CN116821713A - Shock insulation efficiency evaluation method and system based on multivariable dynamic time warping algorithm - Google Patents
Shock insulation efficiency evaluation method and system based on multivariable dynamic time warping algorithm Download PDFInfo
- Publication number
- CN116821713A CN116821713A CN202311108066.8A CN202311108066A CN116821713A CN 116821713 A CN116821713 A CN 116821713A CN 202311108066 A CN202311108066 A CN 202311108066A CN 116821713 A CN116821713 A CN 116821713A
- Authority
- CN
- China
- Prior art keywords
- vibration
- time series
- series data
- multiaxial
- distance
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 230000035939 shock Effects 0.000 title claims abstract description 52
- 238000011156 evaluation Methods 0.000 title claims abstract description 33
- 238000009413 insulation Methods 0.000 title claims abstract description 33
- 238000002955 isolation Methods 0.000 claims abstract description 154
- 238000000034 method Methods 0.000 claims abstract description 37
- 239000011159 matrix material Substances 0.000 claims description 40
- 238000004364 calculation method Methods 0.000 claims description 34
- 238000012545 processing Methods 0.000 abstract description 10
- 230000001133 acceleration Effects 0.000 description 19
- 230000005284 excitation Effects 0.000 description 7
- 238000010586 diagram Methods 0.000 description 6
- 238000004891 communication Methods 0.000 description 4
- 239000004973 liquid crystal related substance Substances 0.000 description 4
- 238000005259 measurement Methods 0.000 description 4
- 238000001514 detection method Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 230000002265 prevention Effects 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 208000001953 Hypotension Diseases 0.000 description 1
- 238000010521 absorption reaction Methods 0.000 description 1
- 238000009825 accumulation Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000000470 constituent Substances 0.000 description 1
- 230000001186 cumulative effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M7/00—Vibration-testing of structures; Shock-testing of structures
- G01M7/02—Vibration-testing by means of a shake table
- G01M7/06—Multidirectional test stands
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Biology (AREA)
- Evolutionary Computation (AREA)
- Bioinformatics & Computational Biology (AREA)
- General Engineering & Computer Science (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
The invention belongs to the technical field of data processing, and provides a method and a system for evaluating the shock insulation efficiency based on a multivariate dynamic time warping algorithm, which are used for acquiring multiaxial shock time series data and multiaxial shock time series data after shock insulation, in order to solve the problem of inaccuracy of the conventional shock insulation efficiency evaluation; calculating the similarity of the multiaxial vibration time series data and the multiaxial vibration time series data after vibration isolation by adopting a dynamic time warping algorithm, and aligning the multiaxial vibration time series data with the multiaxial vibration time series data after vibration isolation according to the similarity; and according to the difference value between the aligned multiaxial vibration time series data and the multiaxial vibration time series data after vibration isolation, performing vibration isolation efficiency evaluation. The data after alignment and matching are utilized to evaluate the vibration isolation efficiency, so that the time lag of vibration data caused by the vibration isolation process is eliminated, and the effective evaluation of the vibration isolation efficiency is realized.
Description
Technical Field
The invention belongs to the technical field of data processing, and particularly relates to a seismic isolation efficiency evaluation method and system based on a multivariate dynamic time warping algorithm.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
When an earthquake or other large vibration event occurs, articles or equipment such as precious cultural relics, precise instruments and the like which are extremely sensitive to vibration are easy to damage to a certain extent due to the influence of vibration waves, and even irrecoverable loss is caused. The shock insulation platform, also called a shock absorption platform, is used as a disaster prevention and reduction emergency device, is often deployed in scenes such as museum cultural relics shock prevention, data center server cabinet shock prevention and the like, and is used for reducing damage of shock such as earthquake to sensitive articles or instruments when the earthquake damage occurs.
The shock insulation efficiency of the shock insulation platform is evaluated, the shock insulation capability of the shock insulation platform can be determined, an important reference basis is provided for shock protection and maintenance of precise instruments and fragile articles, the shock insulation platform can be further guided to be improved, and the safety and shock resistance of target monitoring articles are improved. Therefore, it is important to detect and evaluate the seismic isolation efficiency of the seismic isolation platform.
The vibration isolation efficiency assessment task of the vibration isolation platform relates to a vibration platform for generating a vibration source, a vibration isolation platform to be measured for measuring vibration isolation efficiency and a vibration isolation efficiency detection system.
Aiming at the time lag problem of the data after the earthquake isolation relative to the vibration excitation data, the traditional scheme directly compares the vibration data before and after the earthquake isolation at the same moment in the process of evaluating the earthquake isolation effect, and the inaccuracy of the earthquake isolation efficiency evaluation can be caused, thereby influencing the effective evaluation of the earthquake isolation efficiency.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides the vibration isolation efficiency evaluation method and the vibration isolation efficiency evaluation system based on the multivariate dynamic time warping algorithm, the multiaxial vibration time series data is calculated through the dynamic time warping algorithm and aligned with the multiaxial vibration time series data after vibration isolation, the vibration isolation efficiency is evaluated by using the aligned and matched data, the vibration data time lag caused by the vibration isolation process is eliminated, and the effective evaluation of the vibration isolation efficiency is realized.
