Treatment Device and Method for Sediment Concentration Parameters in the Construction of Anti-Pollution Curtain Layout

Abstract

A processing device and method for sediment concentration parameters in the construction of anti-pollution curtains, belonging to the technical field of sediment concentration parameter processing. It detects the transmission volume at each process at regular intervals, analyzes whether the reliability during parameter transmission meets the standard according to the transmission volume. When the transmission volume is not low, it reconfirms whether the parameter transmission meets the standard according to the number of sediment concentration parameters collected by the parameter collection unit or analyzes the reason for non-compliance according to the time-series change range of the transmission volume of the process. When the time-series change range of the transmission volume is not low, it takes into account the parameters that cause the high transmission volume due to non-compliance of parameter sorting. When the time-series change range of the transmission volume is not large, it takes into account the unstable transmission of wireless network information on-site during parameter transmission and the rapid channel change, which causes the high transmission volume of parameters at the process, improving the control accuracy during parameter transmission.

Description

Technical Field

[0001] The present invention belongs to the technical field of sediment concentration parameter processing, and particularly relates to a processing device and method for sediment concentration parameters for the construction of anti-pollution curtains. Background Art

[0002] An anti-pollution curtain, also known as a floating silt curtain, is a flexible sediment control barrier designed to prevent the spread of silt and sediment in lakes and other water bodies when working in or near water or on the shoreline. The silt curtain is made of permeable or impermeable materials, vertically suspended in water, with a floating material enclosed in the top pocket and a ballast chain enclosed in the lower pocket.

[0003] In practical applications, the current construction of anti-pollution curtains often uses the prior art solution mentioned in the patent publication number "CN119121878A", which often includes a statistical module to obtain the sediment concentration parameters of the construction area of the anti-pollution curtain, and a position movement module to obtain the movement position information of the floating body and the pituitary for the construction of the anti-pollution curtain based on the sediment concentration parameters of the construction area of the anti-pollution curtain.

[0004] The position analysis platform includes a position movement module and a statistical module. The sediment concentration parameters of the construction area of the anti-pollution curtain on which the position movement module is based are often obtained by installing sediment concentration collection devices in each construction area of the anti-pollution curtain. The sediment concentration collection device includes a controller connected to a sediment concentration sensor and a wireless communication module. The controller is communicatively connected to the position analysis platform located within the wireless network via the wireless communication module. Thus, the sediment concentration sensor transmits the sediment concentration parameters of the construction area of the anti-pollution curtain it collects to the controller, and the controller transmits the collected sediment concentration parameters of the construction area of the anti-pollution curtain to the statistical module of the position analysis platform, so that the statistical module obtains the sediment concentration parameters of the construction area of the anti-pollution curtain.

[0005] It can be seen from this that the controller needs to transmit the collected sediment concentration parameters of the construction area of the anti-pollution curtain to the statistical module of the position analysis platform, so that the statistical module can obtain the sediment concentration parameters of the construction area of the anti-pollution curtain. Currently, in order to ensure the reliability of the parameters, on the position analysis platform, by setting restrictions on whether to allow reading for the logged-in accounts, it is ensured that accounts not allowed to read and write cannot use the sediment concentration parameters, so as to ensure the reliable reading of the sediment concentration parameters. However, the control accuracy during the transmission process of the sediment concentration parameters is insufficient, and the analysis accuracy is insufficient. It is not easy to analyze whether malicious software attacks the sediment concentration parameters during the transmission of the sediment concentration parameters.

[0006] That is to say, the control accuracy during the transmission of the sediment concentration parameters of the current construction area of the anti-pollution curtain is insufficient, and there is a hidden danger of sediment concentration parameter leakage. Summary of the Invention

[0007] To solve the defects existing in the prior art, the present invention proposes a processing device and method for sediment concentration parameters in the construction of anti-pollution curtains. The present invention effectively avoids the defects of insufficient control accuracy during the transmission of sediment concentration parameters in the construction area of anti-pollution curtains in the prior art and the potential risk of sediment concentration parameter leakage.

[0008] The present invention adopts the following technical solutions.

