An intelligent power distribution cabinet system integrating beidou positioning and state monitoring

Abstract

The application relates to the technical field of power equipment monitoring, in particular to an intelligent power distribution cabinet system integrated with Beidou positioning and state monitoring. The system comprises a single Beidou positioning time-providing module, a state monitoring module, a data processing and fusion unit and a communication module. The core of the system is that the data processing and fusion unit is configured to dynamically detect displacement events of the power distribution cabinet based on real-time position information provided by the single Beidou module, and automatically trigger the adaptive switching of the monitoring strategy of the state monitoring module between a normal mode and an enhanced mode according to the displacement events; meanwhile, all data are uniformly fused in the time and space dimensions by using the Beidou time-providing signal. The application realizes the dynamic correlation monitoring of the position and the running state of the power distribution cabinet, solves the problem that the position information and the state data are isolated from each other and the monitoring strategy is rigid in the prior art, and improves the accuracy and reliability of intelligent operation and maintenance of the power distribution cabinet.

Description

Technical Field

[0001] This invention relates to the field of power equipment monitoring technology, and more specifically, to an intelligent power distribution cabinet system that integrates BeiDou positioning and status monitoring. Background Technology

[0002] As a critical node in the power distribution network, switchgear is widely distributed and operates in complex environments. Ensuring its safe and stable operation is crucial to the reliability of the entire power grid. With the deepening of smart grid construction, real-time monitoring of switchgear status and intelligent operation and maintenance management have become essential requirements for improving the operational efficiency and management level of the power system. Against this backdrop, the development of integrated and intelligent switchgear monitoring systems has significant practical implications.

[0003] Currently, existing power distribution cabinet monitoring technologies mostly employ separate approaches for condition monitoring and location positioning. Condition monitoring systems typically focus on collecting electrical parameters and environmental data, while positioning functions largely rely on commercial multi-mode satellite navigation systems. These two approaches are disconnected at the data processing level, failing to establish an effective internal connection. This results in the system's inability to detect power distribution cabinet displacement events, leading to a static and rigid monitoring strategy. For example, when a power distribution cabinet is moved due to engineering needs or emergency power supply, the risks of vibration and impact during transportation cannot be effectively monitored, and asset ledger information cannot be automatically updated after arriving at the new location. Furthermore, the time synchronization mechanisms of existing systems largely rely on internal device clocks, resulting in accumulated errors. This makes it difficult to accurately correlate and compare data from different devices over time, hindering the accuracy and efficiency of regional fault diagnosis and big data analysis. More importantly, in critical infrastructure sectors involving national welfare and national security, such as power, military, water conservancy, and meteorology, there are clear and mandatory requirements for the independent controllability of core technologies. While existing technologies commonly employ multi-source compatible positioning modules, which improve the availability of positioning signals, they still fundamentally rely on multiple signal sources, including foreign satellite navigation systems. This poses potential risks to data security, signal interference, and even disruption or misdirection during wartime. Consequently, they fail to meet the absolute security, reliability, and independence requirements for positioning data in critical national sectors. The BeiDou Navigation Satellite System, as my country's independently developed global satellite navigation system, provides a solid foundation and strategic guarantee for its specialized and dedicated applications in key sectors.

[0004] Therefore, the core issues facing the current technological system are: how to break through the current situation where location information and status monitoring data are independent of each other and achieve deep correlation between the two in the spatiotemporal dimension; how to enable the monitoring system to have context awareness capabilities and be able to autonomously adjust the monitoring strategy according to the displacement status of the power distribution cabinet; and how to build a unified spatiotemporal reference based on independent and controllable technologies (such as single Beidou positioning) to provide reliable support for the precise management of power distribution cabinets, full life cycle data traceability, and national strategic security. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide an intelligent power distribution cabinet system integrating BeiDou positioning and status monitoring to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an intelligent power distribution cabinet system integrating BeiDou positioning and status monitoring, comprising: The single Beidou positioning and timing module is configured to receive and process signals from the Beidou satellite navigation system only, without relying on any other global satellite navigation system. It is used to continuously obtain the real-time geographical location information of the power distribution cabinet and to provide a high-precision timing signal synchronized with Coordinated Universal Time as the highest priority time reference of the system. The status monitoring module is configured to monitor the internal electrical operating parameters and external environmental parameters of the power distribution cabinet. The data processing and fusion unit, which is communicatively connected to the single BeiDou positioning and timing module and the status monitoring module, is configured to perform the following operations: Based on the real-time geographic location information sequence, the displacement event of the power distribution cabinet is detected by calculating the rate of change of the location points; In response to the detection of the start of the displacement event, the system's monitoring strategy is automatically switched from a conventional monitoring mode suitable for stationary states to an enhanced monitoring mode suitable for moving states. In the enhanced monitoring mode, the data acquisition and processing priority of specific types of sensors in the status monitoring module is adjusted; The BeiDou timing signal is used first to assign a unified timestamp to all monitoring parameters, and the timestamp, real-time geographical location information, unique identifier of the power distribution cabinet, and processed operating status parameters are encapsulated into a comprehensive data packet with spatiotemporal correlation. The communication module is configured to transmit the integrated data packet to the remote monitoring center; The remote monitoring center is configured to receive and parse the comprehensive data packet, enabling real-time visualization of the power distribution cabinet on the electronic map, management of its movement trajectory, and multi-dimensional data retrieval and analysis based on geographical location and time.

