CN113742822A - Method and device for eliminating temperature time-lag effect of bridge structure response monitoring data - Google Patents
Method and device for eliminating temperature time-lag effect of bridge structure response monitoring data Download PDFInfo
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Abstract
The invention provides a method and a device for eliminating temperature time-lag effect of bridge structure response monitoring data, wherein the method comprises the following steps: respectively adopting different time intervals to translate backwards for the original acquisition time of the bridge structure response monitoring data of the bridge within a preset time period; constructing a relation model between bridge structure response monitoring data corresponding to the original acquisition time after each time interval translation and bridge structure temperature data of the bridge in the preset time period; calculating the goodness of fit of the relation model corresponding to each time interval, and taking the translated original acquisition time corresponding to the time interval with the maximum goodness of fit as the final acquisition time of the bridge structure response monitoring data. The method effectively eliminates the time lag effect of the temperature, enhances the correlation between the bridge structure response monitoring data and the structure temperature data, and is simple to operate.
Description
Technical Field
The invention relates to the technical field of health detection of bridge engineering, in particular to a method and a device for eliminating a temperature time-lag effect of bridge structure response monitoring data.
Background
The bridge structure response monitoring data is an important basis for carrying out bridge structure monitoring evaluation and safety evaluation. The time lag effect of the temperature can cause inaccurate analysis of the correlation between the structural response and the structural temperature based on the bridge structural response health monitoring data, and further cause difficulty in analysis and evaluation of the structural response monitoring data, thereby causing the missed report and the false report of the bridge structural disaster.
The existing method for eliminating the temperature time lag effect generally adopts a single temperature data translation algorithm based on Fourier series. The method uses a sine curve to fit the obtained temperature data and the structural response monitoring data to find out the phase difference between the two. And converting the phase difference into lag time, and then correspondingly translating the structural response monitoring data on a time scale to eliminate the temperature lag effect.
The method has the advantages that the time lag effect of the temperature can be eliminated, and the correlation between the structural response monitoring data and the temperature data is improved. The method has the disadvantages that when the sine curve fitting is carried out, the fitting effect is not easy to control, the phase difference is easy to be solved inaccurately, and the time lag effect eliminating effect of the temperature is poor. Meanwhile, the method is complex to operate and inconvenient to apply in practical engineering.
Disclosure of Invention
The purpose of the invention is as follows: the invention provides a method and a device for eliminating a temperature time-lag effect of bridge structure response monitoring data, which are used for solving the defects of poor temperature time-lag effect elimination effect and complex operation in the prior art, realizing effective elimination of the time-lag effect of temperature, enhancing the correlation between the bridge structure response monitoring data and the structure temperature data, and enabling the evaluation and analysis of the bridge structure response monitoring data to be more accurate and simple to operate.
The technical scheme is as follows: the invention provides a method for eliminating temperature time lag effect of bridge structure response monitoring data, which comprises the following steps:
respectively adopting different time intervals to translate backwards for the original acquisition time of the bridge structure response monitoring data of the bridge within a preset time period;
constructing a relation model between bridge structure response monitoring data corresponding to the original acquisition time after each time interval translation and bridge structure temperature data of the bridge in the preset time period;
calculating the goodness of fit of the relation model corresponding to each time interval, and taking the translated original acquisition time corresponding to the time interval with the maximum goodness of fit as the final acquisition time of the bridge structure response monitoring data.
According to the method for eliminating the temperature time lag effect of the bridge structure response monitoring data, the original acquisition time of the bridge structure response monitoring data of the bridge in the preset time period is respectively translated backwards by adopting different time intervals, and the method comprises the following steps:
averagely dividing the preset time period into a plurality of original sub-time periods, and calculating a first average value of the bridge structure response monitoring data and a second average value of the bridge structure temperature data in each original sub-time period; wherein the time interval is an integral multiple of the duration of the original sub-period;
shifting back the original sub-time periods corresponding to all the first average values by using each time interval;
if the original sub-time period after translation does not exist in the original sub-time period, deleting the first average value corresponding to the original sub-time period after translation;
and if the original sub-time period does not exist in the translated original sub-time period, deleting the second average value corresponding to the original sub-time period.
