Bridge pier health status monitoring method and system

Abstract

The present invention discloses a method and system for monitoring the health status of bridge piers, and relates to the technical field of monitoring the health status of bridge piers. The method comprises: selecting a flexible current sensor suitable for the surface of the bridge pier, and determining the arrangement position of the flexible current sensor on the surface of the bridge pier, and adhering the flexible current sensor to the determined arrangement position to form a sensor network; using a movable collector to establish a wireless connection with the flexible current sensor, and dynamically collecting current data at different positions; extracting features from the current data and constructing a feature subset; based on the feature subset, calculating the bridge pier health status index, and completing the bridge pier health status monitoring. The present invention innovatively introduces improved multi-scale sample entropy and wavelet packet energy entropy feature extraction technology, as well as an electrical parameter extraction method based on a fractional impedance model, which greatly improves the ability to identify minor damage and nonlinear dynamic characteristics of bridge piers.

Description

Technical Field

[0001] The present invention relates to the technical field of bridge pier health status monitoring, and in particular to a bridge pier health status monitoring method and system. Background Art

[0002] With the rapid development of transportation infrastructure, bridges, as key transportation hubs, have received increasing attention for their structural safety and durability. As important load-bearing components of bridges, the health status of bridge piers is directly related to the overall safety performance of the bridge. Therefore, the research and application of pier health monitoring technology has gradually become a hot topic in the field of structural engineering. Early pier monitoring technology mainly relied on manual inspections and traditional rigid sensors. These sensors often detect parameters such as stress, displacement or vibration on the surface of piers through physical contact. Although they can provide effective monitoring data in some cases, their physical properties and rigid structures determine that they are difficult to match well with the complex geometric shapes of piers, especially when facing irregular or curved structures on the surface. The accuracy and integrity of data acquisition are insufficient. In addition, traditional monitoring systems are often fixed in layout, lack flexibility, have limited monitoring coverage, and are difficult to adapt to the dynamic changes of the complex environment of piers.

[0003] Existing pier health monitoring technologies have significant limitations, especially in terms of electrical performance monitoring. Traditional methods usually rely on pre-embedded fixed electrodes during the construction of the pier to monitor the current changes inside the pier. However, this method requires precise electrode arrangement during construction, and since the electrodes can only be installed in local locations on the pier, the monitoring range is limited and cannot fully cover the entire pier surface or structure. In addition, once the electrode pre-embedded position is determined, it cannot be flexibly adjusted later, and the monitoring data is limited to these fixed locations, making it difficult to reflect the dynamically changing electrical properties of the pier during long-term use. This limitation greatly reduces the effectiveness of electrical monitoring, especially when the pier may experience overall degradation, crack expansion, and local damage under different environmental stresses, it is difficult for existing technologies to achieve effective early warning and real-time monitoring. Summary of the invention

[0004] In view of the problems existing in the existing monitoring technology, the present invention is proposed.

[0005] Therefore, the problem to be solved by the present invention is that electrodes need to be pre-buried when manufacturing bridge piers, so that only the current changes and electrical properties at local fixed positions can be measured.

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

[0007] In a first aspect, the present invention provides a method for monitoring the health status of a bridge pier, comprising:

[0008] Selecting a flexible current sensor suitable for the surface of the bridge pier, determining the arrangement position of the flexible current sensor on the surface of the bridge pier, and adhering the flexible current sensor to the determined arrangement position to form a sensor network;

[0009] Using a mobile collector to establish a wireless connection with the flexible current sensor to dynamically collect current data at different locations;

[0010] Extracting features from the current data to construct a feature subset;

[0011] Based on the feature subset, a bridge pier health status index is calculated to complete the bridge pier health status monitoring;

[0012] The arrangement positions include column areas, beam areas and foundation areas;

[0013] The column area is evenly divided into three sub-areas: upper, middle and lower along the pier height direction;

[0014] The crossbeam region includes the connection with the column region, the mid-span portion and the support;

[0015] The foundation area includes the underwater portion of the pier and the water-soil interface.

