Power distribution cabinet remote monitoring system based on wireless communication

Abstract

The invention discloses a power distribution cabinet remote monitoring system based on wireless communication, and relates to the technical field of remote monitoring, and the system comprises a communication scheduling module which is used for receiving an uploaded data packet, carrying out link evaluation through an uploading link optimization method in combination with a real-time network condition, and carrying out link optimization according to an actual link condition and the priority of the uploaded data; selecting an initial uploading link and uploading data; the Bluetooth self-healing module is used for evaluating the link quality according to the link quality data in a data uploading process, dynamically switching an active link and a standby link according to a link quality evaluation result, and carrying out Bluetooth task transmission; the remote control module is used for carrying out data reduction by adopting a multilayer decryption mechanism and a mixed format analysis mechanism based on the encrypted Bluetooth task data, evaluating the operation state of the power distribution cabinet, generating a control instruction through a fuzzy logic control method according to an operation state evaluation result and executing the control instruction; through a dynamic link switching mechanism of the Bluetooth self-healing module, continuous and stable transmission of monitoring data of the power distribution cabinet is ensured.

Description

Technical Field

[0001] The present invention relates to the field of remote monitoring technology, in particular to a remote monitoring system for a power distribution cabinet based on wireless communication. Background Art

[0002] Remote monitoring systems for power distribution cabinets are a crucial component of the Industrial Internet of Things (IIoT). Existing technologies primarily utilize wired or wireless communication for data collection and transmission. In wireless communication solutions, monitoring systems based on short-range wireless protocols such as Bluetooth and Zigbee have developed a standardized architecture, typically consisting of a sensor network, a data transmission module, and a remote monitoring platform. The sensor network collects electrical parameters such as voltage and current, as well as environmental parameters such as temperature and humidity, and transmits these to a monitoring center via wireless communication modules. Existing systems typically utilize a fixed sampling frequency and a single communication link, combined with basic encryption algorithms to ensure data security. These systems can meet basic monitoring needs in typical industrial environments.

[0003] Existing technical solutions still have room for improvement in their adaptability to complex industrial environments. Communication link management lacks dynamic optimization capabilities, and fixed routing mechanisms are difficult to adapt to complex and changing industrial electromagnetic environments. Data transmission solutions also fail to fully consider the timeliness of different types of data, and the real-time performance of critical data transmission needs to be improved. Summary of the Invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a remote monitoring system for distribution cabinets based on wireless communication to solve the problems of lack of dynamic optimization capability of link management and timeliness differences of different types of data transmission.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: The present invention provides a remote monitoring system for a power distribution cabinet based on wireless communication, which includes a power distribution cabinet and a data acquisition module for collecting electrical parameters and environmental parameters of the power distribution cabinet and performing standardization processing to generate a standardized data packet; a data caching module for caching and prioritizing the standardized data packet using a priority sorting method to generate an upload data packet; a communication scheduling module for receiving the upload data packet and, in combination with the real-time network status, performing link evaluation through an upload link optimization method, and selecting an initial upload link and uploading data based on the actual link condition and the priority of the uploaded data; a Bluetooth self-healing module for evaluating the link quality according to the link quality data during the data upload process, dynamically switching the active link and the backup link according to the link quality evaluation result, and performing Bluetooth task transmission; a data upload module for encapsulating the Bluetooth task data in the Bluetooth task using a differential encapsulation method of parameter type, and generating encrypted Bluetooth task data through multi-layer encryption; a remote control module for restoring the data based on the encrypted Bluetooth task data using a multi-layer decryption mechanism and a differential parsing mechanism of parameter type, and evaluating the operating status of the power distribution cabinet, and generating and executing control instructions through a fuzzy logic control method according to the evaluation result.

[0007] As a preferred solution of the remote monitoring system for power distribution cabinet based on wireless communication of the present invention, the electrical parameters include voltage, current, power factor, frequency and circuit breaker status; Environmental parameters include temperature, humidity, vibration, smoke concentration, and cabinet door open / close status; The electrical parameters and environmental parameters are standardized by the dynamic quantile normalization method; An event-triggered dynamic time alignment method is used to establish characteristic mapping relationships between electrical parameters, and a standardized data package is generated by combining it with a dynamic benchmark calibration method.

