Wharf caisson structure monitoring method, system and equipment

Abstract

The invention 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 acquired by strain gauges arranged on a wharf caisson; determining whether the wharf caisson has a structural risk based on the frequency data and the temperature data; and under the condition of determining that the wharf caisson has the structural risk, outputting risk prompt information. According to the technical scheme, the structure risk of the wharf caisson can be judged according to the frequency data and the temperature data collected by the strain gauges arranged on the wharf caisson, and the abnormal prompt information is output under the condition 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 dock caisson monitoring, and in particular to a method, system and equipment for monitoring a dock caisson structure. Background Art

[0002] Caisson is an important hydraulic structure, mainly used in the construction of docks and breakwaters. Caisson is generally prefabricated with steel bars and concrete, with partitions inside. During the construction process, the caisson will be filled with sand or stone, and the top will be covered with a cover plate to form a load-bearing and vertical wall structure.

[0003] Since the wharf caisson will be immersed in water after installation and serve as a pile foundation to bear the weight of the wharf, it is necessary to monitor the structural status of the wharf caisson in order to carry out targeted operation and maintenance of the wharf caisson and thus increase the service life of the wharf. Summary of the invention

[0004] In order to monitor the structural status of a dock caisson, the present application provides a method, system and equipment for monitoring the structure of a dock caisson.

[0005] In the first aspect, the present application provides a method for monitoring a wharf caisson structure, which adopts the following technical solution: A method for monitoring a wharf caisson structure, the method comprising: Obtain frequency data and temperature data collected by strain gauges arranged on the wharf caisson; determining whether the wharf caisson has a structural risk based on the frequency data and the temperature data; When it is determined that the wharf caisson has structural risks, risk warning information is output.

[0006] By adopting the above technical solution, the structural risk of the wharf caisson can be judged through the frequency data and temperature data collected by the strain gauges installed on the wharf caisson, and abnormal prompt information can be output when the structural risk is judged, which can help monitor the structural status of the wharf caisson.

[0007] Optionally, the number of the strain gauges includes more than two, and when it is determined that the wharf caisson has a structural risk, outputting risk warning information includes: In the case where it is determined that the wharf caisson has a structural risk based on the frequency data and temperature data collected by the target strain gauge, determining whether there is an adjacent strain gauge whose distance from the target strain gauge is less than a preset distance threshold; In the case where the adjacent strain gauge exists, performing risk verification on the dock caisson based on the frequency data and temperature data collected by the adjacent strain gauge; When the risk verification result indicates that the wharf caisson has structural risk, the risk warning information is output.

[0008] By adopting the above technical solution, when it is determined based on the data collected by the target strain gauge that there is a structural risk in the wharf caisson and there are adjacent strain gauges of the target strain gauge, the wharf caisson will be risk-checked based on the frequency data and temperature data collected by the adjacent strain gauges, and when the risk check result indicates the existence of a structural risk, risk warning information will be output, which can help improve the accuracy of the output of the risk warning information.

[0009] Optionally, after performing risk verification on the wharf caisson based on the frequency data and temperature data collected by the adjacent strain gauges, the method further includes: When the risk verification result indicates that the wharf caisson does not have a structural risk, performing an abnormality verification on the target strain gauge and the adjacent strain gauges; When the abnormality check result indicates that neither the target strain gauge nor the adjacent strain gauge has abnormality, it is determined that there is no structural risk in the wharf caisson, and the risk warning information is not output.

[0010] By adopting the above technical solution, it can help reduce the impact of strain gauge abnormalities on structural risk judgment, and further help improve the accuracy of structural risk judgment.

[0011] Optionally, the number of the strain gauges includes more than two, and when it is determined that the wharf caisson has a structural risk, risk warning information is output, including: In the case where it is determined that the wharf caisson has a structural risk based on the frequency data and temperature data collected by the target strain gauge, determining whether there is a symmetrical strain gauge symmetrically arranged with the target risk strain gauge; In the presence of the symmetrical strain gauge, determining the predicted risk factor of the dock caisson in combination with the frequency data and temperature data collected by the symmetrical strain gauge; Output risk warning information based on the predicted risk factors.

[0012] By adopting the above technical solution, when it is determined that the wharf caisson has a structural risk based on the data collected by the target strain gauge and there is a symmetrical strain gauge corresponding to the target risk strain gauge, the predicted risk factor of the wharf caisson can be determined in combination with the data collected by the symmetrical strain gauge, and risk warning information can be output based on the predicted risk factor. In this way, when it is determined that the wharf caisson has a structural risk, the cause of the structural risk can be determined.

