Electric cabinet remote data acquisition system based on Internet of Things

Abstract

The invention provides an electric control box remote data acquisition system based on the Internet of Things, and relates to the technical field of data processing, and the method comprises the steps: obtaining the operation state data of an electric control box through a sensor, transmitting the operation state data through a wireless signal network, obtaining a data frame set, analyzing the data identifier of each data frame, verifying the integrity of the data, and obtaining the data frame set; determining performance parameters of the wireless signal network, detecting whether an abnormal change occurs in the transmission process, generating a solution when the abnormal change occurs, generating a retransmission signal when packet loss occurs in the transmission process, determining a retransmission queue according to the data identifier, and transmitting the retransmission signal according to the retransmission queue when delay occurs in the transmission process. The priority of a retransmission queue and the distribution of network bandwidth are dynamically adjusted, and when signal attenuation occurs in the transmission process, the execution sequence is adjusted according to the operation record and result of a solution by switching a transmission channel and adjusting transmission power. The transmission process of the operation data of the electric control box can be detected.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a remote data acquisition system for an electric control box based on the Internet of Things. Background Art

[0002] The existing remote data acquisition system for electric control boxes based on the Internet of Things has a remote monitoring function. The normal operation of the Internet of Things equipment depends on the stability of the network. In the remote area environment, there may be large network signal interference, resulting in unstable wireless network signals or communication interruptions.

[0003] For example, in some industrial applications, electric control boxes are usually deployed in environments far away from the main communication network. In this case, the equipment relies on long-distance wireless signal networks for data transmission. However, long-distance transmission will cause signal attenuation, slow data transmission speed, and increase packet loss and delay during transmission. Summary of the invention

[0004] The purpose of the present invention is to provide an electric control box remote data acquisition system based on the Internet of Things, aiming to solve the problems mentioned in the background technology.

[0005] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0006] A remote data acquisition system for an electric control box based on the Internet of Things, the system comprising:

[0007] The data acquisition module is used to obtain the operating status data of the electric control box through the sensor, and add transmission information to it to obtain a data frame set. The transmission information includes data identification, transmission queue, network bandwidth and transmission channel;

[0008] A signal encoding module is used to encode the data frame set and attach it to the wireless signal through modulation to obtain a transmission signal;

[0009] A signal receiving module is used to receive a transmission signal transmitted through a wireless signal network, and demodulate and decode it to obtain a data frame set;

[0010] A data analysis module is used to analyze the data identification of each data frame, verify the integrity of the data, and determine the performance parameters of the wireless signal network, including packet loss rate, transmission time and signal strength;

[0011] Anomaly detection module, used to screen performance parameters according to preset performance threshold groups and detect whether abnormal changes occur during transmission. The types of abnormal changes include packet loss, delay and signal attenuation;

[0012] The exception analysis module is used to generate solutions based on the type of abnormal changes that occur. The solutions include:

[0013] When packet loss occurs during transmission, a retransmission signal is generated, and the retransmission queue is determined based on the data identifier to retransmit;

[0014] When a delay occurs during transmission, the transmission time is reduced by dynamically adjusting the priority of the retransmission queue and the allocation of network bandwidth;

[0015] When signal attenuation occurs during transmission, the interference to signal strength is reduced by switching transmission channels and adjusting transmission power;

[0016] The feedback optimization module is used to adjust the execution order of the solutions and optimize the transmission process according to the operation records and results of the solutions.

[0017] Furthermore, the data identifier of each data frame is analyzed to verify the integrity of the data and determine the performance parameters of the wireless signal network, including:

[0018] Extracting a sequence number, a timestamp and a device identification of the data frame from the data identification;

[0019] Sort the sequence numbers of the data frames, and if there is a missing sequence number, mark the data frame as a lost frame;

[0020] Compare the timestamp of the data frame with the current time to calculate the actual transmission time of the data frame, and when the actual transmission time exceeds the preset transmission time threshold, mark the data frame as a delayed frame;

[0021] Check whether the device identification of the data frame is consistent with the device identification of the target device. If the device identifications are inconsistent, the data frame is discarded;

[0022] Count the number of all data frames received and the number of lost frames in a unit time, and calculate the packet loss rate based on them;

[0023] Count the actual transmission time of all data frames received within a unit time, and calculate the average value based on the actual transmission time to determine the transmission time;

[0024] The power indicator records changes in the transmitted power and determines the signal strength.

[0025] Furthermore, the performance parameters are screened according to the preset performance threshold group to detect whether abnormal changes occur during the transmission process, including:

[0026] Comparing the performance parameters with the preset performance threshold groups one by one;

[0027] When the packet loss rate is higher than the preset packet loss rate threshold, a packet loss anomaly mark is generated;

[0028] When the transmission time is higher than the preset delay threshold, a delay anomaly flag is generated;

[0029] When the signal strength is lower than the preset signal strength threshold, a signal attenuation abnormality mark is generated;

[0030] When the performance parameter triggers an abnormal flag, the type of abnormal change that occurs in the transmission process is determined.

[0031] Furthermore, when packet loss occurs during transmission, a retransmission signal is generated, and the order of the retransmission queue is determined according to the data identifier, and retransmission is performed, including:

[0032] Generate a retransmission signal based on the packet loss exception flag and the lost frame, and send it to the signal encoding module;

[0033] The importance and urgency of the lost frame are extracted from the data identifier, and the priority score of the lost frame is calculated. The calculation formula of the priority score is:

[0034]

[0035] Where P is the priority score of the lost frame, X is the importance of the lost frame, Y is the urgency of the lost frame, T is the waiting time of the retransmission queue, A is the weight value of the abnormal change of packet loss, ρ and μ are adjustment coefficients, and W x ,W y ,W a are the weight coefficients of importance, urgency, and abnormal change of packet loss respectively;

[0036] According to the priority score of the lost frame, the order of the retransmission queue is determined, and the retransmission data frame is transmitted and the retransmission status is recorded;

[0037] When the retransmission status is failed, a compensation data frame is generated to replace the lost frame.