According to the method for eliminating the temperature time lag effect of the bridge structure response monitoring data, provided by the invention, the construction of a relation model between the bridge structure response monitoring data corresponding to the original acquisition time after each time interval translation and the bridge structure temperature data of the bridge in the preset time period comprises the following steps:
sorting the deleted first average value according to the sequence of the translated original sub-time periods corresponding to the deleted first average value;
sorting the deleted second average value according to the sequence of the original sub-time periods corresponding to the deleted second average value;
and constructing a relation model between the first average value and the second average value according to the first average value and the second average value of the same position in the sequencing result.
According to the method for eliminating the temperature time-lag effect of the bridge structure response monitoring data, provided by the invention, the relation model between the first average value and the second average value is constructed according to the first average value and the second average value at the same position in the sequencing result, and the method comprises the following steps:
according to a first average value and a second average value of the same position in the sequencing result, constructing a relation model between the first average value and the second average value based on a linear regression method; and obtaining parameters of the relational model by adopting a least square method.
According to the method for eliminating the temperature time-lag effect of the bridge structure response monitoring data, provided by the invention, a relation model between a first average value and a second average value is constructed based on a linear regression method according to the first average value and the second average value at the same position in a sequencing result through the following formula:
wherein q is the output of the relational model, T is the input of the relational model, n is the number of the deleted first means, TiIs the ith second average value, Q, in the sorted resultsiFor the ith in the sorting resultAn average value of the average values is calculated,
is the average of the second means after the deletion,
k and b are parameters of the relational model.
According to the method for eliminating the temperature time-lag effect of the bridge structure response monitoring data, the goodness of fit of the relation model corresponding to each time interval is calculated, and the method comprises the following steps:
inputting each deleted second average value into the relation model to obtain the output of the relation model;
calculating a first difference between the output of the relational model and the average of the deleted first means;
calculating a second difference between each of the deleted first averages and an average of the deleted first averages;
and calculating the goodness of fit of the relation model according to the first difference and the second difference.
According to the method for eliminating the temperature time-lag effect of the bridge structure response monitoring data, the goodness of fit of the relation model is calculated according to the first difference and the second difference through the following formula:
wherein R is2For the purpose of the goodness-of-fit,
n is the number of the deleted first means for the output obtained by inputting the deleted ith second means into the relational model,
is the average of the first means after deletion.
The invention also provides a device for eliminating the temperature time lag effect of the bridge structure response monitoring data, which comprises:
the translation module is used for translating the original acquisition time of the bridge structure response monitoring data of the bridge in a preset time period backwards at different time intervals;
the construction module is used for constructing a relation model between bridge structure response monitoring data corresponding to the original acquisition time after each time interval translation and bridge structure temperature data of the bridge;
and the calculation module is used for calculating the goodness of fit of the relation model corresponding to each time interval, and taking the translated original acquisition time corresponding to the time interval with the maximum goodness of fit as the final acquisition time of the bridge structure response monitoring data.
The invention also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein when the processor executes the program, the steps of the method for eliminating the temperature time-lag effect of the bridge structure responding to the monitoring data are realized.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method for eliminating temperature time lag effects in response to monitored data of a bridge structure as described in any one of the above.
According to the method and the device for eliminating the temperature time lag effect of the bridge structure response monitoring data, after the bridge structure response monitoring data move for a certain time interval on a time scale, the goodness of fit between the bridge structure response monitoring data and the bridge structure temperature data is calculated, the actual interval with the maximum goodness of fit is selected as the lag time, the structure response monitoring data are correspondingly translated on the time scale according to the lag time, the time lag effect of the temperature is effectively eliminated, the correlation between the bridge structure response monitoring data and the structure temperature data is enhanced, and the method is simple.
Has the advantages that: compared with the prior art, the invention has the following advantages:
1. the method has the advantages that the method has a good processing effect, effectively solves the time lag effect of the temperature, and greatly improves the reliability of structural state evaluation and safety evaluation based on the structural response monitoring data.
2. The invention has wider application range and can be used for eliminating the temperature time-lag effect of the bridge structure response monitoring data. The bridge structure response monitoring data comprises but is not limited to bridge beam end displacement, deflection, cable tower inclination, pier inclination and settlement and the like, and can be widely applied to correlation analysis between health monitoring system data.
3. Compared with the existing method, the method has the advantages of simple and easy-to-understand principle and convenience for application of actual engineering.