To achieve the above object, a first aspect of the present invention provides a seismic isolation efficiency evaluation method based on a multivariate dynamic time warping algorithm, comprising:
acquiring multiaxial vibration time series data and multiaxial vibration time series data after vibration isolation;
calculating the similarity of the multiaxial vibration time series data and the multiaxial vibration time series data after vibration isolation by adopting a dynamic time warping algorithm, and aligning the multiaxial vibration time series data with the multiaxial vibration time series data after vibration isolation according to the similarity;
and according to the difference value between the aligned multiaxial vibration time series data and the multiaxial vibration time series data after vibration isolation, performing vibration isolation efficiency evaluation.
A second aspect of the present invention provides a seismic isolation efficiency evaluation system based on a multivariate dynamic time warping algorithm, comprising:
the acquisition module is used for: the method comprises the steps of acquiring multiaxial vibration time series data and multiaxial vibration time series data after vibration isolation;
and an alignment module: the method comprises the steps of calculating the similarity of the multiaxial vibration time series data and the multiaxial vibration time series data after vibration isolation by adopting a dynamic time warping algorithm, and aligning the multiaxial vibration time series data with the multiaxial vibration time series data after vibration isolation according to the similarity;
and an evaluation module: and the vibration isolation efficiency evaluation is performed according to the difference value between the aligned multiaxial vibration time series data and the multiaxial vibration time series data after vibration isolation.
The one or more of the above technical solutions have the following beneficial effects:
according to the method, the similarity of the multiaxial vibration time series data and the multiaxial vibration time series data after vibration isolation is calculated through a dynamic time warping algorithm, time alignment matching is carried out on the vibration data and the vibration data after vibration isolation according to the similarity, vibration isolation efficiency is evaluated by utilizing the data after alignment matching, vibration data time lag caused by the vibration isolation process is eliminated, vibration isolation effect is further quantitatively measured, and effective evaluation of the vibration isolation efficiency is achieved.
Additional aspects of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention.
FIG. 1 is a schematic diagram of a system for detecting the shock insulation efficiency of a shock insulation platform according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a shock isolation efficiency detection system according to an embodiment of the present invention;
FIG. 3 is a flowchart of a system for detecting the shock insulation efficiency of a shock insulation platform according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of an MDTW distance matrix according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a first search of an MDTW distance calculation region according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of a one-time expansion search of an MDTW distance calculation region according to an embodiment of the present invention;
FIG. 7 is a diagram illustrating final search results of an MDTW distance calculation region according to the first embodiment of the present invention;
FIG. 8 is a time matching correspondence indicated by the MDTW algorithm according to the first embodiment of the present invention;
FIG. 9 is a flowchart of a shock isolation efficiency detection algorithm according to an embodiment of the present invention;
FIG. 10 is a diagram illustrating a shortest MDTW path solution for pre-and post-shock isolation data according to an embodiment of the present invention;
fig. 11 shows the MDTW correspondence between two sensor data at the first 100 moments in the first embodiment of the present invention.
Reference numerals illustrate:
1. the vibration platform comprises a vibration table, a vibration isolation platform, a first triaxial acceleration sensor, a second triaxial acceleration sensor, a data processing server and a display client.
Detailed Description
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present invention.
Embodiments of the invention and features of the embodiments may be combined with each other without conflict.
Example 1
As shown in fig. 1, the system for detecting the vibration isolation efficiency of the vibration isolation platform according to the present embodiment includes a vibration table 1 for generating a vibration source excitation signal, a vibration isolation platform 2 to be measured for measuring the vibration isolation efficiency, a first triaxial acceleration sensor 3 and a second triaxial acceleration sensor 4 for measuring the vibration signal, a data processing server 5 for receiving sensor data and calculating the vibration isolation efficiency, and a display client 6 for displaying the vibration isolation efficiency.
As shown in fig. 2-3, the shock table 1 is used to generate an excitation load simulating a seismic or other shock source, and the shock table 1 is started to simulate a shock excitation. The vibration isolation platform 2 to be measured is arranged on the vibration table 1, and vibration excitation generated by the vibration table 1 directly acts on the vibration isolation platform 2.
The triaxial acceleration sensor comprises a vibration sensing unit, a wireless communication unit, a power supply unit and a central processing unit. Two triaxial acceleration sensors measure a vibration signal with an accelerometer, the vibration signal comprising three axial acceleration values. The second triaxial acceleration sensor 4 is arranged above the table top of the vibration isolation platform 2 and used for collecting and monitoring vibration data after vibration isolation, and the first triaxial acceleration sensor 3 is arranged on the vibration platform 1 and used for generating vibration excitation and collecting vibration data before vibration isolation. The wireless communication unit adopts UDP protocol to carry out wireless data transmission through WiFi network. The wireless communication unit is connected with the gateway by configuring the WiFi signal appointed by connection in advance, and adopts the UDP wireless communication protocol to send the data to the data processing server through the gateway, and the wireless transmission rate can reach 200Hz.
