A multi-bit control system based on digital coding

Abstract

The present invention relates to the field of digital coding technology, and specifically to a multi-bit control system based on digital coding. The system includes a network monitoring module, a coding adjustment module, a signal reconstruction module, a fault tolerance control module, and a signal processing module. In the present invention, by dynamically monitoring key network performance parameters such as bandwidth, latency, and error rate, the network status changes are obtained in real time, and based on this, intelligent adjustment is performed to ensure that the system can continuously optimize the coding complexity according to the network conditions, flexibly adjust the signal compression ratio, and enable the signal to maintain efficient transmission in a changing network environment. When reconstructing the signal, by comparing the differences between the reconstructed signal and the target signal, the system can adjust the decoding mode based on real-time data feedback and correct the errors, significantly improving the decoding accuracy and signal quality. Relying on the execution signal data with real-time feedback to optimize the power output of the control signal, the signal stability is further enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of digital coding, and particularly to a multi-bit control system based on digital coding. Background Art

[0002] Digital coding technology mainly involves converting information into digital signals and is the basis of modern communication, data storage, and signal processing. It is widely used in applications ranging from simple data transmission to complex encryption systems. The core of digital coding is to convert analog signals or other forms of data into binary codes so that they can be processed, stored, or transmitted by digital electronic devices. It includes various coding techniques such as linear coding, block coding, and convolutional coding, and each coding technique has its specific application scenarios and advantages.

[0003] Among them, the multi-bit control system of digital coding involves a system that uses digital coding methods to achieve the transmission and execution of control instructions at the multi-bit level. In the system, control instructions are encoded into multi-bit forms, allowing for more complex operations and higher control precision. It is suitable for application scenarios that require precise control of multiple parameters, such as automated manufacturing, robotics, or intelligent transportation systems, enabling more efficient processing of a large number of control signals and achieving precise control of system behavior.

[0004] The existing technology mainly relies on fixed coding schemes and preset transmission parameters and cannot automatically adjust according to network changes. In the face of an unstable network environment, it lacks a dynamic adaptation mechanism, resulting in limited signal transmission quality. Especially in the case of large fluctuations in bandwidth and delay, the existing technology cannot timely adjust the coding strategy, thus affecting the stability and accuracy of data transmission. The decoding process of the existing system does not have an effective real-time feedback correction mechanism. When signal errors occur, they cannot be corrected immediately, which further affects the signal stability and easily leads to delays or errors in control instructions. Summary of the Invention

[0005] The purpose of the present invention is to solve the deficiencies existing in the prior art and to propose a multi-bit control system based on digital coding.

[0006] To achieve the above purpose, the present invention adopts the following technical solution: A multi-bit control system based on digital coding, the system includes:

[0007] Based on the currently monitored network status data in real time, the network monitoring module collects bandwidth, delay, and error rate data, captures transmission signal fluctuations, evaluates the performance of the digital coding signal transmission conditions, and calculates the fluctuations of the network performance to obtain the network status fluctuation index;

[0008] The coding adjustment module analyzes the fluctuations of the current network bandwidth and latency according to the network status fluctuation index, dynamically adjusts the coding complexity based on the impact of bandwidth changes on the transmission rate of digital coding signals, calculates the adjusted coding complexity, and obtains the dynamic coding adaptation parameters;

[0009] Based on the dynamic coding adaptation parameters, the signal reconstruction module gradually decodes the received digital coding signals, evaluates the quality of data segments, analyzes the reconstruction accuracy of the signals. If the error is too large, it adjusts the decoding mode and corrects the errors in the signal reconstruction process in real time to obtain the reconstruction error correction index;

[0010] Based on the reconstruction error correction index, the fault tolerance control module analyzes whether the current execution signal meets the requirements in combination with the real-time feedback execution signal data. If the signal quality does not meet the standard, it adjusts the power output of the control signal and corrects the signal transmission mode to obtain the signal correction parameters.

[0011] The improvements of the present invention are that the network status fluctuation index includes bandwidth fluctuation, latency fluctuation, and error rate fluctuation; the dynamic coding adaptation parameters include compression ratio and transmission rate; the reconstruction error correction index includes decoding deviation, error correction amount, and reconstructed signal error; and the signal correction parameters include signal transmission mode and signal execution quality.

[0012] The improvements of the present invention are that the network monitoring module includes:

[0013] The status data acquisition sub-module collects bandwidth, latency, and error rate data based on the current network status data monitored in real time, performs preliminary screening and classification, and verifies the data integrity to obtain the verified status data;

[0014] Based on the verified status data, the network fluctuation calculation sub-module calculates the fluctuations of the bandwidth, latency, and error rate data, evaluates the fluctuation range of each item of data, and uses the formula:

[0015] ;

[0016] Calculate the fluctuation amplitude of the network , where represents the th collected data point, represents the th collected data point, represents the number of data points;

[0017] According to the fluctuation amplitude of the network, the transmission signal evaluation sub-module evaluates the stability performance of the transmission signal in combination with the signal quality to obtain the network status fluctuation index.

