Method for measuring the reinforcement density and the cover thickness of a cement pole

Abstract

The application relates to the field of nondestructive testing of civil engineering, and discloses a cement pole steel bar density and protective layer thickness measurement method, which comprises the following steps: pretreating and marking a grid detection area of a to-be-detected section of a cement pole; moving a multi-coil array probe along a detection path and collecting original electromagnetic induction signals; performing differential processing on the original signals, extracting effective signal components by calculating the peak-to-peak value of the differential signals, and thus eliminating common-mode interference and signal zero drift; mapping the strength of the effective signal components into the spatial coordinates of the steel bar to generate a three-dimensional image; calculating the steel bar density and the protective layer thickness based on the three-dimensional image; and finally, dynamically feeding back and optimizing operation parameters according to measurement errors. Through differential processing and closed-loop feedback control, the application significantly improves the measurement accuracy, anti-interference ability and stability, and realizes efficient detection without zero calibration in the continuous scanning process.

Description

Technical Field

[0001] This invention relates to the field of non-destructive testing technology in civil engineering, specifically a method for measuring the density of steel reinforcement and the thickness of the protective layer in cement poles. Background Technology

[0002] Concrete poles (cement poles) are critical load-bearing structures in power transmission and distribution and communication networks, and their structural safety and durability are of paramount importance. Reinforcement density and protective layer thickness are two core physical parameters for assessing the structural integrity, load-bearing capacity, and corrosion resistance of concrete poles. Therefore, achieving rapid, accurate, and non-destructive testing of the internal reinforcement parameters of in-service concrete poles is of great significance for ensuring the safe operation of infrastructure.

[0003] Currently, nondestructive testing methods based on the principle of electromagnetic induction are the most widely used techniques in this field. These methods typically generate an alternating magnetic field through an excitation coil inside the probe. When the probe approaches a concrete pole, the internal reinforcing bars experience eddy currents in the alternating magnetic field, which in turn generates a secondary induced magnetic field. The receiving coil detects changes in this secondary magnetic field to infer the position and size information of the reinforcing bars.

[0004] However, existing electromagnetic induction detection technologies still face a series of technical challenges in practical applications. On the one hand, the environment at the detection site (such as nearby power transmission lines or substations) is often accompanied by complex power frequency electromagnetic interference. These strong interference signals can easily mix into the weak rebar induction signals, causing a significant decrease in the signal-to-noise ratio of the detection system and affecting measurement accuracy. On the other hand, during long-term continuous scanning operations, the electronic components such as the amplifier circuits of the detection equipment are susceptible to factors such as temperature changes, resulting in significant signal zero-point drift. This drift causes the measurement reference to change continuously, forcing the system to frequently interrupt detection for recalibration, severely restricting detection efficiency and data stability.

[0005] Furthermore, the internal steel reinforcement structure of cement poles is typically complex, with densely packed annular stirrups in addition to longitudinal main reinforcement bars. Existing signal processing algorithms have limited ability to distinguish between main reinforcement signals and stirrup interference signals, often resulting in confusion and misjudgment. This directly leads to a significant reduction in the accuracy of subsequent reinforcement location, especially reinforcement density calculation. Simultaneously, traditional detection systems mostly employ a set of fixed operating parameters calibrated at the factory (such as coil excitation frequency and signal sampling interval). When faced with cement poles of different diameters and reinforcement specifications, or when environmental conditions change, these fixed parameters cannot dynamically adapt, making it difficult to guarantee measurement accuracy and reliability under varying actual working conditions. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a method for measuring the density of reinforcing bars and the thickness of the protective layer in cement poles, which solves the problems of low accuracy and poor stability in measuring reinforcing bar parameters caused by susceptibility to electromagnetic interference, signal drift, and fixed measurement parameters in existing technologies.

[0007] To address the technical problems, this invention provides a method for measuring the density of reinforcing bars and the thickness of the protective layer in cement poles. This method is achieved through the following technical solution:

[0008] S1: First, the surface of the section of the cement pole to be inspected is pre-treated to ensure the stability of the physical basis for inspection, and a grid inspection area consisting of axial inspection path and circumferential inspection ring is marked on it to provide a precise position reference for subsequent data acquisition.

[0009] S2: Subsequently, a multi-coil array probe is used to scan along the detection path within the grid detection area. Preferably, this probe has an arc-shaped probe holder that matches the outer radius of the concrete pole, on which a detection coil array is fixed. This array consists of a ring-shaped coil group arranged circumferentially and a longitudinal coil group arranged axially. This layout can comprehensively sense the original electromagnetic induction signals generated by the longitudinal main reinforcement and circumferential reinforcement inside the concrete pole.

