Sand content parameter processing device and method for antifouling cord fabric facility construction

Abstract

The invention relates to a sand content parameter processing device and method for an antifouling curtain fabric facility worker, and belongs to the technical field of sand content parameter processing. According to the sand content parameter processing method, the transmission amount of each process is detected regularly, and whether the reliability in the parameter transmission period reaches the standard or not is analyzed according to the transmission amount; when the transmission amount is not low, whether the parameter transmission period reaches the standard or not is confirmed again according to the number of the sand content parameters collected by the parameter collection unit, or the reason that the parameter transmission period does not reach the standard is analyzed according to the time sequence variation amplitude of the transmission amount of the process; when the time sequence variation amplitude of the transmission quantity is not low, parameters which are not low in transmission quantity due to the fact that parameter arrangement does not reach the standard are considered, and when the time sequence variation amplitude of the transmission quantity is not large, unstable wireless network information transmission and too fast channel conversion in the field during parameter transmission are considered, so that the transmission quantity of the parameters at the process is not low, and the transmission quantity of the parameters at the process is not low. And the management and control accuracy during the parameter transmission period is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of sand content parameter processing, and in particular relates to a device and method for processing sand content parameters for anti-fouling curtain fabric installation. Background Art

[0002] Anti-fouling curtains, which may also be called floating silt curtains, are flexible sediment control barriers designed to prevent the spread of silt and sediment in lakes and other water bodies when work is being done in the water or on or near a shoreline. Silt curtains are made of permeable or impermeable material and are suspended vertically in the water with floating material enclosed in the top pockets and ballast chains enclosed in the lower pockets.

[0003] In practical applications, the current installation of anti-fouling curtains often uses the existing technical solution mentioned in the patent publication number "CN119121878A", which often includes a statistical module to obtain the sand content parameters of the installation area of ​​the anti-fouling curtain, and a position movement module to obtain the movement position information of the float and the vertical body used for the installation of the anti-fouling curtain based on the sand content parameters of the installation area of ​​the anti-fouling curtain.

[0004] The position analysis platform includes a position movement module and a statistical module. The sand content parameters of the anti-fouling curtain installation area based on the position movement module are often obtained through a sand content collection device provided in each anti-fouling curtain installation area. The sand content collection device includes a controller connected to a sand content sensor and a wireless communication module. The controller is connected to the position analysis platform in the wireless network via the wireless communication module. The sand content sensor transmits the collected sand content parameters of the anti-fouling curtain installation area to the controller. The controller transmits the collected sand content parameters of the anti-fouling curtain installation area to the statistical module of the position analysis platform. In this way, the statistical module obtains the sand content parameters of the anti-fouling curtain installation area.

[0005] It can be seen from this that the controller must transmit the collected sand content parameters of the construction area where the anti-fouling curtain is installed to the statistical module of the location analysis platform, so that the statistical module can obtain the sand content parameters of the construction area where the anti-fouling curtain is installed. At present, in order to ensure the reliability of the parameters, the location analysis platform sets restrictions on whether the login account is allowed to read or not, to ensure that accounts that are not allowed to read and write cannot use the sand content parameters, thereby ensuring the reliable reading of the sand content parameters. However, the control accuracy of the sand content parameter transmission process is not enough, and the analysis accuracy is not enough. It is not easy to analyze whether malware attacks the sand content parameters during the transmission of the sand content parameters.

[0006] In other words, the current anti-fouling curtain installation area does not have sufficient control accuracy during the transmission of sand content parameters, which poses a risk of sand content parameter leakage. Summary of the invention

[0007] In order to solve the defects in the prior art, the present invention proposes a device and method for processing sand content parameters in the installation of anti-fouling curtains. The present invention effectively avoids the defects of the prior art that the control accuracy during the transmission of sand content parameters in the installation area of ​​the anti-fouling curtains is insufficient and there is a hidden danger of leakage of sand content parameters.

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

[0009] A method for processing sand content parameters for anti-fouling curtain installation, comprising:

[0010] The sand content sensor transmits the collected sand content parameters of the anti-fouling curtain installation area to the controller, and the controller transmits the collected sand content parameters of the anti-fouling curtain installation area to the statistical module of the location analysis platform;

[0011] After the controller transmits the collected sand content parameters of the anti-fouling curtain installation area to the location analysis platform, it also includes:

[0012] Step 1: Collect the sand content parameters transmitted by the controller of each sand content collection device;

[0013] Step 2: Use the Wiener filter to filter out the noise value in the sediment content parameter, then add a mark to the filtered sediment content parameter and send it to the statistical module of the location analysis platform;

[0014] Step 3: Identify the symbols in the sand content parameters after filtration;

[0015] Step 4: Use the CNN neural network to construct the action model of the parameters and the convergence conditions of the constructed action model according to the learning set in the adaptive information table, and then analyze whether the reliability during the parameter transmission period meets the standards and update the adaptive information table.