[0013] Optionally, the outputting risk warning information based on the predicted risk factors includes: determining whether the predicted risk factor includes an associated risk factor, the associated risk factor being related to associated data collected by an associated sensor disposed on the wharf caisson; In the case where the predicted risk factor includes the associated risk factor, verifying whether the dock caisson has an associated risk corresponding to the associated risk factor based on the associated data; When it is determined that the dock caisson has the associated risk, risk warning information is output based on the associated risk.

[0014] By adopting the above technical solution, when it is predicted that there are associated risk factors in the risk factors, it can be determined whether the wharf caisson has associated risks corresponding to the associated risk factors based on the associated data corresponding to the associated risk factors, and when it is determined that there are associated risks in the wharf caisson, risk warning information can be output based on the associated risks. This can help to check the risk factors in combination with the associated data, and further help to improve the accuracy of the risk warnings.

[0015] Optionally, after verifying whether the dock caisson has associated risks corresponding to associated risk factors based on the associated data, the method further includes: In the case where it is determined that there is a dock caisson and there is no associated risk, determining whether the predicted risk factors include non-associated risk factors other than the associated risk factors; In a case where the predicted risk factors include the non-correlated risk factors, risk warning information is output based on the non-correlated risk factors.

[0016] By adopting the above technical solution, the specific risk type that may exist in the wharf caisson can be indirectly determined by excluding associated risks, which can help improve the accuracy of risk warnings.

[0017] Optionally, determining whether the predicted risk factors include non-associated risk factors other than the associated risk factors includes: In a case where the predicted risk factors do not include the non-correlated risk factors, determining whether risk verification has been performed in the process of determining the predicted risk factors; In the process of determining the predicted risk factor, when risk verification is performed, reducing the confidence level corresponding to the associated sensor; Determining whether the confidence level of the associated sensor is greater than the confidence level corresponding to the target strain gauge; When the confidence level of the associated sensor is greater than the confidence level corresponding to the target strain gauge, the risk warning information is not output.

[0018] By adopting the above technical solution, when it is determined based on the associated data that there is no associated risk for the wharf caisson and the predicted risk factors include non-associated risk factors, the confidence of the associated sensor can be adjusted based on whether risk verification has been carried out during the determination of the predicted risk factors, and when the confidence of the associated sensor is greater than the confidence corresponding to the target strain gauge, the risk warning information is not output, which can help to further improve the accuracy of the output of the risk warning information.

[0019] Optionally, determining whether the wharf caisson has a structural risk based on the frequency data and the temperature data includes: Calculating a strain variation based on the frequency data and the temperature data; Determining whether the wharf caisson has structural risk based on the strain variation; The strain change is calculated by the following formula: ε=G×C×(R1-R0)+(Y1-Y2)×(T1-T0) Among them, ε is the strain change; G is the instrument standard coefficient; C is the average correction coefficient corresponding to the strain gauge; R1 is the frequency data; R0 is the preset initial frequency data; Y1 is the temperature expansion coefficient of the steel string; Y2 is the temperature expansion coefficient of concrete; T1 is the temperature data; T0 is the preset initial temperature.

[0020] In the second aspect, the present application provides a dock caisson structure monitoring system, which adopts the following technical solution: A dock caisson structure monitoring system, the system comprising at least one strain gauge arranged on the dock caisson, and a controller connected to the strain gauge signal; The controller is used to execute any one of the dock caisson structure monitoring methods provided in the first aspect.

[0021] In a third aspect, the present application provides a dock caisson structure monitoring system, which adopts the following technical solution: An electronic device, comprising: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute any one of the dock caisson structure monitoring methods provided in the first aspect.

[0022] In summary, the present application includes at least one of the following beneficial technical effects: 1. The structural risk of the wharf caisson can be judged by the frequency data and temperature data collected by the strain gauge installed on the wharf caisson, and abnormal prompt information can be output when the structural risk is judged, which can help monitor the structural status of the wharf caisson; 2. Since it is determined based on the data collected by the target strain gauge that the wharf caisson has a structural risk and there are adjacent strain gauges of the target strain gauge, a risk check will be performed on the wharf caisson based on the frequency data and temperature data collected by the adjacent strain gauges, and when the risk check result indicates that there is a structural risk, risk warning information will be output, which can help improve the accuracy of the output of the risk warning information. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a flow chart of a method for monitoring a wharf caisson structure provided in an embodiment of the present application; Figure 2 It is a flowchart of a risk verification method provided in an embodiment of the present application; Figure 3 It is a flowchart of a method for generating risk warning information provided in an embodiment of the present application; Figure 4 It is a flowchart of another method for generating risk warning information provided in an embodiment of the present application; Figure 5 It is a structural schematic diagram of a dock caisson structure monitoring system provided by an embodiment of the present application; Figures 6a to 6d is a schematic diagram of a strain gauge arrangement method provided in an embodiment of the present application; Figure 7 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figure 1-7 It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0025] The present application embodiment discloses a method for monitoring a wharf caisson structure. Figure 1 , the wharf caisson structure monitoring method includes the following steps: Step 101, obtaining frequency data and temperature data collected by strain gauges arranged on the wharf caisson.

