Line error account analysis method, system, equipment and medium

Abstract

The invention relates to the technical field of loop detection, and particularly provides a line error account analysis method, system and device and a medium, and the method comprises the steps: configuring a composite signal feature comprising a unique frequency hopping sequence, a pseudo-random code and time slot division planning for each loop after a host is connected with each line loop, and injecting a signal into a power line according to a plan; the slave machine detects a line signal at a point to be detected in a non-contact manner, and analyzes a frequency hopping sequence and pseudo-random code features to form a detection fingerprint; and performing multi-dimensional comparison on the fingerprint and the characteristics configured by the host, and judging the matching relationship between the to-be-detected point and the specific loop. According to the invention, through the design and joint analysis of the time, frequency and code three-dimensional orthogonal signals, the anti-interference capability, the multi-loop identification precision and the weak signal detection reliability are significantly improved.

Description

Technical Field

[0001] This invention belongs to the field of loop detection technology, specifically relating to a method, system, equipment, and medium for analyzing line misconnections. Background Technology

[0002] In the field of meter relationship detection, traditional methods often employ single-frequency or simple-coded signal injection and amplitude detection techniques, which have weak anti-interference capabilities and are easily affected by noise in complex electromagnetic environments or scenarios with multiple loops, leading to identification errors or missed detections. Existing technologies struggle to distinguish loops with severe signal attenuation and cannot effectively prevent signal crosstalk between adjacent loops, resulting in insufficient detection reliability. Therefore, there is an urgent need for a multi-loop identification method that can achieve high accuracy and high reliability in high-noise environments to improve the accuracy and applicability of meter relationship determination. Summary of the Invention

[0003] In view of the above-mentioned shortcomings of the prior art, the present invention provides a method, system, device and medium for line misoperation analysis to solve the above-mentioned technical problems.

[0004] In a first aspect, the present invention provides a method for analyzing line misoperation, comprising: The host signal injection unit is sequentially connected to multiple circuit loops to be tested; The host configures a unique composite signal feature for each of the line loops. The composite signal feature includes a specific frequency hopping sequence assigned to each loop, a unique pseudo-random code, and a time-division injection time slot plan. The host injects the composite signal characteristics corresponding to each loop into the connected power lines according to the time slot plan; The slave device detects signals from the power line in a non-contact manner at the point to be tested, and extracts frequency hopping sequence features and pseudo-random code features from the signals to form a detection fingerprint; The detected fingerprint is compared with the composite signal features configured by the host for each circuit, and the physical location of the test point is determined to match which circuit based on the comparison result.

[0005] In an optional implementation, the host signal injection unit is sequentially connected to multiple line loops to be detected, including: The host signal injection unit is coupled to the conductors of each circuit individually through magnetic coupling. The magnetic coupling method is achieved by a coupling clamp with an open magnetic core, which is clamped onto the insulating outer sheath of the wire during operation.

[0006] In an optional implementation, the host configures a unique composite signal characteristic for each of the line loops, including: A unique frequency hopping sequence is generated for each line loop. The frequency hopping sequence consists of multiple preset, non-contiguous frequency points arranged in a predetermined order, and the frequency hopping sequences of different loops are different in terms of frequency points or arrangement order. Each line loop is assigned a unique pseudo-random code sequence, which has sharp autocorrelation characteristics and low cross-correlation. Each line loop is assigned a unique transmit time slot, so that the host can inject signals consisting of a combination of frequency hopping sequence and pseudo-random code sequence into different loops in different time slots.

[0007] In an optional implementation, the host injects the composite signal characteristics corresponding to each loop into the connected power lines according to the time slot plan, including: The host computer uses a time-division multiplexing method to transmit carrier signals one frequency point at a time within the transmission time slot allocated to each loop, according to the frequency points and order specified by the frequency hopping sequence generated for that loop. At each frequency point, the host computer modulates the carrier signal using the pseudo-random code sequence allocated to that loop and then injects it.