[0016] Further, the method of subsequently analyzing whether the reliability during parameter transmission is up to standard and refreshing the adaptive information table specifically includes:

[0017] Step 4-1: Detect the amount of information of the sand content parameter transmitted from each process. The amount of information of the sand content parameter transmitted is the transmission amount;

[0018] Step 4-2: Analyze whether the reliability of the parameter transmission period meets the standard according to the average of the transmission volume of each process in multiple pre-defined timed detection periods. If the reliability of the parameter transmission period does not meet the standard during the initial confirmation, re-confirm whether the parameter transmission period meets the standard according to the number of collected sand content parameters, or analyze the reason why the reliability of the parameter transmission period does not meet the standard according to the time series variation of the transmission volume of the process, and register the type of each process;

[0019] Step 4-3: Refresh the adaptive information table according to the arrangement of each event.

[0020] Furthermore, in Step 4-2, the method for analyzing whether the reliability during parameter transfer is up to standard includes:

[0021] If the mean of the transmission amount is not higher than the predefined mean of the transmission amount, the parsing unit confirms that the reliability during the parameter transmission has reached the standard, and registers the currently parsed process as a first-level process;

[0022] If the average of the transmission amount is higher than the predefined average of the transmission amount one and not higher than the predefined average of the transmission amount two, then the analysis unit confirms whether the parameter transmission period meets the standard according to the number of sand content parameters collected by the parameter collection unit and reconfirms;

[0023] If the average of the transmission volume is higher than the predefined average of transmission volume two, the analyzing unit confirms that the reliability during the parameter transmission period does not meet the standard, and analyzes the reason for not meeting the standard according to the timing variation range of the transmission volume of the process.

[0024] Further, in Step 4-2, the average of the transmission volume in the corresponding period of the timing detection period under the same conditions without malware attack is determined based on the parameters of the previous transmission as the average transmission volume benchmark. The average transmission volume defined in advance is the average transmission volume benchmark. The predefined average of the transmission volume is the average of the transmission volume. .

[0025] Furthermore, in Step 4-2, the method of confirming again whether the parameter transfer is up to standard includes:

[0026] The number of sediment content parameters collected by the identification parameter collection unit during a predefined timed detection period;

[0027] If the number of sand content parameters is not higher than the predefined number, the analysis unit confirms that the reliability during parameter transmission is not up to standard, and analyzes the reason for not meeting the standard according to the time series variation range of the transmission amount of the process;

[0028] If the number of the sediment content parameters is higher than the predefined number, the parsing unit confirms that the reliability during the parameter transfer is up to standard and registers the current parsing process as a second-level process.

[0029] Further, in Step 4-2, the predefined number is based on the previous parameter identification, that is, the number of sand content parameters collected by the parameter collection unit in the predefined period under the condition of no malware attack is used as the number standard. The predefined number is the number standard. .

[0030] Furthermore, in Step 4-2, the method for analyzing the reason why the reliability during parameter transmission is not up to standard according to the timing variation range of the transmission amount of the process includes:

[0031] Used to determine the transmission volume of the currently parsed process in each period of the timing detection period, calculate the standard deviation of the transmission volume in each period of the timing detection period, and if the standard deviation is not higher than the pre-defined standard deviation, then the parsing unit confirms that the reason why the reliability during the parameter transmission period does not meet the standard is that the parameter arrangement process does not meet the standard, and registers the message that the reason why the reliability during the parameter transmission period does not meet the standard is that the parameter arrangement process does not meet the standard as a first-level message;

[0032] If the standard deviation is higher than the predefined standard deviation, the parsing unit determines that the reason why the reliability during parameter transfer does not meet the standard is that the channel changes too quickly during parameter transfer, and registers the currently parsed process as a third-level process.

[0033] Furthermore, in Step 4-2, the predefined standard deviation is obtained by pre-definition, that is, obtaining multiple sand content parameters transmitted under the condition of no malware attack, determining the transmission volume of each period, and obtaining the standard deviation of the transmission volume of each period. The pre-defined standard deviation is the standard deviation of the transmission volume. .