[0009] A processing method for sediment concentration parameters in the construction of anti-pollution curtains, comprising:

[0010] The sediment concentration sensor transmits the sediment concentration parameters of the construction area of the anti-pollution curtain collected by it to the controller, and the controller transmits the sediment concentration parameters of the construction area of the anti-pollution curtain collected and transmitted to the statistical module of the position analysis platform;

[0011] After the controller transmits the sediment concentration parameters of the construction area of the anti-pollution curtain collected and transmitted to the position analysis platform, it further includes:

[0012] Step1: Receive the sediment concentration parameters transmitted by the controller of each sediment concentration collection device;

[0013] Step2: Use a Wiener filter to filter and organize the noise values in the sediment concentration parameters, and then attach marks to the filtered and organized sediment concentration parameters and send them to the statistical module of the position analysis platform;

[0014] Step3: Identify the marks attached to the filtered and organized sediment concentration parameters;

[0015] Step4: Use a CNN neural network to construct an action model of the parameters and the convergence conditions for constructing the action model according to the learning set in the adaptive information table, and then analyze whether the reliability during parameter transmission meets the standard and update the adaptive information table.

[0016] Further, the method for analyzing whether the reliability during parameter transmission meets the standard and updating the adaptive information table specifically includes:

[0017] Step4-1: Detect the amount of information of the sediment concentration parameters transmitted at each process, and the amount of information of the transmitted sediment concentration parameters is the transmission amount;

[0018] Step4-2: Analyze whether the reliability during parameter transmission meets the standard according to the average value of the transmission amounts of each process in multiple predefined timing detection periods. When it is initially confirmed that the reliability during parameter transmission does not meet the standard, reconfirm whether the parameter transmission meets the standard according to the number of received sediment concentration parameters, or analyze the reason for the non-compliance of the reliability during parameter transmission according to the temporal variation range of the transmission amounts of the processes, and record the type of each process;

[0019] Step4-3: Refresh the adaptive information table according to the arrangement of each event.

[0020] Further, in Step4-2, the method for analyzing whether the reliability during parameter transfer is up to standard includes:

[0021] If the average value of the transmission volume is not higher than the first pre-defined average value of the transmission volume, then the analysis unit confirms that the reliability during parameter transfer is up to standard, and registers the currently analyzed process as a first-level process;

[0022] If the average value of the transmission volume is higher than the first pre-defined average value of the transmission volume and not higher than the second pre-defined average value of the transmission volume, then the analysis unit confirms that it is necessary to re-confirm whether the parameter transfer is up to standard based on the number of sediment concentration parameters collected by the parameter collection unit;

[0023] If the average value of the transmission volume is higher than the second pre-defined average value of the transmission volume, then the analysis unit confirms that the reliability during parameter transfer is not up to standard, and analyzes the reason for its non-compliance based on the temporal variation range of the transmission volume of the process.

[0024] Further, in Step4-2, the average value of the transmission volume corresponding to the regular detection period under the same conditions without malware attack is regarded as the average value benchmark of the transmission volume according to the parameters transmitted in the past. Here, the first pre-defined average value of the transmission volume is , and the second pre-defined average value of the transmission volume is .

[0025] Further, in Step4-2, the method for re-confirming whether the parameter transfer is up to standard includes:

[0026] Determine the number of sediment concentration parameters collected by the parameter collection unit during the pre-defined regular detection period;

[0027] If the number of sediment concentration parameters is not higher than the pre-defined number, then the analysis unit confirms that the reliability during parameter transfer is not up to standard, and analyzes the reason for its non-compliance based on the temporal variation range of the transmission volume of the process;

[0028] If the number of sediment concentration parameters is higher than the pre-defined number, then the analysis unit confirms that the reliability during parameter transfer is up to standard, and registers the currently analyzed process as a second-level process.

[0029] Further, in Step4-2, the pre-defined number is determined according to the past parameters, that is, the number of sediment concentration parameters collected by the parameter collection unit during the pre-defined period under the condition of no malware attack is used as the number standard, and the pre-defined number is 。

[0030] Further, in Step4-2, the method for analyzing the reason why the reliability during parameter transfer fails according to the temporal variation range of the transfer volume of the process includes:

[0031] Used to determine the transfer volume of the currently analyzed process in each period of the timing detection period, calculate the standard deviation of the transfer volume in each period of the timing detection period. If the standard deviation is not higher than the predefined standard deviation, then the analysis unit confirms that the reason for the failure of the reliability during parameter transfer is that the parameter sorting process fails, and registers the message that the reason for the failure of the reliability during parameter transfer is that the parameter sorting process fails as a first-level message;

[0032] If the standard deviation is higher than the predefined standard deviation, then the analysis unit confirms that the reason for the failure of the reliability during parameter transfer is that the channel changes too fast during parameter transfer, and registers the currently analyzed process as a third-level process.

