A sound and light alarm system and method for preventing theft of a power distribution device

Abstract

The application discloses a power distribution equipment anti-theft sound-light alarm system and method, and relates to the technical field of safety protection, which comprises the following steps: collecting electromagnetic noise signals, flash drive rhythm signals and wireless communication time sequence signals of a power distribution equipment operation site, synchronously processing the electromagnetic noise signals, the flash drive rhythm signals and the wireless communication time sequence signals according to a unified time scale to generate synchronous observation data. Through multi-source signal synchronous collection and frequency correlation analysis, the application realizes real-time identification of electromagnetic interference resonance frequency points and phase shift, accurately locates noise sources and keeps communication stable. Through dynamic adjustment of time rhythm adjustment data, the flash drive signal is randomly micro-jittered, the communication process is breath-exclusion and slip dark window control, so that frequency resonance is inhibited, signal synchronization is restored and the anti-interference and real-time response capability of the alarm system are improved.

Description

Technical Field

[0001] This invention relates to the field of security protection technology, specifically to an audible and visual alarm system and method for preventing theft of power distribution equipment. Background Technology

[0002] Audible and visual alarms for power distribution equipment refer to a comprehensive alarm system that automatically triggers sound and light signals when power distribution equipment is illegally opened, vibrated, damaged, or subjected to abnormal environmental conditions. This system is triggered through sensor detection and control logic linkage. This method typically integrates data from multiple sensors, such as infrared sensors, vibration detectors, magnetic switch sensors, and temperature and humidity monitoring. Once the system detects abnormal intrusion or operation, it immediately activates a high-decibel buzzer and a bright flashing light to provide two-way warning from both near and far. The sound signal attracts the attention of those nearby and deters intrusion, while the light signal provides a visual warning in noisy environments or at night. This overall approach, through combined audio-visual triggering and multi-source detection linkage, constructs a real-time, intuitive, and easily deployable anti-theft alarm system for power distribution equipment, ensuring safe equipment operation and immediate response to abnormal events.

[0003] The existing technology has the following shortcomings:

[0004] Many existing audible and visual alarm systems for power distribution equipment use wireless communication for signal transmission. However, in high-frequency environments or under conditions of strong electromagnetic interference, the strobe drive circuit of the flashlight continuously generates pulsed electromagnetic waves. When its flash period resonates with the communication frequency band, it can easily disrupt signal synchronization within microseconds. This phenomenon not only causes clock drift in the communication module but also triggers short-term signal interruptions, resulting in delays, misalignments, or loss of alarm data packets. Consequently, although audible and visual alarms are triggered at the scene, the main control unit cannot receive the alarm information in a timely manner, leading to a disconnect between the monitoring interface and the actual situation. This can easily cause misjudgments or delays in emergency response, and in severe cases, can cause the entire burglar alarm system to fail during an intrusion incident.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide an audible and visual alarm system and method for preventing theft of power distribution equipment, so as to solve the problems in the background art mentioned above.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a method for audible and visual alarm for theft prevention of power distribution equipment, comprising the following steps:

[0008] Electromagnetic noise signals, flash drive rhythm signals, and wireless communication time series signals are collected from the power distribution equipment operation site. The electromagnetic noise signals, flash drive rhythm signals, and wireless communication time series signals are then processed synchronously according to a unified time scale to generate synchronous observation data, providing a time reference for subsequent frequency correlation analysis.

[0009] Frequency correlation analysis is performed based on synchronous observation data to extract the resonance frequency points and phase offset paths of the flash drive rhythm signal and the wireless communication time series signal, generating interference distribution data and providing frequency reference for interference source localization.

[0010] Based on the analysis of the instantaneous impact period using interference distribution data, the location of the electromagnetic noise source generated by the flash drive circuit is determined, and the loss-of-synchronization risk data is generated to provide a risk basis for communication synchronization adjustment.

[0011] By combining out-of-synchronization risk data to trace back the wireless communication time series signal, out-of-synchronization segments and alarm data misordered distribution are identified, and time rhythm adjustment data is generated to provide input parameters for the dynamic adjustment process.

[0012] The data is dynamically adjusted according to the time rhythm, so that the flash drive rhythm signal enters the random micro-jitter mode, the wireless communication process adopts a breathing mutual exclusion window, and a sliding dark window is inserted in the communication sequence to achieve frequency resonance suppression and signal synchronous recovery.

[0013] Preferably, the steps for generating synchronous observation data are as follows:

[0014] Electromagnetic noise signal acquisition is performed to monitor the changes in electromagnetic field in the space surrounding the power distribution equipment and on the surface of the internal conductive components. Transient pulse signals, electromagnetic radiation interference, conductor coupling interference and power frequency background noise are continuously recorded to form an electromagnetic noise dataset containing time, amplitude and frequency band distribution.

[0015] Perform flash drive rhythm signal acquisition, and record the start time, duration, drive pulse current amplitude and time distribution of the flash trigger signal at the output of the flash drive circuit;

[0016] Perform wireless communication time series signal acquisition, and record the data packet transmission time, carrier occupancy time, reception acknowledgment time, and signal interval duration;

[0017] Electromagnetic noise signals, flash-driven rhythm signals, and wireless communication time series signals are synchronized according to a unified time scale to establish a time index, maintain the continuity and alignment of the signals, and generate synchronized observation data containing time labels, signal type labels, and amplitude information.

[0018] Preferably, the steps for generating interference distribution data are as follows:

[0019] Perform frequency conversion and data segmentation processing to divide the electromagnetic noise signal, flash drive rhythm signal and wireless communication time series signal into multiple continuous segments according to time, ensuring that each signal segment is perfectly aligned on the time axis;

[0020] The frequency component extraction process converts the pulse start time, duration, and interval of the flash-driven rhythm signal into a frequency distribution, analyzes the transmission time, reception time, and carrier occupancy time of the wireless communication time series signal into frequency features, and extracts the energy distribution of the electromagnetic noise signal in different frequency bands.