4. The device for eliminating the temperature time-lag effect of the bridge structure response monitoring data is high in feasibility and simple to operate.
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In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for eliminating temperature time-lag effect of bridge structure response monitoring data according to the present invention;
FIG. 2 is a schematic diagram illustrating a representative value shift of bridge structure response monitoring data in the method for eliminating temperature time-lag effect of bridge structure response monitoring data according to the present invention;
FIG. 3 is a schematic diagram showing a change of a representative value of a structural temperature of a bridge in one day in the method for eliminating a temperature time-lag effect of the bridge structural response monitoring data provided by the present invention;
FIG. 4 is a schematic diagram showing changes in a representative value of a cable tower inclination along a bridge direction in one day of a bridge in the method for eliminating the temperature time-lag effect of the bridge structure response monitoring data provided by the invention;
FIG. 5 is a schematic diagram illustrating a correlation scatter plot between a representative value of a slope of a pylon along a bridge direction and a representative value of a structural temperature when a temperature time-lag effect is not eliminated in the method for eliminating a temperature time-lag effect of the bridge structure response monitoring data provided by the present invention;
FIG. 6 is a schematic diagram illustrating a correlation scatter plot between a representative value of a slope of a pylon along a bridge direction and a representative value of a structural temperature after eliminating a temperature time-lag effect in the method for eliminating the temperature time-lag effect of the bridge structure response monitoring data provided by the present invention;
FIG. 7 is a schematic structural diagram of a device for eliminating temperature time-lag effect according to the present invention;
fig. 8 is a schematic structural diagram of an electronic device provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The method for eliminating the temperature time-lag effect of the bridge structure responding to the monitoring data, which is disclosed by the invention, is described in the following with reference to fig. 1, and comprises the following steps: step 101, respectively adopting different time intervals to translate backwards for the original acquisition time of the bridge structure response monitoring data of the bridge within a preset time period;
optionally, the bridge structure response monitoring data and the bridge structure temperature data in the preset time period are obtained through a sensor installed on the bridge. The bridge structure response monitoring data includes but is not limited to beam end displacement, deflection, cable tower inclination, inclination and settlement of bridge piers and the like.
The time interval being predetermined, e.g. Δ t1、Δt2、Δt3，…，Δtn. When the ith time interval is Δ tiWhen the time is 0, the original acquisition time of the bridge structure response monitoring data is not translated, and the time lag effect is not eliminated.
For any time interval Δ tiMoving the original acquisition time of each bridge structure response monitoring data in a preset time period backwards by delta ti。
102, constructing a relation model between bridge structure response monitoring data corresponding to the original acquisition time after each time interval translation and bridge structure temperature data of the bridge in the preset time period;
the original acquisition time of the bridge structure temperature data is unchanged. The bridge structure temperature data of the bridge corresponding to the original acquisition time is the bridge structure temperature data of which the original acquisition time is the same as the bridge structure response monitoring data.
For example, the original acquisition time of the bridge structure response monitoring data a1 is 1:00, the original acquisition time of a2 is 2:00, the original acquisition time of a3 is 3:00, and the original acquisition time of a4 is 4: 00. The certain time interval is 1 hour, then the acquisition time of a1 is 2:00, the acquisition time of a2 is 3:00, the acquisition time of a3 is 4:00, and the original acquisition time of a4 is 5:00
The original acquisition time of the bridge structure temperature data b1 is 1:00, the original acquisition time of b2 is 2:00, the original acquisition time of b3 is 3:00, and the original acquisition time of b4 is 4:00 within the preset time period. The original acquisition time of the bridge structure temperature data is not moved.
Optionally, (b2, a1), (b3, a2) and (b4, a3) with the same acquisition time after the movement are used as coordinate points to perform curve fitting, and a relation model between the bridge structure response monitoring data and the bridge structure temperature data is obtained.
And translating the original acquisition time of the bridge structure temperature data by adopting each time interval, so that a relation model can be obtained by curve fitting for each time interval.
And 103, calculating the goodness of fit of the relation model corresponding to each time interval, and taking the translated original acquisition time corresponding to the time interval with the maximum goodness of fit as the final acquisition time of the bridge structure response monitoring data.