[0008] As a preferred solution of the remote monitoring system for power distribution cabinets based on wireless communication described in the present invention, wherein: a priority sorting method is adopted to cache and prioritize standardized data packets to generate upload data packets, the steps are as follows: A hybrid cache architecture combining a ring storage structure and a first-in-first-out queue is used to cache standardized data packets. Based on the statistical analysis of historical operation data, a space threshold is defined. When the cache space reaches the space threshold, a hierarchical compression strategy is used to compress the cached standardized data packets. Through the dynamic priority algorithm of data time entropy, the upload priority score of the data in the compressed standardized data packet is calculated, the upload order of the data in the standardized data packet is prioritized from high to low, and an upload data packet is generated.

[0009] As a preferred solution of the remote monitoring system for power distribution cabinets based on wireless communication described in the present invention, wherein: receiving uploaded data packets and combining them with real-time network conditions, performing link evaluation through an upload link optimization method, and selecting an initial upload link and uploading data according to actual link conditions and the priority of uploaded data, the steps are as follows: Monitor network status in real time and collect real-time link quality data; real-time link quality data includes signal strength, transmission delay and packet loss rate; According to the network status and real-time link quality data, the link transmission mass spectrum and link quality comprehensive score of each link are generated, and the upload link with the highest link quality comprehensive score is selected as the active link for data upload.

[0010] As a preferred solution of the remote monitoring system for power distribution cabinets based on wireless communication described in the present invention, wherein: based on the link quality data during data upload, and evaluating the link quality, dynamically switching the active link and the backup link according to the evaluation results, and performing Bluetooth task transmission, the steps are as follows: Sort the links from high to low based on their comprehensive link quality scores and select the top N links as backup links. Based on the historical switching records, a switching threshold is set and compared with the comprehensive link quality score of the current link. The dual-link pre-activation method and fast switching protocol are used to dynamically switch the active link and the backup link, and Bluetooth task transmission is performed.

[0011] As a preferred solution of the remote monitoring system for distribution cabinets based on wireless communication described in the present invention, the dual-link pre-activation method maintains the standby connection state of the active link and the backup link by periodically sending low-power link maintenance pulses and link quality detection packets. When the comprehensive link quality score of the active link is lower than the switching threshold, the backup link is activated and the data transmission channel is switched.

[0012] As a preferred solution of the remote monitoring system of the power distribution cabinet based on wireless communication described in the present invention, the method includes: a differentiated encapsulation method of parameter types, the steps of which are as follows: electrical parameters are divided into blocks according to time length to generate electrical parameter blocks; environmental parameters are divided into blocks according to time intervals to generate environmental parameter blocks; the electrical parameter blocks are converted into binary streams, and the environmental parameters are converted into text format; a type identifier and a priority label are added to each parameter block; and different types of data blocks are combined and encrypted according to a preset ratio.

[0013] As a preferred solution of the distribution cabinet remote monitoring system based on wireless communication described in the present invention, the following steps are adopted: decrypting the uploaded encrypted Bluetooth task data; identifying the type identifier to distinguish between the electrical parameter block and the environmental parameter block; using binary stream parsing for the electrical parameter block and text parsing for the environmental parameter block.

[0014] As a preferred scheme of the power distribution cabinet remote monitoring system based on wireless communication, wherein: the encrypted Bluetooth task data is restored by using a multi-layer decryption mechanism and a parameter type differentiated analysis mechanism, and the running state of the power distribution cabinet is evaluated, control instructions are generated and executed according to the evaluation results by using a fuzzy logic control method, and the steps are as follows: The electrical parameters and environmental parameters in the restored data of the encrypted Bluetooth task data are compared and analyzed in real time, the running state is evaluated by using a multi-dimensional evaluation method of dynamic coupling coefficients, and the evaluation results are generated, including the running state, the abnormal type code and the risk level; According to the evaluation results, a fuzzy rule base is established by using a fuzzy logic control method; The fuzzy rule base establishes a nonlinear correspondence between the evaluation score set and the control instruction set, and according to the nonlinear correspondence, the control instructions are generated and executed by using a centroid decision algorithm.

[0015] As a preferred scheme of the power distribution cabinet remote monitoring system based on wireless communication, wherein: the centroid decision algorithm generates the weighted geometric center coordinates of the control instruction set by using a geometric center positioning method of probability density distribution, maps the weighted geometric center coordinates of the control instruction set to a preset control instruction interval, and generates the corresponding control instructions.

