Wharf caisson structure monitoring method, system and device

Abstract

The application relates to the technical field of wharf caisson monitoring, and provides a wharf caisson structure monitoring method, system and equipment. The wharf caisson structure monitoring method comprises the following steps: acquiring frequency data and temperature data collected by strain gauges arranged on a wharf caisson; determining whether the wharf caisson has a structure risk based on the frequency data and the temperature data; and outputting risk prompt information in the case that it is determined that the wharf caisson has a structure risk. Through the above technical scheme, the frequency data and the temperature data collected by the strain gauges arranged on the wharf caisson can be used to judge the structure risk of the wharf caisson, and abnormal prompt information can be outputted in the case that the structure risk is judged, so that the structure state of the wharf caisson can be monitored.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of wharf caisson monitoring, in particular to a wharf caisson structure monitoring method, system and device. BACKGROUND

[0002] A caisson is an important hydraulic structure, mainly used for the construction of wharfs and breakwaters. The caisson is generally prefabricated from reinforced concrete and has a partition inside. During construction, the caisson is filled with sand or stone blocks, and a cover plate is added on top to form a load-bearing and vertical wall structure.

[0003] After installation, the wharf caisson is submerged in water and serves as a pile foundation to bear the weight of the wharf. Therefore, it is necessary to monitor the structural state of the wharf caisson to carry out targeted operation and maintenance, thereby improving the service life of the wharf. SUMMARY

[0004] In order to monitor the structural state of the wharf caisson, the present application provides a wharf caisson structure monitoring method, system and device.

[0005] In a first aspect, the present application provides a wharf caisson structure monitoring method, which adopts the following technical solution:

[0006] A wharf caisson structure monitoring method, the method comprising:

[0007] Obtaining frequency data and temperature data collected by strain gauges arranged on the wharf caisson;

[0008] Determining whether the wharf caisson has a structural risk based on the frequency data and the temperature data;

[0009] Outputting a risk prompt information in the case where it is determined that the wharf caisson has a structural risk.

[0010] By adopting the above technical solution, the frequency data and temperature data collected by the strain gauges arranged on the wharf caisson can be used to judge the structural risk of the wharf caisson, and abnormal prompt information can be outputted in the case where a structural risk is judged. This can help to monitor the structural state of the wharf caisson.

[0011] Optionally, the number of strain gauges is two or more, and the outputting of the risk prompt information in the case where it is determined that the wharf caisson has a structural risk comprises:

[0012] In the case where it is determined that the wharf caisson has a structural risk based on the frequency data and the temperature data collected by a target strain gauge, determining whether there is an adjacent strain gauge with a distance less than a preset distance threshold from the target strain gauge.

[0013] In the presence of the adjacent strain gauge, the wharf caisson is risk verified based on frequency data and temperature data collected by the adjacent strain gauge;

[0014] In the case where the risk verification result indicates that the wharf caisson has structural risks, the risk prompt information is output.

[0015] By adopting the above technical solutions, in the case where it is determined based on data collected by the target strain gauge that the wharf caisson has structural risks and there is an adjacent strain gauge of the target strain gauge, the wharf caisson can be risk verified based on frequency data and temperature data collected by the adjacent strain gauge, and in the case where the risk verification result indicates that there are structural risks, the risk prompt information is output, which can help improve the accuracy of the output of the risk prompt information.

[0016] Optionally, after the risk verification of the wharf caisson based on the frequency data and the temperature data collected by the adjacent strain gauge, the method further comprises:

[0017] In the case where the risk verification result indicates that the wharf caisson has no structural risks, the target strain gauge and the adjacent strain gauge are abnormally verified;

[0018] In the case where the abnormal verification result indicates that neither the target strain gauge nor the adjacent strain gauge has an abnormality, it is determined that the wharf caisson has no structural risks, and the risk prompt information is not output.

[0019] By adopting the above technical solutions, the influence of the abnormality of the strain gauge on the judgment of the structural risks can be reduced, and the accuracy of the judgment of the structural risks can be improved.

[0020] Optionally, the number of the strain gauges includes two or more, and in the case where it is determined that the wharf caisson has structural risks, the output of the risk prompt information comprises:

[0021] In the case where it is determined based on the frequency data and the temperature data collected by the target strain gauge that the wharf caisson has structural risks, it is determined whether there is a symmetric strain gauge symmetrically arranged with the target risk strain gauge;

[0022] In the presence of the symmetric strain gauge, a predicted risk factor of the wharf caisson is determined in combination with frequency data and temperature data collected by the symmetric strain gauge;

[0023] The risk prompt information is output based on the predicted risk factor.

[0024] By adopting the technical solution, in the case that the target strain gauge determines that the wharf caisson has a structural risk and a symmetric strain gauge corresponding to the target risk strain gauge exists, the prediction risk factor of the wharf caisson can be determined in combination with the data collected by the symmetric strain gauge, and the risk prompt information can be output based on the prediction risk factor, so as to assist in determining the reason for the structural risk of the wharf caisson in the case that the structural risk of the wharf caisson is determined.

