Damage disease identification method for wind-shield wall structure

Abstract

The invention relates to a damage disease identification method for a wind-shield wall structure, and belongs to the field of nondestructive testing of the wind-shield wall structure, and the method comprises the following steps: respectively applying vibration excitation to the wind-shield wall structure without damage disease and the wind-shield wall structure in an in-service state, and collecting dynamic response signals of the two wind-shield wall structures by using a sensor; virtual pulse response function signals SU and SD of the wind-shield wall structure in the in-service state and without damage diseases are calculated; subtraction is carried out on the SU and the SD to obtain a virtual pulse response function signal deviation S; obtaining a sub-band signal sequence {S} of S based on wavelet packet decomposition, and calculating a wavelet packet frequency band energy spectrum E < Somega > and an energy ratio spectrum ER < Somega > of {S}; constructing an improved wavelet packet frequency band energy ratio spectrum ER S; creating a wavelet packet characteristic frequency band vector ER < S > (P + 1) and a damage disease index sigma < ER >; and identifying the damage disease of the wind-shield wall structure in the in-service state through the sigma ER.

Description

Technical Field

[0001] The invention belongs to the technical field of nondestructive testing of windbreak wall structures and relates to a damage and disease identification method for windbreak wall structures. Background Art

[0002] The windbreak wall structure is mainly used to resist wind and waves, resist wind and sand, and protect driving safety. It is widely used in marine engineering, highway engineering, railway engineering and other fields. In the field of marine engineering, the windbreak wall is not only an important structure for offshore platforms to resist wind and waves and protect the safety of personnel and equipment, but also an important facility for offshore platforms to keep warm in winter. In the field of railway engineering, in order to resist crosswinds and sand and gravel attacks and protect driving safety, considering factors such as wind force, wind direction, frequency, terrain and line conditions, a total of 345 kilometers of windbreak walls in various forms such as embankment type, tension type, column plate type, and insertion type were built on the windward side of the Lanzhou-Xinjiang High-speed Railway in Xinjiang. However, under the combined effects of wind and sand erosion, temperature and humidity changes, load, carbonization, corrosion, material aging and other factors, damage and diseases such as concrete wall cracking, wall skin peeling, concrete bulging, and steel-concrete bond failure will continue to occur and accumulate on the windbreak wall. When these damages accumulate to a certain extent, the windbreak wall will be partially damaged at the least, and will be unstable or collapsed at the worst, resulting in major casualties or huge economic losses. Therefore, it is necessary to diagnose the damage and diseases of windbreak walls in service in order to identify the damage and diseases of windbreak walls in time.

[0003] At present, the research on windbreak wall structure mainly focuses on the following aspects: 1) Study on the damage mechanism of windbreak wall structure under the action of wind and sand erosion, freeze-thaw cycle, carbonization and other factors; 2) Study on the aerodynamic response law of coupling between windbreak wall and moving train; 3) Study on the wind and sand deposition law on both sides of windbreak wall under the action of wind and sand two-phase flow; 4) Study on the influence of windbreak wall structure form, height, thickness and spacing on its windproof characteristics. However, there are relatively few studies on the identification of damage and disease of windbreak wall structure, and there is still a lack of relevant literature.

[0004] In view of this, it is urgent to carry out research on the damage and disease identification of windbreak wall structures, and to develop a fast, efficient, simple, convenient, non-destructive, intelligent, and green and environmentally friendly method for windbreak wall structure damage and disease identification, so as to timely identify the damage and disease characteristics of windbreak walls and provide a reference for the design, construction, and maintenance of windbreak wall structures. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide a damage and disease identification method for windbreak wall structures. The method is based on the wavelet packet band energy spectrum theory, converts the virtual impulse response function signal deviation between the dynamic response of the windbreak wall structure in a non-damage and disease state and in service into wavelet packet band energy, and creates wavelet packet characteristic band vectors and damage and disease indicators based on the damage and disease sensitivity analysis of the frequency band. The damage and disease characteristics of the windbreak wall can be quickly identified through the damage and disease indicators.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] A method for identifying damage and disease of a windbreak wall structure comprises the following steps:

[0008] S1: Apply vibration excitation to the windbreak wall structure without damage and in service respectively, and use sensors to collect dynamic response signals of the windbreak wall structure without damage and in service under the excitation;

