A channel quality detection method and system for an electric energy meter

Abstract

The present application relates to the technical field of communication detection, more particularly, the present application relates to a kind of channel quality detection method and system of electric energy meter, method includes: the multiple-source data of electric energy meter communication module in current service cycle is collected and preprocessed, and comprehensive quality index and time delay deviation index are obtained;According to the normalized degradation depth index and dynamic rate amplification index calculated from comprehensive quality index, and combined with time delay deviation index to build comprehensive risk index;Using comprehensive risk index dynamically adjusts the compensation amount when cumulative update, obtains adaptive cumulative state;Adaptive cumulative state is compared with dynamic alarm threshold, and according to the comparison result, execute hierarchical control action.The present application builds comprehensive risk index and dynamically adjusts compensation amount, so that the cumulative speed is automatically accelerated when serious degradation, significantly shortens response delay, while maintaining the inhibition ability to transient interference, improves the accuracy and timeliness of electric energy meter communication channel detection.

Description

Technical Field

[0001] This invention relates to the field of communication detection technology. More specifically, this invention relates to a method and system for detecting the channel quality of an electricity meter. Background Technology

[0002] In low-voltage distribution network areas, electricity meters need to interact with concentrators via communication links to complete data acquisition and control command execution. Frequent start-ups and shutdowns of load devices in the distribution area environment can easily cause transient interference to the communication link, leading to signal quality fluctuations. If channel quality cannot be effectively monitored, control commands may still be issued when the link is unreliable, resulting in command loss or execution timeouts. Therefore, real-time monitoring of the electricity meter's communication channel quality is crucial.

[0003] Existing methods for detecting channel quality in electricity meters mainly include the fixed threshold method and the cumulative calculation method. The cumulative calculation method suppresses normal fluctuations by successively accumulating the deviation between the current value and the reference value and deducting a fixed compensation amount. It only determines degradation when the deviation continues to accumulate in the same direction and exceeds the threshold. This method has advantages in resisting transient interference, but when the channel is severely degraded, because the compensation amount deducted each time is fixed, it takes multiple communication cycles to reach the alarm threshold, resulting in a large response delay.

[0004] Therefore, how to shorten the response delay when the channel is severely degraded is a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0005] To address the aforementioned technical problem of how to shorten response delay when the channel is severely degraded, the present invention provides solutions in the following aspects.

[0006] In the first aspect, a channel quality detection method for an electricity meter includes: Collect multi-source data from the communication module of the electricity meter during the current business cycle and preprocess it to obtain a comprehensive quality index reflecting the downlink channel quality and a delay deviation index reflecting the degree of link interaction congestion. The degradation depth and degradation rate of the current channel quality relative to the historical level are calculated based on the comprehensive quality index, and the normalized degradation depth index and dynamic rate amplification index are obtained respectively. The comprehensive danger index is constructed by combining the delay deviation index. The comprehensive danger index is used to characterize the urgency of channel degradation. The compensation amount during cumulative updates is dynamically adjusted using the comprehensive risk index, so that the compensation amount automatically decreases as the comprehensive risk index increases, thus obtaining the adaptive cumulative state of the current business cycle. The adaptive cumulative state is compared with the dynamic alarm threshold, and hierarchical control actions are performed on the communication module based on the comparison result.

[0007] Optionally, the process of collecting and preprocessing multi-source data includes: Collect the received signal strength indicator value, bit error statistics value, and the time interval from the completion of transmission to receiving the concentrator's acknowledgment reply within the current service cycle; A sliding window mid-range filtering algorithm is used to smooth the received signal strength indication value and the bit error statistics value. Based on the lower limit of the receiving sensitivity and the upper limit of the saturation preset in the communication module specification, the received signal strength is mapped to a dimensionless normalized value. Then, combined with the bit error statistics value, an equal-weight linear fusion strategy is used to construct a comprehensive quality index. The mean and standard deviation of the time interval from the completion of transmission to the receipt of the concentrator's acknowledgment reply in history are calculated using a sliding window. The difference between the real-time time interval from the completion of transmission to the receipt of the concentrator's acknowledgment reply and the mean is calculated, and then divided by the standard deviation to obtain the delay deviation index.