[0010] S3: After acquiring the raw electromagnetic induction signal, differential signal processing is performed on it. The core of this processing lies in configuring physically adjacent detection coils as differential pairs and performing differential operations on the signals they receive. This effectively suppresses external common-mode electromagnetic interference acting on both coils simultaneously. Furthermore, by calculating the peak-to-peak value of the differential signal within each excitation cycle, it is used as the effective signal component characterizing the presence of reinforcing bars. Since the zero-point drift of the signal is a slowly changing DC component, it is naturally canceled out during the peak-to-peak value calculation, thus fundamentally solving the zero-drift problem in long-term continuous measurements. To further improve the accuracy of main reinforcement signal identification, this processing may also include comparing the signal characteristics with a preset stirrup signal feature library to identify and filter out interference signals generated by stirrups.

[0011] S4: Next, 3D imaging of the concrete pole's reinforcing bars is performed. This step establishes a spatial coordinate system for the concrete pole, such as a cylindrical coordinate system, and converts the intensity of the effective signal components extracted in the previous step, i.e., the peak-to-peak value, into the spatial position coordinates of the reinforcing bars in this coordinate system, particularly the radial coordinates, through a preset mapping rule. By integrating the position coordinates of all detection points, a 3D image that can intuitively represent the spatial distribution of all main reinforcing bars is finally generated. Based on this, by analyzing and comparing the changes in the radial coordinates of the same reinforcing bar at different axial positions, it is also possible to calculate and identify inclined reinforcing bars and their specific inclination angles.

[0012] S5: Then, based on the generated 3D image, key physical parameters are calculated. The protective layer thickness is calculated by substituting the peak-to-peak values ​​corresponding to each main reinforcement bar in the 3D image into an empirical model that characterizes the relationship between peak-to-peak values ​​and protective layer thickness, pre-calibrated using standard test blocks. The reinforcement density is calculated by identifying each individual reinforcement bar within a unit detection area of ​​the 3D image, calculating its cross-sectional area, and then dividing the total cross-sectional area of ​​the reinforcement bars in that area by the area of ​​the unit detection area.

[0013] S6: Finally, this invention introduces a closed-loop control mechanism for data feedback optimization. This mechanism first establishes an error model that quantifies the relationship between system operating parameters and the final measurement error. During the measurement process, when the measurement error of the monitored rebar density or protective layer thickness exceeds a preset threshold, the correction amount for the operating parameters is calculated in reverse based on this error model, and one or more operating parameters are dynamically adjusted. The operating parameters may include the probe's coil excitation frequency, the signal sampling time interval for signal processing, or the mapping coefficient used for peak-to-peak value to radial coordinate transformation in three-dimensional imaging.

[0014] This invention provides a method for measuring the density of reinforcing bars and the thickness of the protective layer in cement poles. It has the following beneficial effects:

[0015] 1. This invention employs differential signal processing, configuring physically adjacent detection coils as differential pairs and calculating the peak-to-peak value of the differential signal as the effective signal component. This method not only effectively suppresses common-mode electromagnetic interference in the measurement environment but also eliminates signal zero-point drift generated during long-term continuous measurements in principle, significantly improving signal quality and system stability. It also eliminates the need for frequent interruptions for zeroing during the detection process, thereby increasing detection efficiency.

[0016] 2. This invention achieves accurate reproduction of the spatial distribution of reinforcing bars inside concrete poles by establishing a signal feature library for stirrups to precisely filter out interference signals and combining it with imaging technology capable of generating three-dimensional images and identifying tilted reinforcing bars. This approach ensures the accuracy and integrity of the data source for subsequent parameter calculations, thereby improving the reliability of the final calculation results for reinforcing bar density and protective layer thickness.

