Estimation device and method for sampling data of penetration system of barrel type foundation structure

Abstract

The invention discloses a device and a method for estimating sampled data of a penetration system of a barrel-type foundation structure, which belong to the technical field of electric digital data processing, apply a new method for executing multiple rounds of estimation on the sampled data through another foundation structure to execute potential fault danger confirmation of the barrel-type foundation structure, and can assist a maintainer to reduce the frequency of misestimation and improve the reliability of the maintenance. The task load is efficiently saved; the method comprises the following steps of: analyzing the same attribute of each bucket type basic structure, performing corresponding estimation on sampling data to obtain the approximation of the estimated values of the same sampling data in a similar operation place, and performing immediate change on the sampling sequence of the bucket type basic structure in each estimation to obtain the similarity of the estimated values of the sampling data in the similar operation place. The assisted sampling device may primarily perform detection of highly potentially dangerous infrastructures. The method effectively avoids the defects that in the prior art, misestimation and missed estimation often occur due to the fact that a potential fault danger execution estimation period in the penetration period of the barrel type foundation structure is only compared with a single critical value, wrong prompts are caused, and the task load is increased.

Description

Technical Field

[0001] The present invention belongs to the technical field of electronic digital data processing, and in particular relates to an estimation device and method for sampling data of a bucket-type foundation structure sinking system. Background Art

[0002] The barrel caisson foundation structure consists of three parts: the caisson, the barrel, and the foundation slab. The caisson is a steel cylinder with a conical lower portion and a cylindrical upper portion. The barrel is a steel cylinder or polygonal shape that can be adjusted to suit your needs. The foundation slab is a concrete structure located below the caisson and barrel, which supports the building's loads.

[0003] In actual applications, the current barrel-type foundation structure sinking system is often as mentioned in the prior art solution with patent publication number "CN117488857A", which includes a controller of the water control mechanism of the barrel-type foundation structure sinking system. The controller is connected to the display screen, deep-sea flow meter, pressure sensor, inclinometer, water pressure sensor and penetration depth measuring instrument. The deep-sea flow meter, pressure sensor, inclinometer, water pressure sensor and penetration depth measuring instrument are used to transmit the sampled data thereof to the controller. The data sampled by the deep-sea flow meter, pressure sensor, inclinometer, water pressure sensor and penetration depth measuring instrument are the sampling data of the barrel-type foundation structure sinking system. The controller is used to control the barrel-type foundation structure according to the sampling data of the barrel-type foundation structure sinking system transmitted by the sampling.

[0004] With the increase in the number of bucket-type infrastructures, the failures during the penetration of bucket-type infrastructures are also increasing. It is also necessary to estimate the potential failure risks during the penetration of bucket-type infrastructures based on the sampling data of the bucket-type infrastructure penetration system transmitted by sampling; however, when estimating the potential failure risks of bucket-type infrastructures, misestimation of the potential failure risks during the penetration of bucket-type infrastructures occurs frequently, because multiple bucket-type infrastructures are distributed, the locations of each infrastructure are different, and the external locations have some effects on the estimation of the potential failure risks during the penetration of bucket-type infrastructures, so each infrastructure will have a different abnormal critical value. If only a single critical value is used for comparison, misestimation and omission will often occur, resulting in erroneous prompts and increased workload. Summary of the Invention

[0005] In order to solve the defects in the existing technology, the present invention proposes an estimation device and method for sampling data of a bucket-type foundation structure penetration system, which effectively avoids the defects in the existing technology that the potential failure risk during the bucket-type foundation structure penetration is estimated only through a single critical value comparison, which often leads to misestimation and omission, erroneous prompts and increased workload.

[0006] The present invention utilizes the following technical solutions.

[0007] A method for estimating sampling data of a bucket foundation structure penetration system, comprising:

[0008] The deep-sea flowmeter, pressure sensor, inclinometer, water pressure sensor and penetration depth measuring instrument transmit the sampled data to the controller. The data sampled by the deep-sea flowmeter, pressure sensor, inclinometer, water pressure sensor and penetration depth measuring instrument is the sampling data of the bucket foundation structure sinking system. The controller controls and estimates the bucket foundation structure based on the sampled data of the bucket foundation structure sinking system.

[0009] The controller performs an estimation method on the bucket type foundation structure according to the sampling data of the bucket type foundation structure sinking system transmitted by sampling, comprising:

[0010] Step 1: During the penetration of the bucket-type foundation structure, sampling is performed on each bucket-type foundation structure. A database is constructed to register each sampling process for each bucket-type foundation structure, forming a sampling entry for each bucket-type foundation structure. Based on the sampling status represented by any sampling entry, a risk assessment is performed on the corresponding bucket-type foundation structure.

[0011] Step 2: Analyze the differences between each sampling item and extract the same attributes between different bucket structures. Obtain the sampling data of each same attribute related to a random bucket structure, perform re-estimation when sampling to another bucket structure, and perform real-time verification of the risk of the corresponding sampling item.

[0012] Step 3: When the sampling device samples a random bucket-type infrastructure, it extracts the calibrated risk value of another bucket-type infrastructure and obtains the most recent maintenance log stored in the other bucket-type infrastructure to obtain the expected risk value of the other bucket-type infrastructure. Based on the expected risk value of each bucket-type infrastructure, the sampling sequence in the sampling device is modified.