[0008] Optionally, the calculation of the normalized deterioration depth index includes: Calculate the decrease in the current business cycle comprehensive quality index relative to the arithmetic mean of several historical business cycle comprehensive quality indices, and divide this decrease by the average of the absolute values ​​of the differences between the comprehensive quality indices of adjacent historical cycles to obtain the normalized deterioration depth index.

[0009] Optionally, the calculation of the dynamic rate amplification index includes: The rate of deterioration is calculated by dividing the decline in the overall quality index of the current business cycle relative to the previous business cycle by the average absolute value of the difference in the overall quality index between adjacent historical cycles. The rate of deterioration is then transformed so that it approaches 0 during normal small fluctuations and increases significantly during sharp drops, resulting in a dynamic rate amplification index.

[0010] Optionally, the construction of the comprehensive risk index includes: The deviation intensity index is obtained by multiplying the normalized deterioration depth index and the dynamic rate amplification index; the deviation intensity index is then multiplied by an adjustment coefficient to obtain the comprehensive risk index; the adjustment coefficient is determined based on the magnitude of the time delay deviation index.

[0011] Optionally, obtaining the adaptive cumulative state includes: The adaptive cumulative state is obtained by adding the cumulative state value of the previous business cycle to the difference between the arithmetic mean of the comprehensive quality indicators of several historical business cycles and the comprehensive quality indicator of the current business cycle, then subtracting the compensation amount for dynamic adjustment, and then taking the maximum value between 0 and the obtained result; the compensation amount is determined based on the historical fluctuation range and the comprehensive risk index.

[0012] Optionally, determining the dynamic alarm threshold includes: The maximum allowable response time for key instructions specified in the communication protocol is obtained, divided by a fixed communication cycle to obtain the number of cycles to obtain the fourth parameter, the fourth parameter is multiplied by the first safety factor to obtain the alarm threshold, and the fourth parameter is multiplied by the second safety factor to obtain the emergency threshold.

[0013] Optionally, the step of performing hierarchical control actions on the communication module based on the comparison results includes: When the adaptive cumulative state is less than the alarm threshold, the quality is determined to be normal, and the current transmit power and retransmission strategy are maintained. When the adaptive cumulative status is greater than or equal to the alarm threshold and less than the emergency threshold, the quality is determined to be degraded, the transmission power is increased and the number of data retransmissions is increased, and the degraded status is reported. When the adaptive cumulative status exceeds the emergency threshold, the quality is deemed to be in an emergency, the pending fee control instructions and circuit breaker linkage signals are frozen, the system switches to the backup channel, the local safety power supply logic is activated, and an emergency alarm is reported.

[0014] In a second aspect, a channel quality detection system for an electricity meter includes a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the channel quality detection method for the electricity meter described in any one of the claims is implemented.

[0015] The present invention has the following beneficial effects: 1. This invention constructs a comprehensive danger index reflecting the urgency of channel degradation and uses this index to dynamically adjust the compensation amount during cumulative updates. The compensation amount automatically decreases or even approaches zero as the comprehensive danger index increases. Therefore, when severe channel degradation occurs, the adaptive cumulative state can quickly climb to the alarm threshold, fundamentally solving the technical problem of large response delays in severe degradation response caused by the traditional fixed compensation method which deducts a fixed value each time. Compared with existing technologies, this invention significantly shortens the detection and response time when the channel deteriorates rapidly while maintaining effective suppression of daily transient interference and normal fluctuations, improving the adaptability and reliability of the electricity meter communication link in harsh environments.

[0016] 2. This invention introduces a delay deviation index to coordinately adjust the intensity of signal degradation, enabling early warning when the link layer is congested but the physical layer signal is still acceptable. Combined with a hierarchical control action strategy, it achieves a step-by-step response from power boost to channel switching, ensuring the reliability of electricity meter communication and the safe execution of power control commands. Attached Figure Description

[0017] Figure 1 This is a flowchart of steps S1-S3 in a channel quality detection method for an energy meter according to an embodiment of the present invention. Detailed Implementation

[0018] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments.

[0019] Reference Figure 1 A method for detecting channel quality in an electricity meter includes steps S1-S3, as detailed below: S1: Collect multi-source data from the communication module of the electricity meter during the current service cycle and preprocess it to obtain the channel quality in the receiving direction of the electricity meter and the interaction response delay between the electricity meter and the concentrator.