[0033] Further, in Step4-2, the predefined standard deviation is obtained through predefined means, that is, obtain the sediment concentration parameters transmitted under the condition of no malware attack, determine the transfer volume in each period, obtain the standard deviation of the transfer volume in each period, and the predefined standard deviation is the 。

[0034] A processing device for sediment concentration parameters for the construction of an anti-pollution curtain includes:

[0035] A location analysis platform containing a statistical module and sediment concentration acquisition devices provided in the construction area of each anti-pollution curtain. The statistical module is used to obtain the sediment concentration parameters of the construction area of the anti-pollution curtain. The sediment concentration acquisition device includes a controller connected to a sediment concentration sensor and a wireless communication module. The controller communicates with the location analysis platform located in the wireless network through the wireless communication module. The sediment concentration sensor is used to transmit the sediment concentration parameters of the construction area of the anti-pollution curtain it collects to the controller, and the controller is used to transmit the collected sediment concentration parameters of the construction area of the anti-pollution curtain to the statistical module of the location analysis platform;

[0036] The units running on the location analysis platform include:

[0037] A parameter collection unit, which contains multiple processes and is used to collect the sediment concentration parameters transmitted by the controllers of each sediment concentration acquisition device;

[0038] A parameter sorting unit, which is communicatively connected to the parameter collection unit and is used to filter and sort the noise values in the sediment concentration parameters using a Wiener filter, and then attach a mark to the filtered and sorted sediment concentration parameters and send them to the statistical module of the location analysis platform;

[0039] A mark recognition unit, which is communicatively connected to the parameter sorting unit and is used to recognize the marks attached in the sediment concentration parameter after filtering and sorting;

[0040] An adaptive information table, which is used to store multiple learning set action construction units. The learning set action construction units are communicatively connected to the adaptive information table and are used to use a CNN neural network to construct an action model and the convergence condition of the constructed action model according to the learning set construction parameters in the adaptive information table, and then analyze whether the reliability during parameter transmission meets the standard and update the adaptive information table.

[0041] Further, the units operating on the location analysis platform further include: a transmission volume detection unit, which is communicatively connected to the mark recognition unit and is used to detect the amount of information of the sediment concentration parameter transmitted at each process. The amount of information of the transmitted sediment concentration parameter is the transmission volume;

[0042] An analysis unit, which is communicatively connected to the parameter collection unit, the parameter sorting unit, the mark recognition unit, the adaptive information table, the action construction unit and the transmission volume detection unit respectively, and is used to analyze whether the reliability during parameter transmission meets the standard according to the average value of the transmission volume of each process in multiple predefined timing detection periods. When it is initially confirmed that the reliability during parameter transmission does not meet the standard, reconfirm whether the parameter transmission meets the standard according to the number of sediment concentration parameters collected by the parameter collection unit, or analyze the reason why the reliability during parameter transmission does not meet the standard according to the temporal variation range of the transmission volume of the process, and register the type of each process;

[0043] A message construction unit, which is communicatively connected to the adaptive information table and the analysis unit respectively, and is used to update the adaptive information table according to the arrangement of each event.

[0044] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0045] By periodically detecting the transmission volume at each process, analyzing whether the reliability during parameter transmission meets the standard according to the transmission volume, when the transmission volume is not low, reconfirming whether the parameter transmission meets the standard according to the number of sediment concentration parameters collected by the parameter collection unit or analyzing the reason why it does not meet the standard according to the temporal variation range of the transmission volume of the process. When the temporal variation range of the transmission volume is not low, considering the parameters that cause the high transmission volume due to unqualified parameter sorting, and when the temporal variation range of the transmission volume is not large, considering the unstable wireless network information transmission on-site during parameter transmission and the too fast channel change, which leads to the high transmission volume of the parameters at the process, improving the control accuracy during parameter transmission. Description of the Drawings

[0046] Figure 1It is a partial flowchart of the method for processing the sediment concentration parameter for the construction of the anti-pollution curtain in the present invention;

[0047] Figure 2 It is a partial structural diagram of the device for processing the sediment concentration parameter for the construction of the anti-pollution curtain in the present invention. Detailed implementation manners

[0048] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. The embodiments described herein are only part of the embodiments of the present invention, rather than all of the embodiments. According to the spirit of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0049] As Figure 1 shown, a method for processing the sediment concentration parameter for the construction of the anti-pollution curtain according to the present invention includes:

[0050] The sediment concentration sensor transmits the sediment concentration parameter of the construction area of the anti-pollution curtain it collects to the controller, and the controller transmits the sediment concentration parameter of the construction area of the anti-pollution curtain collected and transmitted to the statistical module of the position analysis platform, so that the statistical module obtains the sediment concentration parameter of the construction area of the anti-pollution curtain;

