, a smart gateway can be a device that can uniformly collect, store, and analyze terminal data, and realize data parsing and modeling.

[0077] Among them, the Internet of Things (IoT) platform can be an integrated platform for data processing and analysis. For example, an IoT platform can be a platform with functions such as full network object model management, data modeling, and device information management.

[0078] Among them, the operating data can be the raw data generated by the power box during operation, such as real-time acquisition data of parameters such as temperature, vibration, current, and voltage.

[0079] Among them, feature data can be data processed by a smart gateway, such as standardized data after data parsing and modeling.

[0080] Among them, the status analysis results can be the results obtained by the IoT platform after analyzing the feature data. For example, the status analysis results can be the identification results of abnormal status and potential faults of the device.

[0081] The control information can be control instructions generated based on the state analysis results. For example, the control information can be control instructions in formats such as JSON (JavaScript Object Notation) and XML (Extensible Markup Language).

[0082] Optionally, the intelligent power box maintenance real-time management platform collects power box operating data through high-precision temperature sensors, vibration sensors, current sensors, and voltage sensors deployed in key components inside the power box; it uses wireless sensor network technology to achieve wireless data transmission; then, the platform uses edge computing technology from an intelligent gateway to preprocess and feature-recognize the collected operating data, including data noise reduction and feature extraction, and formats the feature data according to a unified object model standard; next, the platform uses machine learning and deep learning algorithms from an IoT platform to perform in-depth analysis of the feature data, and identifies abnormal states and potential faults in the power box through a multi-level early warning mechanism (including preliminary early warning, advanced early warning, and emergency early warning), obtaining the power box status analysis results; finally, based on the status analysis results, the platform generates standard-format control information through a visual operation interface, and sends the control information to the power box control unit for execution via SSL / TLS (Secure Sockets Layer / Transport Layer Security) encryption.

[0083] In the aforementioned real-time control method for the power box, multiple sensors installed within the power box collect its operating data. These sensors include temperature, vibration, current, and voltage sensors. A smart gateway performs feature recognition processing on the operating data to obtain characteristic data of the power box. An IoT platform then performs state analysis processing on this characteristic data to obtain the power box's state analysis results. Based on the state analysis results, control information for the power box is generated. Finally, the power box is controlled according to this control information. This solution achieves comprehensive monitoring of the power box's operating status by installing temperature, vibration, current, and voltage sensors within the power box. The smart gateway performs feature recognition processing on the operating data to extract characteristic data. The IoT platform performs state analysis processing on this characteristic data to achieve intelligent judgment of the power box's state. Finally, control information is automatically generated and executed based on the analysis results, effectively reducing manual intervention. This automated monitoring, analysis, and control process improves the efficiency and accuracy of power box control.

[0084] In an exemplary embodiment, the power box status analysis result is obtained by performing status analysis processing on the feature data through an IoT platform. Specifically, this includes: performing fault status analysis processing on the feature data through the fault status analysis model of the IoT platform to obtain fault status analysis information of the power box; and generating the power box status analysis result based on the fault status analysis information.

[0085] Among them, the fault state analysis model can be an analysis model based on machine learning and deep learning algorithms. For example, the fault state analysis model can be an intelligent analysis model that can automatically learn fault characteristics from data and achieve accurate fault classification and identification.

[0086] Among them, the fault status analysis information can be the identification results of abnormal operating status and potential faults of the power box. For example, the fault status analysis information can be analysis information that includes fault type, location and severity.

[0087] Among them, the status analysis results can be comprehensive analysis conclusions generated based on fault status analysis information. For example, the status analysis results can be analysis results that include multi-level warning information such as preliminary warning, advanced warning and emergency warning.

[0088] Optionally, the intelligent power box maintenance real-time management platform first performs in-depth analysis of the feature data through the fault status analysis model of the IoT platform. This fault status analysis model uses machine learning and deep learning algorithms to automatically learn fault characteristics from the data. Next, the intelligent power box maintenance real-time management platform performs noise reduction and feature extraction on the feature data through the fault status analysis model to identify abnormal states and potential faults of the power box and generate fault status analysis information including fault type, location, and severity. Then, based on the fault status analysis information and combined with a preset multi-level early warning mechanism (including preliminary early warning, advanced early warning, and emergency early warning), the intelligent power box maintenance real-time management platform generates the power box status analysis results.