[0021] Frequency correlation analysis is performed to compare the frequency distribution of the flash drive rhythm signal and the wireless communication time series signal within the same time period, determine the frequency overlap area as the resonance frequency point, and extract the phase shift path through phase change.

[0022] By integrating the results of frequency correlation analysis, interference distribution data is generated, and frequency overlap areas, resonant frequency durations, and phase shift paths are recorded to provide frequency references for interference source localization.

[0023] Preferably, when extracting the resonant frequency point and phase shift path, the frequency response of the flash drive rhythm signal and the wireless communication time series signal is compared in time. By detecting the degree of frequency overlap and phase change trend of the two signals in the same time period, the interference occurrence interval is determined, and the interference duration and phase shift amplitude are recorded synchronously in the interference distribution data to improve the accuracy of the frequency correlation results.

[0024] Preferably, the steps for generating out-of-synchronization risk data are as follows:

[0025] Perform time-series filtering of interference distribution data and identification of instantaneous impact periods; extract electromagnetic noise signal intensity changes by analyzing frequency resonance points and phase shift paths and establish a time-frequency correspondence table.

[0026] Perform propagation tracking and comparative analysis of electromagnetic noise signals, determine the propagation direction of the electromagnetic noise source based on the signal arrival time and energy differences at different monitoring locations, and determine whether it originates from the flash drive circuit.

[0027] Perform risk assessment and generate out-of-synchronization risk data by comparing the instantaneous impact period corresponding to the electromagnetic noise source with the wireless communication time series signal, and recording communication delay, retransmission and loss to generate out-of-synchronization risk data;

[0028] The system analyzes and extracts data on the risk of synchronization failure, identifies the period with the most severe interference based on the risk distribution, calculates the synchronization offset range, and generates a reference table for communication synchronization adjustment.

[0029] Preferably, the risk level of communication synchronization failure is determined by calculating the ratio of interference duration to communication timing drift time, and the risk weights of different interference periods are sorted according to the risk level. The communication delay and phase offset parameters of the highest risk period are extracted, and the compensation period and data retransmission interval in the communication synchronization adjustment reference table are optimized.

[0030] Preferably, the steps for generating time rhythm adjustment data are as follows:

[0031] Perform communication time series backtracking analysis, compare the transmission and reception times of communication signals segment by segment with the interference periods indicated by the out-of-synchronization risk data, mark the data packet offset time and locate the out-of-synchronization segment;

[0032] Perform analysis on out-of-synchronization segments and out-of-order data, compare the normal timing of the communication signal with the backtracking results, identify disordered data packets, and generate a list of out-of-order alarm data.

[0033] The execution time rhythm adjustment data generation calculates the transmission interval of each data packet based on the out-of-order distribution and out-of-synchronization segments, and adjusts the sending and receiving times to form time rhythm adjustment data;

[0034] The execution time rhythm adjustment data application uses the adjustment data as input to optimize the timing of communication signals and corrects the sending and receiving intervals of data packets in real time to restore communication synchronization.

[0035] Preferably, the dynamic adjustment steps for adjusting data according to time rhythm are as follows:

[0036] The random micro-jitter mode of the flash drive rhythm signal is activated, and the period of the flash drive signal is randomly offset according to the time rhythm adjustment data to avoid the flash drive signal and the wireless communication signal forming a fixed frequency ratio.

[0037] The communication signal transmission is controlled by a breathing-type mutual exclusion window. The communication transmission window is dynamically divided and the communication interval is adjusted according to the random changes of the flash drive signal, so that the communication process is staggered from the flash cycle in time.

[0038] Perform sliding dark window insertion. When a risk of resonance between the communication signal and the flash drive signal is detected, a blank time window is inserted into the communication timing to avoid peak interference periods through time offset.

[0039] The system performs real-time adjustments to the data, continuously optimizes the transmission and reception times of communication signals based on the adjustment results, monitors the signal transmission status, and dynamically corrects the timing to restore signal synchronization.

[0040] An audible and visual alarm system for theft prevention of power distribution equipment includes a signal synchronization acquisition module, a frequency correlation analysis module, an interference source location module, a timing revision analysis module, and a dynamic rhythm control module.

[0041] The signal synchronization acquisition module collects electromagnetic noise signals, flash drive rhythm signals, and wireless communication time series signals at the power distribution equipment operation site. It then synchronizes these signals according to a unified time scale to generate synchronized observation data, providing a time reference for subsequent frequency correlation analysis.

[0042] The frequency correlation analysis module performs frequency correlation analysis based on synchronous observation data, extracts the resonance frequency points and phase offset paths of the flash drive rhythm signal and the wireless communication time series signal, generates interference distribution data, and provides frequency reference for interference source localization.

[0043] The interference source location module analyzes the instantaneous impact period based on interference distribution data, locates the electromagnetic noise source generated by the flash drive circuit, generates synchronization risk data, and provides a risk basis for communication synchronization adjustment.

[0044] The timing revision analysis module combines out-of-synchronization risk data to trace back wireless communication time series signals, identify the out-of-synchronization segments and alarm data misordered distribution, and generate timing rhythm adjustment data to provide input parameters for the dynamic adjustment process.

[0045] The dynamic rhythm control module adjusts the data according to the time rhythm to perform dynamic adjustment, so that the flash drive rhythm signal enters the random micro-jitter mode, the wireless communication process adopts a breathing mutual exclusion window, and a sliding dark window is inserted in the communication sequence to achieve frequency resonance suppression and signal synchronous recovery.