[0034] A device for processing sand content parameters for anti-fouling curtain installation, comprising:

[0035] A location analysis platform including a statistical module and a sand content collection device provided in each anti-fouling curtain installation area, wherein the statistical module is used to obtain the sand content parameters of the anti-fouling curtain installation area, and the sand content collection device includes a controller connected to a sand content sensor and a wireless communication module, wherein the controller is connected to the location analysis platform located in a wireless network via the wireless communication module, and the sand content sensor is used to transmit the sand content parameters of the anti-fouling curtain installation area collected by the sensor to the controller, and the controller is used to transmit the sand content parameters of the anti-fouling curtain installation area collected and transmitted to the statistical module of the location analysis platform;

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

[0037] A parameter collecting unit, which includes a plurality of processes and is used to collect the sediment content parameters transmitted by the controller of each sediment content collecting device;

[0038] The parameter sorting unit is connected to the parameter collecting unit for filtering the noise value in the sediment content parameter by using the Wiener filter, and then attaching a mark to the filtered sediment content parameter and sending it to the statistical module of the location analysis platform;

[0039] A mark recognition unit, which is connected to the parameter sorting unit for recognizing the mark attached to the sand content parameter after filtering and sorting;

[0040] The adaptive information table is used to store multiple learning set action construction units, which is communicated with the adaptive information table and is used to use the CNN neural network to construct the action model of the parameters according to the learning set in the adaptive information table and the convergence conditions of the constructed action model, and then analyze whether the reliability during the parameter transmission period meets the standards and refresh the adaptive information table.

[0041] Furthermore, the unit running on the position analysis platform also includes: a transmission amount detection unit, which is connected to the mark recognition unit for detecting the amount of information of the sand content parameter transmitted from each process, and the amount of information of the sand content parameter transmitted is the transmission amount;

[0042] The parsing unit is respectively connected to the parameter collecting unit, the parameter sorting unit, the mark recognition unit, the adaptive information table, the action construction unit and the transmission volume detection unit, and is used to parse whether the reliability of the parameter transmission period meets the standard according to the average of the transmission volume of each process in a plurality of pre-defined timing detection periods, and to re-confirm whether the parameter transmission period meets the standard according to the number of collected sand content parameters when the reliability of the parameter transmission period does not meet the standard when the initial confirmation is made, or to parse the reason why the reliability of the parameter transmission period does not meet the standard according to the time series variation range of the transmission volume of the process, and to register the type of each process;

[0043] The message construction unit is respectively connected to the adaptive information table and the analysis unit for refreshing the adaptive information table according to the arrangement status 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, the reliability of the parameter transmission period is analyzed based on the transmission volume to see if it meets the standard. When the transmission volume is not low, the number of sand content parameters collected by the parameter collection unit is used to reconfirm whether the parameter transmission period meets the standard, or the reason for non-compliance is analyzed based on the timing variation of the process transmission volume. When the timing variation of the transmission volume is not low, the parameters that do not meet the standard and cause the high transmission volume are considered to be sorted out. When the timing variation of the transmission volume is not large, the wireless network information transmission at the site during the parameter transmission period is unstable and the channel changes too quickly, thereby causing the transmission volume of the parameters at the process to be high, thereby improving the control accuracy during the parameter transmission period. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1It is a partial flow chart of the method for processing the sand content parameter for the construction of anti-fouling curtain fabrics described in the present invention;

[0047] Figure 2 It is a partial structural diagram of the device for processing the sand content parameters for the construction of anti-fouling curtain fabrics described in the present invention. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely expressed in conjunction with the drawings in the embodiments of the present invention. The embodiments expressed in this application are only partial embodiments of the present invention, not all embodiments. According to the spirit of the present invention, other embodiments obtained by technicians in this field without creative work are all within the protection scope of the present invention.

[0049] like Figure 1 As shown, the method for processing the sand content parameter of the anti-fouling curtain installation according to the present invention comprises:

[0050] The sand content sensor transmits the sand content parameters of the anti-fouling curtain installation area collected by it to the controller, and the controller transmits the sand content parameters of the anti-fouling curtain installation area collected by it to the statistical module of the position analysis platform, so that the statistical module obtains the sand content parameters of the anti-fouling curtain installation area;

[0051] After the controller transmits the collected sand content parameters of the anti-fouling curtain installation area to the location analysis platform, it also includes:

[0052] Step 1: Collect the sand content parameters transmitted by the controller of each sand content collection device;

[0053] Step 2: Use the Wiener filter to filter out the noise value in the sand content parameter, then add a mark to the filtered sand content parameter and send it to the statistical module of the location analysis platform, so that the statistical module can obtain the sand content parameter of the construction area where the anti-fouling curtain is installed;

[0054] Step 3: Identify the symbols in the sand content parameters after filtration;

[0055] Step 4: Use the CNN neural network to construct the action model of the parameters based on the learning set in the adaptive information table and the convergence condition of the constructed action model (minimization of the cross entropy loss function), and then analyze whether the reliability during parameter transmission is up to standard and update the adaptive information table.