[0013] Step 4: For any barrel-type structure, when the sampling device performs re-sampling on it again, the real-time estimated value of the barrel-type structure is obtained, and compared with each real-time calibration estimated value; the barrel-type structure is abnormally identified based on the comparison value and a prompt is displayed on the display screen.

[0014] Preferably, Step 1 specifically includes:

[0015] Step 1-1: When controlling the sampling device to perform sampling on each bucket-type infrastructure, the coordinates of the sampling device and each bucket-type infrastructure are obtained, a sampling sequence is selected that includes all bucket-type infrastructures and is spaced from the lowest to the highest distance from the controller, and the sequence is sent to the controller to initiate sampling according to the sampling sequence;

[0016] Step 1-2: When sampling a random bucket-type infrastructure during the sampling period, the sampling data generated by the bucket-type infrastructure during the sampling process is registered and transferred to the database for storage, forming a sampling entry for the bucket-type infrastructure;

[0017] Step 1-3, divide the sampling data registered in any sampling entry into multiple types of data clusters according to the sampling source, establish a risk estimation model for each type, obtain the risk amount of each type, and add the risk amounts of all types to obtain the risk amount of the sampling entry.

[0018] Preferably, in Step 1-1, a method for obtaining a sampling sequence of distances from the controller from low to high is as follows: based on the coordinates of each bucket-type basic structure and its corresponding sampling device and the coordinates of the controller, the distances of the bucket-type basic structure coordinates and its corresponding sampling device coordinates from the controller are calculated, and the amount obtained by adding the distances of the bucket-type basic structure coordinates and its corresponding sampling device coordinates from the controller is used as the distance of the bucket-type basic structure from the controller. Then, the distances of each bucket-type basic structure from the controller are arranged in order from low to high to obtain a sampling sequence. The controller starts the sampling devices one by one to perform sampling according to the order of the sampling devices corresponding to the bucket-type basic structures corresponding to each element in the sampling sequence, thereby achieving the purpose of performing sampling according to the sampling sequence.

[0019] Preferably, Step 2 specifically includes:

[0020] Step 2-1: Select a random pair of bucket-based structure sampling entries in the database, extract the sampled data between the selected pair of sampling entries for a random class, perform a calculation on the sampled data between the pair of sampling entries for that class to obtain an approximation, set an approximation threshold, and if the obtained approximation exceeds the approximation threshold, it is defined as a primary attribute comparison for that class;

[0021] Step 2-2, perform approximate comparison on the types related to each sampling entry between a pair of bucket-type infrastructures, sum up the attribute comparison frequencies mdpn ncom of the type, and calculate the attribute frequency ratio of the type; set a frequency ratio threshold b zg , if b>b zg, the type is set as a common attribute of the pair of bucket structures, and all the common attributes of the pair of bucket structures form a common attribute group; the common attribute group between any bucket structure and each other bucket structure is extracted and stored in the external memory of the controller;

[0022] In step 2-3, when the sampling device samples a random bucket infrastructure and generates a corresponding sampling entry, the sampling entry is stored in the controller's external memory. When the sampling device samples another bucket infrastructure according to the sampling sequence, the bucket infrastructure currently being detected by the sampling device is set as the current bucket infrastructure, and the attribute groups that are identical between the bucket infrastructure and the current bucket infrastructure are extracted.

[0023] Step 2-4: The sampling device extracts sample data corresponding to the same attribute group related to the bucket-type infrastructure. Based on all the sample data extracted, the risk value of each same attribute related to the bucket-type infrastructure in the current bucket-type infrastructure is obtained. The risk value of other types of the bucket-type infrastructure outside of the same attribute is obtained. Then, the following equation is calculated:

[0024]

[0025] Here, j and k are both natural numbers and j∈(1,d), k∈(1,e), d is the number of the same attribute, e is the number of other types outside the same attribute in the bucket-based structure, (G j )' is the jth risk value of the same attribute, G k It is the k-th type of risk quantity of the bucket-type infrastructure outside the same attribute; the risk quantity G' represented by the sampling data of the bucket-type infrastructure in the instant bucket-type infrastructure is obtained by calculation, and G' is the risk quantity after instant proofreading.

[0026] Preferably, in Step 2-2, the equation for calculating the attribute frequency ratio b of the type is: b1 is the number of sampled entries in one bucket-based structure, and b2 is the number of sampled entries in another bucket-based structure.

[0027] Preferably, Step 3 specifically includes:

[0028] Step 3-1, set up the current sampling device, that is, the sampling device that is sampling the qth barrel-type basic structure, and obtain the distance between the qth barrel-type basic structure and any rth barrel-type basic structure is M qr , the penetration rate of the qth bucket foundation structure is w, and the total sampling time of the qth bucket foundation structure and the rth bucket foundation structure is U qr ;

[0029] Step 3-2: Obtain each sample entry stored in the database for the qth bucket-type infrastructure, extract the risk reduction between any pair of adjacent sample entries, obtain the time of formation of each pair of sample entries, obtain the formation time interval, calculate the time complexity of obtaining the pair of sample entries, and perform the average operation on the loss of all adjacent pairs of sample entries to obtain the time complexity μ of the qth bucket-type infrastructure. q ;

[0030] Step 3-3, obtain the risk of the r-th bucket infrastructure in the most recently formed sampling entry is G r The hazard represented by the rth bucket infrastructure in the qth bucket infrastructure is (G rq )'(Fqp)';

[0031] Step 3-4, similarly, the sampling device performs sampling on any bucket-type infrastructure, performs calculations on the expected risk amount of each other bucket-type infrastructure, and immediately changes the sampling sequence of the sampling device.