[0089] The technical solution provided in this embodiment analyzes and processes feature data through a fault state analysis model on an IoT platform, achieving professional analysis of power box fault states and avoiding the subjectivity and uncertainty inherent in traditional manual analysis. By transforming fault state analysis information into state analysis results, standardized output of fault state information is achieved. This IoT platform-based analysis and processing method significantly improves the accuracy of power box fault state analysis, providing a reliable basis for subsequent fault handling.

[0090] In an exemplary embodiment, control information for the power box is generated based on the state analysis results, specifically including the following: according to a preset multi-level early warning mechanism, the state analysis results are processed to identify the early warning level to obtain the early warning level of the power box; control commands corresponding to the early warning level are generated as control information for the power box.

[0091] Among them, a multi-level early warning mechanism can be a hierarchical early warning system. For example, a multi-level early warning mechanism can include different levels of early warning, such as preliminary early warning, advanced early warning, and emergency early warning.

[0092] Among them, the early warning level identification process can be a process of classifying and judging the status analysis results. For example, the early warning level identification process can be a process of classifying the operating status of the power box according to the set early warning threshold and parameters.

[0093] The warning level can be a grade indicator representing the degree of abnormality in the power box's operating status. For example, the warning level can be different levels such as preliminary warning, advanced warning, or emergency warning.

[0094] Among them, the control instructions can be specific operation commands used to control the operation of the power box. For example, the control instructions can be device control commands in JSON (JavaScript Object Notation) or XML (Extensible Markup Language) format.

[0095] Optionally, the intelligent power box maintenance real-time management platform first identifies the warning level of the power box status analysis results according to a preset multi-level warning mechanism. This warning mechanism includes three levels: preliminary warning, advanced warning, and emergency warning. By comparing the parameters in the status analysis results with the preset warning thresholds, the specific warning level of the power box is determined. Then, based on the identified warning level, the intelligent power box maintenance real-time management platform generates corresponding control commands through the control command generation module, and packages these control commands into control information in JSON (JavaScript Object Notation) or XML (Extensible Markup Language) format, and ensures command security through SSL / TLS encryption transmission.

[0096] The technical solution provided in this embodiment achieves graded early warning of the power unit's operating status by identifying and processing the status analysis results through a preset multi-level early warning mechanism. By generating control commands corresponding to the early warning levels as control information, differentiated control is achieved for different early warning levels. This control information generation method based on early warning levels improves the accuracy and response efficiency of power unit fault handling.

[0097] In an exemplary embodiment, controlling the power box according to the control information specifically includes the following: sending the control command corresponding to the control information to the control terminal of the power box through a remote control system; the control terminal is used to control the power box according to the control command; receiving the execution result corresponding to the control command returned by the control terminal; and determining the control feedback information of the power box based on the execution result.

[0098] Among them, the remote control system can be a control system that establishes a platform and a channel for issuing commands to the device side. For example, the remote control system can be a system that allows input of control commands through a visual operation interface and transmits them through SSL / TLS encryption.

[0099] The control end can be the control execution unit of the power box equipment, such as the equipment terminal that receives control commands and performs corresponding operations.

[0100] The execution result can be the operation status feedback after the control terminal executes the control command, such as the status information of whether the operation is successful or failed.

[0101] Among them, control feedback information can be comprehensive information on the completion status of control operations generated based on the execution results. For example, control feedback information can be feedback data that includes operation status, execution time, execution effect, etc.