[0051] After the controller transmits the sediment concentration parameter of the construction area of the anti-pollution curtain collected and transmitted to the position analysis platform, it further includes:

[0052] Step1: Receive the sediment concentration parameters transmitted by the controllers of each sediment concentration collection device;

[0053] Step2: Use a Wiener filter to filter and process the noise values in the sediment concentration parameters, and then attach marks to the filtered and processed sediment concentration parameters and send them to the statistical module of the position analysis platform, so that the statistical module obtains the sediment concentration parameter of the construction area of the anti-pollution curtain;

[0054] Step3: Identify the marks attached to the filtered and processed sediment concentration parameters;

[0055] Step4: Use a CNN neural network to construct an action model of the parameters and the convergence condition (minimization of the cross-entropy loss function) for constructing the action model according to the learning set in the adaptive information table, and then analyze whether the reliability during the parameter transmission is up to standard and update the adaptive information table.

[0056] In the preferred but non-limiting implementation manner of the present invention, the method for analyzing whether the reliability during the parameter transmission is up to standard and updating the adaptive information table specifically includes:

[0057] Step4-1: Detect the information volume of the sediment concentration parameter transmitted from each process. The information volume of the transmitted sediment concentration parameter is the transmission volume.

[0058] Step4-2: Analyze whether the reliability during parameter transmission meets the standard based on the average value of the transmission volumes of each process in multiple predefined timing detection periods. When it is initially confirmed that the reliability during parameter transmission does not meet the standard, reconfirm whether it meets the standard based on the number of sediment concentration parameters collected by the parameter collection unit. Or, analyze the reason why the reliability during parameter transmission does not meet the standard based on the temporal variation range of the transmission volume of the process, and record the type of each process (different processes are different types).

[0059] Step4-3: Refresh the adaptive information table according to the arrangement of each type of event.

[0060] Therefore, by periodically detecting the transmission volume at each process, analyzing whether the reliability during parameter transmission meets the standard based on the transmission volume, when the transmission volume is not low, reconfirm whether it meets the standard based on the number of sediment concentration parameters collected by the parameter collection unit or analyze the reason why it does not meet the standard based on the temporal variation range of the transmission volume of the process. When the temporal variation range of the transmission volume is not low, consider the parameters that cause the high transmission volume due to unqualified parameter sorting. When the temporal variation range of the transmission volume is not large, consider the unstable wireless network information transmission at the site during parameter transmission and the too-fast channel change, which causes the high transmission volume of the parameters at the process, improving the control accuracy during parameter transmission.

[0061] In a preferred but non-limiting embodiment of the present invention, in Step4-2, the method for analyzing whether the reliability during parameter transmission meets the standard includes:

[0062] The analysis unit is used to analyze whether the reliability during parameter transmission meets the standard based on the average value of the transmission volumes of each process in the predefined timing detection period, and it includes:

[0063] If the average value of the transmission volume is not higher than the first predefined average value of the transmission volume, then the analysis unit confirms that the reliability during parameter transmission meets the standard, and registers the currently analyzed process as a first-level process;

[0064] If the average value of the transmission volume is higher than the first predefined average value of the transmission volume and not higher than the second predefined average value of the transmission volume, then the analysis unit confirms that reconfirmation is performed on whether it meets the standard based on the number of sediment concentration parameters collected by the parameter collection unit;

[0065] If the average of the transmission volume is higher than the average of the pre-defined transmission volume two, then the analysis unit confirms that the reliability during parameter transmission does not meet the standard, and analyzes the reason for non-compliance based on the temporal variation range of the transmission volume of the process.

[0066] In a preferred but non-limiting embodiment of the present invention, in Step4-2, the average of the transmission volume during the corresponding period of the timing detection period under the same conditions without malware attack is regarded as the benchmark of the transmission volume according to the parameters transmitted in the past. Here, the pre-defined average of the transmission volume one is of the benchmark of the transmission volume, and the pre-defined average of the transmission volume two is .

[0067] In a preferred but non-limiting embodiment of the present invention, in Step4-2, the method for reconfirming whether it meets the standard during parameter transmission includes:

[0068] Determine the number of sediment concentration parameters collected by the parameter collection unit during the pre-defined timing detection period;

[0069] If the number of sediment concentration parameters is not higher than the pre-defined number, then the analysis unit confirms that the reliability during parameter transmission does not meet the standard, and analyzes the reason for non-compliance based on the temporal variation range of the transmission volume of the process;

[0070] If the number of sediment concentration parameters is higher than the pre-defined number, then the analysis unit confirms that the reliability during parameter transmission meets the standard, and registers the currently analyzed process as a second-level process.