[0038] Further, when packet loss occurs during transmission, a retransmission signal is generated, and the priority of the retransmission queue is determined according to the data identifier, and retransmission is performed, which also includes:

[0039] Determine the position of the lost frame in the data stream based on the sequence number and timestamp of the lost frame;

[0040] According to the time characteristics of the lost frames, the lost frames are divided into periodic data and non-periodic data;

[0041] When the lost frame is periodic data, the compensation data is obtained according to the change cycle of the device status data and the timestamp of the lost frame, combined with the data frame values ​​of the timestamps before and after the lost frame;

[0042] When the lost frame is non-periodic data, the compensation data is calculated using linear interpolation based on the timestamps before and after the lost frame and its data frame value;

[0043] A compensation data frame is generated according to the compensation data, and a corresponding timestamp and device identification are given to it.

[0044] Furthermore, when a delay occurs during transmission, the transmission time is reduced by dynamically adjusting the priority of the retransmission queue and the allocation of network bandwidth, including:

[0045] Calculate the priority score of the delayed frame according to the delay anomaly mark and the delayed frame;

[0046] Adjust the priority of the retransmission queue according to the priority score of the delayed frame;

[0047] Analyze the current network bandwidth utilization, dynamically adjust the network bandwidth allocation ratio, allocate the network bandwidth to the transmission path of the delayed frame, and ensure the transmission of the delayed frame;

[0048] The delayed frame is transmitted and the retransmission time is recorded.

[0049] Furthermore, when a delay occurs during the transmission process, the transmission time is reduced by dynamically adjusting the priority of the retransmission queue and the allocation of network bandwidth, which also includes:

[0050] When the retransmission transmission time is not significantly reduced, analyzing characteristic parameters of the backup transmission path, the characteristic parameters including packet loss rate, delay time and transmission stability;

[0051] According to the characteristic parameters, the characteristic score of the backup transmission path is calculated. The calculation formula of the characteristic score is:

[0052]

[0053] Among them, S p Score the characteristics of path p, where p is the index of the path, D p is the delay time of path p, L p is the packet loss rate of path p, I p is the transmission stability of path p, D max is the preset delay threshold, W d ,W l ,W i are the coefficients of delay time, packet loss rate and transmission stability respectively, and k is a constant;

[0054] Switch the delayed frame to the backup transmission path with the highest characteristic score for transmission;

[0055] The operation results of each delay adjustment are recorded, and priority adjustment and network bandwidth allocation ratio are dynamically optimized based on them to improve the efficiency of subsequent transmission processes.

[0056] Furthermore, when signal attenuation occurs during transmission, the interference to the signal strength is reduced by switching the transmission channel and adjusting the transmission power, including:

[0057] By collecting the interference level of the current channel, when the interference level is higher than the preset interference threshold, the channel switching mechanism is triggered;

[0058] Retrieve all available channels and obtain attribute parameters of each channel, including signal strength, interference level, network load and bandwidth utilization;

[0059] The attribute score of the channel is calculated based on the performance parameters. The calculation formula of the attribute score is:

[0060]

[0061] Among them, Q c is the attribute score of channel c, c is the index of the channel, H c is the signal strength of channel c, V c is the interference level of channel c, N c is the network load of channel c, B c is the bandwidth utilization of channel c, M c is the maximum bandwidth of channel c, W h ,W v ,W b are the coefficients of signal strength, interference level and bandwidth utilization, α and β are adjustment coefficients, and ∈ is a constant;

[0062] The channel with the highest attribute score is marked as the target channel, and the current channel is switched to the target channel.

[0063] Furthermore, when signal attenuation occurs during transmission, the interference degree to the signal strength is reduced by switching the transmission channel and adjusting the transmission power, which also includes:

[0064] Compensate for signal strength by adjusting the transmission power, gradually increasing the transmission power until the signal strength returns to normal levels;

[0065] When adjusting the transmission power has no effect, the transmission rate is reduced to ensure the stability of the transmission process;

[0066] The effects of switching channels and adjusting transmission power are recorded, and the performance score calculation formula is adjusted accordingly.

[0067] Furthermore, according to the operation records and results of the solutions, the execution order of the solutions is adjusted to optimize the transmission process, including:

[0068] Set the exception handling priority for the type of abnormal change, in descending order, namely packet loss abnormality, delay abnormality, and signal attenuation abnormality;

[0069] When multiple exceptions occur at the same time, the order in which the solutions are executed is determined based on the exception handling priority:

[0070] Prioritize packet loss exceptions and restore data integrity by generating retransmission signals and adjusting transmission queues;

[0071] Secondly, deal with latency anomalies and reduce latency by adjusting queue priority and bandwidth allocation;

[0072] Finally, the signal attenuation anomaly is processed and the signal strength is improved through channel switching and power adjustment;

[0073] Record the performance of each solution.

[0074] The above solution of the present invention includes at least the following beneficial effects:

[0075] The present invention can accurately verify the integrity of each data frame by analyzing the data identifier, sequence number sorting can quickly identify lost frames, timestamp analysis can detect whether there are delayed frames, and device identification verification prevents the mistransmission of data frames of other devices. This one-by-one checking mechanism greatly reduces the data error rate and provides a reliable data foundation for the system. By counting the packet loss rate, transmission time and signal strength, a comprehensive performance evaluation is provided for the network status of the system. This multi-dimensional data analysis helps to discover potential problems in advance and prevent system stagnation due to network failures.

