Processing method and device for detection value of wharf bearing platform construction

Abstract

A method and device for processing a detection value for wharf bearing platform construction belong to the technical field of electrical digital data processing, and are characterized in that the reconstruction deviation of each current numerical value point is compared with a maneuvering critical quantity, the numerical value point higher than the critical quantity is registered as an interference value, and then the interference point is removed by using an interference value sorting method, so that the detection value is obtained. It is guaranteed that the numerical value points of the horizontal steel bars of the wharf bearing platform only contain temperature data meeting the monitoring requirement, the accuracy and efficiency of the sorted temperature data of the horizontal steel bars of the wharf bearing platform sent to a liquid crystal screen to be displayed later are improved, and the adverse effect of interference values on subsequent links is also prevented. And the accuracy and the high efficiency of the sorted temperature data of the horizontal steel bars of the wharf bearing platform, which are sent to the liquid crystal screen to be displayed, are ensured.

Description

Technical Field

[0001] The invention belongs to the technical field of electrical digital data processing, and in particular relates to a method and a device for processing detection values ​​for wharf cap construction. Background Art

[0002] The wharf cap is an important structure that bears and distributes the loads transmitted by the pier body. It is usually set on the top of the foundation piles. Its function is to connect the tops of the piles to form a reinforced concrete platform. When constructing the wharf cap, it is necessary to comprehensively consider multiple factors to ensure the smooth progress of the construction.

[0003] In practical applications, during the construction of the wharf cap, as mentioned in the prior art solution with patent publication number "CN110644363A", it includes a temperature sensor installed on the horizontal steel bars of the wharf cap, and the temperature sensor and the LCD screen are connected to the controller. The temperature sensor is used to sample the temperature data of the horizontal steel bars of the wharf cap and transmit it to the controller. The controller is used to transmit the temperature data of the horizontal steel bars of the wharf cap to the LCD screen for display, thereby completing the temperature detection of the horizontal steel bars of the wharf cap.

[0004] However, due to the clutter of the site where the horizontal steel bars of the wharf cap are located and the suddenness of external electromagnetic interference, the temperature data of the horizontal steel bars of the wharf cap often contains a lot of interference values. Such interference values ​​are not conducive to the performance of the temperature data of the horizontal steel bars of the wharf cap, and are even more not conducive to the accuracy of the temperature data of the horizontal steel bars of the wharf cap displayed on the LCD screen when the temperature data of the horizontal steel bars of the wharf cap containing a lot of interference values ​​is transmitted. Therefore, it is necessary to sort out the interference values ​​in the temperature data of the horizontal steel bars of the wharf cap.

[0005] In the current method of sorting out the interference values ​​in the temperature data of the horizontal steel bars of the wharf cap, a constant critical value is often used to determine whether the temperature data of the horizontal steel bars of the wharf cap is an interference value. However, the constant critical value is not suitable for the mobile and changing properties of the temperature data of the horizontal steel bars of the wharf cap, especially under the complex on-site conditions where the horizontal steel bars of the wharf cap are located. The fluctuation and suddenness of the temperature data of the horizontal steel bars of the wharf cap make it difficult for the constant critical value method to accurately identify the interference value. In addition, the current method of sorting out the interference values ​​in the temperature data of the horizontal steel bars of the wharf cap often lacks in-depth consideration of the composition and properties of the temperature data of the horizontal steel bars of the wharf cap, resulting in insufficient efficiency in sorting out the temperature data of the huge, multi-point, and mobile and changing horizontal steel bars of the wharf cap, and it is not easy to ensure the accuracy and reliability of the data. Summary of the invention

[0006] In order to solve the defects in the prior art, the present invention proposes a processing device and method for detection values ​​of wharf pedestal construction, which compares the reconstructed deviation of each current numerical point with the mobile critical value, and the numerical points exceeding the critical value are registered as interference values, and then the interference value sorting method is used to remove such interference values, thereby ensuring that the numerical points of the horizontal steel bars of the wharf pedestal only contain temperature data that meets the monitoring requirements, improving the accuracy and efficiency of the temperature data of the horizontal steel bars of the wharf pedestal after sorting and displayed on the LCD screen, and also preventing the adverse effects of the interference value on the subsequent links, thereby ensuring the accuracy and efficiency of the temperature data of the horizontal steel bars of the wharf pedestal after sorting and displayed on the LCD screen.

[0007] The present invention uses the following technical solutions.

[0008] A method for processing detection values ​​for wharf cap construction, comprising:

[0009] The temperature sensor samples the temperature data of the horizontal steel bars of the wharf cap and transmits it to the controller. The controller sorts the temperature data of the horizontal steel bars of the wharf cap and then transmits the sorted temperature data of the horizontal steel bars of the wharf cap to the LCD screen for display.

[0010] The method for the controller to sort out the temperature data of the horizontal steel bars of the wharf cap transmitted includes:

[0011] Step 1, using the modulation and demodulation mode to process the previous value point group of the horizontal steel bars of the wharf cap, and setting the initial critical value, where the initial critical value is the initial indicator for determining whether the value point is an interference value;

[0012] Step 2, obtaining the current value point in the current value point group of the horizontal steel bar of the wharf cap and sending it into the modulation and demodulation mode to perform numerical reconstruction, obtaining the reconstruction deviation, and obtaining the reconstruction variance and reconstruction mean according to the reconstruction deviation calculation;

[0013] Step 3: Use the mobile queue refresh rule to send the reconstruction deviation into the mobile queue with a preset capacity according to the time sequence;

[0014] Step 4, refreshing the initial critical amount according to the reconstruction variance and reconstruction mean of all reconstruction deviations in the mobile queue to obtain the maneuvering critical amount;

[0015] Step 5, selecting the reconstruction deviation corresponding to each current value point according to the maneuvering critical amount, obtaining the interference value, and sorting the interference value.