[0016] The present application has the following advantages: through the dynamic link switching mechanism of the Bluetooth self-healing module, the gradient boosting decision tree scoring algorithm is used to comprehensively score the signal strength, transmission delay and packet loss rate, the intelligent switching of the primary and backup links is realized by combining the dual-link pre-activation method, and the continuous and stable transmission of the power distribution cabinet monitoring data in the industrial environment is ensured; through the fuzzy logic control method of the remote control module, the fuzzy rule base is established based on the fusion evaluation of electrical parameters and environmental parameters, and the fuzzy reasoning result is converted into accurate control instructions by using the centroid decision algorithm, thereby realizing the fine regulation and control of the running state of the power distribution cabinet. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0018] Fig. 1 Flowchart of the power distribution cabinet remote monitoring system based on wireless communication.

[0019] Fig. 2 Flowchart of data acquisition and data caching.

[0020] Fig. 3 This is the workflow diagram of the Bluetooth self-healing module.

[0021] Fig. 4 This is the workflow diagram of the remote control module. DETAILED DESCRIPTION

[0022] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0023] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0024] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0025] Reference Figs. 1-4 , is an embodiment of the present invention, which provides a remote monitoring system for a power distribution cabinet based on wireless communication, comprising the following steps: including a power distribution cabinet, further comprising, The data acquisition module collects the electrical parameters and environmental parameters of the power distribution cabinet and performs standardization processing to generate standardized data packets; Electrical parameters include voltage, current, power factor, frequency, and circuit breaker status; It should be noted that the electrical parameters are collected in real time through the voltage transformer, current transformer, power factor transmitter, frequency acquisition module and circuit breaker status sensor installed in the distribution cabinet; among them, when the circuit breaker status is closed, the real-time collected data is 1; when the circuit breaker status is open, the real-time collected data is 0.

[0026] Environmental parameters include temperature, humidity, vibration, smoke concentration, and cabinet door open / close status; It should be noted that environmental parameters are collected in real time through the digital temperature and humidity sensor, three-axis vibration sensor, photoelectric smoke detector and magnetic door switch sensor installed in the distribution cabinet. When the cabinet door switch state is closed, the real-time collected data is 1; when the cabinet door switch state is open, the real-time collected data is 0.

[0027] Normalize electrical and environmental parameters through dynamic quantile normalization; It should be noted that the specific process is: calculate the historical mean and historical standard deviation of each parameter, and then convert each parameter value collected in real time into a standard score. The expression is: ; in, is the standard score, is the parameter value collected in real time, is the historical mean of the parameter value collected in real time, is the historical standard deviation of the parameter values ​​collected in real time; Standardize all parameters of the current expression to achieve unified quantitative expression of parameters of different dimensions.

[0028] An event-triggered dynamic time alignment method is used to establish characteristic mapping relationships between electrical parameters, and a standardized data package is generated by combining it with a dynamic benchmark calibration method.

[0029] Specifically, the waveforms of various electrical parameters are monitored in real time to identify characteristic events, which include voltage surges or dips and current mutations. Based on the first characteristic event, the timing of other electrical parameters is dynamically offset compensated. With the characteristic event as the center, an electrical parameter data window of ±5 cycles is captured. The characteristic quantities of each parameter in the alignment window are calculated, which include amplitude, phase and harmonics. The numerical relationship and waveform characteristics of voltage, current and power factor at the same time are quantified. A characteristic correlation matrix of voltage, current and power factor in the event window is established, and the historical mean and historical standard deviation of each electrical parameter are updated in real time in combination with the dynamic benchmark calibration method. At the same time, the weight of historical data is dynamically adjusted through the exponential weighting method of the attenuation coefficient. At the same time, the standardized environmental parameters and processed electrical parameters are integrated and packaged according to the preset data format, and finally a standardized data packet including all electrical parameters and environmental parameters is generated.