[0018] The improvements of the present invention are that the coding adjustment module includes:

[0019] The bandwidth analysis sub-module obtains bandwidth change data and time series information according to the network state fluctuation index, calculates the bandwidth change rate and the bandwidth difference sequence, compares them with the bandwidth floating reference, identifies the unstable state of the bandwidth, calculates the critical fluctuation time interval, and obtains the bandwidth fluctuation degree;

[0020] The delay judgment sub-module calls the bandwidth fluctuation degree, combines the network delay data, analyzes the maximum delay and the minimum delay within the current time window, evaluates the average fluctuation amplitude of the delay, and judges the synchronization of the bandwidth fluctuation and the delay fluctuation to obtain the delay linkage interval quantity;

[0021] The complexity calculation sub-module adjusts the coding complexity and optimizes the signal compression rate based on the delay linkage interval quantity, using the formula:

[0022] ;

[0023] Calculate the coding complexity adjustment value , and obtain the dynamic coding adaptation parameter, where represents the bandwidth fluctuation degree, represents the delay linkage interval quantity, represents the original coding rate, represents the current signal compression ratio, represents the parameter of the th coding segment, represents the number of coding parameters.

[0024] The improvement of the present invention is that the signal reconstruction module includes:

[0025] The step-by-step decoding sub-module performs frame-level decoding on the received digital coding signal based on the dynamic coding adaptation parameter, analyzes the bit segment and the frame synchronization code, compares the decoded bit values according to the signal mapping rule in the dictionary table, and constructs the initial signal stream;

[0026] The error analysis sub-module calls the initial signal stream, compares it with the reference waveform value in the target signal data, calculates the amplitude difference and the change rate of adjacent sampling points, identifies the matching abnormal interval between signals, and obtains the reconstructed error signal amplitude;

[0027] The mode adjustment sub-module adjusts the coding mode according to the reconstructed error signal amplitude, corrects the error in the signal reconstruction process in real time, using the formula:

[0028] ;

[0029] Obtain the reconstructed error correction index, where represents the adjustment intensity value, The th sampling point representing the initial signal sequence value, and the th corresponding sampling point in the target signal, where the th sampling point represents the weight coefficient, and the

[0030] improvement of the present invention is that the fault tolerance control module includes:

[0031] The error judgment sub-module synchronously compares the signal amplitude sequence and the frequency change trend according to the reconstruction error correction index, calculates the difference between the amplitude-frequency deviation value and the correction index, judges whether the signal is within the acceptable range, and obtains the amplitude-frequency deviation level;

[0032] The signal regulation sub-module calls the amplitude-frequency deviation level to adjust the power output and transmission mode of the signal, using the formula:

[0033] ;

[0034] to obtain the adjusted power output parameter ; where represents the intensity of the th signal detection, is the target signal intensity, is the number of detections, is the adjustment coefficient;

[0035] The parameter generation sub-module detects the transmission coherence and frequency hopping volatility of the corrected signal according to the adjusted power output parameter, judges the signal response adjustment range, and obtains the signal correction parameter.

[0036] Another improvement of the present invention is that the system further includes:

[0037] The signal processing module filters and enhances the control signal based on the signal correction parameter, monitors the signal fluctuation in real time, analyzes the signal fluctuation amplitude, judges whether it is abnormal according to the signal fluctuation amplitude, and if the fluctuation deviation is too large, triggers the retransmission or processing of the signal to obtain the signal fluctuation evaluation result;

[0038] The signal fluctuation evaluation result includes the fluctuation amplitude, the fluctuation deviation, and the signal stability.

[0039] Another improvement of the present invention is that the signal processing module includes:

[0040] Based on the signal correction parameters, the signal filtering sub-module filters and enhances the control signal, monitors the signal fluctuations in real time, calculates the segmented difference and performs mean correction by collecting continuous waveform data, eliminates the discrete values outside the deviation interval, and smooths the data to obtain the fluctuation denoised value;

[0041] The fluctuation amplitude extraction sub-module calls the fluctuation denoised value and calculates the signal fluctuation intensity value according to the fluctuation interval amplitude within the difference time period:

[0042] ;

[0043] Calculate the signal fluctuation intensity value , where represents the instantaneous value of the th time period, represents the mean value of the instantaneous values, represents the jump value of the th time period, represents the mean value of the jump values, represents the number of consecutive jumps, represents the number of intervals within the time period, is the total number of time periods;

[0044] The anomaly judgment sub-module calls the signal fluctuation intensity value, identifies the signal section with deviation mutations, judges whether it exceeds the signal fluctuation tolerance range. If the fluctuation deviation is too large, it triggers the retransmission or processing of the signal to obtain the signal fluctuation evaluation result.

