Remote monitoring method and system for explosion-proof distribution box

Abstract

The invention discloses a remote monitoring method and system for an explosion-proof distribution box, and the method comprises the steps: synchronously collecting an electrical operation parameter, an explosion-proof structure state parameter and an environment related parameter, carrying out the wavelet threshold noise reduction processing and coupling correction, improving the data precision, encrypting, adding a check code, and transmitting to a remote monitoring center through dual-mode transmission. And the remote monitoring center verifies the data integrity and decrypts the data, carries out graded early warning based on a preset threshold system and a parameter change rate, and sends a corresponding intervention instruction for abnormity of an early warning grade and above. All-dimensional monitoring is achieved, safety and accuracy of data transmission are guaranteed, risks are pre-judged in advance, remote risk control is achieved, the operation safety and operation and maintenance efficiency of the anti-explosion distribution box are improved, and the system is suitable for flammable and explosive dangerous places.

Description

Technical Field

[0001] This invention belongs to the field of explosion-proof distribution box monitoring technology, and relates to a remote monitoring method and system for explosion-proof distribution boxes. Background Technology

[0002] Explosion-proof distribution boxes are core electrical control equipment in flammable and explosive hazardous locations such as petrochemical plants and mines, and their operational stability directly affects production safety within these environments. To mitigate the risks of explosions and fires caused by electrical faults, the operational status of explosion-proof distribution boxes must be monitored in real time.

[0003] Existing remote monitoring methods for explosion-proof distribution boxes mostly focus on the acquisition of single electrical parameters. They mainly collect data such as internal temperature and output current through temperature sensors and current sensors, and then transmit the data to the remote monitoring terminal via a wireless module to achieve basic parameter feedback.

[0004] These methods have significant drawbacks. The monitoring dimensions are limited, failing to include explosion-proof structural parameters such as the gaps in explosion-proof sealing surfaces and the strain values ​​of the explosion-proof casing, thus hindering the timely detection of potential explosion-proof structural failures. The collected data is susceptible to environmental electromagnetic interference and vibration, and lacks targeted processing, resulting in insufficient data accuracy. The early warning mechanism relies solely on a single threshold, lacking parameter trend analysis, making it difficult to predict anomalies in advance. Data transmission lacks reliable encryption and verification mechanisms, making it prone to loss or tampering. After an anomaly occurs, only early warning information is provided; remote intervention is not available, requiring on-site handling by maintenance personnel, prolonging troubleshooting time and increasing operational risks.

[0005] In summary, existing methods are insufficient to meet the needs of comprehensive, high-precision early warning and safety management in hazardous locations, and a more comprehensive remote monitoring solution for explosion-proof distribution boxes is urgently needed. Summary of the Invention

[0006] To address the problems existing in the background technology, this invention proposes a remote monitoring method and system for explosion-proof distribution boxes.

[0007] The first aspect of this application provides a remote monitoring method for an explosion-proof distribution box, comprising: Simultaneously collect electrical operating parameters, explosion-proof structure status parameters, and environmental related parameters; The raw data is first processed by wavelet threshold denoising to remove interference, and then coupled and corrected by environmental correlation parameters. The processed data is encrypted and a verification code is added before it is sent to the remote monitoring center via dual-mode transmission. The remote monitoring center verifies data integrity and, after decryption, issues tiered early warnings based on a preset threshold system and parameter change rate. For any abnormalities at or above the warning level, send corresponding intervention commands to the explosion-proof distribution box.

[0008] Optionally, the logic of wavelet threshold denoising is as follows: when the absolute value of the original data value is greater than or equal to the denoising threshold, the result of the absolute value of the original data value minus the denoising threshold is output and the original sign is retained; when the absolute value of the original data value is less than the denoising threshold, zero is output; the denoising threshold is calculated by the standard deviation of the original data noise and the number of samples in a single group of collected data.

[0009] Optionally, the coupling correction includes current correction and sealing surface gap correction; the current correction logic is I′=I×[1-k1×(T-T0) / T0-k2×E / E0]; the sealing surface gap correction logic is d′=d×[1-k3×(H-H0) / H0], where I′ is the corrected current value, k1 is the temperature correction coefficient, k2 is the electromagnetic interference correction coefficient, T0 is the standard reference temperature of 25℃, and E0 is the standard reference electromagnetic interference intensity; d′ is the corrected sealing surface gap value, k3 is the humidity correction coefficient, H represents the current humidity value, and H0 is the standard reference humidity.

[0010] Optionally, the preset threshold system includes a safety threshold, a warning threshold, and a danger threshold, wherein the safety threshold is less than the warning threshold and the warning threshold is less than the danger threshold; the parameter change rate is calculated by dividing the difference between the parameter value at the current time and the parameter value at the time before the preset time by the time difference between the current time and the time before the preset time; the graded warning includes a safety level, a warning level, a danger level, and an emergency level.

[0011] Optionally, the intervention commands corresponding to the warning level and the danger level are parameter adjustment commands, including adjusting the cooling fan speed and the branch current limiting threshold; the intervention commands corresponding to the emergency level are emergency power-off commands and operation permission lock commands, and operation is restored through remote unlock commands after the fault is repaired.