[0025] Optionally, the outputting of the risk prompt information based on the prediction risk factor comprises:

[0026] determining whether the prediction risk factor comprises an associated risk factor related to associated data collected by an associated sensor arranged on the wharf caisson;

[0027] in the case that the prediction risk factor comprises the associated risk factor, verifying whether the wharf caisson has an associated risk corresponding to the associated risk factor based on the associated data;

[0028] in the case that the wharf caisson is determined to have the associated risk, outputting the risk prompt information based on the associated risk.

[0029] By adopting the technical solution, in the case that the prediction risk factor comprises the associated risk factor, whether the wharf caisson has the associated risk corresponding to the associated risk factor can be determined based on the associated data, and in the case that the wharf caisson is determined to have the associated risk, the risk prompt information can be output based on the associated risk, so as to help to check the risk factor in combination with the associated data, and thus the accuracy of the risk prompt can be improved.

[0030] Optionally, after the verifying of whether the wharf caisson has the associated risk corresponding to the associated risk factor based on the associated data, the method further comprises:

[0031] in the case that the wharf caisson is determined to not have the associated risk, determining whether the prediction risk factor comprises a non-associated risk factor other than the associated risk factor;

[0032] in the case that the prediction risk factor comprises the non-associated risk factor, outputting the risk prompt information based on the non-associated risk factor.

[0033] By adopting the technical solution, the specific risk type that the wharf caisson may have can be indirectly determined by excluding the associated risk, and thus the accuracy of the risk prompt can be improved.

[0034] Optionally, the determining of whether the prediction risk factor comprises the non-associated risk factor other than the associated risk factor comprises:

[0035] determining whether risk verification is passed in the determination process of the predictive risk factor in a case where the predictive risk factor does not include the non-associated risk factor;

[0036] reducing the confidence degree of the associated sensor in a case where the risk verification is passed in the determination process of the predictive risk factor;

[0037] determining whether the confidence degree of the associated sensor is greater than the confidence degree corresponding to the target strain gauge;

[0038] not outputting the risk prompt information in a case where the confidence degree of the associated sensor is greater than the confidence degree corresponding to the target strain gauge.

[0039] By adopting the above technical solution, in a case where the associated data determines that there is no associated risk in the wharf caisson and the predictive risk factor includes the non-associated risk factor, the confidence degree of the associated sensor is adjusted based on whether risk verification is passed in the determination process of the predictive risk factor, and the risk prompt information is not outputted in a case where the confidence degree of the associated sensor is greater than the confidence degree corresponding to the target strain gauge, which can help to further improve the accuracy of the output of the risk prompt information.

[0040] Optionally, the determining whether the wharf caisson has a structural risk based on the frequency data and the temperature data comprises:

[0041] calculating a strain change amount based on the frequency data and the temperature data;

[0042] determining whether the wharf caisson has a structural risk based on the strain change amount;

[0043] the strain change amount is calculated by the following formula:

[0044] ε=G×C×(R1-R0)+(Y1-Y2)×(T1-T0)

[0045] wherein, ε is the strain change amount; G is an instrument standard coefficient; C is an average correction coefficient corresponding to the strain gauge; R1 is the frequency data; R0 is an initial frequency data set in advance; Y1 is a temperature expansion coefficient of a steel string; Y2 is a temperature expansion coefficient of concrete; T1 is the temperature data; and T0 is an initial temperature set in advance.

[0046] In a second aspect, the present application provides a wharf caisson structure monitoring system, which adopts the following technical solution:

[0047] A wharf caisson structure monitoring system, the system comprising at least one strain gauge arranged on a wharf caisson, and a controller connected with the strain gauge;

[0048] The controller is configured to perform any one of the wharf caisson structure monitoring methods provided in the first aspect.

[0049] In a third aspect, the application provides a wharf caisson structure monitoring system, which adopts the following technical solution:

[0050] An electronic device, the electronic device comprising:

[0051] at least one processor;

[0052] a memory;

[0053] at least one application program, wherein the at least one application program is stored in the memory and is configured to be executed by the at least one processor, and the at least one application program is configured to perform any one of the wharf caisson structure monitoring methods provided in the first aspect.

[0054] In summary, the application includes at least one of the following beneficial technical effects:

[0055] 1. The structural risk of the wharf caisson can be judged by the frequency data and temperature data collected by the strain gauges arranged on the wharf caisson, and abnormal prompt information can be output in the case of judging the structural risk, which can help to monitor the structural state of the wharf caisson;

[0056] 2. Since the risk of the wharf caisson is determined based on the data collected by the target strain gauge, and there is a neighboring strain gauge of the target strain gauge, the risk of the wharf caisson will be verified based on the frequency data and temperature data collected by the neighboring strain gauge, and the risk prompt information will be output in the case that the risk verification result indicates that there is a structural risk, which can help to improve the accuracy of the risk prompt information output. BRIEF DESCRIPTION OF DRAWINGS

[0057] Figure 1 is a flowchart of a wharf caisson structure monitoring method provided by an embodiment of the application;

[0058] Figure 2 is a flowchart of a risk verification method provided by an embodiment of the application;

[0059] Figure 3 is a flowchart of a risk prompt information generation method provided by an embodiment of the application;

[0060] Figure 4 is a flowchart of another risk prompt information generation method provided by an embodiment of the application;

[0061] Figure 5 is a structural diagram of a wharf caisson structure monitoring system provided by an embodiment of the application;

[0062] Figures 6a to 6d FIG. 1 is a schematic diagram of a strain gauge layout provided by an embodiment of the present application;

[0063] Figure 7 FIG. 2 is a structural schematic diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0064] In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and should not be used to limit the present application. Figures 1-7 In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and should not be used to limit the present application.