[0030] The data cache module uses a priority sorting method to cache and prioritize standardized data packets and generate upload data packets; A hybrid cache architecture combining a ring storage structure and a first-in-first-out (FIFO) queue is used to cache standardized data packets. It should be noted that the ring storage structure stores the latest received standardized data packets in a fixed capacity in a circular manner, and automatically overwrites the earliest stored data when the storage space is full; at the same time, the FIFO queue strictly manages the dequeue order according to the timing of data packet arrival, and the newly generated standardized data packets are written to the tail of the queue in sequence, and the data packets are extracted from the head of the queue in sequence according to the FIFO rules to generate upload data packets, ensuring the timing integrity of data transmission.

[0031] Based on the statistical analysis of historical operation data, a space threshold is defined. When the cache space reaches the space threshold, a hierarchical compression strategy is used to compress the cached standardized data packets. It should be noted that based on the statistical analysis of historical operating data, the space threshold is defined by calculating the historical average occupancy peak. When the cache space occupancy is close to the space threshold, the system automatically executes a hierarchical compression strategy: lossy compression is implemented for historical data, precision-optimized compression is implemented for electrical parameters and environmental parameters collected in real time, and lossless compression is implemented for characteristic events, thereby optimizing the efficiency of storage space utilization while ensuring data integrity.

[0032] Through the dynamic priority algorithm of data time entropy, the upload priority score of the data in the compressed standardized data packet is calculated, the upload order of the data in the standardized data packet is prioritized from high to low, and an upload data packet is generated.

[0033] It should be noted that the dynamic priority algorithm of data time entropy is used to calculate the time entropy value based on the data generation timestamp. The expression is: ; in, is the time-dependent entropy value; is the basic entropy value; is the data aging interval; is the parameter half-life; is the abnormal weighting coefficient; The shorter the aging interval of data is, the higher the aging entropy value is, which reflects the freshness of the data and ensures that the latest key data is processed first; the feature weights are preset according to the parameter type, electrical parameters are given higher weights, environmental parameters are given basic weights, and abnormal records are given the highest weights; the data in the compressed standardized data packet is then divided into three categories for processing: historical data retains key features, electrical parameters and environmental parameters collected in real time maintain the main accuracy, and characteristic events are completely retained; through the synergistic effect of the aging entropy value and the feature weight, the aging entropy value and the feature weight are fused in a fixed ratio to generate a priority score of 0-100 points. Data with a score of 90 points or above is marked as urgent transmission, 80-89 points are high priority, 60-79 points are ordinary level, and below 60 points are delayed transmission.

[0034] The upload priority score of each data packet is obtained, the upload order of the data in the standardized data packet is prioritized in descending order of the upload priority score, and an upload data packet is generated.

[0035] The communication scheduling module receives the uploaded data packets and, based on the real-time network status, performs link evaluation using the upload link optimization method. It then selects the initial upload link and uploads the data based on the actual link conditions and the priority of the uploaded data. Real-time monitoring of network status and collecting real-time link quality data; the real-time link quality data includes signal strength, transmission delay and packet loss rate; Specifically, the signal strength, transmission delay and packet loss rate of each link are collected by a special probe.

[0036] According to the network status and real-time link quality data, the link transmission mass spectrum of each link and the comprehensive link quality score are generated, and the upload link with the highest comprehensive link quality score is selected as the active link for data upload.

[0037] It should be noted that according to the network status and real-time link quality data, the link transmission mass spectrum of each link and the comprehensive link quality score are generated, and the expression is:

[0038] Among them, is the comprehensive link quality score; is the signal strength, is the transmission delay, is the packet loss rate, is the available bandwidth, , , , is the dynamic weight coefficient, is the link for calculating the link transmission mass spectrum; The upload link with the highest comprehensive link quality score is selected as the active link for data upload.

[0039] Bluetooth self-healing module, during data upload, according to link quality data, evaluate link quality, according to the evaluation results, dynamically switch active link and standby link, and perform Bluetooth task transmission; According to the comprehensive link quality score, the links are sorted from high to low, and the top N links are selected as standby links, and the score changes of each standby link are monitored in real time; Based on the historical switching record, set the switching threshold, and compare it with the comprehensive link quality score of the current link, use the double-link pre-activation method and fast switching protocol to dynamically switch the active link and standby link, and perform Bluetooth task transmission.