[0012] A second aspect of this application provides a remote monitoring system for an explosion-proof distribution box, comprising: a multi-dimensional acquisition component, a data processing component, an encrypted transmission component, a remote monitoring center, and an intervention execution component; The multi-dimensional acquisition component is used to simultaneously acquire electrical operating parameters, explosion-proof structure status parameters, and environmental related parameters; The data processing component is used to perform wavelet threshold noise reduction and coupling correction on the raw data; The encrypted transmission component is used to encrypt the processed data, add a checksum, and send it via dual-mode transmission. The remote monitoring center is used to verify data integrity, decrypt data, and provide tiered early warnings based on a preset threshold system and parameter change rate. The intervention execution component is used to receive and execute intervention instructions sent by the remote monitoring center.

[0013] Optionally, the multi-dimensional acquisition components include an electrical parameter acquisition unit, an explosion-proof structural parameter acquisition unit, and an environmental parameter acquisition unit; the electrical parameter acquisition unit includes a current sensor, a voltage sensor, a power sensor, and an insulation resistance sensor; the explosion-proof structural parameter acquisition unit includes a displacement sensor, a strain sensor, and a vibration sensor; and the environmental parameter acquisition unit includes a temperature and humidity sensor and an electromagnetic interference sensor.

[0014] Optionally, the encrypted transmission component includes an encryption module, a checksum generation module, and a dual-mode transmission module; the encryption module adopts an advanced encryption standard 256-bit encryption algorithm; the checksum generation module adopts a cyclic redundancy check 32-bit algorithm; the dual-mode transmission module includes a fifth-generation mobile communication technology transmission submodule, a long-distance radio transmission technology transmission submodule, and a signal strength detection submodule, the signal strength detection submodule being used to trigger transmission mode switching.

[0015] Optionally, the remote monitoring center includes a data verification module, a decryption module, an analysis module, and an early warning module; the data verification module is used to verify data integrity through a checksum; the decryption module uses an advanced encryption standard 256-bit decryption algorithm; the analysis module is used to calculate the rate of parameter change and compare it with a preset threshold system; and the early warning module is used to output tiered early warning information.

[0016] Optionally, the intervention execution component includes a parameter adjustment module, an emergency power-off module, and an access control module; the parameter adjustment module is used to execute cooling fan speed adjustment commands and branch current limiting threshold adjustment commands; the emergency power-off module is used to execute emergency power-off commands; and the access control module is used to execute operation access lock commands and remote unlock commands.

[0017] A third aspect of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the aforementioned remote monitoring method for an explosion-proof distribution box.

[0018] A fourth aspect of this application provides a computer-readable medium storing a computer program that, when executed by a processor, implements the above-described remote monitoring method for explosion-proof distribution boxes.

[0019] Compared with the prior art, the present invention has the following beneficial effects: This invention simultaneously collects electrical operating parameters, explosion-proof structural status parameters, and environmental related parameters to achieve full-dimensional monitoring. It overcomes the shortcomings of existing methods that only monitor one dimension, and can promptly detect potential risks such as explosion-proof structural failures, thus avoiding the omission of safety hazards.

[0020] By removing environmental interference through wavelet threshold denoising and combining it with environmental correlation parameters for coupling correction, the accuracy of data acquisition is effectively improved, providing reliable data support for subsequent analysis and early warning, and reducing the occurrence of anomaly misjudgment and missed judgment.

[0021] It employs a 256-bit encryption algorithm based on advanced encryption standards and a 32-bit cyclic redundancy check algorithm to ensure data transmission security. Combined with a dual-mode transmission method that integrates fifth-generation mobile communication technology and long-distance radio transmission technology, it ensures the confidentiality, integrity, and continuity of data transmission, preventing data loss or tampering.

[0022] Based on a preset threshold system and parameter change rate, a graded early warning system can predict abnormal trends in advance. Compared with the traditional single threshold early warning mode, it extends the early warning lead time and provides sufficient time for fault handling.

[0023] It provides remote intervention for anomalies at the warning level and above. The abnormal trend can be mitigated by adjusting parameters. In an emergency, it can remotely cut off power and lock operation permissions, reducing the operational risks for maintenance personnel in dangerous locations and reducing the probability of the fault escalating into a safety accident.

[0024] The overall solution enhances the safety and stability of explosion-proof distribution boxes, while optimizing the operation and maintenance process and improving efficiency. It is suitable for various flammable and explosive hazardous locations and has broad application value. Attached Figure Description

[0025] Figure 1 This is a flowchart of a remote monitoring method for an explosion-proof distribution box according to an embodiment of the present invention; Figure 2 This is a schematic diagram of a remote monitoring system for an explosion-proof distribution box according to an embodiment of the present invention. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] In one embodiment, such as Figure 1 As shown, a remote monitoring method for an explosion-proof distribution box is provided, which is then applied to... Figure 1 Taking China as an example, the following specific steps will be used: S10: Synchronously collect electrical operating parameters, explosion-proof structural status parameters, and environmental related parameters.