[0102] Optionally, the intelligent maintenance power box real-time management platform first generates control commands through the visual operation interface of the remote control system, converts the control commands into JSON (JavaScript Object Notation) or XML (Extensible Markup Language) format, and sends the control commands to the power box control terminal via MQTT (Message Queuing Telemetry Transmission) or HTTP / HTTPS (Hypertext Transfer Protocol / Secure Hypertext Transfer Protocol) protocol through SSL / TLS encrypted transmission. Then, the intelligent maintenance power box real-time management platform receives the execution results returned by the control terminal, parses and verifies the execution results, and generates control feedback information containing information such as operation status, execution time, and execution effect based on the execution results.

[0103] The technical solution provided in this embodiment achieves remote automated control of the powertrain by sending control commands to the powertrain control terminal and receiving execution results through a remote control system. By having the control terminal return execution results and determine control feedback information, a complete control closed loop is formed, which facilitates timely monitoring of the execution status of control commands. This closed-loop control method based on remote control and feedback improves the accuracy of powertrain control.

[0104] In an exemplary embodiment, multiple sensors installed inside the power box are used to collect operating data of the power box, specifically including the following: collecting temperature data of the power box using a temperature sensor installed inside the power box; collecting vibration data of the power box using a vibration sensor installed inside the power box; collecting current data of the power box using a current sensor installed inside the power box; collecting voltage data of the power box using a voltage sensor installed inside the power box; and fusing the temperature data, vibration data, current data, and voltage data to obtain the operating data of the power box.

[0105] The temperature data can be power box temperature information collected by temperature sensors, such as power box temperature time series data monitored at the micro / nanosecond level.

[0106] The vibration data can be the power box vibration information collected by vibration sensors, such as the power box vibration time series data monitored at the micro / nanosecond level.

[0107] The current data can be the power box current information collected by the current sensor, such as the power box current timing data monitored at the micro / nanosecond level.

[0108] Among them, voltage data can be power box voltage information collected by voltage sensors, such as power box voltage timing data monitored at the micro / nanosecond level.

[0109] Fusion processing can be a process of comprehensively analyzing and processing data collected by multiple sensors. For example, fusion processing can be a process of locally processing and integrating temperature data, vibration data, current data, and voltage data through a data acquisition device.

[0110] Optionally, a high-precision sensor network is deployed in key areas inside the power box. Temperature sensors are installed in areas with high heat density, vibration sensors are installed around moving parts, and current and voltage sensors are installed at key nodes of the power supply line. All sensors use micro / nanosecond sampling frequencies to collect data. The intelligent maintenance power box real-time management platform transmits the collected temperature, vibration, current, and voltage data to a data acquisition unit. The data acquisition unit performs local preprocessing and standardization conversion, and then fuses the data according to a unified physical model standard to finally form standardized measurement data (operational data) reflecting the overall operating status of the power box.

[0111] The technical solution provided in this embodiment achieves multi-dimensional data acquisition of the power box's operating status by deploying multiple sensors, such as temperature sensors, vibration sensors, current sensors, and voltage sensors, within the power box, thus avoiding monitoring blind spots caused by a single sensor. By fusing the collected temperature, vibration, current, and voltage data, complete operating data is formed, which is beneficial for comprehensively reflecting the power box's operating status. This multi-sensor-based data acquisition and fusion processing method improves the comprehensiveness and accuracy of power box operating status monitoring.

[0112] In an exemplary embodiment, before performing feature recognition processing on the operating data through the smart gateway to obtain the power box feature data, the following steps are included: standardizing the operating data to obtain standard data corresponding to the operating data; and performing feature recognition processing on the operating data through the smart gateway to obtain the power box feature data, specifically including: performing feature recognition processing on the standard data through the smart gateway to obtain the power box feature data.

[0113] Standardization processing can be a process of converting data from different sources and formats into a unified standard format. For example, standardization processing can be a process of converting collected operational data into a standardized data format according to a unified object model standard.

[0114] Standard data can be standardized data that has undergone standardization processing. For example, standard data can be standardized measurement data that conforms to the unified object model standard and is convenient for subsequent feature recognition and processing.