[0016] Further, in step 1, there are several temperature sensors, and several temperature sensors are arranged on the surface of the horizontal steel bars of the wharf pedestal. Several temperature sensors synchronously sample the temperature data of the horizontal steel bars of the wharf pedestal. The temperature data are also stored in the memory of the controller when transmitted to the controller. The overall temperature data transmitted by several temperature sensors at the same sampling time form a numerical point of the horizontal steel bars of the wharf pedestal. The previous numerical point group is a numerical point group formed by the controller taking out the numerical points corresponding to each sampling time in the time length set in the previous section in its memory.

[0017] Furthermore, in step 2, the current value point group of the horizontal steel bars of the wharf cap is the value points of the horizontal steel bars of all wharf caps transmitted within a set time period.

[0018] Furthermore, step 1 specifically includes:

[0019] Step 1-1, constructing a modulation and demodulation model, where the modulation and demodulation model includes principal component analysis and PCA inverse transformation;

[0020] Step 1-2, using the principal component analysis method to perform dimensionality reduction on the past value points in the past value point group of the horizontal steel bars of the wharf cap one by one to obtain the corresponding reduced-dimensional values ​​of each past value point, and then the PCA inverse transformation performs operations on the reduced-dimensional values ​​one by one to reconstruct the corresponding reconstructed value points;

[0021] Step 1-3, after obtaining the corresponding reconstruction value points, obtain the past reconstruction deviations of each corresponding reconstruction value point, and all past reconstruction deviations form a past reconstruction deviation group. The variance and mean of the past reconstruction deviations in the past reconstruction deviation group are defined as the starting variance and the starting mean, respectively, and the starting critical amount is calculated based on the starting variance and the starting mean.

[0022] Furthermore, in step 1-3, the method of obtaining the past reconstruction deviation of each corresponding reconstruction value point includes:

[0023] Obtain the L2 norm of the reconstructed numerical point and its corresponding past numerical point, and use the L2 norm as the past reconstruction deviation of the reconstructed numerical point.

[0024] Furthermore, in step 1-3, the operation equation of the initial critical amount is:

[0025] , here, is the starting critical mass, is the starting mean, is the starting variance, is a pre-set constant.

[0026] Furthermore, step 2 specifically includes:

[0027] Step 2-1, performing operations on each current value point in the current value point group one by one through the principal component analysis method of the modulation and demodulation mode, and obtaining the corresponding dimension-reduced value of each current value point;

[0028] Step 2-2, reconstructing the dimension-reduced values ​​of the current value point one by one through the PCA inverse transformation of the modulation and demodulation mode to obtain the corresponding reconstructed value point;

[0029] Step 2-3, obtain the L2 norm between each current value point and its corresponding reconstruction value point, use the L2 norm as the reconstruction deviation corresponding to the current value point, and obtain the reconstruction variance and reconstruction mean based on the reconstruction deviation calculation.

[0030] Furthermore, in step 2-3, the method of obtaining the reconstruction variance and the reconstruction mean according to the reconstruction deviation calculation includes:

[0031] The reconstruction deviations corresponding to all current value points are formed into a reconstruction deviation group, and then the variance and mean of the reconstruction deviations in the reconstruction deviation group are used as the reconstruction variance and reconstruction mean, respectively.

[0032] Furthermore, step 3 specifically includes:

[0033] Step 3-1, arranging the reconstruction deviations according to the time sequence, and obtaining a reconstruction deviation queue arranged according to the time sequence;

[0034] Step 3-2, starting to fill the reconstruction deviation queue arranged in time sequence into the mobile queue, and obtaining a mobile queue containing a preset number of reconstruction deviations;

[0035] Step 3-3, performing a dynamic refresh on the reconstruction deviation in the mobile queue after the mobile queue is initially filled according to the mobile queue refresh rule, so as to maintain the reconstruction deviation in the mobile queue to be recent.

[0036] Furthermore, step 4 specifically includes:

[0037] Step 4-1, add the reconstruction variance and reconstruction mean of all reconstruction deviations in the mobile queue to the previous reconstruction deviation group;

[0038] Step 4-2, calculate the current mean and current variance by calculating the initial variance and initial mean of all previous reconstruction deviation groups, as well as the reconstruction variance and reconstruction mean of all reconstruction deviations in the mobile queue. Here, the calculation equation of the current mean is:

[0039] , here, is the current mean, and are the initial mean and the reconstructed mean, and They are parameter 1 of the initial mean and parameter 2 of the reconstructed mean;

[0040] The current equation for the variance is:

[0041] , here, and They are the number of previous value points and the number of current value points in the mobile queue. and They are the initial variance and the reconstruction variance respectively;

[0042] Step 4-3, obtain the maneuverability critical value based on the current variance and the current mean. Here, the calculation equation of the maneuverability critical value is:

[0043] , here, is the critical mass of mobility, is the current mean, is the current variance, is a pre-set constant.