The goodness of fit reflects the closeness between the fitting value of the bridge structure temperature data obtained through the relational model and the true value of the bridge structure temperature data obtained through the sensor, and the embodiment is not limited to a specific calculation method.
For different time intervals Δ t1、Δt2、Δt3，…，ΔtnCalculating to obtain a linear regression model q1、q2、q3，…，qnTo obtain corresponding goodness of fit R2 1、R2 2、R2 3，…，R2 n. Will maximize goodness of fit R2 maxCorresponding time interval Δ trAs the lag time of the bridge structure temperature data in a preset time period. The original acquisition time of the bridge structure response monitoring data is correspondingly translated according to the lag time, so that the time lag effect of the bridge structure temperature data is effectively eliminated, and the reliability of structural state evaluation and safety evaluation based on the bridge structure response monitoring data is improved.
In the embodiment, after the bridge structure response monitoring data move for a certain time interval on the time scale, the goodness of fit between the bridge structure response monitoring data and the bridge structure temperature data is calculated, the actual interval with the largest goodness of fit is selected as the lag time, the structure response monitoring data are correspondingly translated on the time scale according to the lag time, the time lag effect of the temperature is effectively eliminated, the correlation between the bridge structure response monitoring data and the structure temperature data is enhanced, and the method is simple.
On the basis of the foregoing embodiment, in this embodiment, the shifting backward by using different time intervals for the original acquisition time of the bridge structure response monitoring data of the bridge within the preset time period includes: averagely dividing the preset time period into a plurality of original sub-time periods, and calculating a first average value of the bridge structure response monitoring data and a second average value of the bridge structure temperature data in each original sub-time period; wherein the time interval is an integral multiple of the duration of the original sub-period;
in order to reduce the operation amount and avoid overfitting during the construction of a relation model, a preset time period is averagely divided into a plurality of original sub-time periods, the time length of each original sub-time period is s, and the number of the original sub-time periods is l.
And calculating the average value of the bridge structure response monitoring data and the average value of the bridge structure temperature data in each original sub-time period. And taking the average value of the bridge structure response monitoring data and the average value of the bridge structure temperature data as representative values of corresponding original sub-time periods, namely obtaining the representative values Q of the I bridge structure response monitoring data and the representative values T of the I bridge structure temperature data.
Shifting back the original sub-time periods corresponding to all the first average values by using each time interval;
the representative value T of the bridge structure temperature data is kept unchanged on the time scale, and the number of the representative values is l. Any time interval Δ tiThe representative value Q of the bridge structure response monitoring data is moved by a time interval delta t on a time scale in integral multiple of si。
If the original sub-time period after translation does not exist in the original sub-time period, deleting the first average value corresponding to the original sub-time period after translation; and if the original sub-time period does not exist in the translated original sub-time period, deleting the second average value corresponding to the original sub-time period.
As shown in FIG. 2, the data length of the representative value Qshift of the bridge structure response monitoring data is
With more Q behind
And deleting the data. The data length of the moved bridge structure response monitoring data representative value Q 'is l', lThe expression is as follows:
meanwhile, the representative value T of the bridge structure temperature data is increased in front
And deleting the data to obtain l 'representative values T' of the bridge structure temperature data.
On the basis of the foregoing embodiment, in this embodiment, the building a relationship model between the bridge structure response monitoring data corresponding to the original acquisition time after the translation of each time interval and the bridge structure temperature data of the bridge in the preset time period includes: sorting the deleted first average value according to the sequence of the translated original sub-time periods corresponding to the deleted first average value; sorting the deleted second average value according to the sequence of the original sub-time periods corresponding to the deleted second average value; and constructing a relation model between the first average value and the second average value according to the first average value and the second average value of the same position in the sequencing result.
And sequencing the l 'representative values Q' of the bridge structure response monitoring data according to the sequence of the time periods after the corresponding movement. And sequencing the l 'representative values T' of the bridge structure temperature data according to the sequence of the corresponding time periods. And taking Q 'and T' positioned at the same position in the sequencing result as a data point in a coordinate system to perform curve fitting to obtain a relation model.
On the basis of the foregoing embodiments, in this embodiment, according to a first average value and a second average value of the same position in a sorting result, constructing a relationship model between the first average value and the second average value includes: according to a first average value and a second average value of the same position in the sequencing result, constructing a relation model between the first average value and the second average value based on a linear regression method; and obtaining parameters of the relational model by adopting a least square method.