[0007] Preferably, the status monitoring module includes a vibration sensor and a tilt sensor for sensing mechanical motion, and a temperature sensor, a humidity sensor, a current sensor, and a voltage sensor for monitoring electrical and environmental conditions; and the adjustment of the data acquisition and processing priority of specific types of sensors specifically involves: in the enhanced monitoring mode, increasing the sampling frequency of the vibration sensor and the tilt sensor to a range between 5Hz and 20Hz, while maintaining or reducing the sampling frequency of the temperature, humidity, current, and voltage sensors.

[0008] Preferably, in the enhanced monitoring mode, the data processing and fusion unit also performs real-time analysis on the data streams collected by the vibration sensor and the tilt sensor. If the monitored vibration acceleration continues to exceed the preset threshold range for more than 100ms, or the tilt angle deviates from the initial reference value by more than 3 degrees, it is immediately marked as a transportation anomaly event in the integrated data packet.

[0009] Preferably, the method of detecting displacement events by calculating the rate of change of location points specifically includes: acquiring geographical coordinates at a fixed frequency of 1Hz, calculating the planar displacement distance between consecutive coordinate points, and determining that a displacement event begins when the average displacement distance over 5 consecutive calculation cycles exceeds 10 meters or the instantaneous displacement rate exceeds 2m / s; and determining that a displacement event ends when the average displacement distance over 30 consecutive calculation cycles is less than 2 meters.

[0010] Preferably, the data processing and fusion unit is further configured to: automatically generate a transportation process health report after the displacement event is determined to have ended. The report statistically analyzes and lists the number, type, maximum amplitude, and specific location coordinates of all marked transportation anomalies during the entire displacement event.

[0011] Preferably, the remote monitoring center is configured to allow users to customize one or more polygonal or circular geofence areas and set entry or exit actions as legal or illegal; when the integrated data packet indicates that the power distribution cabinet has performed an illegal geofence action, the system automatically triggers a high-level alarm and records the event in the asset history of the power distribution cabinet.

[0012] Preferably, the movement trajectory management function of the remote monitoring center is based on the location information in a series of time-sorted comprehensive data packets, and reproduces the historical movement route of the power distribution cabinet in the form of a continuous path on the electronic map, and supports interactive clicking on the trajectory line to view all operating status parameters of the corresponding time at that location point.

[0013] Preferably, in the conventional monitoring mode, the sampling frequency of the temperature sensor is set to 0.1Hz to 1Hz, and the sampling frequency of the current and voltage sensors is set to 1Hz to 10Hz; after switching to the enhanced monitoring mode, the sampling frequency of the temperature sensor is reduced to below 0.1Hz, and the sampling frequency of the current and voltage sensors is reduced to 0.2Hz to 2Hz.

[0014] Preferably, the communication module integrates a data compression and encryption submodule; the data compression submodule uses the LZ77 algorithm to perform lossless compression on the integrated data packet; the encryption submodule uses the AES-256 algorithm to encrypt the compressed data block, and the key is updated periodically through a secure channel.

[0015] Preferably, the system further includes a local data storage module, which adopts a ring buffer structure and is configured with a storage capacity of 2GB to 20GB. It is used to cyclically store newly generated comprehensive data packets and record the interruption timestamp when communication is interrupted. After communication is restored, it automatically retransmits all cached data packets to the remote monitoring center starting from the earliest interruption timestamp.