[0008] In an optional implementation, the slave device detects a signal from the power line at the point to be tested in a non-contact manner, and parses frequency hopping sequence features and pseudo-random code features from the signal to form a detection fingerprint, including: The received signal is subjected to time-frequency analysis to identify frequency components in the signal whose intensity exceeds a preset threshold and their time sequence of occurrence, thereby obtaining the measured frequency hopping sequence; Using multiple candidate pseudo-random code sequences pre-agreed with the host, sliding correlation operations are performed on the signal respectively, and the peak value exceeding the correlation peak threshold in the operation result is identified. The pseudo-random code sequence that generates the peak value is determined as the code feature carried in the signal.

[0009] In an optional implementation, multiple candidate pseudo-random code sequences pre-agreed with the host are used to perform sliding correlation operations on the signal, and the peak values ​​exceeding the correlation peak threshold in the operation results are identified. The pseudo-random code sequence that generates the peak value is determined as the code feature carried in the signal, including: Each candidate pseudo-random code sequence is selected sequentially, and the cross-correlation values ​​between the sequence and the received signal at multiple sliding time positions are calculated to form a set of correlation results. From the relevant results, the maximum value is extracted as the relevant peak value of the current candidate code sequence; The correlation peaks calculated from all candidate code sequences are compared with a preset peak threshold. If there is a single candidate code sequence whose correlation peak exceeds the peak threshold, and the ratio of the peak value to the second peak value exceeds the preset signal-to-noise ratio threshold, then the candidate code sequence is determined to be a code feature carried in the signal.

[0010] In an optional implementation, the detected fingerprint is compared with the composite signal features configured by the host for each loop, and the physical location of the test point is determined to match which line loop based on the comparison result, including: A multi-dimensional joint decision algorithm is adopted, which is based on a weighted score of multiple feature parameters extracted from the detected fingerprint. The feature parameters include at least the frequency hopping sequence matching degree, the pseudo-random code correlation peak intensity, and the signal received strength. Calculate the overall matching score between the detected fingerprint and the composite signal features configured by the host for each line loop; The highest comprehensive matching score is compared with a preset decision threshold. If the score exceeds the decision threshold, it is determined that the current test point matches the circuit corresponding to that score.

[0011] Secondly, the present invention provides a line misoperation analysis system, comprising: The loop connection module is used to sequentially establish connections between the host signal injection unit and multiple circuit loops to be tested; The signal configuration module is used by the host to configure a unique composite signal feature for each of the line loops. The composite signal feature includes a specific frequency hopping sequence assigned to each loop, a unique pseudo-random code, and a time-division injection time slot plan. The signal injection module is used by the host to inject the composite signal characteristics corresponding to each loop into the connected power lines according to the time slot plan. The signal detection module is used to detect signals from the power line in a non-contact manner at the test point, and to parse the frequency hopping sequence features and pseudo-random code features from the signals to form a detection fingerprint; The signal matching module is used to compare the detected fingerprint with the composite signal features configured by the host for each circuit, and determine which circuit the physical location of the test point matches based on the comparison result.

[0012] Thirdly, a device is provided, comprising: The memory is used to store the circuit error analysis program; A processor is configured to implement the steps of the line misconnection analysis method as provided in the first aspect when executing the line misconnection analysis program.

[0013] Fourthly, a computer-readable medium is provided, on which a line misconnection analysis program is stored, wherein when the line misconnection analysis program is executed by a processor, the line misconnection analysis method as provided in the first aspect is implemented.

[0014] The beneficial effects of this invention are as follows: the line mismatch analysis method, system, equipment, and medium provided by this invention achieve a breakthrough improvement in meter reading detection technology through the design and joint analysis of time-frequency-code three-dimensional orthogonal signals. It possesses extremely strong resistance to narrowband and impulse noise interference, and can operate stably in complex electromagnetic environments; through dynamic frequency hopping and pseudo-random code dual identification, it can clearly distinguish multi-loop signals, almost eliminating crosstalk misjudgments; the spread spectrum gain significantly improves the weak signal detection capability, making it suitable for long-distance, high-attenuation lines; pseudo-random code modulation and multi-dimensional joint decision mechanism greatly improve the system's anti-counterfeiting and reliability; at the same time, the collected multi-dimensional signal characteristics can also provide a data foundation for intelligent line status diagnosis, demonstrating significant application value. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic flowchart of a method according to an embodiment of the present invention.

[0017] Figure 2 This is a schematic block diagram of a system according to an embodiment of the present invention.