[0071] In a preferred but non-limiting embodiment of the present invention, in Step4-2, the pre-defined number is determined according to the past parameters, that is, the number of sediment concentration parameters collected by the parameter collection unit during the pre-defined period under the condition of no malware attack is used as the number standard. The pre-defined number is .

[0072] Here, considering that the number of sediment concentration parameters will determine the size of the parameter transmission bandwidth, the higher the number of sediment concentration parameters, when the number of sediment concentration parameters in the wireless network is too high, it often causes wireless network congestion, thereby increasing the latency and loss rate of sediment concentration parameters. An excessive number of sediment concentration parameters indicates a greater amount of contention for the wireless network channel, often causing the sediment concentration parameters to queue up for transmission, increasing the transmission time. This application determines the reliability during parameter transmission based on the number of sediment concentration parameters. When the number of sediment concentration parameters is not small, it is confirmed that the reason for the high transmission volume of parameter transmission is because the number of sediment concentration parameters is too high, rather than because of parameter leakage during parameter transmission, improving the control accuracy during parameter transmission.

[0073] In a preferred but non-limiting embodiment of the present invention, in Step4-2, a method for analyzing the reason for the unqualified reliability during the parameter transfer according to the temporal variation amplitude of the transfer volume of the process includes:

[0074] Used to determine the transfer volume of each period of the currently analyzed process during the timing detection period, calculate the standard deviation of the transfer volume of each period during the timing detection period. If the standard deviation is not higher than the pre-defined standard deviation, then the analysis unit confirms that the reason for the unqualified reliability during the parameter transfer is that the parameter sorting process is unqualified, and registers the message that the reason for the unqualified reliability during the parameter transfer is that the parameter sorting process is unqualified as the first-level message;

[0075] If the standard deviation is higher than the pre-defined standard deviation, then the analysis unit confirms that the reason for the unqualified reliability during the parameter transfer is that the channel changes too fast during the parameter transfer, and registers the currently analyzed process as the third-level process.

[0076] In a preferred but non-limiting embodiment of the present invention, in Step4-2, the pre-defined standard deviation is obtained by pre-definition, that is, obtaining the sediment concentration parameters transmitted under the condition of no malware attack, determining the transfer volume of each period, obtaining the standard deviation of the transfer volume of each period, and the pre-defined standard deviation is the .

[0077] Accordingly, first determine the transfer volume of the process in each period, calculate the standard deviation of the transfer volume value, considering that a sudden large transfer volume of a controller in the wireless network deviates from the normal range, which is often caused by the manipulation of the transfer volume caused by a malware attack and other situations. Therefore, determine the fluctuation of the transfer volume at each period according to the standard deviation, analyze the reliability during the parameter transfer according to the fluctuation of the transfer volume, analyze whether there is a situation of parameter malware attack, confirm the existence of a reliability risk when the standard deviation is not low, considering that due to the transfer period, the difference in the wireless network in different intervals is not low, and multiple changes in the wireless network cause large fluctuations in the transfer volume of each period, register the process according to the analysis information, and then analyze whether there is a reliability risk according to the ratio of the number of each type of process, so as to improve the control accuracy in the face of the parameter transfer period and improve the analysis accuracy in the face of the parameter transfer period.

[0078] In a preferred but non-limiting embodiment of the present invention, Step4-2 further includes: calibrating the sorting benchmark according to the ratio of abnormal parameters under the condition that the parameter sorting is unqualified, and specifically:

[0079] Register the parameters with a transfer volume higher than a pre-defined value as abnormal parameters, calculate the ratio of the abnormal parameters to the total number of parameters charged for each process to obtain the abnormal ratio, and organize that the reduction amount of the baseline is inversely proportional to the abnormal ratio; compare the abnormal ratio with a first pre-defined abnormal ratio and a second pre-defined abnormal ratio,

[0080] If the abnormal ratio is not higher than the first pre-defined abnormal ratio, then reduce the first organization baseline, where the first organization baseline is a starting organization baseline pre-defined according to specific requirements ; if the abnormal ratio is higher than the first pre-defined abnormal ratio and not higher than the second pre-defined abnormal ratio, then reduce the second organization baseline, where the second organization baseline is eight ten-thousandths of the starting organization baseline; if the abnormal ratio is higher than the second pre-defined abnormal ratio, then reduce the third organization baseline, where the third organization baseline is six ten-thousandths of the starting organization baseline.

