Intelligent converged terminal with low voltage user supply voltage monitoring function

Abstract

This invention relates to the field of voltage monitoring technology, specifically to an intelligent fusion terminal with low-voltage user power supply voltage monitoring function. The terminal includes: a data acquisition unit for acquiring voltage information and its period to obtain a voltage data segment for the current time period; a fluctuation analysis unit for analyzing the voltage fluctuation at each time point in the voltage data segment to obtain a basic fluctuation intensity parameter for the current time period; a delay adjustment factor acquisition unit for acquiring a delay adjustment factor for the current time period; a threshold adjustment factor acquisition unit for acquiring a threshold adjustment factor for the current time period; and an anomaly monitoring unit for acquiring an adaptive dynamic determination delay and adaptive threshold for the current time period based on the basic fluctuation intensity parameter, delay adjustment factor, and threshold adjustment factor; and performing voltage monitoring based on the adaptive dynamic determination delay and adaptive threshold for each time point. This application can accurately and effectively monitor the user's power supply voltage.

Description

Technical Field

[0001] This invention relates to the field of voltage monitoring technology, and more specifically to an intelligent fusion terminal with low-voltage user power supply voltage monitoring function. Background Technology

[0002] Low-voltage user power supply voltage monitoring is a technical means to monitor the actual voltage experienced by users in low-voltage power supply networks serving a wide range of residential and small commercial users in real time. In power systems, voltage is one of the key indicators of power quality, and its stability directly affects the normal operation and lifespan of electrical equipment. Due to the wide coverage, numerous users, and complex and diverse electricity consumption patterns of low-voltage power supply networks, voltage is easily affected by various factors such as line losses, load fluctuations, and equipment aging, resulting in voltage fluctuations. Excessive voltage will accelerate the aging of electrical equipment insulation, shorten its lifespan, and even cause equipment damage; excessively low voltage will cause equipment to fail to start normally or operate inefficiently, affecting users' normal production and daily life. Therefore, developing an intelligent integrated terminal with low-voltage user power supply voltage monitoring function is crucial. It can promptly detect voltage anomalies, providing a basis for power departments to accurately locate problems and take effective measures to ensure voltage stability, thereby improving power supply service quality and user satisfaction.

[0003] Traditional voltage monitoring technologies often employ fixed thresholds and time-delay judgment methods, which are difficult to adapt to the complex voltage fluctuations caused by frequent switching of impulsive loads (such as air conditioners and welding machines) in low-voltage user scenarios. For example, fixed delays are prone to generating false alarms for instantaneous spikes such as motor startup, while fixed thresholds are prone to triggering repeated over-limit alarms when the voltage fluctuates at critical points, leading to a decrease in the reliability of the monitoring system. Although existing technologies have improved performance by increasing the sampling frequency or introducing simple filtering, they have not yet resolved the contradiction between false alarms and missed alarms in dynamic fluctuation scenarios. Summary of the Invention

[0004] To address the aforementioned technical problems, the present invention aims to provide an intelligent converged terminal with low-voltage user power supply voltage monitoring function. The specific technical solution adopted is as follows:

[0005] One embodiment of the present invention provides an intelligent fusion terminal with low-voltage user power supply voltage monitoring function, the terminal comprising:

[0006] The data acquisition unit is used to acquire the user's voltage signal and obtain the period of the voltage signal; and to form the voltage data segment of the current time by combining the voltage of each time within the first preset time period up to the current time.

[0007] The fluctuation analysis unit is used to analyze the voltage fluctuation at each moment in the voltage data segment and obtain the basic fluctuation intensity parameters for the current moment.

[0008] The delay adjustment factor acquisition unit is used to divide a day into three periods: peak, flat, and trough, and to obtain the peak coefficient of the current time period according to the period to which the current time period belongs; to generate a moving average line based on the difference between the maximum and minimum voltage values ​​in the voltage data segment; and to obtain the delay adjustment factor of the current time period based on the peak coefficient of the current time period, the number of intersections between the waveform of the voltage signal corresponding to the voltage data segment and the moving average line, the effective value of each power frequency cycle in the voltage data segment, and the symmetry of the fluctuation of a cycle in the voltage signal closest to the current time period.

[0009] The threshold adjustment factor acquisition unit is used to acquire the threshold adjustment factor for the current time based on the standard deviation of the voltage at each time within a preset time period after the voltage exceeds the threshold and returns to normal, the voltage change rate at the current time, the frequency domain characteristics of the voltage at each time during the second preset time period up to the current time, and the waveform peak coefficient of one cycle of the voltage signal closest to the current time.