[0032] Preferably, Step 3-3 further includes:

[0033] Operate the following equation:

[0034]

[0035] Here, (U dd ) r is the time interval between the time when the record of the most recently formed sampling entry of the r-th bucket-type infrastructure is formed and the current time; the expected risk amount (G fy ) r ; Obtain the expected hazard value of each bucket-type infrastructure, select the bucket-type infrastructure corresponding to the highest expected hazard value as the target infrastructure for the next sampling of its corresponding sampling device, and change the sampling sequence of the sampling device.

[0036] Preferably, Step 4 specifically includes:

[0037] Step 4-1: Randomly select the qth bucket infrastructure. When the sampling device performs sampling on the qth bucket infrastructure again, obtain each bucket infrastructure sampled by the sampling device between two adjacent sampling entries of the qth bucket infrastructure to form a bucket infrastructure group.

[0038] Step 4-2, randomly select the v-th bucket-type infrastructure in the bucket-type infrastructure group and obtain the time complexity μ of the v-th bucket-type infrastructure. q , and the hazard represented by the qth bucket-type foundation structure in the vth bucket-type foundation structure is (Gqv )'; Total number of identical attributes N in the same attribute group between the qth bucket-type basic structure and the vth bucket-type basic structure qv The approximate amount between the qth bucket-type basic structure and the vth bucket-type basic structure is Here, N is the total number of types of arbitrary bucket-type infrastructure.

[0039] Preferably, Step 4-2 further includes:

[0040] Operate the following equation;

[0041]

[0042] Here, v1 is a natural number and v1∈(1,y), y is the number of bucket infrastructures in the bucket infrastructure group, U qv is the total sampling time of the qth bucket-based structure and the vth bucket-based structure, υ q,v1 Is the approximate amount between the qth bucket infrastructure and the v1th bucket infrastructure; the expected risk of performing detection again by the vth bucket infrastructure is obtained by calculation (G q ) dpnq ;

[0043] Step 4-3, obtain the sampling data of each type related to the qth bucket infrastructure, perform real-time estimation on the qth bucket infrastructure, and calculate the real-time danger amount of the qth bucket infrastructure to be (G q ) bd ; Establish a critical value for the risk reduction ratio if Just carry out abnormal prompt for the qth bucket-type basic structure, that is, transmit the potential fault danger prompt message of the qth bucket-type basic structure to the display screen for display.

[0044] An estimation device for sampling data of a bucket foundation structure sinking system, comprising:

[0045] a controller for the above-water control mechanism of the bucket-type foundation structure sinking system, the controller being connected to a display screen, a deep-sea flow meter, a pressure sensor, an inclinometer, a water pressure sensor, and a penetration depth measuring instrument; the deep-sea flow meter, pressure sensor, inclinometer, water pressure sensor, and penetration depth measuring instrument being used to transmit data sampled by them to the controller; the data sampled by the deep-sea flow meter, pressure sensor, inclinometer, water pressure sensor, and penetration depth measuring instrument being the sampling data of the bucket-type foundation structure sinking system; and the controller being used to control and estimate the bucket-type foundation structure based on the sampling data of the bucket-type foundation structure sinking system transmitted by the sampling;

[0046] The modules running on the controller include:

[0047] An estimation module is configured to perform sampling on each bucket-type infrastructure during its penetration, construct a database to register each sampling process for each bucket-type infrastructure, and form a sampling entry for each bucket-type infrastructure; and perform a risk estimation on the corresponding bucket-type infrastructure based on the sampling condition represented by any sampling entry;

[0048] The parsing module is used to analyze the differences between each sampling item and extract the same attributes between different bucket structures; obtain the sampling data of each same attribute related to any bucket structure, perform re-estimation when sampling to another bucket structure, and perform real-time verification of the risk of the corresponding sampling item;

[0049] a change module configured to extract the calibrated risk value of another bucket-type infrastructure when the sampling device performs sampling on any bucket-type infrastructure, obtain the most recent maintenance log stored in the other bucket-type infrastructure, and obtain the expected risk value of the other bucket-type infrastructure; and perform changes to the sampling sequence in the sampling device based on the expected risk value of each bucket-type infrastructure;

[0050] The prompt module is used to obtain the real-time estimated value of a barrel-type basic structure for a random barrel-type basic structure when the sampling device performs re-sampling on it again, and perform differential comparison with each real-time calibration estimated value; perform abnormal identification on the barrel-type basic structure based on the differential comparison value and send it to the display screen for display of prompts.

[0051] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0052] The existing method of confirming the potential failure risk of bucket-type infrastructure through single critical value comparison is eliminated, and a new method is used to confirm the potential failure risk of bucket-type infrastructure by performing multiple rounds of estimation on the sampling data through other infrastructures. This can help maintainers reduce the frequency of misestimation and effectively save the workload. By performing analysis on the same attributes between each bucket-type infrastructure and performing corresponding estimation on the sampling data, the approximation of the estimated values ​​of the same sampling data in similar operating environments is obtained. The sampling sequence of the bucket-type infrastructure is changed in real time for each estimation, which helps the sampling device to primarily detect infrastructure with high potential risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a flow chart of the method for estimating sampling data of a bucket foundation structure sinking system according to the present invention;

[0054] Figure 2 It is a partial structural diagram of the estimation device for sampling data of the bucket foundation structure penetration system described in the present invention. DETAILED DESCRIPTION

[0055] To make the purpose, technical solutions and advantages of the present invention more clear, the following will be combined with the drawings in the embodiments of the present invention to clearly and completely express the technical solutions of the present invention. The embodiments expressed in this application are only some embodiments of the present invention, not all embodiments. According to the spirit of the present invention, other embodiments obtained by those skilled in the art without making creative work shall fall within the scope of protection of the present invention.