[0017] 3. This invention introduces a data feedback optimization mechanism. By establishing an error model, it calculates and dynamically adjusts key operating parameters such as coil excitation frequency and signal sampling time interval based on the monitored measurement error during the measurement process. This closed-loop control method enables the measurement system to have dynamic adaptive capabilities, suppressing and correcting measurement deviations in real time, ensuring that the measurement results maintain high accuracy and high reliability under different operating conditions. Attached Figure Description

[0018] Figure 1This is a flowchart illustrating the overall method of the present invention;

[0019] Figure 2 This is a schematic diagram of the cement pole detection area of ​​the present invention;

[0020] Figure 3 This is a schematic diagram of the multi-coil array probe structure of the present invention;

[0021] Figure 4 This is a block diagram of the differential signal processing functional module of the present invention;

[0022] Figure 5 This is a flowchart of the three-dimensional imaging process for cement pole reinforcement of the present invention;

[0023] Figure 6 This is a block diagram of the parameter calculation function module of the present invention;

[0024] Figure 7 This is a block diagram of the data feedback optimization function module of the present invention. Detailed Implementation

[0025] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] See attached document Figure 1 and attached Figure 2 This invention provides a method for measuring the density of reinforcing bars and the thickness of the protective layer in cement poles, which may include:

[0027] Pre-treatment of the cement pole inspection area:

[0028] This step aims to provide a flat detection area with clear coordinate references for subsequent signal acquisition. By mechanically treating and marking the surface of the cement pole, it is ensured that the measuring equipment can stably attach and acquire accurate spatial positioning data.

[0029] Surface smoothing treatment:

[0030] The section of the concrete pole to be inspected undergoes surface grinding. This grinding process reduces the surface roughness of the inspection area by removing uneven concrete layers, ensuring that the overall flatness error is less than or equal to [value missing]. For example, an angle grinder can be used with sandpaper of an appropriate grit (such as 80 or 120 grit) for mechanical polishing. During polishing, measuring tools (such as a 2m straightedge with a 0.02mm precision dial indicator) can be used to monitor the surface flatness in real time, ensuring that the difference between the maximum and minimum elevation differences at any testing point does not exceed [a certain value]. When the detection value exceeds At this time, a second polishing is required until the requirements are met.

[0031] ;

[0032] in, This represents the upper limit of the allowable error for surface flatness.

[0033] Gridded detection area marking:

[0034] On the section of the cement pole to be inspected after surface smoothing, use a marking tool (e.g., a marker) to create a grid pattern along the axial and circumferential directions of the cement pole. Mark the grid along the axial direction of the cement pole at a preset axial path spacing. Mark multiple parallel detection paths. Along the circumference of the cement pole, at a preset circumferential spacing. Multiple parallel detection rings are marked. The intersections of these axial paths and circumferential rings form a path ring grid detection area. This grid area guides the movement path of the subsequent coil array probe on the concrete pole surface and provides precise two-dimensional positional information for the acquired signal data.

[0035] To ensure grid accuracy, the marking process can begin by establishing a circumferential reference point (e.g., directly above) and an axial reference line at the starting end of the section of the concrete pole to be inspected. All subsequent markings are performed using this reference. Circumferential equidistant markings can be performed using a flexible measuring ruler, and axial path markings can be assisted using a laser collimator or a long straight guide rail to ensure that the axial path is strictly parallel to the central axis of the concrete pole.

[0036] For example, if the axial path spacing The circumferential band spacing is set to 50mm. Setting the value to 100mm creates a detection area composed of multiple 50mm × 36° grid cells (assuming the outer diameter of the cement pole is 300mm, the circumference is approximately 942mm, and 100mm corresponds to approximately 36°). This preprocessing ensures environmental consistency and data positioning accuracy for subsequent signal acquisition, laying the foundation for the reliability of the entire measurement method.

[0037] See attached document Figure 2This method, after preprocessing, specifically performs multi-coil array probe placement and signal acquisition. This step uses a multi-coil array probe. The multi-coil array probe includes an arc-shaped probe holder and a detection coil array fixed on the arc-shaped probe holder. The arc-shaped probe holder has a preset radius of curvature. The radius With the outer radius of the pretreated cement pole It is matched, or designed as an adjustable structure to accommodate different sizes of concrete pole radii (e.g., to fit). (Variation within the range of 75mm to 200mm).

[0038] The curved probe holder is made of a non-magnetic and electrically insulating material (e.g., ABS engineering plastic or epoxy resin). This structure ensures that when a multi-coil array probe is placed on a concrete pole surface, the curved probe holder can fit tightly against the pole surface, minimizing the contact gap between the curved probe holder and the pole surface. Less than or equal to a preset gap threshold (e.g.) mm).

[0039] The detection coil array is fixed to the side of the curved probe holder facing the concrete pole. The detection coil array comprises multiple sets (e.g., 7 sets) of detection coils, which (e.g., are wound with copper wire, with a coil diameter of...) (between 8mm and 12mm) is configured to operate at a preset excitation frequency. (For example, operating at 50 kHz to 100 kHz). In one embodiment, the detection coil array specifically includes: a ring coil group and a longitudinal coil group.