[0010] The anomaly monitoring unit is used to obtain the adaptive dynamic judgment delay and adaptive threshold for the current time based on the basic fluctuation intensity parameter, delay adjustment factor and threshold adjustment factor at the current time; and to perform voltage monitoring based on the adaptive dynamic judgment delay and adaptive threshold at each time.

[0011] Preferably, the voltage fluctuation at each moment in the voltage data segment is analyzed to obtain the basic fluctuation intensity parameter for the current moment, including:

[0012] The basic fluctuation intensity parameter at the current time is obtained by multiplying and normalizing the difference between the maximum and minimum voltage values ​​in the voltage data segment at the current time, the mean of all voltages in the voltage data segment and the mean of the absolute values ​​of the differences between each voltage in the voltage data segment, and the coefficient of variation of all voltages in the voltage data segment.

[0013] Preferably, the day is divided into three periods: peak, average, and trough, and the peak coefficient for the current time period is obtained based on the period to which the current time period belongs, including:

[0014] The day is divided into three periods: peak, average, and off-peak, based on users' historical electricity consumption habits. A corresponding peak coefficient is assigned to each period. The peak coefficient for the current time period is determined based on the peak coefficient of the period to which the current time period belongs.

[0015] Preferably, a moving average is drawn based on the difference between the maximum and minimum voltage values ​​in the voltage data segment, including:

[0016] The value of half the difference between the maximum and minimum voltage values ​​in the voltage data segment is mapped onto the Y-axis of the coordinate system to obtain a coordinate point. A straight line parallel to the X-axis is drawn through this coordinate point to obtain the moving average line.

[0017] Preferably, the delay adjustment factor for the current time period is obtained based on the peak coefficient at the current time, the number of intersections between the waveform and the moving average in the voltage signal corresponding to the voltage data segment, the effective value of each power frequency cycle in the voltage data segment, and the symmetry of the fluctuation of a cycle in the voltage signal closest to the current time period, including:

[0018] Obtain the time it takes for the voltage to drop from its peak to its trough and the time it takes for the voltage to rise from its trough to its peak in one cycle of the voltage signal closest to the current time, denoted as the fall time and rise time, respectively. Obtain the absolute value of the difference between the fall time and rise time and normalize it to obtain the symmetry of the fluctuation in one cycle of the voltage signal closest to the current time. Arrange the effective values ​​of each power frequency cycle in the voltage data segment into an effective value sequence in chronological order. Obtain the normalized value of the mean of the absolute values ​​of the differences between every two adjacent effective values ​​in the effective value sequence, denoted as the effective value difference. Multiply the sum of the normalized value of the number of intersections between the waveform and the moving average in the voltage signal corresponding to the voltage data segment, the symmetry of the fluctuation in one cycle of the voltage signal closest to the current time, and the effective value difference with the peak coefficient of the current time and normalize it to obtain the delay adjustment factor of the current time.

[0019] Preferably, the threshold adjustment factor for the current time period is obtained based on the standard deviation of the voltage at each time point within a preset time length after the voltage exceeded the threshold and returned to normal, the voltage change rate at the current time period, the frequency domain characteristics of the voltage at each time point in the second preset time period up to the current time period, and the waveform peak coefficient of one cycle of the voltage signal closest to the current time period, including:

[0020] The starting time is defined as the first moment after the voltage returned to normal following the most recent voltage exceeding the threshold. Voltages at each moment within a preset time period are acquired from this starting time to form a voltage sequence, and the standard deviation of the voltage sequence is obtained. Moments before the current time, at a preset interval from the current time, are designated as the moments to be analyzed. The voltage change rate at the current time is obtained by dividing the difference between the voltage at the current time and the moment to be analyzed by the preset interval. If the voltage change rate at the current time is greater than 0, its value remains unchanged; if it is less than or equal to 0, its value is 0. A Fast Fourier Transform is performed on the voltages at each moment within a second preset time period up to the current time to obtain the ratio of high-frequency component energy to total energy, which is recorded as the energy proportion at the current time. The absolute value of the difference between the peak coefficient of the sine wave reference and the voltage signal closest to the current time, the voltage change rate at the current time, and the energy proportion at the current time are summed. The summation result is multiplied by the standard deviation of the voltage sequence and normalized to obtain the threshold adjustment factor for the current time.

[0021] Preferably, the adaptive dynamic determination delay and adaptive threshold for the current time period are obtained based on the baseline fluctuation intensity parameter, delay adjustment factor, and threshold adjustment factor at the current time period, including:

[0022] The delay adjustment coefficient is obtained by multiplying the amplification factor, the basic fluctuation intensity parameter at the current time, and the delay adjustment factor, and adding them to the first preset value. The adjustment coefficient is then multiplied by the basic delay to obtain the adaptive dynamic determination delay at the current time. The threshold adjustment coefficient is obtained by multiplying the maximum voltage offset, the basic fluctuation intensity parameter at the current time, and the threshold adjustment factor. The threshold adjustment coefficient is then added to the basic threshold to obtain the adaptive threshold at the current time.

