Measurement data processing platform and method based on semi-submersible barge launching control

Abstract

A measured data processing platform and method based on semi-submersible barge launching control belong to the technical field of electrical digital data processing, and are characterized in that analysis is executed during the submerging period of a semi-submersible barge, so that whether the submerging period of the semi-submersible barge is reasonable or not is mastered, that is, time abnormal hidden danger estimation analysis during the submerging period is executed on submerging data, and the submerging data are analyzed to determine whether the submerging period of the semi-submersible barge is reasonable or not. Whether the diving of the semi-submersible barge is reasonable or not can be directly mastered, and emphasized management and control can be performed according to the obtained result, so that the diving knowability and stability of the semi-submersible barge are improved; the obtained result is analyzed through the power mechanism and the assisting device, so that whether the abnormal submergence of the semi-submersible barge is caused by the abnormal submergence of the power mechanism and the assisting device or not can be determined, and the power mechanism or the assisting device can be managed and controlled with emphasis according to the obtained result; the stability and the reliability of the power mechanism in the diving process are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric digital data processing, and particularly relates to a measurement data processing platform and method based on semi-submersible barge launching control. Background Art

[0002] A semi-submersible barge (also known as a semi-submersible barge or semi-submersible mother ship) is a special ship that adjusts its own ballast water to submerge the loading deck to carry large floating goods (such as drilling platforms, ships, caissons, etc.). Its core feature is the combination of stability and shallow draft, suitable for offshore engineering transportation and installation operations.

[0003] In practical applications, currently during the launching of a semi-submersible barge, as mentioned in the existing technical solution with the patent publication number "CN105882905B‌", it controls the semi-submersible barge by sampling some data during the launching of the semi-submersible barge.

[0004] However, currently, it is not possible to perform an overall health condition detection on the submerging process of the semi-submersible barge, and it is not possible to know in real time whether the submerging process of the semi-submersible barge is reasonable. Thus, it is not suitable to perform focused management and control on the semi-submersible barge in real time, which weakens the knowability of the submerging of the semi-submersible barge. Moreover, it is not possible to perform focused disturbance estimation on the power mechanism and auxiliary devices of the semi-submersible barge, so it is not possible to accurately determine whether the abnormal submerging of the semi-submersible barge is caused by abnormalities in the power mechanism and auxiliary devices, and thus it is not possible to perform focused allocation on the power mechanism and auxiliary devices in real time. Summary of the Invention

[0005] To solve the deficiencies in the existing technology, the present invention proposes a measurement data processing platform and method based on semi-submersible barge launching control, effectively avoiding the deficiencies in the existing technology that it is not possible to know in real time whether the submerging process of the semi-submersible barge is reasonable, not suitable to perform focused management and control on the semi-submersible barge in real time, weakening the knowability of the submerging of the semi-submersible barge, and not being able to perform focused disturbance estimation on the power mechanism and auxiliary devices of the semi-submersible barge, not being able to accurately determine whether the abnormal submerging of the semi-submersible barge is caused by abnormalities in the power mechanism and auxiliary devices, and not being able to perform focused allocation on the power mechanism and auxiliary devices in real time.

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

[0007] A measurement data processing method based on semi-submersible barge launching control, comprising:

[0008] S1, sampling submerging data during the submerging of the semi-submersible barge, and performing an estimation and analysis of the period anomaly risk during the submerging on the submerging data, and performing a confirmation process on the obtained submerging period offset to obtain reasonable information or abnormal information;

[0009] S2. Under the condition of abnormal information, sample the diving status data and diving disturbance data of the sampling power mechanism, send the diving disturbance data to S4 for performing work correction estimation segmentation response analysis, and perform period power mechanism diving anomaly estimation processing on the diving status data;

[0010] S3. According to the diving anomaly disturbance factor obtained by performing period power mechanism diving anomaly estimation processing, perform confirmation processing on the obtained diving anomaly disturbance factor, so as to obtain qualified information or diving disturbance information;

[0011] S4. According to the method of data recursion, perform work correction estimation segmentation response analysis on the diving disturbance data, and send the obtained reasonable work disturbance weight and abnormal work disturbance weight back to S3;

[0012] S5. Under the condition of abnormal information, perform external diving disturbance estimation function segmentation analysis on the assisted diving aspect by the semi-submersible barge, perform confirmation processing on the obtained assisted diving evaluation factor, and thus obtain stable information or function information.

