A power carrier high frequency channel test system

Abstract

This invention discloses a high-frequency channel testing system for power line carrier circuits, belonging to the field of power system testing technology. It includes a delay characteristic detection module, a signal stability evaluation module, an adaptive time interval calculation module, a frequency step control module, and a weighting coefficient adjustment module. This invention avoids the possibility of erroneous sampling during signal transition phases, thus improving measurement accuracy compared to traditional methods and ensuring high reliability of test results. Through the collaborative work of the two core modules, dynamic optimization of testing efficiency is achieved. It continuously seeks optimal testing efficiency while ensuring accuracy without manual intervention, demonstrating a high level of intelligence. The traceability of the parameters in this invention not only facilitates system debugging, maintenance, and optimization but also provides crucial confidence assurance in application areas such as power system protection, where reliability requirements are extremely high.

Description

Technical Field

[0001] This invention relates to the field of power system testing technology, specifically to a power line carrier high-frequency channel testing system. Background Technology

[0002] In the commissioning and maintenance of multiplexed carrier channels for power grid line protection services, traditional testing methods use fixed time intervals for frequency switching and measurement, which cannot adapt to the differences in delay characteristics of different high-frequency channels. When the delay characteristics of high-frequency channels change, the fixed measurement time interval will result in: if the measurement interval is too short, the signal will be sampled before it is stable, resulting in inaccurate measurement; if the measurement interval is too long, the testing time will be wasted and work efficiency will be reduced.

[0003] Existing technologies lack the ability to perceive the delay characteristics of high-frequency channels in real time, and cannot dynamically adjust the measurement strategy according to the actual channel conditions, making it difficult to achieve the optimal balance between measurement accuracy and efficiency.

[0004] The technical problem to be solved by this invention is how to achieve adaptive adjustment of the measurement time interval during the high-frequency channel test of power line carrier, so as to balance measurement accuracy and test efficiency.

[0005] The information disclosed in the background section above 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 a power line carrier high-frequency channel testing system to solve the problems mentioned in the background art.

[0007] The technical solution of the present invention includes: a delay characteristic detection module, used to send a probe signal to a high-frequency channel to calculate the channel delay parameters;

[0008] The signal stability evaluation module is used to collect the signal amplitude of the high-frequency channel in order to calculate the signal stabilization time and signal stability index.

[0009] An adaptive time interval calculation module is used to calculate an adaptive measurement time interval based on the channel delay parameter, the signal stabilization time, and a preset adaptive weighting coefficient.

[0010] The frequency step control module is used to determine the adaptive step coefficient based on the channel delay parameter and the signal stability index, and calculate the next test frequency in combination with the current test frequency.

[0011] The weighting coefficient adjustment module is used to calculate the test efficiency index, and when the test efficiency index is lower than the preset efficiency threshold, it adjusts the adaptive weighting coefficient based on the preset channel delay reference time and the preset signal stability reference time.

[0012] Preferably, the delay characteristic detection module calculates the channel delay parameter in the following manner:

[0013] For each detection with a preset number of sampling times, the transmission time and reception time of the detection signal are recorded, and the time difference between the two is calculated; the time differences of all detection times are arithmetically averaged to generate the channel delay parameter.

[0014] Preferably, the signal stability evaluation module calculates the signal stability index in the following manner:

[0015] S11. Collect the amplitude of a continuous signal at a preset number of sampling points;

[0016] S12. For each pair of adjacent signal amplitudes, calculate the absolute value of the difference between them and divide it by the amplitude of the previous signal in the pair to obtain a series of continuous rates of change.

[0017] S13. The series of continuous rates of change are arithmetically averaged to generate the signal stability index.

[0018] Preferably, the signal stability assessment module is further used to determine the signal stabilization time by comparing the signal stability index with a preset stability threshold and determining the time difference between the start of measurement and the moment when the signal stability index first falls below the stability threshold as the signal stabilization time.