[0065] An embodiment of the present application discloses a wharf caisson structure monitoring method. Referring to FIG. 1, the wharf caisson structure monitoring method comprises the following steps: Figure 1

[0066] Step 101, acquiring frequency data and temperature data collected by a strain gauge laid on a wharf caisson.

[0067] The strain gauge is used to sense the deformation of the wharf caisson. Specifically, the strain gauge is selected as a buried vibrating wire strain gauge, and the strain gauge is composed of a main body and a coil, and is internally provided with a vibrating wire sensor and a temperature sensor. The frequency data is determined based on the data collected by the vibrating wire sensor, and the temperature data is determined based on the data collected by the temperature sensor. In one example, the strain gauge is selected as a BGK4200 series buried vibrating wire strain gauge.

[0068] In one example, the frequency data is expressed by a frequency modulus, and the frequency data is calculated by the following formula:

[0069] F=f 2 / 1000

[0070] Wherein, F is the frequency modulus, i.e. the frequency data, and the unit is digit; f is the frequency collected by the vibrating wire sensor, and the unit is hertz (HZ).

[0071] In another example, the temperature data is expressed by an actual temperature, and the temperature data is calculated by the following formula:

[0072]

[0073] Wherein, T is the actual temperature, i.e. the temperature data, and the unit is Celsius (℃); R is the resistance value of the thermistor of the temperature sensor, and LnR is the natural logarithm of the resistance value; A, B and C are preset values. In one example, A=1.4051×10 -3 , B=2.369×10 -4 , and C=1.019×10 -7 .​

[0074] Optionally, the number of strain gauges can be one or more than two, and the installation positions of the strain gauges can be selected according to the structural characteristics of the wharf caisson. In an example, the strain gauges are arranged in the middle of the wharf caisson (in the middle of the wall plate) and the support (the vertical intersection of the wall), specifically, the strain gauges can be arranged at least one position of the front vertical plate outside, the rear vertical plate outside, the side plate outside, the bottom plate, the outer toe bottom plate, etc. of the wharf caisson. In addition, the direction of the strain gauge can be set according to the actual monitoring requirements, such as: towards X direction or towards Y direction.

[0075] Correspondingly, in the case where the number of strain gauges includes more than two, the frequency data and the temperature data collected by each strain gauge are acquired respectively.

[0076] In step 102, it is determined whether the wharf caisson has a structural risk based on the frequency data and the temperature data.

[0077] Optionally, determining whether the wharf caisson has a structural risk based on the frequency data and the temperature data includes: calculating a strain change amount based on the frequency data and the temperature data; and determining whether the wharf caisson has a structural risk based on the strain change amount.

[0078] In an example, the strain change amount is calculated by the following formula:

[0079] ε=G×C×(R1-R0)+(Y1-Y2)×(T1-T0)

[0080] Wherein, ε is the strain change amount; G is the instrument standard coefficient, for example: G is 3.15 με / word; C is the average correction coefficient corresponding to the strain gauge; R1 is the frequency data; R0 is the initial frequency data set in advance, for example: the initial frequency data is determined based on the reading value of 9-24 hours after the strain gauge is embedded in the concrete; Y1 is the temperature expansion coefficient of the steel string; Y2 is the temperature expansion coefficient of the concrete; T1 is the temperature data; T0 is the initial temperature set in advance.

[0081] In actual implementation, the strain change amount can be calculated based on other manners, and the present embodiment does not limit the calculation manner of the strain change amount.

[0082] Optionally, determining whether the wharf caisson has a structural risk based on the strain change amount includes: determining whether the strain change amount is greater than a preset change amount threshold; if yes, it is determined that the wharf caisson has a structural risk; if not, it is determined that the wharf caisson does not have a structural risk.

[0083] Further, in a case where it is determined that the strain variation is not greater than the variation threshold, it can be further determined whether a variation range of the strain variation exceeds a preset range threshold; if yes, it is determined that the wharf caisson has a structural risk; if no, it is determined that the wharf caisson does not have a structural risk. In this way, it can be helpful to judge the structural abnormality of the wharf caisson caused by abnormal variation of the variation range.

[0084] In one example, determining whether the wharf caisson has a structural risk based on the strain variation includes: determining stress based on the strain variation; and determining whether the wharf caisson has a structural risk based on a relationship between the stress and a stress threshold. The stress threshold can be fixedly set or can be set based on a service life of the wharf caisson.