[0076] The present invention solves the problem by generating a retransmission signal and adjusting the order of the retransmission queue. The retransmission mechanism uses the data identifier to quickly locate the lost frame and regenerate the transmission signal to ensure that all data frames are successfully transmitted to the receiving end, thereby avoiding the loss or distortion of the monitoring data. The retransmission queue is sorted according to the importance and urgency parameters in the data identifier to ensure the system's timely response to key information. The bandwidth adjustment and queue management strategy are combined in the packet loss processing process to effectively avoid network congestion and resource waste, and improve the retransmission efficiency.

[0077] The present invention reduces transmission time by adjusting the retransmission queue priority and network bandwidth allocation, and ensures that delayed data obtains priority resources in the transmission link by dynamically adjusting the priority of delayed data, thereby shortening the system response time. Through the bandwidth allocation optimization strategy, more bandwidth is allocated to the transmission path where the delayed data frame is located, while reducing the bandwidth occupation of non-critical data. This allocation method can make full use of existing network resources without additional bandwidth. By dynamically detecting and adjusting the transmission path of delayed data, the optimal path is selected according to the path score to avoid network congestion and high-delay areas. This non-global optimization method reduces the delay while ensuring the stability of the overall operation of the system.

[0078] The present invention solves the problem of signal attenuation by switching transmission channels and adjusting transmission power. By analyzing the interference degree in real time and switching to the optimal channel, the continuous influence of signal interference is avoided, and the stability and continuity of data transmission are ensured. When the signal quality decreases, the power is gradually adjusted to reduce power waste and extend the battery life of the equipment. It can also avoid transmission failures caused by channel interference or insufficient power, and ensure that the remote monitoring system can operate stably even in extreme environments. The solution can adapt to different signal attenuation scenarios through a flexible adjustment mechanism, thereby significantly improving the applicability of the system.

[0079] The present invention can dynamically adjust the execution order of solutions according to operation records, and can dynamically adjust the priority of solutions by analyzing the feedback of each exception processing result, ensuring that the system can solve problems with the highest efficiency in different scenarios. Recording the success rate and failure reasons of historical operations helps to avoid the recurrence of similar problems, thereby reducing the occurrence rate of exceptions in system operation, adjusting parameters such as bandwidth and queue priority according to feedback results, further improving the resource utilization of the system, and realizing self-optimization capabilities, thereby improving the intelligence level of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] Figure 1 It is a flowchart of a remote data acquisition system for an electric control box based on the Internet of Things provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0081] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0082] like Figure 1 As shown, an embodiment of the present invention proposes a remote data acquisition system for an electric control box based on the Internet of Things, and the system includes:

[0083] The data acquisition module is used to obtain the operating status data of the electric control box through the sensor, and add transmission information to it to obtain a data frame set. The transmission information includes data identification, transmission queue, network bandwidth and transmission channel;

[0084] A signal encoding module is used to encode the data frame set and attach it to the wireless signal through modulation to obtain a transmission signal;

[0085] A signal receiving module is used to receive a transmission signal transmitted through a wireless signal network, and demodulate and decode it to obtain a data frame set;

[0086] A data analysis module is used to analyze the data identification of each data frame, verify the integrity of the data, and determine the performance parameters of the wireless signal network, including packet loss rate, transmission time and signal strength;

[0087] Anomaly detection module, used to screen performance parameters according to preset performance threshold groups and detect whether abnormal changes occur during transmission. The types of abnormal changes include packet loss, delay and signal attenuation;

[0088] The exception analysis module is used to generate solutions based on the type of abnormal changes that occur. The solutions include:

[0089] When packet loss occurs during transmission, a retransmission signal is generated, and the retransmission queue is determined based on the data identifier to retransmit;

[0090] When a delay occurs during transmission, the transmission time is reduced by dynamically adjusting the priority of the retransmission queue and the allocation of network bandwidth;

[0091] When signal attenuation occurs during transmission, the interference to signal strength is reduced by switching transmission channels and adjusting transmission power;

[0092] The feedback optimization module is used to adjust the execution order of the solutions and optimize the transmission process according to the operation records and results of the solutions.

[0093] In an embodiment of the present invention, a data acquisition module obtains the operating status data of the electric control box through a sensor, and adds information including data identification, transmission queue, network bandwidth and transmission channel to the data to generate a data frame set to ensure the integrity and efficiency of data transmission. Through the precise addition of data identification and the reasonable allocation of transmission queues, the integrity and efficiency of data transmission can be ensured to the maximum extent, which is particularly suitable for industrial environments with poor network conditions; the signal encoding module encodes and modulates the data frame set, attaches it to the wireless signal to generate a transmission signal, and reduces the interference risk during the transmission process through data compression and modulation processing, which is particularly suitable for long-distance wireless communication environments; after receiving the transmission signal, the signal receiving module restores the data frame set through demodulation and decoding. The demodulation and decoding mechanism ensures the lossless restoration capability of data during transmission, and provides reliable input support for subsequent data analysis.

[0094] The data analysis module verifies the integrity of the data frame by analyzing the data identifier, and counts performance parameters such as packet loss rate, transmission time and signal strength. Accurate identifier verification and performance parameter analysis can not only quickly detect transmission anomalies, but also provide basic data support for the dynamic optimization of the system; the anomaly detection module screens packet loss, delay and signal attenuation based on performance parameters and preset threshold groups, and generates corresponding anomaly tags. It can quickly and accurately identify and classify abnormal changes in transmission, thereby improving the system's response speed to abnormal situations; the anomaly analysis module dynamically generates and executes targeted solutions based on the three types of abnormal changes: packet loss, delay and signal attenuation, significantly improving the reliability and efficiency of data transmission; the feedback optimization module records the execution results and effects of these operations, dynamically adjusts the execution order of the solutions, and gradually optimizes the transmission process. Through continuous recording and adjustment, the system's self-learning and self-optimization capabilities are realized, effectively reducing the response time of exception handling and improving overall performance.