[0019] Preferably, the adaptive time interval calculation module calculates the adaptive measurement time interval in the following manner:

[0020] S21. Multiply the channel delay parameter by a preset delay weighting coefficient to obtain a first product;

[0021] S22. Multiply the signal stabilization time by a preset stabilization time weighting coefficient to obtain a second product;

[0022] S23. Multiply the preset fixed safety margin by the preset safety margin weighting coefficient to obtain the third product;

[0023] S24. Add the first product, the second product, and the third product together to generate the adaptive measurement time interval.

[0024] Preferably, the weighting coefficient adjustment module is used to calculate the test efficiency index, and the calculation method is as follows:

[0025] S31. Count the number of valid measurements and the total number of measurements that satisfy the signal stability index below the stability threshold, and calculate the first ratio between the two.

[0026] S32. Calculate the theoretical total test time based on the preset number of test frequency points and the preset fixed measurement interval;

[0027] S33. Accumulate the adaptive measurement time intervals used in each measurement to obtain the actual total test time; calculate the second ratio of the theoretical total test time to the actual total test time.

[0028] S34. Multiply the first ratio by the second ratio to generate the test efficiency index.

[0029] Preferably, when the test efficiency index is lower than the preset efficiency threshold, the weight coefficient adjustment module adjusts the adaptive weight coefficient in the following way:

[0030] S41. Compare the channel delay parameter with the preset channel delay reference time to obtain a first sign;

[0031] S42. Based on the first symbol, the preset learning rate, and the test efficiency index, calculate and generate a first adjustment amount, and add it to the latency weight coefficient;

[0032] S43. Compare the signal stabilization time with the preset signal stabilization reference time to obtain a second symbol;

[0033] S44. Based on the second symbol, the preset learning rate, and the test efficiency index, calculate and generate a second adjustment amount, and add it to the stable time weight coefficient.

[0034] Preferably, the frequency step control module determines the next test frequency by comparing the channel delay parameter and the signal stability index with multiple preset threshold pairs to select the matching adaptive step coefficient from a preset coefficient set; multiplying the adaptive step coefficient with a preset base frequency step value, and adding the product to the current test frequency to generate the next test frequency.

[0035] Preferably, the number of sampling times of the detection signal and the basic frequency step value are determined based on the power industry standard DL / T1520-2016; the stability threshold is determined based on the power line carrier communication standard GB / T16837-2016; and the fixed safety margin is preset based on engineering experience.

[0036] This invention provides an improved high-frequency channel testing system for power line carrier circuits, which has the following improvements and advantages compared to the prior art:

[0037] 1. This invention avoids the possibility of incorrect sampling during the signal transition phase, thereby improving the measurement accuracy compared to traditional methods and ensuring the high reliability of the test results;

[0038] 2. Through the collaborative work of the two core modules, dynamic optimization of testing efficiency was achieved;

[0039] 3. The weight coefficient adjustment module of this invention endows the system with unprecedented autonomous learning and optimization capabilities. The closed-loop feedback and self-correction mechanism enable the system to automatically adapt to various power lines with different delay and interference characteristics, from low-voltage distribution networks to high-voltage transmission lines. Without manual intervention, it can continuously seek the optimal testing efficiency while ensuring accuracy, demonstrating a high level of intelligence. Attached Figure Description

[0040] The present invention will be further explained below with reference to the accompanying drawings and embodiments:

[0041] Figure 1 This is a flowchart of the power line carrier high-frequency channel test system of the present invention. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0043] Example 1:

[0044] Please see Figure 1 The present invention provides a technical solution for a power line carrier high-frequency channel testing system, comprising: a delay characteristic detection module, used to send a probe signal to the high-frequency channel to calculate the channel delay parameters;

[0045] The signal stability assessment module is used to collect the signal amplitude of the high-frequency channel in order to calculate the signal settling time and signal stability index.

[0046] The adaptive time interval calculation module calculates the adaptive measurement time interval based on the channel delay parameter, signal settling time, and preset adaptive weighting coefficients.