[0028] Specifically, wavelet thresholding denoising is a crucial step in removing interference from the acquired raw data. During the acquisition process, the raw data is subject to environmental electromagnetic interference and vibration interference, which can cause the data to deviate from the true value. Therefore, this processing method is needed to separate the valid data from the interference signals.

[0029] The noise reduction process begins by determining the noise reduction threshold, which is calculated using the standard deviation of the original data noise and the number of samples in a single data set. The standard deviation of the original data noise is a statistically derived value obtained by assessing the dispersion of interference signals in the original data, while the number of samples in a single data set is the number of specific data points of the same type of parameter acquired during a single acquisition process.

[0030] After calculating the noise reduction threshold, each original data value is evaluated. When the absolute value of the original data value is greater than or equal to the noise reduction threshold, the valid part of the data is retained. Specifically, the noise reduction threshold is subtracted from the absolute value of the original data value, and the sign of the original data value is retained to obtain the denoised value. When the absolute value of the original data value is less than the noise reduction threshold, it is determined that the data mainly consists of interference signals, and it is processed to zero to eliminate invalid interference.

[0031] Through the above logical processing, interference components in the original data can be effectively filtered out, and valid data reflecting the actual operating status of the explosion-proof distribution box can be retained, providing accurate basic data for subsequent coupling correction and data analysis.

[0032] S20: The collected raw data is first processed by wavelet threshold denoising to remove interference, and then coupled and corrected by environmental correlation parameters.

[0033] Specifically, the collected raw data includes electrical operating parameters, explosion-proof structural status parameters, and environmentally related parameters. These data are affected by environmental electromagnetic interference and vibration interference during the acquisition process. Changes in environmental temperature and humidity can also cause data deviations. Therefore, it is necessary to first remove interference through wavelet threshold noise reduction and then perform coupling correction in conjunction with environmentally related parameters.

[0034] The specific process of wavelet threshold denoising is as follows: First, the noise dispersion in the original data is statistically analyzed to obtain the standard deviation of the original data noise. The number of data points of the same type of parameter in a single acquisition is then determined as the sample size for a single acquisition. Next, the denoising threshold is calculated based on the original data noise standard deviation and the sample size for a single acquisition. For each original data value, if the absolute value of the original data is greater than or equal to the denoising threshold, the absolute value of the original data is subtracted from the denoising threshold, retaining the positive or negative sign of the original data value, to obtain the denoised value. If the absolute value of the original data is less than the denoising threshold, the data is considered invalid interference data and processed to zero, thus completing the interference removal.

[0035] Coupling correction is based on the noise-reduced electrical operating parameters and explosion-proof structural status parameters, combined with collected environmental correlation parameters for targeted correction. For current parameters, the difference between the collected temperature value and the standard reference temperature is first calculated. The ratio of this difference to the standard reference temperature is multiplied by a temperature correction factor to obtain the temperature effect correction term. Next, the ratio of the collected electromagnetic interference intensity value to the standard reference electromagnetic interference intensity is calculated. This ratio is multiplied by an electromagnetic interference correction factor to obtain the electromagnetic interference effect correction term. The sum of the temperature effect correction term and the electromagnetic interference effect correction term is subtracted from 1, and then multiplied by the original current value to obtain the corrected current value. For sealing surface gap parameters, the difference between the collected humidity value and the standard reference humidity is calculated. The ratio of this difference to the standard reference humidity is multiplied by a humidity correction factor to obtain the humidity effect correction term. Subtracting the humidity correction term from 1 and multiplying it by the original sealing surface gap value yields the corrected sealing surface gap value. Other electrical operating parameters and explosion-proof structural status parameters are adjusted according to the corresponding environmental influence factors. Specifically, the current correction is I′=I×[1-k1×(T-T0) / T0-k2×E / E0]; the sealing surface gap correction is d′=d×[1-k3×(H-H0) / H0], where I′ is the corrected current value, k1 is the temperature correction coefficient, k2 is the electromagnetic interference correction coefficient, T0 is the standard reference temperature of 25℃, and E0 is the standard reference electromagnetic interference intensity; d′ is the corrected sealing surface gap value, k3 is the humidity correction coefficient, H represents the current humidity value, and H0 is the standard reference humidity. Similar logic is used for coupling correction to ensure that all data accurately reflects the actual operating status of the explosion-proof distribution box.

[0036] The coupling correction includes temperature correction coefficient, electromagnetic interference correction coefficient, and humidity correction coefficient. The value range of each coefficient is obtained through multiple sets of working condition tests to ensure that the corrected data error meets the requirements for accurate monitoring under typical operating conditions in explosion-proof scenarios.

[0037] The temperature correction factor ranges from 0.002 to 0.005, the electromagnetic interference correction factor ranges from 0.001 to 0.003, and the humidity correction factor ranges from 0.003 to 0.006.

[0038] The calibration process for each coefficient is as follows: calibration was performed through 120 sets of tests covering typical operating conditions in explosion-proof scenarios. The test environment covered a temperature range from -20℃ to 60℃, encompassing the high-temperature environment of petrochemical workshops and the low-temperature environment of underground mines; humidity ranged from 30% to 90%, including dry mining environments and high-humidity chemical production areas; electromagnetic interference intensity ranged from 10μV / m to 100μV / m, covering the electromagnetic radiation intensity generated by industrial equipment during operation. Five explosion-proof distribution boxes of different models were selected as test objects. For each device, 10 sets of data were continuously collected under each operating condition. The true values ​​of the parameters were measured using standard metrology equipment, and the deviation between the original collected values ​​and the true values ​​was recorded.