[0009] S2: Calculate the virtual impulse response function signal S of the windbreak wall structure without damage using the collected dynamic response signal U and the virtual impulse response function signal S of the windbreak wall structure in service D ;

[0010] S3: For S U and S D Perform subtraction operation to obtain the virtual impulse response function signal deviation △S;

[0011] S4: Based on wavelet packet decomposition, obtain the sub-band signal sequence {△S} of △S, and calculate the wavelet packet band energy spectrum E of {△S} △Sω Energy Ratio Spectrum ER △Sω ;

[0012] S5: Damage and disease sensitivity analysis based on sub-bands, constructing improved wavelet packet band energy ratio spectrum ER △S ;

[0013] S6: Create wavelet packet feature band vector ER △S(P+1) and damage index σ ER ;

[0014] S7: Through σ ER Identify damage and diseases of windbreak wall structures in service.

[0015] Furthermore, in step S1, sensors and wireless signal collection equipment are first arranged on the windshield structure, and the wireless signal collection equipment is powered by solar panels and batteries. The power response signal collected by the sensor is transmitted to the computer through the wireless signal collection equipment, and steps S2 to S7 are executed by the computer.

[0016] Further, step S2 specifically includes: taking the dynamic response of the reference point as the virtual excitation and the dynamic response of the calculation point as the virtual response, respectively calculating the virtual impulse response function signal between the virtual excitation and the virtual response of the windbreak wall structure in the undamaged and in-service state, and obtaining the virtual impulse response function signal S of the windbreak wall structure in the undamaged and in-service state U and the virtual impulse response function signal S of the windbreak wall structure in service D .

[0017] Further, step S3 specifically includes:

[0018] For S U and S D Perform subtraction to obtain the virtual impulse response function signal deviation △S between dynamic responses, as shown in the following formula:

[0019] △S=S U -S D

[0020] Further, step S4 specifically includes:

[0021] Perform i-layer wavelet packet decomposition on △S to obtain its sub-band signal sequence {△S}, as shown in the following formula:

[0022]

[0023] Based on the wavelet packet energy spectrum theory, the wavelet packet band energy spectrum E of {△S} can be obtained △Sω , as shown below:

[0024]

[0025] Finally, we get the wavelet packet band energy ratio spectrum ER of {△S} △Sω , as shown below:

[0026]

[0027] Further, in step S5, based on the damage and disease sensitivity analysis of the sub-band, ER △Sω Sort the frequency band energy ratio from large to small to get the improved wavelet packet frequency band energy ratio spectrum ER △S , as shown below:

[0028]

[0029] Further, step S6 specifically includes:

[0030] Define the cumulative energy ratio α and threshold α0, and use α0 to get the value of ER △SThe first P sub-bands with large energy are selected, and the contribution of the residual band to the identification of damage is considered to create the wavelet packet characteristic band vector ER △S(P+1) , as shown below:

[0031]

[0032] Introducing the energy ratio mean M ER :

[0033]

[0034] Then define the damage index—energy ratio standard deviation σ ER :

[0035]

[0036] Further, in step S7, ER Identify damage to windbreak walls, including:

[0037] σ ER The value is zero, and the windbreak wall structure has no damage; ER The value is not zero, and the windbreak wall structure is damaged; and σ ER The larger the value, the more serious the damage to the windbreak wall structure.

[0038] The beneficial effects of the present invention are as follows: the present invention proposes an improved wavelet packet band energy ratio spectrum based on the wavelet packet band energy spectrum theory for the in-service windbreak wall structure, and realizes the identification of the damage and disease characteristics of the windbreak wall structure based on the created wavelet packet characteristic band vector and damage and disease index. Therefore, the method provides an effective means for the damage and disease identification of the in-service windbreak wall structure, and has significant practical application value for ensuring structural safety and preventing potential accidents. Moreover, compared with the previous damage and disease identification methods, the method first proposes the concept of virtual impulse response function signal deviation, and then through the wavelet packet band energy spectrum analysis of the virtual impulse response function signal deviation, based on the band damage and disease sensitivity analysis, creates the wavelet packet characteristic band vector and damage and disease index, and identifies the damage and disease of the windbreak wall structure, which has the characteristics of fast and efficient, simple and convenient, non-destructive and intelligent, green and environmentally friendly. Although the windbreak wall structure is diverse in form, the damage and disease identification principle of the windbreak wall structure is the same. Therefore, this method can be widely used in the damage and disease identification of various types of windbreak wall structures in service (such as column-slab windbreak walls, tension windbreak walls, embankment windbreak walls, cantilever windbreak walls, and plug-in windbreak walls, etc.), and has great application space in the future.