[0085] In one example, the stress is calculated by the following formula:

[0086] δ=ε×E

[0087] wherein δ is the stress, the unit of which is pa, and a commonly used unit is Mpa; ε is the strain variation, the unit of which is strain; and E is the elastic modulus of the concrete, the unit of which is Mpa / ε.

[0088] Optionally, in a case where the number of strain gauges includes two or more, for each strain gauge, it is determined whether the wharf caisson has a structural abnormality based on the frequency data and the temperature data collected by the strain gauge.

[0089] In step 103, in a case where it is determined that the wharf caisson has a structural risk, risk prompt information is output.

[0090] Optionally, the risk prompt information includes a strain gauge identifier corresponding to the strain gauge. In this way, it can be helpful to locate the structural risk of the wharf caisson.

[0091] The wharf caisson structure monitoring method provided by the embodiments of the present application has the following implementation principle: frequency data and temperature data collected by strain gauges arranged on a wharf caisson are acquired; it is determined whether the wharf caisson has a structural risk based on the frequency data and the temperature data; and in a case where it is determined that the wharf caisson has a structural risk, risk prompt information is output. By using the above technical solution, the structural risk of the wharf caisson can be judged based on the frequency data and the temperature data collected by the strain gauges arranged on the wharf caisson, and abnormal prompt information is output in a case where it is judged that there is a structural risk, which can be helpful to monitor the structural state of the wharf caisson.

[0092] In some embodiments, the number of strain gauges includes two or more, and the above step 103, in a case where it is determined that the wharf caisson has a structural risk, outputting risk prompt information, includes: Figure 2

[0093] ​In step 201, when it is determined that the wharf caisson has a structural risk based on the frequency data and the temperature data collected by the target strain gauge, it is determined whether there is an adjacent strain gauge with a distance less than a preset distance threshold from the target strain gauge.

[0094] The preset distance threshold is a maximum distance value between two adjacent strain gauges. Specifically, since the strain gauge may fail during use, in the embodiment, in order to improve the accuracy of risk judgment, multiple adjacent strain gauges may be deployed at some important monitoring positions to find the failure of the strain gauge through data comparison, thereby improving the accuracy of risk judgment.

[0095] In one example, the preset distance threshold is 30 cm.

[0096] In actual implementation, the adjacent strain gauges and the target strain gauge have the same orientation, i.e., the adjacent strain gauges and the target strain gauge are arranged in parallel, which can help ensure the consistency of the data monitoring mode between the adjacent strain gauges.

[0097] It should be noted that in the embodiment, the adjacent strain gauges and the target strain gauge are only used to distinguish different strain gauges, and are not used to limit the type and characteristics of the strain gauges.

[0098] In step 202, when there is an adjacent strain gauge, the wharf caisson is risk-verified based on the frequency data and the temperature data collected by the adjacent strain gauge.

[0099] In one example, the risk verification of the wharf caisson based on the frequency data and the temperature data collected by the adjacent strain gauge includes: determining whether the wharf caisson has a structural risk based on the frequency data and the temperature data collected by the adjacent strain gauge; if yes, generating a risk verification result that there is a structural risk; and if no, generating a risk verification result that there is no structural risk. The specific implementation can be similar to the above description of step 102, and will not be repeated here.

[0100] In another example, the risk verification of the wharf caisson based on the frequency data and the temperature data collected by the adjacent strain gauge includes: correcting the frequency data collected by the target strain gauge based on the frequency data collected by the adjacent strain gauge to obtain corrected frequency data; correcting the temperature data collected by the target strain gauge based on the temperature data collected by the adjacent strain gauge to obtain corrected temperature data; determining whether the wharf caisson has a structural risk based on the corrected frequency data and the corrected temperature data; if yes, generating a risk verification result that there is a structural risk; and if no, generating a risk verification result that there is no structural risk.

[0101] In one example, the frequency data collected by the target strain gauge is corrected based on the frequency data collected by the adjacent strain gauge to obtain corrected frequency data, including: determining the mean value of the frequency data collected by the adjacent strain gauge and the frequency data collected by the target strain gauge as the corrected frequency data.

[0102] Step 203, in the case where the risk verification result indicates that the wharf caisson has structural risks, outputting risk prompt information.

[0103] Optionally, in the case where the risk verification result indicates that the wharf caisson has no structural risks, it can be directly determined that no risk prompt information is outputted, or it can also be determined whether to output risk prompt information based on other manners.

[0104] In the above embodiment, in the case where it is determined that the wharf caisson has structural risks based on the data collected by the target strain gauge and there is an adjacent strain gauge of the target strain gauge, the wharf caisson is verified based on the frequency data and the temperature data collected by the adjacent strain gauge, and in the case where the risk verification result indicates that there are structural risks, the risk prompt information is outputted, which can help to improve the accuracy of the output of the risk prompt information.

[0105] Further, with reference to Figure 2 , in step 202, after the risk verification of the wharf caisson based on the frequency data and the temperature data collected by the adjacent strain gauge, it further includes:

[0106] Step 204, in the case where the risk verification result indicates that the wharf caisson has no structural risks, performing abnormality verification on the target strain gauge and the adjacent strain gauge.