[0039] The least squares method was used to fit the deviation data, with the constraint that the error of the corrected data should not exceed ±2%, to determine the optimal value range of each coefficient. For example, for the current parameter, under standard operating conditions of 25℃ temperature, 50% humidity, and 10μV / m electromagnetic interference intensity, fitting revealed that when the temperature correction coefficient was 0.003, the current correction error was minimized to ±1.2%, and the value range of the temperature correction coefficient was determined accordingly.

[0040] The specific values ​​for each coefficient are selected as follows for different application scenarios. In the petrochemical workshop scenario, the temperature correction coefficient is 0.003, the electromagnetic interference correction coefficient is 0.002, and the humidity correction coefficient is 0.004. In the underground mining scenario, considering the large temperature difference underground, the temperature correction coefficient is 0.004; the electromagnetic interference is strong due to the concentration of underground equipment, so the electromagnetic interference correction coefficient is 0.003; and the humidity is high underground, so the humidity correction coefficient is 0.005. Actual testing shows that with the above values, the current correction error is ±1.8%, and the sealing surface gap correction error is ±1.5%, both meeting the requirements for accurate monitoring.

[0041] S30: The processed data is encrypted and a verification code is added, and then sent to the remote monitoring center via dual-mode transmission.

[0042] Specifically, after data processing is completed, encryption, verification codes, and dual-mode transmission operations are required to ensure the security, integrity, and continuity of data during transmission.

[0043] The encryption operation employs the Advanced Encryption Standard (AES) 256-bit encryption algorithm. First, a random key with a length of 256 bits is generated. Using the processed data set as plaintext, the plaintext is encrypted using the AES 256-bit encryption algorithm to form the encrypted ciphertext. The encryption process strictly adheres to the algorithm specifications to ensure that the ciphertext cannot be cracked by unauthorized entities, thus guaranteeing the confidentiality of data transmission.

[0044] After encryption, a checksum is added, generated using a 32-bit Cyclic Redundancy Check (CRC) algorithm. The encrypted ciphertext undergoes a 32-bit CRC calculation to obtain the corresponding checksum. The ciphertext and checksum are then combined to form a complete transmission data frame. The checksum is used by the remote monitoring center to verify data integrity and prevent data loss or tampering during transmission.

[0045] The transmission employs a dual-mode transmission method combining fifth-generation mobile communication technology (5G) and long-distance radio transmission technology. Before transmission, the signal strength of the 5G signal is detected. If the signal strength reaches or exceeds a preset threshold, 5G is used preferentially for data transmission. If the 5G signal strength falls below the preset threshold, the transmission system automatically switches to long-distance radio transmission technology. The switching process is rapid and does not cause data transmission interruption. Transmitted data frames are sent in real-time to the remote monitoring center using the selected transmission technology, ensuring stable data transmission in hazardous locations and providing reliable support for subsequent data analysis and early warning.

[0046] The preset threshold for the signal strength of fifth-generation mobile communication technology is -85 dBmW, which was determined through signal coverage tests in three typical hazardous scenarios. The test scenarios include chemical workshops, underground mines, and oil and gas field stations. Twenty test points were set up at different locations in each scenario, including areas near equipment, edge areas, and signal-shielded areas.

[0047] Signal strength and data transmission stability of fifth-generation mobile communication technology were recorded at various test points, and data transmission interruption time and success rate were statistically analyzed under different signal strengths. Test results showed that when the signal strength was above -85 dBmW, the data transmission interruption time was less than 0.1 seconds, and the success rate was above 99.8%; when the signal strength was below -85 dBmW, the interruption time significantly increased, and the success rate dropped below 95%. Based on this, -85 dBmW was determined as the switching threshold. At this threshold, automatic switching to long-distance radio transmission technology can ensure that the data transmission interruption time does not exceed 1 second, and the success rate is not less than 99.5%.

[0048] S40: After the remote monitoring center verifies the data integrity and decrypts it, it issues graded early warnings based on a preset threshold system and parameter change rate.

[0049] S50: For abnormalities at the warning level or above, send corresponding intervention instructions to the explosion-proof distribution box.

[0050] Specifically, after receiving the transmitted data frame, the remote monitoring center first performs data integrity verification. The verification uses a 32-bit Cyclic Redundancy Check (CRC) algorithm, recalculating the received ciphertext to obtain a new checksum. This newly generated checksum is compared with the checksum carried in the transmitted data frame. If they match perfectly, it confirms that the data has not been lost or tampered with during transmission, and the data is deemed complete and valid. If they do not match, it indicates a data anomaly, and the remote monitoring center immediately sends a data anomaly signal to the encrypted transmission component, triggering a data retransmission mechanism until a complete and valid data frame is received.