[0039] Other advantages, objectives and features of the present invention will be described in the following description to some extent, and to some extent, will be obvious to those skilled in the art based on the following examination and study, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below in conjunction with the accompanying drawings, wherein:

[0041] Figure 1 is the virtual impulse response function signal S of the windbreak wall structure without damage and disease U ;

[0042] Figure 2 is the virtual impulse response function signal S of the windbreak wall structure dynamic response in service D ;

[0043] Figure 3 It is the virtual impulse response function signal deviation △S between the dynamic response of the windbreak wall structure in the undamaged state and in service state;

[0044] Figure 4 is the wavelet packet band energy ratio spectrum ER△Sω of the virtual impulse response function signal deviation △S between the dynamic responses of the windbreak wall structure;

[0045] Figure 5 The improved wavelet packet band energy ratio spectrum ER is the virtual impulse response function signal deviation △S between the dynamic responses of the windbreak wall structure △S ;

[0046] Figure 6 is the wavelet packet characteristic frequency band vector ER of the virtual impulse response function signal deviation △S between the dynamic responses of the windbreak wall structure △S(P+1) and damage index σ ER ;

[0047] Figure 7 is a principle block diagram of an embodiment of the present invention;

[0048] Figure 8 The present invention is a flowchart of structural damage identification of an in-service windbreak wall according to an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0050] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and thus the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0051] In the following description, numerous details are discussed to provide a more thorough explanation of the embodiments of the present invention. However, it is obvious to those skilled in the art that the embodiments of the present invention can be implemented without these specific details. In other embodiments, well-known structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of the present invention difficult to understand.

[0052] The present invention provides a method for identifying damage and disease of a windbreak wall structure, comprising the following steps:

[0053] Step 1: According to the actual needs of the project, a certain number of sensors and wireless signal collection devices are arranged on the windbreak wall structure, and the sensors and wireless signal collection devices are connected;

[0054] Step 2: Connect the solar panel and the battery, charge the battery through the solar panel, connect the battery and the wireless signal collection device, and use the battery to continuously power the wireless signal collection device;

[0055] Step 3: Vibration excitation is applied to the windbreak wall structure without damage and in service by means of an excitation device, and the sensor collects the dynamic response signal of the windbreak wall structure under the excitation, and the collected signal is transmitted to the computer through a wireless signal collection device;

[0056] Step 4: The computer processes the collected dynamic response signals to obtain the virtual impulse response function signal S of the dynamic response of the windbreak wall structure without damage U ,like Figure 1 As shown in the figure, the virtual impulse response function signal S of the windbreak wall structure dynamic response in service state D ,like Figure 2 As shown;

[0057] Step 5: S U and S D Perform subtraction operation to obtain the virtual impulse response function signal deviation △S;

[0058] Specific: For S U and S D By subtracting, the virtual impulse response function signal deviation △S between dynamic responses can be expressed as:

[0059] △S=S U -S D (1)

[0060] △S Figure 3 As shown;

[0061] Step 6: Perform 6-layer wavelet packet decomposition on △S to obtain its sub-band signal sequence {△S}, and calculate the wavelet packet band energy spectrum E of {△S} △Sω and wavelet packet energy ratio spectrum ER △Sω ;

[0062] Specifically: △S is decomposed by 6-layer wavelet packet to obtain its sub-band signal sequence {△S}, as shown in formula (2):

[0063]

[0064] Then calculate the jth (j=1,2,…,2 6 ) sub-band signal deviation △S jωj· The wavelet packet band energy E △Sjωj :

[0065]

[0066] We can further obtain the wavelet packet band energy spectrum E of {△S} △Sω , as shown in formula (4):

[0067]

[0068] The wavelet packet band energy ratio ER introduced by {△S} △Sjωj :

[0069]

[0070] We can further obtain the wavelet packet band energy ratio spectrum ER of {△S} △Sω , as shown in formula (6):

[0071]

[0072] Wavelet packet band energy ratio spectrum ER of {△S}△Sω ,like Figure 4 shown.