[0081] During parameter organization, the standard deviation and the mean are used to identify parameter points far from the mean, and the organization baseline is the standard deviation and the mean.

[0082] In a preferred but non-limiting embodiment of the present invention, Step4-2 further includes: counting the registration status of each process, and determining the reason for the failure of the reliability during parameter transfer based on the ratio of each registered process, which is:

[0083] Count the number of processes of each type, calculate the ratio of the number of processes of each type divided by the total number of processes respectively to obtain the ratio of the number of processes of each type. If the ratio of the number of first-level processes is the highest, then the analysis unit confirms that the reason for the failure of the reliability during parameter transfer is parameter loss, and registers the message that the reason for the failure of the reliability during parameter transfer is parameter loss as a second-level message;

[0084] If the ratio of the number of second-level processes is the highest, then the analysis unit confirms and re-confirms the reason for the failure of the reliability during parameter transfer based on the ratio of each abnormal parameter;

[0085] If the ratio of the number of third-level processes is the highest, then the analysis unit confirms that the reason for the failure of the reliability during parameter transfer is the situation fluctuation of the wireless network caused by transmissions with too large an interval, and improves the fluctuation situation of the wireless network, and registers the message that the reason for the failure of the reliability during parameter transfer is the situation fluctuation of the wireless network caused by transmissions with too large an interval as a third-level message.

[0086] In a preferred but non-limiting embodiment of the present invention, Step4-2 further includes: calibrating the approximation baseline under the condition of parameter loss, which is:

[0087] Determine the completeness of the stored parameters, calibrate the approximation benchmark according to the completeness. Here, the increase amount of the approximation benchmark and the completeness are inversely proportional; compare the completeness with the first predefined completeness and the second predefined completeness. If the completeness is not higher than the first predefined completeness, then increase the first approximation benchmark, and the first approximation benchmark is the starting approximation benchmark predefined according to specific requirements; if the completeness is higher than the first predefined completeness and not higher than the second predefined completeness, then increase the second approximation benchmark, and the second approximation benchmark is the starting approximation benchmark; if the completeness is higher than the second predefined completeness, then increase the third approximation benchmark, and the third approximation benchmark is the .

[0088] Here, determine the benchmark of abnormal parameters based on past parameters, and determine whether a single parameter is an abnormal parameter according to the approximation benchmark between each parameter and the benchmark of the abnormal parameter.

[0089] In a preferred but non-limiting embodiment of the present invention, Step4-2 further includes: reconfirm the reason for the unqualified reliability during parameter transmission according to the ratio of each abnormal parameter, which is:

[0090] If the ratio of the transmission volume abnormal parameter is not lower than the predefined ratio, then the analysis unit confirms that the reason for the unqualified reliability during parameter transmission is that the parameter sorting process is unqualified, and registers the message that the reason for the unqualified reliability during parameter transmission is that the parameter sorting process is unqualified as the first-level message; if the ratio of the behavior abnormal parameter is not lower than the predefined ratio, then the analysis unit confirms that the reason for the unqualified reliability during parameter transmission is parameter loss, and registers the message that the reason for the unqualified reliability during parameter transmission is parameter loss as the second-level message.

[0091] The predefined ratio is selected within the range between.

[0092] Analyze the reliability during parameter transmission according to the ratio of each abnormal parameter. When the ratio of the parameter with abnormal transmission volume is not low, considering that the parameter sorting benchmark is not high and the parameter sorting is improperly handled, when the ratio of the abnormal parameter is not low, confirm that there is parameter loss, and register each message according to the analysis information, which is conducive to targeted improvement later.

[0093] The message structure unit is used to count the number of each type of message, and refresh the adaptive information table according to the arrangement of each type of message, that is, add the newly generated message to the information table.