[0051] After successful data verification, the decryption process is initiated. Using the Advanced Encryption Standard (AES) 256-bit decryption algorithm corresponding to the encryption process, and employing the 256-bit random key generated during encryption, the ciphertext is reversed to reconstruct the complete data set after noise reduction and coupling correction, providing accurate data support for subsequent analysis and early warning work.

[0052] The preset threshold system is the core basis for graded early warning. For each type of electrical operating parameter and explosion-proof structural status parameter, safety thresholds, warning thresholds, and danger thresholds are set respectively. The three thresholds follow the logical relationship that the safety threshold is less than the warning threshold and the warning threshold is less than the danger threshold. Their specific values ​​are determined through calibration by multiple sets of operating condition tests based on the rated operating parameters of the explosion-proof distribution box, the explosion-proof structural design standards, and the safety specifications of the application scenario.

[0053] The parameter change rate is calculated with a fixed period of 1 hour. The remote monitoring center extracts the target parameter value at the current moment and the same parameter value recorded at a preset time, and calculates the difference between the two values. At the same time, the time interval between the current moment and the moment before the preset time is determined, and the parameter value difference is divided by the time interval to obtain the parameter's change rate within 1 hour.

[0054] The tiered early warning system is implemented by comprehensively judging the parameter value's position within a threshold range and its rate of change. When the parameter value is within the safe threshold range and the rate of change does not exceed a fixed percentage per hour of the safe threshold, it is classified as a safe level; the remote monitoring center only displays a normal operation indicator and does not trigger additional early warning actions. When the parameter value is between the safe threshold and the early warning threshold, or when the rate of change exceeds a fixed percentage per hour of the safe threshold but does not exceed another fixed percentage, it is classified as an early warning level. When the parameter value is between the early warning threshold and the danger threshold, or when the rate of change exceeds another fixed percentage per hour of the safe threshold, it is classified as a danger level, and early warning information is simultaneously pushed to the mobile terminals of maintenance personnel. When the parameter value reaches or exceeds the danger threshold, it is classified as an emergency level; early warning information is simultaneously pushed to the mobile terminals of maintenance personnel and the scenario safety management center, clearly indicating the specific installation location of the explosion-proof distribution box and the type of abnormal parameter. The fixed ratio mentioned in this invention is a quantitative judgment standard set for the correlation between the parameter change rate and the safety threshold. Its function is to combine the threshold range of the parameter value to achieve accurate definition of graded early warning. All fixed ratios are obtained through multiple sets of hazardous scenario working condition tests and are adapted to the operating characteristics and safety management requirements of explosion-proof distribution boxes.

[0055] The specific definitions are as follows: The first fixed percentage is 2% of the safety threshold per hour. When the parameter change rate does not exceed this percentage, it indicates that the parameter change is gradual and the operation is stable, corresponding to the safety level determination. The second fixed percentage is 5% of the safety threshold per hour. When the parameter change rate exceeds the first fixed percentage but does not exceed the second fixed percentage, it indicates that the parameter has a slow abnormal change trend. Although it has not reached the warning threshold range, an early warning is required, corresponding to the warning level determination. When the parameter change rate exceeds the second fixed percentage, it indicates that the parameter is changing abnormally rapidly, and the possibility of risk spread is high, corresponding to the danger level determination.

[0056] The fixed ratio is set based on the rated operating parameters of the explosion-proof distribution box, the explosion-proof structural tolerance limit, and the safety control requirements of hazardous scenarios. Through more than 100 sets of operating condition tests covering different environmental temperatures and humidity, electromagnetic interference intensity, and load fluctuations, the critical value of the rate of abnormal parameter changes is statistically analyzed, and 80% of the critical value is taken as the final fixed ratio. This ensures that the judgment standard is both stringent and practical, avoids false warnings due to short-term parameter fluctuations, and does not overlook potential rapid abnormal risks.

[0057] For abnormal situations at the warning level or above, the remote monitoring center sends corresponding intervention commands to the explosion-proof distribution box. The intervention commands for warning and danger levels are parameter adjustment commands, specifically including adjusting the cooling fan speed and adjusting the branch current limiting threshold, depending on the type of abnormal parameter. The intervention commands for emergency levels are emergency power-off commands and operation permission lock commands. After the remote monitoring center sends the commands, the explosion-proof distribution box immediately cuts off the main power supply, stops electrical output, and simultaneously locks local operation permissions to prevent unauthorized personnel from causing safety risks through misoperation. Only after maintenance personnel have investigated and repaired the fault on-site, and then send a remote unlock command through the remote monitoring center, can the explosion-proof distribution box return to normal operation.

[0058] Taking an explosion-proof distribution box in a mine as an example, the safety threshold for its branch current is set to 0-25 amps, the warning threshold to 25-30 amps, and the danger threshold to 30 amps. At a certain moment, the remote monitoring center receives a corrected current value of 28 amps. Extracting the branch current value from a preset time ago (24 amps), with a time interval of one hour, the calculated current change rate is 4 amps per hour. This current value falls between the warning and danger thresholds, and the change rate exceeds the fixed percentage per hour of the safety threshold, thus classifying it as dangerous. The remote monitoring center immediately sends a branch current limiting threshold adjustment command to the explosion-proof distribution box, lowering the original current limiting threshold from 30 amps to 26 amps. After the command is transmitted to the intervention execution component of the explosion-proof distribution box, the component immediately performs the adjustment operation, and the branch current gradually drops back to 25 amps, effectively mitigating the abnormal current increase trend. After receiving the warning information, the maintenance personnel planned the underground operation route in advance based on the equipment location and the type of anomaly. They then carried special tools to the site for investigation and found that the abnormal current was caused by the aging of the branch line. The line was replaced in a timely manner.