[0026] The strain gauge is used to sense the deformation of the wharf caisson. Specifically, the strain gauge uses an embedded vibrating wire strain gauge, which consists of a strain gauge body and a coil, and has a built-in 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 uses a BGK4200 series embedded vibrating wire strain gauge.

[0027] In one example, the frequency data is represented by a frequency modulus, and the frequency data is calculated by the following formula: F=f 2 / 1000 Among them, F is the frequency modulus, that is, the frequency data, the unit is word (Digit); f is the frequency collected by the vibrating string sensor, the unit is Hertz (HZ).

[0028] In another example, the temperature data is expressed as actual temperature, and the temperature data is calculated by the following formula: Wherein, T is the actual temperature, i.e., temperature data, in degrees Celsius (℃); R is the resistance of the thermistor of the temperature sensor, and LnR is the natural logarithm of the resistance; A, B, and C are preset values. In an example, A is 1.4051×10 -3 , B=2.369×10 -4 , C = 1.019 × 10 -7 .

[0029] Optionally, the number of strain gauges can be one, or more than two, and the installation position of the strain gauge can be selected according to the structural characteristics of the wharf caisson. In one example, strain gauges are arranged at the mid-span (middle of the wall panel) and the support (vertical intersection of the wall) of the wharf caisson. Specifically, corresponding strain gauges can be arranged at at least one position such as the outer side of the front vertical plate, the outer side of the rear vertical plate, the outer side of the side plate, the bottom plate, and the outer toe bottom plate of the wharf caisson. In addition, the direction of the strain gauge can be set according to the actual monitoring needs, such as: towards the X direction or towards the Y direction.

[0030] Correspondingly, when the number of strain gauges includes more than two, the frequency data and temperature data collected by each strain gauge are acquired respectively.

[0031] Step 102: determine whether there is a structural risk for the dock caisson based on the frequency data and the temperature data.

[0032] Optionally, determining whether there is a structural risk for the wharf caisson based on the frequency data and the temperature data includes: calculating a strain change based on the frequency data and the temperature data; and determining whether there is a structural risk for the wharf caisson based on the strain change.

[0033] In one example, the strain change is calculated by the following formula: ε=G×C×(R1-R0)+(Y1-Y2)×(T1-T0) Among them, ε is the strain change; G is the instrument standard coefficient, for example: G is 3.15με / word; C is the average correction coefficient corresponding to the strain gauge; R1 is the frequency data; R0 is the preset initial frequency data, for example: the initial frequency data is determined based on the reading value of the strain gauge 9-24 hours after it is buried 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 preset initial temperature.

[0034] In actual implementation, the strain variation may be calculated based on other methods, and this embodiment does not limit the calculation method of the strain calculation amount.

[0035] Optionally, determining whether there is a structural risk for the wharf caisson based on the strain change includes: determining whether the strain change is greater than a preset change threshold; if so, determining that there is a structural risk for the wharf caisson; if not, determining that there is no structural risk for the wharf caisson.

[0036] Furthermore, when it is determined that the strain variation is not greater than the variation threshold, it can be further determined whether the variation amplitude of the strain variation exceeds the preset amplitude threshold; if so, 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. This can help to judge the structural abnormality of the wharf caisson based on the abnormal change of the variation amplitude.

[0037] In one example, determining whether a wharf caisson has structural risk based on the strain variation includes: determining stress based on the strain variation; and determining whether a wharf caisson has structural risk based on the relationship between the stress and a stress threshold. The stress threshold may be fixed or may be set based on the service life of the wharf caisson.

[0038] In one example, stress is calculated by: δ=ε×E Among them, δ is stress, the unit is pa, and the commonly used unit is MPa; ε is the strain change, the unit is strain; E is the elastic modulus of concrete, the unit is MPa / ε.

[0039] Optionally, when the number of strain gauges includes more than two, for each strain gauge, it is determined whether there is a structural abnormality in the dock caisson based on frequency data and temperature data collected by the strain gauge.