[0047] The frequency stepping control module determines the adaptive stepping coefficient based on the channel delay parameters and signal stability indicators, and calculates the next test frequency in combination with the current test frequency.

[0048] The weighting coefficient adjustment module is used to calculate the test efficiency index and, when the test efficiency index is lower than the preset efficiency threshold, adjust the adaptive weighting coefficient based on the preset channel delay reference time and the preset signal stabilization reference time.

[0049] In this embodiment, intelligent adaptive control of the power line carrier channel testing process is achieved through the precise coordination of its internal functional modules. The delay characteristic detection module, signal stability evaluation module, adaptive time interval calculation module, frequency step control module, and weight coefficient adjustment module in the system constitute a closed-loop dynamic optimization system. This system dynamically generates the optimal test time interval and frequency step strategy by sensing the delay and stability characteristics of the channel in real time, which solves the inherent contradiction between accuracy and efficiency in traditional fixed interval testing methods when facing variable channel environments. This complete system architecture constitutes the technical foundation for the transformation to an intelligent and adaptive channel characteristic representation paradigm.

[0050] Example 2

[0051] The delay characteristic detection module calculates the channel delay parameters in the following way:

[0052] For each detection with a preset number of sampling times, the transmission and reception times of the detection signal are recorded, and the time difference between the two is calculated. The time differences of all detection times are arithmetically averaged to generate the channel delay parameter.

[0053] In this embodiment, the delay characteristic detection module performs a crucial initial task: accurately quantifying the inherent signal propagation delay of the high-frequency channel. This module provides a reliable benchmark parameter for all subsequent adaptive calculations by injecting a series of probe signals into the channel and performing rigorous timing analysis. The calculation method is derived from the mean filtering principle in statistics. The technical motivation is that by performing multiple independent delay measurements and arithmetically averaging the results, it is possible to effectively smooth out and eliminate random errors introduced by sudden interference in the power line environment, thereby obtaining a high-confidence average delay time that represents the true physical characteristics of the channel, ensuring that the decision-making basis of the subsequent adaptive strategy is robust and accurate.

[0054] The delay characteristic detection module uses the following delay detection model to calculate the channel delay parameters. :

[0055]

[0056] in, This indicates the average delay time of a high-frequency channel. The subscript "channel" explicitly states that this parameter is an inherent property of the channel. This indicates the total number of times the detection signal was sampled. Its value is set according to the power industry standard DL / T1520-2016 to ensure the statistical validity of the measurement. Indicates the first The precise moment when the probe signal is confirmed by the receiver of the test system; the subscript "receive" indicates the reception event. The sampling sequence number; Indicates the first The precise time at which the probe signal is emitted by the test system's transmitter; the subscript `send` indicates the transmission event. The sampling sequence number has a value range of [1, N];

[0057] In practical applications, the delay characteristic detection module sends a signal before each test frequency switch. The module detects a signal; it precisely records the nanosecond-level timestamps of each transmission and reception, calculating 10 independent delay samples, such as [14.2, 15.1, 14.8, 15.3, 14.9, 15.2, 14.7, 15.4, 14.6, 15.8] ms; the module sums these sample values ​​and divides by 10 to obtain the average delay. ms; this calculated parameter As a precise and stable channel characteristic indicator, the number of times the probe signal is sampled is immediately transmitted to the adaptive time interval calculation module and the frequency stepping control module. The direct technical effect is that it provides a first-hand, high-precision decision-making basis for the system to dynamically adjust the measurement waiting time and sweep rate, ensuring the effectiveness of subsequent adaptive algorithms. The core adjustable parameter in this model is the number of times the probe signal is sampled. The recommended value of 10, which follows the power industry standard DL / T1520-2016, is determined to be a balance between measurement accuracy and test time cost: fewer samplings may not effectively filter out random noise, while too many samplings will unnecessarily prolong test preparation time.