[0020] Electricity meters operate in low-voltage distribution network areas with frequent load fluctuations, and the communication channel quality is affected by multiple factors such as transient interference, background noise, and link congestion. To accurately assess the channel status, it is necessary to obtain multi-dimensional data reflecting physical layer signal strength, data transmission reliability, and the degree of link layer interaction congestion.

[0021] First, through the data receiving interface of the electricity meter communication module, the received signal strength indicator value within the current business cycle is synchronously collected during regular meter reading and business communication to record the signal transmission attenuation status. Through the transmission error statistics unit of the communication module, the bit error statistics value within the current business cycle is synchronously collected to record the degree of data transmission damage. Through the protocol timer interface of the communication module, after each data frame is sent, the time interval from the completion of transmission to receiving the acknowledgment reply from the concentrator is synchronously recorded to characterize the degree of link interaction congestion.

[0022] Furthermore, by using the communication cycle timer of the main control unit of the electricity meter, with a fixed communication cycle as a unified time reference, the discretely collected received signal strength indication value, bit error statistics value, and the time interval from the completion of transmission to the receipt of the concentrator confirmation reply are mapped into an equally spaced time sequence, thereby eliminating the time misalignment caused by random fluctuations in the arrival time of service frames.

[0023] Then, all the collected data are preprocessed as follows: A sliding window mid-range filtering algorithm with a window size of 5 is used to smooth the received signal strength indication value and the bit error rate statistics. Then, based on the lower limit of receiver sensitivity and the upper limit of saturation preset in the communication module specifications, the received signal strength is mapped to a dimensionless normalized value. Simultaneously, combined with the bit error rate statistics, an equal-weighted linear fusion strategy is used to construct a comprehensive quality index that reflects the overall quality of the downlink channel in the direction of the electricity meter's receiver. A higher comprehensive quality index indicates a stronger downlink signal and a lower bit error rate, while a lower value indicates a poorer downlink performance.

[0024] A sliding window with a window size of 7 is used to calculate the mean and standard deviation of the time interval from the completion of data frame transmission to the receipt of an acknowledgment reply from the concentrator in historical data. The difference between the real-time time interval from the completion of transmission to the receipt of an acknowledgment reply from the concentrator and the mean is calculated, and then divided by the standard deviation to obtain a latency deviation index reflecting the interaction latency between the energy meter and the concentrator relative to its historical normal. A latency deviation index close to 0 indicates normal interaction latency, greater than 0 indicates that the current latency is significantly higher than the historical average, reflecting link congestion or busy conditions at the other end, and less than 0 indicates abnormally low latency.

[0025] After the above processing, transient pulses in the original sampled values ​​are effectively suppressed, multi-source data are strictly aligned in time, and the comprehensive quality index and time delay deviation index calculated above are both dimensionless unified indicators.

[0026] S2: Based on the comprehensive quality index and the delay deviation index, a comprehensive danger index reflecting the urgency of channel degradation is constructed, and the cumulative compensation amount is adjusted according to the comprehensive danger index to obtain the adaptive cumulative state of the current service cycle, so as to balance the response speed against transient interference and severe degradation.

[0027] Among existing methods for detecting channel quality in electricity meters, one approach sets a fixed threshold, which can easily misjudge transient interference as continuous degradation. Another approach accumulates the deviation and subtracts a fixed value to offset normal fluctuations, but the fixed subtraction amount results in slow accumulation and delayed response when severe degradation occurs. Furthermore, even if the physical layer signal is acceptable, control commands may still time out and fail when the link layer is severely congested, and traditional methods, relying solely on signal quality, cannot detect such risks.

[0028] Therefore, based on the comprehensive quality index and time delay deviation index calculated by S1 above, a comprehensive risk index is first constructed that can quantify the depth of deterioration, capture the rate of deterioration, and integrate the time delay deviation. Then, the compensation amount subtracted each time the state is updated is dynamically adjusted using this index: the higher the risk, the smaller the compensation amount (even close to zero), so that the accumulation speed is automatically accelerated; the lower the risk, the compensation amount is close to the historical normal fluctuation range, effectively filtering out daily interference.

[0029] The specific process for constructing the aforementioned comprehensive risk index is as follows: First, in order to quantify the urgency of channel quality degradation, we cannot only look at the difference between the current value and the historical benchmark. We also need to consider whether this degradation is a slow accumulation or a sharp drop. That is, we need to assess both the depth and rate of degradation at the same time.