Each triaxial acceleration sensor is provided with an independent power supply unit, and the power supply unit consists of a rechargeable battery and a wireless charging coil. The rechargeable battery can ensure that the sensor can still continue to work when power failure occurs. The rechargeable battery charges through wireless charging coil, and wireless charging coil divide into transmitting terminal and receiving terminal, and the transmitting terminal can direct switch-on 220V power, and receiving terminal and sensor are close to in order to realize wireless charging. The power cord may cause a tear to the sensor during vibration and cause vibration disturbances, resulting in inaccurate measurement data. Therefore, the wireless charging mode is adopted, inaccuracy in acceleration data measurement caused by connection of a power line to the sensor can be avoided, measurement accuracy of the acceleration sensor is guaranteed, meanwhile, the sensor can continuously work, and the central processing unit is used for processing organization and management of all constituent units in the sensor.
The data processing server is used for receiving vibration data acquired by the sensor and transmitting control instructions to the sensor. In addition, the data processing server runs the proposed seismic isolation efficiency evaluation algorithm, calculates the seismic isolation efficiency of the seismic isolation platform in real time according to the vibration data, and then displays the seismic isolation efficiency data on the display client; the display client is used for displaying vibration data acquired by the sensor and the vibration isolation efficiency calculated by the server in real time, and a user or a system can monitor the vibration isolation efficiency data in real time at the client. Meanwhile, a user can set and send control instructions to the sensor at the client, such as adjusting the acquisition frequency of the sensor, calibrating the sensor data, and the like.
The embodiment discloses a seismic isolation efficiency evaluation method based on a multivariate dynamic time warping algorithm, which comprises the following steps:
acquiring multiaxial vibration time series data and multiaxial vibration time series data after vibration isolation;
calculating the similarity of the multiaxial vibration time series data and the multiaxial vibration time series data after vibration isolation by adopting a dynamic time warping algorithm, and aligning the multiaxial vibration time series data with the multiaxial vibration time series data after vibration isolation according to the similarity;
and according to the difference value between the aligned multiaxial vibration time series data and the multiaxial vibration time series data after vibration isolation, performing vibration isolation efficiency evaluation.
In this embodiment, a multivariate dynamic time warping (Multivariate Dynamic Time Warping, MDTW) algorithm for alignment of isolation time series is provided for the multi-sensor channel time series data collected by the multi-sensors.
And in a certain time, vibration data acquired by the two triaxial acceleration sensors respectively form two time sequences. Due to the vibration isolation function of the vibration isolation platform, compared with the time sequence acquired by the triaxial acceleration sensor under the vibration isolation platform, the time sequence data acquired by the triaxial acceleration sensor on the vibration isolation platform shows smaller amplitude and wave crest and wave trough time lag.
The two time sequences can be aligned by using a dynamic time warping algorithm, so that the similarity of the two time sequences on a time axis is maximized, and the alignment matching relationship between different moments of the two time sequences can be calculated by using the dynamic time warping algorithm. And then, calculating the difference value of vibration amplitude values between the two aligned time sequences, wherein the vibration reduction difference value can be used as objective evaluation of the vibration isolation efficiency, so that the vibration isolation efficiency of the vibration isolation platform is obtained.
Assume that vibration data of three axes acquired by a triaxial acceleration sensor arranged on a vibration isolation platform and a triaxial acceleration sensor arranged on a vibration table are respectivelyAnd->Wherein->And->A number of time steps representing a time sequence; column vector->Sum column vectorData samples acquired by two triaxial acceleration sensors in three axial directions are respectively represented, and Euclidean distance is calculated by using Euclidean space rules>To characterize the data gap between two time sequences, which represents +.>The formula is as follows:
（1）
wherein, the liquid crystal display device comprises a liquid crystal display device,three acceleration measurement directions are respectively indicated.
As shown in FIG. 4, a cumulative distance matrix between two three-dimensional time series is calculatedThe calculation formula is as follows:
（2）
distance matrixComprises->The distance value is the matrix element, and all matrix elements are not involved when searching the shortest path of the MDTW in the distance matrix, so that calculation of the complete distance matrix at one time can result in high calculation cost and low calculation efficiency. The vibration data before and after the vibration isolation have similarity, and the generated shortest path is generally close to the anti-diagonal line of the matrix in the distance matrix. In order to submit the calculation efficiency, the present embodiment proposes a simplified MDTW shortest path searching method that is opposed by iterative calculationThe MDTW distance of the area near the corner line greatly reduces the calculation cost and improves the calculation efficiency of the MDTW algorithm.
As shown in fig. 9, the seismic isolation efficiency evaluation method based on the multivariate dynamic time warping algorithm provided in this embodiment specifically includes:
step 1: selecting three diagonal stripe regions adjacent to the anti-diagonal line in the distance matrix, including the anti-diagonal line, i.eThe region is calculated for the first time as MDTW distance.
Step 2: after the MDTW distance is calculated for the first time, the shortest path searching process is carried out in the area, therebyBegin getting +.>Wherein the position of the minimum value in the distance comparison matrix is used as the starting point of the next distance comparison matrix.