[0095] The operating status data of the electric control box is obtained through the sensor, and transmission information is added to it to obtain a data frame set. The transmission information includes data identification, transmission queue, network bandwidth and transmission channel, specifically including:

[0096] Various operating data of the electric control box are collected through different types of sensors, and transmission information is attached to them. The data identifiers include serial numbers, timestamps, and device identifiers, which ensure the integrity and uniqueness of the data during the transmission process. For example, the serial number can help the receiving end to reorganize the data frame in sequence, the timestamp is used to verify the timeliness of data transmission, and the device identifier ensures the accuracy of the data source; the transmission queue is used to define the priority of the data frame to ensure that key data is transmitted first, for example, alarm data and fault information can be assigned to a high-priority queue to achieve fast transmission; the network bandwidth and channel information are based on the network conditions in the collection environment, and the appropriate network bandwidth and channel parameters are pre-set to provide optimization support for subsequent data transmission.

[0097] The data frame set is encoded and attached to the wireless signal through modulation to obtain a transmission signal, which specifically includes:

[0098] The data frame set is encoded and compressed using compression coding to compress and integrate the data frame set into a more compact transmission unit, which not only reduces data redundancy but also enhances anti-interference ability; it is then attached to the wireless signal through modulation technology to form a transmission signal that can be transmitted through the network, and the encoded data is embedded in the wireless signal through the selected modulation method frequency modulation, thereby improving the signal strength and stability of the data during transmission.

[0099] The receiving of a transmission signal transmitted through a wireless signal network, and demodulation and decoding thereof to obtain a data frame set specifically includes:

[0100] The wireless signal is captured by the receiving device to ensure that the integrity of the signal is not affected by the external environment, and the demodulation and decoding method matching the signal encoding module is used to gradually restore the original data frame set.

[0101] In a preferred embodiment of the present invention, analyzing the data identifier of each data frame, verifying the integrity of the data, and determining the performance parameters of the wireless signal network include:

[0102] Extracting a sequence number, a timestamp and a device identification of the data frame from the data identification;

[0103] Sort the sequence numbers of the data frames, and if there is a missing sequence number, mark the data frame as a lost frame;

[0104] Compare the timestamp of the data frame with the current time to calculate the actual transmission time of the data frame, and when the actual transmission time exceeds the preset transmission time threshold, mark the data frame as a delayed frame;

[0105] Check whether the device identification of the data frame is consistent with the device identification of the target device. If the device identifications are inconsistent, the data frame is discarded;

[0106] Count the number of all data frames received and the number of lost frames in a unit time, and calculate the packet loss rate based on them;

[0107] Count the actual transmission time of all data frames received within a unit time, and calculate the average value based on the actual transmission time to determine the transmission time;

[0108] The power indicator records changes in the transmitted power and determines the signal strength.

[0109] In an embodiment of the present invention, the serial number, timestamp and device identification of the data frame are extracted from the data identification. By extracting and parsing the above identification information, the accuracy and efficiency of data processing are ensured, and the integrity of the data is verified; the packet loss rate is calculated by counting the number of data frames received and the number of lost frames per unit time. The packet loss rate is an important indicator for measuring network stability. By counting the packet loss rate in continuous time periods, it can also provide a basis for trend analysis of network status, thereby optimizing channel selection and bandwidth allocation strategies; the transmission time of all data frames received per unit time is counted, and the average value is calculated. The statistics of actual transmission time reflect the real-time transmission capability of the network; the transmission power change of the data frame is recorded by the power indicator, and the change curve of the signal strength is recorded in real time to identify possible signal attenuation. By analyzing the trend of signal strength changes, the potential risk of network fluctuations is predicted. The monitoring of signal strength provides key input for the subsequent anomaly detection module.

[0110] The sequence number, timestamp and device identification of the data frame are extracted from the data identification, specifically including:

[0111] The sequence number is used as the unique identifier of the data frame to distinguish the position and order of each data frame. The sequence numbers of the data frames are sorted. If the continuity of the sequence number is interrupted, it is marked as a lost frame. This sorting mechanism ensures the orderliness of data reception and can quickly identify the loss of data frames.

[0112] The timestamp records the generation time of the data frame, which is used to calculate the transmission time and determine the timeliness of the data. The received timestamp is compared with the current time. If it exceeds the preset transmission time threshold, it is marked as a delayed frame and used to calculate the actual transmission time.

[0113] The device identifier indicates the source of the data, ensures that the received data matches the target device, and checks whether the device identifier of the data frame is consistent with the target device. If not, the data frame is discarded, which can effectively prevent erroneous operations caused by the wrong source.

[0114] In a preferred embodiment of the present invention, the performance parameters are screened according to a preset performance threshold group to detect whether abnormal changes occur during the transmission process, including:

[0115] Comparing the performance parameters with the preset performance threshold groups one by one;

[0116] When the packet loss rate is higher than the preset packet loss rate threshold, a packet loss anomaly mark is generated;

[0117] When the transmission time is higher than the preset delay threshold, a delay anomaly flag is generated;

[0118] When the signal strength is lower than the preset signal strength threshold, a signal attenuation abnormality mark is generated;

[0119] When the performance parameter triggers an abnormal flag, the type of abnormal change that occurs in the transmission process is determined.

[0120] In the embodiment of the present invention, by comparing these parameters with the preset performance thresholds one by one, specific abnormality types can be accurately screened and marked, providing clear input for subsequent abnormality analysis and solutions. The determination of the abnormal change type can clearly distinguish different types of problems.