[0013] Furthermore, in S1, the period anomaly risk estimation analysis method during diving includes:

[0014] Define the total diving period of the semi-submersible barge as the working time interval, obtain the diving data of the semi-submersible barge during the working time interval, and obtain the basic diving data of the semi-submersible barge with reasonable diving;

[0015] Obtain the state function data of the semi-submersible barge during the working time interval, and define the number of state function data exceeding the defined critical value as the working function factor, and then obtain the offset calibration factor corresponding to the working function factor within the defined working function factor range.

[0016] Furthermore, in S1, each defined working function factor range corresponds to an offset calibration factor.

[0017] Furthermore, in S1, obtain the quantity obtained by performing standardized processing on each type of corresponding data in the diving data during the working time interval by using the Z-score method, and define the quantity obtained by multiplying the quantity obtained after the standardized processing by the offset calibration factor value as the calibrated diving data, compare the calibrated diving data with the basic diving data, that is, define the quantity obtained by subtracting the basic diving data from the calibrated diving data as the diving period offset , and perform confirmation processing on the diving period offset :

[0018] If the diving period offset is all lower than the defined diving period offset critical value, a qualified message is formed;

[0019] If the diving period offset is not lower than the defined diving period offset threshold value, an abnormal message is formed.

[0020] Furthermore, in S2 to S3, the method for estimating and disposing of abnormal diving of the period power mechanism includes:

[0021] Define the number of power mechanisms in the semi-submersible barge as , where is a positive integer, obtain the diving status data of each power mechanism in the semi-submersible barge during the working time interval. The diving status data includes a state estimation factor and an attribute presentation factor. Define the quantity obtained by multiplying the state estimation factor by the attribute presentation factor as the power mechanism estimation factor, and obtain the corresponding reasonable working disturbance weight value and the abnormal working disturbance weight value ;

[0022] Obtain the quantity obtained by multiplying the power mechanism estimation factor of each power mechanism by the corresponding reasonable working disturbance weight value or the abnormal working disturbance weight value and define it as the diving obstacle estimation factor. And perform a confirmation disposal on the diving obstacle estimation factor , and perform the following confirmation disposal:

[0023] If the diving obstacle estimation factor is not lower than the defined diving obstacle estimation factor threshold value, it is determined that the corresponding power mechanism is a disturbed power mechanism. Divide the corresponding number of the disturbed power mechanism by and define the quotient value as the diving abnormal disturbance factor. And perform a confirmation disposal on the diving abnormal disturbance factor:

[0024] If the diving abnormal disturbance factor is lower than the defined diving abnormal disturbance factor threshold value, a compliance message is formed;

[0025] If the diving abnormal disturbance factor is not lower than the defined diving abnormal disturbance factor threshold value, a diving disturbance message is formed.

[0026] Furthermore, in S4, the method for parsing the response of the work correction estimation segmentation includes:

[0027] Obtain the diving disturbance data of each power mechanism in the semi-submersible barge during the working time interval. The diving disturbance data includes an internal loss estimation factor and an obstacle evaluation value;

[0028] Compare the internal damage estimation factor and the obstacle evaluation value with the defined critical value of the internal damage estimation factor and the defined critical value of the obstacle evaluation value respectively. Define the quantity obtained by adding the numbers of the internal damage estimation factor and the obstacle evaluation value that are respectively higher than the defined critical value of the internal damage estimation factor and the defined critical value of the obstacle evaluation value as the estimation risk factor. If the estimation risk factor is 0, it is determined that the corresponding power mechanism is a reasonable power mechanism. If the estimation risk factor is non-zero, it is determined that the corresponding power mechanism is a disturbance power mechanism.

[0029] Further, in S4, define the quantity obtained by multiplying the internal damage estimation factor of the reasonable power mechanism by the obstacle evaluation value as the reasonable operation estimation factor, and obtain the number of the reasonable operation estimation factors of the reasonable power mechanism within the defined range of the reasonable operation estimation factor as the reasonable working disturbance weight , define the quantity obtained by multiplying the internal damage estimation factor of the abnormal power mechanism by the obstacle evaluation value as the abnormal operation estimation factor, and obtain the abnormal working disturbance weight of the abnormal operation estimation factor of the disturbance power mechanism within the defined range of the abnormal operation estimation factor , where and are both positive integers.

[0030] Further, in S5, the external diving disturbance estimation effect segmentation analysis method includes:

[0031] Obtain the assisting device of the semi-submersible barge during the working time interval, obtain the external diving disturbance data of each assisting device, and perform confirmation processing on the external diving disturbance data. If the external diving disturbance data is not less than the defined critical value of the external diving disturbance data, it is determined that the corresponding assisting device is a diving disturbance device.