[0016] The arrangement positions also include stress concentration points and potential crack prone locations;

[0017] The stress concentration point is the area where the equivalent stress under static and dynamic loads solved by the finite element method exceeds 80% of the material yield strength, as shown in the following formula: ;in, is the stress deviator tensor, is the equivalent stress, is the yield strength of the material.

[0018] As a preferred solution of the bridge pier health status monitoring method of the present invention, the determination of the potential crack prone location includes calculating J Points, when the J When the integral value is approximately equal to the critical fracture toughness of the material, it is considered that cracks are likely to occur at that location;

[0019] Said J The integral is calculated as follows: ;in, is the strain energy density, Along the integral path The surface force component, is the displacement component, is the integral path The outward normal vector at any point is x The weight in direction, is the critical fracture toughness, is the displacement component about x The partial derivative of x The rate of change in direction.

[0020] As a preferred solution of the bridge pier health status monitoring method of the present invention, the feature subset includes time domain features, frequency domain features and electrical performance features;

[0021] The time domain features include multi-scale sample entropy;

[0022] The frequency domain feature is determined by converting the current signal from the time domain to the frequency domain, and identifying the main frequency components in the current signal and their corresponding energy distribution by calculating the power spectrum density;

[0023] The electrical performance feature extraction is obtained by equivalent resistance, conductivity calculation and parameter extraction based on a fractional impedance model.

[0024] As a preferred solution of the bridge pier health status monitoring method of the present invention, the calculation of the multi-scale sample entropy is shown in the following formula: ;in, is a time series, is the embedding dimension, is the similarity threshold, is the scale factor, and are the matching counts in m and m+1 dimensional phase space, respectively.

[0025] As a preferred solution of the bridge pier health status monitoring method of the present invention, the current signal is converted from the time domain to the frequency domain, as shown in the following formula: ;in, represents the frequency domain signal, is the time domain signal, is the signal length, is the frequency index, is the time index, is an imaginary unit, To calculate the amplitude and phase of each frequency component;

[0026] The power spectral density is calculated as follows: ;in, is the Fourier transform result of the signal, is the sampling frequency;

[0027] The energy distribution is obtained by calculating the energy entropy, and the calculation of the energy entropy is shown in the following formula: ;in, is the energy entropy of the ith frequency band, is the normalized energy of the jth wavelet packet coefficient in the ith frequency band, is the frequency band weight factor based on power spectral density;

[0028] in, The calculation of is as follows: ;in, is the average power spectral density of the ith frequency band, M is the total number of frequency bands, is the average power spectral density of the kth frequency band.

[0029] As a preferred solution of the bridge pier health status monitoring method of the present invention, the calculation of the bridge pier health status index includes:

[0030] Normalizing each feature of the feature subset, and calculating a dynamic weight of the normalized feature;

[0031] Calculate the weighted average of all characteristics to obtain the pier health index;

[0032] The calculation of the dynamic weight is shown in the following formula: ;in, It is a feature The basic weight of is the adjustment factor, usually between 0.2 and 0.5. It reflects the degree to which the characteristic deviates from the ideal state. Features The dynamic weight of are the standardized features.

[0033] In a second aspect, the present invention provides a pier health status monitoring system, comprising:

[0034] A network construction module, used for selecting a flexible current sensor suitable for the surface of the bridge pier, determining the arrangement position of the flexible current sensor on the surface of the bridge pier, and adhering the flexible current sensor to the determined arrangement position to form a sensor network;

[0035] A data acquisition module is used to establish a wireless connection with the flexible current sensor using a movable collector to dynamically collect current data at different positions;

[0036] A feature extraction module, used to extract features from the current data and construct a feature subset;

[0037] The status monitoring module is used to calculate the pier health status index based on the feature subset and complete the pier health status monitoring.