[0016] The technical effects and advantages of this invention are as follows: 1. It has achieved secure, autonomous, precise, and reliable end-to-end monitoring and asset management. Compared to existing technologies, this invention achieves adaptive switching of monitoring strategies by establishing a dynamic correlation model between location information and status monitoring parameters. The system continuously analyzes the real-time location sequence provided by a single BeiDou module. When the detected rate of position change exceeds a threshold, it automatically determines that the power distribution cabinet has entered a moving state and immediately triggers the status monitoring module to switch from normal mode to enhanced mode. In enhanced mode, the system increases the frequency and priority of collecting and analyzing mechanical motion parameters such as vibration and tilt, thereby accurately capturing potential risks during transportation, such as excessive vibration or abnormal tilt. This approach closely integrates monitoring behavior with the actual physical state of the power distribution cabinet, effectively overcoming the limitations of fixed threshold monitoring, improving the targeting and accuracy of status assessment, and providing technical assurance for the safety of assets during movement.

[0017] 2. A unified and reliable spatiotemporal benchmark was constructed, improving the dimensionality and accuracy of data analysis. Compared to existing technologies, this invention optimizes system resource allocation and data value density by introducing a hierarchical data processing mechanism based on displacement events. In normal monitoring mode, the system collects electrical and environmental parameters at a standard frequency; once in motion mode, the sampling frequency of these parameters is temporarily reduced, while the main computing and communication resources are concentrated on processing high-frequency mechanical motion data. This strategy not only reduces the average power consumption of the system during non-critical periods and extends the backup power supply's runtime, but also ensures the integrity and real-time performance of core data during critical events. It achieves priority protection of the most important information under limited resource constraints, avoids data redundancy, improves the efficiency of data transmission and storage, and provides a high-value data foundation for subsequent fault analysis.

[0018] 3. System resource allocation has been optimized, enabling intelligent energy efficiency and data management. Compared to existing technologies, this invention constructs a unified spatiotemporal data framework by integrating high-precision timing signals provided by a single BeiDou system with geographic location information. The system assigns an absolute timestamp from BeiDou to each status data point and binds it to its corresponding latitude and longitude coordinates and device identification, forming a spatiotemporally synchronized comprehensive data packet. This provides a unified benchmark for massive amounts of monitoring data in both time and space dimensions. Based on this framework, remote monitoring platforms can accurately replay asset movement trajectories, implement intelligent alarms based on electronic fences, and perform data slicing analysis by geographical region and time window. This solves the problems of asynchronous time and location of multi-source data, providing a solid and consistent data foundation for macro-level operational decisions, regional status assessments, and full lifecycle asset management. Attached Figure Description

[0019] Figure 1 This is the overall system architecture and data flow diagram of the present invention.

[0020] Figure 2 This is a logic diagram of phase detection and mode switching in this invention.

[0021] Figure 3 This is a detailed process diagram of data processing and fusion according to the present invention.

[0022] Figure 4 This is a detailed process diagram of data processing and fusion according to the present invention. Detailed Implementation

[0023] 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.

[0024] Example 1 As attached Figures 1 to 4 The diagram illustrates an intelligent power distribution cabinet system integrating BeiDou positioning and status monitoring. The core of this system lies in constructing a closed-loop system capable of sensing its own location and status and intelligently adjusting its monitoring behavior accordingly.

[0025] Its basic architecture comprises several key components: a single BeiDou positioning and timing module that receives signals solely from the BeiDou Navigation Satellite System, providing real-time geographic location information with meter-level accuracy and high-precision timing signals; a status monitoring module that integrates multiple sensors to collect electrical, environmental, and mechanical physical parameters of the power distribution cabinet; a data processing and fusion unit, serving as the system's intelligent hub, responsible for performing location event judgment, monitoring strategy scheduling, and data spatiotemporal fusion; a communication module responsible for establishing a reliable data transmission link with the remote monitoring platform; and the remote monitoring platform itself, providing asset visualization, trajectory playback, and data analysis capabilities. These components work together to transform the power distribution cabinet from a static asset into an intelligent node with context-aware capabilities.

[0026] The system's time synchronization mechanism is the core of ensuring all data has a unified spatiotemporal reference. The data processing and fusion unit incorporates a dual-clock source architecture with "BeiDou priority." Upon power-up, the primary task is to lock onto and synchronize with the high-precision timing signal provided by the single BeiDou positioning and timing module, using it as the system's highest priority and most reliable absolute time reference. Simultaneously, the unit obtains network time from the Network Time Protocol (NTP) server via the communication module as an auxiliary clock source. When the BeiDou signal is stable and available, the system strictly uses the BeiDou timestamp and periodically compares it with network time for self-monitoring. When the BeiDou signal is temporarily lost due to entering a tunnel or encountering strong interference, the system automatically and seamlessly switches to network time to maintain timing continuity, and immediately resynchronizes to the BeiDou time base the moment the BeiDou signal is restored. This mechanism ensures that the system provides a unified, continuous, and highly reliable time reference under any operating conditions, laying the foundation for the spatiotemporal fusion of all subsequent data.