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

[0057] Step 4-1: Detect the amount of information of the sand content parameter transmitted from each process. The amount of information of the sand content parameter transmitted is the transmission amount;

[0058] Step 4-2: Analyze whether the reliability of the parameter transmission period meets the standard according to the average of the transmission volume of each process in multiple pre-defined timed detection periods. If the reliability of the parameter transmission period does not meet the standard during the initial confirmation, re-confirm whether the parameter transmission period meets the standard according to the number of collected sand content parameters, or analyze the reason why the reliability of the parameter transmission period does not meet the standard according to the time series variation of the transmission volume of the process, and register the type of each process (different processes have different types);

[0059] Step 4-3: Refresh the adaptive information table according to the arrangement of each event.

[0060] Based on this, the transmission volume of each process is detected at regular intervals, and the reliability of the parameter transmission period is analyzed based on the transmission volume to see if it meets the standard. When the transmission volume is not low, the number of sand content parameters collected by the parameter collection unit is used to reconfirm whether the parameter transmission period meets the standard, or the reason for non-compliance is analyzed based on the timing variation of the process transmission volume. When the timing variation of the transmission volume is not low, the parameters that do not meet the standard and cause the high transmission volume are considered to be sorted out. When the timing variation of the transmission volume is not large, the wireless network information transmission at the site during the parameter transmission is unstable and the channel changes too fast, thereby causing the transmission volume of the parameters at the process to be high, thereby improving the control accuracy during the parameter transmission period.

[0061] In a preferred but non-limiting embodiment of the present invention, in Step 4-2, the method for analyzing whether the reliability during parameter transfer is up to standard includes:

[0062] The analysis unit is used to analyze whether the reliability of parameter transmission during the period of transmission meets the standard according to the average of the transmission volume of each process in the pre-defined timing detection period, which includes:

[0063] If the mean of the transmission amount is not higher than the predefined mean of the transmission amount, the parsing unit confirms that the reliability during the parameter transmission has reached the standard, and registers the currently parsed process as a first-level process;

[0064] If the average of the transmission amount is higher than the predefined average of the transmission amount one and not higher than the predefined average of the transmission amount two, then the analysis unit confirms whether the parameter transmission period meets the standard according to the number of sand content parameters collected by the parameter collection unit and reconfirms;

[0065] If the average of the transmission volume is higher than the predefined average of transmission volume two, the analyzing unit confirms that the reliability during the parameter transmission period does not meet the standard, and analyzes the reason for not meeting the standard according to the timing variation range of the transmission volume of the process.

[0066] In a preferred but non-limiting embodiment of the present invention, in Step 4-2, the average of the transmission amount in the corresponding period of the timing detection period under the same conditions without malware attack is determined based on the parameters of the previous transmission as the average transmission amount benchmark, and the average transmission amount defined in advance is the average transmission amount benchmark. The predefined average of the transmission volume is the average of the transmission volume. .

[0067] In a preferred but non-limiting embodiment of the present invention, in Step 4-2, the method for reconfirming whether the parameter transfer period meets the standard includes:

[0068] The number of sediment content parameters collected by the identification parameter collection unit during a predefined timed detection period;

[0069] If the number of sand content parameters is not higher than the predefined number, the analysis unit confirms that the reliability during parameter transmission is not up to standard, and analyzes the reason for not meeting the standard according to the time series variation range of the transmission amount of the process;

[0070] If the number of the sediment content parameters is higher than the predefined number, the parsing unit confirms that the reliability during the parameter transfer is up to standard and registers the current parsing process as a second-level process.

[0071] In a preferred but non-limiting embodiment of the present invention, in Step 4-2, the pre-defined number is based on the previous parameter identification, that is, the number of sand content parameters collected by the parameter collection unit in the pre-defined period under the condition of no malware attack is used as the number standard, and the pre-defined number is the number standard. .

[0072] It is taken into account here that the number of sand content parameters will determine the size of the parameter transmission bandwidth. The higher the number of sand content parameters, when the number of sand content parameters in the wireless network is too high, it will often cause wireless network congestion, thereby increasing the delay and loss rate of the sand content parameters. Excessively high sand content parameters indicate a greater amount of competition for wireless network channels, often causing the sand content parameters to queue up for transmission, increasing the transmission time. The present application determines the reliability of the parameter transmission period based on the number of sand content parameters. When the number of sand content parameters is large, it is determined that the reason why the parameter transmission rate is not low is because the number of sand content parameters is too high, rather than because of parameter leakage during the parameter transmission period, thereby improving the control accuracy during the parameter transmission period.