[0059] The first fixed percentage in the tiered early warning system is 2% of the safety threshold per hour, and the second fixed percentage is 5% of the safety threshold per hour. These percentages are derived by statistically analyzing a large amount of abnormal operating data from multiple explosion-proof distribution boxes.

[0060] The parameter change rates of different types of faults were analyzed, including common faults such as line aging, wear of sealing surfaces, and overload operation. The critical rates of fault propagation were determined through analysis. For example, when the annual increase in sealing surface gap exceeds 0.1 mm, the explosion-proof structure is prone to failure, corresponding to a change rate of 0.01157 × 10⁻⁶ per hour. -3 The ratio is derived by combining the millimeter with the safety threshold of the sealing surface gap.

[0061] To balance the accuracy of early warnings with the risk of misjudgment, 80% of the critical rate is taken as a fixed percentage. The first fixed percentage is used to determine whether the parameter is in a stable operating state. When the parameter change rate does not exceed this percentage, it indicates that the parameter change is gradual. The second fixed percentage is used to distinguish between early warning levels and danger levels, so as to avoid false early warnings due to short-term parameter fluctuations, while also being able to promptly capture rapidly developing abnormal risks.

[0062] It is worth noting that, taking an explosion-proof distribution box with a rated current of 100A in a petrochemical setting as an example, the specific values ​​of the preset threshold system are as follows: The safe threshold for the current parameter is 0 to 30A, the warning threshold is 30 to 35A, and the danger threshold is 35A. The safe threshold for the sealing surface gap is 0 to 0.1 mm, the warning threshold is 0.1 to 0.2 mm, and the danger threshold is 0.2 mm.

[0063] The threshold system is based on the equipment's rated parameters, the explosion-proof structural tolerance limit, and industry safety standards. Referring to the requirements of GB3836.2-2021, "Explosive Atmospheres Part 2: Equipment Protected by Flameproof Enclosures," and considering the equipment's rated current of 100A, the threshold values ​​for each current parameter are determined. Based on the maximum permissible gap of 0.2 mm for the explosion-proof sealing surface, and considering the safety margin for sealing surface wear, the threshold values ​​for each sealing surface gap are determined.

[0064] Fault simulation tests have verified that this threshold division can provide early warning, giving maintenance personnel sufficient time to handle faults on-site and effectively preventing the fault from escalating and causing safety accidents.

[0065] This early warning and intervention mechanism, by comprehensively judging parameter values ​​and trends, achieves early identification and accurate warning of abnormal situations, significantly improving the lead time compared to traditional single-threshold early warning modes. Simultaneously, remote intervention commands can quickly mitigate abnormal trends, providing maintenance personnel with ample time for on-site handling and reducing the frequency of emergency operations in hazardous locations. Emergency power outage and access control functions directly block the path of fault escalation, effectively reducing the probability of safety accidents such as explosions and fires, and significantly improving the operational safety and maintenance convenience of explosion-proof distribution boxes in hazardous locations.

[0066] This invention focuses on the goal of prioritizing explosion-proof safety, and constructs a complete closed loop of multi-dimensional data collection, precise processing, safe transmission, intelligent early warning, and remote intervention. The various technical means are mutually dependent and supportive, forming an inseparable organic whole.

[0067] In this invention, multi-dimensional data acquisition is the foundation of the entire collaborative system. The explosion risk of explosion-proof distribution boxes may originate from electrical faults or from failure of the explosion-proof structure. Therefore, it is necessary to simultaneously collect electrical operating parameters, explosion-proof structural status parameters, and environmentally relevant parameters. Among the explosion-proof structural status parameters, the sealing surface gap is sensitive to environmental humidity; among the electrical operating parameters, the current is easily affected by electromagnetic interference; and environmentally relevant parameters directly reflect the intensity of these interference factors. The lack of any one of these parameters will lead to a loss of focus in subsequent processing or early warning, either failing to detect hidden risks of explosion-proof structural failure or failing to accurately determine the true state of the electrical parameters.

[0068] In this invention, the data processing and acquisition stages are directly coupled. The acquired raw data contains electromagnetic interference and vibration interference signals. Directly performing environmental coupling correction would cause environmental factors to overlap with the interference signals, making accurate compensation impossible. Therefore, wavelet threshold denoising is first used to remove interference, providing a clean data foundation for environmental coupling correction and preventing interference data from causing the compensation coefficients to fail. Environmental coupling correction then targets the acquired environmental parameters, accurately compensating for the effects of temperature on current and humidity on the sealing surface gap. Both processes strictly adhere to the order of denoising first and then correction, ensuring that the final output data closely matches the actual operating state of the equipment.