[0038] The beneficial effect of the present invention is that by adopting flexible current sensors and movable collectors, combined with advanced finite element analysis models and multi-scale damage theory, all-round and high-precision health status monitoring of bridge piers is achieved. This method innovatively introduces improved multi-scale sample entropy and wavelet packet energy entropy feature extraction technology, as well as an electrical parameter extraction method based on a fractional impedance model, which greatly improves the ability to identify minor damage and nonlinear dynamic characteristics of bridge piers. At the same time, by introducing dynamic weight calculation and a comprehensive health status index evaluation system, accurate quantification and classification of the health status of bridge piers are achieved. This comprehensive and systematic monitoring method not only improves the accuracy and reliability of bridge pier health status assessment, but also provides a scientific basis for the formulation of bridge maintenance strategies, effectively prolongs the service life of bridges, and improves the safety and economic benefits of transportation infrastructure. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0040] Figure 1 Flow chart of the pier health status monitoring method. DETAILED DESCRIPTION

[0041] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0042] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0043] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0044] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0045] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0046] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0047] Example 1: Reference Figure 1 , which is the first embodiment of the present invention, provides a method for monitoring the health status of a bridge pier, comprising:

[0048] Select a flexible current sensor suitable for the surface of the bridge pier. The flexible current sensor has the characteristics of being bendable and stretchable.

[0049] Further, determining the arrangement position of the flexible current sensor on the surface of the bridge pier, the arrangement position includes the column, beam and foundation part of the bridge pier;

[0050] More specifically, according to the results of the force analysis of the pier structure, the pier surface is divided into multiple monitoring areas, including the column area, the beam area and the foundation area. The column area is evenly divided into three sub-areas: upper, middle and lower along the height direction of the pier; the beam area includes the connection with the column, the mid-span part and the vicinity of the support; the foundation area includes the underwater part and the water-soil interface.

[0051] Then, in each monitoring area, stress concentration points and potential crack-prone locations are determined based on the pre-established finite element analysis model. At these key locations, a high-density sensor layout plan is planned to achieve focused monitoring of these areas.

[0052] For example, the finite element analysis model is based on nonlinear multi-scale coupling theory, and the control equation of the finite element analysis model is as follows: ;in, is the divergence of the stress tensor, is the stress tensor, is the body force vector, is the density, is the acceleration vector.

[0053] In the process of designing the finite element analysis model, the heterogeneity of the pier material is considered and a multi-scale damage factor is introduced. , the constitutive relation modified by multi-scale damage factor: ;

[0054] in, is the elasticity tensor, is the strain tensor.

[0055] The existing solutions for multi-scale damage factors have given a complete definition, and this embodiment will not elaborate on it.

[0056] To describe the crack propagation, the phase field fracture model is used: ; and the crack evolution equation: ;in, is the damage variable, is the fracture energy, is the length parameter, is the positive strain energy density, is a degradation function.

[0057] Based on the above model, the stress distribution under static and dynamic loads is solved by finite element method. The stress concentration point is defined as the equivalent stress Exceeding the material yield strength 80% of the area: ;in, is the stress deviator tensor.

[0058] Potential crack prone locations are calculated J The integral is determined when J The integral value is close to the critical fracture toughness of the material When , it is considered that this position is prone to cracks: ;in, is the strain energy density, Along the integral path The surface force component, is the displacement component, is the integral path The outward normal vector at any point is x The weight in direction, is the critical fracture toughness, is the displacement component about x The partial derivative of x The rate of change in direction.

[0059] After determining stress concentration points and potential crack-prone locations, a high-density sensor layout is planned at these key locations to achieve focused monitoring of these areas.