[0073] In a preferred but non-limiting embodiment of the present invention, in Step 4-2, the method for analyzing the reason why the reliability during parameter transmission is not up to standard according to the timing variation range of the transmission amount of the process includes:

[0074] Used to determine the transmission volume of the currently parsed process in each period of the timing detection period, calculate the standard deviation of the transmission volume in each period of the timing detection period, and if the standard deviation is not higher than the pre-defined standard deviation, then the parsing unit confirms that the reason why the reliability during the parameter transmission period does not meet the standard is that the parameter arrangement process does not meet the standard, and registers the message that the reason why the reliability during the parameter transmission period does not meet the standard is that the parameter arrangement process does not meet the standard as a first-level message;

[0075] If the standard deviation is higher than the predefined standard deviation, the parsing unit determines that the reason why the reliability during parameter transfer does not meet the standard is that the channel changes too quickly during parameter transfer, and registers the currently parsed process as a third-level process.

[0076] In a preferred but non-limiting embodiment of the present invention, in Step 4-2, the predefined standard deviation is predefined, that is, multiple sand content parameters transmitted under the condition of no malware attack are obtained, the transmission volume of each time period is determined, and the standard deviation of the transmission volume of each time period is obtained. The predefined standard deviation is the standard deviation of the transmission volume. .

[0077] Based on this, we first determine the transmission volume of the process in each time period, and calculate the standard deviation of the transmission volume value. Taking into account that a controller in the wireless network suddenly has a huge transmission volume and deviates from the normal range, it is often due to a malware attack that causes the transmission volume to be manipulated. Therefore, the fluctuation of the transmission volume in each time period is determined according to the standard deviation, and the reliability of the parameter transmission period is analyzed according to the fluctuation of the transmission volume, and whether there is a parameter malware attack. When the standard deviation is not low, it is determined that there is a reliable risk. Taking into account that the wireless networks in different intervals are different during the transmission period, and the fluctuation of the transmission volume in each time period caused by multiple changes of the wireless network is large, the process is registered according to the analysis information, and then it is analyzed whether there is a reliable risk according to the number ratio of each process, so as to improve the control accuracy during the parameter transmission period and improve the analysis accuracy during the parameter transmission period.

[0078] In a preferred but non-limiting embodiment of the present invention, Step 4-2 further includes: calibrating the sorting benchmark according to the ratio of abnormal parameters when the parameter sorting fails to meet the standard, which is specifically:

[0079] Register the parameters whose transmission volume is higher than the predefined value as abnormal parameters, calculate the ratio of the abnormal parameters to the total number of parameters collected by each process, obtain the abnormal ratio, arrange the reduction of the benchmark to be inversely proportional to the abnormal ratio; compare the abnormal ratio with the first predefined abnormal ratio and the second predefined abnormal ratio,

[0080] If the abnormality ratio is not higher than the first predefined abnormality ratio, then the first sorting reference is reduced, and the first sorting reference is the starting sorting reference predefined according to the specific requirements. ; If the anomaly ratio is higher than the first pre-defined anomaly ratio and not higher than the second pre-defined anomaly ratio, then reduce the second sorting benchmark, which is 8 / 10,000 of the initial sorting benchmark; if the anomaly ratio is higher than the second pre-defined anomaly ratio, then reduce the third sorting benchmark, which is 6 / 10,000 of the initial sorting benchmark.

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

[0082] In a preferred but non-limiting embodiment of the present invention, Step 4-2 further includes: summing up the registration status of each process, and determining the reason why the reliability during parameter transfer is not up to standard according to the ratio of each registered process, which is:

[0083] The number of processes of each type is summed up, and the ratio of the number of processes of each type is calculated by dividing the number of processes of each type by the total number of processes, to obtain the ratio of the number of processes of each type. If the ratio of the number of processes of the first level is the highest, then the parsing unit determines that the reason why the reliability during parameter transmission is not up to standard is parameter loss, and registers the message that the reason why the reliability during parameter transmission is not up to standard is parameter loss as the second level message;

[0084] If the ratio of the number of processes at the second level is the highest, the analysis unit confirms the reason why the reliability during parameter transfer is not up to standard based on the ratio of each abnormal parameter and performs reconfirmation;

[0085] If the ratio of the number of third-level processes is the highest, then the parsing unit confirms that the reason why the reliability during parameter transmission is not up to standard is that the transmission interval is too large, causing the wireless network status to fluctuate, and improves the fluctuating status of the wireless network, and registers the message that the reason why the reliability during parameter transmission is not up to standard is that the transmission interval is too large, causing the wireless network status to fluctuate as a third-level message.