[0032] Further, in S5, define the quantity obtained by dividing the number of the diving disturbance devices by the total number of the assisting devices as the assisting diving estimation factor, and perform confirmation processing on the assisting diving estimation factor:

[0033] If the assisting diving estimation factor is lower than the defined critical value of the assisting diving estimation factor, a stable message is formed;

[0034] If the assisting diving estimation factor is not less than the defined critical value of the assisting diving estimation factor, an effect message is formed.

[0035] A measurement data processing platform based on semi-submersible barge launching control, including:

[0036] An estimation module, which is used to sample diving data during the diving of the semi-submersible barge, and perform analysis on the abnormal hidden danger of the period during the diving on the diving data, and perform confirmation processing on the obtained diving period offset to obtain a reasonable message or an abnormal message;

[0037] A response module, which is used to sample the diving condition data and diving disturbance data of the power mechanism under the condition of abnormal messages, send the diving disturbance data into S4 to perform work correction estimation segmentation response analysis, and perform abnormal estimation processing of the power mechanism during the period for the diving condition data;

[0038] A confirmation module, which is used to perform confirmation processing on the obtained diving abnormal disturbance factor according to the diving abnormal disturbance factor obtained by the abnormal estimation processing of the power mechanism during the period, so as to obtain a qualified message or a diving disturbance message;

[0039] An analysis module, which is used to perform work correction estimation segmentation response analysis on the diving disturbance data according to the method of data recursion, and send the obtained reasonable work disturbance weight and abnormal work disturbance weight back to S3;

[0040] A processing module, which is used to perform external diving disturbance estimation function segmentation analysis on the assisted diving aspect with the help of a semi-submersible barge under the condition of abnormal messages, perform confirmation processing on the obtained assisted diving evaluation factor, and thus obtain a stable message or a function message.

[0041] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0042] By performing analysis during the diving of the semi-submersible barge, it is possible to grasp whether the diving during the diving of the semi-submersible barge is reasonable, that is, to perform abnormal hidden danger estimation analysis of the period during the diving on the diving data, which is conducive to directly grasping whether the diving of the semi-submersible barge is reasonable, and is conducive to making focused control according to the obtained results, thereby improving the knowability and stability of the diving of the semi-submersible barge; and by performing analysis on the obtained results from both the power mechanism and the assisting device, it is conducive to confirming whether the abnormal diving of the semi-submersible barge is caused by the abnormality of the power mechanism and the assisting device, and is conducive to performing focused control on the power mechanism or the assisting device according to the obtained results to improve the stability and reliability of the diving process of the power mechanism. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 is a flowchart of the measurement data processing method based on the semi-submersible barge launching control described in the present invention;

[0044] Figure 2 is a partial structure diagram of the measurement data processing platform based on the semi-submersible barge launching control described in the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0045] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will, in conjunction with the accompanying drawings in the embodiments of the present invention, clearly and completely describe the technical solutions of the present invention. The embodiments described in this application are only partial embodiments of the present invention, rather than all embodiments. According to the spirit of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0046] As Figure 1 shown, a method for processing measurement data based on semi-submersible barge launching control according to the present invention includes:

[0047] S1, sampling the diving data during the diving of the semi-submersible barge, and performing an estimation and analysis of the abnormal hidden dangers during the diving period on the diving data, and performing a confirmation process on the obtained diving period offset to obtain reasonable information or abnormal information;

[0048] S2, under the condition of abnormal information, sampling the diving condition data and diving disturbance data of the power mechanism, sending the diving disturbance data to S4 for a working correction estimation segmentation response analysis, and performing a period power mechanism diving abnormality estimation process on the diving condition data;

[0049] S3, performing a confirmation process on the obtained diving abnormal disturbance factor according to the diving abnormal disturbance factor obtained from the period power mechanism diving abnormality estimation process to obtain a qualified message or a diving disturbance message;

[0050] S4, performing a working correction estimation segmentation response analysis on the diving disturbance data according to the data recursion method, and sending the obtained reasonable working disturbance weight and abnormal working disturbance weight back to S3;

[0051] S5, under the condition of abnormal information, performing an external diving disturbance estimation function segmentation analysis on the semi-submersible barge assisted diving aspect, and performing a confirmation process on the obtained assisted diving evaluation factor to obtain a stable message or a function message.

[0052] In this application, analysis is performed during the diving of the semi-submersible barge, thereby determining whether the diving during the diving of the semi-submersible barge is reasonable, that is, performing an analysis of the potential risks of abnormal time periods during the diving on the diving data, which is conducive to directly determining whether the diving of the semi-submersible barge is reasonable, and is conducive to making focused control based on the obtained results, thereby improving the knowability and stability of the diving of the semi-submersible barge; and through the obtained results, analysis is performed on both the power mechanism and the assisting device, which is conducive to determining whether the abnormal diving of the semi-submersible barge is caused by the abnormalities of the power mechanism and the assisting device, and is conducive to performing focused control on the power mechanism or the assisting device based on the obtained results to improve the stability and reliability of the diving process of the power mechanism.