The relational model in this embodiment is a linear regression model. And taking the Q 'and the T' which are positioned at the same position in the sequencing result as a data point in a coordinate system, and calculating parameters in the linear regression model to obtain the linear regression model.
On the basis of the above embodiment, in this embodiment, a relationship model between a first average value and a second average value of the same position in the sorting result is constructed based on a linear regression method by the following formula:
q＝kt+b；
wherein q is the output of the relational model, T is the input of the relational model, n is the number of the deleted first means, TiIs the ith second average value, Q, in the sorted resultsiAs the ith first average value in the sorted result,
is the average of the second means after the deletion,
is the average of the first means after deletion.
N in the formula is l' in the above. And k and b are parameters in the linear regression model and are obtained by adopting a least square method.
On the basis of the foregoing embodiments, in this embodiment, the calculating the goodness of fit of the relationship model corresponding to each time interval includes: inputting each deleted second average value into the relation model to obtain the output of the relation model;
and inputting each T 'of the l' representative values T 'of the bridge structure temperature data into the relation model, and acquiring a fitting value of the representative value of the bridge structure response monitoring data corresponding to each T'.
Calculating a first difference between the output of the relational model and the average of the deleted first means;
and calculating the difference between the fitting value of the representative value of the bridge structure response monitoring data corresponding to each T' and the measured value of the representative value of the bridge structure response monitoring data.
Calculating a second difference between each of the deleted first averages and an average of the deleted first averages;
and calculating the average value of the measured values of the representative values of the bridge structure response monitoring data corresponding to each T ' and the measured values Q ' of the l ' representative values of the bridge structure response monitoring data.
And calculating the goodness of fit of the relation model according to the first difference and the second difference.
And calculating the goodness of fit of the relation model according to the first difference values and the second difference values corresponding to all T'. The present embodiment is not limited to a specific calculation method.
On the basis of the above embodiment, in this embodiment, the goodness of fit of the relationship model is calculated according to the first difference and the second difference by the following formula:
wherein R is2For the purpose of the goodness-of-fit,
n is the number of the deleted first means for the output obtained by inputting the deleted ith second means into the relational model,
is the average of the first means after deletion.
Calculating R of the relation model obtained by each time interval through the formula2。R2The closer to 1, the better the fitting of the representation relational model.
And selecting the structural monitoring data of 12 days in 6 months in 2020 to establish the correlation between the forward bridge inclination of the pylon and the structural temperature. The sensors are selected from a sensor used for monitoring the inclination along the bridge direction on the cable tower and a temperature sensor at the quarter-span position of the main beam. And calculating the representative value of the inclination of the cable towers along the bridge direction and the representative value of the bridge structure temperature by taking 2min as a time interval, and totaling 720 representative values of the inclination of the cable towers along the bridge direction and 720 representative values of the structure temperature.
Fig. 3 and 4 show changes of the representative value of the structural temperature and the representative value of the inclination of the cable tower along the bridge in one day. Fig. 5 is a scatter diagram showing a correlation between a representative value of a forward-to-bridge inclination of a pylon and a representative value of a structural temperature when a temperature hysteresis effect is not eliminated. In fig. 5, the linear correlation between the representative value of the slope of the cable tower along the bridge and the representative value of the structure temperature is low, and a remarkable time lag effect exists. FIG. 6 is a plot of a correlation scattergram of representative values of the slope of the pylon along the bridge and representative values of the structure temperature after eliminating the effect of temperature time lag. As can be seen from fig. 6, there is a high linear correlation between the representative value of the slope of the cable tower along the bridge and the representative value of the temperature of the structure at this time, which illustrates that the present embodiment can effectively eliminate the time lag effect of the temperature in the structure monitoring data.
Table 1 shows a correlation model and R between a representative value Q of the slope of the cable tower and a representative value T of the temperature of the structure, which are established by linear regression analysis when the time lag effect of the temperature is not eliminated2 0And (6) checking the result. Table 2 shows the maximum value R of the goodness of fit2 maxAnd a linear regression equation at this time.