[0046] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0047] This invention introduces multi-source signal synchronous acquisition and frequency correlation analysis into the anti-theft audible and visual alarm process of power distribution equipment. This establishes a dynamic correlation between the flashing drive rhythm signal and the wireless communication time series signal on a unified time scale, enabling real-time identification of resonant frequency points and phase shift paths caused by electromagnetic interference. This process achieves rapid location of electromagnetic noise sources and accurate identification of synchronization risks, ensuring stable data transmission even in strong electromagnetic environments. It effectively avoids signal drift and alarm delay problems, ensuring that alarm information responds synchronously to actual intrusion events.

[0048] This invention achieves dynamic adjustment by modifying the timing rhythm data, giving the flashing drive rhythm signal random micro-jitter characteristics. It also enables the wireless communication process to operate using a breathing-style mutual exclusion window and a sliding dark window, thus reducing the interference of frequency resonance on communication synchronization in the time domain. This method gives the alarm signal transmission path adaptive characteristics under dynamic conditions, allowing for continuous and stable restoration of signal synchronization. This improves the alarm system's anti-interference capability and real-time performance in complex electromagnetic environments, ensuring reliable triggering and closed-loop information transmission of the burglar alarm device. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0050] Figure 1 This is a flowchart of an audible and visual alarm method for preventing theft of power distribution equipment according to the present invention.

[0051] Figure 2 This is a schematic diagram of a module of an audible and visual alarm system for preventing theft of power distribution equipment according to the present invention. Detailed Implementation

[0052] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0053] This invention provides, for example Figure 1 The method for audible and visual alarm for theft prevention of power distribution equipment, as shown, includes the following steps:

[0054] Electromagnetic noise signals, flash drive rhythm signals, and wireless communication time series signals are collected from the power distribution equipment operation site. The electromagnetic noise signals, flash drive rhythm signals, and wireless communication time series signals are then processed synchronously according to a unified time scale to generate synchronous observation data, providing a time reference for subsequent frequency correlation analysis.

[0055] In implementing the audible and visual alarm method for theft prevention of power distribution equipment, in order to generate synchronous observation data with a unified time scale to support subsequent frequency correlation analysis, synchronous acquisition and processing are carried out on electromagnetic noise signals, flashing drive rhythm signals, and wireless communication time series signals generated at the power distribution equipment operation site. The specific implementation steps are as follows:

[0056] The electromagnetic environment at the power distribution equipment operating site is monitored and signals are acquired. The electromagnetic noise signal acquisition range covers the electromagnetic field changes in the space surrounding the power distribution equipment and the surface of conductive components inside the equipment. The sampling process includes sampling transient pulse signals, electromagnetic radiation interference, conductor coupling interference, and power frequency background noise, which are continuously recorded in chronological order to form a multi-dimensional electromagnetic noise dataset containing time, amplitude, and frequency band distribution. Simultaneously, the flash drive rhythm signal is acquired, with sampling points set at the output of the flash drive circuit. The sampling content includes the start time, duration, driving pulse current amplitude, and its distribution on the time axis of the flash trigger signal, ensuring a complete reflection of the start, duration, and end characteristics of each flash cycle. Furthermore, wireless communication time series signals are acquired, with the sampling range covering the complete communication process between the transmitting and receiving ends of the communication module, including data packet transmission time, carrier occupancy time, reception acknowledgment time, and signal interval duration. By synchronously sampling within the same time domain, all three types of signals are recorded with time as the core parameter, providing raw input for subsequent synchronous processing.

[0057] After signal acquisition, the electromagnetic noise signal, flash drive rhythm signal, and wireless communication time series signal underwent time scale unification and synchronization alignment. First, the data recording times of the three types of signals were precisely compared, and the signal sequence with the longest time span was selected as the time reference. Based on this, interpolation and time extension methods were used to make the other two types of signals form comparable sampling nodes on the same time axis. The electromagnetic noise signal maintained continuity on the time axis, and its waveform characteristics and time index were completely preserved. The periodic boundaries of the flash drive rhythm signal were determined using a trigger point extraction algorithm, mapping the start and end points of each flash cycle to a unified time reference. The time information of the wireless communication time series signal was determined by comparing the transmission and reception times to determine its time span, and the start and end times of the communication activity were matched with the flash drive cycle and the peak time of the electromagnetic noise. Through this time scale unification method, the electromagnetic noise signal, flash drive rhythm signal, and wireless communication time series signal were synchronized on the same time axis, providing a foundation for subsequent synchronization reconstruction.

[0058] After time synchronization processing, the three types of signals undergo synchronous reconstruction and time series organization to form continuous observation data that can be directly used for subsequent analysis. The reconstruction of the electromagnetic noise signal maintains the integrity of the original sampled waveform, arranging the sampled signals sequentially along the time axis and marking the peak time and duration of interference in each waveform segment. The reconstruction of the flash-driven rhythm signal is based on each flash cycle, marking the trigger pulse, continuous pulse, and decay process on a unified time scale and establishing a one-to-one time mapping with the peak periods of the electromagnetic noise signal. The organization of the wireless communication time series signal involves timing calibration based on the original communication events, marking the transmission time, transmission interval, and acknowledgment time of each communication data packet sequentially on a unified time axis, and establishing a correspondence with the trigger time of the flash-driven rhythm and the abrupt change points of the electromagnetic noise. Through this process, the three types of signals form a synchronous and continuous distribution along the time axis, resulting in a three-dimensional time data set containing changes in electromagnetic interference intensity, flash cycle distribution, and communication timing variations. This data set can directly reflect the time dependence between the signals in subsequent frequency analysis.