[0056] like Figure 1 As shown, the present invention provides a method for estimating sampling data of a bucket foundation structure sinking system, comprising:

[0057] The deep-sea flow meter, pressure sensor, inclinometer, water pressure sensor and penetration depth meter transmit the data sampled by them to the controller. The data sampled by the deep-sea flow meter, pressure sensor, inclinometer, water pressure sensor and penetration depth meter are the sampling data of the bucket-type foundation structure sinking system. The controller controls and estimates the bucket-type foundation structure based on the sampling data of the bucket-type foundation structure sinking system transmitted by the sampling; the method by which the controller controls the bucket-type foundation structure based on the sampling data of the bucket-type foundation structure sinking system transmitted by the sampling may be the corresponding control method mentioned in the prior art solution with patent publication number "CN117488857A".

[0058] The controller performs a method for estimating the bucket-type foundation structure based on the bucket-type foundation structure sinking system sampling data transmitted by sampling, and the method runs on the controller, including:

[0059] Step 1: During the penetration of the bucket-type foundation structure, sampling is performed on each bucket-type foundation structure. A database is constructed to register each sampling process for each bucket-type foundation structure, forming a sampling entry for each bucket-type foundation structure. Based on the sampling status represented by any sampling entry, a risk assessment is performed on the corresponding bucket-type foundation structure.

[0060] In a preferred but non-limiting embodiment of the present invention, Step 1 specifically comprises:

[0061] Step 1-1: When controlling the sampling device to perform sampling on each bucket-type infrastructure, the coordinates of the sampling device and each bucket-type infrastructure are obtained, a sampling sequence is selected that includes all bucket-type infrastructures and is spaced from the lowest to the highest distance from the controller, and the sequence is sent to the controller to initiate sampling according to the sampling sequence;

[0062] The sampling device includes a deep-sea flowmeter, a pressure sensor, an inclinometer, a water pressure sensor, and a penetration depth meter. One sampling device corresponds to one bucket-type foundation structure. The coordinates of the controller, the sampling device, and the bucket-type foundation structure can all be obtained via a GPS module mounted thereon. In a preferred but non-limiting embodiment of the present invention, in Step 1-1, a method for obtaining a sampling sequence of distances from the controller from low to high is as follows: based on the coordinates of each bucket-type foundation structure and its corresponding sampling device, combined with the coordinates of the controller, the distances of the bucket-type foundation structure coordinates and their corresponding sampling device coordinates from the controller are calculated, and the sum of the distances from the bucket-type foundation structure coordinates and their corresponding sampling device coordinates to the controller is used as the distance from the bucket-type foundation structure to the controller. Subsequently, the distances from each bucket-type foundation structure to the controller are arranged in order from low to high to obtain a sampling sequence. The controller then activates the sampling devices one by one to perform sampling according to the order of the sampling devices corresponding to the bucket-type foundation structures in the sampling sequence, thereby achieving the purpose of performing sampling according to the sampling sequence.

[0063] Step 1-2: When sampling a random bucket-type infrastructure during the sampling period, the sampling data generated by the bucket-type infrastructure during the sampling process is registered and transferred to the database for storage, forming a sampling entry for the bucket-type infrastructure;

[0064] Steps 1-3 divide the sampled data registered in any sampling entry into multiple data clusters based on the sampling source. A risk estimation model is established for each cluster, and the risk value for each cluster is calculated. The risk values ​​for all clusters are then summed to obtain the risk value for the sampling entry. Deep-sea flowmeters, pressure sensors, inclinometers, water pressure sensors, and penetration depth meters are five different sampling sources.

[0065] Step 2: Analyze the differences between each sampling item and extract the same attributes between different bucket structures. Obtain the sampling data of each same attribute related to a random bucket structure, perform re-estimation when sampling to another bucket structure, and perform real-time verification of the risk of the corresponding sampling item.

[0066] In a preferred but non-limiting embodiment of the present invention, Step 2 specifically comprises:

[0067] Step 2-1, select a random pair of bucket-based structure sampling items in the database, extract the sampling data between the selected pair of sampling items for a random category, perform calculations on the sampling data between the pair of sampling items for the category to obtain an approximation, set an approximation threshold, and if the obtained approximation is higher than the approximation threshold, it is defined as a primary attribute comparison of the category; the approximation can be a Pearson coefficient.

[0068] Step 2-2, perform approximate comparison on the types related to each sampling entry between a pair of bucket-type infrastructures, sum up the attribute comparison frequencies mdpn ncom of the type, and calculate the attribute frequency ratio of the type; set a frequency ratio threshold b zg , if b>b zg , the type is set as a common attribute of the pair of bucket structures, and all the common attributes of the pair of bucket structures form a common attribute group; the common attribute group between any bucket structure and each other bucket structure is extracted and stored in the external memory of the controller;

[0069] In a preferred but non-limiting embodiment of the present invention, in Step 2-2, the equation for calculating the attribute frequency ratio b of the type is: b1 is the number of sampled entries in one bucket-based structure, and b2 is the number of sampled entries in another bucket-based structure.