[0040] The ring coil assembly contains Groups (e.g.) ) Circular detection coils. These coils are evenly distributed along the circumference of the arc-shaped probe holder (i.e., the marked direction of the detection ring). This circular coil assembly is used to detect the annular reinforcing bars inside the cement pole. To ensure the accuracy of radial measurements, this... The radial distance deviation between the center of the ring detection coil and the axis of the cement pole. Controlled within a preset threshold Inside.

[0041] ;

[0042] in, It is the upper limit of the permissible radial deviation of the toroidal coil, for example mm.

[0043] Longitudinal coil group includes Groups (e.g.) Longitudinal detection coils. These coils are distributed along the axial direction of the arc-shaped probe frame (i.e., the marked detection path direction). This longitudinal coil group is used to adapt to the detection of the longitudinal main reinforcement bars inside the concrete pole. To ensure the accuracy of axial positioning, this... The axial deviation between the center of the longitudinal detection coil and the detection path it is located in. Controlled within a preset threshold Inside.

[0044] ;

[0045] in, It is the upper limit of the allowable longitudinal coil axial deviation, for example .

[0046] During signal acquisition, the arc-shaped probe holder of the multi-coil array probe is tightly fitted onto the pre-processed grid detection area. The multi-coil array probe moves along a marked detection path at a preset speed. (For example The device moves at a constant speed of 1 cm / s. During this movement, an excitation signal (e.g., a 5V cosine wave) is applied to the excitation end (transmitting coil) of the detection coil array, while its receiving end (receiving coil) collects in real time the electromagnetic induction signal generated by the electromagnetic induction effect of the steel bars (including longitudinal main bars and ring bars) inside the cement pole.

[0047] To ensure movement speed To ensure constant speed, a multi-coil array probe can be mounted on a mechanically moving device driven by a stepper motor. This device includes a guide rail laid along the axial direction of a concrete pole, on which the multi-coil array probe moves in a controlled manner, thus eliminating speed inconsistencies introduced by manual operation. The acquired raw electromagnetic induction signal is digitized by a high-speed analog-to-digital converter (ADC) and transmitted in real time via a standard data interface (e.g., USB or Ethernet) to a signal processing unit that performs subsequent processing steps.

[0048] To ensure the effectiveness of differential signal processing in the subsequent S3 step, the detection coil and signal acquisition circuit used must meet the preset signal-to-noise ratio (SNR) requirements. Specifically, when the effective amplitude of the acquired electromagnetic induction signal... Greater than or equal to a minimum signal threshold At that time, the signal-to-noise ratio of the signal It must be greater than or equal to a required signal-to-noise ratio threshold. .

[0049] ;

[0050] in, It is the set minimum effective signal amplitude, for example .

[0051] ;

[0052] in, It is the required minimum signal-to-noise ratio, for example .

[0053] The acquired raw electromagnetic induction signals are transmitted to the subsequent signal processing unit. Before each measurement task, a standardized calibration check can be performed on the multi-coil array probe. This check uses a standard test block containing rebar of known diameter and embedment depth. The multi-coil array probe is placed at the designated location on the test block, signals are acquired, and peak-to-peak values ​​are calculated. Compare this value with the calibration value of the standard test block. Comparison. Only when... Only when the error is less than the preset calibration error threshold is the multi-coil array probe and its acquisition system confirmed to be in normal working condition, and subsequent measurement tasks authorized to begin.

[0054] See attached document Figure 3 After acquiring the raw electromagnetic induction signal, the method performs differential signal processing. This step processes the acquired raw electromagnetic induction signal to extract the effective signal components related to the main reinforcement and suppress common-mode interference, stirrup interference signals in the frequency band, and signal zero drift. This processing is performed by a signal processing unit, which may include a differential amplification module, a signal quantization module, an interference rejection module, a main reinforcement identification module, and a zero drift elimination module.

[0055] The differential amplifier module configures physically adjacent detection coils (including coils in the loop coil group and the longitudinal coil group) within the detection coil array in S2 as differential pairs. One coil acts as the excitation transmitter, and the other as the induction receiver. The differential amplifier module receives the signal from the receiving coil and differentially amplifies it. This operation enhances the signal difference caused by local reinforcement while suppressing common-mode interference signals that act simultaneously on both coils due to external electromagnetic fields or power fluctuations.