[0059] After completing the synchronization reconstruction, the established synchronized observation data underwent time benchmark confirmation and data fusion. The time benchmark confirmation process, centered on a unified time scale, indexed each sampling point of the electromagnetic noise signal, each flash cycle node of the flash-driven rhythm signal, and each communication event of the wireless communication time series signal. Each index contains a corresponding time label, signal type label, and amplitude information, ensuring all data are clearly located within a unified time domain. Subsequently, multi-source data fusion processing was performed to maintain the temporal correspondence between the three types of signals, constructing a continuous time series suitable for subsequent frequency analysis. During the fusion process, the amplitude changes of the electromagnetic noise signal and the pulse distribution of the flash-driven rhythm signal were synchronously superimposed, and the activity periods of the wireless communication time series signal were embedded within the same time interval, forming a complete time-series alignment result. The final synchronized observation data includes time mappings of electromagnetic noise changes, flash-driven cycle information, and communication event distributions, providing a unified time benchmark for subsequent frequency correlation analysis. This process ensures that the time relationship between signals is accurately recorded and synchronized when the power distribution equipment is running, so that it can be directly used for resonance point identification, phase offset path estimation and interference source tracing analysis in the subsequent analysis stage, forming a complete and continuous time series observation basis.

[0060] Frequency correlation analysis is performed based on synchronous observation data to extract the resonance frequency points and phase offset paths of the flash drive rhythm signal and the wireless communication time series signal, generating interference distribution data and providing frequency reference for interference source localization.

[0061] In the implementation of audible and visual alarm methods for theft prevention in power distribution equipment, frequency correlation analysis based on synchronous observation data is a crucial step. This analysis allows for the extraction of the resonant frequency points and phase shift paths between the flashing drive rhythm signal and the wireless communication time series signal, thereby generating interference distribution data and ultimately providing a frequency reference for subsequent interference source localization. The specific implementation steps are as follows:

[0062] Frequency conversion and data segmentation are performed on the synchronized observation data. First, after data synchronization, each segment of signal data is processed. Specifically, the electromagnetic noise signal, the flash drive rhythm signal, and the wireless communication time series signal are divided into several small segments according to time, ensuring that each segment is perfectly aligned in time. In this process, it is necessary to accurately identify the time peak of the electromagnetic noise signal and the transmission time of the wireless communication signal, and map them one-to-one with the pulse trigger time of the flash drive signal. For each data segment, a window function is used for signal segmentation to ensure the integrity of the signal data within each time period and avoid data loss. During this process, the intensity of the electromagnetic noise signal, the period of the flash signal, and the transmission and reception times of the wireless communication are all marked and recorded as key data to ensure synchronous analysis on the same time scale.

[0063] Frequency components are extracted for each data segment. For flash drive rhythm signals, the frequency components of each flash pulse cycle are first extracted, including the pulse start time, duration, and interval between cycles, to determine the corresponding frequency range. When extracting the frequency components of the flash signal, the periodicity of the changes needs to be determined based on different drive pulse times. The changes of each pulse in the time domain are analyzed and converted into frequency information in the frequency domain. For wireless communication signals, the transmission and reception times of each data packet are first extracted, the time interval between data packets and the carrier occupancy time are analyzed, and the frequency distribution of the communication signal is calculated. Electromagnetic noise signals are extracted by decomposing their spectrum and extracting the energy distribution of the noise signal in different frequency bands. The frequency components of all signals are integrated into the same time window to provide basic data for subsequent frequency analysis.

[0064] Frequency correlation analysis was performed to extract resonant frequencies and phase shift paths. This process first compares the frequency characteristics of the flash drive signal with those of the wireless communication signal to identify their resonant frequencies. Specifically, overlapping frequency ranges in the frequency distributions of the two signals were identified, and the time periods during which these frequency ranges occurred were determined. By comparing their respective frequency responses, the frequency overlap intervals between the flash drive signal and the communication signal were found; these intervals are the resonant frequencies. After identifying the resonant frequencies, the phase shift between the two signals was further analyzed. By comparing the phase changes of the flash drive signal and the wireless communication signal within the same time period, the phase shift path was determined. This phase shift path reveals how frequency fluctuations in the flash drive signal affect the synchronization state of the communication signal, including phase advance or lag. This analysis helps determine the degree of interference of the flash signal on the communication signal and its impact on communication timing at different time points.

[0065] Based on frequency correlation analysis results, interference distribution data is generated to provide frequency references for interference source localization. After extracting resonant frequencies and phase shift paths, all interference information is integrated into an interference distribution dataset. This dataset includes the frequency overlap region for each time period, the duration of each resonant frequency, and the corresponding phase shift path. Within each time period, the frequency characteristics, phase changes, and interference intensity of the interference signal are recorded in the interference distribution data. Furthermore, frequency reference tables are established according to different interference frequency bands, indicating the probability of interference between flash drive signals and communication signals within a specific time period. This interference distribution dataset provides accurate frequency references for subsequent interference source localization, enabling the tracking of specific interference sources during equipment operation and providing data support for subsequent interference suppression.

[0066] Based on the analysis of the instantaneous impact period using interference distribution data, the location of the electromagnetic noise source generated by the flash drive circuit is determined, and the loss-of-synchronization risk data is generated to provide a risk basis for communication synchronization adjustment.

[0067] Based on the interference distribution data, the instantaneous impact period is analyzed and the location of the electromagnetic noise source generated by the flash drive circuit is located. At the same time, the loss-of-synchronization risk data is generated. The specific implementation steps are as follows:

[0068] Interference distribution data was subjected to time-series filtering and instantaneous impact period identification. By segmenting and analyzing the frequency resonance points and phase shift paths recorded in the interference distribution data, the time intervals of interference occurrence were expanded sequentially along the time axis. During the analysis, the electromagnetic noise signal intensity changes within consecutive time periods before and after each resonance frequency point were extracted, establishing a time-frequency correspondence table. This table contains complete information on the interference start time, interference peak time, interference end time, and corresponding frequency bandwidth. When processing each time period, the pulse trigger time of the flash-driven rhythm signal was compared with the transmission start and end times of the wireless communication time series signal. By comparing the overlapping intervals of the two, the time periods affected by the flash-driven communication process were determined. By continuously scanning the entire observation period, multiple sets of instantaneous impact period data were gradually extracted, each set corresponding to a flash trigger event and the corresponding electromagnetic interference signal. The result of this process is a set of instantaneous impact data containing precise start and end times, corresponding frequency ranges, energy peaks, and influencing signal types, providing dual time and frequency references for subsequent interference source localization.