[0086] In a preferred but non-limiting embodiment of the present invention, Step 4-2 further includes: calibrating the approximation benchmark under the condition of parameter loss, which is:

[0087] Determine the completeness of the stored parameters, calibrate the approximation benchmark based on the completeness, where the increase in the approximation benchmark is inversely proportional to the completeness; compare the completeness with a first pre-defined completeness and a second pre-defined completeness, and if the completeness is not higher than the first pre-defined completeness, increase the first approximation benchmark, which is a pre-defined starting approximation benchmark according to the 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, which is the initial approximation benchmark. If the completeness is higher than the second predefined completeness, then increase the third similarity benchmark, which is the initial similarity benchmark. .

[0088] Here, the abnormal parameter is determined based on the previous parameters, and whether a single parameter is an abnormal parameter is determined based on the similarity between each parameter and the abnormal parameter's benchmark.

[0089] In a preferred but non-limiting embodiment of the present invention, Step 4-2 further includes: reconfirming the reason why the reliability during parameter transfer is not up to standard according to the ratio of each abnormal parameter, which is:

[0090] If the ratio of abnormal transmission volume parameters is not lower than the pre-defined ratio, the parsing unit confirms that the reason why the reliability during parameter transmission is not up to standard is that the parameter sorting process is not up to standard, and registers the message that the reason why the reliability during parameter transmission is not up to standard is that the parameter sorting process is not up to standard as a first-level message; if the ratio of abnormal behavior parameters is not lower than the pre-defined ratio, the parsing unit confirms that the reason why the reliability during parameter transmission is not up to standard is parameter loss, and registers the message that the reason why the reliability during parameter transmission is not up to standard is parameter loss as a second-level message.

[0091] Predefined ratios in the range Select and use it.

[0092] The reliability of parameter transmission is analyzed according to the ratio of each abnormal parameter. When the ratio of abnormal parameters in transmission is not low, it is considered that the parameter sorting benchmark is not high and the parameter sorting is improper. When the ratio of abnormal parameters is not low, it is confirmed that parameters are missing, and each message is registered according to the analyzed information, which is conducive to focused improvement in the future.

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

[0094] like Figure 2As shown, the device for processing sand content parameters for anti-fouling curtain installation according to the present invention comprises:

[0095] A position analysis platform containing a position movement module and a statistical module (the position analysis platform can be a computer in a 4G network) and a sand content collection device provided in each anti-fouling curtain installation area. The statistical module is used to obtain the sand content parameters of the anti-fouling curtain installation area. The position movement module is used to obtain the movement position information of the floating body and the vertical body used for the anti-fouling curtain installation according to the sand content parameters of the anti-fouling curtain installation area. The sand content collection device includes a controller (the controller can be a single-chip microcomputer, a PLC or an industrial computer) connected to a sand content sensor and a wireless communication module (the wireless communication module can be a 4G module). The controller is connected to the position analysis platform in the wireless network via the wireless communication module. The sand content sensor is used to transmit the sand content parameters of the anti-fouling curtain installation area collected by it to the controller. The controller is used to transmit the sand content parameters of the anti-fouling curtain installation area collected and transmitted to the statistical module of the position analysis platform. In this way, the statistical module obtains the sand content parameters of the anti-fouling curtain installation area.

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

[0097] A parameter collecting unit, which includes a plurality of processes and is used to collect the sediment content parameters transmitted by the controller of each sediment content collecting device;

[0098] The parameter sorting unit is connected to the parameter collecting unit for filtering and sorting the noise value in the sand content parameter by using the Wiener filter, and then attaching a mark to the filtered sand content parameter and sending it to the statistical module of the location analysis platform, so that the statistical module obtains the sand content parameter of the installation area of ​​the anti-fouling curtain; the mark is a unique code assigned to the sand content parameter.

[0099] A mark recognition unit, which is connected to the parameter sorting unit for recognizing the mark attached to the sand content parameter after filtering and sorting;

[0100] The adaptive information table is used to store multiple learning sets (learning sets are the sand content parameters after filtering and sorting); the adaptive information table is an information table for storing multiple learning sets.

[0101] The action construction unit is communicated with the adaptive information table and is used to use the CNN neural network to construct the action model of the parameters according to the learning set in the adaptive information table and the convergence condition of the constructed action model (the convergence condition can be the minimization of the cross entropy loss function), and then analyze whether the reliability during the parameter transmission is up to standard and update the adaptive information table.