[0018] Figure 3 This is a schematic diagram of the structure of a device provided in an embodiment of the present invention. Detailed Implementation

[0019] To enable those skilled in the art to better understand the technical solutions of this invention, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this invention.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

[0021] The line misconnection analysis method provided in this embodiment of the invention is executed by a computer device, and correspondingly, the line misconnection analysis system runs in the computer device.

[0022] Figure 1 This is a schematic flowchart illustrating a method according to an embodiment of the present invention. Wherein, Figure 1 The implementing entity can be a line misconnection analysis system. Depending on different requirements, the order of the steps in this flowchart can be changed, and some steps can be omitted.

[0023] like Figure 1 As shown, the method includes: S1. Establish connections between the host signal injection unit and multiple circuit loops to be tested in sequence; S2. The host configures a unique composite signal feature for each of the line loops, the composite signal feature including a specific frequency hopping sequence assigned to each loop, a unique pseudo-random code, and a time-division injection time slot plan; S3. The host injects the composite signal characteristics corresponding to each circuit into the connected power lines according to the time slot plan; S4. The slave device detects the signal from the power line at the test point in a non-contact manner, and parses the frequency hopping sequence features and pseudo-random code features from the signal to form a detection fingerprint; S5. Compare the detected fingerprint with the composite signal features configured by the host for each circuit, and determine which circuit the physical location of the test point matches based on the comparison result.

[0024] In one embodiment of the present invention, based on step S1, the following will provide a possible embodiment and describe its specific implementation in a non-limiting manner.

[0025] The host signal injection unit establishes a physical connection with the circuit under test using a non-invasive magnetic coupling method. This connection is achieved through a dedicated coupling clamp containing a high-performance open magnetic core. During operation, the operator does not need to disconnect wires or damage insulation; they simply align the opening of the coupling clamp with the conductor of the target circuit, then close the clamp to securely grip the conductor's insulation. Due to the closed magnetic core, the injected signal can be efficiently coupled into the conductor through electromagnetic induction. When testing multiple circuits, simply clamp the coupling clamp onto the conductors of different circuits sequentially to quickly and reliably complete the signal injection connection for all circuits. This method is safe, convenient, and does not affect the normal electrical connection and operation of the circuit.

[0026] In a specific example, especially in the scenario of a household meter relationship census in a newly built community, the step of "establishing connections between the host signal injection unit and multiple line loops to be detected in sequence" is performed as follows: The operators first work at the unit's centralized meter box. Assuming there are 6 electricity meters in the meter box (corresponding to households on floors 1 to 6), there are 6 independent physical circuits to be tested (i.e., the wires from the outgoing terminals of each electricity meter to the main circuit breaker of the corresponding household).

[0027] Preparation and Positioning: Open the meter box and identify the corresponding outgoing wires for each electricity meter. The main unit is placed next to the meter box, and its signal injection unit is connected to a specially designed magnetic coupling clamp. The core of this coupling clamp is an open ring-shaped magnetic core, with an external clamping jaw mechanism that can be opened and closed.

[0028] Establishing a connection (taking loop 1 as an example): The operator holds the coupling clamp and aligns its opening with the live wire of electricity meter No. 1 (corresponding to household 101). Then, the clamp is closed, causing the magnetic core to tightly fit onto the insulation of the conductor, forming a closed magnetic circuit. At this point, the main unit's signal injection unit establishes a non-contact, electrically isolated physical connection with the conductor of "loop 1" through magnetic coupling. The signal can be efficiently injected through electromagnetic induction without stripping the wire or disconnecting the original electrical connection.

[0029] Connect multiple circuits sequentially: After completing the signal injection and detection cycle for circuit 1, the operator opens the coupling clamp and removes it from the wires of circuit 1. Subsequently, following the same procedure, the coupling clamp is sequentially clamped onto the outgoing wires of energy meters 2, 3, ... up to 6, thereby establishing temporary injection connections with all circuits to be tested one by one.

[0030] In one embodiment of the present invention, based on step S2, the following will provide a possible embodiment and describe its specific implementation in a non-limiting manner.