[0040] Step 103: when it is determined that there is a structural risk in the wharf caisson, output risk warning information.

[0041] Optionally, the risk warning information includes a strain gauge identifier corresponding to the strain gauge, which can help locate the structural risk of the wharf caisson.

[0042] The implementation principle of the dock caisson structure monitoring method provided in the embodiment of the present application is: obtaining frequency data and temperature data collected by strain gauges arranged on the dock caisson; determining whether there is a structural risk in the dock caisson based on the frequency data and temperature data; and outputting risk warning information when it is determined that there is a structural risk in the dock caisson. By adopting the above technical solution, the structural risk of the dock caisson can be judged by the frequency data and temperature data collected by the strain gauges arranged on the dock caisson, and abnormal warning information can be output when the structural risk is judged, which can help monitor the structural status of the dock caisson.

[0043] In some embodiments, the number of strain gauges includes more than two, referring to Figure 2 In the above step 103, when it is determined that there is a structural risk in the wharf caisson, the risk warning information is output, including: Step 201 : when it is determined that the wharf caisson has a structural risk based on the frequency data and temperature data collected by the target strain gauge, it is determined whether there is an adjacent strain gauge whose distance to the target strain gauge is less than a preset distance threshold.

[0044] The preset distance threshold is the maximum spacing value between two adjacent strain gauges. Specifically, since the strain gauge may fail during use, in order to help improve the accuracy of risk judgment, in this embodiment, multiple adjacent strain gauges may be deployed at some important monitoring locations to detect strain gauge failures through data comparison, which can help improve the accuracy of risk judgment.

[0045] In one example, the preset distance threshold is 30 cm.

[0046] In actual implementation, the adjacent strain gauges and the target strain gauge have the same orientation, that is, the adjacent strain gauges and the target strain gauge are arranged in parallel, which can help ensure the consistency of the data monitoring method between the adjacent strain gauges.

[0047] It should be additionally explained that, in the present embodiment, the adjacent strain gauges and the target strain gauges are only used to distinguish different strain gauges, and are not used to limit the types, characteristics, etc. of the strain gauges.

[0048] Step 202: In the case where there are adjacent strain gauges, risk verification is performed on the wharf caisson based on frequency data and temperature data collected by the adjacent strain gauges.

[0049] In one example, risk verification of a wharf caisson is performed based on frequency data and temperature data collected by adjacent strain gauges, including: determining whether there is a structural risk for the wharf caisson based on the frequency data and temperature data collected by adjacent strain gauges; if so, generating a risk verification result that there is a structural risk; if not, generating a risk verification result that there is no structural risk. The specific implementation method can be analogous to the introduction to step 102 above, and this embodiment will not be repeated here.

[0050] In another example, a risk check of a wharf caisson is performed based on frequency data and temperature data collected by adjacent strain gauges, including: correcting frequency data collected by a target strain gauge based on frequency data collected by the adjacent strain gauges to obtain corrected frequency data; correcting temperature data collected by the target strain gauge based on temperature data collected by the adjacent strain gauges to obtain corrected temperature data; determining whether there is a structural risk in the caisson wharf based on the corrected frequency data and the corrected temperature data; if so, generating a risk check result of a structural risk; if not, generating a risk check result of a non-structural risk.

[0051] In one example, correcting the frequency data collected by the target strain gauge based on the frequency data collected by the adjacent strain gauge to obtain the corrected frequency data includes: determining the average 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.

[0052] Step 203: when the risk verification result indicates that the wharf caisson has structural risk, output risk warning information.

[0053] Optionally, when the risk verification result indicates that there is no structural risk in the wharf caisson, it may be directly determined not to output the risk warning information, or it may be determined whether to output the risk warning information based on other methods.

[0054] In the above implementation, when it is determined based on the data collected by the target strain gauge that there is a structural risk in the wharf caisson and there are adjacent strain gauges of the target strain gauge, a risk check will be performed on the wharf caisson based on the frequency data and temperature data collected by the adjacent strain gauges, and when the risk check result indicates the existence of a structural risk, risk warning information will be output, which can help improve the accuracy of the output of the risk warning information.

[0055] For further information, please refer to Figure 2 In step 202, after performing risk verification on the wharf caisson based on the frequency data and temperature data collected by adjacent strain gauges, the method further includes: Step 204 , when the risk verification result indicates that there is no structural risk in the wharf caisson, an abnormality verification is performed on the target strain gauge and the adjacent strain gauges.