[0030] The algorithm calculates the difference between the arithmetic mean of the overall quality indicators of several historical business cycles preceding the current business cycle and the overall quality indicator of the current business cycle, compares this difference with 0, and outputs the maximum value as the first parameter. This maximum value ensures that a positive difference is output only when the current quality is lower than the historical benchmark; if the quality is higher than the benchmark, a value of 0 is output, thus masking positive changes caused by signal recovery.

[0031] The mean of the absolute values ​​of the differences in the comprehensive quality indicators of adjacent business cycles across all business cycles, including the current business cycle and several previous historical business cycles, is further calculated as the second parameter.

[0032] The first parameter calculated above is further divided by the second parameter and the preset zero-prevention value to obtain the normalized degradation depth index for the current service cycle. The normalized degradation depth index reflects the unidirectional degradation depth of the downlink channel quality relative to its historical health level; the larger the value, the more severe the degradation.

[0033] Next, in addition to assessing the depth of the deterioration, it is also necessary to evaluate the speed at which this deterioration occurs. If quality drops sharply within one or two business cycles, the risks it may pose are far greater than those of a similar depth but a slow decline.

[0034] The difference between the comprehensive quality index of the previous service cycle and the current service cycle is calculated. A positive value indicates a quality decline, and the maximum value is compared with 0 to obtain the third parameter. The negative value is truncated to ensure that the third parameter is 0 when the quality recovers. The third parameter is divided by the second parameter to obtain the deterioration rate ratio relative to the historical fluctuation rate. After adding 1, the natural logarithm is taken so that the output is close to 0 during normal small fluctuations, while the nonlinearity of the logarithmic function makes the output significantly larger during large drops. Finally, 1 is added again to calculate the dynamic rate amplification index of the current service cycle. The dynamic rate amplification index reflects the instantaneous rate of downlink channel quality deterioration relative to the historical fluctuations. When the channel quality is stable or recovering, the third parameter is 0, and the dynamic rate amplification index is 1, with no amplification. When the channel deteriorates, the dynamic rate amplification index is greater than 1, and the faster the deterioration, the larger the dynamic rate amplification index, to achieve deterioration-specific amplification and avoid erroneous responses to favorable changes.

[0035] Furthermore, by multiplying the above-mentioned normalized deterioration depth index with the dynamic rate amplification index, we obtain the deviation intensity index for the current business cycle. This product combines the deterioration depth and deterioration rate: when the quality is stable or recovering, the deviation intensity index approaches 0; when the quality continues to deteriorate rapidly, the deviation intensity index increases significantly.

[0036] Secondly, while signal quality degradation is the primary risk, in actual operation, even if the signal strength is acceptable, if the interaction delay increases significantly due to link congestion, control commands may still time out and fail. Therefore, it is necessary to incorporate delay deviation indicators into the risk assessment system to coordinate the adjustment of signal degradation intensity.

[0037] When the interaction latency is within the historical normal level, the original signal risk assessment remains unchanged. When the interaction latency is significantly higher, indicating congestion or high traffic, the signal risk should be amplified to provide early warning. When the interaction latency is abnormally lower, indicating extremely smooth link operation, the signal risk should be appropriately reduced to avoid unnecessary alarms due to minor fluctuations. Simultaneously, the adjustment range should increase smoothly as the deviation increases, but it should not be amplified or reduced indefinitely; it should be limited to a reasonable range.

[0038] Based on the above logic, a comprehensive risk index is constructed, which satisfies the following relationship: In the formula, For the current business cycle The overall risk index, For the current business cycle Deviation strength index For the current business cycle The time delay deviation index It is the hyperbolic tangent function.

[0039] In the above calculations, This constitutes an adjustment coefficient, which is used when the interaction latency is normal. When it approaches 0, the adjustment coefficient is 1, which is incorrect. Make adjustments; when interaction is congested When the value is greater than 0, the adjustment coefficient is greater than 1, thus amplifying the signal risk; when the interaction is abnormally smooth... When the value is less than 0, the adjustment coefficient is less than 1, thereby reducing the risk of signal failure.