[0115] Optionally, the intelligent maintenance power box real-time management platform first standardizes the collected operating data according to a unified object model standard, including data format conversion, unit unification, time synchronization and other preprocessing operations, and converts the processed data into standard formats such as JSON (JavaScript Object Notation) or XML (Extensible Markup Language); then, the intelligent maintenance power box real-time management platform uses the edge computing capabilities of the intelligent gateway to perform feature recognition processing on the standardized data, including data noise reduction, feature extraction, pattern recognition and other operations, and finally generates feature data containing key information such as the power box operating status, performance indicators, and fault characteristics.

[0116] The technical solution provided in this embodiment achieves data format unification and standardization by standardizing the running data before feature recognition processing; and improves the accuracy and efficiency of feature recognition by performing feature recognition processing on the standardized data through an intelligent gateway.

[0117] The following application example illustrates the real-time control method for the power box provided in this application. This application example demonstrates the application of this method to an intelligent maintenance power box real-time management platform, as shown in Figures 2 and 3.

[0118] This application example relates to the field of industrial automation and intelligent management, specifically a management platform for real-time monitoring, fault diagnosis, and intelligent maintenance of power distribution equipment. By integrating advanced sensor technology, data processing and analysis technology, and remote communication technology, this platform enables real-time monitoring of the power distribution equipment's operating status, fault early warning, and intelligent scheduling, significantly improving the maintenance efficiency and operational safety of the power distribution equipment.

[0119] Existing power box management systems mostly employ traditional methods of periodic maintenance and manual inspection, which suffer from long maintenance cycles, low efficiency, and significant safety hazards. With the development of industrial automation and intelligence, higher demands are being placed on power box management. Therefore, developing a real-time management platform capable of monitoring power box operating status in real time, providing timely fault warnings, and intelligently scheduling maintenance tasks is of great significance.

[0120] Involving technological development:

[0121] 1. Advances in Sensor Technology: With the continuous development of sensor technology, modern sensors can achieve higher-precision data acquisition and support multi-parameter monitoring, such as temperature, vibration, current, and voltage, making comprehensive monitoring of the power unit possible. Furthermore, the application of wireless sensor network technology allows sensors to be flexibly deployed in various key parts of the power unit, enabling wireless data transmission and reducing wiring costs and complexity.

[0122] 2. Enhanced Data Processing and Analysis Capabilities: Cloud computing technology provides powerful support for the storage and processing of massive amounts of data, while edge computing enables preliminary processing at the data source, reducing data transmission latency and improving system response speed. Through big data analytics and artificial intelligence technologies, the operating data of the power unit can be deeply analyzed to discover potential operational problems and predict fault occurrences, providing decision support for intelligent maintenance.

[0123] 3. Innovation in Fault Diagnosis and Early Warning Technologies: Fault diagnosis models based on machine learning and deep learning algorithms can automatically learn fault characteristics from data, achieving accurate fault classification and identification, and improving the accuracy and efficiency of fault diagnosis. Combining real-time monitoring data and fault diagnosis results, the intelligent early warning system can promptly detect potential faults and notify relevant personnel through various means, such as SMS, email, and APP (application) push notifications, ensuring timely handling of faults.

[0124] 4. Integration of Information and Intelligent Management Platforms: Data acquisition, processing, analysis, fault diagnosis, early warning, scheduling, and maintenance functions are integrated into a unified platform to achieve full lifecycle management of the power unit. A visual interface displays key data such as the power unit's operating status, fault information, and maintenance progress, enabling managers to intuitively understand the power unit's operation and improve management efficiency.

[0125] In summary, the technological development of intelligent power box real-time management platforms exhibits trends towards high precision, multi-parameter operation, wireless connectivity, cloud computing, big data integration, intelligence, integration, visualization, and high security and reliability. These technological advancements provide strong support for the intelligent management of power boxes, continuously advancing industrial automation and intelligence.

[0126] The relevant technologies can be mainly summarized into the following aspects:

[0127] 1. Remote monitoring and data acquisition technology:

[0128] Related technology description: Currently, many industrial equipment have implemented remote monitoring functions. These devices collect operational data in real time through sensors deployed on the equipment and transmit it to a remote monitoring center via wireless or wired networks. These technologies provide the data foundation for a real-time management platform for intelligent maintenance power boxes.