[0069] Based on the identified instantaneous impact period, the propagation characteristics of electromagnetic noise signals are tracked and compared to pinpoint the specific location of the electromagnetic noise source. This process begins by extracting the electromagnetic noise signal waveform within the instantaneous impact period and analyzing the trends in rise time, peak duration, and fall time. Subsequently, the electromagnetic noise signals collected from different monitoring points are compared temporally, comparing the arrival time and amplitude of the same interference event at different monitoring locations one by one. The propagation direction of the interference signal is determined by the temporal sequence of the signals. Combining the attenuation characteristics of interference intensity with distance, the relative location of the electromagnetic noise source can be calculated by comparing the signal energy differences across multiple monitoring locations. During the analysis, the trigger time of the flash drive rhythm signal is used as a reference point. The start time of each interference event is compared with the pulse trigger time of the flash drive signal to determine whether the interference signal directly originates from the flash drive circuit. When the interference period completely overlaps with the flash trigger time and the signal propagation direction is consistent with the location of the drive circuit, it can be determined that the interference event is generated by the flash drive circuit. By performing the same localization analysis on the electromagnetic signals of all interference periods, the specific circuit area or component causing the interference is finally determined, forming the location result of the electromagnetic noise source.

[0070] After locating the noise source, a risk assessment and synchronization loss risk data generation are performed on the location results. In this process, the instantaneous impact period corresponding to the electromagnetic noise source is correlated with the wireless communication time series signal for analysis, and the abnormal performance of the communication process during the interference period is statistically analyzed. First, the normal timing of the communication signal is identified and compared with the communication activity during the interference period, recording the transmission delay, reception delay, data retransmission, and data loss of communication data packets under interference. By comparing the average transmission interval of communication data before and after the interference, the degree of timing deviation caused by the interference is assessed. Furthermore, the ratio of interference duration to communication timing drift time is calculated to determine the degree of communication synchronization loss risk. When generating synchronization loss risk data, a corresponding risk record entry is established for each interference period, recording the time location, interference frequency, interference intensity, phase shift amplitude, communication delay time, and data loss ratio. By summarizing the risk records for all interference periods, a complete synchronization loss risk data table is generated, providing accurate risk parameters for communication synchronization adjustment.

[0071] Based on the out-of-synchronization risk data, the adjustment range and basis for communication synchronization are extracted to provide guidance for subsequent synchronization optimization. By analyzing the risk distribution of different interference periods in the out-of-synchronization risk data, the periods with the most severe impact on communication due to interference are identified. For high-risk periods, key areas for communication adjustment are determined, and the tolerable synchronization offset range is calculated. Combining the location data of electromagnetic noise sources and interference frequency information, the time windows most susceptible to interference during communication are estimated. Based on these time windows, a communication synchronization adjustment reference table is further generated, which includes the adjustment cycle, delay compensation value, data retransmission suggestions, and communication interval optimization schemes corresponding to each interference period. In this way, the out-of-synchronization risk data is transformed into an actionable basis for synchronization adjustment, enabling the subsequent communication rhythm revision process to be supported by data and ensuring that the communication process maintains stable time coordination and data continuity even when interference persists.

[0072] By combining out-of-synchronization risk data to trace back the wireless communication time series signal, out-of-synchronization segments and alarm data misordered distribution are identified, and time rhythm adjustment data is generated to provide input parameters for the dynamic adjustment process.

[0073] The process of tracing back the wireless communication time series signal based on the out-of-synchronization risk data, identifying the misaligned distribution of out-of-synchronization segments and alarm data, and generating time rhythm adjustment data is crucial. To ensure that the alarm system maintains stable communication and data synchronization under electromagnetic interference or other external influences, the specific implementation steps are as follows:

[0074] The system traces the time series of communication signals and analyzes each segment in conjunction with out-of-synchronization risk data. During the tracing process, it first analyzes each potentially affected time interval of the communication signal based on the interference periods identified by the out-of-synchronization risk data. Each interference period corresponds to the transmission of one or more wireless communication data packets. The sending, transmission, and reception times of these data packets are abnormal during the interference period, such as packet loss, delay, or out-of-order delivery. For each affected period, the system first compares the normal transmission time of the signal with the actual received time using timestamps, marking the difference between the data packet offset and the normal timing. Simultaneously, it checks for packet loss and analyzes its correlation with the interference signal to determine whether the packet loss in that period is related to the resonant frequency or phase shift of the interference signal. Through this tracing analysis, specific out-of-synchronization segments can be located, and the transmission problems of each data packet in these segments, such as misalignment or delay, as well as the specific time and location of the out-of-synchronization event, can be accurately recorded.

[0075] Based on the backtracking results, the out-of-sequence distribution of synchronization loss segments and alarm data is identified and marked. By comparing the normal timing of the communication signal with the backtracked synchronization loss segments, the characteristics of each synchronization loss segment are further clarified. First, according to the sending and receiving order of data packets, it is determined which data packets were out of order during the interference period. Next, these out-of-sequence data packets are compared with the normal transmission sequence to analyze the cause and type of the error. For example, is there synchronization loss due to electromagnetic noise, or is there a data packet misalignment problem caused by excessively long or short communication intervals? The system records the details of each synchronization loss segment, forming an out-of-sequence alarm data list, including the timestamp of each out-of-sequence data packet, the type of sequence error (such as packet loss, delay, out-of-sequence, etc.), the period of influence of the interference source, and the magnitude of the misorder. In this way, the distribution of synchronization loss and out-of-sequence during the entire communication process is accurately recorded, forming a complete synchronization loss and out-of-sequence data report, providing detailed data support for subsequent synchronization adjustments.