[0058] Example 3

[0059] The signal stability assessment module calculates the signal stability index in the following ways:

[0060] S11. Collect the amplitude of a continuous signal at a preset number of sampling points;

[0061] S12. For each pair of adjacent signal amplitudes, calculate the absolute value of the difference between them and divide it by the amplitude of the previous signal in the pair to obtain a series of continuous rates of change.

[0062] S13. Take the arithmetic mean of a series of continuous rates of change to generate a signal stability index;

[0063] The signal stability assessment module is also used to determine the signal stabilization time. The determination method is as follows: the signal stability index is compared with a preset stability threshold, and the time difference between the start of measurement and the moment when the signal stability index first falls below the stability threshold is determined as the signal stabilization time.

[0064] In this embodiment, the core function of the signal stability assessment module is to quantitatively determine whether the test signal has entered a steady state after frequency switching, and to accurately calculate the time required to reach that steady state. This module analyzes the minute fluctuations in the amplitude of continuous sampling, providing a key criterion for the system to decide when to perform effective measurements, thereby avoiding measurement inaccuracies caused by sampling during the signal transition phase. This stability index... The calculation formula originates from the steady-state determination theory in the field of signal processing. The technical motivation is to establish a quantitative and objective index to describe the severity of signal amplitude fluctuations during transient response; only when the fluctuations converge to a sufficiently small range, i.e. Only when the signal falls below a recognized threshold can it be considered stable, and only then can the measurement be considered valid and repeatable.

[0065] The signal stability assessment module uses the following model to calculate the signal stability index. :

[0066]

[0067] in, This is a dimensionless signal stability index; the subscript "stability" indicates that this is a stability parameter. This is the total number of consecutive sampling points used to evaluate stability; its value is selected based on signal processing theory, with a typical value of 5. For the first The signal amplitude at each sampling point, subscript This refers to the sampling sequence number within this evaluation period; The sampling sequence number has a value range of [1, M-1].

[0068] Based on this stability index, the signal settling time The calculation model is as follows:

[0069]

[0070] in, This indicates the signal settling time; the subscript "settle" indicates stability. Indicators of signal stability First time below the preset stability threshold The moment; This indicates the initial time at which amplitude measurement begins at the current frequency;

[0071] During a single frequency measurement, for example at 40kHz, the signal stability assessment module continuously collects data. The module calculates four continuous rates of change based on a formula, given several amplitude points, such as [-45.2, -45.1, -45.15, -45.12, -45.14] dBm, and then obtains the average value. The module compares this result with a preset stability threshold. Comparison; due to The module determines that the signal has reached stability; assuming this condition is met for the first time at the 3rd sampling point, and the sampling interval is 10ms, then the settling time is... The timeframe was set at 20ms; the direct technical effect of this process is that the system can confirm the signal's stable state in a data-driven manner, ensuring that the amplitude of each formal measurement is acquired during the signal's steady-state period, thereby improving measurement accuracy and providing another crucial real-time parameter for calculating the dynamic measurement interval. The stability threshold here The value is 0.01, which comes from the national standard GB / T16837-2016 "Power Line Carrier Communication Equipment". This standard defines the acceptable range of signal fluctuations in power line carrier communication, ensuring the authority and universality of the stability criterion of this invention.

[0072] Example 4

[0073] The adaptive time interval calculation module calculates the adaptive measurement time interval in the following way:

[0074] S21. Multiply the channel delay parameter by the preset delay weight coefficient to obtain the first product;

[0075] S22. Multiply the signal settling time by the preset settling time weighting coefficient to obtain the second product;

[0076] S23. Multiply the preset fixed safety margin by the preset safety margin weighting coefficient to obtain the third product;

[0077] S24. Add the first product, the second product, and the third product together to generate an adaptive measurement time interval;

[0078] The adaptive time interval calculation module is the central computing unit for intelligent decision-making in the system. Through a weighted summation model, it integrates the dynamic characteristics of the channel and the necessary safety redundancy into an optimal measurement waiting time. This module integrates real-time data from different modules and aims to generate an optimized time interval that ensures measurement accuracy while minimizing the total test duration. This calculation model originates from the feedforward control concept in control system theory. The technical motivation is to create a calculation formula that can dynamically respond to the actual channel conditions, replacing the fixed, lengthy waiting intervals based on worst-case assumptions in traditional testing methods.