Step 3: in the process of iteratively solving the minimum value in the distance comparison matrix, if the position of the minimum value is the boundary of the current MDTW distance calculation region, the MDTW distance calculation region needs to be expanded to two sides by one anti-diagonal stripe. For example, the location of the minimum value occurs for the first time at the MDTW distance calculation region boundary, i.e. the minimum value occurs atOr->Then the current region needs to be extended beyond the boundary by a diagonal stripe, namelyAnd->The MDTW distance calculation region at this time contains fiveThe strips are diagonally striped.
Step 4: if the minimum value arrives at the positionThe edge of the distance comparison matrix has been reached beforeThen the distance comparison matrix is not iterated again until reaching, respectively, down or left along a straight line。
Step 5: searching through the steps to find the shortest path so as to find the alignment correspondence of two time series, for example。
Step 6: calculating a seismic isolation difference value according to the alignment corresponding relation, and defining the seismic isolation difference values of the two sensors in three axial directionsThe method comprises the following steps:
（3）
wherein, the liquid crystal display device comprises a liquid crystal display device,a sensor arranged on the vibration table>Data points,/->Is the +.f. of the sensor on the isolation table determined according to the corresponding relation>Data points,/->And->Corresponding time points after alignment of the two time series.
Thereby obtaining the time sequence of the seismic isolation difference valueThe method comprises the following steps:
（4）
step 7: the vibration isolation efficiency is the first sensor arranged on the vibration tabletThe ratio of the vibration isolation difference corresponding to a data point to the vibration value of the data pointThe method comprises the following steps:
（5）
and summing the instantaneous vibration isolation efficiency of each direction to obtain the vibration isolation efficiency accumulation sum in the whole time sequence range, namely:
（6）
step 8: for time sequence lengthObtaining the average vibration isolation efficiency of each axial direction of the corresponding period by using weighted average>The method comprises the following steps:
（7）
step 9: finally, the calculation formula of the comprehensive vibration isolation efficiency of the vibration isolation platform under vibration excitation at the current moment is as follows:
（8）
the vibration isolation efficiency of the vibration isolation platform corresponding to any moment can be obtained by repeating the calculation steps.
Fig. 5-7 illustrate the calculation of the time alignment correspondence of two three-variable time series using the MDTW algorithm. The left side of the figure is time series data after shock insulation, the upper side is time series data before shock insulation, and the main body part of fig. 5 to 7 shows the MDTW distance and the shortest MDTW path. Fig. 5 shows that the MDTW distances corresponding to the data are calculated in the first MDTW distance calculation area, and are filled in the square. A shortest path search process between the two time sequences is performed in the region, and the abscissa position of the boundary of the touch region in the search process is (18, 17). The MDTW distance calculation area is extended outward as in fig. 6, and then the shortest path search is continued from (18, 17) until (12, 10) reaches the area boundary again, the MDTW distance calculation area is extended outward, and the shortest path search is continued, and the search result is finally obtained as in fig. 7. The dashed lines between the two time series in fig. 8 connect the time series data at different times, respectively, and the connecting lines indicate the time matching correspondence indicated by the MDTW algorithm calculation at different times.
Aiming at the method and the system for detecting the shock insulation efficiency of the shock insulation platform, which are provided by the embodiment, the operation process of the method and the system and the obtained experimental result are shown by an experimental example. In this experimental example, the vibration mode of the vibration table was set to a vertical fixed frequency, the vibration intensity was set to 30%, the vibration frequency was set to 10Hz, the return rates of two sensors placed on the vibration table and the vibration isolation platform were set to 100Hz, and three axial vibration data were acquired X, Y, Z, respectively. MDTW results for vibration data near 100 historical moments are calculated online every 100ms using these data. And respectively calculating the instantaneous shock insulation efficiency of each moment of the three axial directions and the average shock insulation efficiency within the range of 100 moments according to the time matching corresponding relation obtained by the MDTW, and then integrating the average shock insulation efficiencies of the three axial directions by using an integration algorithm to obtain the comprehensive shock insulation efficiency. Table 1 shows the results of the evaluation of the seismic isolation efficiency every 100ms during the experimental example test, including the average seismic isolation efficiency of the X-axis, Y-axis, Z-axis, and the integrated seismic isolation efficiency. Table 2 shows the instantaneous shock insulation efficiency at a time of 00:02:31.320, which is close to 100 historical times, and changes in real time within a certain range under the condition that the vibration mode is not changed.
Table 1: integrated shock insulation efficiency every 100 milliseconds
Table 2: instantaneous shock insulation efficiency near 100 historic moments
Fig. 10 shows the MDTW solution result of the shortest path calculated between the data before and after the seismic isolation corresponding to table 2. As can be seen from the broken lines in the figure, the shortest path calculated by the proposed MDTW algorithm is a broken line near the anti-diagonal region, and only a small portion of the MDTW distance of the anti-diagonal stripe region is calculated. Compared with the calculation of the complete MDTW distance matrix element, the method provided in the experiment reduces the calculation amount of the MDTW distance matrix by 81.9%, saves 70.83ms calculation time and improves the calculation speed by 79.78%.
Fig. 11 shows the time matching correspondence obtained by MDTW between the time series before and after the shock isolation in fig. 10, it can be seen that most of the correspondence is that the post-shock-isolation data with relatively rear time and the pre-shock-isolation data with relatively front time correspond to each other due to the hysteresis effect of the shock-isolation table on the shock wave, and the amplitude of the shock wave is also reduced to different extents.