[0107] In one example, the abnormality verification on the target strain gauge and the adjacent strain gauge includes: determining whether there is an abnormal strain gauge between the target strain gauge and the adjacent strain gauge; if yes, determining that the target strain gauge and / or the adjacent strain gauge has an abnormality; if no, determining that the target strain gauge and the adjacent strain gauge have no abnormality.

[0108] Optionally, the determination of whether there is an abnormal strain gauge between the target strain gauge and the adjacent strain gauge includes: determining whether the difference between the frequency data collected by the adjacent strain gauge and the frequency data collected by the target strain gauge is greater than a preset frequency data difference threshold; if yes, determining that there is an abnormal strain gauge between the target strain gauge and the adjacent strain gauge.

[0109] Further, in a case where the difference between the frequency data collected by the adjacent strain gauge and the frequency data collected by the target strain gauge is less than or equal to a preset frequency threshold, it is further determined whether the difference between the temperature data collected by the adjacent strain gauge and the temperature data collected by the target strain gauge is greater than a preset temperature data difference threshold; if yes, it is determined that there is an abnormal strain gauge between the target strain gauge and the adjacent strain gauge; if no, it is determined that there is no abnormal strain gauge between the target strain gauge and the adjacent strain gauge.

[0110] In another example, the abnormality checking of the target strain gauge and the adjacent strain gauge includes: analyzing the change of the frequency data collected by the target strain gauge and the change of the frequency data collected by the adjacent strain gauge to determine whether there is a change difference point; in a case where there is a change difference point, it is determined that the strain gauge corresponding to the change difference point is abnormal; in a case where there is no change difference point, it is determined that the target strain gauge and the adjacent strain gauge are both normal.

[0111] Step 205, in a case where the abnormality checking result indicates that the target strain gauge and the adjacent strain gauge are both normal, it is determined that the wharf caisson does not have a structural risk, and no risk prompt information is output.

[0112] Optionally, in a case where the abnormality checking result indicates that the adjacent strain gauge is abnormal, it is determined that the wharf caisson has a structural risk, and risk abnormality prompt information is output; in a case where the abnormality checking result indicates that the target strain gauge is abnormal, it is determined that the wharf caisson does not have a structural risk, and no risk prompt information is output.

[0113] Further, in a case where the abnormality checking result indicates that the strain gauge is abnormal, the abnormal strain gauge is marked to prompt maintenance of the abnormal strain gauge.

[0114] In the above further scheme, the abnormality checking of the target strain gauge and the adjacent strain gauge is performed in a case where the checking result indicates that the wharf caisson does not have a structural risk, and the wharf caisson is determined to not have a structural risk in a case where the abnormality checking result indicates that both are normal, which can help to reduce the influence of the abnormal strain gauge on the structural risk judgment, and thus can help to improve the accuracy of the structural risk judgment.

[0115] In some embodiments, the number of strain gauges includes two or more, and the reference Figure 3 Step 103, in a case where it is determined that the wharf caisson has a structural risk, risk prompt information is output, including the following steps:

[0116] Step 301, in a case where it is determined that the wharf caisson has a structural risk based on the frequency data and the temperature data collected by the target strain gauge, it is determined whether there is a symmetric strain gauge symmetrically arranged with the target risk strain gauge.

[0117] The symmetric arrangement refers to the strain gauge arranged on the opposite side or opposite face. For example, the target strain gauge is located on the left face of the wharf caisson, and the symmetric strain gauge is located on the right face of the wharf caisson. For another example, the target strain gauge is located on the first side of the wharf caisson, and the symmetric strain gauge is located on the second side opposite to the first side of the wharf caisson.

[0118] Specifically, there are various reasons leading to the structural risk, such as the inclination and torsion of the wharf caisson, and the data acquisition range of a single strain gauge is limited, so it is difficult to accurately determine the reason leading to the structural risk. Therefore, in the embodiment, in order to improve the accuracy of risk judgment, at least part of the strain gauges can be symmetrically arranged when the strain gauges are arranged, so as to determine or exclude the reason leading to the structural risk by comparing the data collected by the symmetrically arranged strain gauges, and then the reason leading to the structural risk can be accurately determined.

[0119] In step 302, in the case that the symmetric strain gauges exist, the predicted risk factor of the wharf caisson is determined in combination with the frequency data and the temperature data collected by the symmetric strain gauges.

[0120] Optionally, the predicted risk factor of the wharf caisson is determined in combination with the frequency data and the temperature data collected by the symmetric strain gauges, which includes: calculating the strain change amount corresponding to the symmetric strain gauges based on the frequency data and the temperature data collected by the symmetric strain gauges; determining whether the difference between the strain change amount corresponding to the symmetric strain gauges and the strain change amount corresponding to the target strain gauge is greater than the change amount difference threshold; if yes, determining that the predicted risk factor is the inclination or the uneven stress; and if no, determining that the predicted risk factor is the factor other than the inclination and the uneven stress, such as the torsion, crack, etc.

[0121] In actual implementation, the risk factor can also be predicted based on the change of the frequency data and the temperature data, and the prediction manner of the risk factor is not limited in the embodiment.