[0102] In a preferred but non-limiting embodiment of the present invention, the unit running on the position analysis platform further includes: a transmission amount detection unit, which is communicatively connected with the mark recognition unit and is used to detect the amount of information of the sand content parameter transmitted from each process, and the amount of information of the sand content parameter transmitted is the transmission amount;

[0103] The analysis unit is respectively 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, and is used to analyze whether the reliability of the parameter transmission period meets the standard according to the average of the transmission volume of each process in a plurality of pre-defined timing detection periods, and to re-confirm whether the parameter transmission period meets the standard according to the number of collected sand content parameters when the reliability of the parameter transmission period does not meet the standard when the initial confirmation is made, or to analyze the reason why the reliability of the parameter transmission period does not meet the standard according to the time series variation amplitude of the transmission volume of the process, and to register the type of each process (the type of process can be divided according to different methods, such as dividing the process of the installation area of ​​the plurality of anti-fouling curtains that are closest to each other where the sand content parameters are collected into one type);

[0104] The message construction unit is respectively connected to the adaptive information table and the analysis unit for refreshing the adaptive information table according to the arrangement status of each event.

[0105] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modification or equivalent replacement that does not deviate from the spirit and scope of the present invention should be covered within the protection space of the claims of the present invention.

Claims

1. A method for processing sand content parameters for anti-fouling curtain installation, characterized in that: include: The sand content sensor transmits the collected sand content parameters of the anti-fouling curtain installation area to the controller, and the controller transmits the collected sand content parameters of the anti-fouling curtain installation area to the statistical module of the location analysis platform; After the controller transmits the collected sand content parameters of the anti-fouling curtain installation area to the location analysis platform, it also includes: Step 1: Collect the sand content parameters transmitted by the controller of each sand content collection device; Step 2: Use the Wiener filter to filter out the noise value in the sediment content parameter, then add a mark to the filtered sediment content parameter and send it to the statistical module of the location analysis platform; Step 3: Identify the symbols in the sand content parameters after filtration; Step 4: Use the CNN neural network to construct the action model of the parameters and the convergence conditions of the constructed action model according to the learning set in the adaptive information table, and then analyze whether the reliability during the parameter transmission period meets the standards and update the adaptive information table.

2. The method for processing sand content parameters for anti-fouling curtain installation according to claim 1 is characterized in that: Then, the method of analyzing whether the reliability during parameter transmission meets the standard and refreshing the adaptive information table specifically includes: Step 4-1: Detect the amount of information of the sand content parameter transmitted from each process. The amount of information is the amount transmitted; Step 4-2: Analyze whether the reliability of the parameter transmission period meets the standard according to the average of the transmission volume of each process in multiple pre-defined timed detection periods. If the reliability of the parameter transmission period does not meet the standard during the initial confirmation, re-confirm whether the parameter transmission period meets the standard according to the number of collected sand content parameters, or analyze the reason why the reliability of the parameter transmission period does not meet the standard according to the time series variation range of the transmission volume of the process, and register the type of each process; Step 4-3: Refresh the adaptive information table according to the arrangement of each event.

3. The method for processing sand content parameters for anti-fouling curtain installation according to claim 2 is characterized in that: In Step 4-2, the method for analyzing whether the reliability during parameter transfer is up to standard includes: If the mean of the transmission amount is not higher than the predefined mean of the transmission amount, the parsing unit confirms that the reliability during the parameter transmission has reached the standard, and registers the currently parsed process as a first-level process; If the average of the transmission amount is higher than the predefined average of the transmission amount one and not higher than the predefined average of the transmission amount two, then the analysis unit confirms whether the parameter transmission period meets the standard according to the number of sand content parameters collected by the parameter collection unit and reconfirms; If the average of the transmission volume is higher than the predefined average of transmission volume two, the analyzing unit confirms that the reliability during the parameter transmission period does not meet the standard, and analyzes the reason for not meeting the standard according to the timing variation range of the transmission volume of the process.

4. The method for processing sand content parameters for anti-fouling curtain installation according to claim 3 is characterized in that: In Step 4-2, based on the parameters of previous transmissions, the average transmission volume in the corresponding period of the timing detection period under the same conditions without malware attack is determined as the average transmission volume benchmark. The average transmission volume defined in advance is the average transmission volume benchmark. The predefined average of the transmission volume is the average of the transmission volume. .