[0040] It should be noted that based on the historical switching records, the 90th percentile value of the historical link on-link quality score data is calculated, and a safety margin of 5 points is added to set the switching threshold; the 90th percentile value refers to the 90th cutoff value after the historical link quality scores are sorted by numerical size; the comprehensive link quality score of the current active link is compared with the switching threshold and the backup link score in real time. When the comprehensive link quality score of the active link is continuously lower than the switching threshold for more than 3 seconds, and the comprehensive link quality score of at least one backup link is higher than the active link by more than 10 points, the switching is triggered, and the dual-link pre-activation method is used to pre-establish the physical layer connection of the backup link and synchronize the transmission parameters. At the same time, the active link and the backup link are seamlessly switched at the MAC layer based on the fast switching protocol. After the switching is completed, the Bluetooth task transmission inherits the original link data packet sequence number and resumes transmission from the last unconfirmed packet, while maintaining short parallel transmission of the new and old links until it is confirmed that all data packets have been delivered, to ensure seamless service connection.

[0041] The dual-link pre-activation method maintains the active link and the backup link in a standby connection state by periodically sending low-power link maintenance pulses and link quality detection packets. When the comprehensive link quality score of the active link is lower than the switching threshold, the backup link is activated and the data transmission channel is switched.

[0042] The low-power link maintenance pulse is a periodic micro-power signal used in the Bluetooth self-healing module to maintain the standby state of the backup link; The link quality detection package periodically sends link quality data to calculate the comprehensive link quality score in real time, providing a basis for link switching decisions.

[0043] It should be noted that the dual-link pre-activation method maintains the backup link in a standby connection state with a μA current by periodically sending low-power link maintenance pulses and simplified link quality detection packets of 20ms in length. When the active link score is lower than the threshold, the backup link is activated to the full-function transmission mode within 30ms and switches to the backup link. During the switching process, maintenance pulses are continuously sent until the new link transmission is stable.

[0044] The data upload module uses a differentiated encapsulation method based on parameter types to encapsulate the Bluetooth task data of the Bluetooth task and generates encrypted Bluetooth task data through multi-layer encryption; Bluetooth task data includes electrical parameters and environmental parameters. Electrical parameters are divided into blocks according to duration to generate electrical parameter blocks; environmental parameters are divided into blocks according to time intervals to generate environmental parameter blocks. Electrical parameter blocks are converted into binary streams, and environmental parameters are converted into text format. Type identification and priority tags are added to each parameter block. Different types of data blocks are combined and encrypted according to preset ratios.

[0045] It should be noted that electrical parameters are segmented into 100ms time windows to generate equal-length data blocks, and environmental parameters are grouped into fixed intervals of 1 second; Electrical parameters are encoded in big-endian binary format. Each parameter value is converted to a 4-byte floating-point number and packaged in a binary structure. Environmental parameters are converted to JSON text format, retaining 1 decimal place of precision. Add type identification and priority tags to each data block. 0xA1 indicates electrical parameter block, and 0xB1 indicates environmental parameter block. The preset ratio is determined by analyzing the actual proportion of electrical and environmental parameters in historical transmission data, and the electrical parameter blocks and environmental parameter blocks are staggered at a fixed ratio of 4:1; The electrical parameter block is encrypted using AES-256-CBC, and the environmental parameter block is encrypted using RSA-OAEP; Generates encapsulated and encrypted Bluetooth task data.

[0046] The remote control module uses a multi-layer decryption mechanism and a differentiated parsing mechanism of parameter types to restore data based on encrypted Bluetooth task data, and evaluates the operating status of the distribution cabinet. According to the operating status evaluation results, it generates and executes control instructions through the fuzzy logic control method.

[0047] It should be noted that the uploaded encrypted Bluetooth task data will be decrypted; the type identifier will be identified to distinguish between the electrical parameter block and the environmental parameter block; binary stream parsing will be used for the electrical parameter block and text parsing will be used for the environmental parameter block.

[0048] Decrypt the encrypted Bluetooth task data uploaded to the remote receiver in layers. The electrical parameter block is decrypted using AES-256-CBC, and the environmental parameter block is decrypted using RSA-OAEP. Parse type identification to distinguish electrical parameter blocks from environmental parameter blocks; The electrical parameter block uses binary stream parsing to align timestamps at 100ms intervals and reconstruct the time series. The environmental parameter block uses text parsing to supplement missing data points at 1-second intervals. Restore encrypted Bluetooth task data.