[0044] Furthermore, step 5 specifically includes:

[0045] Compare the mobile critical value with the reconstruction deviation of the current numerical point. If the reconstruction deviation is higher than the mobile critical value, the current numerical point corresponding to the reconstruction deviation will be identified as an interference value, and the interference value will be removed. The current numerical point after removing the interference value is the sorted temperature data of the horizontal steel bars of the wharf foundation.

[0046] A device for processing detection values ​​for wharf cap construction, comprising:

[0047] A temperature sensor is installed on the horizontal steel bar of the wharf cap. The temperature sensor and the LCD screen are connected to the controller. The temperature sensor is used to sample the temperature data of the horizontal steel bar of the wharf cap and transmit it to the controller. The controller is used to sort out the temperature data of the horizontal steel bar of the wharf cap, and then transmit the sorted temperature data of the horizontal steel bar of the wharf cap to the LCD screen for display.

[0048] The modules running on the controller include:

[0049] The past processing module is used to process the past numerical point group of the horizontal steel bars of the wharf cap using a modulation and demodulation mode, and set a starting critical value. Here, the starting critical value is a starting indicator for determining whether a numerical point is an interference value;

[0050] A reconstruction module, which is used to obtain the current numerical point in the current numerical point group of the horizontal steel bars of the wharf cap and send it into the modulation and demodulation mode to perform numerical reconstruction, obtain the reconstruction deviation, and obtain the reconstruction variance and reconstruction mean according to the reconstruction deviation calculation;

[0051] A queue module, which is used to use the mobile queue refresh rule to send the reconstruction deviation into the mobile queue of the pre-set capacity according to the time sequence;

[0052] A maneuvering module, which is used to refresh the initial critical amount according to the reconstruction variance and reconstruction mean of all reconstruction deviations in the mobile queue to obtain the maneuvering critical amount;

[0053] The sorting module is used to select the reconstruction deviation corresponding to each current value point according to the maneuvering critical amount, obtain the interference value, and sort the interference value.

[0054] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0055] A modulation and demodulation mode is used to process the past numerical point groups of the horizontal steel bars of the wharf cap, and a starting critical value is set. Here, the starting critical value is a starting indicator for determining whether a numerical point is an interference value; the current numerical point of the horizontal steel bars of the wharf cap is obtained and sent to the modulation and demodulation mode for numerical reconstruction, and a reconstruction deviation is obtained, and a reconstruction variance and a reconstruction mean are obtained based on the reconstruction deviation calculation; the reconstruction deviation is sent to a mobile queue with a preset capacity according to a time sequence using a mobile queue refresh rule; the starting critical value is refreshed based on the reconstruction variance and reconstruction mean of all reconstruction deviations in the mobile queue to obtain a mobile critical value. The present invention performs numerical sorting based on the mobile critical value, which significantly improves the performance and reliability of the temperature data of the horizontal steel bars of the wharf cap. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is a flow chart of the method for processing the detection value of the wharf cap construction described in the present invention;

[0057] Figure 2 It is a partial structural diagram of the detection value processing device for wharf cap construction described in the present invention. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solution and advantages of the present invention clearer, the following will be combined with the drawings in the embodiments of the present invention to clearly and completely express the technical solution 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.

[0059] like Figure 1 As shown, a method for processing detection values ​​for wharf cap construction according to the present invention includes:

[0060] The temperature sensor samples the temperature data of the horizontal steel bars of the wharf cap and transmits it to the controller. The controller sorts the temperature data of the horizontal steel bars of the wharf cap and then transmits the sorted temperature data of the horizontal steel bars of the wharf cap to the LCD screen for display, thereby completing the temperature detection of the horizontal steel bars of the wharf cap.

[0061] The method for the controller to sort out the temperature data of the horizontal steel bars of the wharf cap transmitted includes:

[0062] Step 1, using the modulation and demodulation mode to process the previous value point group of the horizontal steel bars of the wharf cap, and setting the initial critical value, where the initial critical value is the initial indicator for determining whether the value point is an interference value;

[0063] In a preferred but non-restrictive embodiment of the present invention, in step 1, the number of temperature sensors is several, and the several temperature sensors are installed on the horizontal steel bars of the wharf pedestal. The sampling time of the temperature data of the horizontal steel bars of the wharf pedestal is also the sampling time of its corresponding temperature data. When the temperature data is transmitted to the controller, it is also stored in the memory of the controller. The overall temperature data transmitted by the several temperature sensors at the same sampling time forms a numerical point of the horizontal steel bars of the wharf pedestal. The previous numerical point group is a numerical point group formed by the controller taking out the numerical points corresponding to each sampling time in the time length set in the previous section in its memory.

[0064] In this application, the modulation and demodulation mode is used to process the past numerical point groups of the horizontal steel bars of the pier foundation, and an initial critical value is set based on the total analysis of the past values. The critical value is the initial indicator for determining whether the numerical point is an interference value.

[0065] The initial critical value is used to provide a reference indicator when the modulation and demodulation mode has not been fully adapted to the changes in the on-site conditions of the horizontal steel bars of the wharf foundation. It is suitable for preventing excessive misidentification of interference values ​​or failure to detect interference values ​​during the mode initialization stage.