[0056] In one example, performing an abnormality check on a target strain gauge and an adjacent strain gauge includes: determining whether there is an abnormal strain gauge between the target strain gauge and the adjacent strain gauge; if so, determining that an abnormality exists in the target strain gauge and / or the adjacent strain gauge; if not, determining that neither the target strain gauge nor the adjacent strain gauge has an abnormality.

[0057] Optionally, determining 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 so, determining that there is an abnormal strain gauge between the target strain gauge and the adjacent strain gauge.

[0058] Furthermore, when 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 the 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 the preset temperature data difference threshold; if so, it is determined that there is an abnormal strain gauge between the target strain gauge and the adjacent strain gauge; if not, it is determined that there is no abnormal strain gauge between the target strain gauge and the adjacent strain gauge.

[0059] In another example, an abnormality check is performed on a target strain gauge and an adjacent strain gauge, including: analyzing changes in frequency data historically collected by the target strain gauge and changes in frequency data historically collected by the adjacent strain gauge to determine whether there is a change difference point; if there is a change difference point, determining that the strain gauge corresponding to the change difference point has an abnormality; if there is no change difference point, determining that neither the target strain gauge nor the adjacent strain gauge has an abnormality.

[0060] Step 205: when the abnormality check result indicates that the target strain gauge and the adjacent strain gauges are not abnormal, it is determined that there is no structural risk in the wharf caisson, and no risk warning information is output.

[0061] Optionally, when the abnormal verification result indicates that an adjacent strain gauge has an abnormality, it is determined that the wharf caisson has a structural risk, and risk abnormality prompt information is output; when the abnormal verification result indicates that a target strain gauge has an abnormality, it is determined that the wharf caisson has no structural risk, and no risk warning information is output.

[0062] Furthermore, when the abnormality check result indicates that the strain gauge is abnormal, the strain gauge with the abnormality is marked as abnormal to prompt maintenance of the strain gauge with the abnormality.

[0063] In the above further scheme, when the verification results indicate that there is no structural risk to the wharf caisson, the target strain gauge and the adjacent strain gauges are subjected to abnormality verification, and when the abnormality verification results indicate that there is no abnormality, it is determined that there is no structural risk to the wharf caisson. This can help reduce the impact of the strain gauge abnormality on the structural risk judgment, and further help improve the accuracy of the structural risk judgment.

[0064] In some embodiments, the number of strain gauges includes more than two, referring to Figure 3 Step 103, when it is determined that there is a structural risk in the wharf caisson, outputting risk warning information includes the following steps: Step 301 : when it is determined that the wharf caisson has a structural risk based on the frequency data and temperature data collected by the target strain gauge, it is determined whether there is a symmetrical strain gauge symmetrically arranged with the target risk strain gauge.

[0065] Among them, symmetrical arrangement refers to strain gauges arranged on opposite sides or opposite sides. For example: if the target strain gauge is located on the left side of the dock caisson, the symmetrical strain gauge is located on the right side of the dock caisson. For another example: if the target strain gauge is located on the first side of the dock caisson, the symmetrical strain gauge is located on the second side of the dock caisson opposite to the first side.

[0066] Specifically, there are many reasons that may lead to structural risks, such as tilting and twisting of the wharf caisson, and the data collection range of a single strain gauge is limited, making it difficult to accurately determine the cause of the structural risk. Based on this, in this embodiment, in order to help improve the accuracy of risk judgment, at least part of the strain gauges may be symmetrically arranged when the strain gauges are arranged, so that the data collected by the symmetrically arranged strain gauges can be compared to determine or eliminate the causes of the structural risks, which can help accurately determine the causes of the structural risks.

[0067] Step 302: In the case where there is a symmetrical strain gauge, the predicted risk factor of the wharf caisson is determined by combining the frequency data and temperature data collected by the symmetrical strain gauge.

[0068] Optionally, the predicted risk factors of the wharf caisson are determined in combination with the frequency data and temperature data collected by the symmetrical strain gauge, including: calculating the strain change corresponding to the symmetrical strain gauge based on the frequency data and temperature data collected by the symmetrical strain gauge; determining whether the difference between the strain change corresponding to the symmetrical strain gauge and the strain change corresponding to the target strain gauge is greater than a change difference threshold; if so, determining that the predicted risk factor is tilt or uneven force; if not, determining that the predicted risk factor is a factor other than tilt and uneven force, such as torsion, cracks, etc.

[0069] In actual implementation, risk factors may also be predicted based on changes in frequency data and temperature data. This embodiment does not limit the prediction method of risk factors.

[0070] Step 303: output risk warning information based on the predicted risk factors.