[0053] In a preferred but non-limiting embodiment of the present invention, in S1, the method for estimating the potential risks of abnormal time periods during diving includes:

[0054] Define the total diving period of the semi-submersible barge as the working time interval, obtain the diving data of the semi-submersible barge during the working time interval, the diving data includes the diving displacement and the diving inclination angle, and obtain the basic diving data of the semi-submersible barge with reasonable diving; the basic diving data of the semi-submersible barge with reasonable diving is the average value of the diving data of the semi-submersible barge obtained during the previous execution of the same task as the current semi-submersible barge and successfully performing the diving task according to the diving requirements. The average value of the diving data includes the average value of the diving displacement and the average value of the diving inclination angle. The diving displacement and the diving inclination angle can be sampled by a linear sensor and an inclination sensor respectively.

[0055] Obtain the state action data of the semi-submersible barge during the working time interval, the state action data includes the water pressure received by the semi-submersible barge or the water level where the semi-submersible barge is located, the water pressure or the water level is sampled by a water pressure sensor or a water level sensor provided at a certain place on the semi-submersible barge respectively, and define the number of the state action data exceeding the defined critical value as the working action factor, and then obtain the offset calibration factor corresponding to the working action factor within the defined working action factor range. The critical value can be set according to specific requirements, and the working action factor range can be set as several continuous ranges according to specific requirements.

[0056] In a preferred but non-limiting embodiment of the present invention, in S1, each defined working action factor range corresponds to an offset calibration factor. The offset calibration factor can be determined according to specific requirements.

[0057] Define the data type in the diving data as , is a positive integer, and when , it represents the type of diving displacement, and when , it represents the type of diving inclination angle.

[0058] In a preferred but non-limiting embodiment of the present invention, in S1, a quantity obtained by standardizing each type of corresponding data in the diving data during the working time interval using the Z-score method is multiplied by the offset calibration factor value, and the resulting quantity is defined as the calibrated diving data. The calibrated diving data is compared with the basic diving data, that is, the quantity obtained by subtracting the basic diving data from the calibrated diving data is defined as the diving period offset. , and for the diving period offset perform a confirmation process:

[0059] If the diving period offset is lower than the defined critical value of the diving period offset, a reasonable message is formed; it represents that the diving of the semi-submersible barge is reasonable, that is, the semi-submersible barge has successfully performed the diving task according to the set requirements.

[0060] If the diving period offset is not lower than the defined critical value of the diving period offset, an abnormal message is formed. It represents that the diving of the semi-submersible barge is abnormal, that is, the semi-submersible barge has not successfully performed the diving task according to the set requirements. The critical value of the diving period offset can be set according to specific requirements.

[0061] When forming a reasonable message or an abnormal message, it is beneficial to directly determine whether the diving of the semi-submersible barge is reasonable, and it is beneficial to make targeted control accordingly, thereby improving the knowability and stability of the diving of the semi-submersible barge.

[0062] Under the condition of obtaining an abnormal message, sample the diving condition data of the power mechanism, and perform an estimation process for the abnormal diving of the power mechanism during the period on the diving condition data, that is, analyze from the diving state of the power mechanism and combine the disturbance weights of each power mechanism for analysis, thereby improving the analysis accuracy of the power mechanism. In a preferred but non-limiting embodiment of the present invention, in S2 to S3, the method for estimating the abnormal diving of the power mechanism during the period includes:

[0063] Define the number of power mechanisms in the semi-submersible barge as , is a positive integer. Obtain the diving condition data of each power mechanism in the semi-submersible barge during the working time interval. The diving condition data includes a state estimation factor and an attribute presentation factor. The quantity obtained by multiplying the state estimation factor by the attribute presentation factor is defined as the power mechanism estimation factor. Obtain the corresponding reasonable working disturbance weight and the abnormal working disturbance weight ;

[0064] Obtain the product of the power mechanism estimation factor of each power mechanism and the corresponding reasonable working disturbance weight or the abnormal working disturbance weight The quantity obtained is defined as the diving obstacle estimation factor , and for the diving obstacle estimation factor perform a confirmation process:

[0065] If the diving obstacle estimation factor is not lower than the defined critical value of the diving obstacle estimation factor (the critical value of the diving obstacle estimation factor can be set according to specific requirements), it is determined that the corresponding power mechanism is a disturbance power mechanism, and the corresponding number of the disturbance power mechanism is divided by The obtained quotient value is defined as the diving abnormal disturbance factor, and a confirmation process is performed on the diving abnormal disturbance factor:

[0066] If the diving abnormal disturbance factor is lower than the defined critical value of the diving abnormal disturbance factor (the critical value of the diving abnormal disturbance factor can be set according to specific requirements), a compliance message is formed; the compliance message represents that the diving abnormality of the semi-submersible barge is not caused by the disturbance of the power mechanism.