[0121] When a performance parameter triggers an abnormal flag, the type of abnormal change that occurs in the transmission process is determined, including:

[0122] Packet loss anomaly: some data frames are lost due to network interference or channel congestion;

[0123] Delay anomaly is the phenomenon that the data frame transmission time exceeds the preset range due to network congestion or improper priority allocation;

[0124] Signal attenuation is the decrease in signal strength caused by channel interference, physical obstacles or insufficient power.

[0125] In a preferred embodiment of the present invention, when packet loss occurs during transmission, a retransmission signal is generated, and the order of the retransmission queue is determined according to the data identifier, and retransmission is performed, including:

[0126] Generate a retransmission signal based on the packet loss exception flag and the lost frame, and send it to the signal encoding module;

[0127] The importance and urgency of the lost frame are extracted from the data identifier, and the priority score of the lost frame is calculated. The calculation formula of the priority score is:

[0128]

[0129] Where P is the priority score of the lost frame, X is the importance of the lost frame, Y is the urgency of the lost frame, T is the waiting time of the retransmission queue, A is the weight value of the abnormal change of packet loss, δ and μ are adjustment coefficients, and W x ,W y ,W aare the weight coefficients of importance, urgency, and abnormal change of packet loss respectively;

[0130] According to the priority score of the lost frame, the order of the retransmission queue is determined, and the retransmission data frame is transmitted and the retransmission status is recorded;

[0131] When the retransmission status is failed, a compensation data frame is generated to replace the lost frame.

[0132] In an embodiment of the present invention, a retransmission signal is generated according to the packet loss exception mark and the lost frame, and is sent to the signal encoding module. Through this detection and retransmission signal generation mechanism, the system can quickly respond to data loss problems, trigger the retransmission process, and ensure the integrity of the data. This mechanism avoids monitoring failures or data processing errors caused by data loss; calculating the priority score of the lost frame can realize dynamic data queue management, so that the most critical and urgent data frames are transmitted first. This mechanism significantly reduces the impact of packet loss on system operation and ensures that critical data can be restored in time; determining the order of the retransmission queue based on the priority score of the lost frame can effectively utilize limited network bandwidth resources, give priority to the transmission of important data that affects the stability or security of system operation, and reduce network congestion and loss risks.

[0133] In a preferred embodiment of the present invention, when packet loss occurs during transmission, a retransmission signal is generated, and the priority of the retransmission queue is determined according to the data identifier, and retransmission is performed, which also includes:

[0134] Determine the position of the lost frame in the data stream based on the sequence number and timestamp of the lost frame;

[0135] According to the time characteristics of the lost frames, the lost frames are divided into periodic data and non-periodic data;

[0136] When the lost frame is periodic data, the compensation data is obtained according to the change cycle of the device status data and the timestamp of the lost frame, combined with the data frame values ​​of the timestamps before and after the lost frame;

[0137] When the lost frame is non-periodic data, the compensation data is calculated using linear interpolation based on the timestamps before and after the lost frame and its data frame value;

[0138] A compensation data frame is generated according to the compensation data, and a corresponding timestamp and device identification are given to it.

[0139] In an embodiment of the present invention, the specific position of the lost frame in the data stream is located by using the serial number and timestamp information of the lost frame, so that the specific time point of the lost data frame in the data stream can be accurately located, thereby avoiding misjudgment and redundant compensation operations, and improving the efficiency of the subsequent compensation mechanism; distinguishing the type of lost data makes the compensation strategy targeted, which helps the system to select different compensation methods according to actual scenarios, thereby improving the compensation effect and saving system resources; the compensation data frame generation process ensures that the receiving end can receive the complete data stream, and verifies its authenticity through the combination of the timestamp and the device identification, thereby ensuring the integrity and stability of the system transmission data.

[0140] Among them, when the lost frame is periodic data, the compensation data is obtained according to the change cycle of the device status data and the timestamp of the lost frame, combined with the data frame values ​​of the timestamps before and after the lost frame, including:

[0141] Periodic data refers to frames with fixed time intervals for transmitting data. For example, a sensor collects device status data at fixed intervals. Time interpolation calculation is performed based on the change cycle of the device status data and the timestamp of the lost data frame, combined with the data frame values ​​in the time range before and after.

[0142] When the lost frame is non-periodic data, the compensation data is calculated by linear interpolation according to the timestamps before and after the lost frame and its data frame value, which specifically includes:

[0143] Non-periodic data refers to random data that does not have a fixed interval in time, such as fault alarm data or burst transmission data. The compensation data value is calculated using the linear interpolation method based on the timestamp of the lost data frame and the data frame values ​​before and after it.

[0144] In a preferred embodiment of the present invention, when a delay occurs during transmission, the transmission time is reduced by dynamically adjusting the priority of the retransmission queue and the allocation of network bandwidth, including:

[0145] Calculate the priority score of the delayed frame according to the delay anomaly mark and the delayed frame;

[0146] Adjust the priority of the retransmission queue according to the priority score of the delayed frame;

[0147] Analyze the current network bandwidth utilization, dynamically adjust the network bandwidth allocation ratio, allocate the network bandwidth to the transmission path of the delayed frame, and ensure the transmission of the delayed frame;

[0148] The delayed frame is transmitted and the retransmission time is recorded.

[0149] In an embodiment of the present invention, the priority of the retransmission queue is adjusted according to the priority score of the delayed frame. Through the priority score of the delayed frame, the system can dynamically evaluate the transmission urgency of different data frames and adjust the order of the transmission queue so that key data can be transmitted as early as possible, thereby reducing the impact of delays on data integrity and real-time performance; analyze the current network bandwidth utilization, dynamically adjust the network bandwidth allocation ratio, and through real-time monitoring of network bandwidth usage, the system can quickly identify the cause of network congestion, thereby implementing an effective bandwidth allocation strategy to ensure that delayed frames are transmitted preferentially through paths with sufficient resources.