[0079] The adaptive time interval calculation module uses the following model to calculate the adaptive measurement time interval. :

[0080]

[0081] In the formula, The term "interval" represents the final calculated adaptive measurement time interval. This is a dimensionless delay weighting coefficient used to adjust the proportion of channel delay in the total interval. It is the average channel delay time provided by the delay characteristic detection module; This is the settling time weighting coefficient, which is dimensionless and used to adjust the proportion of the signal settling time in the total interval. It is the signal stabilization time calculated by the signal stability assessment module; This is a dimensionless safety margin weighting coefficient used to adjust the effect of a fixed safety margin. It is a preset fixed safety margin time used to compensate for potential unmodeled delays or system response errors;

[0082] Received ms and After ms, the adaptive time interval calculation module uses its internally set initial weight coefficients. and fixed safety margin ms, perform calculation:

[0083]

[0084] This calculation means that at the current 40kHz frequency, the system will wait precisely 66.5ms after switching frequencies before performing the next measurement. The direct technical effect of this dynamic calculation is a significant improvement in testing efficiency compared to the traditional fixed interval of 100ms or even longer. On high-quality channels—those with low latency and fast stability—this interval becomes very short, reducing the total testing time by 30-50%. On poor-quality channels, the interval automatically lengthens to ensure measurement accuracy, achieving an intelligent balance between efficiency and accuracy. The weighting coefficients in this model... and fixed margin The initial value setting has a clear theoretical or engineering basis: delay weighting coefficient The initial value is 2.5, derived from the oversampling concept of Shannon's sampling theorem; the steady-state time weighting coefficient... The initial value is 1.2, based on the safety margin principle of control theory; safety margin weighting coefficient. Initial value is 1.0; fixed safety margin The value is set to 5ms, which is an engineering value derived from extensive field testing experience in power systems.

[0085] Example 5

[0086] The weighting coefficient adjustment module is used to calculate the test efficiency index, and its calculation method is as follows:

[0087] S31. Count the number of valid measurements and the total number of measurements that meet the signal stability index below the stability threshold, and calculate the first ratio between the two.

[0088] S32. Calculate the theoretical total test time based on the preset number of test frequency points and the preset fixed measurement interval;

[0089] S33. Accumulate the adaptive measurement time intervals used in each measurement to obtain the total actual test time; calculate the second ratio of the theoretical total test time to the actual total test time.

[0090] S34. Multiply the first ratio by the second ratio to generate a test efficiency index.

[0091] When the test efficiency index is lower than the preset efficiency threshold, the weight coefficient adjustment module adjusts the adaptive weight coefficient in the following ways:

[0092] S41. Compare the channel delay parameter with the preset channel delay reference time to obtain the first symbol;

[0093] S42. Based on the first symbol, the preset learning rate, and the test efficiency index, calculate and generate the first adjustment amount, and add it to the latency weight coefficient;

[0094] S43. Compare the signal stabilization time with the preset signal stabilization reference time to obtain the second symbol;

[0095] S44. Based on the second symbol, the preset learning rate, and the test efficiency index, calculate and generate the second adjustment amount, and add it to the steady-state time weight coefficient.

[0096] In this embodiment, the weight coefficient adjustment module is the core of the system's long-term autonomous learning and optimization, and its function is performance monitoring and automatic parameter tuning. This module continuously evaluates the overall efficiency of the testing process, and when the efficiency is not up to standard, it initiates a feedback-based adjustment algorithm to fine-tune the core weight parameters in the adaptive time interval calculation model, enabling the system to better adapt to the characteristics of specific lines or specific interference environments; test efficiency indicators The design is a comprehensive performance evaluation method that takes into account both the quality of measurement, i.e., the effective measurement rate and the speed, i.e., the time saving rate; the adaptive adjustment algorithm of the weight coefficients is derived from the incremental learning idea in machine learning, and the core motivation is to give the system an experience-based iterative optimization capability.