[0040] Finally, in traditional accumulation methods, a fixed value is subtracted with each update to offset daily fluctuations. While this filters out transient disturbances, it also leads to slow accumulation during severe deterioration. To resist daily fluctuations while responding quickly to severe deterioration, the amount of compensation deducted needs to automatically decrease with the level of danger.

[0041] Using the second parameter calculated above as a base reference, representing the historical average rate of fluctuation, i.e., the natural fluctuation rhythm of environmental background interference; based on this, the accumulated state value of the previous business cycle is added to the deviation of the current business cycle's quality from the historical health benchmark, and then a dynamic adjustment compensation amount calculated from the base reference is subtracted to obtain the adaptive accumulated state of the current business cycle. That is, it satisfies the following relationship: In the formula, For the current business cycle The adaptive cumulative state value, For the previous business cycle The adaptive cumulative state value, which is calculated from the previous time step using the same recursive formula, is set to 0 during the initial run of the system. This serves as a historical health baseline, automatically learned and generated by the main control unit during stable phases. Specifically, it involves a moving average of comprehensive quality indicators over several consecutive business cycles, and only applies to the comprehensive risk index. Update when the temperature remains below the safe limit; freeze when the temperature worsens. This is the current business cycle. The dynamic adjustment compensation amount, among which, Based on reference quantity, For the current business cycle The overall risk index, It is an exponential function with the natural constant e as its base. Outer layer Ensure that the cumulative state is non-negative.

[0042] Compared to the traditional fixed compensation method, It remains stable when the channel fluctuates slightly, and can quickly accumulate to the alarm threshold within a few service cycles when it is severely degraded, resulting in a significantly improved response speed.

[0043] S3: Based on the comparison between the adaptive cumulative state of the current service cycle and the dynamic alarm threshold, control actions are performed on the communication module, and the system is smoothly reset after the channel is restored.

[0044] Through the calculation of S2 above, an adaptive cumulative state value that can reflect evidence of continuous channel degradation is obtained. This is then compared with appropriate reference limits to determine the level of risk in the current business cycle. At the same time, since the intensity of environmental interference varies in different distribution areas and power safety regulations have strict upper limits on the response time of control commands, the reference limits need to be adaptively generated based on historical fluctuations and safety time limits.

[0045] Furthermore, once the channel recovers from a degraded state, the accumulated value cannot be simply reset to zero immediately, otherwise, the residual slight fluctuations may cause frequent switching; however, it also cannot remain in the alarm state for an extended period, as this would affect normal services. Therefore, a stable reset mechanism needs to be designed to enable the system to automatically return to the normal monitoring mode.

[0046] First, the maximum allowable response time for key instructions specified in the communication protocol is obtained, and then divided by the fixed communication cycle determined by S1 above to obtain the fourth parameter, which represents the maximum number of communication cycles that can be experienced within the maximum allowable response time. The fourth parameter is then multiplied by a preset first safety factor to obtain the alarm threshold. For example, the first safety factor is set to 2.

[0047] Furthermore, the fourth parameter is multiplied by a preset second safety factor to obtain the emergency threshold. For example, the second safety factor is set to 3.

[0048] In this embodiment, the first safety factor is used to characterize the time safety margin ratio for triggering a channel degradation alarm. Its value must be greater than 1 to ensure that sufficient adjustment period is reserved before the instruction times out. The second safety factor is used to characterize a more stringent time safety margin ratio reserved before triggering emergency control actions (such as freeze instructions or channel switching). To prevent false triggering, its value must be greater than the first safety factor.

[0049] The first safety factor is determined based on the minimum time consumption of the retransmission mechanism at the communication protocol layer. When the system determines degradation and executes the strategy of 'increasing transmission power and increasing the number of retransmissions', a complete retransmission confirmation mechanism includes: the time consumed by the master station to issue the command. Terminal processing and response time Link round-trip propagation delay and protocol stack retransmission timeout Therefore, the minimum total time for the retransmission mechanism is... To ensure sufficient time for retransmission before the instruction times out, the alarm must reserve an equivalent number of cycles in advance. Let the first safety factor be... ,but ,in For fixed communication cycles.

[0050] The second safety factor is calibrated based on the extreme hardware time consumption of physical layer channel switching. When the system executes the 'freeze command and switches to the backup low-frequency redundant channel', the RF module does not complete the switching instantaneously, but must undergo the following physical actions: register power-off reset time. Time required for the phase-locked loop to relock the spare frequency band and the handshake time for joining the backup channel network. Therefore, the ultimate physical time consumption for channel switching is... To ensure the switching action is completed before the command expires, the emergency threshold must reserve an equivalent number of cycles. Let the second safety factor be calibrated as follows: ,but .