[0129] Technical features: High-precision, multi-parameter sensors, stable data transmission channels, and data processing capabilities of the remote monitoring center together constitute the core of remote monitoring and data acquisition technology.

[0130] 2. Data processing and analysis techniques:

[0131] Related technical description: With the development of big data and artificial intelligence technologies, data processing and analysis technologies have been widely applied in various fields. In the field of industrial automation, by cleaning, transforming, modeling, and analyzing the collected data through data analysis algorithms, abnormal situations and potential problems in equipment operation can be discovered.

[0132] Technical features: Big data processing technology can quickly process massive amounts of data, while artificial intelligence algorithms can learn from the data and extract valuable information to provide decision support for intelligent maintenance.

[0133] 3. Fault diagnosis and early warning technology:

[0134] Related Technology Description: Fault diagnosis and early warning technology is an important research direction in the field of industrial automation. Related technologies enable fault diagnosis and early warning based on rules, statistical methods, and machine learning algorithms. Through the analysis of equipment operating data, these technologies can identify the type, location, and severity of faults and issue early warning signals in advance.

[0135] Technical characteristics: The accuracy and timeliness of fault diagnosis and early warning technologies are crucial for improving equipment reliability and safety. Related technologies can achieve these goals to a certain extent, but continuous optimization and improvement are still needed.

[0136] However, the relevant technologies have the following problems:

[0137] 1. Limitations of Data Acquisition and Transmission: While sensor technology has made some progress, its accuracy and stability still need improvement in certain complex environments. Furthermore, the coverage area of ​​sensors may not be sufficient to comprehensively monitor all critical components of the power unit, resulting in blind spots in data acquisition. Wireless transmission is susceptible to signal interference and network congestion, leading to data transmission delays or losses. In addition, while wired transmission is stable, it suffers from high cabling costs and maintenance difficulties.

[0138] 2. Complexity of Data Processing and Analysis: The power unit generates a massive amount of data, which is diverse in type, including both structured and unstructured data. How to efficiently and accurately process this data and extract valuable information is a significant challenge currently facing technology. The accuracy and adaptability of fault diagnosis and early warning algorithms directly affect the accuracy and timeliness of intelligent maintenance. However, existing algorithms have limitations in handling complex fault modes and cannot fully meet practical needs.

[0139] 3. Limitations of Fault Diagnosis and Early Warning: Due to imperfections in algorithms or errors in data acquisition, fault diagnosis and early warning systems may experience false alarms or missed alarms. False alarms increase the workload of maintenance personnel, while missed alarms may lead to serious accidents. Ensuring the timeliness and accuracy of early warning signals is crucial during real-time monitoring. However, current technologies cannot issue early warning signals sufficiently before a fault occurs, resulting in missed opportunities for optimal intervention.

[0140] 4. Integration and Stability of Intelligent Maintenance Systems: Intelligent maintenance systems require the integration of various advanced technologies, including sensor technology, signal processing technology, and intelligent control technology. The integration and stability of these technologies directly affect the overall performance and reliability of the intelligent maintenance system. In practical applications, compatibility issues exist between different equipment models, increasing the difficulty of system integration. Furthermore, technical obstacles exist in data exchange and sharing between different systems.

[0141] Overview of this application example:

[0142] This application example, through a technical approach combining a smart gateway and an IoT platform, provides unified access and edge computing capabilities for data from online monitoring, robot control, and video. It addresses the challenges of inconsistent communication protocols and difficult data sharing in traditional monitoring systems, enabling unified collection, storage, and analysis of terminal data.

[0143] 1. Design a real-time data processing system to monitor and preprocess the power box operating data online;

[0144] 2. Design standardized module interfaces and communication protocols to enable seamless and quick access to devices with any protocol, ensuring compatibility and interoperability between modules;

[0145] 3. Introduce cloud computing and Internet of Things technologies to achieve remote monitoring and intelligent control scheduling management, thereby improving the overall performance and reliability of the system;

[0146] 4. Introduce an intelligent safety monitoring system to monitor and provide early warnings in real time during the daily operation of the power box.