[0071] In one example, the risk warning information includes the type of predicted risk factors, for example: the risk warning information includes "the dock caisson may be tilted or unevenly stressed."

[0072] In the above embodiment, when it is determined that the wharf caisson has a structural risk based on the data collected by the target strain gauge and there is a symmetrical strain gauge corresponding to the target risk strain gauge, the predicted risk factor of the wharf caisson is determined in combination with the data collected by the symmetrical strain gauge, and risk warning information is output based on the predicted risk factor. In this way, when it is determined that the wharf caisson has a structural risk, it can assist in determining the cause of the structural risk.

[0073] For further reference, Figure 4 The above step 303, outputting risk warning information based on the predicted risk factors, includes the following steps: Step 401, determining whether the predicted risk factors include associated risk factors.

[0074] Among them, the associated risk factors are related to the associated data collected by the associated sensors set on the wharf caisson, and the type of the associated risk factors is set based on the setting of the sensors in the wharf caisson. In actual implementation, the type of the associated sensor is different from the strain gauge, for example: the associated sensor is an inclination sensor, a displacement sensor, a stress-free gauge, etc.

[0075] In one example, the predicted risk factor includes tilt, and a tilt sensor is provided on the dock caisson, and accordingly, the associated risk factor includes the tilt angle collected by the tilt sensor.

[0076] Step 402: When the predicted risk factor includes an associated risk factor, verify whether the dock caisson has an associated risk corresponding to the associated risk factor based on the associated data.

[0077] Among them, the corresponding relationship between the associated data and the associated risk factors is preset.

[0078] In one example, the associated sensor includes a tilt sensor, and correspondingly, the associated data includes a tilt angle. Whether there is an associated risk corresponding to an associated risk factor for the wharf caisson based on the associated data includes: determining whether the wharf caisson is tilted based on the tilt angle; if so, determining that there is an associated risk for the wharf caisson; if not, determining that there is no risk type corresponding to the wharf caisson.

[0079] Step 403: when it is determined that there is an associated risk for the wharf caisson, risk warning information is output based on the associated risk.

[0080] In one example, the associated risk is tilting, and the risk warning information includes "the dock caisson may tilt."

[0081] In the above implementation, when it is predicted that there are associated risk factors in the risk factors, it can be determined whether the wharf caisson has associated risks corresponding to the associated risk factors based on the associated data corresponding to the associated risk factors, and when it is determined that there are associated risks in the wharf caisson, risk warning information can be output based on the associated risks. This can help to check the risk factors in combination with the associated data, and further help to improve the accuracy of the risk warnings.

[0082] For further information, please refer to Figure 4 In the above step 402, after verifying whether the dock caisson has associated risks corresponding to associated risk factors based on the associated data, the following steps are also included: Step 404: when it is determined that there is no associated risk for the wharf caisson, determine whether the predicted risk factors include non-associated risk factors other than the associated risk factors.

[0083] In one example, the predicted risk factors include: tilt or uneven force. A tilt sensor is provided on the dock caisson. In this case, the associated factors include tilt, and correspondingly, the unassociated factors include uneven force.

[0084] Step 405: when the predicted risk factors include non-correlated risk factors, output risk warning information based on the non-correlated risk factors.

[0085] In one example, the non-correlated factors include uneven force. In this case, the risk warning information includes "the dock caisson may have uneven force."

[0086] In the above further scheme, when it is determined based on the associated data that there is no associated risk for the wharf caisson and the predicted risk factors include non-associated risk factors, risk warning information is output based on the non-associated risk factors. In this way, the specific risk type that may exist in the wharf caisson can be indirectly determined by excluding associated risks, which can help improve the accuracy of risk warnings.

[0087] For further reference, Figure 4 In step 404, determining whether the predicted risk factors include non-correlated risk factors other than the correlated risk factors includes: Step 406: When the predicted risk factors do not include non-correlated risk factors, determine whether the predicted risk factors have been subjected to risk verification during the determination process.

[0088] In one example, determining whether the predicted risk factor has been subjected to risk verification during the determination process includes: determining that the predicted risk factor has been subjected to risk verification when there is an adjacent strain gauge corresponding to the target strain gauge and a verification result based on frequency data and temperature data collected by the adjacent strain gauge indicates that there is a structural risk in the wharf caisson. For specific implementation methods, see steps 201 to 203.

[0089] Step 407 : in the process of determining the predicted risk factor, after the risk verification, reduce the confidence level corresponding to the associated sensor.