[0067] If the diving abnormal disturbance factor is not lower than the defined critical value of the diving abnormal disturbance factor, a diving disturbance message is formed. The diving disturbance message represents that the diving abnormality of the semi-submersible barge is caused by the disturbance of the power mechanism. When forming the compliance message or the diving disturbance message, it is advisable to directly determine whether the diving abnormality of the semi-submersible barge is caused by the disturbance of the power mechanism.

[0068] In this application, the state estimation factor represents the number of the parameter data of each power mechanism outside the set range (the set range is the reasonable working range of the power mechanism). The parameter data includes the output power of the generator of the power mechanism (obtained by sampling with a power sensor) or the oil pressure of the fuel of the electromechanical equipment of the power mechanism (obtained by sampling with an oil pressure sensor), etc., and the state estimation factor is a function parameter reflecting the failure of the power mechanism.

[0069] In this application, the attribute presentation factor represents the quantity obtained by subtracting the temperature value at the start of the operation of each power mechanism from the highest temperature value during the operation of the power mechanism (the temperature value is obtained by sampling with a temperature sensor). The higher the value of the attribute presentation factor, the higher the probability risk of abnormality of the power mechanism.

[0070] Perform a working correction estimation segmentation response analysis on the diving disturbance data according to the data recursion method, so as to determine the reasonable working disturbance weight or the abnormal working disturbance weight of each power mechanism. In a preferred but non-limiting embodiment of the present invention, in S4, the working correction estimation segmentation response analysis method includes:

[0071] Obtain the diving disturbance data of each power mechanism in the semi-submersible barge during the working time interval. The diving disturbance data includes the internal loss estimation factor and the obstacle evaluation value;

[0072] In this application, the internal loss estimation factor represents the quantity obtained by first standardizing the input current value and input voltage value of each power mechanism via the Z-score method, and then multiplying all the quantities obtained after the standardization process. This resulting quantity is regarded as the internal loss estimation factor.

[0073] In this application, the obstacle evaluation value represents the number of input current values of each power mechanism within the set reasonable input current value range (this reasonable input current value range is the reasonable current value range that the power mechanism is subject to). The higher the value of the obstacle evaluation value, the higher the probability of abnormal diving of each power mechanism.

[0074] Compare the internal loss estimation factor and the obstacle evaluation value with the defined internal loss estimation factor critical value and the defined obstacle evaluation value critical value (the defined internal loss estimation factor critical value and the defined obstacle evaluation value critical value can be set according to specific requirements). Define the quantity obtained by adding the numbers in the internal loss estimation factor and the obstacle evaluation value that are respectively higher than the defined internal loss estimation factor critical value and the defined obstacle evaluation value critical value as the estimation risk factor. If the estimation risk factor is 0, it is determined that the corresponding power mechanism is a reasonable power mechanism. If the estimation risk factor is non-zero, it is determined that the corresponding power mechanism is a disturbed power mechanism.

[0075] In a preferred but non-limiting embodiment of the present invention, in S4, the quantity obtained by multiplying the internal loss estimation factor of the reasonable power mechanism by the obstacle evaluation value is defined as the reasonable operation estimation factor. The number of reasonable operation estimation factors of the reasonable power mechanism within the defined reasonable operation estimation factor range (the reasonable operation estimation factor range can be set according to specific requirements) is used as the reasonable working disturbance weight , and the quantity obtained by multiplying the internal loss estimation factor of the abnormal power mechanism by the obstacle evaluation value is defined as the abnormal operation estimation factor. The abnormal working disturbance weight of the abnormal operation estimation factor of the disturbed power mechanism within the defined abnormal operation estimation factor range (the abnormal operation estimation factor range can be set according to specific requirements) is obtained , where and are both positive integers.

[0076] In this application, a set of working disturbance boundary values is set for the defined reasonable operation estimation factor range of the reasonable power mechanism, and , and a set of abnormal working disturbance boundary values is set for the defined abnormal operation estimation factor range of the abnormal power mechanism, and .