[0060] More specifically, a concentric circle arrangement strategy is adopted around the stress concentration point. With the stress concentration point as the center, multiple flexible current sensors are arranged radially, with the spacing gradually increasing from the inside to the outside. The inner circle spacing is 5 cm, and the maximum outer circle spacing does not exceed 20 cm, to ensure accurate capture of stress gradient changes. For potential crack-prone locations, a grid arrangement method is adopted. Sensors are arranged in both vertical and parallel directions in the predicted crack extension direction to form a dense grid with a grid size of 10 cm × 10 cm to monitor the initiation and extension of cracks.

[0061] In the transition area between the two types of key positions, an adaptive density distribution strategy is adopted. The sensor density decreases as the distance from the key position increases, but the distance between any two adjacent sensors is ensured not to exceed 30cm. At the same time, considering the geometric characteristics of the pier structure, the layout density of flexible sensors is increased in special structures such as corners and curved transition areas, and the spacing is reduced to 3-5cm. In addition, in order to improve the redundancy and reliability of monitoring, at least three sensors with the same function are arranged at each key position to form a local sensor cluster, and the measurement accuracy and anti-interference ability are improved through data fusion technology. Finally, combined with the overall stress characteristics of the pier, a uniform layout interval of 50cm is maintained at non-critical positions to achieve comprehensive monitoring of the overall structural health status.

[0062] Adhere the flexible current sensor to the determined layout position to form a sensor network;

[0063] Then, the mobile collector is used to establish a wireless connection with the flexible current sensor to dynamically collect current data at different locations; time series analysis is performed on the collected current data to extract current change characteristics and electrical performance parameters.

[0064] Specifically, the collected raw current data is preprocessed. Then, time domain feature extraction is performed. The statistical characteristics of the current signal are calculated, including the mean, standard deviation, kurtosis and skewness. The nonlinear time series analysis method is used to quantify the complexity and regularity of the current signal. However, the traditional sample entropy only analyzes the signal complexity at a single scale, thereby ignoring the dynamic characteristics of the pier structure at different time scales. The improved multi-scale sample entropy of the present invention captures the complexity changes of the current signal at multiple time scales by introducing a scale factor τ. This is particularly effective for identifying small and progressive damage in pier structures, and an improved multi-scale sample entropy (IMSE) calculation method is proposed: ;in, is a time series, is the embedding dimension, is the similarity threshold, is the scale factor, and are the matching counts in m and m+1 dimensional phase space, respectively.

[0065] Subsequently, frequency domain feature extraction is performed. The current signal is converted from the time domain to the frequency domain by applying the fast Fourier transform (FFT), and its spectral characteristics are deeply analyzed. Specifically, the power spectral density (PSD) is calculated to identify the main frequency components in the current signal and their corresponding energy distribution. The wavelet packet transform is further introduced, combined with the time-frequency analysis technology, to extract the energy characteristics of each frequency band, and construct the frequency band energy ratio feature vector. In practical applications, it is found that the traditional frequency domain analysis method cannot fully describe the time-frequency characteristics of the non-stationary current signal in the pier structure. Therefore, this embodiment proposes a feature extraction method based on wavelet packet energy entropy on this basis, which is used to more accurately quantify the energy distribution and complexity of the frequency domain signal.

[0066] To elaborate, the fast Fourier transform (FFT) is used to convert the current signal from the time domain to the frequency domain, which can be expressed as follows: ;in, represents the frequency domain signal, is the time domain signal, is the signal length, is the frequency index, is the time index, is an imaginary unit, To calculate the amplitude and phase of each frequency component.

[0067] The power spectral density (PSD) can be calculated using the following formula: ;in, is the Fourier transform result of the signal, is the sampling frequency.

[0068] The improved wavelet packet energy entropy feature extraction method can be expressed as follows: ;in, is the energy entropy of the ith frequency band, is the normalized energy of the jth wavelet packet coefficient in the ith frequency band, is the frequency band weight factor based on power spectrum density, and the specific calculation formula is as follows: ;in, is the average power spectral density of the ith frequency band, M is the total number of frequency bands, is the average power spectral density of the kth frequency band.