TABLE 1 Linear regression model and R of temperature-Tower Tilt representative values2 0Test results
| Linear regression function | R2 0 |
| Q＝-0.472T+0.003 | 0.709 |
TABLE 2R2 maxAnd linear regression model of temperature-tower inclination representative value at this time
| Linear regression function | R2 max |
| Q＝-0.425T+0.002 | 0.991 |
The temperature time lag effect eliminating device for bridge structure response monitoring data provided by the invention is described below, and the temperature time lag effect eliminating device for bridge structure response monitoring data described below and the temperature time lag effect eliminating method for bridge structure response monitoring data described above can be referred to correspondingly.
As shown in fig. 7, the apparatus comprises a translation module 701, a construction module 702, and a calculation module 703, wherein:
the translation module 701 is used for translating the original acquisition time of the bridge structure response monitoring data of the bridge in a preset time period backwards at different time intervals;
the construction module 702 is configured to construct a relationship model between bridge structure response monitoring data corresponding to the original acquisition time after each time interval is translated and bridge structure temperature data of the bridge;
the calculating module 703 is configured to calculate a goodness-of-fit of the relationship model corresponding to each time interval, and use the translated original acquisition time corresponding to the time interval with the highest goodness-of-fit as the final acquisition time of the bridge structure response monitoring data.
In the embodiment, after the bridge structure response monitoring data move for a certain time interval on the time scale, the goodness of fit between the bridge structure response monitoring data and the bridge structure temperature data is calculated, the actual interval with the largest goodness of fit is selected as the lag time, the structure response monitoring data are correspondingly translated on the time scale according to the lag time, the time lag effect of the temperature is effectively eliminated, the correlation between the bridge structure response monitoring data and the structure temperature data is enhanced, and the method is simple.
Fig. 8 illustrates a physical structure diagram of an electronic device, and as shown in fig. 8, the electronic device may include: a processor (processor)810, a communication Interface 820, a memory 830 and a communication bus 840, wherein the processor 810, the communication Interface 820 and the memory 830 communicate with each other via the communication bus 840. Processor 810 may invoke logic instructions in memory 830 to perform a method for eliminating temperature skew effects of a bridge structure in response to monitored data, the method comprising: respectively adopting different time intervals to translate backwards for the original acquisition time of the bridge structure response monitoring data of the bridge within a preset time period; constructing a relation model between bridge structure response monitoring data corresponding to the original acquisition time after each time interval translation and bridge structure temperature data of the bridge in the preset time period; calculating the goodness of fit of the relation model corresponding to each time interval, and taking the translated original acquisition time corresponding to the time interval with the maximum goodness of fit as the final acquisition time of the bridge structure response monitoring data.
In addition, the logic instructions in the memory 830 may be implemented in software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product, the computer program product includes a computer program stored on a non-transitory computer readable storage medium, the computer program includes program instructions, when the program instructions are executed by a computer, the computer can execute the method for eliminating the temperature time-lag effect of the bridge structure response monitoring data provided by the above methods, the method includes: respectively adopting different time intervals to translate backwards for the original acquisition time of the bridge structure response monitoring data of the bridge within a preset time period; constructing a relation model between bridge structure response monitoring data corresponding to the original acquisition time after each time interval translation and bridge structure temperature data of the bridge in the preset time period; calculating the goodness of fit of the relation model corresponding to each time interval, and taking the translated original acquisition time corresponding to the time interval with the maximum goodness of fit as the final acquisition time of the bridge structure response monitoring data.
In yet another aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor, is implemented to perform the method for eliminating the temperature time-lag effect of the bridge structure response monitoring data provided above, the method comprising: respectively adopting different time intervals to translate backwards for the original acquisition time of the bridge structure response monitoring data of the bridge within a preset time period; constructing a relation model between bridge structure response monitoring data corresponding to the original acquisition time after each time interval translation and bridge structure temperature data of the bridge in the preset time period; calculating the goodness of fit of the relation model corresponding to each time interval, and taking the translated original acquisition time corresponding to the time interval with the maximum goodness of fit as the final acquisition time of the bridge structure response monitoring data.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for eliminating temperature time-lag effect of bridge structure response monitoring data is characterized by comprising the following steps:
respectively adopting different time intervals to translate backwards for the original acquisition time of the bridge structure response monitoring data of the bridge within a preset time period;
constructing a relation model between bridge structure response monitoring data corresponding to the original acquisition time after each time interval translation and bridge structure temperature data of the bridge in the preset time period;
calculating the goodness of fit of the relation model corresponding to each time interval, and taking the translated original acquisition time corresponding to the time interval with the maximum goodness of fit as the final acquisition time of the bridge structure response monitoring data.