[0066] Step 2, obtaining the current value point in the current value point group of the horizontal steel bar of the wharf cap and sending it into the modulation and demodulation mode to perform numerical reconstruction, obtaining the reconstruction deviation, and obtaining the reconstruction variance and reconstruction mean according to the reconstruction deviation calculation;

[0067] In a preferred but non-limiting embodiment of the present invention, in step 2, the current value point group of the horizontal steel bars of the dock cap is the value points of the horizontal steel bars of all dock caps transmitted within the current set time length. The current time here is the current moment, and the current set time length is a set time length from the current moment. For example, the current moment is 15:00 on the day, that is, the current moment is 15:00 on the day, and the set time length is 5 seconds, so the current set time length is the period from 15:00 on the day to 15:00:05 on the day.

[0068] In the present application, the numerical points of the horizontal steel bars of the wharf pedestal currently obtained and transmitted are sent to the modulation and demodulation mode, and the mode sends out the reconstructed numerical points, so as to calculate the difference between the source numerical points (the source numerical points are the numerical points of the horizontal steel bars of the wharf pedestal currently obtained and transmitted) and the reconstructed numerical points, that is, the reconstruction deviation, so as to quantify the deviation between the current numerical points and the model evaluation values, and provide a numerical basis for the subsequent interference value detection.

[0069] Step 3: Use the mobile queue refresh rule to send the reconstruction deviation into the mobile queue with a preset capacity according to the time sequence;

[0070] In the present application, a time period queue of a constant span is constructed. When a new reconstruction deviation is formed, it is added to the queue, but the deviation first sent to the queue is removed to maintain a constant number of deviations in the queue.

[0071] Through the mobile queue rules, the mobile detection of the reconstruction deviation of the numerical point in the most recent section is achieved, so that the interference value detection can adapt well to the changes in the conditions at the site where the horizontal steel bars of the wharf pedestal are located, thereby improving the mobile adaptability and accuracy of the interference value detection and reducing the number of misidentified interference values ​​caused by the changes in the conditions at the site where the horizontal steel bars of the wharf pedestal are located.

[0072] Step 4, refreshing the initial critical amount according to the reconstruction variance and reconstruction mean of all reconstruction deviations in the mobile queue to obtain the maneuvering critical amount;

[0073] In the present application, the mean and variance of the reconstruction deviation in the mobile queue are calculated, and the starting critical amount is configured based on this total measurement to form a mobile critical amount. The mobile critical amount can more accurately reflect the total attributes of the current numerical point, reduce the number of reasonable temperature data mistaken for interference values ​​and the number of interference values ​​mistaken for reasonable temperature data, and can adapt to significant changes in the length of time presented by temperature data, thereby improving the robustness and stability of interference value detection.

[0074] Step 5, selecting the reconstruction deviation corresponding to each current value point according to the maneuvering critical amount, obtaining the interference value, and sorting the interference value.

[0075] In the present application, the reconstructed deviation of each current numerical point is compared with the mobile critical value, and the numerical points exceeding the critical value are registered as interference values, and then the interference value sorting method is used to remove such interference values, thereby ensuring that the numerical points of the horizontal steel bars of the wharf pedestal contain only temperature data that meets the monitoring requirements, thereby improving the accuracy and efficiency of the temperature data of the horizontal steel bars of the wharf pedestal after sorting and displayed on the LCD screen, and also preventing the adverse effects of the interference value on subsequent links, thereby ensuring the accuracy and efficiency of the temperature data of the horizontal steel bars of the wharf pedestal after sorting and displayed on the LCD screen.

[0076] In a preferred but non-limiting embodiment of the present invention, step 1 specifically comprises:

[0077] Step 1-1, constructing a modulation and demodulation model, where the modulation and demodulation model includes principal component analysis and PCA inverse transformation;

[0078] In this application, the principal component analysis method is used to perform dimensionality reduction on the past numerical points in the past numerical point group of the horizontal steel bars of the pier foundation one by one to obtain the corresponding reduced-dimensional values ​​of each past numerical point, and the PCA inverse transformation attempts to reconstruct the corresponding restored values, that is, the corresponding reconstructed numerical points, through the reduced-dimensional values.

[0079] Step 1-2, using the principal component analysis method to perform dimensionality reduction on the past value points in the past value point group of the horizontal steel bars of the wharf cap one by one to obtain the corresponding reduced-dimensional values ​​of each past value point, and then the PCA inverse transformation performs operations on the reduced-dimensional values ​​one by one to reconstruct the corresponding reconstructed value points;

[0080] Step 1-3, after obtaining the corresponding reconstruction value points, obtain the past reconstruction deviations of each corresponding reconstruction value point, and all past reconstruction deviations form a past reconstruction deviation group. The variance and mean of the past reconstruction deviations in the past reconstruction deviation group are defined as the starting variance and the starting mean, respectively, and the starting critical amount is calculated based on the starting variance and the starting mean.

[0081] In a preferred but non-limiting embodiment of the present invention, in steps 1-3, the method for obtaining the past reconstruction deviation of each corresponding reconstruction value point includes:

[0082] Obtain the L2 norm of the reconstructed numerical point and its corresponding past numerical point, and use the L2 norm as the past reconstruction deviation of the reconstructed numerical point.

[0083] In a preferred but non-limiting embodiment of the present invention, in steps 1-3, the operation equation of the initial critical amount is:

[0084] , here, is the starting critical mass, is the starting mean, is the starting variance, is a pre-set constant. The constant can be three.