[0070] In step 2-3, when the sampling device samples a random bucket infrastructure and generates a corresponding sampling entry, the sampling entry is stored in the controller's external memory. When the sampling device samples another bucket infrastructure according to the sampling sequence, the bucket infrastructure currently being detected by the sampling device is set as the current bucket infrastructure, and the attribute groups that are identical between the bucket infrastructure and the current bucket infrastructure are extracted.

[0071] Step 2-4: The sampling device extracts sample data corresponding to the same attribute group associated with the bucket-type infrastructure. Based on the total sample data, the risk value of each attribute associated with the bucket-type infrastructure in the current bucket-type infrastructure is obtained. The risk value of other types of bucket-type infrastructure outside of the same attribute is also obtained. This risk value can be calculated using the LS method. Then, the following equation is calculated:

[0072]

[0073] Here, j and k are both natural numbers and j∈(1,d), k∈(1,e), d is the number of the same attribute, e is the number of other types outside the same attribute in the bucket-based structure, (G j )' is the jth risk value of the same attribute, G k It is the k-th type of risk quantity of the bucket-type infrastructure outside the same attribute; the risk quantity G' represented by the sampling data of the bucket-type infrastructure in the instant bucket-type infrastructure is obtained by calculation, and G' is the risk quantity after instant proofreading.

[0074] Step 3: When the sampling device samples a random bucket-type infrastructure, it extracts the calibrated risk value of another bucket-type infrastructure and obtains the most recent maintenance log stored in the other bucket-type infrastructure to obtain the expected risk value of the other bucket-type infrastructure. Based on the expected risk value of each bucket-type infrastructure, the sampling sequence in the sampling device is modified.

[0075] In a preferred but non-limiting embodiment of the present invention, Step 3 specifically comprises:

[0076] Step 3-1, set up the current sampling device, that is, the sampling device that is sampling the qth barrel-type basic structure, and obtain the distance between the qth barrel-type basic structure and any rth barrel-type basic structure is M qr , the penetration rate of the qth bucket foundation structure is w, and the total sampling time of the qth bucket foundation structure and the rth bucket foundation structure is U qr ;

[0077] Step 3-2: Obtain each sample entry stored in the database for the qth bucket-type infrastructure, extract the risk reduction between any pair of adjacent sample entries (the risk reduction can be the L2 norm), obtain the entry formation time of each pair of sample entries, obtain the formation time interval (the time interval is the absolute value of the amount obtained by subtracting the entry formation time of the pair of sample entries), calculate the time complexity of obtaining the pair of sample entries, and perform the average operation on the losses of all adjacent pairs of sample entries to obtain the time complexity μ of the qth bucket-type infrastructure. q ;

[0078] Step 3-3, obtain the risk of the r-th bucket infrastructure in the most recently formed sampling entry is G r The hazard represented by the rth bucket infrastructure in the qth bucket infrastructure is (G rq )'(Fqp)';

[0079] In a preferred but non-limiting embodiment of the present invention, Step 3-3 further comprises:

[0080] Operate the following equation:

[0081]

[0082] Here, (U dd ) r is the time interval between the time when the record of the most recently formed sampling entry of the r-th bucket-type infrastructure is formed and the current time; the expected risk amount (G fy ) r; Obtain the expected hazard value of each bucket-type infrastructure, select the bucket-type infrastructure corresponding to the highest expected hazard value as the target infrastructure for the next sampling of its corresponding sampling device, and change the sampling sequence of the sampling device.

[0083] Just as the risk of establishing a bucket infrastructure in the most recent sampling entry is ten, and the risk represented in another bucket infrastructure is twelve, the time complexity of establishing another bucket infrastructure is one tenth, and the total sampling time of the two bucket infrastructures is one hour, the time interval between the formation of the bucket infrastructure is nine hours, so the expected risk of the bucket infrastructure obtained by calculation is

[0084] Step 3-4, similarly, the sampling device performs sampling on any bucket-type infrastructure, performs calculations on the expected risk amount of each other bucket-type infrastructure, and immediately changes the sampling sequence of the sampling device.

[0085] Step 4: For any barrel-type structure, when the sampling device performs re-sampling on it again, the real-time estimated value of the barrel-type structure is obtained, and compared with each real-time calibration estimated value; the barrel-type structure is abnormally identified based on the comparison value and a prompt is displayed on the display screen.

[0086] In a preferred but non-limiting embodiment of the present invention, Step 4 specifically comprises:

[0087] Step 4-1: Randomly select the qth bucket infrastructure. When the sampling device performs sampling on the qth bucket infrastructure again, obtain each bucket infrastructure sampled by the sampling device between two adjacent sampling entries of the qth bucket infrastructure to form a bucket infrastructure group.

[0088] Step 4-2, randomly select the v-th bucket-type infrastructure in the bucket-type infrastructure group and obtain the time complexity μ of the v-th bucket-type infrastructure. q , and the hazard represented by the qth bucket-type foundation structure in the vth bucket-type foundation structure is (G qv )'; Total number of identical attributes N in the same attribute group between the qth bucket-type basic structure and the vth bucket-type basic structure qv The approximate amount between the qth bucket-type basic structure and the vth bucket-type basic structure is Here, N is the total number of types of arbitrary bucket-type infrastructure.