[0122] In step 303, the risk prompt information is output based on the predicted risk factor.

[0123] In one example, the risk prompt information includes the type of the predicted risk factor, such as the risk prompt information including “the wharf caisson may exist inclination or uneven stress”.

[0124] In the above embodiment, in the case that the wharf caisson exists the structural risk based on the data collected by the target strain gauge and the symmetric strain gauge corresponding to the target risk strain gauge exists, the predicted risk factor of the wharf caisson is determined in combination with the data collected by the symmetric strain gauge, and the risk prompt information is output based on the predicted risk factor, so as to assist in determining the reason leading to the structural risk in the case that the wharf caisson exists the structural risk.

[0125] Further, referenceFigure 4 The step 303 outputs the risk prompt information based on the predicted risk factor, including the following steps:

[0126] In step 401, it is determined whether the predicted risk factor includes an associated risk factor.

[0127] The associated risk factor is related to associated data collected by an associated sensor arranged on the wharf caisson, and the type of the associated risk factor is set based on the arrangement of the sensor in the wharf caisson. In actual implementation, the type of the associated sensor is different from the strain gauge, such as an inclination sensor, a displacement sensor, a stress-free meter, etc.

[0128] In one example, the predicted risk factor includes inclination, and the wharf caisson is provided with an inclination sensor, and accordingly, the associated risk factor includes an inclination angle collected by the inclination sensor.

[0129] In step 402, in the case where the predicted risk factor includes the associated risk factor, it is checked whether the wharf caisson has an associated risk corresponding to the associated risk factor based on the associated data.

[0130] The corresponding relationship between the associated data and the associated risk factor is set in advance.

[0131] In one example, the associated sensor includes an inclination sensor, and accordingly, the associated data includes an inclination angle, and it is determined whether the wharf caisson has an associated risk corresponding to the associated risk factor based on the associated data, including: determining whether the wharf caisson has inclination based on the inclination angle; if yes, it is determined that the wharf caisson has the associated risk; and if no, it is determined that the wharf caisson does not have the risk type corresponding thereto.

[0132] In step 403, in the case where it is determined that the wharf caisson has the associated risk, the risk prompt information is output based on the associated risk.

[0133] In one example, the associated risk is inclination, and at this time, the risk prompt information includes “the wharf caisson may have inclination”.

[0134] In the above embodiments, in the case where the predicted risk factor has the associated risk factor, it is determined whether the wharf caisson has an associated risk corresponding to the associated risk factor based on associated data corresponding to the associated risk factor, and in the case where it is determined that the wharf caisson has the associated risk, the risk prompt information is output based on the associated risk, which can help to check the risk factor in combination with the associated data, and thus can help to improve the accuracy of the risk prompt.

[0135] Further, with reference to Figure 4The step 402 further includes the following steps:

[0136] The step 404 includes determining whether the prediction risk factor includes a non-correlation risk factor other than the correlation risk factor in a case where it is determined that the wharf caisson does not have the correlation risk.

[0137] In one example, the prediction risk factor includes inclination or uneven force, the wharf caisson is provided with an inclination sensor, the correlation factor includes inclination, and the non-correlation factor includes uneven force.

[0138] The step 405 includes outputting risk prompt information based on the non-correlation risk factor in a case where the prediction risk factor includes the non-correlation risk factor.

[0139] In one example, the non-correlation factor includes uneven force, and the risk prompt information includes “the wharf caisson may have uneven force”.

[0140] In the further scheme, in a case where it is determined based on the correlation data that the wharf caisson does not have the correlation risk and the prediction risk factor includes the non-correlation risk factor, the risk prompt information is outputted based on the non-correlation risk factor, so that the specific risk type that the wharf caisson may have is indirectly determined by excluding the correlation risk, and the accuracy of the risk prompt can be improved.

[0141] Further, with reference to Figure 4 , the step 404 includes determining whether the prediction risk factor includes a non-correlation risk factor other than the correlation risk factor, including:

[0142] The step 406 includes determining whether the prediction risk factor is subjected to risk verification in a determination process of the prediction risk factor in a case where the prediction risk factor does not include the non-correlation risk factor.

[0143] In one example, the step of determining whether the prediction risk factor is subjected to risk verification in a determination process of the prediction risk factor includes determining that the prediction risk factor is subjected to risk verification in a case where there is an adjacent strain gauge corresponding to a target strain gauge, and a verification result obtained based on frequency data and temperature data collected by the adjacent strain gauge indicates that the wharf caisson has a structural risk. The specific implementation manner is described with reference to the steps 201 to 203.

[0144] The step 407 includes reducing a confidence degree of the correlation sensor in a case where the prediction risk factor is subjected to risk verification in a determination process of the prediction risk factor.

[0145] The confidence of the associated sensor is used to indicate the reliability of the data collected by the associated sensor, and the initial value of the confidence of the associated sensor is preset, and the confidence corresponding to the associated sensor is adjusted according to the actual monitoring situation in the actual monitoring process. For example, the initial value of the confidence corresponding to the associated sensor is 100%, and the decreasing amplitude is 5% each time.