[0085] In the present application, the past reconstruction deviations of each past numerical point are registered. Such past reconstruction deviations reflect the function of the model reconstruction value. By performing a total analysis on such past reconstruction deviations, their initial mean and initial variance can be calculated, and the initial critical quantity is confirmed by multiplying the variance with a pre-set constant and adding the mean. The critical quantity is the starting indicator for determining whether a numerical point is an interference value.

[0086] In a preferred but non-limiting embodiment of the present invention, step 2 specifically comprises:

[0087] Step 2-1, performing operations on each current value point in the current value point group one by one through the principal component analysis method of the modulation and demodulation mode, and obtaining the corresponding dimension-reduced value of each current value point;

[0088] Step 2-2, reconstructing the dimension-reduced values ​​of the current value point one by one through the PCA inverse transformation of the modulation and demodulation mode to obtain the corresponding reconstructed value point;

[0089] Step 2-3, obtain the L2 norm between each current value point and its corresponding reconstruction value point, use the L2 norm as the reconstruction deviation corresponding to the current value point, and obtain the reconstruction variance and reconstruction mean based on the reconstruction deviation calculation.

[0090] In a preferred but non-limiting embodiment of the present invention, in step 2-3, the method for obtaining the reconstruction variance and the reconstruction mean according to the reconstruction deviation calculation includes:

[0091] The reconstruction deviations corresponding to all current value points are formed into a reconstruction deviation group, and then the variance and mean of the reconstruction deviations in the reconstruction deviation group are used as the reconstruction variance and reconstruction mean, respectively.

[0092] In the present application, the L2 norm between the current numerical point and the reconstructed numerical point is calculated. For each current numerical point, there will be a corresponding reconstruction deviation, which is the difference between the source numerical point and the reconstructed numerical point. Then, a total analysis is performed on the reconstruction deviations of all current numerical points, and the mean (reconstruction mean) and variance (reconstruction variance) of such deviations are calculated. The reconstruction mean reflects the mean deviation of the model reconstruction value, and the reconstruction variance represents the discrete amplitude of the deviation. Such total quantities will be used for subsequent refresh of the maneuvering critical quantity.

[0093] In a preferred but non-limiting embodiment of the present invention, step 3 specifically comprises:

[0094] Step 3-1, arranging the reconstruction deviations according to the time sequence, and obtaining a reconstruction deviation queue arranged according to the time sequence;

[0095] In the present application, the reconstruction deviations of all current numerical points are gathered, and are arranged in chronological order according to the sampling moments of the various numerical points to form a reconstruction deviation queue. Here, each numerical value in the reconstruction deviation queue is a numerical cluster containing a sampling moment and a corresponding reconstruction deviation. The arrangement method ensures that the reconstruction deviations are arranged in chronological order according to the sampling moments of the corresponding numerical points, which is critical to the formation of subsequent mobile queue rules.

[0096] Step 3-2, starting to fill the reconstruction deviation queue arranged in time sequence into the mobile queue, and obtaining a mobile queue containing a preset number of reconstruction deviations;

[0097] In the present application, a mobile queue with a corresponding capacity (the corresponding capacity is the number of values ​​in the mobile queue) is set in advance. The capacity of the queue is often confirmed based on the analysis of past values, and represents the number of value points that can be sampled within a period of time (such as 2s). The pre-set number of deviations before the corresponding sampling time in the arranged reconstructed deviation queue is sent to the mobile queue. The capacity of the queue should be high enough to obtain the short-term trend of the current value point, but not too high to cause feedback delay.

[0098] Step 3-3, performing a dynamic refresh on the reconstruction deviation in the mobile queue after the mobile queue is initially filled according to the mobile queue refresh rule, so as to maintain the reconstruction deviation in the mobile queue to be recent.

[0099] In the present application, as a new current value point is delivered, its reconstruction deviation is calculated and added to the end of the mobile queue. The reconstruction deviation at the front of the mobile queue is synchronously removed to maintain the number of reconstruction deviations in the queue constant. This means that the value in the queue always reflects the condition of the horizontal steel bars of the wharf foundation in the recent period of time. The refresh rules of the mobile queue ensure that the mobile critical amount can be configured according to the latest current value point, thereby improving the timeliness and accuracy of interference value detection.

[0100] In a preferred but non-limiting embodiment of the present invention, step 4 specifically comprises:

[0101] Step 4-1, add the reconstruction variance and reconstruction mean of all reconstruction deviations in the mobile queue to the previous reconstruction deviation group;

[0102] In the present application, the reconstruction variance and reconstruction mean of all reconstruction deviations are aggregated in the mobile queue, and such total quantities are aggregated with the previous reconstruction deviation group to form an overall value group. This method ensures that the total attributes of new values ​​and past values ​​are taken into account, and provides an overall total value for the calculation of the maneuvering critical amount.

[0103] Step 4-2, calculate the current mean and current variance by calculating the initial variance and initial mean of all previous reconstruction deviation groups, as well as the reconstruction variance and reconstruction mean of all reconstruction deviations in the mobile queue. Here, the calculation equation of the current mean is:

[0104] , here, is the current mean, and are the initial mean and the reconstructed mean, and They are parameter 1 of the initial mean and parameter 2 of the reconstructed mean;

[0105] Here, the values ​​of parameter 1 and parameter 2 can be and .