[0051] Based on the alarm threshold and emergency threshold determined above, the two together divide the adaptive cumulative state of the current business cycle into three intervals: normal, deterioration, and emergency.

[0052] More specifically, when the adaptive cumulative state of the current business cycle is greater than or equal to 0 and less than the alarm threshold, the quality level is determined to be normal. The main control unit controls the communication module to maintain the current transmission power and retransmission strategy, and the detection process maintains normal low-power operation. At this time, the energy meter communication link is in a safe and stable state.

[0053] When the adaptive cumulative status of the current service cycle is greater than or equal to the alarm threshold but less than the emergency threshold, the quality level is determined to be degraded. The main control unit controls the communication module to increase the transmit power, increase the number of data retransmissions from 2 to 4, and report the channel degradation status to the master station system. At this time, the downlink channel has experienced continuous degradation but has not yet reached an emergency level.

[0054] When the adaptive cumulative status of the current business cycle exceeds the emergency threshold, the quality level is determined to be emergency. The main control unit immediately freezes pending fee control commands and circuit breaker linkage signals, switches the control communication module to the backup low-frequency redundant channel, activates local safety power supply logic, and reports an emergency alarm through an independent operation and maintenance channel. At this point, the communication link is extremely unreliable, and there is a risk of control command loss.

[0055] After the channel recovers from degradation, the system needs to smoothly return to normal to avoid repeated alarms and handovers caused by residual accumulated values ​​or instantaneous fluctuations. When the channel meets the condition that the comprehensive quality index is greater than the historical health benchmark and the comprehensive danger index is less than 0.5 for three consecutive service cycles, the main control unit executes a gradual handover: first, it restores the main channel communication, then it retransmits the temporary storage command, and finally, it clears the adaptive accumulated state and re-enables the adaptive update of the historical health benchmark. The setting of three consecutive cycles is a hysteresis judgment to prevent false resets caused by instantaneous fluctuations; a comprehensive quality index greater than the historical health benchmark indicates that the current quality has recovered to above the health benchmark; a comprehensive danger index less than 0.5 indicates that the comprehensive danger index has dropped to the safe zone. Gradual handover prevents state oscillations. This mechanism ensures a stable transition of the system during the interference-recovery cycle.

[0056] Thus, based on the comparison results of the adaptive cumulative state and the dynamic threshold, the main control unit automatically executes hierarchical control from power adjustment to channel switching, and achieves a smooth reset after the channel health is restored. This completes the complete closed loop of acquisition → detection → decision → execution → recovery, realizing adaptive, rapid, and accurate detection and control of the communication channel quality of the energy meter.

[0057] The present invention also provides a channel quality detection system for an electricity meter. The system includes a processor and a memory, the memory storing computer program instructions, which, when executed by the processor, implement the channel quality detection method for an electricity meter according to the first aspect of the present invention.

[0058] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and will not be described in detail here.