[0069] The better feature extraction method of wavelet packet energy entropy further improves the quantification ability of current signal complexity through refined analysis of the energy of each frequency band, and more comprehensively characterizes the health status of the bridge pier.

[0070] Next, the electrical performance parameters are extracted. Based on Ohm's law and Kirchhoff's law, and combined with the geometric parameters of the pier structure, the equivalent resistance and conductivity of the pier are calculated. In addition, the complex impedance analysis method is used to construct the Nyquist plot by measuring the impedance response at different frequencies, and to extract the key parameters of the equivalent circuit model, such as parallel capacitance and charge transfer resistance. On this basis, a parameter extraction method based on the fractional-order impedance model is proposed to further improve the characterization accuracy of the electrical performance and ensure a more comprehensive electrical evaluation of the health status of the pier.

[0071] It needs to be explained in detail that since the equivalent resistance and conductivity of the bridge pier are prior art, this embodiment will not be elaborated in detail.

[0072] The parameter extraction method based on the fractional-order impedance model can be expressed as follows: ;in, is the complex impedance, is the high frequency limiting resistance, is the DC resistance, is the characteristic time constant, is a fractional exponential (0<α<1), is the angular frequency.

[0073] Finally, feature selection and dimensionality reduction were performed. The principal component analysis (PCA) method was used to reduce the dimensionality of the extracted features, and the principal components with an explained variance ratio of more than 95% were retained. The recursive feature elimination (RFE) algorithm was used in combination with the support vector machine (SVM) classifier to select the most discriminative feature subset.

[0074] The maximum relevance minimum redundancy (mRMR) algorithm based on mutual information is further introduced to further optimize the feature set to ensure that the selected features are both independent of each other and highly relevant to the health status of the bridge pier. The improved feature importance scoring method proposed in this embodiment can be expressed as follows: ;in, Features The importance score of Features The mutual information with the target variable Y (bridge pier health status), Features and the features in the selected feature set S The mutual information of , β is the balance parameter, is the size or length of the selected feature set S. This method iteratively calculates the score of each candidate feature and selects the feature with the highest score, and finally constructs a feature subset that is highly correlated with the health status of the pier and independent of each other.

[0075] Based on the current variation characteristics and electrical performance parameters, a pier health status assessment model is constructed to generate a pier health status report.

[0076] Specifically, the feature subsets are normalized to ensure that features of different dimensions can be compared. The minimum-maximum normalization method is used for normalization.

[0077] Furthermore, for each standardized feature , calculate its dynamic weight, to ensure that the closer the eigenvalue is to the worst state, the greater its weight is, which is defined as follows: ;in, It is a feature The basic weight of is the adjustment factor, usually between 0.2 and 0.5. It reflects the degree to which the characteristic deviates from the ideal state.

[0078] Furthermore, the pier health index is calculated by taking the weighted average of all characteristics and then multiplying it by 100 to get a score between 0 and 100: ; Further, the bridge pier condition is divided into five levels by calculating the comprehensive health status index (BPHI). The BPHI score ranges from 0 to 100, with higher scores indicating better conditions. Specifically, 90 points and above are excellent (A-level), indicating that the bridge pier is in the best condition; 75 to 89 points are good (B-level), indicating that the condition is good but requires some preventive maintenance; 60 to 74 points are fair (C-level), indicating that the bridge pier functions normally but needs close monitoring; 40 to 59 points are poor (D-level), indicating that there are obvious problems that need to be repaired in time; and below 40 points are dangerous (E-level), indicating that the bridge pier has serious safety hazards and immediate measures need to be taken.

[0079] Furthermore, this embodiment also provides a pier health status monitoring system, including:

[0080] A network construction module, used for selecting a flexible current sensor suitable for the surface of the bridge pier, determining the arrangement position of the flexible current sensor on the surface of the bridge pier, and adhering the flexible current sensor to the determined arrangement position to form a sensor network;

[0081] A data acquisition module is used to establish a wireless connection with the flexible current sensor using a movable collector to dynamically collect current data at different positions;

[0082] A feature extraction module, used to extract features from the current data and construct a feature subset;

[0083] The status monitoring module is used to calculate the pier health status index based on the feature subset and complete the pier health status monitoring.