[0077] Under abnormal message conditions, perform segmentation analysis of the external diving disturbance estimation function during the diving assisted by a semi-submersible barge. In a preferred but non-limiting embodiment of the present invention, in S5, the method for segmenting and analyzing the external diving disturbance estimation function includes:

[0078] Obtain the assisting devices of the semi-submersible barge during the working time interval. The assisting devices include the ventilation pipe and air pipe of the semi-submersible barge. Obtain the external diving disturbance data of each assisting device. The method for obtaining the external diving disturbance data is as follows: First, obtain all the wind speed values of the assisting device whose wind speed (the wind speed can be sampled by a wind speed sensor) is lower than the defined wind speed critical value (this critical value can be set according to specific requirements). Multiply the quantity obtained by normalizing all the wind speed values through the Z-score method by the working presentation level to obtain the quantity as the external diving disturbance data, and perform verification processing on the external diving disturbance data. If the external diving disturbance data is not lower than the defined external diving disturbance data critical value, it is determined that the corresponding assisting device is a diving disturbance device.

[0079] In a preferred but non-limiting embodiment of the present invention, in S5, divide the number of diving disturbance devices by the total number of assisting devices to obtain the assisting diving estimation factor, and perform verification processing on the assisting diving estimation factor:

[0080] If the assisting diving estimation factor is lower than the defined assisting diving estimation factor critical value (this critical value can be set according to specific requirements), a stable message is formed; the stable message indicates that the assisting device is not an abnormal disturbance factor in the diving process of the semi-submersible barge.

[0081] If the assisting diving estimation factor is not lower than the defined assisting diving estimation factor critical value, an action message is formed. The action message indicates that the assisting device is an abnormal disturbance factor in the diving process of the semi-submersible barge. When forming a stable message or an action message, it is advisable to directly determine whether the assisting device is an abnormal disturbance factor in the diving process of the semi-submersible barge, and it is advisable to perform focused control on the diving disturbance device, thereby improving the diving stability and reliability of the semi-submersible barge.

[0082] In this application, the working presentation level represents the set level value (this value can be set according to specific requirements) corresponding to the wind pressure of the assisting device being within the defined wind pressure range (this range can be several ranges set according to specific requirements). The higher the value of the working presentation level, the higher the probability of abnormality of the assisting device.

[0083] For each defined wind pressure range, a set level value is set, and the set level value increases with the increase of the defined wind pressure range. That is, the set level value corresponding to the first defined wind pressure range is lower than the set level value corresponding to the second defined wind pressure range, and the set level value corresponding to the second defined wind pressure range is lower than the set level value corresponding to the third defined wind pressure range. Similarly, the magnitude order of the set level values corresponding to other wind pressure ranges can be obtained.

[0084] In summary, this application performs analysis during the diving period of the semi-submersible barge, thereby grasping whether the diving during the diving period of the semi-submersible barge is reasonable. That is, an analysis of the potential risks of abnormal time periods during the diving period is performed on the diving data, which is conducive to directly grasping whether the diving of the semi-submersible barge is reasonable, and is conducive to making targeted control based on the obtained results, thereby improving the knowability and stability of the diving of the semi-submersible barge; and through the obtained results, analysis is performed on both the power mechanism and the assisting device, which is conducive to confirming whether the abnormal diving of the semi-submersible barge is caused by the abnormality of the power mechanism and the assisting device, and is conducive to performing targeted control on the power mechanism or the assisting device based on the obtained results to improve the stability and reliability of the diving process of the power mechanism.

[0085] As Figure 2 shown, a measurement data processing platform based on the control of the semi-submersible barge launching of the present invention includes:

[0086] An estimation module, which is used to sample diving data during the diving period of the semi-submersible barge, and perform an analysis of the potential risks of abnormal time periods during the diving period on the diving data, and perform a confirmation process on the obtained diving time offset to obtain reasonable information or abnormal information;

[0087] A response module, which is used to sample the diving condition data and diving disturbance data of the power mechanism under the condition of abnormal information, send the diving disturbance data to S4 to perform a working correction estimation segmentation response analysis, and perform an estimation process on the diving condition data for abnormal diving of the power mechanism during the time period;

[0088] A confirmation module, which is used to perform a confirmation process on the obtained diving abnormal disturbance factor according to the diving abnormal disturbance factor obtained from the estimation process of the abnormal diving of the power mechanism during the time period, so as to obtain compliance information or diving disturbance information;

[0089] An analysis module, which is used to perform a working correction estimation segmentation response analysis on the diving disturbance data according to the method of data recursion, and send the obtained reasonable working disturbance weight and abnormal working disturbance weight back to S3;

[0090] A disposal module, which is used to perform split analysis of the external diving disturbance estimation function during the assisted diving of a semi-submersible barge under the condition of an abnormal message, and perform confirmation disposal on the obtained assisted diving evaluation factors, so as to obtain stable messages or function messages.