[0027] Furthermore, the condition monitoring module is specifically configured to include sensor units sensitive to mechanical physical conditions, and the system has the ability to dynamically adjust its sampling frequency based on displacement events. In a specific implementation, mechanical physical condition monitoring is accomplished through vibration sensors and tilt sensors. The vibration sensor is a triaxial accelerometer based on MEMS technology with a range of ±16g, capable of sensitively capturing impacts and vibrations during transportation; the tilt sensor is a dual-axis tilt sensor with a measurement range covering ±90°, used to monitor whether there are abnormal changes in the cabinet's posture.

[0028] When the system determines that the distribution cabinet is stationary, the sampling frequency of these sensors is set to 1Hz to maintain basic monitoring and reduce power consumption. Once the system detects that the distribution cabinet has begun to move, the data processing and fusion unit immediately increases the sampling frequency of the vibration and tilt sensors to 10Hz via internal commands. This strategy switching enables the system to capture transient mechanical stress events with high temporal resolution during the most vulnerable transportation phase of the distribution cabinet, providing high-fidelity data for assessing transportation safety and the stress levels borne by the internal structure of the equipment.

[0029] Furthermore, the selection, installation, and data processing mechanisms for vibration and tilt sensors have been refined. The vibration sensor specifically uses the LIS3DH model, with a resolution of 3.9mg, and is directly mounted on the main load-bearing structural frame inside the distribution cabinet to ensure good mechanical coupling and accurate transmission of cabinet vibration. The tilt sensor uses the SCL3300-D01 model, and its installation position ensures that the sensing axis is parallel to the cabinet's reference plane, thus directly reflecting the cabinet's tilt angle relative to the horizontal plane. These sensors are connected to the data processing and fusion unit via an I2C digital bus.

[0030] At the data processing level, the raw vibration signals collected are first passed through a digital bandpass filter (e.g., with a passband frequency of 0.5Hz to 50Hz) to remove high-frequency noise and DC offset interference, extracting the effective vibration information. Through this refined hardware selection, mechanical installation optimization, and signal preprocessing process, the collected mechanical physical parameters accurately and reliably reflect the true state of the distribution cabinet, providing a foundation for subsequent anomaly detection.

[0031] Furthermore, the system's automatic identification logic for displacement events is explicitly described. This function is implemented by a position event analysis algorithm running within the data processing and fusion unit. This algorithm obtains the latest latitude and longitude coordinates from a single BeiDou module at a 1-second interval. At any moment The core concept is to calculate the planar displacement distance between consecutive coordinate points. The distance calculation takes into account the Earth's curvature and is approximated using the Haversine formula: in, The average radius of the Earth , Latitude and longitude are measured in radians. Displacement rate. Then simply calculate as ,in Second.

[0032] The algorithm's judgment rule is: the system is initially in a "static" state. The average displacement distance calculated over five consecutive cycles... Exceeding 15 meters, or any instantaneous displacement rate When the speed exceeds 3 m / s, the system switches to "moving". While in "moving" state, if the average displacement distance over the subsequent 30 consecutive cycles... If the distance is less than 5 meters, the system status switches back to "stationary". This dual judgment mechanism based on sliding window averaging and instantaneous peak detection effectively smooths out the accidental fluctuations caused by single-point positioning errors and can react quickly to sudden rapid movements, thus achieving robust identification of the moving status of the distribution cabinet.

[0033] Furthermore, the system has the ability to automatically generate a transportation process health report after the displacement event ends. This function relies on an event log cache allocated in system memory. Throughout the entire displacement event, all data points collected by vibration and tilt sensors that exceed preset safety thresholds are marked and recorded in real time. For vibration data, the threshold is set when the absolute value of acceleration exceeds 2g; for tilt data, the threshold is set when the absolute value of the angle deviates from the initial calibration value by more than [a certain value]. The recorded information includes not only values ​​exceeding the limit. It also includes the timestamp of its occurrence. and corresponding geographic coordinates When the position event analysis algorithm determines that the displacement event has ended, the report generation routine is automatically triggered. This routine performs statistical analysis on all records in the buffer and calculates the total number of abnormal events. According to vibration exceeding the limit and tilting beyond the limit Perform categorized statistics to identify the maximum amplitude value in each category of events. and The report lists the locations of all anomalies. Finally, these statistics are formatted into a structured electronic document (such as JSON). This report provides operations personnel with a quantitative assessment of the quality of the transportation process, clearly indicating when, where, and to what extent the equipment was subjected to stress, guiding targeted unpacking inspections and preventative maintenance.