[0089] In a preferred but non-limiting embodiment of the present invention, Step 4-2 further comprises:

[0090] Operate the following equation;

[0091]

[0092] Here, v1 is a natural number and v1∈(1,y), y is the number of bucket infrastructures in the bucket infrastructure group, U qv is the total sampling time of the qth bucket-based structure and the vth bucket-based structure, υ q,v1 Is the approximate amount between the qth bucket infrastructure and the v1th bucket infrastructure; the expected risk of performing detection again by the vth bucket infrastructure is obtained by calculation (G q ) dpnq ;

[0093] Step 4-3, obtain the sampling data of each type related to the qth bucket infrastructure, perform real-time estimation on the qth bucket infrastructure, and calculate the real-time danger amount of the qth bucket infrastructure to be (G q ) bd ; Establish a critical value for the risk reduction ratio if An abnormal prompt is executed for the qth bucket-type infrastructure, that is, a potential fault danger prompt message of the qth bucket-type infrastructure is transmitted to the display screen for display, thereby prompting the maintainer that the qth bucket-type infrastructure has a potential fault danger and needs maintenance.

[0094] like Figure 2 As shown, the present invention provides an estimation device for sampling data of a bucket foundation structure sinking system, comprising:

[0095] a controller for the above-water control mechanism of the bucket-type foundation structure sinking system, the controller being connected to a display screen, a deep-sea flow meter, a pressure sensor, an inclinometer, a water pressure sensor, and a penetration depth measuring instrument; the deep-sea flow meter, pressure sensor, inclinometer, water pressure sensor, and penetration depth measuring instrument being used to transmit data sampled by them to the controller; the data sampled by the deep-sea flow meter, pressure sensor, inclinometer, water pressure sensor, and penetration depth measuring instrument being the sampling data of the bucket-type foundation structure sinking system; and the controller being used to control and estimate the bucket-type foundation structure based on the sampling data of the bucket-type foundation structure sinking system transmitted by the sampling;

[0096] The modules running on the controller include:

[0097] An estimation module is configured to perform sampling on each bucket-type infrastructure during its penetration, construct a database to register each sampling process for each bucket-type infrastructure, and form a sampling entry for each bucket-type infrastructure; and perform a risk estimation on the corresponding bucket-type infrastructure based on the sampling condition represented by any sampling entry;

[0098] The parsing module is used to analyze the differences between each sampling item and extract the same attributes between different bucket structures; obtain the sampling data of each same attribute related to any bucket structure, perform re-estimation when sampling to another bucket structure, and perform real-time verification of the risk of the corresponding sampling item;

[0099] a change module configured to extract the calibrated risk value of another bucket-type infrastructure when the sampling device performs sampling on any bucket-type infrastructure, obtain the most recent maintenance log stored in the other bucket-type infrastructure, and obtain the expected risk value of the other bucket-type infrastructure; and perform changes to the sampling sequence in the sampling device based on the expected risk value of each bucket-type infrastructure;

[0100] The prompt module is used to obtain the real-time estimated value of a barrel-type basic structure for a random barrel-type basic structure when the sampling device performs re-sampling on it again, and perform differential comparison with each real-time calibration estimated value; perform abnormal identification on the barrel-type basic structure based on the differential comparison value and send it to the display screen for display of prompts.

[0101] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0102] The existing method of confirming the potential failure risk of bucket-type infrastructure through single critical value comparison is eliminated, and a new method is used to confirm the potential failure risk of bucket-type infrastructure by performing multiple rounds of estimation on the sampling data through other infrastructures. This can help maintainers reduce the frequency of misestimation and effectively save the workload. By performing analysis on the same attributes between each bucket-type infrastructure and performing corresponding estimation on the sampling data, the approximation of the estimated values ​​of the same sampling data in similar operating environments is obtained. The sampling sequence of the bucket-type infrastructure is changed in real time for each estimation, which helps the sampling device to primarily detect infrastructure with high potential risks.

[0103] 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 with 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 scope of protection of the claims of the present invention.

Claims

1. A method for estimating sampling data of a bucket foundation structure penetration system, characterized in that: include: The deep-sea flowmeter, pressure sensor, inclinometer, water pressure sensor and penetration depth measuring instrument transmit the sampled data to the controller. The data sampled by the deep-sea flowmeter, pressure sensor, inclinometer, water pressure sensor and penetration depth measuring instrument is the sampling data of the bucket foundation structure sinking system. The controller controls and estimates the bucket foundation structure based on the sampled data of the bucket foundation structure sinking system. The controller performs an estimation method on the bucket type foundation structure according to the sampling data of the bucket type foundation structure sinking system transmitted by sampling, comprising: Step 1: During the penetration of the bucket-type foundation structure, sampling is performed on each bucket-type foundation structure. A database is constructed to register each sampling process for each bucket-type foundation structure, forming a sampling entry for each bucket-type foundation structure. Based on the sampling status represented by any sampling entry, a risk assessment is performed on the corresponding bucket-type foundation structure. Step 2: Analyze the differences between each sampling item and extract the same attributes between different bucket structures. Obtain the sampling data of each same attribute related to a random bucket structure, perform re-estimation when sampling to another bucket structure, and perform real-time verification of the risk of the corresponding sampling item. Step 3: When the sampling device samples a random bucket-type infrastructure, it extracts the calibrated risk value of another bucket-type infrastructure and obtains the most recent maintenance log stored in the other bucket-type infrastructure to obtain the expected risk value of the other bucket-type infrastructure. Based on the expected risk value of each bucket-type infrastructure, the sampling sequence in the sampling device is modified. Step 4: For any barrel-type structure, when the sampling device performs re-sampling on it again, the real-time estimated value of the barrel-type structure is obtained, and compared with each real-time calibration estimated value; the barrel-type structure is abnormally identified based on the comparison value and a prompt is displayed on the display screen.