2. The method for eliminating the temperature time-lag effect of the bridge structure response monitoring data according to claim 1, wherein the step of translating the original acquisition time of the bridge structure response monitoring data of the bridge within the preset time period backwards respectively by adopting different time intervals comprises the steps of:
averagely dividing the preset time period into a plurality of original sub-time periods, and calculating a first average value of the bridge structure response monitoring data and a second average value of the bridge structure temperature data in each original sub-time period; wherein the time interval is an integral multiple of the duration of the original sub-period;
shifting back the original sub-time periods corresponding to all the first average values by using each time interval;
if the original sub-time period after translation does not exist in the original sub-time period, deleting the first average value corresponding to the original sub-time period after translation;
and if the original sub-time period does not exist in the translated original sub-time period, deleting the second average value corresponding to the original sub-time period.
3. The method for eliminating the temperature time-lag effect of the bridge structure response monitoring data according to claim 2, wherein the constructing a relationship model between the bridge structure response monitoring data corresponding to the original acquisition time after the translation of each time interval and the bridge structure temperature data of the bridge in the preset time period comprises:
sorting the deleted first average value according to the sequence of the translated original sub-time periods corresponding to the deleted first average value;
sorting the deleted second average value according to the sequence of the original sub-time periods corresponding to the deleted second average value;
and constructing a relation model between the first average value and the second average value according to the first average value and the second average value of the same position in the sequencing result.
4. The method for eliminating the temperature time-lag effect of the bridge structure response monitoring data according to claim 3, wherein the constructing a relation model between the first average value and the second average value according to the first average value and the second average value at the same position in the sequencing result comprises:
according to a first average value and a second average value of the same position in the sequencing result, constructing a relation model between the first average value and the second average value based on a linear regression method; and obtaining parameters of the relational model by adopting a least square method.
5. The method for eliminating the temperature time-lag effect of the bridge structure response monitoring data according to claim 4, wherein a relation model between the first average value and the second average value is constructed based on a linear regression method according to the following formula according to the first average value and the second average value of the same position in the sequencing result:
q＝kt+b；
wherein q is the output of the relational model, T is the input of the relational model, n is the number of the deleted first means, TiIs the ith second average value, Q, in the sorted resultsiAs the ith first average value in the sorted result,
is the average of the second means after the deletion,
k and b are parameters of the relational model.
6. The method for eliminating the temperature time-lag effect of the bridge structure response monitoring data according to any one of claims 2 to 5, wherein the calculating of the goodness of fit of the relation model corresponding to each time interval comprises:
inputting each deleted second average value into the relation model to obtain the output of the relation model;
calculating a first difference between the output of the relational model and the average of the deleted first means;
calculating a second difference between each of the deleted first averages and an average of the deleted first averages;
and calculating the goodness of fit of the relation model according to the first difference and the second difference.
7. The method of claim 6, wherein the goodness-of-fit of the relationship model is calculated from the first difference and the second difference by the following equation:
wherein R is2For the purpose of the goodness-of-fit,
n is the number of the deleted first means for the output obtained by inputting the deleted ith second means into the relational model,
is the average of the first means after deletion.
8. A bridge structures responds to temperature time lag effect remove device of monitoring data which characterized in that includes:
the translation module is used for translating the original acquisition time of the bridge structure response monitoring data of the bridge in a preset time period backwards at different time intervals;
the construction module is used for constructing a relation model between bridge structure response monitoring data corresponding to the original acquisition time after each time interval translation and bridge structure temperature data of the bridge;
and the calculation module is used for calculating the goodness of fit of the relation model corresponding to each time interval, and taking the translated original acquisition time corresponding to the time interval with the maximum goodness of fit as the final acquisition time of the bridge structure response monitoring data.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program performs the steps of the method for eliminating temperature time lag effects in response to monitored data of a bridge structure according to any one of claims 1 to 7.
10. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the steps of the method for eliminating temperature time lag effects in response to monitoring data for a bridge structure according to any one of claims 1 to 7.
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