[0146] Optionally, in the case where the prediction risk does not pass the risk check in the determination process, step 408 can be directly executed, or the risk prompt information can also not be output.

[0147] Step 408: Determine whether the confidence of the associated sensor is greater than the confidence corresponding to the target strain gauge.

[0148] The confidence of the strain gauge is used to indicate the reliability of the data collected by the strain gauge, and the confidence of the strain gauge is preset. Further, in the case where it is determined that the strain gauge is abnormal during use, the confidence corresponding to the strain gauge can be appropriately reduced. In actual implementation, the judgment manner of the strain gauge abnormality can be analogous to the specific content of step 204, and will not be described here.

[0149] Step 409: In the case where the confidence of the associated sensor is greater than the confidence corresponding to the target strain gauge, the risk prompt information is not output.

[0150] Specifically, in the case where the confidence of the associated sensor is greater than the confidence corresponding to the target strain gauge, it means that the terminal caisson is highly unlikely to have an associated risk factor, and since the prediction risk factor does not include a non-associated risk factor, the probability of the terminal caisson having a structural risk is low in this case, and therefore the risk prompt information is not output.

[0151] In one example, the confidence of the associated sensor is 85%, and the confidence corresponding to the target strain gauge is 80%, and in this case, the risk prompt information is not output.

[0152] Optionally, in the case where the confidence of the associated sensor is not greater than the confidence corresponding to the target strain gauge, the risk prompt information is output.

[0153] Optionally, in the case where the confidence of the associated sensor is greater than the confidence corresponding to the target strain gauge, the following steps are included: recording the risk number corresponding to the associated sensor; determining whether the risk number corresponding to the associated sensor is greater than a preset risk number threshold; in the case where the risk number corresponding to the associated sensor is greater than the risk number threshold, outputting the risk prompt information, reducing the confidence corresponding to the associated sensor, and recalculating the risk number corresponding to the associated sensor.

[0154] In the further scheme, in a case where it is determined based on the association data that the wharf caisson does not have an associated risk and the predicted risk factor includes a non-associated risk factor, the confidence of the associated sensor is adjusted based on whether a risk check is passed in a determination process of the predicted risk factor, and in a case where the confidence of the associated sensor is greater than the confidence corresponding to the target strain gauge, the risk prompt information is not output. In this way, the accuracy of the output of the risk prompt information can be further improved.

[0155] The embodiment of the present application further discloses a wharf caisson structure monitoring system. Referring to Figure 5 , the wharf caisson structure monitoring system comprises at least one strain gauge 510 arranged on the wharf caisson and a controller 520 connected with the strain gauge.

[0156] The controller 520 is configured to execute the wharf caisson structure monitoring method provided by the method embodiment.

[0157] In one example, referring to Figures 6a to 6d , Figure 6a is a layout diagram of the strain gauge 510 on the front wall (rear wall), Figure 6b is a layout diagram of the strain gauge 510 on the left side wall, Figure 6c is a layout diagram of the strain gauge 510 on the bottom plate, Figure 6d is a layout diagram of the strain gauge 510 on the outer toe.

[0158] In some embodiments, the wharf caisson structure monitoring system further comprises an associated sensor 530 arranged on the wharf caisson, and the associated sensor 530 is connected with the controller 520. The associated sensor 530 can include at least one of an inclination sensor, a displacement sensor, a stress-free gauge and other sensors that can be used to collect associated data, and the associated information is used to determine whether the wharf caisson has a structural risk.

[0159] The embodiment of the present application further provides an electronic device. As shown in Figure 7 , the electronic device 600 shown in Figure 7 comprises a processor 601 and a memory 603. The processor 601 and the memory 603 are connected, such as through a bus 602. Optionally, the electronic device 600 can further comprise a transceiver 604. It should be noted that the transceiver 604 is not limited to one in actual application, and the structure of the electronic device 600 does not constitute a limitation on the embodiment of the present application.

[0160] The processor 601 can be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), or other programmable logic device, transistor logic device, hardware component, or any combination thereof. It can implement or execute various exemplary logical blocks, modules, and circuits described in conjunction with the disclosure. The processor 601 can also be a combination of computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0161] The bus 602 can include a path for transmitting information between the above-mentioned components. The bus 602 can be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, or the like. The bus 602 can be divided into an address bus, a data bus, and the like. For ease of representation, Figure 7 In the figure, only one thick line is used to represent the bus, but it does not mean that there is only one bus or only one type of bus.

[0162] The memory 603 can be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, an EEPROM (Electrically Erasable Programmable Read Only Memory), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program codes in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0163] The memory 603 is used to store application program codes for implementing the scheme of the present application, and is controlled by the processor 601 to execute. The processor 601 is used to execute the application program codes stored in the memory 603 to realize the content shown in the foregoing method embodiments.

[0164] The electronic device includes, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a PDA (Personal Digital Assistant), a PAD (Tablet Personal Computer), and the like, and a fixed terminal such as a digital TV, a desktop computer, and the like. It can also be a server, and the like.Figure 7 The electronic device shown is merely an example and should not bring any limitation to the function and scope of use of the embodiments of the present application.