[0031] S201. Generating a Unique Frequency Hopping Sequence: The host computer internally pre-sets a set of selectable frequency points, such as 10 discrete frequency points (f1, f2, ..., f10) distributed within the 50kHz to 1MHz frequency band. Before detection begins, the host's processing unit automatically generates and binds a unique frequency hopping sequence for each circuit under test. This sequence non-contiguously selects several frequency points (e.g., 3) from the aforementioned set and arranges them in a preset order. For example, the sequence [f1, f4, f7] is assigned to circuit 1, [f2, f5, f9] to circuit 2, and [f3, f6, f10] to circuit 3, etc. This ensures that the frequency points contained in the sequences of any two circuits are not completely identical, or even if they contain the same frequency points, their arrangement order is different, thereby achieving orthogonal design in the frequency dimension to combat narrowband interference and distinguish different circuits.

[0032] S202. Assigning a Unique Pseudo-Random Code Sequence: The master assigns a unique pseudo-random code sequence with sharp autocorrelation and low cross-correlation to each line loop (e.g., using Gold codes with different initial phases or m-sequences of different orders). For example, Gold code sequence X is assigned to loop 1, and Gold code sequence Y is assigned to loop 2. These code sequences are pre-stored in the memories of the master and slave, and a correspondence table between the master and slave loops is established. This pseudo-random code will be used to modulate the carrier (e.g., BPSK). Its good correlation characteristics allow the slave to extract weak signals from strong noise through correlation operations, and provide a second "digital ID" for each loop, enhancing the uniqueness of identification and anti-counterfeiting capabilities.

[0033] S203. Allocation of a Unique Transmit Time Slot: The host divides the entire detection cycle into several time slots of equal length. Each line loop is assigned a dedicated transmit time slot (or a set of time slots for transmitting multiple frequency points in its frequency hopping sequence). For example, within a 100-millisecond cycle, it is divided into 6 time slots, each allocated to one of the 6 loops. The host's built-in high-precision clock ensures that it strictly adheres to this precision. In the time slot of loop 1, a signal modulated with pseudo-random code X, with frequencies hopping in the order [f1, f4, f7], is transmitted; in the time slot of loop 2, a signal modulated with pseudo-random code Y, with frequencies hopping in the order [f2, f5, f9], is transmitted, and so on. This time-division multiplexing (TDMA) injection strategy fundamentally avoids intermodulation interference that may result from the simultaneous injection of multiple strong signals, ensuring signal purity and allowing the host to independently adjust the transmit power of each loop based on slave feedback.

[0034] In one embodiment of the present invention, based on step S3, the following will provide a possible embodiment and describe its specific implementation in a non-limiting manner.

[0035] The core process of signal injection performed by the host is as follows, which is coordinated and controlled by the host's internal central processing unit (CPU) or field-programmable gate array (FPGA): Timing and Execution: The host's internal high-precision clock circuit serves as the time reference. The host's control unit operates strictly according to a preset "time slot-loop" mapping table. For example, a detection period of T milliseconds is divided into N time slots (N being the number of loops under test). When the clock indicator enters the dedicated transmission time slot allocated to loop K, the control unit immediately activates the signal generation and injection channel for loop K.

[0036] Sequential Frequency Hopping and Carrier Generation: Within the transmit time slot of loop K, the host computer controls its programmable radio frequency (RF) signal generator or direct digital frequency synthesizer (DDS) to generate high-frequency carrier signals sequentially at each frequency point, according to the frequency hopping sequence (e.g., [f_A, f_D, f_F]) pre-generated for loop K. First, a carrier with frequency f_A is generated within time slot Δt1, then it switches to frequency f_D within Δt2, and finally to frequency f_F within Δt3. The duration of each frequency point (e.g., 10 milliseconds) is preset.

[0037] Pseudo-random code modulation: During the transmission time slice at each frequency point (e.g., within Δt1 of transmitting f_A), the host's baseband processing unit (such as a DSP) synchronously generates a unique pseudo-random code sequence (e.g., a Gold code sequence X) assigned to loop K. This code sequence is output at a code rate (Chipspersecond) much lower than the carrier frequency. The modulator (e.g., a BPSK modulator) receives this code sequence and the carrier, using the "1"s and "0"s of the pseudo-random code to control the carrier phase (e.g., 0° and 180°), thereby completing the modulation and generating the final modulated signal.