[0150] The priority score of the delayed frame is calculated according to the delay abnormality mark and the delayed frame, and the calculation formula of the priority score is the same as the calculation formula of the priority score of the lost frame.

[0151] Among them, analyzing the current network bandwidth utilization and dynamically adjusting the network bandwidth allocation ratio include:

[0152] Real-time analysis of the current network bandwidth usage, including the current network bandwidth utilization, the proportion of network bandwidth occupied by the data traffic being transmitted, whether the data transmission path is congested, etc. Based on the analysis of the current network bandwidth usage, the network bandwidth allocation is dynamically adjusted to increase the bandwidth allocation ratio of delayed data frames, dynamically allocate more network bandwidth to data frames with high delay priority scores, reduce the bandwidth allocation ratio of non-critical data frames, and reclaim part of the bandwidth from low-priority data streams to give priority to the transmission of delayed data.

[0153] In a preferred embodiment of the present invention, when a delay occurs during transmission, the transmission time is reduced by dynamically adjusting the priority of the retransmission queue and the allocation of network bandwidth, and further comprising:

[0154] When the retransmission transmission time is not significantly reduced, analyzing characteristic parameters of the backup transmission path, the characteristic parameters including packet loss rate, delay time and transmission stability;

[0155] According to the characteristic parameters, the characteristic score of the backup transmission path is calculated. The calculation formula of the characteristic score is:

[0156]

[0157] Among them, S p Score the characteristics of path p, where p is the index of the path, D p is the delay time of path p, L p is the packet loss rate of path p, I p is the transmission stability of path p, D max is the preset delay threshold, W d ,W l ,W iare the coefficients of delay time, packet loss rate and transmission stability respectively, and k is a constant;

[0158] Switch the delayed frame to the backup transmission path with the highest characteristic score for transmission;

[0159] The operation results of each delay adjustment are recorded, and priority adjustment and network bandwidth allocation ratio are dynamically optimized based on the results to improve the efficiency of subsequent transmission processes.

[0160] In an embodiment of the present invention, the characteristic scores of the backup transmission paths are calculated, and the delayed frames are switched to the backup transmission paths with the highest characteristic scores for transmission. By dynamically searching and switching the backup paths, the system can optimize data transmission through multi-path alternatives under complex network conditions, thereby significantly reducing delay problems and improving network availability and transmission reliability. The operation results of each delay adjustment are recorded to accumulate historical data, and the effectiveness of the current delay processing solution is analyzed based on the historical data. By continuously recording and analyzing the delay adjustment operation results, the system can continuously optimize the delay frame priority adjustment strategy according to the actual transmission effect, and automatically optimize the network bandwidth allocation ratio according to the recorded historical delay adjustment results to meet current network needs and alleviate network congestion.

[0161] In a preferred embodiment of the present invention, when signal attenuation occurs during transmission, the interference degree to the signal strength is reduced by switching the transmission channel and adjusting the transmission power, including:

[0162] By collecting the interference level of the current channel, when the interference level is higher than the preset interference threshold, the channel switching mechanism is triggered;

[0163] Retrieve all available channels and obtain attribute parameters of each channel, including signal strength, interference level, network load and bandwidth utilization;

[0164] The attribute score of the channel is calculated based on the performance parameters. The calculation formula of the attribute score is:

[0165]

[0166] Among them, Q c is the attribute score of channel c, c is the index of the channel, H c is the signal strength of channel c, V c is the interference level of channel c, N c is the network load of channel c, B c is the bandwidth utilization of channel c, M c is the maximum bandwidth of channel c, W h ,W v ,W bare the coefficients of signal strength, interference level and bandwidth utilization, α and β are adjustment coefficients, and ∈ is a constant;

[0167] The channel with the highest attribute score is marked as the target channel, and the current channel is switched to the target channel.

[0168] In an embodiment of the present invention, by collecting the interference level of the current channel, when the interference level is higher than a preset interference threshold, the channel switching mechanism is triggered. Through real-time channel interference detection, the system can identify in real time whether the signal strength of the current transmission path is affected by environmental factors or external signal interference; the attribute score of the channel is calculated according to the performance parameters. Through the scoring mechanism, the system can effectively select the channel that best suits the current transmission conditions from all available channels, thereby minimizing interference and transmission failure rate during data transmission; the channel with the highest attribute score is marked as the target channel, and the current channel is switched to the target channel. By switching to a low-interference channel, the stability and reliability of data transmission are significantly enhanced, especially in an environment where the transmission channel is unstable.

[0169] In a preferred embodiment of the present invention, when signal attenuation occurs during transmission, the interference degree to the signal strength is reduced by switching the transmission channel and adjusting the transmission power, and further comprising:

[0170] Compensate for signal strength by adjusting the transmission power, gradually increasing the transmission power until the signal strength returns to normal levels;

[0171] When adjusting the transmission power has no effect, the transmission rate is reduced to ensure the stability of the transmission process;

[0172] The effects of switching channels and adjusting transmission power are recorded, and the performance score calculation formula is adjusted accordingly.

[0173] In an embodiment of the present invention, the signal strength is compensated by adjusting the transmission power and gradually increasing the transmission power. By increasing the transmission power in steps, the system can effectively compensate for the decrease in signal strength caused by signal attenuation, while avoiding equipment overheating or energy waste caused by a one-time large adjustment; when adjusting the transmission power has no effect, the transmission rate is reduced. By appropriately adjusting the transmission rate, the signal transmission frequency is reduced, the demand for channel resources is reduced, and the transmission quality is further stabilized to ensure that data can be smoothly transmitted to the receiving end. The operational effects of switching channels and adjusting the transmission power are recorded, and the performance score calculation formula is adjusted accordingly. Through historical performance data analysis, the optimal adjustment strategy in the current environment is dynamically learned, which helps to improve the automated response speed and effect of similar signal attenuation problems in the future.