[0097] The weighting coefficient adjustment module uses the following model to calculate the test efficiency index. :

[0098]

[0099] In the formula, It is a dimensionless test efficiency index, and the subscript efficiency indicates efficiency; To meet the requirements during the testing process The total number of valid measurements, with the subscript "valid" indicating that the measurement was valid. The total number of test attempts is indicated by the subscript "total". The term "fixed" represents the theoretical total time required to complete the same number of tests at the same frequency using the traditional fixed interval method. The actual time consumed by using the adaptive interval method of this invention is represented by the subscript actual;

[0100] when When the value falls below a preset threshold of 0.8, the adaptive adjustment algorithm for the weight parameters is triggered.

[0101]

[0102]

[0103]

[0104] In the formula, These are the adjusted new weight coefficients, with the subscript "new" indicating a new one; These are the old weighting coefficients before adjustment, with the subscript "old" indicating the old ones; The learning rate is dimensionless and controls the step size of each adjustment; a typical value is 0.1. This is a sign function, taking values ​​of -1, 0, or 1; These are the preset reference delay time, reference settling time, and reference measurement error rate, which serve as benchmarks for performance evaluation. The subscript ref indicates a reference.

[0105] In the formula, the measurement error rate Used to quantize within the current adaptive measurement time interval The unreliability of the measurement results is calculated as follows: when performing multiple measurements, statistically analyze those measurements that, even while waiting... Subsequently, its signal stability index It still failed to fall below the preset stability threshold. The number of measurements taken is recorded as the number of invalid measurements. The number of invalid measurements compared to the total number of measurement attempts. The ratio of these values ​​is the measurement error rate. The calculation formula is:

[0106]

[0107] This ratio reflects the current safety margin. The adequacy of the setting; if this value is too high, it means that the current safety margin is insufficient to cope with random interference in the channel or unmodeled system characteristics, leading to an increased measurement failure rate; and This is a maximum acceptable error rate threshold preset by the system designer, used to adjust the safety margin weights. The basis for decision-making;

[0108] In a complex channel environment with high latency and strong interference, the system may detect... The value was measured in milliseconds, and due to interference, multiple measurements could not stabilize within a short period of time, resulting in... The calculated value is 0.7, which is below the threshold of 0.8; the weighting coefficient adjustment module is activated; it compares the measured 50ms delay with the reference value. ms comparison, The result is 1; the new delay weight is calculated as follows:

[0109]

[0110] Similarly, for and Adjustments are made; the direct technical effect of these adjustments is that the system optimizes its operating parameters based on measured performance degradation through an iterative feedback loop, increasing the weight of factors such as latency and settling time, thus improving the subsequent calculations. It will be longer, for example, from 150ms to 205.65ms; this mechanism enables the system to automatically switch to a more conservative and accuracy-focused testing mode when facing harsh environments, dynamically finding the most suitable testing strategy on lines with different characteristics, greatly improving the system's intelligence and environmental adaptability; the efficiency threshold of 0.8 here is a key operational benchmark, below which it indicates that the adaptive strategy has failed to bring the expected performance gain and self-optimization is required.

[0111] Example 6

[0112] The frequency step control module determines the next test frequency in the following way: it compares the channel delay parameters and signal stability indicators with multiple sets of preset threshold pairs to select a matching adaptive step coefficient from the preset coefficient set; it multiplies the adaptive step coefficient with the preset base frequency step value and adds the product to the current test frequency to generate the next test frequency.

[0113] The number of sampling times for the detection signal and the fundamental frequency step value are determined based on the power industry standard DL / T1520-2016; the stability threshold is determined based on the power line carrier communication standard GB / T16837-2016; and the fixed safety margin is preset based on engineering experience.