[0076] The system generates timing adjustment data based on out-of-order data. After identifying and recording out-of-synchronization segments and out-of-order alarm data, the system needs to generate a timing adjustment plan based on this data. According to the distribution of out-of-order data and the time periods of out-of-synchronization segments, the system calculates the optimal transmission time and interval for each data packet, adjusting its transmission time and reception acknowledgment time. Specifically, when the reception delay of a data packet exceeds a predetermined tolerance range, the system calculates a new time window, which rearranges the transmission and reception of data packets within the original out-of-order period. For packet loss or out-of-order situations occurring within the time window, the system decides whether to fine-tune the communication interval based on the severity of the out-of-order situation. For example, if the out-of-order situation is minor, the system may restore synchronization by shortening the interval time; while in cases of severe out-of-order situations, it may restore the normal communication order by increasing the number of retransmissions or adjusting the signal transmission time window. Each adjustment relies on previously recorded out-of-synchronization segment data to ensure that the synchronization adjustment measures are accurate to each time period and minimize the impact on other data packets.

[0077] The generated timing adjustment data is applied to the dynamic adjustment process. After generating the timing adjustment data, the system uses this data as input to automatically adjust the timing of the communication signal. The system optimizes the sending and receiving times of each data packet based on the adjusted timing, ensuring that the communication process is no longer affected by previous interference periods and that normal communication synchronization can be restored. Specifically, the system performs time correction in real time during actual data transmission, adjusting the sending interval and transmission time of each data packet, and dynamically adjusts the communication frequency based on the adjustment results to reduce the impact of future interference periods on signal synchronization. The adjusted timing is continuously monitored and optimized based on real-time feedback data. The entire process can respond to synchronization issues in real time and ensure stable transmission of the communication signal even in complex interference environments through dynamic adjustment.

[0078] According to the time rhythm, the data is dynamically adjusted to make the flash drive rhythm signal enter the random micro-jitter mode, the wireless communication process adopts the breathing mutual exclusion window, and the sliding dark window is inserted in the communication sequence to achieve frequency resonance suppression and signal synchronous recovery.

[0079] Performing dynamic adjustments to bring the flash drive rhythm signal into a random micro-jitter mode, employing a breathing-type mutual exclusion window and inserting a sliding dark window into the communication timing are crucial steps to ensure signal synchronization recovery and avoid frequency resonance interference. The specific implementation steps are as follows:

[0080] The system initiates a random micro-jitter mode for the flash drive rhythm signal. In this phase, the system adjusts the period of the flash drive signal based on previously adjusted timing data. Within each flash cycle, instead of using a fixed time interval, a random range of variation is introduced to ensure a slight offset in the trigger time of each flash signal. This offset is typically generated within a predetermined time range, thus avoiding periodic resonance between the flash drive signal and the communication signal. To achieve this, the system first sets the minimum and maximum deviation ranges for each flash cycle, ensuring the deviation range is small enough not to affect the alarm system's functionality while effectively breaking the interference of a fixed cycle. Then, based on these parameters, the system periodically inserts a random time offset at the trigger time of each flash cycle, so that the flash signal no longer maintains a fixed frequency ratio with the communication signal. In this way, the frequency relationship between the flash signal and the communication signal is randomized, avoiding frequency resonance and reducing interference with the wireless communication signal.

[0081] A breathing-style mutual exclusion window is used to control the transmission of communication signals. Because the random micro-jitter of the flash drive signal alters its trigger time, the transmission of the communication signal also needs to be dynamically adjusted to avoid overlap or excessive proximity between the flash and communication signals in time. In this step, the communication process is divided into multiple mutually exclusive time windows, the length of which is dynamically adjusted according to the random changes in the flash signal. The length of each mutual exclusion window is adjusted based on the current periodic variation of the flash signal, ensuring that the communication signal does not overlap with the flash signal during transmission. Each data packet is transmitted within a specified time window, and there is a rest interval between each transmission window, which is adjusted according to the micro-jitter of the flash signal. By introducing this breathing-style mutual exclusion window, the transmission time of the communication signal does not overlap with the period of the flash signal, ensuring that the transmission and reception of each data packet are not interfered with. Each adjustment is based on the real-time trigger time of the flash signal, dynamically calculating and allocating an appropriate time window to stagger the communication and flash signals in time, avoiding interference caused by frequency resonance.

[0082] A sliding dark window is inserted into the communication timing. To further optimize signal synchronization and suppress interference, the system introduces a sliding dark window into the communication timing based on the real-time electromagnetic environment and the synchronization status of the communication signal. The purpose of this dark window insertion process is to avoid interference caused by frequency resonance during the transmission of the communication signal. The insertion of the sliding dark window is based on real-time feedback of the communication timing. When the system detects that there may be a high risk of resonance interference between the communication signal and the flash signal during certain time periods, the system inserts a short "blank" time window, i.e., a sliding dark window, during these periods. The size and position of the sliding dark window are dynamically adjusted according to the micro-jitter period of the flash signal to avoid peak periods of electromagnetic interference. The function of this "blank" time window is to postpone or advance the transmission time of certain data packets, thereby avoiding data transmission during periods of high interference. In some cases, the sliding dark window can extend the communication interval and adjust the transmission order of data packets to ensure that the signal is not transmitted during peak interference. Through this sliding mechanism, the overlap between the communication signal and the interference signal is avoided, the synchronization loss problem during the communication process is alleviated, and thus the reliability of signal transmission is improved.