[0174] The signal strength is compensated by adjusting the transmission power, and the transmission power is gradually increased until the signal strength returns to a normal level, specifically including:

[0175] When the current signal strength is detected to be attenuated, the system starts the transmission power adjustment mechanism:

[0176] Initial incremental adjustment, the system gradually increases the transmission power of the current wireless communication device in smaller steps;

[0177] Dynamic power increment calculation: dynamically calculate the incremental value of transmission power in each time interval based on the actual signal strength measurement results and the signal target strength;

[0178] The increments are applied gradually, and after each power adjustment the system measures in real time whether the signal strength at the receiving end has returned to the target level.

[0179] In a preferred embodiment of the present invention, the execution order of the solutions is adjusted according to the operation records and results of the solutions, and the transmission process is optimized, including:

[0180] Set the exception handling priority for the type of abnormal change, in descending order, namely packet loss abnormality, delay abnormality, and signal attenuation abnormality;

[0181] When multiple exceptions occur at the same time, the order in which the solutions are executed is determined based on the exception handling priority:

[0182] Prioritize packet loss exceptions and restore data integrity by generating retransmission signals and adjusting transmission queues;

[0183] Secondly, deal with latency anomalies and reduce latency by adjusting queue priority and bandwidth allocation;

[0184] Finally, the signal attenuation anomaly is processed and the signal strength is improved through channel switching and power adjustment;

[0185] Record the performance of each solution.

[0186] In an embodiment of the present invention, the type of abnormal change is set as an exception handling priority, and the order of solutions is dynamically adjusted, so that the system can flexibly select a processing path according to actual environmental changes, thereby shortening the fault response time and improving the continuity and reliability of data transmission; the execution effect of each solution is recorded, and continuous effect monitoring and data iteration enable the system to have learning capabilities, and can dynamically evolve its decision-making logic according to environmental changes and abnormal feedback, thereby improving the intelligence level of the system.

[0187] Among them, the type of abnormal change is set as the exception handling priority, including:

[0188] The system sets priorities for different types of exceptions and handles them in order from high to low:

[0189] Packet loss may lead to data transmission loss, directly affecting the operation of core services, so it should be handled with priority;

[0190] Delay will affect the real-time nature of data transmission and should be treated as a secondary priority;

[0191] Although signal attenuation will also affect the transmission quality, the impact is relatively small and is handled last;

[0192] The execution order of each exception plan is dynamically adjusted based on historical feedback and current abnormal performance. For example, if historical records show that the current network status is more likely to trigger delay exceptions, the system can automatically increase the priority of delay exception processing.

[0193] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A remote data acquisition system for electric control boxes based on the Internet of Things, characterized in that: The system comprises: The data acquisition module is used to obtain the operating status data of the electric control box through the sensor, and add transmission information to it to obtain a data frame set. The transmission information includes data identification, transmission queue, network bandwidth and transmission channel; A signal encoding module is used to encode the data frame set and attach it to the wireless signal through modulation to obtain a transmission signal; A signal receiving module is used to receive a transmission signal transmitted through a wireless signal network, and demodulate and decode it to obtain a data frame set; A data analysis module is used to analyze the data identification of each data frame, verify the integrity of the data, and determine the performance parameters of the wireless signal network, including packet loss rate, transmission time and signal strength; Anomaly detection module, used to screen performance parameters according to preset performance threshold groups and detect whether abnormal changes occur during transmission. The types of abnormal changes include packet loss, delay and signal attenuation; The exception analysis module is used to generate solutions based on the type of abnormal changes that occur. The solutions include: When packet loss occurs during transmission, a retransmission signal is generated, and the retransmission queue is determined based on the data identifier to retransmit; When a delay occurs during transmission, the transmission time is reduced by dynamically adjusting the priority of the retransmission queue and the allocation of network bandwidth; When signal attenuation occurs during transmission, the interference to signal strength is reduced by switching transmission channels and adjusting transmission power; The feedback optimization module is used to adjust the execution order of the solutions and optimize the transmission process according to the operation records and results of the solutions.

2. According to the Internet of Things-based electric control box remote data acquisition system of claim 1, it is characterized in that: Analyze the data identifier of each data frame, verify the integrity of the data, and determine the performance parameters of the wireless signal network, including: Extracting a sequence number, a timestamp and a device identification of the data frame from the data identification; Sort the sequence numbers of the data frames, and if there is a missing sequence number, mark the data frame as a lost frame; Compare the timestamp of the data frame with the current time to calculate the actual transmission time of the data frame, and when the actual transmission time exceeds the preset transmission time threshold, mark the data frame as a delayed frame; Check whether the device identification of the data frame is consistent with the device identification of the target device. If the device identifications are inconsistent, the data frame is discarded; Count the number of all data frames received and the number of lost frames in a unit time, and calculate the packet loss rate based on them; Count the actual transmission time of all data frames received within a unit time, and calculate the average value based on the actual transmission time to determine the transmission time; The power indicator records changes in the transmitted power and determines the signal strength.

3. According to the Internet of Things-based electric control box remote data acquisition system of claim 2, it is characterized in that: Screen performance parameters according to preset performance threshold groups to detect whether abnormal changes occur during transmission, including: Comparing the performance parameters with the preset performance threshold groups one by one; When the packet loss rate is higher than the preset packet loss rate threshold, a packet loss anomaly mark is generated; When the transmission time is higher than the preset delay threshold, a delay anomaly flag is generated; When the signal strength is lower than the preset signal strength threshold, a signal attenuation abnormality mark is generated; When the performance parameter triggers an abnormal flag, the type of abnormal change that occurs in the transmission process is determined.