[0049] Perform real-time comparative analysis of electrical and environmental parameters in the decrypted and restored Bluetooth mission data, evaluate the operating status using a multi-dimensional evaluation method for dynamic coupling coefficients, and generate evaluation results that include operating status, anomaly type code, and risk level. It should be noted that the electrical parameters and environmental parameters are cross-compared in real time, the linkage characteristics between the parameters are analyzed, and the linkage strength between the electrical parameters and the environmental parameters is calculated in real time through the multi-dimensional evaluation method of the dynamic coupling coefficient. The evaluation results are generated in combination with the fixed grading standards.

[0050] According to the evaluation results, the evaluation scores are integrated to establish an evaluation score set, a control instruction set is preset inside the remote control module, and a fuzzy rule base is established through the fuzzy logic control method; the fuzzy rule base establishes a nonlinear correspondence between the evaluation score set and the control instruction set, and according to the said nonlinear correspondence, the centroid decision algorithm is used to generate and execute control instructions.

[0051] It should be noted that, through fuzzy logic control, the evaluation score set is matched with the preset control strategy in an "if-then" rule matching process, constructing a fuzzy rule base containing the membership relationship between the evaluation score set as input and the control instruction set as output. The input evaluation score set is converted into a fuzzy quantity through a membership function, and then matched with the fuzzy set of output control instructions in an "if-then" conditional matching process. A centroid decision algorithm is used to locate the geometric center of the probability density distribution. Based on the probability of control instruction use, a weighted average of the control instruction probabilities is calculated, with the weights determined by the importance of each control instruction. The weighted geometric center coordinates of the control instruction set are then generated and mapped to a preset control instruction range. The corresponding control instructions are generated and executed. The preset instruction range is divided into a fixed threshold range for the control instructions based on the distribution of historical control instructions.

[0052] In summary, the present invention adopts: the dynamic link switching mechanism of the Bluetooth self-healing module, adopts the gradient boosting decision tree scoring algorithm to comprehensively score the signal strength, transmission delay and packet loss rate, and combines the dual-link pre-activation method to realize the intelligent switching of the primary and standby links, thereby ensuring the continuous and stable transmission of the distribution cabinet monitoring data in the industrial environment; through the fuzzy logic control method of the remote control module, a fuzzy rule base is established based on the fusion evaluation of electrical parameters and environmental parameters, and the centroid decision algorithm is used to convert the fuzzy reasoning results into precise control instructions, thereby realizing the refined regulation of the operating status of the distribution cabinet.

[0053] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A remote monitoring system for a power distribution cabinet based on wireless communication, comprising a power distribution cabinet, characterized in that: Also includes, The data acquisition module collects the electrical parameters and environmental parameters of the power distribution cabinet and performs standardization processing to generate standardized data packets; The data cache module uses a priority sorting method to cache and prioritize standardized data packets and generate upload data packets; The communication scheduling module receives the uploaded data packets and evaluates the links based on the real-time network status through the upload link optimization method. It selects the initial upload link and uploads the data based on the actual link conditions and the priority of the uploaded data. The Bluetooth self-healing module evaluates link quality based on link quality data during data upload and dynamically switches between the active link and the backup link based on the link quality evaluation results to perform Bluetooth task transmission. The data upload module uses a differentiated encapsulation method based on parameter types to encapsulate the Bluetooth task data in the Bluetooth task and generates encrypted Bluetooth task data through multi-layer encryption; The remote control module uses a multi-layer decryption mechanism and a differentiated parsing mechanism of parameter types to restore data based on encrypted Bluetooth task data, and evaluates the operating status of the distribution cabinet. According to the operating status evaluation results, it generates and executes control instructions through the fuzzy logic control method.

2. The remote monitoring system for power distribution cabinets based on wireless communication according to claim 1, characterized in that: The electrical parameters include voltage, current, power factor, frequency and circuit breaker status; The environmental parameters include temperature, humidity, vibration, smoke concentration and cabinet door switch status; The electrical parameters and environmental parameters are standardized by the dynamic quantile normalization method; An event-triggered dynamic time alignment method is used to establish characteristic mapping relationships between electrical parameters, and a standardized data package is generated by combining it with a dynamic benchmark calibration method.