[0045] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0046] In the present invention, by dynamically monitoring key network performance parameters such as bandwidth, delay, and error rate, the network state changes are obtained in real time, and based on this, intelligent adjustments are made to ensure that the system can continuously optimize the coding complexity according to the network conditions, flexibly adjust the signal compression ratio, so that the signal can maintain efficient transmission in a changing network environment. When reconstructing the signal, by comparing the differences between the reconstructed signal and the target signal, the system can adjust the decoding mode based on real-time data feedback and correct the errors, significantly improving the decoding accuracy and signal quality. Relying on the real-time feedback of the execution signal data, the power output of the control signal is optimized to further enhance the signal stability. By dynamically filtering and enhancing the control signal, the system can analyze the signal fluctuation situation in real time, correct excessive fluctuations, prevent signal loss or transmission errors, and ensure the high reliability and response ability of the multi-bit control system in a complex environment. Brief Description of the Drawings

[0047] Figure 1 is the system flow chart of the present invention;

[0048] Figure 2Flow chart of the network monitoring module in the present invention;

[0049] Figure 3 Flow chart of the encoding adjustment module in the present invention;

[0050] Figure 4 Flow chart of the signal reconstruction module in the present invention;

[0051] Figure 5 Flow chart of the fault tolerance control module in the present invention;

[0052] Figure 6 Flow chart of the signal processing module in the present invention. Detailed implementation manners

[0053] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0054] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. In addition, in the description of the present invention, "a plurality of" means two or more unless otherwise specifically defined. Embodiment

[0055] Please refer to Figure 1 , the present invention provides a technical solution: a multi-bit control system based on digital coding includes:

[0056] Based on the currently monitored network status data in real time, the network monitoring module collects bandwidth, delay and error rate data, captures the fluctuations of the transmission signal, analyzes the network status through data analysis, evaluates the performance of the digital coding signal transmission conditions, and calculates the fluctuations of the network performance to obtain the network status fluctuation index;

[0057] According to the network status fluctuation index, the encoding adjustment module analyzes the fluctuations of the current network bandwidth and delay, based on the impact of the bandwidth change on the digital coding signal transmission rate, combines the delay change, dynamically adjusts the encoding complexity, optimizes the signal compression rate, and calculates the adjusted encoding complexity to obtain the dynamic encoding adaptation parameter;

[0058] The signal reconstruction module gradually decodes the received digital encoded signal based on the dynamic coding adaptation parameters, evaluates the quality of the data segment, analyzes the reconstruction accuracy of the signal by comparing the difference between the reconstructed signal and the target signal. If the error is too large, it adjusts the decoding mode and corrects the errors in the signal reconstruction process in real time to obtain the reconstruction error correction index;

[0059] The fault tolerance control module analyzes whether the current execution signal meets the requirements based on the reconstruction error correction index and combines the execution signal data fed back in real time. If the signal quality does not meet the standard, it adjusts the power output of the control signal and corrects the signal transmission mode to obtain the signal correction parameter;

[0060] The signal processing module filters and enhances the control signal based on the signal correction parameter, monitors the signal fluctuation in real time, analyzes the signal fluctuation amplitude, and determines whether it is abnormal based on the signal fluctuation amplitude. If the fluctuation deviation is too large, it triggers the retransmission or processing of the signal to obtain the signal fluctuation evaluation result.

[0061] The network state fluctuation indicators include bandwidth fluctuation, latency fluctuation, and error rate fluctuation. The dynamic coding adaptation parameters include compression ratio and transmission rate. The reconstruction error correction indicators include decoding deviation, error correction amount, and reconstructed signal error. The signal correction parameters include signal transmission mode and signal execution quality. The signal fluctuation evaluation results include fluctuation amplitude, fluctuation deviation, and signal stability.

[0062] Please refer to Figure 2 , the network monitoring module includes:

[0063] The status data acquisition sub-module collects bandwidth, latency, and error rate data based on the current network status data monitored in real time, performs preliminary screening and classification, and verifies the data integrity to obtain the verified status data;

[0064] The bandwidth, latency, and error rate data of the network are collected in real time through monitoring devices. During this process, the collector obtains several data points per second to ensure the time accuracy and continuity of the data. Then, preliminary data screening is performed. The screening step excludes abnormal data below a certain accuracy by setting a fluctuation threshold. For example, the lower limit of the bandwidth data is set to 50 Mbps. For data points below this value, the system marks them as abnormal and excludes them. Subsequently, the bandwidth, latency, and error rate data are classified and stored separately according to different data types to ensure a clear data structure for subsequent calculations and analyses. During this process, the system verifies the integrity of the data according to the set rules to ensure that there are no missing items or format errors. If there are abnormal fluctuations or missing items in a certain piece of data, the system will automatically collect it again until the data integrity is confirmed. Finally, network status data is generated. For example, during the collection process, the collection results of the bandwidth data are (55, 59, 60, 57) Mbps, the latency data is (30, 31, 29, 32) ms, and the error rate data is (0.02, 0.03, 0.01, 0.02)%. The data will be used for subsequent fluctuation calculations and transmission signal evaluations.

[0065] Based on the verified status data, the network fluctuation calculation sub-module calculates the volatility of the bandwidth, latency, and error rate data, and evaluates the fluctuation range of each piece of data. The formula used is:

[0066] ;

[0067] Calculate the fluctuation amplitude of the network , where represents the th collected data point, which represents the actual measured value of a certain network status data (such as bandwidth, latency, error rate, etc.), represents the th collected data point, that is, the previous data point adjacent to , represents the number of data points;

[0068] For example, the values in the bandwidth data are (55, 59, 60, 57) Mbps. First, calculate the fluctuation amplitude of the bandwidth data. According to the formula, calculate the difference between every two adjacent data points of the bandwidth data:

[0069] Calculate the difference between 55 and 59: Mbps;

[0070] Calculate the difference between 59 and 60: Mbps;