[0094] Such as Figure 2As shown, a processing device for sediment concentration parameters for the construction of anti-pollution curtains according to the present invention includes:

[0095] A position analysis platform containing a position movement module and a statistics module (the position analysis platform can be a computer within a 4G network) and sediment concentration acquisition devices provided in the construction area of each anti-pollution curtain. The statistics module is used to obtain the sediment concentration parameters of the construction area of the anti-pollution curtain, and the position movement module is used to obtain the movement position information of the floating body and the pituitary for the construction of the anti-pollution curtain based on the sediment concentration parameters of the construction area of the anti-pollution curtain; the sediment concentration acquisition device includes a controller (the controller can be a single-chip microcomputer, a PLC, or an industrial control computer) connected to a sediment concentration sensor and a wireless communication module (the wireless communication module can be a 4G module). The controller is communicatively connected to the position analysis platform located within the wireless network via the wireless communication module. The sediment concentration sensor is used to transmit the sediment concentration parameters of the construction area of the anti-pollution curtain it collects to the controller, and the controller is used to transmit the sediment concentration parameters of the construction area of the anti-pollution curtain collected and transmitted to the statistics module of the position analysis platform, so that the statistics module obtains the sediment concentration parameters of the construction area of the anti-pollution curtain;

[0096] The units running on the position analysis platform include:

[0097] A parameter collection unit, which contains multiple processes and is used to collect the sediment concentration parameters transmitted by the controllers of each sediment concentration acquisition device;

[0098] A parameter sorting unit, which is communicatively connected to the parameter collection unit and is used to filter and sort the noise values in the sediment concentration parameters using a Wiener filter, and then attach a mark to the filtered and sorted sediment concentration parameters and send them to the statistics module of the position analysis platform, so that the statistics module obtains the sediment concentration parameters of the construction area of the anti-pollution curtain; this mark is a unique code configured for the sediment concentration parameters.

[0099] A mark identification unit, which is communicatively connected to the parameter sorting unit and is used to identify the marks attached to the filtered and sorted sediment concentration parameters;

[0100] An adaptive information table, which is used to store multiple learning sets (the learning sets are the filtered and sorted sediment concentration parameters); the adaptive information table is an information table for storing multiple learning sets.

[0101] An action structure unit, which is communicatively connected to the adaptive information table and is used to construct an action model of the parameters and the convergence conditions for constructing the action model (the convergence conditions can be the minimization of the cross-entropy loss function) using a CNN neural network based on the learning sets in the adaptive information table, and then analyze whether the reliability during parameter transmission meets the standard and update the adaptive information table.

[0102] In a preferred but non-limiting embodiment of the present invention, the units operating on the location analysis platform further include: a throughput detection unit, which is communicatively connected to the symbol recognition unit and is used to detect the amount of information of the sediment concentration parameter transmitted at each process, and the amount of information of the sediment concentration parameter transmitted is the throughput;

[0103] An analysis unit, which is communicatively connected to the parameter collection unit, the parameter arrangement unit, the symbol recognition unit, the adaptive information table, the action construction unit and the throughput detection unit respectively, and is used to analyze whether the reliability during parameter transmission meets the standard according to the average throughput of each process in a plurality of predefined timing detection periods. When it is initially confirmed that the reliability during parameter transmission does not meet the standard, it reconfirms whether the parameter transmission meets the standard according to the number of sediment concentration parameters collected. Or, it analyzes the reason why the reliability during parameter transmission does not meet the standard according to the temporal variation range of the throughput of the process, and registers the type of each process (the type of the process can be divided according to different classification methods. For example, the process of the construction area of the nearest plurality of antifouling curtains where the sediment concentration parameter is collected is divided into one type);

[0104] A message construction unit, which is communicatively connected to the adaptive information table and the analysis unit respectively, and is used to refresh the adaptive information table according to the arrangement of each event.

[0105] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that: still can modify the specific implementation manners of the present invention or make equivalent replacements, and any modification or equivalent replacement without departing from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A method for processing sediment concentration parameters for the construction of anti-pollution curtains, characterized in that, Including: The sediment concentration sensor transmits the sediment concentration parameters of the construction area of the anti-pollution curtain it collects to the controller, and the controller transmits the sediment concentration parameters of the construction area of the anti-pollution curtain collected and transmitted to the statistical module of the location analysis platform; After the controller transmits the sediment concentration parameters of the construction area of the anti-pollution curtain collected and transmitted to the location analysis platform, it also includes: Step1: Receive the sediment concentration parameters transmitted by the controller of each sediment concentration collection device; Step2: Use a Wiener filter to filter and organize the noise values in the sediment concentration parameters, and then send the sediment concentration parameters after filtering and organizing with marks attached to the statistical module of the location analysis platform; Step3: Identify the marks attached to the sediment concentration parameters after filtering and organizing; Step4: Use a CNN neural network to construct an action model of the parameters and the convergence conditions for constructing the action model according to the learning set in the adaptive information table, and then analyze whether the reliability during parameter transmission meets the standard and update the adaptive information table; Subsequently, the method for analyzing whether the reliability during parameter transmission meets the standard and updating the adaptive information table specifically includes: Step4-1: Detect the amount of information of the sediment concentration parameters transmitted at each process, and the amount of information of the transmitted sediment concentration parameters is the transmission amount; Step4-2: Analyze whether the reliability during parameter transmission meets the standard according to the average of the transmission amounts at each process in multiple predefined timing detection periods. When it is initially confirmed that the reliability during parameter transmission does not meet the standard, reconfirm whether it meets the standard according to the number of sediment concentration parameters received, or analyze the reason for the non-compliance of the reliability during parameter transmission according to the temporal variation range of the transmission amount of the process, and record the type of each process; Step4-3: Update the adaptive information table according to the arrangement of each event.