[0056] The signal quantization module receives the output signal from the differential amplifier module. For each excitation signal cycle, the signal quantization module measures and records the maximum value of the differential signal voltage within that cycle. and minimum value Subsequently, the signal quantization module calculates the difference between these two values ​​to obtain a peak-to-peak value of the quantized signal intensity. .

[0057] ;

[0058] in, It represents the maximum instantaneous value of the differentially amplified signal voltage within one excitation signal cycle. It represents the minimum instantaneous value of the differentially amplified signal voltage within one excitation signal cycle. This represents the calculated peak-to-peak value of the differential signal.

[0059] The interference removal module is used to identify and filter out interference signals generated by the stirrups (non-main reinforcement) inside the concrete pole. The module contains a stirrup signal feature library that stores preset characteristic parameters of the stirrup signals, including a frequency range. and the peak-to-peak range (For example, frequencies in the 20-30kHz range and) (within 1-2 mV). This stirrup signal feature library was established through previous experiments. The specific establishment process includes: preparing multiple cement specimens containing stirrups of different diameters and different binding methods, scanning these specimens using the probe of this invention, and specifically collecting the electromagnetic induction signals generated by the stirrups. By performing spectral analysis and statistics on a large number of collected stirrup signals, its frequency and peak-to-peak value were determined. The concentrated distribution range of the stirrups was used to construct the signal feature library.

[0060] A comparison unit compares the signal characteristics output by the signal quantization module with parameters in the stirrup signal characteristic library. If the signal characteristics match, a filtering unit (e.g., a bandpass filter with a passband of 50-100kHz) suppresses or filters out the signal.

[0061] The main reinforcement identification module judges the signal after interference removal processing. The module identifies the main reinforcement signal based on two preset conditions: the peak-to-peak value of the signal. It must be greater than or equal to a minimum signal threshold. And the frequency of the signal It must be within the preset excitation frequency range Only signals that simultaneously meet both of these conditions are considered valid main rib signals and are transmitted to subsequent 3D imaging steps.

[0062] ;

[0063] ;

[0064] in, The minimum effective signal amplitude is set, for example... mV. The frequency of the signal currently being processed. For example, the set excitation frequency range kHz, kHz].

[0065] The zero-drift elimination module embodies the inherent characteristics of this differential processing method. This is due to the slowly varying DC zero-point drift present in the measurement system. It will be applied equally to the signal. and Therefore, when performing peak calculations, this zero drift value is naturally canceled out.

[0066] ;

[0067] in, This is the zero-point drift value of the measurement system. This characteristic makes the measurement results... Unaffected by zero-point drift, no interruption-based zeroing is required during the continuous scanning and testing of the cement pole. Before starting a complete testing task, only an initial verification of the probe is needed using a standard, metal-free blank test block to confirm the current output. It should be close to zero.

[0068] See attached document Figure 4 After processing the signal and identifying the main reinforcement signals, the method performs three-dimensional imaging of the cement pole reinforcement. This step outputs discrete one-dimensional peak-to-peak data corresponding to each main reinforcement signal. The system collects location information and converts it into a three-dimensional image that can intuitively represent the spatial distribution of the steel bars inside the concrete pole. This process is performed by a three-dimensional imaging unit, which may include a coordinate system establishment module, a coordinate mapping module, a coordinate transformation module, an image generation module, and an inclined steel bar detection module.

[0069] The coordinate system establishment module first establishes a cylindrical coordinate system for the cement pole segment to be inspected. The origin of this coordinate system is located at the center of the circle on the starting end face of the segment to be inspected. The coordinate system parameters are defined as follows:

[0070] radial coordinates : range is ,in It is the outer radius of the cement pole.

[0071] Inscribed angle coordinates : range is .

[0072] Axial coordinates : range is ,in This is the total length of the marked detection path. Each valid main rib signal output is assigned a unique identifier based on its acquisition position on the marked grid detection area. coordinate.

[0073] The coordinate mapping module maps the peak-to-peak value of each valid main reinforcement signal. Mapped to the radial coordinates of the signal source (i.e., the reinforcing bar) in a cylindrical coordinate system. This mapping relationship is determined through a pre-calibration process and stored as a mapping rule or function. In one embodiment, the mapping rule is a linear relationship, ensuring that the radial coordinates... Mapping error Less than or equal to a preset error threshold (For example For example, mapping rules can be defined as mm). For every 0.1mV increase, the radial coordinate... The size decreased by 0.06 mm.