[0090] The confidence of the associated sensor is used to indicate the reliability of the data collected by the associated sensor. The initial value of the confidence of the associated sensor is preset, and the confidence corresponding to the associated sensor will be adjusted according to the actual monitoring situation during the actual monitoring process. For example, the initial value of the confidence corresponding to the associated sensor is 100%, and the amplitude of each reduction is 5%.

[0091] Optionally, when the predicted risk has not been subjected to risk verification during the determination process, step 408 may be directly executed, or risk warning information may not be output.

[0092] Step 408 , determining whether the confidence level of the associated sensor is greater than the confidence level corresponding to the target strain gauge.

[0093] The confidence level of the strain gauge is used to indicate the reliability of the data collected by the strain gauge, and the confidence level of the strain gauge is preset. Furthermore, when it is determined that the strain gauge is abnormal during use, the confidence level corresponding to the strain gauge can be appropriately reduced. In actual implementation, the method for determining the abnormality of the strain gauge can be analogous to the specific content of step 204 above, which will not be repeated here.

[0094] Step 409: when the confidence level of the associated sensor is greater than the confidence level corresponding to the target strain gauge, no risk warning information is output.

[0095] Specifically, when the confidence of the associated sensor is greater than the confidence corresponding to the target strain gauge, it means that there is a high probability that there are no associated risk factors for the wharf caisson. Since the predicted risk factors do not include non-associated risk factors, the probability of structural risks in the wharf caisson is low in this case, so no risk warning information is output.

[0096] In one example, the confidence level of the associated sensor is 85%, and the corresponding confidence level of the target strain gauge is 80%. In this case, no risk warning information is output.

[0097] Optionally, when the confidence level of the associated sensor is not greater than the confidence level corresponding to the target strain gauge, risk warning information is output.

[0098] Optionally, when the confidence level of the associated sensor is greater than the confidence level corresponding to the target strain gauge, the method includes: recording the number of risk times corresponding to the associated sensor once; determining whether the number of risk times corresponding to the associated sensor is greater than a preset risk time threshold; when the number of risk times corresponding to the associated sensor is greater than the risk time threshold, outputting risk warning information, reducing the confidence level corresponding to the associated sensor, and recalculating the number of risk times corresponding to the associated sensor.

[0099] In the above further scheme, when it is determined based on the associated data that there is no associated risk for the wharf caisson and the predicted risk factors include non-associated risk factors, the confidence of the associated sensor is adjusted based on whether risk verification has been carried out during the determination of the predicted risk factors, and when the confidence of the associated sensor is greater than the confidence corresponding to the target strain gauge, the risk warning information is not output. This can help to further improve the accuracy of the output of the risk warning information.

[0100] The present application also discloses a dock caisson structure monitoring system. Figure 5 The dock caisson structure monitoring system includes at least one strain gauge 510 arranged on the dock caisson, and a controller 520 connected to the strain gauge signal.

[0101] The controller 520 is used to execute the dock caisson structure monitoring method provided by the above method embodiment.

[0102] In one example, reference Figures 6a to 6d , Figure 6a FIG. 5 is a schematic diagram of the arrangement of the strain gauge 510 on the front wall (rear wall). Figure 6b This is a schematic diagram of the arrangement of the strain gauge 510 on the left wall. Figure 6c FIG. 5 is a schematic diagram of the arrangement of the strain gauge 510 on the bottom plate. Figure 6d FIG. 5 is a schematic diagram of the arrangement of the strain gauge 510 on the outer toe.

[0103] In some embodiments, the dock caisson structure monitoring system further includes an associated sensor 530 disposed on the dock caisson, and the associated sensor 530 is signal-connected to the controller 520. The associated sensor 530 may include at least one of sensors such as an inclination sensor, a displacement sensor, and a stress-free meter that can be used to collect associated data, and the associated information is used to determine whether there is a structural risk in the dock caisson.

[0104] The present application also provides an electronic device. Figure 7 As shown, Figure 7The electronic device 600 shown includes: 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 may also include a transceiver 604. It should be noted that in actual applications, the transceiver 604 is not limited to one, and the structure of the electronic device 600 does not constitute a limitation on the embodiments of the present application.

[0105] Processor 601 may 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 devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. Processor 601 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0106] The bus 602 may include a path to transmit information between the above components. The bus 602 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 602 may be divided into an address bus, a data bus, etc. For ease of representation, Figure 7 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0107] The memory 603 can be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to these.

[0108] The memory 603 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 601. The processor 601 is used to execute the application code stored in the memory 603 to implement the contents shown in the above method embodiment.