[0091] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0092] By performing analysis during the diving of the semi-submersible barge, it is possible to grasp whether the diving during the diving of the semi-submersible barge is reasonable, that is, to perform analysis on the abnormal hidden danger of the diving period of the diving data, which is conducive to directly grasping whether the diving of the semi-submersible barge is reasonable, and is conducive to making targeted control based on the obtained results, so as to improve the knowability and stability of the diving of the semi-submersible barge; and by performing analysis on the obtained results from two aspects of the power mechanism and the assisting device, it is conducive to confirming whether the abnormal diving of the semi-submersible barge is caused by the abnormality of the power mechanism and the assisting device, and is conducive to performing targeted control on the power mechanism or the assisting device based on the obtained results to improve the stability and reliability of the diving process of the power mechanism.

[0093] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that: modifications or equivalent replacements can still be made to the specific embodiments of the present invention, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention shall be covered by the protection scope of the claims of the present invention.

Claims

1. A measurement data processing method based on semi-submersible barge launching control, characterized in that: include: S1, during the diving period of the semi-submersible barge, the diving data is sampled, and the abnormal hidden danger estimation and analysis of the diving data during the diving period is performed, and the obtained diving period offset is calculated. Perform confirmation processing to obtain reasonable information or abnormal information; S2, under the condition of abnormal information, samples the diving status data and diving disturbance data of the power mechanism, sends the diving disturbance data to S4 for work correction estimation and segmentation response analysis, and performs diving abnormal estimation and treatment on the diving status data during the period of power mechanism diving; S3, according to the diving abnormal disturbance factor obtained under the diving abnormal estimation treatment of the power mechanism during the period, performing confirmation treatment on the obtained diving abnormal disturbance factor, so as to obtain the compliance information or the diving disturbance information; S4, based on the data recursion method, performs work correction estimation, segmentation and response analysis on the submerged disturbance data, and obtains the reasonable work disturbance weight and abnormal working disturbance weight Send back to S3; S5. Under abnormal information conditions, the semi-submersible barge assisted diving aspect performs external diving disturbance estimation and effect segmentation and analysis, and performs confirmation processing on the obtained assisted diving evaluation factors, thereby obtaining stable information or effect information.

2. The measurement data processing method based on semi-submersible barge launching control according to claim 1 is characterized in that: In S1, the method for estimating and analyzing the abnormal hidden dangers during the diving period includes: Define the total diving period of the semi-submersible barge as the working time interval, obtain the diving data of the semi-submersible barge during the working time interval, and obtain the basic diving data of the semi-submersible barge with reasonable diving; The state action data of the semi-submersible barge in the working time interval is obtained, and the number of the state action data exceeding the defined critical value is defined as the working action factor, and then the offset calibration factor corresponding to the working action factor being within the defined working action factor range is obtained.

3. The measurement data processing method based on semi-submersible barge launching control according to claim 2 is characterized in that: In S1, each defined working factor category is associated with an offset calibration factor.

4. The measurement data processing method based on semi-submersible barge launching control according to claim 3 is characterized in that: In S1, the corresponding data of each type in the diving data in the working time interval is obtained by using the Z-score method to standardize the data, and the amount obtained by multiplying the amount obtained by the standardized treatment by the offset calibration factor value is defined as the calibrated diving data, and the calibrated diving data and the basic diving data are compared, that is, the amount obtained by subtracting the basic diving data from the calibrated diving data is defined as the diving period offset , and the dive period offset Execute confirmation disposal: If the dive period offset If they are all lower than the defined dive period offset threshold, reasonable news is formed; If the dive period offset If it is not lower than the defined dive period offset threshold, an abnormal message is generated.