[0084] This embodiment also provides a computer device, which is suitable for the case of a bridge pier health status monitoring method, including a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the bridge pier health status monitoring method proposed in the above embodiment.

[0085] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0086] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for monitoring the health status of a bridge pier as proposed in the above embodiment is implemented.

[0087] The storage medium proposed in this embodiment and the data storage method proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be found in the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0088] Embodiment 2: This is the second embodiment of the present invention. This embodiment provides a method for monitoring the health status of bridge piers. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0089] In order to verify the effectiveness of the bridge pier health status monitoring method based on flexible current sensors proposed in this paper, a main pier of a large cross-sea bridge located in a coastal city was selected for experiment. The pier is 85 meters high and 12 meters in diameter, and adopts a reinforced concrete structure. The experiment lasted for 12 months, covering different seasons and climate conditions.

[0090] First, according to the invention content, a flexible current sensor suitable for the surface of the bridge pier was selected. The selected sensor is a flexible current sensor made of a self-developed graphene / polydimethylsiloxane (PDMS) composite material, which has excellent bendability and stretchability and can fit the curved surface structure of the bridge pier well. The sensitivity of the sensor is 0.05μA / MPa, the measurement range is 0-500MPa, and the resolution reaches 0.01MPa.

[0091] Next, based on the results of the force analysis of the pier structure, the pier surface was divided into multiple monitoring areas. The column area was evenly divided into three sub-areas: upper, middle, and lower, each with a height of about 28 meters. The beam area included the connection with the column, the mid-span part, and the vicinity of the support. The foundation area included the underwater part (about 20 meters deep) and the water-soil interface.

[0092] Subsequently, a three-dimensional finite element model of the bridge pier was established using ANSYS software, taking into account the nonlinear multi-scale coupling theory and material heterogeneity. The multi-scale damage factor D(x, y, z) was introduced into the model, and the phase field fracture model was used to describe the crack propagation. Through static and dynamic load analysis, stress concentration points and potential crack-prone locations were determined.

[0093] A high-density sensor layout scheme is adopted at the determined key locations. Sensors are arranged radially around the stress concentration point with the point as the center, with an inner circle spacing of 5cm and an outer circle maximum spacing of 20cm. A 10cm×10cm grid layout method is adopted at locations prone to potential cracks. In the transition area, an adaptive density distribution strategy is used, and the distance between adjacent sensors does not exceed 30cm. In special structures such as the edges and corners of bridge piers and the transition zone of curved surfaces, the sensor spacing is reduced to 3-5cm. At least 3 sensors with the same function are arranged at each key location to form a local sensor cluster. Non-critical locations maintain a uniform layout interval of 50cm.

[0094] A total of 2,856 flexible current sensors were placed on the entire pier surface to form a comprehensive sensor network. Special epoxy resin glue was used to firmly adhere the sensors to the pier surface to ensure long-term stable operation.

[0095] A self-developed mobile collector is used to establish a wireless connection with the sensor, with a collection frequency of 100Hz. The collector has the characteristics of high precision, low noise, and wide bandwidth, and can accurately capture tiny current changes. The data is transmitted to the cloud server in real time via the 5G network for storage and analysis.

[0096] The collected current data is analyzed in time series to extract the current variation characteristics and electrical performance parameters. First, data preprocessing is performed, including denoising, outlier detection, and missing value interpolation. Then, time domain feature extraction is performed, statistical features are calculated, and the improved multiscale sample entropy (IMSE) method is applied. In frequency domain feature extraction, in addition to the traditional fast Fourier transform (FFT) and power spectral density (PSD) analysis, a feature extraction method based on wavelet packet energy entropy is introduced.