[0038] Power Amplification and Coupling Injection: The generated time-frequency-code three-dimensional composite signal is amplified by a power amplifier and then sent to a signal injection unit that has been physically connected to the loop K conductor via a magnetic coupling clamp. The signal is efficiently injected into the power line through electromagnetic induction. At the start of the next time slot, the host control unit switches to the next loop (e.g., loop K+1) and repeats the frequency hopping and modulation process, but uses a different frequency hopping sequence and pseudo-random code assigned to that loop.

[0039] In one embodiment of the present invention, based on step S4, the following will provide a possible embodiment and describe its specific implementation in a non-limiting manner.

[0040] S401. Perform time-frequency analysis on the received signal to identify frequency components in the signal whose intensity exceeds a preset threshold and their time sequence of occurrence, thereby obtaining the measured frequency hopping sequence.

[0041] The slave device's analog-to-digital converter (ADC) captures the broadband signal from the sensing probe at a sufficiently high sampling rate. The captured signal is first fed into a digital signal processing unit for short-time Fourier transform (STFT) analysis. Specifically, the processor windows the signal (e.g., using a Hamming window) and performs segmented fast Fourier transforms (FFTs) to obtain a two-dimensional spectrum (spectral graph) of the signal power spectrum over time. The algorithm then detects all frequency points in each time segment where the power spectrum value exceeds a preset energy threshold and records these frequency points as the "active" signal frequency components at that moment. By tracking the order in which these active frequency components appear over time, the algorithm can reconstruct the frequency change pattern followed by the signal on the time axis, i.e., the measured frequency hopping sequence. For example, if frequencies f_A, f_D, and f_F are detected appearing sequentially, the measured frequency hopping sequence is determined to be [f_A, f_D, f_F].

[0042] S402. Using multiple candidate pseudo-random code sequences pre-agreed with the host, perform sliding correlation operations on the signal respectively, identify the peak value in the operation result that exceeds the correlation peak threshold, and determine the pseudo-random code sequence that generates the peak value as the code feature carried in the signal.

[0043] Step 1: Initialization and Data Preparation The slave device's memory pre-stores N candidate pseudo-random code sequences (such as Gold code sequences C1, C2, ..., CN, where N is the total number of loops) that are completely synchronized with the master device. The processor loads the received, pre-processed (such as frequency conversion and filtering) digitized baseband signal segment into memory as the signal vector S to be analyzed.

[0044] Step 2: Sliding correlation calculation and peak extraction For each candidate pseudo-random code sequence Ck (k=1 to N), the processor executes: Sliding cross-correlation operation: Calculates the cross-correlation value between Ck and the signal vector S at all possible sliding time positions. This is typically achieved by using Ck as a template and performing a sliding dot product on S, or by using a fast convolution algorithm to efficiently generate a sequence of correlation results Rk.

[0045] Extracting the relevant peak value: In the correlation result sequence Rk, find the maximum absolute value (or square value), denoted as Pk, which is the correlation peak value of candidate code Ck under the current signal. Simultaneously, the position (time offset) of this peak value in the sequence Rk can be recorded.

[0046] Step 3: Threshold Comparison and Competition Decision The processor sorts and compares all N relevant peak values ​​P1, P2, ..., PN obtained from the calculation: Preset threshold comparison: Set a dynamic or static peak threshold P_th. This threshold may be set based on the noise floor power or an empirical value. The processor filters out candidates among all peak values ​​Pk that are greater than P_th.

[0047] Uniqueness and SNR Verification: Among candidates exceeding the threshold, further checks are performed to determine if there exists a unique peak P_max that is not only the highest but also satisfies the condition P_max / P_second > SNR_th, where P_second is the second highest correlation peak and SNR_th is a preset signal-to-noise ratio threshold (e.g., 3.0). This step aims to ensure that the signal characteristics are sufficiently significant to clearly distinguish them from noise and other mismatched code sequences, avoiding misjudgments due to accidental noise spikes or weak cross-correlation.

[0048] Step 4: Code Feature Determination If the condition in step three (there is a unique peak value that exceeds the threshold and satisfies the signal-to-noise ratio threshold) is met, the processor determines that the candidate pseudo-random code sequence Ck corresponding to the peak value P_max is the code feature carried in the currently received signal and outputs it as the key information of the coding dimension in the "detection fingerprint".