[0071] Calculate the difference between 60 and 57: Mbps;

[0072] Calculate the average value of the differences:

[0073] ;

[0074] Perform a similar calculation on the latency data (30, 31, 29, 32) ms:

[0075] Calculate the difference between 30 and 31: ms;

[0076] Calculate the difference between 31 and 29: ms;

[0077] Calculate the difference between 29 and 32: ms;

[0078] Then, calculate the average value of the differences:

[0079] ;

[0080] Perform the same calculation on the error rate data (0.02, 0.03, 0.01, 0.02) %:

[0081] Calculate the difference between 0.02 and 0.03: %;

[0082] Calculate the difference between 0.03 and 0.01: %;

[0083] Calculate the difference between 0.01 and 0.02: %;

[0084] Calculate the average value of the differences:

[0085] ;

[0086] Through calculation, the fluctuation ranges of the bandwidth, latency, and error rate are obtained as 2.67 Mbps, 2.0 ms, and 0.0133 % respectively. The fluctuation ranges will be used for further evaluation of the network performance and to generate network performance fluctuation metrics.

[0087] The transmission signal evaluation sub-module evaluates the stability performance of the transmission signal according to the fluctuation range of the network and in combination with the signal quality, and obtains the network state fluctuation metric;

[0088] By combining the bandwidth, latency, and error rate fluctuation ranges of the network, calculate the stability index of the transmitted signal. For example, when the bandwidth fluctuation amplitude is 2.67 Mbps, the latency fluctuation amplitude is 1.33 ms, and the error rate fluctuation amplitude is 0.01%, the system performs a weighted average of the metrics, assigns corresponding weights to each metric using the set weight coefficients. The bandwidth accounts for 40%, the latency accounts for 30%, and the error rate accounts for 30%. Then, calculate the weighted average to obtain a comprehensive transmitted signal fluctuation index. Through calculation, obtain the final network state fluctuation index, which indicates the stability performance of the network during this time period and further provides a basis for network state assessment.

[0089] Please refer to Figure 3 , the encoding adjustment module includes:

[0090] The bandwidth analysis sub-module obtains the bandwidth change data and time series information according to the network state fluctuation index. By calculating the bandwidth change rate and the bandwidth difference sequence, comparing with the bandwidth floating benchmark, identify the unstable state of the bandwidth, calculate the key fluctuation time interval, and obtain the bandwidth fluctuation degree;

[0091] The system collects the bandwidth value once per second from a certain communication node, obtaining sequence data such as [92.5, 91.8, 88.7, 95.2] Mbps, corresponding to time points [0, 1, 2, 3] seconds. Obtain the difference sequence [-0.7, -3.1, 6.5] Mbps by calculating the difference between adjacent bandwidth data, and further divide the difference by the sampling time interval of 1 second to obtain the bandwidth change rate sequence, which are -0.7 Mbps / s, -3.1 Mbps / s, and 6.5 Mbps / s respectively. Subsequently, set the bandwidth floating benchmark value of ±2 Mbps / s. The basis for this value setting is that the absolute value of the bandwidth change in the long-term measured stable state does not exceed 2 Mbps / s, which belongs to the acceptable range of transmission fluctuations formulated by the service operator. When comparing the difference sequence, it is found that the bandwidth fluctuation amplitudes in the second and third segments are -3.1 Mbps and 6.5 Mbps respectively, exceeding the floating benchmark. Therefore, these two time periods are determined as bandwidth unstable periods. Extract the section with the longest duration in the period as the key fluctuation interval. In this implementation, the interval length is 1 second for both. Calculate that the number of unstable time periods is 2, and the average bandwidth fluctuation is (|-3.1| + |6.5|) / 2 = 4.8 Mbps. Through the expression: fluctuation degree = average bandwidth fluctuation × number of sections × average duration = 4.8 × 2 × 1 = 9.6 Mbps, obtain the bandwidth fluctuation degree value.

[0092] The latency judgment sub-module calls the bandwidth fluctuation degree, combines the network latency data, analyzes the maximum latency and minimum latency within the current time window, evaluates the average fluctuation amplitude of the latency, and judges the synchronization between the bandwidth fluctuation and the latency fluctuation to obtain the latency linkage interval quantity;

[0093] The call bandwidth fluctuation degree value is 9.6 Mbps. Combining with the collected delay sequence data [21, 24, 27, 40, 25] ms, calculate the maximum and minimum values of this sequence. The maximum value is 40 ms and the minimum value is 21 ms. Take the difference and divide it by the number of observations to get the average fluctuation amplitude, that is, (40 - 21) / 5 = 3.8 ms. This value is used to evaluate whether it exceeds the delay fluctuation threshold. The delay threshold is set to 5 ms. According to the requirements for high-delay mutation identification in the communication industry practice, this value can be obtained through statistical analysis of the network average delay deviation in multiple scenarios. Currently, the measured fluctuation amplitude does not exceed the set threshold, but it needs to be judged in combination with the bandwidth fluctuation time period. The key bandwidth fluctuation period appears from the 2nd to the 3rd second, and the corresponding delay periods are 27 ms and 40 ms respectively, and the fluctuation amplitude is 13 ms, which is much higher than the threshold. The bandwidth and delay increase synchronously, so it can be determined that this is an effective linkage section. A total of 2 such sections are identified, and the average duration is 1.5 seconds. The weight is set to 0.9 according to the linkage strength (this value is obtained through the linkage trend regression strength evaluation model and truncated to one decimal place after normalization). Calculate the linkage interval quantity = number of linkage sections × duration × weight = 2 × 1.5 × 0.9 = 2.7, and obtain the delay linkage interval quantity.