[0106] In this application, during the calculation of the current mean and the current variance, the initial mean and variance of the previous values ​​(corresponding to parameter 1, respectively) are given lower importance ( ), and give higher importance to the reconstructed mean and variance (corresponding to parameter 2, respectively) of the current value (that is, the value in the mobile queue) ( ), by giving the current value a higher criticality, the current mean can be closer to the actual situation of the current value. The synchronized mean of past values ​​still has some effect on the conclusion, ensuring the stability of the current mean and preventing strong fluctuations caused by a single interference value.

[0107] The current equation for the variance is:

[0108] , here, and They are the number of previous value points and the number of current value points in the mobile queue. and are the initial variance and the reconstruction variance respectively.

[0109] The calculation of the current variance takes into account the variance of past values ​​and current values ​​as a whole. By configuring the criticality of each value in the dividend (determined by the number of numerical points), it ensures that the current variance not only reflects the stability of past values, but also the mobility of current values. The calculation method of the current variance ensures that the flexible configuration of the interference value detection critical amount can take into account the long-term trend of past values ​​and the short-term fluctuations of current values, thereby improving the mobility and accuracy of the critical amount setting and reducing the risk of misidentification and failure to detect interference values.

[0110] Step 4-3, obtain the maneuverability critical value based on the current variance and the current mean. Here, the calculation equation of the maneuverability critical value is:

[0111] , here, is the critical mass of mobility, is the current mean, is the current variance, is a pre-set constant.

[0112] In this application, It is usually set to three to ensure that the critical value can accurately distinguish between reasonable values ​​and interference values. By entering the current mean and the current variance into the equation, a dynamically refreshed critical value can be obtained, which can be autonomously configured according to the total attributes of the value, thereby improving the accuracy and adaptability of interference value detection.

[0113] In a preferred but non-limiting embodiment of the present invention, step 5 specifically comprises:

[0114] Compare the mobile critical value with the reconstruction deviation of the current numerical point. If the reconstruction deviation is higher than the mobile critical value, the current numerical point corresponding to the reconstruction deviation will be identified as an interference value, and the interference value will be removed. The current numerical point after removing the interference value is the sorted temperature data of the horizontal steel bars of the wharf foundation.

[0115] In this application, when facing the reconstruction deviation of each current value point, it is compared with the maneuvering threshold. If the reconstruction deviation is higher than the maneuvering threshold, it means that there is a significant deviation between the value point and the reasonable value of the model evaluation. At this time, the value point is identified as an interference value. The interference value detection is based on the difference between the current value point and the model reconstruction value point, that is, the reconstruction deviation. Through comparison with the maneuvering threshold, the corresponding interference condition can be identified immediately.

[0116] Once an interference value is detected, it is immediately identified and its status is recorded in the current value group. It is often done by attaching an interference mark to the record, or storing it in an interference value queue for later processing. Recording the sampling time, source data value, reconstruction error, etc. of the interference value will be crucial to analyzing the source of interference and improving on-site conditions.

[0117] Perform sorting on the numerical points identified as interference, and sorting is to remove the interference values.

[0118] Based on this, by introducing the modulation and demodulation mode set according to the previous numerical point group of the horizontal steel bars of the wharf pedestal, and combining the mobile critical quantity configuration scheme, the efficient and accurate processing of the temperature data of the horizontal steel bars of the wharf pedestal was achieved, which not only significantly improved the recognition accuracy of the interference value, but also effectively reduced the two quantities of misidentification and undetected interference values, ensuring the credibility and efficiency of the numerical collation.

[0119] That is, through the reconstruction process of the modulation and demodulation mode, the in-depth consideration of the composition and properties of the temperature data of the horizontal steel bars of the wharf cap is further strengthened, so that the reasonable fluctuation range of the temperature data of the horizontal steel bars of the wharf cap can be more accurately evaluated, and an accurate basis is provided for the setting of the mobile critical amount. The mobile critical amount can provide real-time feedback on the changing trend of the temperature data of the horizontal steel bars of the wharf cap. Even when the temperature data of the horizontal steel bars of the wharf cap fluctuates greatly, it can also maintain excellent interference value detection function.

[0120] In addition, the application of mobile queue refresh rules further enhances the method's ability to handle time series values, allowing it to flexibly configure critical quantities within a continuous range of numerical points to ensure the rapid and accurate identification of the recently transmitted temperature data of the horizontal steel bars of the wharf pedestal. This not only improves the timeliness of the temperature data compilation of the horizontal steel bars of the wharf pedestal, but also ensures the timeliness and accuracy of the temperature data of the horizontal steel bars of the wharf pedestal.

[0121] Finally, the performance of the temperature data of the horizontal steel bars of the wharf pedestal organized by this application has been significantly improved, and the interference values ​​have been efficiently removed, providing more reliable and high-performance numerical support for the subsequent execution of the temperature data of the horizontal steel bars of the wharf pedestal displayed on the LCD screen.

[0122] like Figure 2 As shown, the present invention provides a device for processing detection values ​​for wharf cap construction, comprising:

[0123] A temperature sensor is installed on the horizontal steel bar of the wharf cap. The temperature sensor and the LCD screen are connected to the controller. The temperature sensor is used to sample the temperature data of the horizontal steel bar of the wharf cap and transmit it to the controller. The controller is used to sort out the temperature data of the horizontal steel bar of the wharf cap, and then transmit the sorted temperature data of the horizontal steel bar of the wharf cap to the LCD screen for display, thereby completing the temperature detection of the horizontal steel bar of the wharf cap.