[0109] The electronic devices include, but are not limited to, mobile terminals such as mobile phones, notebook computers, PDAs (personal digital assistants), PADs (tablet computers), etc., and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server terminal, etc. Figure 7 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0110] It should be understood that although the steps in the flowchart of the accompanying drawings are shown in sequence according to the instructions of the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise clearly stated in this document, the execution of these steps is not strictly limited in order and can be performed in other orders.

[0111] The above are only some implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for monitoring a wharf caisson structure, characterized in that: The method comprises: Obtain frequency data and temperature data collected by strain gauges arranged on the wharf caisson; determining whether the wharf caisson has a structural risk based on the frequency data and the temperature data; When it is determined that the wharf caisson has structural risks, risk warning information is output.

2. The method according to claim 1, characterized in that The number of the strain gauges includes more than two, and when it is determined that the wharf caisson has a structural risk, outputting risk warning information includes: In the case where it is determined that the wharf caisson has a structural risk based on the frequency data and temperature data collected by the target strain gauge, determining whether there is an adjacent strain gauge whose distance from the target strain gauge is less than a preset distance threshold; In the case where the adjacent strain gauge exists, performing risk verification on the dock caisson based on the frequency data and temperature data collected by the adjacent strain gauge; When the risk verification result indicates that the wharf caisson has structural risk, the risk warning information is output.

3. The method according to claim 2, characterized in that After the risk verification of the wharf caisson is performed based on the frequency data and temperature data collected by the adjacent strain gauges, the method further includes: When the risk verification result indicates that the wharf caisson does not have a structural risk, performing an abnormality verification on the target strain gauge and the adjacent strain gauges; When the abnormality check result indicates that neither the target strain gauge nor the adjacent strain gauge has abnormality, it is determined that there is no structural risk in the wharf caisson, and the risk warning information is not output.

4. The method according to claim 1, characterized in that: The number of the strain gauges includes more than two, and when it is determined that the wharf caisson has a structural risk, risk warning information is output, including: In the case where it is determined that the wharf caisson has a structural risk based on the frequency data and temperature data collected by the target strain gauge, determining whether there is a symmetrical strain gauge symmetrically arranged with the target risk strain gauge; In the presence of the symmetrical strain gauge, determining the predicted risk factor of the dock caisson in combination with the frequency data and temperature data collected by the symmetrical strain gauge; Output risk warning information based on the predicted risk factors.

5. The method according to claim 4, characterized in that The outputting risk warning information based on the predicted risk factors includes: determining whether the predicted risk factor includes an associated risk factor, the associated risk factor being related to associated data collected by an associated sensor disposed on the wharf caisson; In the case where the predicted risk factor includes the associated risk factor, verifying whether the dock caisson has an associated risk corresponding to the associated risk factor based on the associated data; When it is determined that the dock caisson has the associated risk, risk warning information is output based on the associated risk.

6. The method according to claim 5, characterized in that After verifying whether the dock caisson has an associated risk corresponding to an associated risk factor based on the associated data, the method further includes: In the case where it is determined that there is a dock caisson and there is no associated risk, determining whether the predicted risk factors include non-associated risk factors other than the associated risk factors; In a case where the predicted risk factors include the non-correlated risk factors, risk warning information is output based on the non-correlated risk factors.

7. The method according to claim 6, characterized in that The determining whether the predicted risk factors include non-associated risk factors other than the associated risk factors comprises: In a case where the predicted risk factors do not include the non-correlated risk factors, determining whether risk verification has been performed in the process of determining the predicted risk factors; In the process of determining the predicted risk factor, when risk verification is performed, reducing the confidence level corresponding to the associated sensor; Determining whether the confidence level of the associated sensor is greater than the confidence level corresponding to the target strain gauge; When the confidence level of the associated sensor is greater than the confidence level corresponding to the target strain gauge, the risk warning information is not output.

8. The method according to claim 1, characterized in that The determining whether the wharf caisson has a structural risk 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 risk based on the strain variation; The strain change is calculated by the following formula: ε=G×C×(R1-R0)+(Y1-Y2)×(T1-T0) Among them, ε is the strain change; G is the instrument standard coefficient; C is the average correction coefficient corresponding to the strain gauge; R1 is the frequency data; R0 is the preset initial frequency data; Y1 is the temperature expansion coefficient of the steel string; Y2 is the temperature expansion coefficient of concrete; T1 is the temperature data; T0 is the preset initial temperature.

9. A dock caisson structure monitoring system, characterized in that: The system includes at least one strain gauge arranged on the dock caisson, and a controller connected to the strain gauge signal; The controller is used to execute the dock caisson structure monitoring method described in any one of claims 1-8.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the dock caisson structure monitoring method according to any one of claims 1 to 8.

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