[0049] In one embodiment of the present invention, based on step S5, a possible embodiment will be given below, and its specific implementation will be described in a non-limiting manner.

[0050] S501. Multidimensional Feature Parameter Extraction and Quantization The slave device first extracts and quantifies the following key feature parameters from the generated "detection fingerprint": Frequency hopping sequence matching degree ( The measured frequency hopping sequence is compared with the expected frequency hopping sequence for each loop preset by the host. The number of matching frequency points and their order consistency are calculated. For example, if there is a perfect match (both frequency points and order are correct), then... Set to 1.0 (or 100%); if only some frequency points match or the order is incorrect, deduct points according to the preset rules.

[0051] Pseudo-random code correlation peak intensity ( For the identified pseudo-random code characteristics, take its correlation peak value P. max The absolute amplitude or energy value as This value directly reflects the strength and signal-to-noise ratio of the coded component in the signal.

[0052] Signal reception strength ( : Measures the average power of the signal received at the current detection location or the signal strength indication at a specific frequency.

[0053] S502. Weighted Composite Matching Score Calculation For each loop i configured by the host, the slave calculates the comprehensive matching score between the currently detected fingerprint and the expected features of that loop. The algorithm employs a pre-defined weighted scoring model, the basic form of which can be expressed as:

[0054] in: , , These are preset weighting coefficients (e.g.) =0.4, =0.5, =0.1), which respectively reflect the relative importance of frequency hopping matching, code correlation strength and signal strength in the decision.

[0055] It is a score that measures the matching degree between the fingerprint and the frequency hopping sequence of loop i.

[0056] It is the peak intensity obtained by performing correlation operations using the pseudo-random code of loop i. It is a normalization factor used to... Adjust to a suitable numerical range.

[0057] It is the signal received strength measured during the analysis of the characteristics of loop i. It is a reference intensity value used for normalization. The components can also be designed as piecewise functions, giving high scores only when the signal strength is within a reasonable attenuation range (neither too weak nor too strong, excluding near-field coupling interference).

[0058] After calculation, a set of fractions S1, S2, ..., S is obtained. N (N is the total number of loops).

[0059] S503. Threshold Comparison and Final Decision The processor executes the final decision: Sorting and Selection: Find the highest score S from the set of comprehensive matching scores. max and its corresponding loop identifier ID max .

[0060] Threshold decision: Set S max With a preset decision threshold S th (For example, 0.8 or 80 points) are compared.

[0061] Output results: If S max >=S th Then determine the physical location of the current test point and the loop ID.max Matching. The slave device displays a matching success message (e.g., "Current location: Household 102, Matched meter: Meter No. 2").

[0062] If S max th If the signal is too weak, interference is too strong, or no valid signal is detected, the slave device will provide a corresponding prompt.

[0063] To further prevent misjudgment, a uniqueness verification can be added: check the highest score S. max With the second highest score S second To check whether the difference is greater than a certain tolerance, and to avoid uncertainty caused by the similar scores of the two circuits.

[0064] In some embodiments, the line misoperation analysis system may include multiple functional modules composed of computer program segments. The computer programs for each program segment in the line misoperation analysis system may be stored in the memory of a computer device and executed by at least one processor to perform (see details). Figure 1 (Description) Function for analyzing incorrect subscribers on the line.

[0065] In this embodiment, the line misoperation analysis system can be divided into multiple functional modules according to its functions, such as... Figure 2 As shown. The module referred to in this invention is a series of computer program segments that can be executed by at least one processor and perform a fixed function, and is stored in memory. In this embodiment, the functions of each module will be described in detail in subsequent embodiments.

[0066] The loop connection module is used to sequentially establish connections between the host signal injection unit and multiple circuit loops to be tested; The signal configuration module is used by the host to configure a unique composite signal feature for each of the line loops. The composite signal feature includes a specific frequency hopping sequence assigned to each loop, a unique pseudo-random code, and a time-division injection time slot plan. The signal injection module is used by the host to inject the composite signal characteristics corresponding to each loop into the connected power lines according to the time slot plan. The signal detection module is used to detect signals from the power line in a non-contact manner at the test point, and to parse the frequency hopping sequence features and pseudo-random code features from the signals to form a detection fingerprint; The signal matching module is used to compare the detected fingerprint with the composite signal features configured by the host for each circuit, and determine which circuit the physical location of the test point matches based on the comparison result.