[0074] The coordinate transformation module receives the cylindrical coordinates of all data points. And convert it to coordinates in the Cartesian rectangular coordinate system. This conversion is performed according to the following standard mathematical formula:

[0075] ;

[0076] ;

[0077] ;

[0078] in, These are the transformed rectangular coordinates. These are the original cylindrical coordinates.

[0079] The image generation module generates a 3D voxel image based on the transformed Cartesian coordinate point set. The module first divides the 3D space into a voxel grid with a preset pixel resolution (e.g., 0.5mm × 0.5mm × 0.5mm). Then, it assigns each data point... Associated peak-to-peak value Assign it to the voxel in which it resides. Finally, according to The value sets the color or grayscale value of the voxel, thereby generating a 3D image.

[0080] When two or more reinforcing bars are close together, their induced signals will overlap. To accurately separate and locate each reinforcing bar, peak detection and separation algorithms can be applied to the signal intensity data before generating the image. For example, Gaussian fitting or deconvolution algorithms can be applied to the signal intensity profile in each axial or circumferential direction to decompose the overlapping signal peaks into multiple independent signal peaks. The center position of each separated independent signal peak is determined as the center position of an independent reinforcing bar, thereby improving the resolution of densely packed reinforcing bar areas. For example, a color mapping rule can be set as follows: when... At mV, the voxel appears black; when At mV, the voxel is displayed as white, and values ​​between the two correspond to different gray levels.

[0081] The inclined rebar detection module is used to identify and quantify rebars that are inclined relative to the axis of the concrete pole. The module extracts data from different axial positions as the longitudinal coil group moves along the same detection path. The signals were collected from the same rebar. The inclined rebar detection module first obtains the radial coordinates corresponding to these two signals through the coordinate mapping module. Subsequently, the value of the reinforcing bar was calculated. Inclination angle in the plane .

[0082] ;

[0083] in, The angle of inclination of the steel reinforcement is calculated. In axial position The radial coordinates of the same reinforcing bar measured at the location. These are the coordinates of two different axial measurement positions.

[0084] When the calculated tilt angle Greater than a preset angle threshold (For example When this occurs, the reinforcing bar is identified as an inclined reinforcing bar. This inclined angle information... (For example, the angle calculation error is less than or equal to) The annotations will be added to the 3D image generated by the image generation module.

[0085] See attached document Figure 5 After generating a 3D image of the reinforcing steel in the cement pole, the method performs calculations on the steel density and the cover thickness. This step, based on the generated 3D image, quantitatively calculates the key physical parameters of the cement pole using a parameter calculation unit. This parameter calculation unit may include a cover thickness calculation module and a steel density calculation module.

[0086] The protective layer thickness calculation module first establishes the peak-to-peak value of the differential signal. With the thickness of the concrete cover for reinforcing bars The functional relationship between them. This relationship is established by considering a known protective layer thickness (e.g., ...). The peak-to-peak value was determined using standard test blocks of the same material and steel reinforcement specifications through pre-calibration measurements. By measuring these standard test blocks, a set of corresponding peak-to-peak value data was obtained. Based on these data, By fitting linear regression, the constant coefficients in the following empirical formula are determined. and .

[0087] Specifically, the fitting process employs the least squares method. This is achieved by collecting data from at least two (preferably three or more) protective layer thicknesses that are different and precisely known. The peak-to-peak value of the standard test block , constitute a data point set Substitute these data points into the system of linear equations and solve for the coefficients that minimize the sum of squared residuals. and The standard test block must be made in a way that ensures its concrete material and steel reinforcement specifications are consistent with the cement rod to be tested, so as to guarantee the accuracy of the calibration model.

[0088] The protective layer thickness calculation module then extracts the signal peak-to-peak value associated with each identified individual main reinforcement bar from the 3D image generated by S4. . This Substitute the value into the calibrated empirical formula to calculate the protective layer thickness corresponding to the main reinforcement. .

[0089] ;

[0090] in, For the first The thickness of the protective layer for the reinforcing bars. These are the constant coefficients obtained through calibration measurements and data fitting of standard test blocks. To extract from a 3D image, and related to the first Peak-to-peak value of the differential signal corresponding to each reinforcing bar.

[0091] The rebar density calculation module selects a unit detection area in the 3D image for calculation. This unit detection area has a preset length (e.g., 100mm) along the axial direction of the cement bar and covers a preset angle (e.g., 30°) along the circumference.

[0092] The rebar density calculation module first calculates the area of ​​the unit inspection area. This calculation requires the average cover thickness of all reinforcing bars in the area. This value can be obtained by applying all calculated values ​​within the region. The average value is obtained.