[0097] In terms of electrical performance parameter extraction, the equivalent resistance and conductivity of the bridge pier were calculated, and the Nyquist plot was constructed using the complex impedance analysis method. In addition, a parameter extraction method based on the fractional impedance model was applied to further improve the accuracy of the electrical performance characterization.

[0098] Finally, feature selection and dimensionality reduction are performed. The principal component analysis (PCA) method is used to reduce the dimensionality of the extracted features, and the recursive feature elimination (RFE) algorithm and the maximum relevance minimum redundancy (mRMR) algorithm based on mutual information are combined to select the most discriminative feature subset.

[0099] Based on the selected feature subset, a pier health status assessment model was constructed. The features were standardized using the minimum-maximum normalization method, and the dynamic weights were calculated. The pier health status index (BPHI) was obtained by calculating the weighted average, and the pier conditions were divided into five levels.

[0100] The following are the experimental data and analysis results, as shown in Table 1:

[0101] Table 1 Experimental data table

[0102] Monitoring area Equivalent resistance (Ω) Conductivity (S / m) IMSE value Wavelet Packet Energy Entropy Fractional impedance α value BPHI score Health level Upper part of column 2345.67 0.000426 1.876 4.532 0.892 92.5 A Middle of column 2156.89 0.000464 2.103 4.789 0.857 88.3 B Lower part of column 1987.54 0.000503 2.456 5.124 0.801 79.6 B Beam connection 2567.32 0.000390 1.654 4.321 0.923 95.1 A Beam mid-span 2432.18 0.000411 1.789 4.567 0.905 93.7 A Beam support 2098.76 0.000477 2.321 4.987 0.832 82.9 B Basic underwater 1876.43 0.000533 2.876 5.432 0.745 71.2 C Base Junction 1765.29 0.000566 3.123 5.678 0.712 65.8 C

[0103] From the data, it can be observed that there are significant differences in the equivalent resistance and conductivity of different areas of the pier. The equivalent resistance of the upper part of the column and the crossbeam area is higher (2300-2600Ω) and the conductivity is lower (0.00039-0.00046 S / m), indicating that the structural integrity of these areas is better. In contrast, the equivalent resistance of the foundation area is significantly lower (1700-1900Ω) and the conductivity is higher (0.00053-0.00057 S / m), which suggests corrosion or structural changes in the underwater environment and the water-soil interface.

[0104] The MSE value increases from top to bottom, with lower IMSE values ​​(1.6-2.1) in the upper part of the column and the crossbeam area, and significantly higher IMSE values ​​(2.8-3.1) in the foundation area. This indicates that the structural complexity of the lower part of the pier and the foundation area has increased, and there may be minor damage or structural changes.

[0105] The trend of the wavelet packet energy entropy is similar to that of the IMSE value, which gradually increases from top to bottom. The values ​​of the upper part of the column and the beam area are between 4.3-4.8, while the foundation area reaches 5.4-5.7. This further confirms the possible structural anomalies in the foundation area.

[0106] According to the comprehensive assessment, most areas of the piers are in Grade A (excellent) and Grade B (good) condition. The BPHI scores of the upper part of the column, the beam connection and the mid-span of the beam are over 90 points, indicating the best health. The scores of the middle and lower part of the column and the beam support area are between 80-89 points, which are in good condition. However, the scores of the underwater part of the foundation and the water-soil interface are 71.2 and 65.8 respectively, which are downgraded to Grade C (fair) and need to be closely monitored.