[0165] It should be understood that although the steps in the flowcharts of the drawings are shown in sequence according to the direction of the arrows, the steps are not necessarily executed in sequence according to the direction of the arrows. Unless explicitly stated herein, the execution of the steps is not strictly limited in sequence, and they can be executed in other sequences.

[0166] The above is only some embodiments of the present application, and it should be pointed out that for those skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, which should be considered as the protection scope of the present application.

Claims

1. A method of monitoring a wharf caisson structure, characterized by, The method comprises: acquiring frequency data and temperature data collected by a strain gauge arranged on a wharf caisson; determining whether the wharf caisson has a structural risk based on the frequency data and the temperature data; outputting risk prompt information in a case where it is determined that the wharf caisson has a structural risk; the number of the strain gauges comprises two or more, and the outputting of the risk prompt information in the case where it is determined that the wharf caisson has a structural risk comprises: in a case where it is determined that the wharf caisson has a structural risk based on frequency data and temperature data collected by a target strain gauge, determining whether there is a symmetric strain gauge symmetrically arranged with the target strain gauge; in a case where the symmetric strain gauge exists, determining a predicted risk factor of the wharf caisson in combination with frequency data and temperature data collected by the symmetric strain gauge; outputting risk prompt information based on the predicted risk factor; the outputting of the risk prompt information based on the predicted risk factor comprises: determining whether the predicted risk factor comprises a correlation risk factor related to correlation data collected by a correlation sensor arranged on the wharf caisson; in a case where the predicted risk factor comprises the correlation risk factor, verifying whether the wharf caisson has an associated risk corresponding to the correlation risk factor based on the correlation data; in a case where it is determined that the wharf caisson has the associated risk, outputting risk prompt information based on the associated risk; after the verifying of whether the wharf caisson has an associated risk corresponding to the correlation risk factor based on the correlation data, the method further comprises: in a case where it is determined that the wharf caisson does not have the associated risk, determining whether the predicted risk factor comprises a non-correlation risk factor other than the correlation risk factor; in a case where the predicted risk factor comprises the non-correlation risk factor, outputting risk prompt information based on the non-correlation risk factor; the determining of whether the predicted risk factor comprises the non-correlation risk factor other than the correlation risk factor comprises: in a case where the predicted risk factor does not comprise the non-correlation risk factor, determining whether risk verification is performed in a process of determining the predicted risk factor; in a case where risk verification is performed in the process of determining the predicted risk factor, reducing a confidence degree corresponding to the correlation sensor; determining whether the confidence degree of the correlation sensor is greater than a confidence degree corresponding to the target strain gauge; in a case where the confidence degree of the correlation sensor is greater than the confidence degree corresponding to the target strain gauge, not outputting the risk prompt information.

2. The method of claim 1, wherein, the number of the strain gauges comprises two or more, and the outputting of the risk prompt information in the case where it is determined that the wharf caisson has a structural risk comprises: in a case where it is determined that the wharf caisson has a structural risk based on frequency data and temperature data collected by a target strain gauge, determining whether there is an adjacent strain gauge with a distance less than a preset distance threshold from the target strain gauge; in a case where the adjacent strain gauge exists, performing risk verification on the wharf caisson based on frequency data and temperature data collected by the adjacent strain gauge; In a case where the risk checking result indicates that the wharf caisson has structural risks, the risk prompt information is output.

3. The method of claim 2, wherein, After the risk checking on the wharf caisson based on the frequency data and the temperature data collected by the adjacent strain gauge, the method further comprises: In a case where the risk checking result indicates that the wharf caisson has no structural risks, performing abnormality checking on the target strain gauge and the adjacent strain gauge; In a case where the abnormality checking result indicates that the target strain gauge and the adjacent strain gauge have no abnormality, determining that the wharf caisson has no structural risks, and not outputting the risk prompt information.

4. The method of claim 1, wherein, The method for determining whether the wharf caisson has structural risks based on the frequency data and the temperature data comprises: calculating a strain variation based on the frequency data and the temperature data; determining whether the wharf caisson has structural risks based on the strain variation; The strain variation is calculated by the following formula: ε=G×C×(R1-R0)+(Y1-Y2)×(T1-T0) wherein, ε is the strain variation; G is an instrument standard coefficient; C is an average correction coefficient corresponding to the strain gauge; R1 is the frequency data; R0 is initial frequency data set in advance; Y1 is a temperature expansion coefficient of a steel string; Y2 is a temperature expansion coefficient of concrete; T1 is the temperature data; and T0 is initial temperature set in advance.

5. A wharf caisson structure monitoring system characterized by, The system comprises at least one strain gauge arranged on the wharf caisson and a controller connected with the strain gauge; The controller is configured to execute the wharf caisson structure monitoring method according to any one of claims 1-4.

6. An electronic device, comprising: The electronic device comprises: at least one processor; a memory; at least one application program, wherein the at least one application program is stored in the memory and configured to be executed by the at least one processor, and the at least one application program is configured to execute the wharf caisson structure monitoring method according to any one of claims 1-4.

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