[0114] The frequency stepping control module achieves intelligent allocation of test resources by dynamically adjusting the frequency step size during the frequency sweep process. Based on the channel quality of the current frequency point, the module determines whether to perform a rapid jump or fine probing in the next step, aiming to efficiently sweep through high-quality frequency bands while conducting more intensive probing in complex or edge frequency bands, thereby optimizing the time efficiency of the entire frequency sweep process. The technical motivation is that the characteristics of power line carrier channels are not uniformly distributed across different frequency bands, so it is necessary to dynamically adjust the resolution of the frequency sweep based on real-time measurement results to achieve fine-grained management of test time.

[0115] The frequency stepping control module is used to determine the adaptive stepping coefficient. Its rule set divides channel quality into four levels, with the specific correspondence as follows:

[0116] when Time (corresponding to excellent quality) The value is 2.0;

[0117] when Time (corresponding to good quality) The value is 1.5;

[0118] when Time (corresponding to standard quality) The value is 1.0;

[0119] In other cases (corresponding to poorer or more complex quality). The value is 0.5;

[0120] In the formula, These are dimensionless adaptive step coefficients, with the subscript `adapt` indicating adaptation; these threshold pairs are derived from empirical analysis of a large amount of power line channel data, and they will apply specific... and The numerical range is correlated with the optimal scan resolution;

[0121] Next test frequency The calculation model is as follows:

[0122]

[0123] in, The next frequency point to be tested is in kHz, and the subscript next indicates the next one. The current frequency being tested is in kHz, and the subscript "current" indicates the current frequency. The preset base frequency step value is in kHz and can be selected as 1, 5, or 10, based on the DL / T1520-2016 standard.

[0124] Assuming the current testing frequency kHz, basic step kHz; measured by the system and The frequency step control module compares these values ​​with internal rules and determines the channel quality as "Good," therefore selecting... Therefore, the frequency of the next test is calculated as follows:

[0125]

[0126] The direct technical effect of this process is that, in frequency bands with good channel quality, the system sweeps frequencies with a step size of 1.5 times the base size, significantly accelerating the testing process; conversely, if measurements are taken at another frequency point... The system will select The step size is reduced to 2.5kHz, allowing for a more precise scan in this complex frequency band. This intelligent stepping mechanism greatly improves the overall efficiency of full-band scanning while ensuring that important channel features are not missed.

[0127] The reliability and practicality of this invention are ensured by adhering to industry standards and engineering practices; the number of sampling times of the detection signal. and fundamental frequency step value The selection of parameters strictly followed the provisions of the power industry standard DL / T1520-2016, ensuring the consistency of test methods and the comparability of data; stability threshold The determination of this is based on the national standard for power line carrier communication.