5. The measurement data processing method based on semi-submersible barge launching control according to claim 4 is characterized in that: From S2 to S3, the method for estimating and handling the abnormality of the power mechanism during diving includes: The number of power mechanisms in a semi-submersible barge is defined as , is a positive integer. The diving status data of each power mechanism in the semi-submersible barge during the working time interval are obtained. The diving status data includes the state estimation factor and the attribute presentation factor. The state estimation factor multiplied by the attribute presentation factor is defined as the power mechanism estimation factor. The corresponding reasonable working disturbance weight of each power mechanism is obtained. and abnormal working disturbance weight ; Get the power mechanism estimation factor of each power mechanism multiplied by the corresponding reasonable working disturbance weight Or abnormal working disturbance weight The resulting quantity is defined as the dive barrier estimation factor , and the dive barrier estimation factor Execute confirmation disposal: If the dive barrier estimation factor If the value is not less than the defined critical value of the dive obstacle estimation factor, the corresponding power mechanism is considered to be a disturbance power mechanism, and the corresponding number of disturbance power mechanisms is divided by The obtained quotient is defined as the submerged abnormal disturbance factor, and confirmation processing is performed on the submerged abnormal disturbance factor: If the submerged abnormal disturbance factor is lower than the defined submerged abnormal disturbance factor critical value, a compliance message is generated; If the submersible abnormal disturbance factor is not lower than the defined submersible abnormal disturbance factor critical value, a submersible disturbance message is generated.

6. The measurement data processing method based on semi-submersible barge launching control according to claim 5 is characterized in that: In S4, the work correction estimation segmentation response parsing method includes: Obtain the diving disturbance data of each power mechanism in the semi-submersible barge during the working time interval, and the diving disturbance data includes the internal loss estimation factor and the obstacle assessment value; The internal loss estimation factor and the obstacle assessment value are compared with the defined internal loss estimation factor critical value and the defined obstacle assessment value critical value respectively. The amount obtained by adding the number of internal loss estimation factors and obstacle assessment values ​​that are respectively higher than the defined internal loss estimation factor critical value and the defined obstacle assessment value critical value is defined as the estimated risk factor. If the estimated risk factor is 0, the corresponding power mechanism is determined to be a reasonable power mechanism. If the estimated risk factor is not 0, the corresponding power mechanism is determined to be a disturbed power mechanism.

7. The measurement data processing method based on semi-submersible barge launching control according to claim 6 is characterized in that: In S4, the amount obtained by multiplying the internal loss estimation factor of the reasonable power mechanism by the obstacle assessment value is defined as the reasonable operation estimation factor, and the number of reasonable operation estimation factors of the reasonable power mechanism that are within the defined reasonable operation estimation factor range is obtained as the reasonable working disturbance weight. , the abnormal operation estimation factor is defined as the amount obtained by multiplying the internal loss estimation factor of the abnormal power mechanism by the obstacle assessment value, and the abnormal operation estimation factor of the disturbance power mechanism is obtained in the abnormal operation estimation factor range of the defined abnormal operation estimation factor. , here, and All are positive integers.

8. The measurement data processing method based on semi-submersible barge launching control according to claim 7 is characterized in that: In S5, the external submerged disturbance estimation action segmentation and analysis method includes: Obtain the assisting devices of the semi-submersible barge during the working distance, obtain the external diving disturbance data of each assisting device, and perform confirmation processing on the external diving disturbance data. If the external diving disturbance data is not lower than the defined external diving disturbance data critical value, the corresponding assisting device is determined to be a diving disturbance device.

9. The measurement data processing method based on semi-submersible barge launching control according to claim 8 is characterized in that: In S5, the amount obtained by dividing the number of submergence disturbance devices by the total number of assisting devices is used as an assisting submergence estimation factor, and a confirmation process is performed on the assisting submergence estimation factor: If the assisting dive estimation factor is lower than the defined assisting dive estimation factor critical value, a stable message is formed; If the assisting dive estimation factor is not lower than the defined assisting dive estimation factor critical value, an action message is generated.

10. A measurement data processing platform based on semi-submersible barge launching control, characterized in that: include: The estimation module is used to sample the diving data during the diving of the semi-submersible barge, and perform an estimation analysis of the abnormal hidden dangers during the diving period on the diving data, and obtain the diving period offset Perform confirmation processing to obtain reasonable information or abnormal information; The response module is used to sample the diving status data and diving disturbance data of the power mechanism under the condition of abnormal information, send the diving disturbance data to S4 to perform work correction estimation and segmentation response analysis, and perform the diving abnormality estimation and treatment of the power mechanism during the diving status data; A confirmation module is used to perform confirmation processing on the obtained diving abnormal disturbance factor according to the diving abnormality estimation processing of the power mechanism during the period, so as to obtain a standard-reaching message or a diving disturbance message; The analysis module is used to perform work correction estimation, segmentation and response analysis on the submerged disturbance data based on the data recursion method, and obtain the reasonable work disturbance weight and abnormal working disturbance weight Send back to S3; The treatment module is used to perform external diving disturbance estimation and effect segmentation and analysis through the semi-submersible barge assisted diving under abnormal information conditions, perform confirmation treatment on the obtained assisted diving evaluation factors, and obtain stable information or effect information based on this.

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