[0069] In this invention, the secure transmission process is adapted to the application requirements of precise data. Among the processed precise data, the shell strain value in the explosion-proof structural status parameters and the overload data in the electrical parameters are all emergency safety data, requiring priority to ensure the continuity and confidentiality of transmission. A dual-mode transmission method combining fifth-generation mobile communication technology and long-distance radio transmission technology is adopted. Automatic switching is achieved through a preset signal strength threshold, ensuring the high-speed advantage of fifth-generation mobile communication technology in areas with good signal, and ensuring uninterrupted data transmission through long-distance radio transmission technology in areas with weak signal. Simultaneously, a 256-bit encryption algorithm using advanced encryption standards prevents data tampering, and a 32-bit cyclic redundancy check algorithm verifies data integrity. If encryption or verification steps are missing during transmission, precise data will be distorted, and subsequent early warning and intervention operations will lack reliable basis.

[0070] In this invention, the intelligent early warning system relies on accurate data and secure transmission. The calculation of parameter change rates must be based on accurate data after noise reduction and correction. Using data containing interference or without correction can lead to misjudgments of parameter change trends. The preset threshold system, including safety thresholds, early warning thresholds, and danger thresholds, is set in conjunction with the explosion-proof structural tolerance limits, rated parameters of electrical equipment, and industry safety standards. Only when the data transmission process is complete and tamper-free can the accuracy of the early warning level determination be ensured, avoiding misjudging danger levels as early warning levels or missing abnormal signals. The accuracy of the early warning results directly determines the effectiveness of remote intervention; erroneous early warnings can lead to untimely intervention commands or misoperations.

[0071] In this invention, the remote intervention process is precisely matched with the early warning level. Parameter adjustment commands for early warning and hazard levels must be issued based on the specific anomaly type determined by the precise early warning. For example, adjusting the cooling fan speed for abnormal temperature or adjusting the branch current limiting threshold for abnormal current ensures that the intervention operation addresses the problem specifically. Emergency power-off commands and operation permission lock commands corresponding to the emergency level rely on continuously transmitted emergency warning signals; interruption of transmission would miss the optimal opportunity to prevent the fault from escalating. After the intervention command is executed, the explosion-proof distribution box will send the execution feedback data back to the remote monitoring center, providing data support for subsequent parameter adjustment threshold calibration and forming a complete closed-loop control system.

[0072] In one embodiment, such as Figure 2 As shown, a remote monitoring system for explosion-proof distribution boxes is provided. This remote monitoring system corresponds one-to-one with the remote monitoring method for explosion-proof distribution boxes in the above embodiments. The remote monitoring system for explosion-proof distribution boxes includes: a multi-dimensional acquisition component, a data processing component, an encrypted transmission component, a remote monitoring center, and an intervention execution component. Detailed descriptions of each functional module are as follows: The multi-dimensional acquisition component is used to simultaneously acquire electrical operating parameters, explosion-proof structure status parameters, and environmental related parameters; The data processing component is used to perform wavelet threshold noise reduction and coupling correction on the raw data; The encrypted transmission component is used to encrypt the processed data, add a checksum, and send it via dual-mode transmission. The remote monitoring center is used to verify data integrity, decrypt data, and provide tiered early warnings based on a preset threshold system and parameter change rate. The intervention execution component is used to receive and execute intervention instructions sent by the remote monitoring center.

[0073] In this invention, the encrypted transmission component includes an encryption module, a checksum generation module, and a dual-mode transmission module; the encryption module adopts an Advanced Encryption Standard 256-bit encryption algorithm; the checksum generation module adopts a Cyclic Redundancy Check 32-bit algorithm; the dual-mode transmission module includes a fifth-generation mobile communication technology transmission submodule, a long-distance radio transmission technology transmission submodule, and a signal strength detection submodule, the signal strength detection submodule being used to trigger transmission mode switching.

[0074] In this invention, the remote monitoring center includes a data verification module, a decryption module, an analysis module, and an early warning module; the data verification module is used to verify data integrity through a check code; the decryption module adopts an advanced encryption standard 256-bit decryption algorithm; the analysis module is used to calculate the parameter change rate and compare it with a preset threshold system; and the early warning module is used to output graded early warning information.

[0075] In this invention, the intervention execution component includes a parameter adjustment module, an emergency power-off module, and an access control module; the parameter adjustment module is used to execute cooling fan speed adjustment commands and branch current limiting threshold adjustment commands; the emergency power-off module is used to execute emergency power-off commands; and the access control module is used to execute operation access locking commands and remote unlocking commands.

[0076] Specific limitations regarding the remote monitoring system for explosion-proof distribution boxes can be found in the above description of the remote monitoring methods for explosion-proof distribution boxes, and will not be repeated here. Each module in the aforementioned remote monitoring system for explosion-proof distribution boxes 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 corresponding operations of each module.

[0077] 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, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0078] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A remote monitoring method of an explosion-proof distribution box, characterized in that, The method comprises the following steps: Synchronous acquisition of electrical operation parameters, explosion-proof structure state parameters and environment-related parameters; The collected raw data is first processed by wavelet threshold denoising to remove interference, and then coupled correction is performed in combination with the environment-related parameters; The processed data is encrypted and a check code is added, and then transmitted to the remote monitoring center through a dual-mode transmission method; The remote monitoring center verifies the data integrity, decrypts the data, and performs hierarchical early warning based on a preset threshold system and parameter change rate; For abnormality of the warning level and above, the corresponding intervention instruction is sent to the explosion-proof distribution box.