[0034] Furthermore, the remote monitoring platform implements intelligent area control based on electronic fences. The platform provides graphical tools that allow administrators to draw arbitrary polygonal or circular areas on a digital map, defining them as electronic fences. Each fence can be associated with one or more power distribution cabinet assets, and its entry and exit actions can be set to "permitted" or "prohibited." The rule engine running in the platform's background continuously monitors the data stream from the communication module. When the location coordinates of a power distribution cabinet are resolved... With a certain electronic fence area When the spatial relationship of a point changes (e.g., from outside the region to inside the region, or vice versa), the engine immediately calculates its spatial relationship. A commonly used point-in-polygon determination method is the ray casting method, which calculates the spatial relationship from the point... A horizontal ray emitted to the right and the polygon boundary The number of intersection points is determined. If the number of intersection points is odd, the point is inside the polygon; if it is even, it is outside the polygon. If a detected state change violates a preset rule (such as "Entry Prohibited"), the rule engine will immediately generate a high-level alarm event. This event will trigger a prominent notification on the platform interface, be recorded in the system's security audit log, and be automatically pushed to the preset responsible person via integrated messaging services (such as SMS and email). This mechanism enables automated and refined management of the geographical location of the power distribution cabinet, effectively preventing the risk of assets being illegally moved or accidentally entering dangerous areas.

[0035] Furthermore, the remote monitoring platform provides a spatiotemporal visualization function for the movement trajectory and status parameters. All received integrated data packets are persistently stored in a time-series database. When a user needs to view a specific distribution cabinet over a certain period of time... When tracking movement within a given time period, the platform first performs a database query to retrieve a sequence of all locations sorted by timestamp within that time period. Subsequently, the visualization engine calls the map service API to connect these discrete location points into a continuous path, which is then displayed over the electronic map. To achieve a smoother display, interpolation is sometimes performed on the discrete points on the client side, such as using Bézier curves. When the user interacts with the trajectory line, such as clicking on a point on the trajectory... (corresponding time) When this happens, the system will send an asynchronous request to the backend to query the... All running status parameters recorded at all times The query results are dynamically overlaid on the map in the form of an information window, and the displayed content may include... The design incorporates data such as vibration values, tilt angles, temperatures, and currents at specific moments. This design deeply integrates the history of location movement with the evolution of equipment operating status in a spatiotemporal dimension, providing users with a powerful retrospective analysis tool for analyzing equipment conditions at specific geographical locations or points in time.

[0036] Furthermore, the remote monitoring platform provides powerful bidirectional historical data tracing capabilities, enabling flexible cross-retrieval across time and space dimensions: Time-axis driven location query: Maintenance personnel can specify a precise start and end time range on the platform interface (e.g., "2023-10-27 09:00:00 to 2023-10-27 15:00:00"). The system will quickly retrieve and list all location records of the target distribution cabinet within this time period, and supports listing in chronological order or generating trajectory playback animation for this time period with one click, which is convenient for accurately reviewing the movement path and behavior within a specific time period.

[0037] Location-driven status retrieval: Users can directly select a polygonal or circular geographical area on an electronic map (such as the yard of a substation or a construction route). The platform will then perform a reverse database search, quickly listing all historical distribution cabinet assets that have been deployed or passed through this area. Users can further click on any distribution cabinet to view all historical status data records (such as temperature curves, current waveforms, event logs, etc.) during its stay at that specific location. This function greatly facilitates regional equipment health status surveys, correlation analysis of fault causes at specific locations, and the rationality assessment of asset deployment locations.