[0067] Figure 3 ​The line misconnection analysis method provided in the embodiments of this application can be applied to devices. Those skilled in the art will understand that the device structure involved in the embodiments of this invention does not constitute a limitation on the device. A device may include more or fewer components than illustrated, or combine certain components, or have different component arrangements. In the embodiments of this invention, the device includes, but is not limited to, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the embodiments of this application described and / or claimed herein.

[0068] The device 300 may include a processor 310, a memory 320, and a communication unit 330. These components communicate via one or more buses. Those skilled in the art will understand that the server structure shown in the figure does not constitute a limitation of the present invention. It may be a bus topology or a star topology, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0069] The memory 320 can be used to store execution instructions of the processor 310. The memory 320 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. When the execution instructions in the memory 320 are executed by the processor 310, the device 300 is able to perform some or all of the steps in the above method embodiments.

[0070] The processor 310 serves as the control center of the storage device, connecting various parts of the electronic device via various interfaces and lines. It executes software programs and / or modules stored in the memory 320, and calls data stored in the memory to perform various functions of the electronic device and / or process data. The processor can be composed of integrated circuits (ICs), such as a single packaged IC or multiple packaged ICs with the same or different functions connected together. For example, the processor 310 may consist only of a central processing unit (CPU). In this embodiment of the invention, the CPU may have a single processing core or include multiple processing cores.

[0071] The communication unit 330 is used to establish a communication channel, enabling the storage device to communicate with other devices. It can receive user data sent by other devices or send user data to other devices.

[0072] The present invention also provides a computer medium, wherein the computer medium may store a program, which, when executed, may include some or all of the steps provided in the embodiments of the present invention. The medium may be a magnetic disk, an optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0073] Those skilled in the art will clearly understand that the techniques in the embodiments of the present invention can be implemented using software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solutions in the embodiments of the present invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a medium such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, or any other medium capable of storing program code. It includes several instructions to cause a computer device (which may be a personal computer, a server, or a second device, network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0074] The same or similar parts between the various embodiments in this specification can be referred to mutually. In particular, the device embodiments are basically similar to the method embodiments, so the description is relatively simple, and the relevant parts can be referred to the description in the method embodiments.

[0075] In the embodiments provided by this invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between systems or modules may be electrical, mechanical, or other forms.

[0076] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0077] In addition, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0078] Although the present invention has been described in detail with reference to the accompanying drawings and preferred embodiments, the present invention is not limited thereto. Various equivalent modifications or substitutions can be made to the embodiments of the present invention by those skilled in the art without departing from the spirit and essence of the invention, and such modifications or substitutions should all be within the scope of the present invention. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should also be covered within the protection scope of the present invention.

Claims

1. A method for analyzing line misoperation, characterized in that, include: The host signal injection unit is sequentially connected to multiple circuit loops to be tested; The host configures a unique composite signal feature for each of the line loops. The composite signal feature includes a specific frequency hopping sequence assigned to each loop, a unique pseudo-random code, and a time-division injection time slot plan. The host injects the composite signal characteristics corresponding to each loop into the connected power lines according to the time slot plan; The slave device detects signals from the power line in a non-contact manner at the point to be tested, and extracts frequency hopping sequence features and pseudo-random code features from the signals to form a detection fingerprint; The detected fingerprint is compared with the composite signal features configured by the host for each circuit, and the physical location of the test point is determined to match which circuit based on the comparison result.

2. The method according to claim 1, characterized in that, The host signal injection unit is sequentially connected to multiple circuit loops to be tested, including: The host signal injection unit is coupled to the conductors of each circuit individually through magnetic coupling. The magnetic coupling method is achieved by a coupling clamp with an open magnetic core, which is clamped onto the insulating outer sheath of the wire during operation.

3. The method according to claim 1, characterized in that, The host configures a unique composite signal characteristic for each of the said line loops, including: A unique frequency hopping sequence is generated for each line loop. The frequency hopping sequence consists of multiple preset, non-contiguous frequency points arranged in a predetermined order, and the frequency hopping sequences of different loops are different in terms of frequency points or arrangement order. Each line loop is assigned a unique pseudo-random code sequence, which has sharp autocorrelation characteristics and low cross-correlation. Each line loop is assigned a unique transmit time slot, so that the host can inject signals consisting of a combination of frequency hopping sequence and pseudo-random code sequence into different loops in different time slots.