[0147] This application example aims to build an intelligent real-time management platform for power box maintenance. By integrating high-precision sensors, big data processing, machine learning algorithms, and remote collaboration technologies, it achieves real-time monitoring, intelligent analysis, fault early warning, remote guidance, intelligent scheduling and optimization of power box operating status. This improves the reliability and safety of power box operation, reduces maintenance costs, increases work efficiency, and establishes a standardized set of electricity permitting criteria to accurately manage the power consumption of power boxes, thus solving the problem of inaccurate electricity consumption indicators. Simultaneously, the platform can effectively calculate temporary electricity consumption.

[0148] The core content of this application example:

[0149] 1. Data Acquisition and Transmission System:

[0150] High-precision sensors: High-precision, multi-parameter sensors, such as temperature sensors, vibration sensors, current sensors, and voltage sensors, are deployed in key parts inside the power box to collect equipment operating data in real time.

[0151] Data monitoring standards: Standards for building a unified access platform for multi-source data, providing a unified and standardized object model standard, and enabling seamless and fast access for any protocol device.

[0152] Data Acquisition Unit: Responsible for processing the data collected by the sensors locally and uploading it to the cloud server according to the communication protocol. The data acquisition unit has functions such as encryption / authentication, breakpoint resumption, self-describing, and intelligent control to ensure the security and reliability of data transmission.

[0153] 2. Intelligent Analysis System:

[0154] Big Data Processing Platform: Utilizing cloud computing and big data technologies, this platform constructs a high-efficiency data processing platform to rapidly process and analyze massive amounts of collected data. Advanced technologies such as distributed computing and in-memory computing improve data processing efficiency and accuracy.

[0155] Intelligent analysis algorithms: Employing machine learning, deep learning, and other algorithms, the processed data undergoes in-depth mining and analysis. The algorithm model can automatically identify abnormal equipment states and potential faults, and predict fault development trends, providing a scientific basis for subsequent maintenance decisions.

[0156] 3. Fault early warning and remote control system:

[0157] Multi-level early warning mechanism: Establish a multi-level early warning mechanism, including preliminary early warning, advanced early warning, and emergency early warning. By setting reasonable early warning thresholds and parameters, ensure the timeliness and accuracy of early warning signals. Once an anomaly is detected, the system will automatically send early warning information to relevant personnel and prompt appropriate handling measures.

[0158] Remote Control System: Establishes a command distribution channel between the platform and the device side. Users input relevant control commands through a visual interface. The control center receives user input, converts it into a device-specific control command format, such as JSON or XML, and selects an appropriate communication protocol based on the device and network environment, such as MQTT (Message Queuing Telemetry Transport), HTTP / HTTPS (Hypertext Transfer Protocol / Secure Hypertext Transfer Protocol), or CoAP (CoAP). It ensures effective command transmission and employs encryption methods such as SSL / TLS to protect data transmission and implements an authentication mechanism to prevent unauthorized access. Upon receiving a command, the device parses the command content, identifies the specific operation instructions and related parameters, executes the corresponding operation according to the parsing results, and sends the execution result back to the control center after completion.

[0159] 4. Information and intelligent management platform:

[0160] Highly integrated platform: Employing standardized interfaces and protocols, it enables seamless integration and data exchange between various systems. The management platform offers a wealth of functional modules and a user-friendly interface, facilitating user operations such as device management, data querying, and report generation.

[0161] Referring to Figure 2, the architecture of the intelligent maintenance power box real-time management platform in this application example is divided into three layers: the application layer, the platform layer, and the access layer. The application layer contains business application systems for consistency checks of the equipment information model. The platform layer consists of an IoT platform for access data parsing and modeling, including equipment information model and network-wide object model management. The access layer consists of intelligent gateways for data collection and modeling, including equipment information model and data modeling, and data parsing through edge fusion applications. Multiple terminal devices are connected at the bottom of the access layer. The entire system ensures data accuracy through consistency checks and distribution mechanisms. The data flow and processing between each layer is as follows: terminal devices transmit data to the intelligent gateway; the intelligent gateway processes the data from the terminals through data parsing; after processing by the edge fusion application, the data is transmitted to the IoT platform; the IoT platform performs network-wide object model management and data modeling; finally, the processed data is transmitted to the business application system for application-level processing.