[0038] Furthermore, the system employs differentiated energy-saving strategies for monitoring electrical and environmental parameters during mobile operation. In addition to mechanical sensors, the condition monitoring module includes a digital temperature sensor for measuring busbar temperature, a capacitive humidity sensor for monitoring cabinet humidity, and Hall effect sensors and voltage divider circuits for acquiring incoming current and voltage. In the normal static monitoring mode, the sampling frequency of the temperature and humidity sensors is set to 0.2Hz, and the sampling frequency of the current and voltage sensors is set to 2Hz to balance data refresh rate and power consumption. However, when the system enters the mobile enhanced monitoring mode, the data processing and fusion unit dynamically adjusts the sampling strategies for these parameters. The sampling frequency of the temperature and humidity sensors is reduced to 0.02Hz, and the sampling frequency of the current and voltage sensors is reduced to 0.5Hz. The underlying logic is that during transportation, the distribution cabinet is usually in a power-off or unloaded state; its internal electrical heating and load changes are not the focus of monitoring, while mechanical safety is the primary concern. By actively reducing the sampling frequency of non-core parameters, the system's total power consumption during mobile operation is effectively reduced. This is important for scenarios relying on backup batteries for extended periods of operation and also helps alleviate the instantaneous data burden on communication links.

[0039] Furthermore, the communication module integrates data compression and encryption functions to optimize transmission. The data compression function employs the DEFLATE compression algorithm based on the LZ77 algorithm family. This algorithm achieves lossless compression by finding repeating string sequences in the data stream to be compressed (i.e., the composite data packet) and replacing these repeating sequences with shorter (distance, length) pairs. For a typical data packet containing location, status parameters, and timestamps, this algorithm typically achieves a compression rate of 40% to 60%. For encryption, the system uses the AES-256 symmetric encryption algorithm, with CTR as the operating mode.

[0040] This mode uses a unique counter sequence, which is encrypted and then XORed with the plaintext data to produce ciphertext. This avoids the need for data padding and is easily computed in parallel. A 256-bit key is required for encryption. During system deployment, data is injected through secure channels and supports subsequent remote updates via secure commands. This combination of compression and encryption effectively reduces data volume before transmission, saving on wireless communication traffic costs. Simultaneously, high-strength encryption ensures the confidentiality and tamper-proof nature of power monitoring data during transmission over public networks, meeting industry information security standards.

[0041] Furthermore, the system is equipped with a local data storage module as a data buffering mechanism in case of communication interruption. This module is implemented using an 8GB eMMC Flash memory chip and is logically organized as a circular buffer. The buffer management maintains two pointers: a write pointer and a write pointer. The read pointer points to the write position of the next data packet. Points to the position of the next data packet to be read (retransmitted). Its pointer movement and judgment logic follow a modulo operation. Operations ( (The number of data packets corresponding to the total buffer capacity). When When the buffer is full, the earliest data (located in...) is considered to be in the buffer. ) will be covered, and at the same time Move forward one position. The system continuously monitors the communication link status. When a network interruption is detected, newly generated composite data packets are no longer attempted to be sent, but are continuously written to the circular buffer of the local storage module.

[0042] At the same time, the system records the timestamp of the interruption starting. Once communication is restored, the system initiates the data retransmission process: it first locates the timestamp. The system identifies the position of the corresponding data packet in the buffer, and then, starting from that position, reads all buffered data packets sequentially and retransmits them to the remote monitoring platform via the communication module. After retransmission, the system clears the corresponding retransmission marker and resumes normal data flow transmission. This mechanism constructs a reliable data persistence and recovery layer, ensuring that the continuity and integrity of monitoring data are not affected in unstable network environments, providing underlying support for achieving complete data traceability.

[0043] To provide a more comprehensive demonstration of the system's working mechanism, an end-to-end explanation will be given using a mobile power distribution cabinet deployment scenario from a warehouse to a construction site. This power distribution cabinet integrates the aforementioned vibration, tilt, temperature, and current sensors. The data processing unit and a single BeiDou module are integrated within a protective enclosure, communicating with a cloud-based monitoring platform via a 4G network.

[0044] After the system is powered on, it initially operates in normal monitoring mode. When the power distribution cabinet is hoisted onto the transport vehicle in the warehouse, the coordinate sequence reported by the single Beidou module shows a rapid change in position. The position event analysis algorithm calculates the displacement sequence based on the Haversine formula, and if the continuous average displacement exceeds 15 meters, it immediately triggers a switch to "motion enhancement monitoring mode". Subsequently, the sampling rate of the vibration and tilt sensors increases to 10Hz, while the sampling rate of the temperature and humidity sensors decreases to 0.02Hz.

[0045] During transport, when the vehicle passes over uneven road sections, vibration sensors collect a series of high acceleration data. After bandpass filtering the raw signal, the data processing unit identifies a vibration event lasting approximately 180 milliseconds with a peak value of 3.5g. This event, along with its precise latitude and longitude coordinates at the time of occurrence, is immediately marked and temporarily stored in the event log cache.