4. The method according to claim 1, characterized in that, The host injects the composite signal characteristics corresponding to each loop into the connected power lines according to the time slot plan, including: The host computer uses a time-division multiplexing method to transmit carrier signals one frequency point at a time within the transmission time slot allocated to each loop, according to the frequency points and order specified by the frequency hopping sequence generated for that loop. At each frequency point, the host computer modulates the carrier signal using the pseudo-random code sequence allocated to that loop and then injects it.

5. The method according to claim 1, characterized in that, The slave device detects signals from the power line at the test point in a non-contact manner, and parses frequency hopping sequence features and pseudo-random code features from the signals to form a detection fingerprint, including: The received signal is subjected to time-frequency analysis to identify frequency components in the signal whose intensity exceeds a preset threshold and their time sequence of occurrence, thereby obtaining the measured frequency hopping sequence; Using multiple candidate pseudo-random code sequences pre-agreed with the host, sliding correlation operations are performed on the signal respectively, and the peak value exceeding the correlation peak threshold in the operation result is identified. The pseudo-random code sequence that generates the peak value is determined as the code feature carried in the signal.

6. The method according to claim 5, characterized in that, Using multiple candidate pseudo-random code sequences pre-agreed with the host, sliding correlation operations are performed on the signal, and peak values ​​exceeding the correlation peak threshold in the operation results are identified. The pseudo-random code sequence that generates the peak value is determined as the code feature carried in the signal, including: Each candidate pseudo-random code sequence is selected sequentially, and the cross-correlation values ​​between the sequence and the received signal at multiple sliding time positions are calculated to form a set of correlation results. From the relevant results, the maximum value is extracted as the relevant peak value of the current candidate code sequence; The correlation peaks calculated from all candidate code sequences are compared with a preset peak threshold. If there is a single candidate code sequence whose correlation peak exceeds the peak threshold, and the ratio of the peak value to the second peak value exceeds the preset signal-to-noise ratio threshold, then the candidate code sequence is determined to be a code feature carried in the signal.

7. The method according to claim 1, characterized in that, The detected fingerprint is compared with the composite signal features configured by the host for each circuit. Based on the comparison result, it is determined which circuit the physical location of the test point matches, including: A multi-dimensional joint decision algorithm is adopted, which is based on a weighted score of multiple feature parameters extracted from the detected fingerprint. The feature parameters include at least the frequency hopping sequence matching degree, the pseudo-random code correlation peak intensity, and the signal received strength. Calculate the overall matching score between the detected fingerprint and the composite signal features configured by the host for each line loop; The highest comprehensive matching score is compared with a preset decision threshold. If the score exceeds the decision threshold, it is determined that the current test point matches the circuit corresponding to that score.

8. A line misoperation analysis system, characterized in that, include: The loop connection module is used to sequentially establish connections between the host signal injection unit and multiple circuit loops to be tested; The signal configuration module is used by the host to configure a unique composite signal feature for each of the line loops. The composite signal feature includes a specific frequency hopping sequence assigned to each loop, a unique pseudo-random code, and a time-division injection time slot plan. The signal injection module is used by the host to inject the composite signal characteristics corresponding to each loop into the connected power lines according to the time slot plan. The signal detection module is used to detect signals from the power line in a non-contact manner at the test point, and to parse the frequency hopping sequence features and pseudo-random code features from the signals to form a detection fingerprint; The signal matching module is used to compare the detected fingerprint with the composite signal features configured by the host for each circuit, and determine which circuit the physical location of the test point matches based on the comparison result.

9. A line misconnection analysis device, characterized in that, include: The memory is used to store the circuit error analysis program; A processor is configured to implement the steps of the line misoperation analysis method as described in any one of claims 1-7 when executing the line misoperation analysis program.

10. A computer-readable medium storing a computer program, characterized in that, The readable medium stores a line misconnection analysis program, which, when executed by a processor, implements the steps of the line misconnection analysis method as described in any one of claims 1-7.

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