2. The method for estimating sampling data of a bucket foundation structure penetration system according to claim 1, characterized in that: Step 1 specifically includes: Step 1-1: When controlling the sampling device to perform sampling on each bucket-type infrastructure, the coordinates of the sampling device and each bucket-type infrastructure are obtained, a sampling sequence is selected that includes all bucket-type infrastructures and is spaced from the lowest to the highest distance from the controller, and the sequence is sent to the controller to initiate sampling according to the sampling sequence; Step 1-2: When sampling a random bucket-type infrastructure during the sampling period, the sampling data generated by the bucket-type infrastructure during the sampling process is registered and transferred to the database for storage, forming a sampling entry for the bucket-type infrastructure; Step 1-3, divide the sampling data registered in any sampling entry into multiple types of data clusters according to the sampling source, establish a risk estimation model for each type, obtain the risk amount of each type, and add the risk amounts of all types to obtain the risk amount of the sampling entry.

3. The method for estimating sampling data of a bucket foundation structure penetration system according to claim 2, characterized in that: In Step 1-1, a method for obtaining a sampling sequence of distances from the controller from low to high is as follows: based on the coordinates of each bucket-type basic structure and its corresponding sampling device and the coordinates of the controller, the distances of the bucket-type basic structure coordinates and its corresponding sampling device coordinates from the controller are calculated, and the amount obtained by adding the distances of the bucket-type basic structure coordinates and its corresponding sampling device coordinates from the controller is used as the distance of the bucket-type basic structure from the controller. Then, the distances of each bucket-type basic structure from the controller are arranged in order from low to high to obtain a sampling sequence. The controller starts the sampling devices one by one to perform sampling according to the order of the sampling devices corresponding to the bucket-type basic structures corresponding to each element in the sampling sequence, thereby achieving the purpose of performing sampling according to the sampling sequence.

4. The method for estimating sampling data of a bucket foundation structure sinking system according to claim 3, characterized in that: Step 2 specifically includes: Step 2-1: Select a random pair of bucket-based structure sampling entries in the database, extract the sampled data between the selected pair of sampling entries for a random class, perform a calculation on the sampled data between the pair of sampling entries for that class to obtain an approximation, set an approximation threshold, and if the obtained approximation exceeds the approximation threshold, it is defined as a primary attribute comparison for that class; Step 2-2, perform approximate comparison on the types related to each sampling entry between a pair of bucket-type infrastructures, sum up the attribute comparison frequencies mdpn ncom of the type, and calculate the attribute frequency ratio of the type; set a frequency ratio threshold b zg , if b>b zg , the type is set as a common attribute of the pair of bucket structures, and all the common attributes of the pair of bucket structures form a common attribute group; the common attribute group between any bucket structure and each other bucket structure is extracted and stored in the external memory of the controller; In step 2-3, when the sampling device samples a random bucket infrastructure and generates a corresponding sampling entry, the sampling entry is stored in the controller's external memory. When the sampling device samples another bucket infrastructure according to the sampling sequence, the bucket infrastructure currently being detected by the sampling device is set as the current bucket infrastructure, and the attribute groups that are identical between the bucket infrastructure and the current bucket infrastructure are extracted. Step 2-4: The sampling device extracts sample data corresponding to the same attribute group related to the bucket-type infrastructure. Based on all the sample data extracted, the risk value of each same attribute related to the bucket-type infrastructure in the current bucket-type infrastructure is obtained. The risk value of other types of the bucket-type infrastructure outside of the same attribute is obtained. Then, the following equation is calculated: Here, j and k are both natural numbers and j∈(1,d), k∈(1,e), d is the number of the same attribute, e is the number of other types outside the same attribute in the bucket-based structure, (G j )' is the jth risk value of the same attribute, G k It is the k-th type of risk quantity of the bucket-type infrastructure outside the same attribute; the risk quantity G′ represented by the sampling data of the bucket-type infrastructure in the instant bucket-type infrastructure is obtained by calculation, and G′ is the risk quantity after instant correction.

5. The method for estimating sampling data of a bucket foundation structure penetration system according to claim 4, characterized in that: In Step 2-2, the equation for calculating the attribute frequency ratio b of this type is: b1 is the number of sampled entries in one bucket-based structure, and b2 is the number of sampled entries in another bucket-based structure.