[0162] Referring to Figure 3, the functional structure of the intelligent maintenance power box real-time management platform in this application example includes multiple data sources, data access components, a data processing center, and a management platform. Specifically, the data sources include: sensing devices, micro / nanosecond-level monitoring data, time-series databases, system-level relational data, images, videos, audio, other files, and equipment fault recording data. This data is processed through four components: industrial IoT access components, cascading synchronization / ferry components, data components, and unstructured access components, transforming the data into both standardized measurement data and unstructured data. The core functional modules of the system include: application enablement, data cascading, a rules engine, IoT management, cloud-edge collaboration, intelligent operation and maintenance, and connection management. Regarding data sources, the system supports various data types, including: relational data, time-series data, unstructured data, semi-structured data, cached data, and vector data. Through intelligent IoT components (automatic access for all types) and service components, an industrial IoT platform is formed. Additionally, it includes two core platforms: an industrial IoT management platform and an industrial big data center.

[0163] The technical solution provided in this application example achieves the following technical effects:

[0164] 1. Improve maintenance efficiency: Through real-time monitoring and intelligent scheduling, rapid response and timely handling of power box failures are achieved, significantly shortening the maintenance cycle;

[0165] 2. Reduced safety risks: Reduced the number and risks of manual inspections and maintenance, improving the safety of power box operation;

[0166] 3. Optimize resource allocation: Intelligent scheduling is carried out based on the actual needs of maintenance tasks and resource availability, achieving optimized resource allocation and efficient utilization;

[0167] 4. Improved management level: Through data-driven management, comprehensive monitoring and refined management of the power box's operating status have been achieved, thereby improving the overall management level.

[0168] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0169] Based on the same inventive concept, this application also provides a power box real-time control device for implementing the aforementioned power box real-time control method. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more power box real-time control device embodiments provided below can be found in the limitations of the power box real-time control method described above, and will not be repeated here.

[0170] In an exemplary embodiment, as shown in FIG4, a power box real-time control device is provided, the power box real-time control device 400 may include:

[0171] The data acquisition module 401 is used to acquire the operating data of the power box through multiple sensors installed in the power box; the sensors include a temperature sensor, a vibration sensor, a current sensor and a voltage sensor;

[0172] The data recognition module 402 is used to perform feature recognition processing on the operating data through the smart gateway to obtain the feature data of the power box;

[0173] Data analysis module 403 is used to perform state analysis processing on feature data through the Internet of Things platform to obtain the state analysis results of the power box;

[0174] The information generation module 404 is used to generate control information for the power box based on the status analysis results.

[0175] The target control module 405 is used to control the power box based on the control information.

[0176] In an exemplary embodiment, the data analysis module 403 is further configured to perform fault state analysis processing on the feature data through the fault state analysis model of the Internet of Things platform to obtain fault state analysis information of the power box; and generate the state analysis result of the power box based on the fault state analysis information.

[0177] In an exemplary embodiment, the information generation module 404 is further configured to perform early warning level identification processing on the status analysis results according to a preset multi-level early warning mechanism to obtain the early warning level of the power box; and generate control instructions corresponding to the early warning level as control information of the power box.

[0178] In an exemplary embodiment, the target control module 405 is further configured to send control instructions corresponding to the control information to the control terminal of the power box via a remote control system; the control terminal is configured to control the power box according to the control instructions; receive the execution result corresponding to the control instructions returned by the control terminal; and determine the control feedback information of the power box according to the execution result.