According to the method and the system for detecting the shock insulation efficiency of the shock insulation platform, time lag phenomenon caused by the shock insulation process of the shock insulation platform is processed, reliability of shock insulation efficiency evaluation results is improved, and meanwhile, calculation speed can meet online deployment.
Example two
An object of the present embodiment is to provide a seismic isolation efficiency evaluation system based on a multivariate dynamic time warping algorithm, including:
the acquisition module is used for: the method comprises the steps of acquiring multiaxial vibration time series data and multiaxial vibration time series data after vibration isolation;
and an alignment module: the method comprises the steps of calculating the similarity of the multiaxial vibration time series data and the multiaxial vibration time series data after vibration isolation by adopting a dynamic time warping algorithm, and aligning the multiaxial vibration time series data with the multiaxial vibration time series data after vibration isolation according to the similarity;
and an evaluation module: and the vibration isolation efficiency evaluation is performed according to the difference value between the aligned multiaxial vibration time series data and the multiaxial vibration time series data after vibration isolation.
The alignment module further comprises a distance calculation module, wherein the distance calculation module is used for: the method comprises the steps of calculating the data distance between multiaxial vibration time series data and multiaxial vibration time series data after vibration isolation by using Euclidean distance, calculating an accumulated distance matrix according to the calculated data distance, and calculating the similarity between the multiaxial vibration time series data and the multiaxial vibration time series data after vibration isolation by using a dynamic time warping algorithm according to the calculated distance matrix.
In the distance calculation module, further comprising:
the selecting module is used for selecting a plurality of diagonal strip areas adjacent to the opposite diagonal line and the opposite diagonal line in the distance matrix, and calculating according to the selected diagonal strip areas;
and a search module: the method comprises the steps of searching the shortest path in a selected diagonal area to obtain a distance comparison matrix, and taking the minimum value in the obtained distance comparison matrix as the starting point of the distance comparison matrix obtained next time;
and (3) an iteration module: and continuously carrying out shortest path search iteration until the shortest path is obtained by searching, and indicating the alignment corresponding relation between the multiaxial vibration time series data and the multiaxial vibration time series data after vibration isolation according to the shortest path.
It will be appreciated by those skilled in the art that the modules or steps of the invention described above may be implemented by general-purpose computer means, alternatively they may be implemented by program code executable by computing means, whereby they may be stored in storage means for execution by computing means, or they may be made into individual integrated circuit modules separately, or a plurality of modules or steps in them may be made into a single integrated circuit module. The present invention is not limited to any specific combination of hardware and software.
While the foregoing description of the embodiments of the present invention has been presented in conjunction with the drawings, it should be understood that it is not intended to limit the scope of the invention, but rather, it is intended to cover all modifications or variations within the scope of the invention as defined by the claims of the present invention.
Claims (10)
1. The seismic isolation efficiency evaluation method based on the multivariable dynamic time warping algorithm is characterized by comprising the following steps of:
acquiring multiaxial vibration time series data and multiaxial vibration time series data after vibration isolation;
calculating the similarity of the multiaxial vibration time series data and the multiaxial vibration time series data after vibration isolation by adopting a dynamic time warping algorithm, and aligning the multiaxial vibration time series data with the multiaxial vibration time series data after vibration isolation according to the similarity;
and according to the difference value between the aligned multiaxial vibration time series data and the multiaxial vibration time series data after vibration isolation, performing vibration isolation efficiency evaluation.
2. The method for evaluating the seismic isolation efficiency based on the multivariate dynamic time warping algorithm according to claim 1, wherein the euclidean distance is used for calculating the data distance between the multiaxial vibration time series data and the multiaxial vibration time series data after the seismic isolation, a distance matrix is calculated according to the calculated data distance, and the dynamic time warping algorithm is used for calculating the similarity between the multiaxial vibration time series data and the multiaxial vibration time series data after the seismic isolation according to the calculated distance matrix.
3. The method for evaluating the seismic isolation efficiency based on the multivariate dynamic time warping algorithm according to claim 2, wherein the similarity between the multiaxial vibration time series data and the multiaxial vibration time series data after the seismic isolation is calculated by the dynamic time warping algorithm according to the calculated distance matrix, specifically comprising:
selecting an anti-diagonal line and a plurality of diagonal line areas adjacent to the anti-diagonal line in the distance matrix, and calculating according to the selected diagonal line areas;
searching the shortest path in the selected diagonal area to obtain a distance comparison matrix, and taking the minimum value in the obtained distance comparison matrix as the starting point of the distance comparison matrix obtained next time;
and continuously carrying out shortest path search iteration until the shortest path is obtained by searching, and indicating the alignment corresponding relation between the multiaxial vibration time series data and the multiaxial vibration time series data after vibration isolation according to the shortest path.
4. The method for evaluating the seismic isolation efficiency based on the multivariate dynamic time warping algorithm according to claim 3, wherein when the minimum value is obtained in the distance comparison matrix in an iteration mode, if the position of the minimum value is the boundary of the current distance calculation area, the current distance calculation area is extended to two sides by one diagonal stripe.