[0107] It should be noted that the above embodiments are only used to illustrate the technical solutions 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 solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for monitoring the health status of a bridge pier, characterized in that: include: Selecting a flexible current sensor suitable for the surface of the bridge pier, determining the arrangement position of the flexible current sensor on the surface of the bridge pier, and adhering the flexible current sensor to the determined arrangement position to form a sensor network; Using a mobile collector to establish a wireless connection with the flexible current sensor to dynamically collect current data at different locations; Extracting features from the current data to construct a feature subset; Based on the feature subset, a bridge pier health status index is calculated to complete the bridge pier health status monitoring; The arrangement positions include column areas, beam areas and foundation areas; The column area is evenly divided into three sub-areas: upper, middle and lower along the pier height direction; The crossbeam region includes the connection with the column region, the mid-span portion and the support; The foundation area includes the underwater part of the pier and the water-soil interface; The arrangement positions also include stress concentration points and potential crack prone locations; The stress concentration point is the area where the equivalent stress under static and dynamic loads solved by the finite element method exceeds 80% of the material yield strength, as shown in the following formula: ； in, is the stress deviator tensor, is the equivalent stress, is the material yield strength; Wherein, the equivalent stress is determined by the following formula: ； in, is the elasticity tensor, is the strain tensor, is the multi-scale damage factor; The determination of the potential crack prone location includes calculating Points, when the When the integral value is approximately equal to the critical fracture toughness of the material, it is considered that cracks are likely to occur at that location; Said The integral is calculated as follows: ； in, is the strain energy density, Along the integral path The surface force component, is the displacement component, is the integral path The outward normal vector at any point is The weight in direction, is the critical fracture toughness, is the displacement component about The partial derivative of rate of change in direction; The feature subset includes time domain features, frequency domain features and electrical performance features; The time domain features include multi-scale sample entropy; The frequency domain feature is determined by converting the current signal from the time domain to the frequency domain, and identifying the main frequency components in the current signal and their corresponding energy distribution by calculating the power spectrum density; The electrical performance feature extraction is obtained by equivalent resistance, conductivity calculation and parameter extraction based on a fractional impedance model; The calculation of the multi-scale sample entropy is shown in the following formula: ； in, is a time series, is the embedding dimension, is the similarity threshold, is the scale factor, and are the matching counts in m and m+1 dimensional phase space, respectively; The current signal is converted from the time domain to the frequency domain as shown below: ； in, represents the frequency domain signal, is the time domain signal, is the signal length, is the frequency index, is the time index, is an imaginary unit, To calculate the amplitude and phase of each frequency component; The power spectral density is calculated as follows: ； in, is the Fourier transform result of the signal, is the sampling frequency; The energy distribution is obtained by calculating the energy entropy, and the calculation of the energy entropy is shown in the following formula: ； in, is the energy entropy of the ith frequency band, is the normalized energy of the jth wavelet packet coefficient in the ith frequency band, is the frequency band weight factor based on power spectral density; in, The calculation of is as follows: ； in, is the average power spectral density of the ith frequency band, and M is the total number of frequency bands.

2. The method for monitoring the health status of a bridge pier according to claim 1, characterized in that: The calculation of the pier health index includes: Normalizing each feature of the feature subset, and calculating a dynamic weight of the normalized feature; Calculate the weighted average of all characteristics to obtain the pier health index; The calculation of the dynamic weight is shown in the following formula: ； in, It is a feature The basic weight of is the adjustment coefficient, ranging from 0.2 to 0.

5. It reflects the degree to which the characteristic deviates from the ideal state. Features The dynamic weight of are the standardized features.

3. A bridge pier health status monitoring system, based on the bridge pier health status monitoring method according to any one of claims 1 to 2, characterized in that: include, A network construction module, used for selecting a flexible current sensor suitable for the surface of the bridge pier, determining the arrangement position of the flexible current sensor on the surface of the bridge pier, and adhering the flexible current sensor to the determined arrangement position to form a sensor network; A data acquisition module is used to establish a wireless connection with the flexible current sensor using a movable collector to dynamically collect current data at different positions; A feature extraction module, used to extract features from the current data and construct a feature subset; The status monitoring module is used to calculate the pier health status index based on the feature subset and complete the pier health status monitoring.

Images