[0073] Step 7: Based on the sub-band damage sensitivity analysis, the improved wavelet packet band energy ratio spectrum ER is obtained △S ;

[0074] Specifically: ER △Sω The higher the energy of the jth sub-band, the stronger the sub-band deviation signal △S j On the contrary, if ER △Sω The lower the j-th sub-band energy is or even zero, the smaller the sub-band signal deviation is. j The lower the variation, the lower it is even. △Sω The greater the energy of the neutron band, the greater its sensitivity to damage. △Sω The sub-band with larger energy can be used to reflect the structural damage information. △Sω Sort the frequency band energy ratio from large to small to get the improved wavelet packet frequency band energy ratio spectrum ER △S , as shown in formula (7):

[0075]

[0076] Improved wavelet packet band energy ratio spectrum ER △S ,like Figure 5 shown.

[0077] Step 8: In order to effectively extract damage and disease information, consider the contribution of the residual frequency band to damage and disease identification and create a wavelet packet characteristic frequency band vector ER △S(P+1) and damage index σ ER ;

[0078] Specifically: In ER △S In the above equation, those sub-bands with extremely small or zero energy are difficult to effectively reflect the damage information. In order to extract the structural damage information more effectively, the cumulative energy ratio α is defined as:

[0079]

[0080] And define a threshold α0 (α≤α0), through α0 (let α0=98%), we can get △Sω The first 12 sub-bands with larger energy are selected, and the remaining (2 6 -12=52) sub-bands. However, considering the integrity of the damage information and the contribution of the sub-bands with smaller energy to the identification of damage, the remaining 52 sub-bands are combined into the (12+1=13)th band, and the 13th band is called the residual band, and the energy ratio of the residual band is defined as ER△S13 for:

[0081]

[0082] So create a new energy ratio sequence instead of ER △S , and called the wavelet packet characteristic band vector ER △S13 , as shown in formula (10):

[0083]

[0084] Wavelet packet characteristic band vector ER △S13 ,like Figure 6 shown.

[0085] In order to quantitatively extract damage information, the energy ratio mean M is introduced. ER :

[0086]

[0087] Then define the damage and disease index reflecting the damage and disease information—energy ratio standard deviation σ ER :

[0088]

[0089] Step 9: Through σ ER Identify damage and disease of windbreak walls;

[0090] Specifically: ER The value is zero, indicating that the amplitude of △S is zero, that is, {S U} and {S D} coincide with each other, so the windbreak wall structure has no damage; σ ER If the value is not zero, it means that the amplitude of △S is not zero, and there is a deviation in the △S sub-band signal, so there is damage to the windbreak wall structure. ER The larger the value, the greater the variation of △S, the greater the deviation of the △S sub-band signal, and the more serious the damage to the windbreak wall structure.

[0091] Damage and disease index σ ER Values, such as Figure 6 as shown in .

[0092] In the above embodiments, the description's reference to "this embodiment" indicates that a particular feature, structure, or characteristic described in conjunction with the embodiment is included in at least some embodiments, but not necessarily all embodiments. Multiple occurrences of "this embodiment" do not necessarily all refer to the same embodiment.

[0093] In the above-described embodiments, although the invention has been described in conjunction with specific embodiments of the invention, many substitutions, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art based on the foregoing description. For example, other storage structures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed. Embodiments of the invention are intended to encompass all such substitutions, modifications, and variations that fall within the broad scope of the appended claims.

[0094] This embodiment further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, any one of the methods in this embodiment is implemented.

[0095] This embodiment also provides an electronic terminal, including: a processor and a memory;

[0096] The memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the terminal executes any one of the methods in this embodiment.

[0097] The computer-readable storage medium in this embodiment can be understood by ordinary technicians in this field: all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to the computer program. The aforementioned computer program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk and other media that can store program codes.