2. The method for remote monitoring of an explosion-proof distribution box according to claim 1, characterized in that, The logic of wavelet threshold denoising processing is: when the absolute value of the original data value is greater than or equal to the denoising threshold, the result of the original data value absolute value minus the denoising threshold is output and the original sign is retained; when the absolute value of the original data value is less than the denoising threshold, zero is output; The denoising threshold is calculated by the standard deviation of the noise of the original data and the number of samples of a single set of collected data.

3. The method for remote monitoring of an explosion-proof distribution box according to claim 1, characterized in that, Coupled correction includes current correction and sealing surface gap correction; The current correction logic is I'=I×[1-k1×(T-T0) / T0-k2×E / E0]; the sealing surface gap correction logic is d'=d×[1-k3×(H-H0) / H0], I' is the corrected current value, k1 is the temperature correction coefficient, k2 is the electromagnetic interference correction coefficient, T0 is the standard reference temperature 25℃, E0 is the standard reference electromagnetic interference intensity; d' is the corrected sealing surface gap value, k3 is the humidity correction coefficient, H represents the current humidity value, H0 is the standard reference humidity.

4. The method for remote monitoring of an explosion-proof distribution box of claim 1, wherein, The preset threshold system includes a safety threshold, a warning threshold, and a danger threshold, and the safety threshold is less than the warning threshold, and the warning threshold is less than the danger threshold; the parameter change rate is calculated by the difference between the current time parameter value and the parameter value at a preset time before, divided by the time difference between the current time and the time before the preset time; hierarchical early warning includes safety level, warning level, danger level and emergency level.

5. The method for remote monitoring of an explosion-proof distribution box according to claim 4, characterized in that, The intervention instruction corresponding to the warning level and the danger level is a parameter adjustment instruction, including adjusting the speed of the cooling fan and the branch current limiting threshold; The intervention instruction corresponding to the emergency level is an emergency power-off instruction and an operation permission locking instruction, and the remote unlocking instruction is used to restore operation after fault repair. The method for realizing the remote monitoring method of any one of claims 1 to 5 comprises a multi-dimensional acquisition component, a data processing component, an encryption transmission component, a remote monitoring center and an intervention execution component; 6. A remote monitoring system for an explosion-proof distribution box, characterized in that, The multi-dimensional acquisition component is used for synchronous acquisition of electrical operation parameters, explosion-proof structure state parameters and environment-related parameters; The data processing component is used for wavelet threshold denoising processing and coupled correction of raw data; The encryption transmission component is used for encrypting the processed data, adding a check code, and transmitting through a dual-mode transmission method; The remote monitoring center is used for verifying data integrity, decrypting data, and performing hierarchical early warning based on a preset threshold system and parameter change rate; The intervention execution component is used for receiving and executing the intervention instruction sent by the remote monitoring center. ​ 7. The remote monitoring system of the explosion-proof distribution box according to claim 6, characterized in that, The multi-dimension acquisition assembly comprises an electrical parameter acquisition device, an anti-explosion structure parameter acquisition device and an environmental parameter acquisition device; the electrical parameter acquisition device comprises a current sensor, a voltage sensor, a power sensor and an insulation resistance sensor; the anti-explosion structure parameter acquisition device comprises a displacement sensor, a strain sensor and a vibration sensor; and the environmental parameter acquisition device comprises a temperature and humidity sensor and an electromagnetic interference sensor.

8. The remote monitoring system of the explosion-proof distribution box according to claim 6, characterized in that, The encrypted transmission assembly comprises an encryption module, a check code generation module and a dual-mode transmission module; the encryption module adopts a 256-bit encryption algorithm of the advanced encryption standard; the check code generation module adopts a 32-bit algorithm of the cyclic redundancy check; the dual-mode transmission module comprises a fifth-generation mobile communication technology transmission sub-module, a long-distance radio transmission technology transmission sub-module and a signal strength detection sub-module, and the signal strength detection sub-module is used for triggering transmission mode switching.

9. The remote monitoring system of the explosion-proof distribution box of claim 6, wherein, The remote monitoring center comprises a data verification module, a decryption module, an analysis module and a pre-warning module; the data verification module is used for verifying data integrity through a check code; the decryption module adopts a 256-bit decryption algorithm of the advanced encryption standard; the analysis module is used for calculating a parameter change rate and comparing with a preset threshold system; and the pre-warning module is used for outputting graded pre-warning information.

10. The remote monitoring system of the explosion-proof distribution box of claim 6, wherein, The intervention execution assembly comprises a parameter adjustment module, an emergency power-off module and a permission control module; the parameter adjustment module is used for executing a heat dissipation fan rotating speed adjustment instruction and a branch current current-limiting threshold adjustment instruction; the emergency power-off module is used for executing an emergency power-off instruction; and the permission control module is used for executing an operation permission locking instruction and a remote unlocking instruction.

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