[0094] Based on the delay linkage interval quantity, the complexity calculation sub-module adjusts the coding complexity and optimizes the signal compression ratio, using the formula:

[0095] ;

[0096] Calculate the adjusted value of the coding complexity , and obtain the dynamic coding adaptation parameter, where represents the bandwidth fluctuation degree, measuring the change amplitude of the network bandwidth per unit time, represents the delay linkage interval quantity, used to describe the correlation degree between the delay fluctuation and the bandwidth change, represents the original coding rate, represents the current signal compression ratio, represents the th coding segment parameter, including the coding rate, complexity or other coding quality parameters, represents the number of coding parameters;

[0097] Call the aforementioned bandwidth fluctuation degree value of 9.6 Mbps, introduce the original coding rate of 3200 kbps, the signal compression ratio of 0.75, and the three coding parameter values are 1.1, 0.95, and 1.0 respectively. To ensure that data is calculated on the same scale, normalize each data item. Select the linear normalization method to normalize parameters such as the bandwidth fluctuation degree value, delay linkage interval quantity, and coding rate to between 0 and 1. The normalized bandwidth fluctuation degree value, delay linkage interval quantity, and coding rate are 0.32, 0.27, and 0.8 respectively. Then, substitute the normalized data into the calculation formula for operation, and calculate the numerator part:

[0098] ;

[0099] Calculate the denominator part:

[0100] ;

[0101] Calculate :

[0102] ;

[0103] Obtain the coding complexity adjustment value of 0.206, which reflects the required degree of dynamically adjusting the coding complexity after comprehensive analysis of bandwidth fluctuation and delay linkage under the current network conditions.

[0104] Please refer to Figure 4 , the signal reconstruction module includes:

[0105] The step-by-step decoding sub-module decodes the received digital coding signal at the frame level based on the dynamic coding adaptation parameters, analyzes the bit segments and frame synchronization codes, compares the decoded bit values according to the signal mapping rules in the dictionary table, and constructs the initial signal stream;

[0106] During the step-by-step decoding process, according to the dynamic coding adaptation parameters, the received digital coding signal is decoded at the frame level. At this time, the system extracts the bit segments in the coding signal frame by frame and analyzes them in combination with the inter-segment synchronization code to ensure the correct decoding of each frame. To ensure the accuracy of decoding, the system uses the dynamic coding adaptation parameters to match and decode each bit segment in real time according to the rules of the bit segments and the inter-segment synchronization code, and generates preliminary decoded bit values. This process involves mapping the bits of each frame, referring to the preset signal mapping rules in the dictionary table. By gradually comparing the decoded bit values, the accurate decoding of each bit is ensured, and finally a preliminary initial signal sequence value is constructed. For example, assuming that the received digital signal stream is 1100110010, decoding through this signal mapping rule, the obtained bit values are 1100, 0110, 0101. Then the bit segments will be assembled into a preliminary decoded signal stream. During the process, each sampling point will be compared with the preset dictionary table according to the synchronizing code parsed in real time to ensure the accuracy of the decoded signal sequence.

[0107] The error analysis sub-module calls the initial signal stream, compares it with the reference waveform value in the target signal data, calculates the amplitude difference and change rate of adjacent sampling points, identifies the abnormal matching interval between signals, and obtains the amplitude of the reconstructed error signal;

[0108] In the error analysis stage, the initial signal sequence value is called and compared with the reference waveform value in the target signal data. Specifically, by calculating the amplitude difference and change rate of each sampling point, the deviation between the decoded signal and the target signal is identified. To identify the error, adjacent sampling points are calculated. By statistically analyzing the amplitude difference between sampling points, an amplitude difference sequence is obtained, and the change rate between adjacent sampling points is further calculated. If there are sudden changes or extremely large change rate terms in the amplitude difference sequence, the system will identify the point as an abnormal matching interval and generate the corresponding amplitude value of the reconstructed error signal. For example, assuming that the amplitude of the target signal at a certain sampling point is 5, while the amplitude of the initial signal is 3, then the amplitude difference is 2. If this difference is greater than the set reference threshold, it will be considered an abnormal point. This process helps to determine the reconstruction error of the signal and further optimize the signal decoding process.

[0109] The mode adjustment sub-module adjusts the coding mode according to the amplitude of the reconstructed error signal, and corrects the errors in the signal reconstruction process in real time. The formula is used:

[0110] ;

[0111] The reconstruction error correction index is obtained, where represents the adjustment intensity value, represents the th sampling point of the initial signal sequence value, Represents the th sampling point in the target signal, represents the weight coefficient of the th sampling point, represents the total number of sampling points;

[0112] If during the signal decoding process, the amplitudes of the sampling points in the initial signal sequence and the target signal are as follows:

[0113] Sampling point 1: Initial signal amplitude , target signal amplitude , weight coefficient ;

[0114] Sampling point 2: Initial signal amplitude , target signal amplitude , weight coefficient ;

[0115] Sampling point 3: Initial signal amplitude , target signal amplitude , weight coefficient ;

[0116] The total number of sampling points is , calculate the error value of each sampling point, and find the total error:

[0117] For sampling point 1, the error , the squared error is , and multiply by the weight coefficient , to get the weighted error as ;

[0118] For sampling point 2, the error , the squared error is , and multiply by the weight coefficient , to get the weighted error as ;

[0119] For sampling point 3, the error , the squared error is , and multiply by the weight coefficient , to get the weighted error as ;

[0120] Calculate the adjustment intensity value:

[0121] ;

[0122] This result shows that the adjustment intensity value is 1.61. Through this value, the decoding mode can be further adjusted to ensure that the error is corrected during the signal reconstruction process, achieving higher signal accuracy.

[0123] Please refer to Figure 5 , the fault tolerance control module includes:

[0124] Based on the reconstruction error correction index, the error judgment sub-module synchronously compares the signal amplitude sequence with the frequency change trend, calculates the difference between the amplitude-frequency deviation value and the correction index, determines whether the signal is within the acceptable range, and obtains the amplitude-frequency deviation level;

[0125] Obtain the reconstruction error correction index and the current execution signal data. By comparing the signal amplitude sequence with the frequency change trend, determine whether the signal meets the acceptable error range. For example, assume that the currently received signal amplitude sequence is: [4, 5, 7, 6, 4], and the correction index is a certain standard error range (such as ±1). The actual fluctuations of the signal amplitude sequence need to be compared with the correction index. If some amplitudes exceed the preset range, the system will identify such over-limit errors. For the frequency change trend, assume that the target frequency change is between [1.2, 1.3, 1.4], and the measured frequency change is [1.1, 1.35, 1.2]. The difference is calculated as the deviation value between the actual frequency and the target frequency. In this process, by calculating the deviation values of the amplitude and frequency, the deviation level of the error signal can be accurately obtained, and based on this, further signal adjustment is carried out. In this process, by collecting error range data, determine whether the signal meets the basic quality requirements, and obtain the amplitude-frequency deviation level, such as "slight deviation" or "severe deviation".

[0126] The signal regulation sub-module calls the amplitude-frequency deviation level to adjust the power output and transmission mode of the signal, using the formula:

[0127] ;

[0128] Obtain the adjusted power output parameters ; where, represents the intensity of the th signal detection, which is the measured value of the signal intensity collected at different time points or different signal transmission path nodes, is the target signal intensity, which is the intensity standard that the signal is expected to reach under ideal conditions, is the number of detections, is the adjustment coefficient, used to adjust the final power output according to the deviation amount of the signal;

[0129] Perform power adjustment according to the amplitude-frequency deviation level. If the target signal intensity is 6dB, the signal detection values (among 5 measurement nodes) are: [5, 6.2, 6.5, 5.8, 6.1], the number of detections , the adjustment coefficient , then the process of each item in the formula is to calculate the deviation:

[0130] ;

[0131] ;

[0132] ;

[0133] ;

[0134] ;

[0135] The sum of the deviations is:

[0136] 1 + 0.2 + 0.5 + 0.2 + 0.1 = 2.0. Calculate the adjusted power output value:

[0137] ;

[0138] The obtained adjusted power output value is 0.32 dB. Through this adjustment, the signal output will be adjusted to be closer to the target value of 6 dB, thereby improving the signal transmission quality.

[0139] The parameter generation sub-module detects the transmission coherence and hopping frequency volatility of the corrected signal according to the adjusted power output parameters, judges the signal response adjustment range, and obtains the signal correction parameters;

[0140] Detect whether the adjusted signal has stable transmission characteristics, and judge whether the adjustment is effective by calculating the fluctuation of the signal at each node. For example, the transmission values of the intensity of the corrected signal at each node are: [5.5, 6.0, 5.8, 6.2, 6.1]. The hopping frequency volatility is calculated as the change range of the signal intensity at each node. Assuming that the detected signal fluctuation interval is [5.0, 6.2], the fluctuation amplitude is the maximum value 6.2 minus the minimum value 5.0, and the fluctuation amplitude is 1.2 dB. By analyzing the volatility and transmission coherence, obtain the signal correction parameters, such as "signal stability" or "fluctuation range". The correction parameters indicate whether the signal has been properly adjusted to obtain the signal correction parameters.

[0141] Please refer to Figure 6 , the signal processing module includes:

[0142] The signal filtering sub-module filters and enhances the control signal based on the signal correction parameters, monitors the signal fluctuation in real time, performs segmented difference calculation and mean correction by collecting continuous waveform data, eliminates discrete values outside the deviation interval, and smooths the data to obtain the fluctuation denoised value;

[0143] The signal filtering submodule filters and enhances the control signal based on the signal correction parameters. The signal correction parameters usually come from the initial calibration process of the sensor or the correction feedback of the external sampling system. For example, in the urban power supply system, a control node is offset due to voltage disturbance. The offset can be used as a signal correction parameter and repaired. On this basis, the control signal is filtered and enhanced. First, the timing waveform data of the control signal must be obtained, and the original data of each cycle is collected to form a signal sequence. By comparing the data difference between the two time points before and after, a difference sequence is formed, and then the average value of each difference is calculated to form a mean correction sequence to remove system noise interference. For example, for a group of control The signal sequence [2.9, 3.1, 3.0, 3.4, 2.8] is subjected to difference processing to obtain the difference sequence [+0.2, -0.1, +0.4, -0.6]. Samples whose absolute differences are greater than a certain offset limit, such as 0.5mV, are screened out and can be regarded as discrete values, such as -0.6. After elimination, the signal stream is reaggregated for mean smoothing processing. The window width of the smoothing processing can be set to 3 data points, and each group of 3 values ​​is subjected to sliding mean processing. For example, the average of [2.9, 3.1, 3.0] is 3.0, and the average of [3.1, 3.0, 3.4] is 3.17. The smoothing operation of the entire signal is completed, and finally the fluctuation denoising value is obtained.

[0144] The fluctuation amplitude extraction submodule calls the fluctuation denoising value according to its fluctuation interval amplitude in the difference time period:

[0145] ;

[0146] Calculate the signal fluctuation strength value ,in, Representative The instantaneous value of the time period, represents the mean of the instantaneous values, Representative The jump value of the time period, Represents the mean of the jump values, Represents the number of consecutive jumps, represents the number of intervals in the time period, is the total number of time periods;

[0147] By dividing the signal sequence into segments and setting the time window length, such as every 5 seconds as an observation window, the instantaneous value is extracted in each period With jump value , where the instantaneous value is the current sampling point value, the jump value is the difference between the current value and the previous sampling value, and further based on the average value of each instantaneous value in the sampling segment Average with jump value , calculate the difference amplitude of each period, and set the number of continuous jumps is the number of times the absolute value of the jump value is greater than 0.3 mV within a time period, which is combined with the number of time period intervals Combine and substitute into the formula. For example, the instantaneous values and jump values are as follows: Instantaneous values {3.2, 2.9, 3.5, 3.0, 3.3}, jump values {0.4, 0.2, 0.5, 0.3, 0.6}, and the average value is calculated as , , then calculate the difference part and the square root part of each term, and then sum them up:

[0148] ;

[0149] This result indicates that the fluctuation intensity value is 0.7533. If the fluctuation intensity reference value is 0.75, it means that the current fluctuation state exceeds the stable interval range and needs to further enter the abnormal judgment process.

[0150] The abnormal judgment sub-module calls the signal fluctuation intensity value to identify the signal section with deviation mutations, and judges whether it exceeds the signal fluctuation tolerance range. If the fluctuation deviation is too large, it triggers the retransmission or processing of the signal to obtain the signal fluctuation evaluation result;

[0151] By comparing with the set signal fluctuation tolerance value, for example, set to 0.75. If the calculated value is 0.7533, which is obviously higher than the set threshold, it can be determined that there are deviation mutations in the current signal. Then, by detecting the change direction and periodic repeatability of the jump value in the current signal, it is judged whether it belongs to transient disturbance. If it is judged as continuous deviation disturbance, it is marked. At the same time, the system calls the relay channel to retransmit or resample the current signal, and re-performs filtering and fluctuation judgment, and summarizes and generates the signal fluctuation evaluation result.

[0152] The above is only the preferred embodiment of the present invention, and it does not limit the present invention in other forms. Any person skilled in the art may use the disclosed technical content to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, as long as it does not depart from the technical solution content of the present invention, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention still belong to the protection scope of the technical solution of the present invention.

Claims

1. A multi-bit control system based on digital coding, characterized in that, The system includes: Based on the current network status data monitored in real time, the network monitoring module collects bandwidth, latency, and error rate data, captures fluctuations in the transmission signal, evaluates the performance of the digital coding signal transmission conditions, and calculates the fluctuations in network performance to obtain the network status fluctuation index; According to the network status fluctuation index, the coding adjustment module analyzes the fluctuations in the current network bandwidth and latency, and based on the impact of the bandwidth change on the digital coding signal transmission rate, dynamically adjusts the coding complexity, calculates the adjusted coding complexity, and obtains the dynamic coding adaptation parameter; The coding adjustment module includes: Based on the network status fluctuation index, the bandwidth analysis sub-module obtains the bandwidth change data and time series information, calculates the bandwidth change rate and the bandwidth difference sequence, compares them with the bandwidth floating reference, identifies the unstable state of the bandwidth, calculates the critical fluctuation time interval, and obtains the bandwidth fluctuation degree; The latency judgment sub-module calls the bandwidth fluctuation degree, combines the network latency data, analyzes the maximum latency and minimum latency within the current time window, evaluates the average fluctuation amplitude of the latency, and judges the synchronization of the bandwidth fluctuation and the latency fluctuation to obtain the latency linkage interval quantity; Based on the latency linkage interval quantity, the complexity calculation sub-module adjusts the coding complexity, optimizes the signal compression rate, and uses the formula: ； Calculate the coding complexity adjustment value , to obtain the dynamic coding adaptation parameter, where represents the bandwidth fluctuation degree represents the delay linkage interval quantity represents the original coding rate represents the current signal compression ratio represents the parameter of the th coding segment, and represents the number of coding parameters; Based on the dynamic coding adaptation parameter, the signal reconstruction module gradually decodes the received digital coding signal, evaluates the quality of the data segment, analyzes the reconstruction accuracy of the signal. If the error is too large, it adjusts the decoding mode and corrects the error in the signal reconstruction process in real time to obtain the reconstruction error correction index; Based on the reconstruction error correction index, the fault tolerance control module combines the real-time feedback execution signal data, analyzes whether the current execution signal meets the requirements. If the signal quality does not meet the standard, it adjusts the power output of the control signal, corrects the signal transmission mode, and obtains the signal correction parameter.

2. The multi-bit control system based on digital coding according to claim 1, wherein The network status fluctuation index includes bandwidth fluctuation, latency fluctuation, and error rate fluctuation. The dynamic coding adaptation parameter includes compression rate and transmission rate. The reconstruction error correction index includes decoding deviation, error correction amount, and reconstructed signal error. The signal correction parameter includes signal transmission mode and signal execution quality.

3. The multi-bit control system based on digital coding according to claim 1, characterized in that, The network monitoring module includes: Based on the current network status data monitored in real time, the status data collection sub-module collects bandwidth, latency, and error rate data, performs preliminary screening and classification, and verifies the data integrity to obtain the verified status data; Based on the verified status data, the network fluctuation calculation sub-module calculates the fluctuations of the bandwidth, latency, and error rate data, evaluates the fluctuation range of each item of data, and uses the formula: ； Calculate the fluctuation amplitude of the network , where represents the th data point collected, represents the th data point collected, represents the number of data points; According to the fluctuation amplitude of the network, the transmission signal evaluation sub-module combines the signal quality to evaluate the stability performance of the transmission signal and obtains the network status fluctuation index.

4. The multi-bit control system based on digital coding according to claim 1, wherein The signal reconstruction module includes: Based on the dynamic coding adaptation parameter, the step-by-step decoding sub-module performs frame-level decoding on the received digital coding signal, analyzes the bit segment and the frame synchronization code, compares the decoded bit values according to the signal mapping rules in the dictionary table, and constructs the initial signal stream; The error analysis sub-module calls the initial signal flow, compares it with the reference waveform values in the target signal data, calculates the amplitude difference and change rate between adjacent sampling points, identifies the matching abnormal intervals between signals, and obtains the amplitude of the reconstructed error signal; The mode adjustment sub-module adjusts the coding mode according to the amplitude of the reconstructed error signal, corrects the errors in the signal reconstruction process in real time, using the formula: ； Obtain the reconstruction error correction index, where represents the adjustment intensity value, represents the -th sampling point of the initial signal sequence value, represents the corresponding -th sampling point in the target signal, represents the -th sampling point weight coefficient, represents the total number of sampling points.

5. The multi-bit control system based on digital coding according to claim 1, characterized in that The fault tolerance control module includes: The error judgment sub-module synchronously compares the signal amplitude sequence with the frequency change trend according to the reconstructed error correction index, calculates the difference between the amplitude-frequency deviation value and the correction index, judges whether the signal is within the acceptable interval, and obtains the amplitude-frequency deviation level; The signal regulation sub-module calls the amplitude-frequency deviation level and adjusts the power output and transmission mode of the signal, using the formula: ； Obtain the adjusted power output parameter ; where represents the intensity of the th signal detection, is the target signal intensity, is the number of detections, is the adjustment coefficient; The parameter generation sub-module detects the transmission coherence and frequency hopping volatility of the corrected signal according to the adjusted power output parameters, judges the signal response adjustment range, and obtains the signal correction parameters.

6. The multi-bit control system based on digital coding according to claim 1, characterized in that The system further includes: The signal processing module filters and enhances the control signal based on the signal correction parameters, monitors the signal fluctuation in real time, analyzes the signal fluctuation amplitude, judges whether it is abnormal according to the signal fluctuation amplitude. If the fluctuation deviation is too large, it triggers the retransmission or processing of the signal, and obtains the signal fluctuation evaluation result; The signal fluctuation evaluation result includes the fluctuation amplitude, fluctuation deviation, and signal stability.

7. The multi-bit control system based on digital coding according to claim 6, characterized in that, The signal processing module includes: The signal filtering sub-module filters and enhances the control signal based on the signal correction parameters, monitors the signal fluctuation in real time, performs segmented difference calculation and mean correction by collecting continuous waveform data, eliminates the discrete values in the deviation interval, and smooths the data to obtain the fluctuation denoising value; The fluctuation amplitude extraction sub-module calls the fluctuation denoising value, according to the fluctuation interval amplitude in the different time periods: ； Calculate the signal fluctuation intensity value , where represents the instantaneous value of the time period, represents the mean value of the instantaneous value, represents the jump value of the time period, represents the mean value of the jump value, represents the number of consecutive jumps, represents the number of intervals within the time period, is the total number of time periods; The abnormal judgment sub-module calls the signal fluctuation intensity value, identifies the signal section with deviation mutation, judges whether it exceeds the signal fluctuation tolerance range. If the fluctuation deviation is too large, it triggers the retransmission or processing of the signal, and obtains the signal fluctuation evaluation result.

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