5. A method for evaluating the seismic isolation efficiency based on a multivariate dynamic time warping algorithm according to claim 3, wherein if the minimum value calculated in the distance comparison matrix reaches the edge position of the distance matrix first, the iterative distance comparison matrix is stopped.
6. The method for evaluating the shock insulation efficiency based on the multivariate dynamic time warping algorithm according to claim 1, wherein the shock insulation efficiency evaluation is performed according to the difference value between the aligned multiaxial shock time series data and the shock-insulated multiaxial shock time series data, specifically:
calculating the vibration isolation difference value of the aligned multiaxial vibration time series data and the vibration-isolated multiaxial vibration time series data;
representing the vibration isolation efficiency according to the ratio of the calculated vibration isolation difference value to the data point of the multiaxial vibration time sequence data after corresponding vibration isolation;
based on the time sequence length, the average vibration isolation efficiency of each axial direction of the corresponding time period is obtained by utilizing weighted average according to the calculated vibration isolation efficiency, and then the comprehensive vibration isolation efficiency is obtained.
7. The method for evaluating the seismic isolation efficiency based on the multivariate dynamic time warping algorithm according to claim 6, wherein the seismic isolation efficiency is characterized according to the ratio of the calculated seismic isolation difference value to the data point of the corresponding multi-axial vibration time series data after the seismic isolation, specifically:
taking the ratio of the calculated seismic isolation difference value to the data point of the multiaxial vibration time series data after corresponding seismic isolation as the instantaneous seismic isolation efficiency;
and summing the instantaneous vibration isolation efficiencies of all the axial directions to obtain the vibration isolation efficiency in the whole time sequence range.
8. The seismic isolation efficiency evaluation system based on the multivariable dynamic time warping algorithm is characterized by comprising:
the acquisition module is used for: the method comprises the steps of acquiring multiaxial vibration time series data and multiaxial vibration time series data after vibration isolation;
and an alignment module: the method comprises the steps of calculating the similarity of the multiaxial vibration time series data and the multiaxial vibration time series data after vibration isolation by adopting a dynamic time warping algorithm, and aligning the multiaxial vibration time series data with the multiaxial vibration time series data after vibration isolation according to the similarity;
and an evaluation module: and the vibration isolation efficiency evaluation is performed according to the difference value between the aligned multiaxial vibration time series data and the multiaxial vibration time series data after vibration isolation.
9. The system for evaluating the seismic isolation efficiency based on the multivariate dynamic time warping algorithm according to claim 8, wherein in the alignment module, a distance calculation module is further included, wherein the distance calculation module: the method comprises the steps of calculating the data distance between multiaxial vibration time series data and multiaxial vibration time series data after vibration isolation by using Euclidean distance, calculating an accumulated distance matrix according to the calculated data distance, and calculating the similarity between the multiaxial vibration time series data and the multiaxial vibration time series data after vibration isolation by using a dynamic time warping algorithm according to the calculated distance matrix.
10. The system for evaluating the seismic isolation efficiency based on the multivariate dynamic time warping algorithm according to claim 9, wherein the distance calculation module further comprises:
the selecting module is used for selecting a plurality of diagonal strip areas adjacent to the opposite diagonal line and the opposite diagonal line in the distance matrix, and calculating according to the selected diagonal strip areas;
and a search module: the method comprises the steps of searching the shortest path in a selected diagonal area to obtain a distance comparison matrix, and taking the minimum value in the obtained distance comparison matrix as the starting point of the distance comparison matrix obtained next time;
and (3) an iteration module: and continuously carrying out shortest path search iteration until the shortest path is obtained by searching, and indicating the alignment corresponding relation between the multiaxial vibration time series data and the multiaxial vibration time series data after vibration isolation according to the shortest path.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311108066.8A CN116821713B (en) | 2023-08-31 | 2023-08-31 | Shock insulation efficiency evaluation method and system based on multivariable dynamic time warping algorithm |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311108066.8A CN116821713B (en) | 2023-08-31 | 2023-08-31 | Shock insulation efficiency evaluation method and system based on multivariable dynamic time warping algorithm |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116821713A true CN116821713A (en) | 2023-09-29 |