[0083] During the dynamic adjustment process, all adjustment data is applied to ensure signal synchronization recovery. After the above adjustments are completed, the system monitors the transmission status of each data packet in real time and continuously optimizes the transmission timing of data packets based on the adjusted time rhythm. During this process, the transmission interval of the communication signal, the transmission time of each data packet, and the reception time are continuously updated and corrected based on the previously generated adjustment data. The system ensures stable signal transmission in interference environments by monitoring the actual transmission status of each signal packet in real time. If new interference signals or changes occur, the system will make dynamic feedback adjustments based on previous adjustment experience data. This continuous dynamic adjustment not only ensures the stable transmission of alarm data packets but also continuously optimizes the synchronization of communication signals in complex electromagnetic environments, thereby ensuring that alarm signals are accurately and timely transmitted to the monitoring center. The system's real-time monitoring function continuously corrects the timing based on changes in communication signal quality, ensuring that each adjustment improves transmission reliability and avoids synchronization loss or alarm delay.

[0084] This invention introduces multi-source signal synchronous acquisition and frequency correlation analysis into the anti-theft audible and visual alarm process of power distribution equipment. This establishes a dynamic correlation between the flashing drive rhythm signal and the wireless communication time series signal on a unified time scale, enabling real-time identification of resonant frequency points and phase shift paths caused by electromagnetic interference. This process achieves rapid location of electromagnetic noise sources and accurate identification of synchronization risks, ensuring stable data transmission even in strong electromagnetic environments. It effectively avoids signal drift and alarm delay problems, ensuring that alarm information responds synchronously to actual intrusion events.

[0085] This invention achieves dynamic adjustment by modifying the timing rhythm data, giving the flashing drive rhythm signal random micro-jitter characteristics. It also enables the wireless communication process to operate using a breathing-style mutual exclusion window and a sliding dark window, thus reducing the interference of frequency resonance on communication synchronization in the time domain. This method gives the alarm signal transmission path adaptive characteristics under dynamic conditions, allowing for continuous and stable restoration of signal synchronization. This improves the alarm system's anti-interference capability and real-time performance in complex electromagnetic environments, ensuring reliable triggering and closed-loop information transmission of the burglar alarm device.

[0086] This invention provides, for example Figure 2 The illustrated audible and visual alarm system for theft prevention of power distribution equipment includes a signal synchronization acquisition module, a frequency correlation analysis module, an interference source location module, a timing revision analysis module, and a dynamic rhythm control module.

[0087] The signal synchronization acquisition module collects electromagnetic noise signals, flash drive rhythm signals, and wireless communication time series signals at the power distribution equipment operation site. It then synchronizes these signals according to a unified time scale to generate synchronized observation data, providing a time reference for subsequent frequency correlation analysis.

[0088] The frequency correlation analysis module performs frequency correlation analysis based on synchronous observation data, extracts the resonance frequency points and phase offset paths of the flash drive rhythm signal and the wireless communication time series signal, generates interference distribution data, and provides frequency reference for interference source localization.

[0089] The interference source location module analyzes the instantaneous impact period based on interference distribution data, locates the electromagnetic noise source generated by the flash drive circuit, generates synchronization risk data, and provides a risk basis for communication synchronization adjustment.

[0090] The timing revision analysis module combines out-of-synchronization risk data to trace back wireless communication time series signals, identify the out-of-synchronization segments and alarm data misordered distribution, and generate timing rhythm adjustment data to provide input parameters for the dynamic adjustment process.

[0091] The dynamic rhythm control module adjusts the data according to the time rhythm to perform dynamic adjustment, so that the flash drive rhythm signal enters the random micro-jitter mode, the wireless communication process adopts a breathing mutual exclusion window, and a sliding dark window is inserted in the communication sequence to achieve frequency resonance suppression and signal synchronous recovery.

[0092] The present invention provides an audible and visual alarm method for preventing theft of power distribution equipment, which is implemented by the aforementioned audible and visual alarm system for preventing theft of power distribution equipment. For details of the specific method and process of the audible and visual alarm system for preventing theft of power distribution equipment, please refer to the embodiment of the aforementioned audible and visual alarm method for preventing theft of power distribution equipment, which will not be repeated here.

[0093] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A sound and light alarm method for preventing theft of a power distribution apparatus, characterized by, Includes the following steps: Electromagnetic noise signals, flash drive rhythm signals, and wireless communication time series signals are collected from the power distribution equipment operation site. The electromagnetic noise signals, flash drive rhythm signals, and wireless communication time series signals are then processed synchronously according to a unified time scale to generate synchronous observation data. Frequency correlation analysis is performed based on synchronous observation data to extract the resonance frequency points and phase shift paths of the flash drive rhythm signal and the wireless communication time series signal, and to generate interference distribution data. Based on the analysis of the instantaneous impact period using interference distribution data, the location of the electromagnetic noise source generated by the flash drive circuit is determined, and step loss risk data is generated. By combining out-of-synchronization risk data to trace back wireless communication time series signals, out-of-synchronization segments and alarm data are identified and misordered distribution is generated to generate time rhythm adjustment data. The steps for generating time rhythm adjustment data are as follows: Perform communication time series backtracking analysis, compare the transmission and reception times of communication signals segment by segment with the interference periods indicated by the out-of-synchronization risk data, mark the data packet offset time and locate the out-of-synchronization segment; Perform analysis on out-of-synchronization segments and out-of-order data, compare the normal timing of the communication signal with the backtracking results, identify disordered data packets, and generate a list of out-of-order alarm data. The execution time rhythm adjustment data generation calculates the transmission interval of each data packet based on the out-of-order distribution and out-of-synchronization segments, and adjusts the sending and receiving times to form time rhythm adjustment data; The execution time rhythm adjustment data application uses the adjustment data as input to optimize the timing of communication signals and corrects the sending and receiving intervals of data packets in real time to restore communication synchronization; The data is dynamically adjusted according to the time rhythm, so that the flash drive rhythm signal enters the random micro-jitter mode, the wireless communication process adopts a breathing mutual exclusion window, and a sliding dark window is inserted in the communication sequence. The following are the steps for dynamically adjusting data according to time rhythm: The random micro-jitter mode of the flash drive rhythm signal is activated, and the period of the flash drive signal is randomly offset according to the time rhythm adjustment data to avoid the flash drive signal and the wireless communication signal forming a fixed frequency ratio. The communication signal transmission is controlled by a breathing-type mutual exclusion window. The communication transmission window is dynamically divided and the communication interval is adjusted according to the random changes of the flash drive signal, so that the communication process is staggered from the flash cycle in time. A sliding dark window insertion is performed. When a resonance risk is detected between the communication signal and the flash drive signal, a blank time window is inserted into the communication timing to avoid peak interference periods through time offset. The system performs real-time adjustments to the data, continuously optimizes the transmission and reception times of communication signals based on the adjustment results, monitors the signal transmission status, and dynamically corrects the timing to restore signal synchronization.