[0059] It should be noted that those skilled in the art can make various modifications and improvements without departing from the inventive concept, and these all fall within the scope of protection of this invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A method for detecting channel quality in an electricity meter, characterized in that, include: Multi-source data from the electricity meter communication module within the current service cycle is collected and preprocessed to obtain a comprehensive quality index reflecting downlink channel quality and a delay deviation index reflecting link congestion. This includes: collecting the received signal strength indicator (RSS), bit error rate statistics, and the time interval from transmission completion to receiving a concentrator acknowledgment within the current service cycle; smoothing the RSS and bit error rate statistics using a sliding window mid-range filtering algorithm, and mapping the RSS to a dimensionless normalized value based on the lower limit of receiver sensitivity and the upper limit of saturation preset in the communication module specifications; then constructing the comprehensive quality index using an equal-weight linear fusion strategy combined with the bit error rate statistics; calculating the mean and standard deviation of the historical time interval from transmission completion to receiving a concentrator acknowledgment using a sliding window, calculating the difference between the real-time time interval from transmission completion to receiving a concentrator acknowledgment and the mean, and then dividing by the standard deviation to obtain the delay deviation index. The degradation depth and degradation rate of the current channel quality relative to the historical level are calculated based on the comprehensive quality index, and the normalized degradation depth index and dynamic rate amplification index are obtained respectively. The comprehensive danger index is constructed by combining the delay deviation index. The comprehensive danger index is used to characterize the urgency of channel degradation. The compensation amount during cumulative updates is dynamically adjusted using the comprehensive risk index, so that the compensation amount automatically decreases as the comprehensive risk index increases, thus obtaining the adaptive cumulative state of the current business cycle. The calculation formula used is as follows: In the formula, For the current business cycle The adaptive cumulative state value, For the previous business cycle The adaptive cumulative state value, which is calculated from the previous time step using the same recursive formula, is set to 0 during the initial run of the system. This serves as a historical health baseline, automatically learned and generated by the main control unit during stable phases. Specifically, it involves a moving average of comprehensive quality indicators over several consecutive business cycles, and only applies to the comprehensive risk index. Update when the temperature remains below the safe limit; freeze when the temperature worsens. This is the current business cycle. The dynamic adjustment compensation amount, among which, Based on reference quantity, For the current business cycle The overall risk index, It is an exponential function with the natural constant e as its base; outer layer Ensure the cumulative state is non-negative; The adaptive cumulative state is compared with the dynamic alarm threshold, and hierarchical control actions are performed on the communication module based on the comparison result.

2. The channel quality detection method for an electricity meter according to claim 1, characterized in that, The calculation of the normalized deterioration depth index includes: Calculate the decrease in the current business cycle comprehensive quality index relative to the arithmetic mean of several historical business cycle comprehensive quality indices, and divide this decrease by the average of the absolute values ​​of the differences between the comprehensive quality indices of adjacent historical cycles to obtain the normalized deterioration depth index.

3. The channel quality detection method for an electricity meter according to claim 1, characterized in that, The calculation of the dynamic rate amplification index includes: Calculate the difference between the comprehensive quality index of the previous business cycle and the current business cycle. A positive value indicates a decline in quality, and the maximum value is compared with 0 to obtain the third parameter. The negative value is truncated at the maximum value to ensure that the third parameter is 0 when the quality recovers. Divide the third parameter by the second parameter to obtain the deterioration rate ratio relative to the historical fluctuation rate. Add 1 and take the natural logarithm to make the output close to 0 when there are normal small fluctuations, while the nonlinearity of the logarithmic function makes the output significantly increase when there is a large drop. Finally, add 1 again to calculate the dynamic rate amplification index of the current business cycle.

4. The channel quality detection method for an electricity meter according to claim 1, characterized in that, The construction of the comprehensive risk index includes: The deviation intensity index is obtained by multiplying the normalized deterioration depth index and the dynamic rate amplification index; the deviation intensity index is then multiplied by an adjustment coefficient to obtain the comprehensive risk index; the adjustment coefficient is determined based on the magnitude of the time delay deviation index.

5. The channel quality detection method for an electricity meter according to claim 1, characterized in that, The determination of the dynamic alarm threshold includes: The maximum allowable response time for key instructions specified in the communication protocol is obtained, divided by a fixed communication cycle to obtain the number of cycles to obtain the fourth parameter, the fourth parameter is multiplied by the first safety factor to obtain the alarm threshold, and the fourth parameter is multiplied by the second safety factor to obtain the emergency threshold.

6. The channel quality detection method for an electricity meter according to claim 1, characterized in that, The step of performing hierarchical control actions on the communication module based on the comparison results includes: When the adaptive cumulative state is less than the alarm threshold, the quality is determined to be normal, and the current transmit power and retransmission strategy are maintained. When the adaptive cumulative status is greater than or equal to the alarm threshold and less than the emergency threshold, the quality is determined to be degraded, the transmission power is increased and the number of data retransmissions is increased, and the degraded status is reported. When the adaptive cumulative status exceeds the emergency threshold, the quality is deemed to be in an emergency, the pending fee control instructions and circuit breaker linkage signals are frozen, the system switches to the backup channel, the local safety power supply logic is activated, and an emergency alarm is reported.

7. A channel quality detection system for an electricity meter, characterized in that, include: A processor and a memory, the memory storing computer program instructions that, when executed by the processor, implement the channel quality detection method for an energy meter according to any one of claims 1-6.

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