2. The method for processing sediment concentration parameters for the construction of anti-pollution curtains according to claim 1, characterized in that In Step4-2, the method for analyzing whether the reliability during parameter transmission meets the standard includes: If the average of the transmission amounts is not higher than the first predefined average of the transmission amounts, then the analysis unit confirms that the reliability during parameter transmission meets the standard, and records the currently analyzed process as a first-level process; If the average of the transmission amounts is higher than the first predefined average of the transmission amounts and not higher than the second predefined average of the transmission amounts, then the analysis unit confirms that it is necessary to reconfirm whether the parameter transmission period meets the standard according to the number of sediment concentration parameters received by the parameter receiving unit; If the average of the transmission amounts is higher than the second predefined average of the transmission amounts, then the analysis unit confirms that the reliability during parameter transmission does not meet the standard, and analyzes the reason for its non-compliance according to the temporal variation range of the transmission amount of the process.

3. The processing method for sediment concentration parameters for the construction of anti-pollution curtains according to claim 2, characterized in that, In Step4-2, the average of the transmission amounts in the corresponding period of the timing detection period under the same conditions without malware attack is regarded as the benchmark of the average of the transmission amounts according to the previously transmitted parameters. Here, the first predefined average of the transmission amounts is 85% - 95% of the benchmark of the average of the transmission amounts, and the second predefined average of the transmission amounts is 105% - 115% of the benchmark of the average of the transmission amounts.

4. The method for processing the sediment concentration parameter for the construction of the anti-pollution curtain according to claim 3, characterized in that, In Step4-2, the method for reconfirming whether the parameter transmission period meets the standard includes: The number of sediment concentration parameters collected by the recognition parameter collection unit during a predefined timing detection period; If the number of sediment concentration parameters is not higher than the predefined number, then the parsing unit confirms that the reliability during parameter transfer is not up to standard, and analyzes the reason for the non-compliance based on the temporal variation range of the transmission volume of the process; If the number of sediment concentration parameters is higher than the predefined number, then the parsing unit confirms that the reliability during parameter transfer is up to standard, and registers the currently parsed process as a second-level process.

5. The processing method for sediment concentration parameters for the construction of anti-pollution curtains according to claim 4, characterized in that, In Step4-2, the predefined number is determined based on previous parameters, that is, the number of sediment concentration parameters collected by the parameter collection unit during a predefined period under the condition of no malware attack is used as the number standard, and the predefined number is 85% - 120% of this number standard.

6. The processing method of the sediment concentration parameter for the construction of the anti-pollution curtain according to claim 5, characterized in that, In Step4-2, the method for analyzing the reason for the non-compliance of the reliability during parameter transfer based on the temporal variation range of the transmission volume of the process includes: Used to determine the transmission volume of each period of the currently parsed process during the timing detection period, calculate the standard deviation of the transmission volume of each period during the timing detection period. If the standard deviation is not higher than the predefined standard deviation, then the parsing unit confirms that the reason for the non-compliance of the reliability during parameter transfer is that the parameter sorting process is not up to standard, and registers the message that the reason for the non-compliance of the reliability during this parameter transfer period is that the parameter sorting process is not up to standard as a first-level message; If the standard deviation is higher than the predefined standard deviation, then the parsing unit confirms that the reason for the non-compliance of the reliability during parameter transfer is that the channel changes too quickly during parameter transfer, and registers the currently parsed process as a third-level process.

7. The processing method for sediment concentration parameters for the construction of anti-pollution curtains according to claim 6, characterized in that, In Step4-2, the predefined standard deviation is obtained through predefined means, that is, obtaining multiple sediment concentration parameters transmitted under the condition of no malware attack, determining the transmission volume of each period, obtaining the standard deviation of the transmission volume of each period, and the predefined standard deviation is 95% - 115% of the standard deviation of this transmission volume.

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