[0128] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A power line carrier high-frequency channel testing system, characterized in that, include: The delay characteristic detection module is used to send a probe signal to the high-frequency channel in order to calculate the channel delay parameters; The signal stability evaluation module is used to collect the signal amplitude of the high-frequency channel in order to calculate the signal stabilization time and signal stability index. An adaptive time interval calculation module is used to calculate an adaptive measurement time interval based on the channel delay parameter, the signal stabilization time, and a preset adaptive weighting coefficient. The frequency step control module is used to determine the adaptive step coefficient based on the channel delay parameter and the signal stability index, and calculate the next test frequency in combination with the current test frequency. The weight coefficient adjustment module is used to calculate the test efficiency index and, when the test efficiency index is lower than the preset efficiency threshold, adjust the adaptive weight coefficient based on the preset channel delay reference time and the preset signal stability reference time. The signal stability evaluation module calculates the signal stability index in the following manner: S11. Collect the amplitude of a continuous signal at a preset number of sampling points; S12. For each pair of adjacent signal amplitudes, calculate the absolute value of the difference between them and divide it by the amplitude of the previous signal in the pair to obtain a series of continuous rates of change. S13. The series of continuous rates of change are arithmetically averaged to generate the signal stability index; The signal stability assessment module is also used to determine the signal stabilization time. The determination method is as follows: the signal stability index is compared with a preset stability threshold, and the time difference between the start of measurement and the moment when the signal stability index first falls below the stability threshold is determined as the signal stabilization time. The adaptive time interval calculation module calculates the adaptive measurement time interval in the following manner: S21. Multiply the channel delay parameter by a preset delay weighting coefficient to obtain a first product; S22. Multiply the signal stabilization time by a preset stabilization time weighting coefficient to obtain a second product; S23. Multiply the preset fixed safety margin by the preset safety margin weighting coefficient to obtain the third product; S24. Add the first product, the second product, and the third product together to generate the adaptive measurement time interval; The signal stability assessment module uses the following model to calculate the signal stability index. : ； in, This is a dimensionless signal stability index; the subscript "stability" indicates that this is a stability parameter. This is the total number of consecutive sampling points used to evaluate stability; its value is selected based on signal processing theory, with a typical value of 5. For the first The signal amplitude at each sampling point; The sampling sequence number has a value range of [1, M-1]. Based on this stability index, the signal settling time The calculation model is as follows: ； in, This indicates the signal settling time; the subscript "settle" indicates stability. Indicators of signal stability First time below the preset stability threshold The moment; This indicates the initial time at which amplitude measurement begins at the current frequency; The adaptive time interval calculation module uses the following model to calculate the adaptive measurement time interval. : ； In the formula, The term "interval" represents the final calculated adaptive measurement time interval. This is a dimensionless delay weighting coefficient used to adjust the proportion of channel delay in the total interval. It is the average channel delay time provided by the delay characteristic detection module; This is the settling time weighting coefficient, which is dimensionless and used to adjust the proportion of the signal settling time in the total interval. It is the signal stabilization time calculated by the signal stability assessment module; This is a dimensionless safety margin weighting coefficient used to adjust the effect of a fixed safety margin. It is a preset fixed safety margin time used to compensate for potential unmodeled delays or system response errors.

2. The power line carrier high-frequency channel test system according to claim 1, characterized in that, The delay characteristic detection module calculates the channel delay parameter in the following manner: For each detection with a preset number of sampling times, the transmission time and reception time of the detection signal are recorded, and the time difference between the two is calculated; the time differences of all detection times are arithmetically averaged to generate the channel delay parameter.

3. The power line carrier high-frequency channel test system according to claim 2, characterized in that, The weighting coefficient adjustment module is used to calculate the test efficiency index, and the calculation method is as follows: S31. Count the number of valid measurements and the total number of measurements that satisfy the signal stability index below the stability threshold, and calculate the first ratio between the two. S32. Calculate the theoretical total test time based on the preset number of test frequency points and the preset fixed measurement interval; S33. Accumulate the adaptive measurement time intervals used in each measurement to obtain the actual total test time; calculate the second ratio of the theoretical total test time to the actual total test time. S34. Multiply the first ratio by the second ratio to generate the test efficiency index.

4. The power line carrier high-frequency channel test system according to claim 3, characterized in that, When the test efficiency index is lower than the preset efficiency threshold, the weighting coefficient adjustment module adjusts the adaptive weighting coefficient in the following way: S41. Compare the channel delay parameter with the preset channel delay reference time to obtain a first sign; S42. Based on the first symbol, the preset learning rate, and the test efficiency index, calculate and generate a first adjustment amount, and add it to the latency weight coefficient; S43. Compare the signal stabilization time with the preset signal stabilization reference time to obtain a second symbol; S44. Based on the second symbol, the preset learning rate, and the test efficiency index, calculate and generate a second adjustment amount, and add it to the stable time weight coefficient.

5. The power line carrier high-frequency channel test system according to claim 3, characterized in that, The frequency step control module determines the next test frequency by comparing the channel delay parameter and the signal stability index with multiple preset threshold pairs to select the matching adaptive step coefficient from the preset coefficient set; multiplying the adaptive step coefficient with a preset base frequency step value, and adding the product to the current test frequency to generate the next test frequency.

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