[0124] The modules running on the controller include:

[0125] The past processing module is used to process the past numerical point group of the horizontal steel bars of the wharf cap using a modulation and demodulation mode, and set a starting critical value. Here, the starting critical value is a starting indicator for determining whether a numerical point is an interference value;

[0126] A reconstruction module, which is used to obtain the current numerical point in the current numerical point group of the horizontal steel bars of the wharf cap and send it into the modulation and demodulation mode to perform numerical reconstruction, obtain the reconstruction deviation, and obtain the reconstruction variance and reconstruction mean according to the reconstruction deviation calculation;

[0127] A queue module, which is used to use the mobile queue refresh rule to send the reconstruction deviation into the mobile queue of the pre-set capacity according to the time sequence;

[0128] A maneuvering module, which is used to refresh the initial critical amount according to the reconstruction variance and reconstruction mean of all reconstruction deviations in the mobile queue to obtain the maneuvering critical amount;

[0129] The sorting module is used to select the reconstruction deviation corresponding to each current value point according to the maneuvering critical amount, obtain the interference value, and sort the interference value. The controller can be an FPGA, a PLC or an industrial computer.

[0130] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0131] A modulation and demodulation mode is used to process the past numerical point groups of the horizontal steel bars of the wharf cap, and a starting critical value is set. Here, the starting critical value is a starting indicator for determining whether a numerical point is an interference value; the current numerical point of the horizontal steel bars of the wharf cap is obtained and sent to the modulation and demodulation mode for numerical reconstruction, and a reconstruction deviation is obtained, and a reconstruction variance and a reconstruction mean are obtained based on the reconstruction deviation calculation; the reconstruction deviation is sent to a mobile queue with a preset capacity according to a time sequence using a mobile queue refresh rule; the starting critical value is refreshed based on the reconstruction variance and reconstruction mean of all reconstruction deviations in the mobile queue to obtain a mobile critical value. The present invention performs numerical sorting based on the mobile critical value, which significantly improves the performance and reliability of the temperature data of the horizontal steel bars of the wharf cap.

[0132] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions 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 modifications or equivalent replacements that do 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 detection values ​​for wharf cap construction, characterized in that: include: The temperature sensor samples the temperature data of the horizontal steel bars of the wharf cap and transmits it to the controller. The controller sorts the temperature data of the horizontal steel bars of the wharf cap and then transmits the sorted temperature data of the horizontal steel bars of the wharf cap to the LCD screen for display. The method for the controller to sort out the temperature data of the horizontal steel bars of the wharf cap transmitted includes: Step 1, using the modulation and demodulation mode to process the previous value point group of the horizontal steel bars of the wharf cap, and setting the initial critical value, where the initial critical value is the initial indicator for determining whether the value point is an interference value; Step 2, obtaining the current value point in the current value point group of the horizontal steel bar of the wharf cap and sending it into the modulation and demodulation mode to perform numerical reconstruction, obtaining the reconstruction deviation, and obtaining the reconstruction variance and reconstruction mean according to the reconstruction deviation calculation; Step 3: Use the mobile queue refresh rule to send the reconstruction deviation into the mobile queue with a preset capacity according to the time sequence; Step 4, refreshing the initial critical amount according to the reconstruction variance and reconstruction mean of all reconstruction deviations in the mobile queue to obtain the maneuvering critical amount; Step 5, selecting the reconstruction deviation corresponding to each current value point according to the maneuvering critical amount, obtaining the interference value, and sorting the interference value.

2. The method for processing detection values ​​for wharf cap construction according to claim 1, characterized in that: In step 1, there are several temperature sensors, and several temperature sensors are arranged on the surface of the horizontal steel bars of the wharf cap. Several temperature sensors synchronously sample the temperature data of the horizontal steel bars of the wharf cap. When the temperature data is transmitted to the controller, it is also stored in the memory of the controller. The overall temperature data transmitted by several temperature sensors at the same sampling time forms a numerical point of the horizontal steel bars of the wharf cap. The previous numerical point group is a numerical point group formed by the controller taking out the numerical points corresponding to each sampling time in the time length set in the previous section in its memory.

3. The method for processing detection values ​​for wharf cap construction according to claim 2, characterized in that: In step 2, the current value point group of the horizontal steel bars of the wharf cap is the value points of the horizontal steel bars of all wharf caps transmitted within a set time period.

4. The method for processing detection values ​​for wharf cap construction according to claim 3, characterized in that: Step 1 specifically includes: Step 1-1, constructing a modulation and demodulation model, where the modulation and demodulation model includes principal component analysis and PCA inverse transformation; Step 1-2, using the principal component analysis method to perform dimensionality reduction on the past value points in the past value point group of the horizontal steel bars of the wharf cap one by one to obtain the corresponding reduced-dimensional values ​​of each past value point, and then the PCA inverse transformation performs operations on the reduced-dimensional values ​​one by one to reconstruct the corresponding reconstructed value points; Step 1-3, after obtaining the corresponding reconstruction value points, obtain the past reconstruction deviations of each corresponding reconstruction value point, and all past reconstruction deviations form a past reconstruction deviation group. The variance and mean of the past reconstruction deviations in the past reconstruction deviation group are defined as the starting variance and the starting mean, respectively, and the starting critical amount is calculated based on the starting variance and the starting mean.