6. The method for estimating sampling data of a bucket foundation structure penetration system according to claim 5, characterized in that: Step 3 specifically includes: Step 3-1, set up the current sampling device, that is, the sampling device that is sampling the qth barrel-type basic structure, and obtain the distance between the qth barrel-type basic structure and any rth barrel-type basic structure is M qr , the penetration rate of the qth bucket foundation structure is w, and the total sampling time of the qth bucket foundation structure and the rth bucket foundation structure is U qr ; Step 3-2: Obtain each sample entry stored in the database for the qth bucket-type infrastructure, extract the risk reduction between any pair of adjacent sample entries, obtain the time of formation of each pair of sample entries, obtain the formation time interval, calculate the time complexity of obtaining the pair of sample entries, and perform the average operation on the loss of all adjacent pairs of sample entries to obtain the time complexity μ of the qth bucket-type infrastructure. q ; Step 3-3, obtain the risk of the r-th bucket infrastructure in the most recently formed sampling entry is G r The hazard represented by the rth bucket infrastructure in the qth bucket infrastructure is (G rq )'(Fqp)'; Step 3-4, similarly, the sampling device performs sampling on any bucket-type infrastructure, performs calculations on the expected risk amount of each other bucket-type infrastructure, and immediately changes the sampling sequence of the sampling device.

7. The method for estimating sampling data of a bucket foundation structure penetration system according to claim 6, characterized in that: Step 3-3 also includes: Operate the following equation: Here, (U dd ) r is the time interval between the time when the record of the most recently formed sampling entry of the r-th bucket-type infrastructure is formed and the current time; the expected risk amount (G fy ) r ; Obtain the expected hazard value of each bucket-type infrastructure, select the bucket-type infrastructure corresponding to the highest expected hazard value as the target infrastructure for the next sampling of its corresponding sampling device, and change the sampling sequence of the sampling device.

8. The method for estimating sampling data of a bucket foundation structure penetration system according to claim 7, characterized in that: Step 4 specifically includes: Step 4-1: Randomly select the qth bucket infrastructure. When the sampling device performs sampling on the qth bucket infrastructure again, obtain each bucket infrastructure sampled by the sampling device between two adjacent sampling entries of the qth bucket infrastructure to form a bucket infrastructure group. Step 4-2, randomly select the v-th bucket-type infrastructure in the bucket-type infrastructure group and obtain the time complexity μ of the v-th bucket-type infrastructure. q , and the hazard represented by the qth bucket-type foundation structure in the vth bucket-type foundation structure is (G qv )'; Total number of identical attributes N in the same attribute group between the qth bucket-type basic structure and the vth bucket-type basic structure qv The approximate amount between the qth bucket-type basic structure and the vth bucket-type basic structure is Here, N is the total number of types of any bucket-type infrastructure; Step 4-3, obtain the sampling data of each type related to the qth bucket infrastructure, perform real-time estimation on the qth bucket infrastructure, and calculate the real-time danger amount of the qth bucket infrastructure to be (G q ) bd ; Establish a critical value for the risk reduction ratio if Just carry out abnormal prompt for the qth bucket-type basic structure, that is, transmit the potential fault danger prompt message of the qth bucket-type basic structure to the display screen for display.

9. The method for estimating sampling data of a bucket foundation structure penetration system according to claim 8, characterized in that: Step 4-2 also includes: Operate the following equation; Here, v1 is a natural number and v1∈(1,y), y is the number of bucket infrastructures in the bucket infrastructure group, U qv is the total sampling time of the qth bucket-based structure and the vth bucket-based structure, υ q,v1 Is the approximate amount between the qth bucket infrastructure and the v1th bucket infrastructure; the expected risk of performing detection again by the vth bucket infrastructure is obtained by calculation (G q ) dpnq .

10. An estimation device for sampling data of a bucket foundation structure sinking system, characterized in that: include: a controller for the above-water control mechanism of the bucket-type foundation structure sinking system, the controller being connected to a display screen, a deep-sea flow meter, a pressure sensor, an inclinometer, a water pressure sensor, and a penetration depth measuring instrument; the deep-sea flow meter, pressure sensor, inclinometer, water pressure sensor, and penetration depth measuring instrument being used to transmit data sampled by them to the controller; the data sampled by the deep-sea flow meter, pressure sensor, inclinometer, water pressure sensor, and penetration depth measuring instrument being the sampling data of the bucket-type foundation structure sinking system; and the controller being used to control and estimate the bucket-type foundation structure based on the sampling data of the bucket-type foundation structure sinking system transmitted by the sampling; The modules running on the controller include: An estimation module is configured to perform sampling on each bucket-type infrastructure during its penetration, construct a database to register each sampling process for each bucket-type infrastructure, and form a sampling entry for each bucket-type infrastructure; and perform a risk estimation on the corresponding bucket-type infrastructure based on the sampling condition represented by any sampling entry; The parsing module is used to analyze the differences between each sampling item and extract the same attributes between different bucket structures; obtain the sampling data of each same attribute related to any bucket structure, perform re-estimation when sampling to another bucket structure, and perform real-time verification of the risk of the corresponding sampling item; a change module configured to extract the calibrated risk value of another bucket-type infrastructure when the sampling device performs sampling on any bucket-type infrastructure, obtain the most recent maintenance log stored in the other bucket-type infrastructure, and obtain the expected risk value of the other bucket-type infrastructure; and perform changes to the sampling sequence in the sampling device based on the expected risk value of each bucket-type infrastructure; The prompt module is used to obtain the real-time estimated value of a barrel-type basic structure for a random barrel-type basic structure when the sampling device performs re-sampling on it again, and perform differential comparison with each real-time calibration estimated value; perform abnormal identification on the barrel-type basic structure based on the differential comparison value and send it to the display screen for display of prompts.

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