3. The remote monitoring system for power distribution cabinets based on wireless communication according to claim 2, characterized in that: The method of using priority sorting is used to cache and prioritize the standardized data packets and generate upload data packets. The steps are as follows: A hybrid cache architecture combining a ring storage structure and a first-in-first-out queue is used to cache standardized data packets. Based on the statistical analysis of historical operation data, a space threshold is defined. When the cache space reaches the space threshold, a hierarchical compression strategy is used to compress the cached standardized data packets. Through the dynamic priority algorithm of data time entropy, the upload priority score of the data in the compressed standardized data packet is calculated, the upload order of the data in the standardized data packet is prioritized from high to low, and an upload data packet is generated.

4. The remote monitoring system for power distribution cabinets based on wireless communication according to claim 3, characterized in that: The receiving of the upload data packet and combining it with the real-time network status, the link evaluation is performed through the upload link optimization method, and the initial upload link is selected and the data is uploaded according to the actual link conditions and the priority of the uploaded data. The steps are as follows: Monitor network status in real time and collect real-time link quality data; the real-time link quality data includes signal strength, transmission delay and packet loss rate; According to the network status and real-time link quality data, the link transmission mass spectrum and link quality comprehensive score of each link are generated, and the upload link with the highest link quality comprehensive score is selected as the active link for data upload.

5. The remote monitoring system for power distribution cabinets based on wireless communication according to claim 4, characterized in that: During the data upload process, based on the link quality data, the link quality is evaluated and the active link and the backup link are dynamically switched according to the evaluation results to perform Bluetooth task transmission. The steps are as follows: Sort the links from high to low based on their comprehensive link quality scores and select the top N links as backup links. Based on the historical switching records, a switching threshold is set and compared with the comprehensive link quality score of the current link. The dual-link pre-activation method and fast switching protocol are used to dynamically switch the active link and the backup link, and Bluetooth task transmission is performed.

6. The remote monitoring system for power distribution cabinets based on wireless communication according to claim 5, characterized in that: The dual-link pre-activation method maintains the active link and the backup link in a standby connection state by periodically sending low-power link maintenance pulses and link quality detection packets. When the comprehensive link quality score of the active link is lower than the switching threshold, the backup link is activated and the data transmission channel is switched.

7. The remote monitoring system for power distribution cabinets based on wireless communication according to claim 6, characterized in that: The differentiated encapsulation method of the parameter type has the following steps: The electrical parameters are divided into blocks according to the duration to generate electrical parameter blocks; The environmental parameters are divided into blocks according to time intervals to generate environmental parameter blocks; Convert electrical parameter blocks into binary streams and environmental parameters into text format; Add type identification and priority labels to each parameter block; Different types of data blocks are combined and encrypted in a preset ratio.

8. The remote monitoring system for power distribution cabinets based on wireless communication according to claim 7, characterized in that: The parameter type differentiation parsing mechanism has the following steps: Decrypt the uploaded encrypted Bluetooth task data; Identify type identification and distinguish between electrical parameter blocks and environmental parameter blocks; Binary stream parsing is used for electrical parameter blocks, and text parsing is used for environmental parameter blocks.

9. The remote monitoring system for power distribution cabinets based on wireless communication according to claim 8, characterized in that: Based on the encrypted Bluetooth task data, a multi-layer decryption mechanism and a differentiated parsing mechanism based on parameter types are used to restore the data and evaluate the operating status of the distribution cabinet. Based on the evaluation results, control instructions are generated and executed using the fuzzy logic control method. The steps are as follows: Perform real-time comparative analysis of electrical and environmental parameters in the restored encrypted Bluetooth task data, evaluate the operating status using a multi-dimensional evaluation method for dynamic coupling coefficients, and generate evaluation results that include operating status, anomaly type code, and risk level. According to the evaluation results, a fuzzy rule base is established through fuzzy logic control method; The fuzzy rule base establishes a nonlinear correspondence between the evaluation score set and the control instruction set. According to the nonlinear correspondence, the centroid decision algorithm is used to generate and execute control instructions.

10. The remote monitoring system for power distribution cabinets based on wireless communication according to claim 9, characterized in that: The center of mass decision algorithm generates the geometric center coordinates of the control instruction set through the geometric center positioning method of probability density distribution, maps the geometric center coordinates of the control instruction set to a preset control instruction interval, and generates corresponding control instructions.

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