5. The method for processing detection values ​​for wharf cap construction according to claim 4, characterized in that: In step 1-3, the method of obtaining the past reconstruction deviation of each corresponding reconstruction value point includes: Obtain the L2 norm of the reconstructed value point and its corresponding past value point, and use the L2 norm as the past reconstruction deviation of the reconstructed value point; In steps 1-3, the calculation equation for the initial critical volume is: , here, is the starting critical mass, is the starting mean, is the starting variance, is a pre-set constant.

6. The method for processing detection values ​​for wharf cap construction according to claim 5, characterized in that: Step 2 specifically includes: Step 2-1, performing operations on each current value point in the current value point group one by one through the principal component analysis method of the modulation and demodulation mode, and obtaining the corresponding dimension-reduced value of each current value point; Step 2-2, reconstructing the dimension-reduced values ​​of the current value point one by one through the PCA inverse transformation of the modulation and demodulation mode to obtain the corresponding reconstructed value point; Step 2-3, obtain the L2 norm between each current value point and its corresponding reconstruction value point, use the L2 norm as the reconstruction deviation corresponding to the current value point, and obtain the reconstruction variance and reconstruction mean based on the reconstruction deviation calculation.

7. The method for processing detection values ​​for wharf cap construction according to claim 6, characterized in that: In step 2-3, the method of obtaining the reconstruction variance and the reconstruction mean according to the reconstruction deviation calculation includes: The reconstruction deviations corresponding to all current value points are formed into a reconstruction deviation group, and then the variance and mean of the reconstruction deviations in the reconstruction deviation group are used as the reconstruction variance and reconstruction mean, respectively.

8. The method for processing detection values ​​for wharf cap construction according to claim 7, characterized in that: Step 3 specifically includes: Step 3-1, arranging the reconstruction deviations according to the time sequence, and obtaining a reconstruction deviation queue arranged according to the time sequence; Step 3-2, starting to fill the reconstruction deviation queue arranged in time sequence into the mobile queue, and obtaining a mobile queue containing a preset number of reconstruction deviations; Step 3-3, performing a dynamic refresh on the reconstruction deviation in the mobile queue after the mobile queue is initially filled according to the mobile queue refresh rule, so as to maintain the reconstruction deviation in the mobile queue to be recent.

9. The method for processing detection values ​​for wharf cap construction according to claim 8, characterized in that: Step 4 specifically includes: Step 4-1, add the reconstruction variance and reconstruction mean of all reconstruction deviations in the mobile queue to the previous reconstruction deviation group; Step 4-2, calculate the current mean and current variance by calculating the initial variance and initial mean of all previous reconstruction deviation groups, as well as the reconstruction variance and reconstruction mean of all reconstruction deviations in the mobile queue. Here, the calculation equation of the current mean is: , here, is the current mean, and are the initial mean and the reconstructed mean, and They are parameter 1 of the initial mean and parameter 2 of the reconstructed mean; The current equation for the variance is: , here, and They are the number of previous value points and the number of current value points in the mobile queue. and They are the initial variance and the reconstruction variance respectively; Step 4-3, obtain the maneuverability critical value based on the current variance and the current mean. Here, the calculation equation of the maneuverability critical value is: , here, is the critical mass of mobility, is the current mean, is the current variance, is a constant set in advance; Step 5 specifically includes: Compare the mobile critical value with the reconstruction deviation of the current numerical point. If the reconstruction deviation is higher than the mobile critical value, the current numerical point corresponding to the reconstruction deviation will be identified as an interference value, and the interference value will be removed. The current numerical point after removing the interference value is the sorted temperature data of the horizontal steel bars of the wharf foundation.

10. A device for processing detection values ​​for wharf cap construction, characterized in that: include: A temperature sensor is installed on the horizontal steel bar of the wharf cap. The temperature sensor and the LCD screen are connected to the controller. The temperature sensor is used to sample the temperature data of the horizontal steel bar of the wharf cap and transmit it to the controller. The controller is used to sort out the temperature data of the horizontal steel bar of the wharf cap, and then transmit the sorted temperature data of the horizontal steel bar of the wharf cap to the LCD screen for display. The modules running on the controller include: The past processing module is used to process the past numerical point group of the horizontal steel bars of the wharf cap using a modulation and demodulation mode, and set a starting critical value. Here, the starting critical value is a starting indicator for determining whether a numerical point is an interference value; A reconstruction module, which is used to obtain the current numerical point in the current numerical point group of the horizontal steel bars of the wharf cap and send it into the modulation and demodulation mode to perform numerical reconstruction, obtain the reconstruction deviation, and obtain the reconstruction variance and reconstruction mean according to the reconstruction deviation calculation; A queue module, which is used to use the mobile queue refresh rule to send the reconstruction deviation into the mobile queue of the pre-set capacity according to the time sequence; A maneuvering module, which is used to refresh the initial critical amount according to the reconstruction variance and reconstruction mean of all reconstruction deviations in the mobile queue to obtain the maneuvering critical amount; The sorting module is used to select the reconstruction deviation corresponding to each current value point according to the maneuvering critical amount, obtain the interference value, and sort the interference value.

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