[0093] ;

[0094] in, The area of ​​the unit testing area. Let be the outer radius of the cement pole. This refers to the average protective layer thickness of all reinforcing bars within the unit's testing area.

[0095] Subsequently, the rebar density calculation module identifies each individual rebar within the unit's inspection area by analyzing the 3D image and determines its diameter. Determine the diameter of the reinforcing bar. The specific method is as follows: In the 3D image, extract a signal intensity profile along a direction perpendicular to the rebar axis. This profile appears as a bell-shaped curve with the rebar center as the peak value. By calculating the width of the curve where the signal intensity is halfway up the peak value (i.e., the full width at half-peak), and based on the pre-established calibration relationship between the Full Width and Mean (FWHM) and the actual diameter of the rebar using standard test blocks, the diameter of the rebar can be calculated. Based on this diameter, calculate the cross-sectional area of ​​a single reinforcing bar. .

[0096] ;

[0097] in, For the first The cross-sectional area of ​​the reinforcing bar. To determine the first from the three-dimensional image The diameter of the reinforcing bar.

[0098] The rebar density calculation module calculates the cross-sectional area of ​​all rebars within a unit inspection area. Summing yields the total cross-sectional area of ​​the reinforcing bars in that area. Finally, the reinforcement density of the area is calculated by dividing the total cross-sectional area of ​​the reinforcing bars by the area of ​​the unit inspection zone. .

[0099] ;

[0100] in, This is the calculated steel reinforcement density.

[0101] Furthermore, when the rebar density calculation module analyzes a 3D image, if it identifies areas with rebar laps within a unit detection area, it will calculate the total cross-sectional area of ​​the rebar. At that time, the extra cross-sectional area of ​​the overlapping part will be included in the sum to affect the final density calculation result. Make corrections.

[0102] See attached document Figure 6After calculating the rebar density and cover thickness, the method performs data feedback optimization. This step establishes a closed-loop feedback control mechanism to dynamically adjust key operating parameters of the system during measurement, ensuring that the measurement accuracy of rebar density and cover thickness remains within preset tolerances. This process is executed by a data feedback optimization unit, which may include an error model building module and a parameter feedback correction module.

[0103] The error model building module generates a mathematical model that quantifies the relationship between system operating parameters and the final measurement error. This module collects a set of system operating parameters, including the coil excitation frequency set in the multi-coil array probe arrangement and signal acquisition. The signal sampling time interval set in differential signal processing. Mapping coefficients used to convert signal peak-to-peak values ​​to radial coordinates in 3D imaging of reinforced concrete poles. .

[0104] The error model building module utilizes datasets obtained from numerous previous experiments or calibration tasks to establish the relationship between these operating parameters and measurement errors (such as rebar density measurement error). And the measurement error of protective layer thickness A multiple linear regression model between ( ) and ( ). To ensure the effectiveness of the model, the goodness of fit (i.e., coefficient of determination) of the established model is used. It must be greater than a preset threshold (e.g.) .

[0105] ;

[0106] ;

[0107] in, This is due to the measurement error of the steel reinforcement density. This is due to measurement error in the protective layer thickness. The excitation frequency of the coil is denoted as . This represents the signal sampling time interval. These are the coordinate mapping coefficients. These are the fitting coefficients for the steel reinforcement density error model. These are the fitting coefficients for the protective layer thickness error model.

[0108] The parameter feedback correction module operates during actual measurement tasks. It receives measurement error values ​​from the parameter calculation unit in real time. and It compares these real-time error values ​​with a preset error threshold ( and (Compare)

[0109] The upper limit of the allowable error for measuring steel reinforcement density, for example, 0.01. / .

[0110] The upper limit of the allowable measurement error for the protective layer thickness, for example, 0.5. .

[0111] When detected or At this time, the parameter feedback correction module is activated. The parameter feedback correction module uses the established error model to calculate one or more operating parameters in reverse. The correction amount. The correction amount can be calculated using a proportional control algorithm. For example, for frequency... The adjustment, its correction amount It can be calculated using the following formula:

[0112] ;

[0113] in, It is a preset proportional gain coefficient. This is the target error value (usually zero). The calculated... It is added to the current frequency setting to form a new operating frequency. This adjustment process is performed iteratively each time the error exceeds the threshold, until the error converges to within the allowable range.