5. The method for processing sand content parameters for anti-fouling curtain installation according to claim 4 is characterized in that: In Step 4-2, the method to confirm whether the parameter transfer is up to standard includes: The number of sediment content parameters collected by the identification parameter collection unit during a predefined timed detection period; If the number of sand content parameters is not higher than the predefined number, the analysis unit confirms that the reliability during parameter transmission is not up to standard, and analyzes the reason for not meeting the standard according to the time series variation range of the transmission amount of the process; If the number of the sediment content parameters is higher than the predefined number, the parsing unit confirms that the reliability during the parameter transfer is up to standard and registers the current parsing process as a second-level process.

6. The method for processing sand content parameters for anti-fouling curtain installation according to claim 5, characterized in that: In Step 4-2, the predefined number is based on the previous parameter identification, that is, the number of sand content parameters collected by the parameter collection unit in the predefined period under the condition of no malware attack is used as the number standard. The predefined number is the number standard. .

7. The method for processing sand content parameters for anti-fouling curtain installation according to claim 6, characterized in that: In Step 4-2, the method for analyzing the reason why the reliability during parameter transmission is not up to standard according to the timing variation range of the process transmission amount includes: Used to determine the transmission volume of the currently parsed process in each period of the timing detection period, calculate the standard deviation of the transmission volume in each period of the timing detection period, and if the standard deviation is not higher than the pre-defined standard deviation, then the parsing unit confirms that the reason why the reliability during the parameter transmission period does not meet the standard is that the parameter arrangement process does not meet the standard, and registers the message that the reason why the reliability during the parameter transmission period does not meet the standard is that the parameter arrangement process does not meet the standard as a first-level message; If the standard deviation is higher than the predefined standard deviation, the parsing unit determines that the reason why the reliability during parameter transfer does not meet the standard is that the channel changes too quickly during parameter transfer, and registers the currently parsed process as a third-level process.

8. The method for processing sand content parameters for anti-fouling curtain installation according to claim 7, characterized in that: In Step 4-2, the predefined standard deviation is obtained by pre-definition, that is, obtaining multiple sand content parameters transmitted under the condition of no malware attack, determining the transmission volume in each period, and obtaining the standard deviation of the transmission volume in each period. The pre-defined standard deviation is the standard deviation of the transmission volume. .

9. A device for processing sand content parameters for anti-fouling curtain installation, characterized in that: include: A location analysis platform including a statistical module and a sand content collection device provided in each anti-fouling curtain installation area, wherein the statistical module is used to obtain the sand content parameters of the anti-fouling curtain installation area, and the sand content collection device includes a controller connected to a sand content sensor and a wireless communication module, wherein the controller is connected to the location analysis platform located in a wireless network via the wireless communication module, and the sand content sensor is used to transmit the sand content parameters of the anti-fouling curtain installation area collected by the sensor to the controller, and the controller is used to transmit the sand content parameters of the anti-fouling curtain installation area collected and transmitted to the statistical module of the location analysis platform; The units running on the location analysis platform include: A parameter collecting unit, which includes a plurality of processes and is used to collect the sediment content parameters transmitted by the controller of each sediment content collecting device; The parameter sorting unit is connected to the parameter collecting unit for filtering the noise value in the sediment content parameter by using the Wiener filter, and then attaching a mark to the filtered sediment content parameter and sending it to the statistical module of the location analysis platform; A mark recognition unit, which is connected to the parameter sorting unit for recognizing the mark attached to the sand content parameter after filtering and sorting; An adaptive information table, which is used to store multiple learning sets; The action construction unit is connected to the adaptive information table and is used to use the CNN neural network to construct the action model of the parameters according to the learning set in the adaptive information table and the convergence condition of the action model, and then analyze whether the reliability during the parameter transmission is up to standard and update the adaptive information table.

10. The device for processing sand content parameters for anti-fouling curtain installation according to claim 9, It is characterized in that The units running on the position analysis platform also include: a transmission amount detection unit, which is connected to the mark recognition unit for detecting the amount of information of the sand content parameter transmitted from each process, and the amount of information of the sand content parameter transmitted is the transmission amount; The parsing unit is respectively connected to the parameter collecting unit, the parameter sorting unit, the mark recognition unit, the adaptive information table, the action construction unit and the transmission volume detection unit, and is used to parse whether the reliability of the parameter transmission period meets the standard according to the average of the transmission volume of each process in a plurality of pre-defined timing detection periods, and to re-confirm whether the parameter transmission period meets the standard according to the number of collected sand content parameters when the reliability of the parameter transmission period does not meet the standard when the initial confirmation is made, or to parse the reason why the reliability of the parameter transmission period does not meet the standard according to the time series variation range of the transmission volume of the process, and to register the type of each process; The message construction unit is respectively connected to the adaptive information table and the analysis unit for refreshing the adaptive information table according to the arrangement status of each event.

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