[0098] The electronic terminal provided in this embodiment includes a processor, a memory, a transceiver and a communication interface. The memory and the communication interface are connected to the processor and the transceiver and complete communication with each other. The memory is used to store computer programs, the communication interface is used to communicate, and the processor and the transceiver are used to run computer programs so that the electronic terminal executes each step of the above method.

[0099] In this embodiment, the memory may include a random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0100] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0101] The present invention can be used in many general or special computing system environments or configurations, such as personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and the like.

[0102] The present invention may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0103] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution, which should be included in the scope of the claims of the present invention.

Claims

1. A method for identifying damage and disease of a windbreak wall structure, characterized in that: The following steps are involved: S1: Apply vibration excitation to the windbreak wall structure without damage and in service respectively, and use sensors to collect dynamic response signals of the windbreak wall structure without damage and in service under the excitation; S2: Calculate the virtual impulse response function signal S of the windbreak wall structure without damage using the collected dynamic response signal U and the virtual impulse response function signal S of the windbreak wall structure in service D ; S3: For S U and S D Perform subtraction operation to obtain the virtual impulse response function signal deviation △S; S4: Based on wavelet packet decomposition, obtain the sub-band signal sequence {△S} of △S, and calculate the wavelet packet band energy spectrum E of {△S} △Sω Energy Ratio Spectrum ER △Sω ; S5: Damage and disease sensitivity analysis based on sub-bands, constructing improved wavelet packet band energy ratio spectrum ER △S ; S6: Create wavelet packet feature band vector ER △S(P+1) and damage index σ ER ; S7: Through σ ER Identify damage and diseases of windbreak wall structures in service.

2. The damage and disease identification method for windbreak wall structure according to claim 1 is characterized in that: In step S1, firstly, sensors and wireless signal collection equipment are arranged on the windshield structure, and the wireless signal collection equipment is powered by solar panels and batteries. The power response signal collected by the sensor is transmitted to the computer through the wireless signal collection equipment, and steps S2 to S7 are executed by the computer.

3. The damage and disease identification method for windbreak wall structure according to claim 1 is characterized in that: Step S2 specifically includes: taking the dynamic response of the reference point as the virtual excitation and the dynamic response of the calculation point as the virtual response, respectively calculating the virtual impulse response function signal between the virtual excitation and the virtual response of the windbreak wall structure in the undamaged and in-service state, and obtaining the virtual impulse response function signal S of the windbreak wall structure in the undamaged and in-service state. U and the virtual impulse response function signal S of the windbreak wall structure in service D .

4. The damage and disease identification method for windbreak wall structure according to claim 1 is characterized in that: Step S3 specifically includes: For S U and S D Perform subtraction to obtain the virtual impulse response function signal deviation △S between dynamic responses, as shown in the following formula: △S=S U -S D 。 5. The damage and disease identification method for windbreak wall structure according to claim 1 is characterized in that: Step S4 specifically includes: Perform i-layer wavelet packet decomposition on △S to obtain its sub-band signal sequence {△S}, as shown in the following formula: Based on the wavelet packet energy spectrum theory, the wavelet packet band energy spectrum E of {△S} can be obtained △Sω , as shown below: Finally, we get the wavelet packet band energy ratio spectrum ER of {△S} △Sω , as shown below:

6. The damage and disease identification method for windbreak wall structure according to claim 1 is characterized in that: In step S5, based on the damage and disease sensitivity analysis of the sub-band, ER △Sω Sort the frequency band energy ratio from large to small to get the improved wavelet packet frequency band energy ratio spectrum ER △S , as shown below:

7. The damage and disease identification method for windbreak wall structure according to claim 1 is characterized in that: Step S6 specifically includes: Define the cumulative energy ratio α and threshold α0, and use α0 to get the value of ER △S The first P sub-bands with large energy are selected, and the contribution of the residual band to the identification of damage is considered to create the wavelet packet characteristic band vector ER △S(P+1) , as shown below: Introducing the energy ratio mean M ER : Then define the damage index—energy ratio standard deviation σ ER :

8. The damage and disease identification method for windbreak wall structure according to claim 1 is characterized in that: In step S7, σ ER Identify damage to windbreak walls, including: σ ER The value is zero, and the windbreak wall structure has no damage; ER The value is not zero, and the windbreak wall structure is damaged; and σ ER The larger the value, the more serious the damage to the windbreak wall structure.

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