[0114] For example, when When the threshold is exceeded, the module calculates a value based on the rebar density error model that allows... Reduce the frequency correction amount and adjust the coil excitation frequency accordingly. ;when When the threshold is exceeded, the module calculates a value based on the protective layer thickness error model that allows... Reduce the sampling interval correction amount and adjust the signal sampling time interval accordingly. .

[0115] Through this error model-based parameter iterative correction, a closed-loop control system is formed. This system can continuously suppress the measurement error within the allowable range during the detection task, thereby achieving dynamic and stable control of the measurement accuracy.

Claims

1. A method for measuring the density of reinforcing bars and the thickness of the protective layer in cement poles, characterized in that, Includes the following steps: S1. The section of the cement pole to be inspected is surface-leveled, and a grid inspection area is marked on the surface after the surface is leveled. S2. A multi-coil array probe is moved along the detection path within the grid detection area to collect the original electromagnetic induction signal generated by the steel bars inside the cement pole; S3. Perform differential processing on the original electromagnetic induction signal and extract the effective signal component related to the main rib. The step of differential processing on the original electromagnetic induction signal includes: configuring detection coils that are physically adjacent as differential pairs; and calculating the peak-to-peak value of the differentially processed original electromagnetic induction signal during the excitation period as the effective signal component, and eliminating common-mode interference and signal zero drift. S4. Map the intensity of the effective signal component to the spatial coordinates of the reinforcing bar, and generate a three-dimensional image representing the spatial distribution of the reinforcing bar. Generating the three-dimensional image representing the spatial distribution of the reinforcing bar includes: establishing a cylindrical coordinate system for the cement pole; and converting the peak-to-peak value of the effective signal component into the radial coordinates of the reinforcing bar in the cylindrical coordinate system through a preset mapping rule. S5. Based on the three-dimensional image, calculate the steel reinforcement density and protective layer thickness of the cement pole; S6. Based on the measurement error of the steel reinforcement density and the protective layer thickness, dynamically adjust the acquired or processed original electromagnetic induction signal, wherein the dynamic adjustment specifically includes: establishing an error model that quantifies the relationship between the operating parameters and the measurement error; and when the measurement error exceeds a preset threshold, calculating and correcting the operating parameters based on the error model.

2. The method for measuring the density of reinforcing bars and the thickness of the protective layer in cement poles according to claim 1, characterized in that, The multi-coil array probe includes: An arc-shaped probe holder with a radius of curvature matching the outer radius of the cement pole; And a detection coil array fixed on the arc-shaped probe holder, the detection coil array including a ring coil group arranged in the circumferential direction and a longitudinal coil group arranged in the axial direction.

3. The method for measuring the density of reinforcing bars and the thickness of the protective layer in a cement pole according to claim 1, characterized in that, The step of differential processing of the original electromagnetic induction signal further includes: The features of the original electromagnetic induction signal processed by differential analysis are compared with a preset stirrup signal feature library that stores stirrup signal features; And to filter out interference signals that match the features in the stirrup signal feature library.

4. The method for measuring the density of reinforcing bars and the thickness of the protective layer in a cement pole according to claim 1, characterized in that, The three-dimensional imaging of the cement pole reinforcement also includes: By analyzing the radial coordinate changes of the same reinforcing bar at different axial positions, the inclined reinforcing bars and their inclination angles are calculated and identified.

5. The method for measuring the density of reinforcing bars and the thickness of the protective layer in a cement pole according to claim 1, characterized in that, The thickness of the protective layer is calculated through the following steps: The peak-to-peak value of the effective signal component is substituted into an empirical model that characterizes the relationship between the peak-to-peak value and the protective layer thickness, which is pre-calibrated using a standard test block, to calculate and obtain the protective layer thickness.

6. The method for measuring the density of reinforcing bars and the thickness of the protective layer in a cement pole according to claim 1, characterized in that, The calculation of the steel reinforcement density is obtained through the following steps: Individual steel bars are identified within the unit detection area of ​​the three-dimensional image, and their respective cross-sectional areas are calculated; The steel reinforcement density is obtained by dividing the total cross-sectional area of ​​the steel reinforcement within the unit detection area by the area of ​​the unit detection area.

7. The method for measuring the density of reinforcing bars and the thickness of the protective layer in a cement pole according to claim 1, characterized in that, The operating parameters include: At least one of the following: the coil excitation frequency of the multi-coil array probe, the signal sampling time interval for differential processing of the original electromagnetic induction signal, and the mapping coefficient used in the three-dimensional imaging of the cement pole reinforcement to convert the signal peak-to-peak value into radial coordinates.

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