[0023] The embodiments of the present invention have at least the following beneficial effects: This application collects the user's voltage signal and obtains the period of the voltage signal; it forms a voltage data segment for the current time by composing the voltage at each moment within a first preset time period up to the current time; then it analyzes the voltage fluctuation at each moment in the voltage data segment to obtain the basic fluctuation intensity parameter for the current time, and evaluates the intensity and characteristics of the voltage fluctuation; further, it analyzes the voltage in the voltage signal and the waveform of the voltage signal to obtain the delay adjustment factor and the threshold adjustment factor respectively; then, based on the basic fluctuation intensity parameter, delay adjustment factor and threshold adjustment factor for the current time, it obtains the adaptive dynamic judgment delay and adaptive threshold for the current time, thereby achieving a balance between impulsive load and steady-state over-limit, reducing false alarms and missed alarms; finally, it performs voltage monitoring based on the adaptive dynamic judgment delay and adaptive threshold for each moment, improving the accuracy and rationality of monitoring the user's power supply voltage. Attached Figure Description

[0024] To more clearly illustrate the technical solutions and advantages 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, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a unit block diagram of an intelligent fusion terminal with low-voltage user power supply voltage monitoring function provided in an embodiment of the present invention. Detailed Implementation

[0026] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of an intelligent fusion terminal with low-voltage user power supply voltage monitoring function proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0027] 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.

[0028] The following description, in conjunction with the accompanying drawings, details a specific solution for an intelligent fusion terminal with low-voltage user power supply voltage monitoring function provided by the present invention.

[0029] Example: The main application scenario of this invention is: This application dynamically adjusts two key parameters in the over-limit judgment by real-time evaluation of the intensity and characteristics of voltage fluctuations, determines the delay time and voltage threshold, and then monitors the user's voltage accordingly.

[0030] Please see Figure 1 The diagram illustrates a unit block diagram of an intelligent converged terminal with low-voltage user power supply voltage monitoring function provided by an embodiment of the present invention. The system includes the following units:

[0031] The data acquisition unit is used to acquire the user's voltage signal and obtain the period of the voltage signal; it combines the voltage at each moment within a first preset time period up to the current moment into a voltage data segment for the current moment.

[0032] Before monitoring the supply voltage to low-voltage users, voltage data acquisition is essential. Voltage data acquisition typically utilizes voltage sensors or smart meters, continuously collecting voltage signals from the low-voltage user side at a preset sampling frequency (sampling at fixed time intervals; in this scheme, it's set to once per second) to form a time series, simultaneously acquiring the waveform and complete cycle of the voltage signal. After initial acquisition, when calculating various characteristics, the original voltage signal needs to be preprocessed to remove outliers and smooth noise, resulting in a processed voltage signal ready for further analysis.

[0033] Meanwhile, in order to combine the data around the current time for corresponding analysis, data storage is required. Therefore, the voltage at each time within the first preset time period up to the current time is used to form the voltage data segment of the current time, where the reference value of the first preset time length is 1 minute.

[0034] The fluctuation analysis unit is used to analyze the voltage fluctuation at each moment in the voltage data segment and obtain the basic fluctuation intensity parameters for the current moment.

[0035] In low-voltage user scenarios, voltage fluctuations are complex and diverse, with significant differences in fluctuation characteristics caused by different factors. Quantifying the severity of current voltage fluctuations is fundamental to the entire improvement scheme. By defining basic fluctuation intensity parameters, and integrating three characteristics—voltage range, mean absolute rate of change, and voltage coefficient of variation—the fluctuation intensity is comprehensively characterized from three dimensions: amplitude, rate of change, and relative dispersion. The voltage range can quickly capture drastic voltage jumps caused by sudden impact loads; the mean absolute rate of change can identify rapid fluctuation events such as the switching of high-power appliances; and the voltage coefficient of variation enables a normalized comparison of fluctuation intensity under different reference voltages. Obtaining basic fluctuation intensity parameters provides a crucial foundational metric for subsequent accurate analysis of voltage fluctuations, enabling subsequent steps to be based on objective fluctuation intensity data and ensuring the scientific validity and accuracy of the entire improvement scheme.

[0036] Therefore, the basic fluctuation intensity parameter for each moment in the voltage data segment is obtained by analyzing the voltage fluctuation at each time point. Specifically, the basic fluctuation intensity parameter for the current moment is obtained by multiplying and normalizing the difference between the maximum and minimum voltage values ​​in the voltage data segment at the current moment, the mean of all voltage values ​​in the voltage data segment and the mean of the absolute values ​​of the differences between each voltage value in the voltage data segment, and the coefficient of variation of all voltage values ​​in the voltage data segment.

[0037] The specific calculation model for the fundamental fluctuation intensity parameter at the current time is as follows:

[0038] ,

[0039] Where Ai represents the basic fluctuation intensity parameter corresponding to the i-th time (current time); Vmaxi and Vmini represent the maximum and minimum voltage values ​​in the voltage data segment at the current time, respectively; Vij represents the mean voltage in the voltage data segment at the current time; Vj represents the j-th voltage in the voltage data segment at the current time; sum(J) represents the number of voltages in the voltage data segment; Cvi represents the coefficient of variation in the voltage data segment at the current time. The coefficient of variation eliminates the influence of the mean value and purely reflects the degree of dispersion of the fluctuation relative to the average level. The larger the value, the greater the degree of dispersion of the fluctuation; (Vmaxi - Vmini) reflects the maximum amplitude of the voltage fluctuation in the voltage data segment. It is extremely sensitive to sudden impact loads (such as the start of an air conditioning compressor). The larger the value, the more severe the voltage jump. This represents the average rate of voltage change; the larger the value, the more frequent the voltage jumps.

[0040] This allows us to obtain the basic fluctuation intensity parameters at the current time.

[0041] The delay adjustment factor acquisition unit is used to divide a day into three periods: peak, flat, and trough, and to obtain the peak coefficient of the current time period according to the period to which the current time period belongs; to draw a moving average line based on the difference between the maximum and minimum voltage values ​​in the voltage data segment; and to obtain the delay adjustment factor of the current time period based on the peak coefficient of the current time period, the number of intersections between the waveform of the voltage signal corresponding to the voltage data segment and the moving average line, the effective value of each power frequency cycle in the voltage data segment, and the symmetry of the fluctuation of a cycle in the voltage signal closest to the current time period.

[0042] After obtaining the basic fluctuation intensity parameters, simply understanding the fluctuation intensity is insufficient; a deeper analysis of the fluctuation's temporal characteristics and waveform morphology is also necessary to more accurately determine the nature of the voltage fluctuation. The delay adjustment factor, through features such as voltage change rate exceeding threshold count and voltage zero-crossing rate, determines whether the current high fluctuation is a short-lived shock or a persistent disturbance, thereby deciding whether to extend the judgment delay to avoid false alarms for instantaneous spikes and ensure a rapid response to steady-state over-limits.

[0043] The delay adjustment factor aims to dynamically adjust the waiting confirmation time after a limit exceedance. First, the voltage zero-crossing rate reflects the frequency of voltage oscillation around a trend line; high-frequency oscillations are prone to misinterpretation, and a high zero-crossing rate necessitates a longer delay. Second, the mean difference between the effective values ​​of adjacent cycles reflects the severity of load changes; a large difference indicates continuous load fluctuations, requiring a longer delay. Simultaneously, the asymmetry between peak and trough times can identify impulsive loads. In low-voltage user scenarios, resistive loads (such as electric water heaters) typically exhibit symmetrical waveforms during switching, while inductive loads (such as motors) experience rapid voltage drops and slow recovery upon startup. This asymmetry is a typical characteristic of impulsive loads, requiring a longer delay to allow for complete voltage stabilization. Finally, based on residential electricity consumption patterns, load fluctuations are frequent and significant during peak hours, necessitating a generally longer delay. By comprehensively considering these characteristics, a delay adjustment factor is derived; a larger value indicates a longer delay to avoid false alarms and ensure rapid response to genuine limit exceedances.

[0044] Furthermore, it is necessary to determine whether the current time falls within any of the daily electricity consumption periods. Based on users' historical electricity consumption habits, the day is divided into three periods: peak, average, and off-peak. A corresponding peak coefficient is assigned to each of these periods. The peak coefficient for the current time is determined based on the peak coefficient of the period to which the current time belongs.

[0045] It should be noted that dividing the day into peak, average, and off-peak periods is existing technology and will not be elaborated on here. It mainly relates to users' electricity consumption habits. For example, the evening peak is from 6 PM to 10 PM, the off-peak is from midnight to 6 AM, and the rest is average. Furthermore, the peak coefficients assigned to peak, average, and off-peak periods need to be determined based on the load (electricity consumption) of each period. The larger the load during peak hours, the larger the corresponding peak coefficient and the longer the delay should be, with a maximum of 1. Conversely, the peak coefficient should be appropriately reduced. Off-peak and average loads are generally smaller and more stable, so a lower peak coefficient can be assigned. For example, the peak coefficients for the three periods could be 1 for peak hours, 0.2 for off-peak hours, and 0.2 for average hours.

[0046] Furthermore, a moving average needs to be set to determine whether the waveform of the voltage signal corresponding to the voltage data segment crosses the moving average. The moving average is created based on the difference between the maximum and minimum voltage values ​​in the voltage data segment. Specifically, half the difference between the maximum and minimum voltage values ​​in the voltage data segment is mapped onto the Y-axis of the coordinate system to obtain a coordinate point. A straight line parallel to the X-axis is drawn through this coordinate point to obtain the moving average.

[0047] Finally, the delay adjustment factor for the current time is obtained based on the peak coefficient at the current time, the number of intersections between the waveform and the moving average in the voltage signal corresponding to the voltage data segment, the effective value of each power frequency cycle in the voltage data segment, and the symmetry of the fluctuation of a cycle in the voltage signal closest to the current time.

[0048] Specifically, the time it takes for the voltage to drop from its peak to its trough and the time it takes for the voltage to rise from its trough to its peak in a cycle of the voltage signal closest to the current time are obtained and denoted as the fall time and rise time, respectively. The absolute value of the difference between the fall time and rise time is obtained and normalized to obtain the symmetry of the fluctuation in a cycle of the voltage signal closest to the current time. The effective values ​​of each power frequency cycle in the voltage data segment are arranged into an effective value sequence in chronological order. The normalized value of the mean of the absolute values ​​of the differences between any two adjacent effective values ​​in the effective value sequence is obtained and denoted as the effective value difference. The sum of the normalized value of the number of intersections between the waveform and the moving average in the voltage signal corresponding to the voltage data segment, the symmetry of the fluctuation in a cycle of the voltage signal closest to the current time, and the effective value difference is multiplied by the peak coefficient of the current time and normalized to obtain the delay adjustment factor of the current time.

[0049] The specific calculation model for the delay adjustment factor is as follows:

[0050] ,

[0051] Where Fi represents the delay adjustment factor corresponding to the i-th time (current time); Hi represents the peak coefficient corresponding to the current time. During peak periods, load fluctuations are frequent and large, so the overall delay should be longer; norm represents the normalization function; Zci is the number of intersections between the waveform and the moving average line in the voltage signal corresponding to the voltage data segment. It represents the number of times the voltage sample value crosses its moving average line in the most recent minute (within the time corresponding to the voltage data segment). Each crossover is counted as a fluctuation. The higher the number of fluctuations, the longer the delay should be to avoid repeatedly triggering alarms during oscillations. Let Sum(K) represent the effective values ​​of the k-th and (k-1)-th power frequency cycles in the voltage data segment, respectively, and let Sum(K) represent the number of effective values. The effective value difference represents the difference between effective values, directly reflecting the severity of load changes; the larger the value, the more drastic the load fluctuation. Tdowni and Tupi represent the time it takes for the voltage to drop from its peak to its trough and the time it takes for the voltage to rise from its trough to its peak within a cycle of the voltage signal closest to the current time, respectively; these are the fall time and rise time. norm(|Tdowni-Tupi|) is the symmetry of the fluctuation within a cycle of the voltage signal closest to the current time. The more asymmetrical the fluctuation, the more it conforms to the characteristics of an impulsive load, and the longer the delay needs to be to wait for the voltage to fully stabilize. From this, the delay adjustment factor for the current time can be obtained.

[0052] The threshold adjustment factor acquisition unit is used to acquire the threshold adjustment factor for the current time based on the standard deviation of the voltage at each time within a preset time period after the voltage exceeds the threshold and returns to normal, the voltage change rate at the current time, the frequency domain characteristics of the voltage at each time during the second preset time period up to the current time, and the waveform peak coefficient of one cycle of the voltage signal closest to the current time.

[0053] The above-mentioned delay adjustment factor at the current time point has been obtained. When further adjusting the threshold, the threshold adjustment factor needs to be obtained. The threshold adjustment factor is based on the characteristics such as the base voltage change rate and the waveform peak coefficient. When the voltage recovers from the over-limit state, the threshold is dynamically increased according to the fluctuation waveform characteristics to prevent the voltage from frequently crossing back and forth near the critical point and to ensure the stability of the voltage after recovery.

[0054] The threshold adjustment factor is used to dynamically adjust the threshold for determining voltage recovery to normal. First, the current voltage change rate reflects the direction of voltage movement. An increase indicates the voltage is moving towards exceeding the limit, with a low probability of recovery; the threshold should be increased to allow for a safety margin. A decrease indicates the voltage is moving away from the limit, and the threshold can be maintained. Second, the proportion of high-frequency energy in the fluctuation spectrum reflects the fluctuations caused by power electronic equipment. High-frequency components are usually caused by power electronic equipment (such as switching power supplies and frequency converters). Voltage fluctuations generated by such loads are frequent and sharp; even if the effective value returns to normal, the spikes may still damage the equipment. Therefore, the threshold needs to be increased to avoid frequent state switching during minor fluctuations. Simultaneously, the degree to which the voltage waveform peak coefficient deviates from the sine wave reflects waveform distortion. A large deviation requires a slightly higher threshold (for example, LED driver power supplies may cause voltage peak distortion; even if the effective value is within the normal range, the peak may still threaten the equipment insulation). Finally, the voltage stability after recovery reflects historical recovery patterns. If historical voltage fluctuations after recovery are large (such as frequent small oscillations), the current threshold should be increased to allow for stability and avoid repeated triggering at critical points. These characteristics are combined to obtain the threshold adjustment factor. The larger the value, the more the threshold needs to be increased, to prevent the voltage from frequently crossing back and forth near the critical point and to ensure voltage stability after recovery. Together with the delay adjustment factor, it ensures the adaptive adjustment of the detection parameters.

[0055] Therefore, the threshold adjustment factor for the current time is obtained based on the standard deviation of the voltage at each time within a preset time period after the voltage exceeds the threshold and returns to normal, the voltage change rate at the current time, the frequency domain characteristics of the voltage at each time during the second preset time period up to the current time, and the waveform peak coefficient of one cycle of the voltage signal closest to the current time.

[0056] Specifically, the starting time is the first moment after the voltage returned to normal following the most recent voltage exceeding the threshold. Voltages at each moment within a preset time period are acquired from this starting time to form a voltage sequence, and the standard deviation of the voltage sequence is obtained. Moments before the current time, at a preset interval from the current time, are recorded as moments to be analyzed. The voltage change rate at the current time is obtained by dividing the difference between the voltage at the current time and the moment to be analyzed by the preset interval. If the voltage change rate at the current time is greater than 0, the value of the voltage change rate at the current time remains unchanged; if the voltage change rate at the current time is less than or equal to 0, the value of the voltage change rate at the current time is 0. A Fast Fourier Transform is performed on the voltages at each moment within a second preset time period up to the current time to obtain the ratio of the energy of the high-frequency components to the total energy, recorded as the energy proportion at the current time. The absolute value of the difference between the peak coefficient of the sine wave reference and the waveform of one cycle of the voltage signal closest to the current time, the voltage change rate at the current time, and the energy proportion at the current time are summed. The summation result is multiplied by the standard deviation of the voltage sequence and normalized to obtain the threshold adjustment factor for the current time.

[0057] The specific calculation model for the threshold adjustment factor is as follows:

[0058] ,

[0059] Where Gi is the threshold adjustment factor corresponding to the i-th time (current time), and θi represents the standard deviation of the voltage sequence, which is the standard deviation of the voltage at each time within a preset time length after the voltage exceeds the threshold and returns to normal the most recent time. The larger the standard deviation, the higher the recovery threshold should be to reserve a stable space and avoid repeated triggering at the critical point. This represents the voltage change rate (signed) at the current time. The preset interval is rounded to 3 seconds. A larger value indicates that the voltage is moving towards the over-limit direction, with a low probability of recovery. The threshold should be increased to reserve a safety margin. If it is less than or equal to 0, it indicates that the voltage is moving away from the over-limit, and the threshold can be maintained, i.e., this item is set to 0. Egi and Ei represent the energy of the high-frequency components and the total energy obtained by performing a Fast Fourier Transform on the voltage at each time of the second preset time period up to the current time, respectively. A larger ratio of the two indicates more frequent and sharper voltage fluctuations. The threshold needs to be increased to avoid frequent state switching in small fluctuations. Cf represents the sine wave reference, i.e. Upi represents the maximum absolute value (peak value) of the instantaneous waveform of a period in the voltage signal most recent to the current time, and Urmsi represents the root mean square value (RMS value) of the fluctuation waveform of a period in the voltage signal most recent to the current time. The ratio of the two is the waveform peak coefficient of a period in the voltage signal most recent to the current time. This indicates the degree of waveform distortion. The larger the value, the more obvious the waveform distortion. The threshold should be appropriately increased to avoid risks.

[0060] The anomaly monitoring unit is used to obtain the adaptive dynamic judgment delay and adaptive threshold for the current time based on the basic fluctuation intensity parameter, delay adjustment factor and threshold adjustment factor at the current time; and to perform voltage monitoring based on the adaptive dynamic judgment delay and adaptive threshold at each time.

[0061] The adaptive delay time adjusts the base delay based on a delay adjustment factor and the base fluctuation intensity. This extends the delay during periods of severe fluctuation to avoid false alarms, while ensuring a rapid response during stable periods. Similarly, the adaptive threshold adjusts the base threshold based on a threshold adjustment factor and the base fluctuation intensity. This increases the threshold during complex fluctuations to ensure voltage stability after recovery, while maintaining the threshold for rapid recovery confirmation during simple fluctuations. This combined approach enables real-time adaptive adjustment of the over-limit judgment parameters, allowing the improved scheme to better adapt to complex low-voltage user scenarios, effectively reducing false alarms and missed alarms, and improving the reliability and effectiveness of detection.

[0062] Therefore, the adaptive dynamic determination delay and adaptive threshold for the current time are obtained based on the basic fluctuation intensity parameter, delay adjustment factor and threshold adjustment factor at the current time.

[0063] Specifically, the amplification factor, the basic fluctuation intensity parameter at the current time, and the delay adjustment factor are multiplied together and added to the first preset value to obtain the delay adjustment factor; the adjustment factor is multiplied by the basic delay to obtain the adaptive dynamic determination delay at the current time; the maximum voltage offset, the basic fluctuation intensity parameter at the current time, and the threshold adjustment factor are multiplied together to obtain the threshold adjustment factor; the threshold adjustment factor is added to the basic threshold to obtain the adaptive threshold at the current time.

[0064] The specific adaptive dynamic determination delay and adaptive threshold calculation model for the current time period are as follows:

[0065] ,

[0066] ,

[0067] Where Ti and Ui are the adaptive dynamic judgment delay and adaptive threshold corresponding to the i-th time (current time), respectively; T0 and U0 are the basic delay (e.g., 3 seconds) and basic threshold (e.g., 253V, i.e., the national standard upper limit), respectively; k1 is the amplification factor (e.g., 2), which controls the maximum delay duration and can be set according to the user scenario; Ai, Fi, and Gi represent the basic fluctuation intensity parameter, delay adjustment factor, and threshold adjustment factor of the current time, respectively; T0*(1+k1*Ai*Fi) indicates that the adaptive dynamic judgment delay increases with the increase of the basic fluctuation intensity parameter and the delay adjustment factor, and (1+k1*Ai*Fi) is the delay adjustment coefficient; ΔU is the maximum voltage offset (e.g., 3V, i.e., the threshold can be increased to 256V), which can be adjusted according to the actual situation. The smaller this value is, the smaller the adjustment range; U0+(ΔU*Ai*Gi) indicates that the adaptive threshold increases with the increase of the basic fluctuation intensity parameter and the threshold adjustment factor; (ΔU*Ai*Gi) is the threshold adjustment coefficient.

[0068] This allows us to obtain the adaptive dynamic decision delay and adaptive threshold at the current time. Similarly, we can obtain the adaptive dynamic decision delay and adaptive threshold at each time. Furthermore, voltage monitoring is performed based on the adaptive dynamic decision delay and adaptive threshold at each time.

[0069] Specifically, after obtaining the dynamic judgment delay and regression threshold corresponding to each moment, the low-voltage user power supply voltage monitoring can be completed. The terminal continuously collects voltage data. When the voltage value exceeds the adaptive threshold, it is not directly judged as abnormal, but an adaptive dynamic judgment delay is initiated. The adaptive dynamic judgment delay is a stage. During this stage, the voltage change is closely monitored. If the voltage still exceeds the adaptive threshold after the delay ends, the abnormality is confirmed and the time, amplitude, and other information are recorded. At the same time, an alarm is triggered to notify the operation and maintenance personnel. When the voltage recovers from the abnormal state during the delay stage and does not exceed the adaptive threshold again during the delay stage, it is judged as recovered. This mechanism can avoid false recovery judgments caused by brief voltage rebounds or fluctuations. The dynamic judgment delay filters out accidental interference, and the adaptive threshold ensures the accuracy of recovery judgment. The combination of the two allows the terminal to accurately capture the real voltage abnormality and recovery situation, providing reliable data support for analyzing power supply quality, locating faults, and optimizing operation and maintenance strategies, effectively improving the stability and reliability of low-voltage user power supply.

[0070] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0071] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0072] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A smart fusion terminal with low-voltage user power supply voltage monitoring function, characterized in that, The terminal includes: The data acquisition unit is used to acquire the user's voltage signal and obtain the period of the voltage signal; and to form the voltage data segment of the current time by combining the voltage of each time within the first preset time period up to the current time. The fluctuation analysis unit is used to analyze the voltage fluctuation at each moment in the voltage data segment to obtain the basic fluctuation intensity parameter at the current moment. Specifically, it multiplies and normalizes the difference between the maximum and minimum voltage values ​​in the voltage data segment at the current moment, the mean of all voltages in the voltage data segment and the mean of the absolute values ​​of the differences between each voltage in the voltage data segment, and the coefficient of variation of all voltages in the voltage data segment to obtain the basic fluctuation intensity parameter at the current moment. The delay adjustment factor acquisition unit divides a day into three periods: peak, flat, and trough. It acquires the peak coefficient for each current time period based on its time period. It also creates a moving average based on the difference between the maximum and minimum voltage values ​​in the voltage data segment. The unit acquires the delay adjustment factor for the current time period based on the peak coefficient, the number of intersections between the waveform and the moving average in the voltage signal corresponding to the current data segment, the effective value of each power frequency cycle in the voltage data segment, and the symmetry of the fluctuation in a cycle of the voltage signal closest to the current time period. Specifically, it acquires the time it takes for the voltage to drop from its peak to its trough and the time it takes for the voltage to rise from its trough to its peak in a cycle of the voltage signal closest to the current time period. The time difference between the time difference and the time rise are denoted as the time difference and the time rise are denoted as the time difference and the time rise are denoted as the time difference and the time rise are denoted as the time difference. The absolute value of the difference between the time difference and the time rise are denoted as the time difference and the time difference is denoted as the time difference. The time difference is denoted as the time difference. The time difference is denoted as the time difference. The time delay adjustment factor is obtained by multiplying the sum of the number of intersections between the waveform and the moving average of the voltage signal corresponding to the voltage data segment, the time difference, the time difference, and the peak coefficient of the current time. The threshold adjustment factor acquisition unit is used to acquire the threshold adjustment factor for the current time period based on the standard deviation of the voltage at each time point within a preset time length after the voltage exceeded the threshold and returned to normal, the voltage change rate at the current time period, the frequency domain characteristics of the voltage at each time point within a second preset time period up to the current time period, and the waveform peak coefficient of one cycle of the voltage signal closest to the current time period. Specifically, it takes the first time point after the voltage exceeded the threshold and returned to normal, which is closest to the current time period, as the starting time point. Starting from the starting time point, it acquires the voltage at each time point within a preset time length to form a voltage sequence and acquires the standard deviation of the voltage sequence. It records the time points before the current time period that are a preset interval away from the current time period as the time points to be analyzed. It uses the current time point and the time points to be analyzed... The voltage difference at each moment is divided by a preset interval to obtain the voltage change rate at the current moment. If the voltage change rate at the current moment is greater than 0, the value of the voltage change rate at the current moment remains unchanged; if the voltage change rate at the current moment is less than or equal to 0, the value of the voltage change rate at the current moment is 0. Fast Fourier transform is performed on the voltage at each moment of the second preset time period up to the current moment to obtain the ratio of the energy of the high-frequency component to the total energy, which is recorded as the energy proportion at the current moment. The absolute value of the difference between the waveform peak coefficient of the sine wave reference and the voltage signal closest to the current moment, the voltage change rate at the current moment, and the energy proportion at the current moment are summed. The summed result is multiplied by the standard deviation of the voltage sequence and normalized to obtain the threshold adjustment factor at the current moment. An anomaly monitoring unit is used to obtain the adaptive dynamic judgment delay and adaptive threshold for the current time period based on the basic fluctuation intensity parameter, delay adjustment factor, and threshold adjustment factor at the current time period. Specifically, it multiplies the amplification factor, the basic fluctuation intensity parameter, and the delay adjustment factor at the current time period and adds them to a first preset value to obtain the delay adjustment coefficient; multiplies the adjustment coefficient by the basic delay to obtain the adaptive dynamic judgment delay at the current time period; multiplies the maximum voltage offset, the basic fluctuation intensity parameter, and the threshold adjustment factor at the current time period to obtain the threshold adjustment coefficient; adds the threshold adjustment coefficient by the basic threshold to obtain the adaptive threshold at the current time period; and monitors the voltage based on the adaptive dynamic judgment delay and adaptive threshold at each time period.

2. The intelligent fusion terminal with low-voltage user power supply voltage monitoring function according to claim 1, characterized in that, The process of dividing a day into three periods—peak, average, and trough—and obtaining the peak coefficient for a given time period based on its corresponding time period includes: The day is divided into three periods: peak, average, and off-peak, based on users' historical electricity consumption habits. A corresponding peak coefficient is assigned to each period. The peak coefficient for the current time period is determined based on the peak coefficient of the period to which the current time period belongs.

3. The intelligent fusion terminal with low-voltage user power supply voltage monitoring function according to claim 1, characterized in that, The step of creating a moving average based on the difference between the maximum and minimum voltage values ​​in the voltage data segment includes: The value of half the difference between the maximum and minimum voltage values ​​in the voltage data segment is mapped onto the Y-axis of the coordinate system to obtain a coordinate point. A straight line parallel to the X-axis is drawn through this coordinate point to obtain the moving average line.

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