| CN116821713B CN116821713B (en) | 2023-11-24 |
Family
ID=88114950
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311108066.8A Active CN116821713B (en) | 2023-08-31 | 2023-08-31 | Shock insulation efficiency evaluation method and system based on multivariable dynamic time warping algorithm |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116821713B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117150932A (en) * | 2023-10-30 | 2023-12-01 | 浙江威格泵业有限公司 | Energy efficiency evaluation method of variable-frequency booster shielding pump |
Citations (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| IL113204A0 (en) * | 1995-03-30 | 1995-06-29 | Advanced Recognition Tech | Pattern recognition system |
| US20120070073A1 (en) * | 2010-09-18 | 2012-03-22 | Suryaprakash Kompalli | Searching document images |
| CN107105092A (en) * | 2017-04-18 | 2017-08-29 | 华东师范大学 | A kind of human body tumble recognition methods based on dynamic time warping |
| CN108154187A (en) * | 2018-01-04 | 2018-06-12 | 湘潭大学 | A kind of deep hole based on vibration signal, which is pecked, bores processing quality detection method |
| CN108320750A (en) * | 2018-01-23 | 2018-07-24 | 东南大学—无锡集成电路技术研究所 | A kind of implementation method based on modified dynamic time warping speech recognition algorithm |
| CN108664277A (en) * | 2018-05-15 | 2018-10-16 | 精伦电子股份有限公司 | Awakening method and device are lifted based on 3-axis acceleration sensor |
| CN109409496A (en) * | 2018-11-14 | 2019-03-01 | 重庆邮电大学 | One kind being based on the improved LDTW sequence similarity amount method of ant group algorithm |
| CN109783051A (en) * | 2019-01-28 | 2019-05-21 | 中科驭数（北京）科技有限公司 | A kind of Time Series Similarity computing device and method |
| CN110488218A (en) * | 2019-08-26 | 2019-11-22 | 国网重庆市电力公司电力科学研究院 | A kind of electric energy meter operating status appraisal procedure and assessment device |
| CN110749929A (en) * | 2019-10-28 | 2020-02-04 | 山东科技大学 | Machine learning-based complex area seismic reflection layer identification and tracking method |
| CN112446313A (en) * | 2020-11-20 | 2021-03-05 | 山东大学 | Volleyball action recognition method based on improved dynamic time warping algorithm |
| CN114547760A (en) * | 2022-04-27 | 2022-05-27 | 江苏南通冠仟新材料科技有限公司 | High-rise building shock insulation damping life management method based on data design optimization processing |
| CN114580071A (en) * | 2022-04-28 | 2022-06-03 | 江苏南通冠仟新材料科技有限公司 | Adjacent floor shock insulation damping comfort evaluation method based on computer aided design |
| CN115097526A (en) * | 2022-08-22 | 2022-09-23 | 江苏益捷思信息科技有限公司 | Seismic acquisition data quality evaluation method |
| CN115392284A (en) * | 2022-07-14 | 2022-11-25 | 天津大学 | Site micro-vibration source identification method based on machine learning |
| CN115436044A (en) * | 2022-09-02 | 2022-12-06 | 湖南五凌电力科技有限公司 | On-load tap-changer mechanical fault diagnosis method and device and electronic equipment |
| CN115600779A (en) * | 2022-10-19 | 2023-01-13 | 中国计量大学（Cn） | Heat supply effect on-line evaluation method based on constrained derivative dynamic time warping |
| CN116018245A (en) * | 2020-07-28 | 2023-04-25 | 川崎重工业株式会社 | State monitoring device, state abnormality determination method, and state abnormality determination program |
| CN116357396A (en) * | 2023-06-06 | 2023-06-30 | 精英数智科技股份有限公司 | Gas curve associated fluctuation anomaly identification method, device and related assembly |
| CN116559648A (en) * | 2023-05-31 | 2023-08-08 | 武汉黉门电工科技有限公司 | GIS isolating switch mechanical state detection method based on driving motor power detection |
| CN116612240A (en) * | 2023-05-22 | 2023-08-18 | 南京工业大学 | Construction method of building digital twin model for structural safety monitoring |
-
2023
- 2023-08-31 CN CN202311108066.8A patent/CN116821713B/en active Active
Patent Citations (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| IL113204A0 (en) * | 1995-03-30 | 1995-06-29 | Advanced Recognition Tech | Pattern recognition system |
| US20120070073A1 (en) * | 2010-09-18 | 2012-03-22 | Suryaprakash Kompalli | Searching document images |
| CN107105092A (en) * | 2017-04-18 | 2017-08-29 | 华东师范大学 | A kind of human body tumble recognition methods based on dynamic time warping |
| CN108154187A (en) * | 2018-01-04 | 2018-06-12 | 湘潭大学 | A kind of deep hole based on vibration signal, which is pecked, bores processing quality detection method |
| CN108320750A (en) * | 2018-01-23 | 2018-07-24 | 东南大学—无锡集成电路技术研究所 | A kind of implementation method based on modified dynamic time warping speech recognition algorithm |
| CN108664277A (en) * | 2018-05-15 | 2018-10-16 | 精伦电子股份有限公司 | Awakening method and device are lifted based on 3-axis acceleration sensor |
| CN109409496A (en) * | 2018-11-14 | 2019-03-01 | 重庆邮电大学 | One kind being based on the improved LDTW sequence similarity amount method of ant group algorithm |
| CN109783051A (en) * | 2019-01-28 | 2019-05-21 | 中科驭数（北京）科技有限公司 | A kind of Time Series Similarity computing device and method |
| CN110488218A (en) * | 2019-08-26 | 2019-11-22 | 国网重庆市电力公司电力科学研究院 | A kind of electric energy meter operating status appraisal procedure and assessment device |