4. According to the Internet of Things-based electric control box remote data acquisition system of claim 3, it is characterized in that: When packet loss occurs during transmission, a retransmission signal is generated, and the order of the retransmission queue is determined according to the data identifier, and retransmission is performed, including: Generate a retransmission signal based on the packet loss exception flag and the lost frame, and send it to the signal encoding module; The importance and urgency of the lost frame are extracted from the data identifier, and the priority score of the lost frame is calculated. The calculation formula of the priority score is: Where P is the priority score of the lost frame, X is the importance of the lost frame, Y is the urgency of the lost frame, T is the waiting time of the retransmission queue, A is the weight value of the abnormal change of packet loss, δ and μ are adjustment coefficients, and W x ,W y ,W a are the weight coefficients of importance, urgency, and abnormal change of packet loss respectively; According to the priority score of the lost frame, the order of the retransmission queue is determined, and the retransmission data frame is transmitted and the retransmission status is recorded; When the retransmission status is failed, a compensation data frame is generated to replace the lost frame.

5. The electric control box remote data acquisition system based on the Internet of Things according to claim 4 is characterized in that: When packet loss occurs during transmission, a retransmission signal is generated, and the priority of the retransmission queue is determined according to the data identifier, and retransmission is performed, which also includes: Determine the position of the lost frame in the data stream based on the sequence number and timestamp of the lost frame; According to the time characteristics of the lost frames, the lost frames are divided into periodic data and non-periodic data; When the lost frame is periodic data, the compensation data is obtained according to the change cycle of the device status data and the timestamp of the lost frame, combined with the data frame values ​​of the timestamps before and after the lost frame; When the lost frame is non-periodic data, the compensation data is calculated using linear interpolation based on the timestamps before and after the lost frame and its data frame value; According to the compensation data, a compensation data frame is generated and given a corresponding timestamp and device identification.

6. The electric control box remote data acquisition system based on the Internet of Things according to claim 5 is characterized in that: When a delay occurs during transmission, the transmission time is reduced by dynamically adjusting the priority of the retransmission queue and the allocation of network bandwidth, including: Calculate the priority score of the delayed frame according to the delay anomaly mark and the delayed frame; Adjust the priority of the retransmission queue according to the priority score of the delayed frame; Analyze the current network bandwidth utilization, dynamically adjust the network bandwidth allocation ratio, allocate the network bandwidth to the transmission path of the delayed frame, and ensure the transmission of the delayed frame; The delayed frame is transmitted and the retransmission time is recorded.

7. The electric control box remote data acquisition system based on the Internet of Things according to claim 6 is characterized in that: When a delay occurs during transmission, the transmission time is reduced by dynamically adjusting the priority of the retransmission queue and the allocation of network bandwidth. This also includes: When the retransmission transmission time is not significantly reduced, analyzing characteristic parameters of the backup transmission path, the characteristic parameters including packet loss rate, delay time and transmission stability; According to the characteristic parameters, the characteristic score of the backup transmission path is calculated. The calculation formula of the characteristic score is: Among them, S p Score the characteristics of path p, where p is the index of the path, D p is the delay time of path p, L p is the packet loss rate of path p, I p is the transmission stability of path p, D max is the preset delay threshold, W d ,W l ,W i are the coefficients of delay time, packet loss rate and transmission stability respectively, and k is a constant; Switch the delayed frame to the backup transmission path with the highest characteristic score for transmission; The operation results of each delay adjustment are recorded, and priority adjustment and network bandwidth allocation ratio are dynamically optimized based on them to improve the efficiency of subsequent transmission processes.

8. The electric control box remote data acquisition system based on the Internet of Things according to claim 7 is characterized in that: When signal attenuation occurs during transmission, the interference to signal strength can be reduced by switching transmission channels and adjusting transmission power, including: By collecting the interference level of the current channel, when the interference level is higher than the preset interference threshold, the channel switching mechanism is triggered; Retrieve all available channels and obtain attribute parameters of each channel, including signal strength, interference level, network load and bandwidth utilization; The attribute score of the channel is calculated based on the performance parameters. The calculation formula of the attribute score is: Among them, Q c is the attribute score of channel c, c is the index of the channel, H c is the signal strength of channel c, V c is the interference level of channel c, N c is the network load of channel c, B c is the bandwidth utilization of channel c, M c is the maximum bandwidth of channel c, W h ,W v ,W b are the coefficients of signal strength, interference level and bandwidth utilization, α and β are adjustment coefficients, and ∈ is a constant; The channel with the highest attribute score is marked as the target channel, and the current channel is switched to the target channel.

9. The electric control box remote data acquisition system based on the Internet of Things according to claim 8 is characterized in that: When signal attenuation occurs during transmission, the interference to signal strength is reduced by switching transmission channels and adjusting transmission power. This also includes: Compensate for signal strength by adjusting the transmission power, gradually increasing the transmission power until the signal strength returns to normal levels; When adjusting the transmission power has no effect, the transmission rate is reduced to ensure the stability of the transmission process; The effects of switching channels and adjusting transmission power are recorded, and the performance score calculation formula is adjusted accordingly.

10. The electric control box remote data acquisition system based on the Internet of Things according to claim 9 is characterized in that: Adjust the execution order of the solutions and optimize the transmission process based on the operation records and results of the solutions, including: Set the exception handling priority for the type of abnormal change, in descending order, namely packet loss abnormality, delay abnormality, and signal attenuation abnormality; When multiple exceptions occur at the same time, the order in which the solutions are executed is determined based on the exception handling priority: Prioritize packet loss exceptions and restore data integrity by generating retransmission signals and adjusting transmission queues; Secondly, deal with latency anomalies and reduce latency by adjusting queue priority and bandwidth allocation; Finally, the signal attenuation anomaly is processed and the signal strength is improved through channel switching and power adjustment; Record the performance of each solution.

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