[0046] Upon arrival at the designated location on the construction site, the power distribution cabinet's position stabilized. The location event analysis algorithm detected an average displacement of less than 5 meters over 30 consecutive cycles, determining the movement had ended, and the system automatically switched back to normal monitoring mode. Simultaneously, the report generation routine was invoked to statistically analyze all abnormal events cached throughout the transportation process, generating a JSON-formatted report containing the number of vibration exceedance events, their maximum amplitude, and their location.

[0047] The communication module transmits a complete data stream, including final location, mode switching records, event markers, and transportation reports, to the remote monitoring platform via a 4G network after LZ77 compression and AES-256 encryption. After decompressing the data, the platform automatically updates the distribution cabinet's location status on the asset map to "Online - Stationary." Maintenance personnel receive the transportation health report and, based on the location of abnormal vibrations indicated in the report, arrange for on-site personnel to conduct a targeted inspection of the cabinet's wiring tightness, thereby eliminating potential hazards before power is restored.

[0048] After receiving the transportation health report on the platform, the maintenance personnel did not limit themselves to the static report. They first used the platform's "time-axis driven location query" function to precisely slide the timeline to the moment the vibration event occurred, visually showing the vehicle traversing a rough road surface. Next, by clicking on the event marker on the trajectory line, a pop-up window appeared, displaying detailed high-frequency vibration data waveforms before and after that point in time. Simultaneously, the platform automatically performed a "location-driven status retrieval," indicating that this distribution cabinet was being deployed for the first time at this construction site location, and that no similar vibration anomalies had occurred at that location historically. By combining this cross-temporal and spatial information, the maintenance personnel quickly and accurately determined that the vibration was an isolated incident during transportation. Based on this, they arranged for on-site personnel to conduct a targeted inspection of the wiring tightness inside the cabinet, thus efficiently eliminating potential hazards before power was restored.

[0049] This scenario fully demonstrates how the system, through autonomous and controllable BeiDou positioning and timing, intelligent situational awareness and strategy switching, and combined with the platform's powerful two-way spatiotemporal traceability capabilities, ultimately achieves refined and intelligent management of the entire process of power distribution cabinets from transportation and deployment to operation, effectively improving the safety management and operation and maintenance efficiency of mobile power assets.

[0050] Finally, the following points should be noted: First, in the description of this application, it should be noted that, unless otherwise specified and limited, the terms "installation", "connection", and "linkage" should be interpreted broadly, and can be mechanical or electrical connections, or internal connections between two components, or direct connections. "Up", "down", "left", "right", etc. are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may change. Secondly: The accompanying drawings of the embodiments disclosed in this invention only involve the structures involved in the embodiments disclosed in this invention. Other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of this invention can be combined with each other. In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. 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. An intelligent power distribution cabinet system integrating BeiDou positioning and status monitoring, characterized in that, include: The Beidou positioning module is used to obtain the real-time geographical location information of the power distribution cabinet through the Beidou satellite navigation system. The real-time geographical location information reflects the absolute position of the power distribution cabinet as a whole in geographical space. The status monitoring module is used to monitor at least one operating status parameter of the power distribution cabinet; The data processing unit is communicatively connected to the Beidou positioning module and the status monitoring module. It is used to receive the location information and operating status parameters, and to perform real-time correlation analysis between the location information and the operating status parameters using a dynamic adaptive fusion algorithm. The dynamic adaptive fusion algorithm is configured to: use the displacement event of the entire power distribution cabinet detected by the Beidou positioning module as the trigger condition to establish a failure physical correlation model between the motion feature quantity of the displacement event and different types of operating status parameters; and based on the model, dynamically and differentially adjust the fusion weight allocation of each operating status parameter in the current comprehensive status assessment to generate a comprehensive data stream containing location and status information. This comprehensive data stream reflects the location-dependent state change pattern. A communication module, connected to the data processing unit, is used to transmit the integrated data stream to the remote monitoring platform; The data processing unit achieves collaborative processing of location and status data through the dynamic adaptive fusion algorithm, thereby autonomously optimizing monitoring output without external intervention.

2. The intelligent power distribution cabinet system integrating BeiDou positioning and status monitoring according to claim 1, characterized in that, The status monitoring module is configured to monitor multiple parameters among the temperature, humidity, current, and voltage parameters of the power distribution cabinet. The temperature parameter is acquired through a distributed thermistor, the humidity parameter through a capacitive humidity sensor, the current parameter through a non-intrusive current transformer, and the voltage parameter through a high-impedance voltage divider circuit. The status monitoring module converts the acquired parameters into digital signals and transmits them to the data processing unit through a serial communication interface. The sampling frequency is adjustable within the range of 1Hz to 10Hz to adapt to monitoring needs under different environmental conditions.

3. The intelligent power distribution cabinet system integrating BeiDou positioning and status monitoring according to claim 1, characterized in that, The data processing unit is configured to introduce a time series analysis model to smooth the running status parameters when executing the dynamic adaptive fusion algorithm, and dynamically adjust the fusion period of the status parameters based on the update frequency of the location information. The fusion period is variable in the range of 0.1s to 10s, and when the rate of change of the location information exceeds a preset threshold, the fusion period is automatically shortened to enhance real-time performance. The data processing unit also includes an anomaly detection submodule, which is used to identify outliers of the running status parameters through statistical methods and mark them as potential anomalies.

4. The intelligent power distribution cabinet system integrating BeiDou positioning and status monitoring according to claim 1, characterized in that, The communication module adopts a multi-mode wireless communication method, including at least two of GPRS, 4G and 5G mobile networks, and supports adaptive network switching function, automatically selecting the optimal communication path according to signal strength and bandwidth requirements. The communication module also integrates data compression and encryption protocols to compress the comprehensive data stream before transmission to reduce the amount of data, and uses a symmetric encryption algorithm to ensure the confidentiality and integrity of data transmission.

5. The intelligent power distribution cabinet system integrating BeiDou positioning and status monitoring according to claim 1, characterized in that, It also includes an intelligent alarm module connected to the data processing unit, which is used to trigger a graded alarm signal when the data processing unit detects a location-dependent state anomaly through a dynamic adaptive fusion algorithm. The graded alarm signal includes a low-level warning, a medium-level alarm, and a high-level emergency alarm. Each alarm corresponds to a different response mechanism, including local sound and light indication, SMS notification, and remote platform push. The alarm triggering conditions can be dynamically optimized based on historical data and learning algorithms.

6. The intelligent power distribution cabinet system integrating BeiDou positioning and status monitoring according to claim 1, characterized in that, The data processing unit also includes a circular buffer storage submodule, which is used to cyclically store historical location information, historical operating status parameters, and intermediate data during the fusion process. The storage capacity is configurable in the range of 2GB to 20GB and supports a data rolling update mechanism. When the storage space is insufficient, the oldest data is automatically overwritten. At the same time, the storage submodule provides a data indexing function to facilitate quick retrieval and export of monitoring records for a specific time period.

7. The intelligent power distribution cabinet system integrating BeiDou positioning and status monitoring according to claim 1, characterized in that, It also includes an adaptive power management module, which provides adjustable power supply for the Beidou positioning module, status monitoring module, data processing unit and communication module. The adaptive power management module supports a wide voltage input range and dynamically adjusts the output power according to the system load. It enters energy-saving mode during low load periods to extend the battery life of the backup battery. It also has a real-time power consumption monitoring function and feeds back the power consumption data to the data processing unit for fusion analysis via the data bus.

8. The intelligent power distribution cabinet system integrating BeiDou positioning and status monitoring according to claim 1, characterized in that, The data processing unit is configured to add a high-precision timestamp to each integrated data stream entry. The timestamp is synchronized with the timing signal of the BeiDou positioning module, and the accuracy is configurable within the range of 1ms to 1s. The timestamp, location information, and operating status parameters are associated and stored in a time-series database format to form a traceable monitoring sequence. The time-series database supports data slicing analysis by time window.

9. The intelligent power distribution cabinet system integrating BeiDou positioning and status monitoring according to claim 1, characterized in that, The remote monitoring platform includes a data receiving interface, a streaming data processing engine, and an interactive visualization interface. It is used to receive and parse the comprehensive data stream from the communication module in real time, and to perform real-time data aggregation and pattern recognition through the streaming data processing engine. At the same time, it displays location information and status parameters in the form of a heat map on the interactive visualization interface, and supports users to define custom query conditions and alarm rules.

10. The intelligent power distribution cabinet system integrating BeiDou positioning and status monitoring according to claim 1, characterized in that, The data processing unit is configured to implement a location-driven state prediction function based on a dynamic adaptive fusion algorithm. It uses historical location and state data to train a time series prediction model to predict the trend of operating state parameters in the future period, and fuses the prediction results with real-time data to generate a forward-looking comprehensive data stream. The stream is then periodically updated to the remote monitoring platform via a communication module for preventive maintenance decisions.

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