[0179] In an exemplary embodiment, the data acquisition module 401 is further configured to acquire temperature data of the power box using a temperature sensor installed inside the power box; acquire vibration data of the power box using a vibration sensor installed inside the power box; acquire current data of the power box using a current sensor installed inside the power box; acquire voltage data of the power box using a voltage sensor installed inside the power box; and fuse the temperature data, vibration data, current data, and voltage data to obtain the operating data of the power box.

[0180] In an exemplary embodiment, the device 400 further includes: a data processing module for standardizing the operating data to obtain standard data corresponding to the operating data; and a data recognition module 402 for performing feature recognition processing on the standard data through a smart gateway to obtain feature data of the power box.

[0181] Each module in the aforementioned real-time control device for the power box can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0182] In an exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram is shown in Figure 5. The computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface of the computer device is used for exchanging information between the processor and external devices. The communication interface of the computer device is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a real-time control method for a power box. The display unit of the computer device is used to form a visually visible image and may be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0183] Those skilled in the art will understand that the structure shown in Figure 5 is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or may combine certain components, or may have different component arrangements.

[0184] In one exemplary embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0185] In one exemplary embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above-described method embodiments.

[0186] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0187] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, 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 many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0188] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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.

[0189] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A real-time control method for a power box, characterized in that, The method includes: The power box's operating data is collected by multiple sensors installed inside the power box; the sensors include a temperature sensor, a vibration sensor, a current sensor, and a voltage sensor. The power box's feature data is obtained by performing feature recognition processing on the operating data through a smart gateway. The power box's status analysis results are obtained by performing state analysis processing on the feature data through an IoT platform. Based on the state analysis results, control information for the power box is generated; The power box is controlled according to the control information.

2. The method according to claim 1, characterized in that, The process of performing state analysis on the feature data through an IoT platform to obtain the state analysis results of the power box includes: The fault status analysis model of the IoT platform is used to perform fault status analysis processing on the feature data to obtain the fault status analysis information of the power box. Based on the fault status analysis information, the status analysis result of the power box is generated.

3. The method according to claim 1, characterized in that, The step of generating control information for the power unit based on the state analysis results includes: According to the preset multi-level early warning mechanism, the state analysis results are processed to identify the early warning level, and the early warning level of the power box is obtained. A control command corresponding to the warning level is generated and used as the control information for the power box.

4. The method according to claim 1, characterized in that, The step of controlling the power box according to the control information includes: The remote control system sends the control command corresponding to the control information to the control terminal of the power box; the control terminal is used to control the power box according to the control command. Receive the execution result corresponding to the control command returned by the control terminal; Based on the execution result, the control feedback information of the power box is determined.

5. The method according to claim 1, characterized in that, The method of collecting operating data of the power box through multiple sensors installed inside the power box includes: Temperature data of the power box is collected by the temperature sensor installed inside the power box; Vibration data of the power box is collected by the vibration sensor installed inside the power box; The current data of the power box is collected by the current sensor installed inside the power box; The voltage data of the power box is collected by the voltage sensor installed inside the power box; The temperature data, vibration data, current data, and voltage data are fused together to obtain the operating data of the power box.

6. The method according to any one of claims 1 to 5, characterized in that, Before performing feature recognition processing on the operating data through the smart gateway to obtain the feature data of the power box, the process further includes: The operational data is standardized to obtain standard data corresponding to the operational data. The step of performing feature recognition processing on the operating data through a smart gateway to obtain the feature data of the power box includes: The standard data is processed by the smart gateway to obtain the feature data of the power box.

7. A real-time control device for a power box, characterized in that, The device includes: The data acquisition module is used to collect the operating data of the power box through multiple sensors installed inside the power box; the sensors include a temperature sensor, a vibration sensor, a current sensor, and a voltage sensor. The data recognition module is used to perform feature recognition processing on the operating data through the smart gateway to obtain the feature data of the power box; The data analysis module is used to perform state analysis processing on the feature data through the Internet of Things platform to obtain the state analysis results of the power box; The information generation module is used to generate control information for the power box based on the state analysis results. The target control module is used to control the power box according to the control information.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

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

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

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