2. The power distribution apparatus theft-preventing audible and visual alarm method of claim 1, wherein, The steps for generating synchronous observation data are as follows: Electromagnetic noise signal acquisition is performed to monitor the changes in electromagnetic field in the space surrounding the power distribution equipment and on the surface of the internal conductive components. Transient pulse signals, electromagnetic radiation interference, conductor coupling interference and power frequency background noise are continuously recorded to form an electromagnetic noise dataset containing time, amplitude and frequency band distribution. Perform flash drive rhythm signal acquisition, and record the start time, duration, drive pulse current amplitude and time distribution of the flash trigger signal at the output of the flash drive circuit; Perform wireless communication time series signal acquisition, and record the data packet transmission time, carrier occupancy time, reception acknowledgment time, and signal interval duration; Electromagnetic noise signals, flash-driven rhythm signals, and wireless communication time series signals are synchronized according to a unified time scale to establish a time index, maintain the continuity and alignment of the signals, and generate synchronized observation data.

3. The theft-proof audible and visual alarm method for power distribution equipment according to claim 2, wherein, The steps for generating interference distribution data are as follows: Perform frequency conversion and data segmentation processing to divide the electromagnetic noise signal, flash drive rhythm signal and wireless communication time series signal into multiple continuous segments according to time, ensuring that each signal segment is perfectly aligned on the time axis; The frequency component extraction process converts the pulse start time, duration, and interval of the flash-driven rhythm signal into a frequency distribution, analyzes the transmission time, reception time, and carrier occupancy time of the wireless communication time series signal into frequency features, and extracts the energy distribution of the electromagnetic noise signal in different frequency bands. Frequency correlation analysis is performed to compare the frequency distribution of the flash drive rhythm signal and the wireless communication time series signal within the same time period, determine the frequency overlap area as the resonance frequency point, and extract the phase shift path through phase change. By integrating the results of frequency correlation analysis, interference distribution data is generated, and frequency overlap areas, resonant frequency durations, and phase shift paths are recorded to provide frequency references for interference source localization.

4. The audible and visual alarm method for theft prevention of power distribution equipment according to claim 3, characterized in that, When extracting the resonant frequency point and phase shift path, the frequency response of the flash drive rhythm signal and the wireless communication time series signal is compared in time. By detecting the degree of frequency overlap and phase change trend of the two signals in the same time period, the interference occurrence interval is determined, and the interference duration and phase shift amplitude are recorded synchronously in the interference distribution data.

5. The theft-proof audible and visual alarm method for power distribution equipment according to claim 3, wherein, The steps for generating data on the risk of falling out of step are as follows: Perform time-series filtering of interference distribution data and identification of instantaneous impact periods; extract electromagnetic noise signal intensity changes by analyzing frequency resonance points and phase shift paths and establish a time-frequency correspondence table. Perform propagation tracking and comparative analysis of electromagnetic noise signals, determine the propagation direction of the electromagnetic noise source based on the signal arrival time and energy differences at different monitoring locations, and determine whether it originates from the flash drive circuit. Perform risk assessment and generate out-of-synchronization risk data by comparing the instantaneous impact period corresponding to the electromagnetic noise source with the wireless communication time series signal, and recording communication delay, retransmission and loss to generate out-of-synchronization risk data; The system analyzes and extracts data on the risk of synchronization failure, identifies the period with the most severe interference based on the risk distribution, calculates the synchronization offset range, and generates a reference table for communication synchronization adjustment.

6. The theft-proof audible and visual alarm method for power distribution equipment according to claim 5, wherein, By calculating the ratio of interference duration to communication timing drift time, the risk level of communication synchronization loss is determined. Based on the risk level, the risk weights of different interference periods are sorted, and the communication delay and phase offset parameters of the highest risk period are extracted to optimize the compensation period and data retransmission interval in the communication synchronization adjustment reference table.

7. The power distribution equipment theft prevention audible and visual alarm system for implementing the power distribution equipment theft prevention audible and visual alarm method of any of claims 1-6, wherein, It includes a signal synchronization acquisition module, a frequency correlation analysis module, an interference source location module, a timing revision analysis module, and a dynamic rhythm control module. The signal synchronization acquisition module collects electromagnetic noise signals, flash drive rhythm signals, and wireless communication time series signals at the power distribution equipment operation site. It then processes these signals synchronously according to a unified time scale to generate synchronous observation data. The frequency correlation analysis module performs frequency correlation analysis based on synchronous observation data, extracts the resonant frequency points and phase shift paths of the flash drive rhythm signal and the wireless communication time series signal, and generates interference distribution data. The interference source localization module analyzes the instantaneous impact period based on interference distribution data, locates the electromagnetic noise source generated by the flash drive circuit, and generates loss-of-synchronization risk data. The timing revision analysis module combines out-of-synchronization risk data to trace back wireless communication time series signals, identify the out-of-synchronization segments and alarm data misorder distribution, and generate timing rhythm adjustment data. The dynamic rhythm control module adjusts the data according to the time rhythm to perform dynamic adjustment, so that the flash drive rhythm signal enters the random micro-jitter mode, the wireless communication process adopts a breathing mutual exclusion window, and a sliding dark window is inserted in the communication timing.

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