| CN110749929A (en) * | 2019-10-28 | 2020-02-04 | 山东科技大学 | Machine learning-based complex area seismic reflection layer identification and tracking method |
| CN116018245A (en) * | 2020-07-28 | 2023-04-25 | 川崎重工业株式会社 | State monitoring device, state abnormality determination method, and state abnormality determination program |
| CN112446313A (en) * | 2020-11-20 | 2021-03-05 | 山东大学 | Volleyball action recognition method based on improved dynamic time warping algorithm |
| CN114547760A (en) * | 2022-04-27 | 2022-05-27 | 江苏南通冠仟新材料科技有限公司 | High-rise building shock insulation damping life management method based on data design optimization processing |
| CN114580071A (en) * | 2022-04-28 | 2022-06-03 | 江苏南通冠仟新材料科技有限公司 | Adjacent floor shock insulation damping comfort evaluation method based on computer aided design |
| CN115392284A (en) * | 2022-07-14 | 2022-11-25 | 天津大学 | Site micro-vibration source identification method based on machine learning |
| CN115097526A (en) * | 2022-08-22 | 2022-09-23 | 江苏益捷思信息科技有限公司 | Seismic acquisition data quality evaluation method |
| CN115436044A (en) * | 2022-09-02 | 2022-12-06 | 湖南五凌电力科技有限公司 | On-load tap-changer mechanical fault diagnosis method and device and electronic equipment |
| CN115600779A (en) * | 2022-10-19 | 2023-01-13 | 中国计量大学（Cn） | Heat supply effect on-line evaluation method based on constrained derivative dynamic time warping |
| CN116612240A (en) * | 2023-05-22 | 2023-08-18 | 南京工业大学 | Construction method of building digital twin model for structural safety monitoring |
| CN116559648A (en) * | 2023-05-31 | 2023-08-08 | 武汉黉门电工科技有限公司 | GIS isolating switch mechanical state detection method based on driving motor power detection |
| CN116357396A (en) * | 2023-06-06 | 2023-06-30 | 精英数智科技股份有限公司 | Gas curve associated fluctuation anomaly identification method, device and related assembly |
Non-Patent Citations (3)
| Title |
|---|
| D. GUTHALS等: "Wavefront compensation using liquid crystal spatial light modulators-scaling issues", 2000 DIGEST OF THE LEOS SUMMER TOPICAL MEETINGS, pages 17 - 18 * |
| 付晨;钟诚;叶波;: "MapReduce并行加速数据流多模式相似性搜索", 计算机应用, vol. 37, no. 01, pages 37 - 41 * |
| 李顺等: "基于关键帧和骨骼信息的人体动作识别方法", 传感器与微系统, vol. 38, no. 11, pages 26 - 30 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117150932A (en) * | 2023-10-30 | 2023-12-01 | 浙江威格泵业有限公司 | Energy efficiency evaluation method of variable-frequency booster shielding pump |
| CN117150932B (en) * | 2023-10-30 | 2024-01-26 | 浙江威格泵业有限公司 | Energy efficiency evaluation method of variable-frequency booster shielding pump |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116821713B (en) | 2023-11-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105784237B (en) | A kind of Micro-thrust test system and method | |
| CN116821713B (en) | Shock insulation efficiency evaluation method and system based on multivariable dynamic time warping algorithm | |
| CN110608862A (en) | Method for measuring dynamic mean deflection of bridge through tilt angle sensor | |
| CN201731984U (en) | Wireless inclination based bridge structure deflection measurement system | |
| CN108286987A (en) | A kind of unmanned plane flies the calibration method of control module MEMS motion sensors | |
| CN110285832B (en) | Method for detecting long-term stability defect of calibration parameter of fiber-optic gyroscope inertial measurement product | |
| CN104870952A (en) | Integrity of a civil structure | |
| CN111650539A (en) | Method, system and device for detecting operating parameters of lead and computer equipment | |
| CN107884743A (en) | Suitable for the direction of arrival intelligence estimation method of arbitrary structures sound array | |
| CN108180895A (en) | A kind of method based on height above sea level peak value measurement relative altitude | |
| CN105423978B (en) | Detection method, the device and system of the engineering piping length of multi-line system | |
| CN112985867B (en) | Steering engine testing method, device, equipment and storage medium | |
| CN116499696B (en) | Method for improving dynamic accuracy of attitude angle of wind tunnel model test model | |
| CN111197974B (en) | Barometer height measuring and calculating method based on Android inertial platform | |
| CN103528739A (en) | Impulse testing system | |
| CN111766557A (en) | Method for analyzing influence on detection precision of electric energy meter based on K-Means algorithm | |
| CN109758703A (en) | A kind of error correction systems and method for fire-fighting scene of a fire pressure-altitude sensor | |
| CN105093985B (en) | A kind of control sensor powering method | |
| CN114839482A (en) | Power frequency withstand voltage breakdown position positioning method and device of low-voltage comprehensive distribution box | |
| CN109540710B (en) | Integrated multi-parameter multi-channel material strength measurement and control system | |
| CN113134848A (en) | Measurement mode based on six-axis robot repeated positioning precision | |
| CN103322958B (en) | A kind of linear transducer and the detection method of linear transducer | |
| CN103505195B (en) | Method and device for measuring human body pulse and mobile terminal | |
| CN111596611A (en) | Dynamic characteristic test and analysis system of numerical control machine tool | |
| CN117109639B (en) | Temperature drift error detection method and system of hemispherical resonator gyroscope |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |