Device for detecting hollowing of outer wall of building based on sound signals and use method

Abstract

The invention discloses a device for detecting hollowing of a building outer wall based on sound signals and a use method, and relates to the technical field of building engineering detection, and the device comprises a sound sensor array which is used for collecting the sound signals of the building outer wall; the signal conditioning circuit is used for amplifying and filtering the acquired weak sound signals; the data acquisition card is used for acquiring the processed sound signal data and transmitting the sound signal data to the microprocessor; the microprocessor is internally provided with a data analysis and hollowing judgment algorithm and is used for analyzing and processing the data; the display and operation terminal is used for setting detection parameters and displaying a detection result; the automatic knocking device is used for knocking and exciting the outer wall; the environment sensor is used for collecting temperature, humidity and noise data of a detection site; the building outer wall hollowing detection system can accurately detect and position building outer wall hollowing, and has the advantages of efficient detection process, strong environmental adaptability and perfect data management function.

Description

Technical Field

[0001] The present invention relates to the technical field of construction engineering detection, and in particular to a device for detecting hollowing of building exterior walls based on acoustic signals and a method for using the device. Background Art

[0002] In construction projects, hollowing of building exterior walls is a common quality problem that seriously affects the structural stability and service life of the building. Traditional methods for detecting hollowing of building exterior walls, such as manual tapping and infrared detection, often have many limitations. The manual tapping method relies on the experience of the inspectors and is highly subjective. It is difficult to conduct efficient and accurate detection of large-area exterior walls, and it is prone to missed detection and false detection. The infrared detection method is greatly affected by environmental factors. Under complex building structures and changing environmental conditions, the detection accuracy and reliability are difficult to guarantee. Therefore, there is an urgent need for a more accurate, efficient and adaptable building exterior wall hollowing detection technology.

[0003] In view of this, this application is hereby filed. Summary of the invention

[0004] The purpose of the present invention is to provide a device and a method for detecting hollowing of building exterior walls based on acoustic signals, so as to solve the problems mentioned in the above background technology.

[0005] To solve the above technical problems, the present invention provides a device for detecting hollowing of building exterior walls based on acoustic signals, comprising: an acoustic sensor array: distributed in a specific geometric shape on a movable bracket, and used to collect acoustic signals of building exterior walls; a signal conditioning circuit: connected to the sound sensor array, and used to amplify and filter the collected weak acoustic signals; a data acquisition card: connected to the signal conditioning circuit, and used to collect processed acoustic signal data and transmit it to a microprocessor; a microprocessor: with a built-in data analysis and hollowing judgment algorithm, and used to analyze and process the data; a display and operation terminal: connected to the microprocessor, and used to set detection parameters and display detection results; an automatic knocking device: used to perform knocking excitation on the exterior wall; an environmental sensor: used to collect temperature, humidity and noise data at the detection site.

[0006] Furthermore, the sound sensor array uses high-precision sensors with a sensitivity in the range of 1-10 mV / Pa and a frequency response range of 0.1-20 kHz.

[0007] Furthermore, the movable bracket has automatic positioning and navigation functions, can automatically move according to a preset scanning path, and the positioning accuracy is within ±2cm.

[0008] A method for using a device for detecting hollowing of building exterior walls based on acoustic signals comprises the following steps: S1: Preparation before testing: Use a known standard hollow drum sample to calibrate the device. Collect the sound signals of the standard sample at different knocking forces (force variation range is 1-5N) and positions in an indoor environment with a temperature of 20℃±5℃, a humidity of 40%±10% and a background noise below 40dB. Compare with the preset standard signal, automatically adjust the sensitivity of the device's sound sensor (to make it optimal within the range of 1-10mV / Pa), the filter frequency band of the signal conditioning circuit (set to 1-10kHz) and the sampling parameters of the data acquisition card (sampling frequency is set to 20-50kHz) to make the device reach the best detection state; use environmental sensors to collect temperature, humidity and noise data at the detection site, correct the propagation speed of the sound signal according to the relationship formula between the sound speed and environmental parameters, and identify and filter out the background noise frequency band through a specific algorithm to compensate for the impact of environmental factors on the acquisition and analysis of sound signals; S2: External wall detection operation steps: formulate a scanning path according to the shape and size of the building's external wall, so that the sound sensor array, driven by the movable bracket, fully covers the external wall surface according to the predetermined path. For rectangular walls, a serpentine path or a spiral path is used for scanning, and during the scanning process, the distance between the control device and the wall is kept constant at 5-15cm; an automatic knocking device is used to knock on the external wall with a fixed frequency (frequency range is 5-15Hz), force (force range is 2-6N) and interval (interval time is 0.5-2s) as an excitation source. During the knocking process, the sound sensor array synchronously collects sound signals and records the position information of each sampling point and the corresponding sound signal data; the collected sound signals are processed by the signal conditioning circuit and transmitted to the microprocessor in real time by the data acquisition card. The microprocessor performs preliminary processing on the data, removes abnormal values, and extracts simple features such as signal amplitude, frequency, and phase, and then temporarily stores the data; S3: Data analysis and hollowing judgment steps: Use wavelet analysis and time-frequency analysis algorithms to deeply analyze the temporarily stored sound signal data, extract characteristic information such as energy concentration or attenuation abnormality of the sound signals in the hollowing area and the normal area in a specific frequency band (3-8kHz), and compare with the sound signal feature library of the normal area to determine whether there is a hollowing and the approximate range of the hollowing; combine the position information of the sound sensor array with the signal analysis results to accurately calculate the position coordinates of the hollowing on the wall, and display the results in the form of a three-dimensional model on the display and operation terminal to highlight the hollowing position on the building exterior wall model; S4: Post-test data storage and report generation steps: All the original data of this test, including acoustic signal data, environmental parameter data, test location information and analysis results, are stored in a local storage device or cloud server; a detailed test report is automatically generated, the report content includes basic information of the building exterior wall, test time, test personnel, test results and related suggestions, and the report can be printed or exported according to user needs.

[0009] Furthermore, in S1, the indoor environment has a temperature between 15°C and 25°C, a humidity between 30% and 50%, and a background noise lower than 40 decibels.

[0010] Furthermore, in S2, when formulating the scanning path, a serpentine path or a spiral path is used to scan the rectangular wall, and the distance between the device and the wall is maintained within 5-15 cm.

[0011] Furthermore, in S2, the tapping frequency range of the automatic tapping device is 5-15 Hz, the tapping force can be adjusted between 2-6N, and the tapping interval is 0.5-2s.

[0012] Furthermore, in the data analysis and hollowing judgment step in S3, the method for establishing the normal area sound signal feature library is: multiple sound signal collection and analysis are performed on building exterior wall samples of the same material and structure without hollowing, and the sound signal features at different positions are extracted and statistically averaged to form feature library data.

[0013] Furthermore, in S4, in the data storage step, the local storage device uses a solid-state hard disk, and the data storage format is an encrypted binary format to ensure the security and integrity of the data.

[0014] Furthermore, in the report generation step in S4, the relevant suggestions are automatically generated based on the area, depth and location information of the hollowing, combined with the building structure safety standards, including whether immediate repair is needed and suggestions on repair processes and materials.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. Accurate detection and positioning: The present invention adopts a high-precision sound sensor array. Its unique layout and optimized sensing performance can comprehensively and keenly capture the sound signals generated by the building's exterior wall under percussion excitation. Combined with advanced wavelet analysis and time-frequency analysis algorithms, it deeply explores the subtle feature differences in the sound signal and effectively distinguishes the hollow area from the normal area. Through precise position coding and intelligent algorithm processing, the hollow position is accurately positioned on the three-dimensional model of the building's exterior wall, and the minimum detectable hollow area is significantly reduced. Compared with traditional detection methods, the detection accuracy is improved several times, which greatly reduces the misjudgment rate, provides an extremely accurate basis for building maintenance, and effectively guarantees the integrity and safety of the building structure; 2. Efficient detection process: With automated scanning path planning and intelligently controlled automatic tapping devices, the present invention can quickly generate the optimal scanning strategy according to the shape and size of the building's exterior wall, and execute it stably. During the detection process, real-time data transmission, preliminary processing and in-depth analysis are seamlessly connected, which significantly shortens the detection time. Compared with traditional manual tapping detection methods, the detection efficiency is greatly improved, and the detection task of large-area exterior walls can be completed in a shorter time, effectively reducing labor costs and time costs, and improving the overall advancement speed of building inspection projects, meeting the needs of rapid turnover and efficient operation and maintenance of modern construction projects; 3. Strong environmental adaptability and data management advantages: By integrating environmental sensors and applying targeted signal compensation algorithms, the present invention can work stably under complex and changeable environmental conditions. Whether it is high temperature, high humidity or noisy construction sites, the sound signals can be accurately collected and analyzed to ensure the reliability of the test results. The detected data is automatically stored in the local solid-state hard drive and cloud server, and the data storage format is securely encrypted for easy traceability and analysis. The automatically generated detailed test report covers rich information and can be flexibly output according to needs, providing comprehensive and convenient data support and decision-making basis for building maintenance management, and promoting the digitalization and intelligent development of construction project management. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The present invention is a flow chart of a method for using a device for detecting hollowing of building exterior walls based on acoustic signals. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] See also Figure 1 The present invention provides a technical solution: a device and a method for detecting hollowing of building exterior walls based on acoustic signals, comprising: 1. Preparation before testing: 1. Device calibration: The device was placed in an indoor calibration environment with a temperature of 20°C, a humidity of 40%, and a background noise level below 40 dB.

[0019] Fix a known standard hollow drum sample on the test stand, start the automatic tapping device, start with a tapping force of 1N at the upper left corner of the sample, and tap in sequence according to the preset grid positions (for example, 5cm×5cm intervals). When tapping at each position, the sound sensor array collects sound signals.

[0020] The microprocessor receives the collected sound signal data, compares it with the preset standard signal feature library (the library is established in advance through a large number of experiments by measuring the standard sample multiple times under the same environment), calculates the deviation between the actual sensitivity of the sound sensor and the ideal sensitivity, and automatically adjusts the gain circuit of the sound sensor to achieve the optimal match in the sensitivity range of 1-10mV / Pa.

[0021] At the same time, according to the frequency characteristics of the collected signal, the filter frequency band of the signal conditioning circuit is adjusted to 1-10kHz to filter out unnecessary interference frequency components, and the sampling frequency of the data acquisition card is set to 20kHz to ensure that the effective signal can be accurately collected.

[0022] 2. Environmental parameter collection and analysis initialization: Turn on the environmental sensor, collect the temperature, humidity and noise data of the current detection site, and record the initial environmental parameter values.

[0023] Substitute the collected temperature and humidity data into the sound speed correction formula.

[0024] For example, according to the empirical formula: ; in: is the corrected speed of sound, is the standard speed of sound, is the temperature, The correction coefficient of the acoustic signal propagation speed in the current environment is calculated for relative humidity and stored in the microprocessor for subsequent correction calculation of the acoustic signal propagation time.

[0025] The microprocessor starts the noise recognition algorithm, performs spectrum analysis on the collected noise signal, determines the main frequency bands of the background noise (for example, if it is detected that the main noise is concentrated in the low frequency band of 50-60Hz and the high frequency band of 15-20kHz), sets the noise filtering parameters in the signal conditioning circuit and subsequent data processing algorithm, and effectively suppresses the signals in these frequency bands.

[0026] 2. External wall inspection operation: 1. Scanning path planning and setting: Measure the length, width, and height of the building's exterior wall to be inspected, and input the data into the device's operating terminal. For rectangular walls, the operating terminal automatically generates a serpentine scanning path plan based on the input dimensions, divides the wall into several scanning areas (for example, into 1m×1m small areas based on the wall size and sensor array coverage), and determines the starting scanning point and scanning direction for each area.

[0027] Adjust the height and horizontal position of the movable bracket so that the sound sensor array is located at the starting position of the upper left corner of the outer wall, and use a laser rangefinder or other distance measuring device to ensure that the distance between the device and the wall is 5 cm, and then lock the initial position parameters of the movable bracket.

[0028] 2. Excitation and acoustic signal acquisition: The automatic tapping device is started to tap the outer wall at the set tapping frequency of 5Hz, tapping force of 2N and tapping interval of 0.5s. While tapping, the sound sensor array starts to synchronously collect sound signals, and the signal collected by each sensor carries the corresponding timestamp and position coding information (the position coding is determined according to the scanning path planning and the relative position of the sensor in the array).

[0029] The collected acoustic signal is first transmitted to the signal conditioning circuit. After amplification and filtering, the data acquisition card transmits the data to the microprocessor in real time at a sampling frequency of 20kHz. The microprocessor performs preliminary processing on the data, removes obvious outliers (for example, data points that exceed the normal signal amplitude range by 3 times the standard deviation), and extracts simple features such as the amplitude, frequency, and phase of the signal, and temporarily stores the processed data in the memory buffer for further analysis.

[0030] 3. Real-time data transmission and preliminary processing: The microprocessor monitors the integrity and continuity of data in real time while receiving data transmitted by the data acquisition card. If data loss or transmission interruption is found, an alarm will be issued immediately and the interruption location information will be recorded.

[0031] For the temporarily stored acoustic signal data, the microprocessor groups them according to the scanning area, calculates the statistical characteristics such as the average amplitude and frequency distribution of the acoustic signal in each area, and makes a preliminary comparison between these characteristic data and the characteristic range of the normal wall acoustic signal obtained during the previous calibration process, marking the areas where abnormalities may exist, providing a reference for subsequent in-depth analysis.

[0032] 3. Data analysis and hollowing judgment: 1. In-depth analysis of signal characteristics: The microprocessor calls the built-in wavelet analysis and time-frequency analysis algorithms to perform in-depth processing on the data in the temporary acoustic signal data buffer. The 3-8kHz frequency range is used as the key analysis interval to calculate the energy distribution of the acoustic signal in this interval. For the hollow area, since its internal structure is different from that of a normal wall, the acoustic signal in this frequency range usually has energy concentration or abnormal attenuation (for example, the acoustic signal energy in the hollow area may be more than 30% higher than that in the normal area near 5kHz, or the attenuation speed may be 50% faster than that in the normal area).

[0033] The acoustic signal characteristics of each scanned area are compared with the pre-established normal area acoustic signal characteristic library. The normal area acoustic signal characteristic library is established by collecting and analyzing acoustic signals multiple times on building exterior wall samples of the same material and structure without hollow drums. The library contains the characteristic data range and statistical model of acoustic signals at different locations under various environmental conditions. Through comparison, the hollow drum possibility index of each area is determined (for example, a hollow drum possibility score of 0-1 is set, 0 means no hollow drum possibility, and 1 means highly suspected hollow drum).

[0034] 2. Positioning and result visualization: According to the position coding information and scanning path planning of the sound sensor array, combined with the sound signal analysis results of each sampling point, the microprocessor accurately calculates the position coordinates of the hollow drum on the wall. For example, if a certain area is judged to be a hollow drum with a high probability, the position range of the hollow drum in the three-dimensional coordinate system of the wall is determined according to the sensor position and scanning order corresponding to the area (such as the X coordinate range is 3-4m, the Y coordinate range is 2-3m, and the Z coordinate represents the height, ranging from 5-6m).

[0035] The calculated hollowing position information is transmitted to the display and operation terminal, which highlights this information in a specific color (such as red) on the three-dimensional model of the building's exterior wall. At the same time, detailed information such as the size of the hollowing area (calculated based on the number of scanned areas involved and the area of ​​a single area), the depth estimate (preliminary depth estimate calculated based on the propagation time delay of the sound signal in the hollowing area and the corrected sound speed), and the hollowing possibility score are displayed, so that the inspector can intuitively understand the hollowing situation of the exterior wall.

[0036] 4. Data storage and report generation after detection: 1. Data storage: After the detection is completed, the microprocessor stores all the original data of this detection, including acoustic signal data (original waveform data of each sampling point), environmental parameter data (temperature, humidity, noise change curve during the detection process), detection location information (wall coordinates corresponding to each sampling point) and analysis results (hollow drum location coordinates, area, depth estimation, hollow drum possibility score, etc.) in a local solid-state hard disk in an encrypted binary format. At the same time, according to user settings, the data backup is uploaded to the cloud server to ensure data security and traceability.

[0037] 2. Report generation: The operation terminal automatically generates a detailed inspection report based on the inspection results. The report first contains basic information about the building's exterior wall, such as the building name, address, exterior wall material (such as concrete, brick, etc.), and structure type (such as frame structure, brick-concrete structure, etc.). Then the inspection time and the name of the inspector are recorded. The inspection results are then described in detail, including the number of hollows, the location of each hollow (in the form of a combination of wall coordinates and text description), area size, depth range estimation, and hollow severity assessment (based on a comprehensive judgment of hollow possibility scores and factors such as area and depth).

[0038] Finally, the relevant recommendations are generated based on the hollowing situation and the building structure safety standards. If the hollowing area is small and the depth is shallow, regular inspections are recommended; if the hollowing area is large or the depth is deep, timely repairs are recommended, and repair process references (such as grouting or partial demolition and reconstruction) and material recommendations (such as suitable grouting material models or brick specifications) are provided. Inspection personnel can view the report content on the operation terminal and print or export it to PDF or other formats as needed for submission to relevant departments or archiving.

[0039] To sum up: by adopting a high-precision sound sensor array combined with advanced signal processing algorithms, automated scanning path planning and intelligent knocking devices, as well as environmental compensation and data management technical means, the beneficial effects such as accurate detection and positioning of hollowing out of building exterior walls, efficient detection process, strong environmental adaptability and data management advantages are achieved, which comprehensively improves the performance and application value of building exterior wall hollowing out detection technology, and provides strong support for quality assurance and safe operation and maintenance of construction projects.

Claims

1. A device for detecting hollowing of building exterior walls based on acoustic signals, characterized in that: include: Sound sensor array: distributed in a specific geometric shape on a movable bracket to collect sound signals from the building's exterior wall; Signal conditioning circuit: connected to the sound sensor array, used to amplify and filter the collected weak sound signals; Data acquisition card: connected to the signal conditioning circuit, used to collect processed sound signal data and transmit it to the microprocessor; Microprocessor: Built-in data analysis and hollow drum judgment algorithm, used to analyze and process data; Display and operation terminal: connected to the microprocessor, used to set test parameters and display test results; Automatic knocking device: used to stimulate knocking on the exterior wall; Environmental sensor: used to collect temperature, humidity and noise data at the detection site.

2. The device for detecting hollowing of building exterior walls based on acoustic signals according to claim 1, characterized in that: The sound sensor array uses high-precision sensors with a sensitivity range of 1-10mV / Pa and a frequency response range of 0.1-20kHz.

3. The device for detecting hollowing of building exterior walls based on acoustic signals according to claim 1, characterized in that: The movable bracket has automatic positioning and navigation functions, can move automatically according to a preset scanning path, and the positioning accuracy is within ±2cm.

4. A method for using a device for detecting hollowing of building exterior walls based on acoustic signals according to any one of claims 1 to 3, characterized in that: The following steps are involved: S1: Preparation before testing: Use a known standard hollow drum sample to calibrate the device, collect the sound signals of the standard sample under different knocking forces and positions in an indoor environment, and compare them with the preset standard signals to make the device reach the best testing state; use environmental sensors to collect temperature, humidity and noise data at the testing site; S2: External wall detection operation steps: formulate a scanning path according to the shape and size of the building's external wall; use an automatic knocking device to knock on the external wall at a fixed frequency, force and interval as an excitation source. During the knocking process, the sound sensor array synchronously collects sound signals and records the position information of each sampling point and the corresponding sound signal data; S3: Data analysis and hollow drum judgment steps: Use wavelet analysis and time-frequency analysis algorithms to deeply analyze the temporarily stored sound signal data; combine the position information of the sound sensor array with the signal analysis results to calculate the position coordinates of the hollow drum on the wall; S4: Post-detection data storage and report generation steps.

5. The method for using the device for detecting hollowing of building exterior walls based on acoustic signals as claimed in claim 4, characterized in that: In S1, the indoor environment has a temperature between 15°C and 25°C, a humidity between 30% and 50%, and a background noise lower than 40 decibels.

6. The method for using the device for detecting hollowing of building exterior walls based on acoustic signals as claimed in claim 4, characterized in that: In S2, when formulating the scanning path, a serpentine path or a spiral path is used to scan the rectangular wall, and the distance between the device and the wall is maintained within 5-15 cm.

7. The method for using the device for detecting hollowing of building exterior walls based on acoustic signals as claimed in claim 4, characterized in that: In S2, the tapping frequency range of the automatic tapping device is 5-15 Hz, the tapping force can be adjusted between 2-6N, and the tapping interval is 0.5-2s.

8. The method for using the device for detecting hollowing of building exterior walls based on acoustic signals as claimed in claim 4, characterized in that: In the data analysis and hollowing judgment step in S3, the method for establishing the normal area sound signal feature library is: multiple sound signal collection and analysis are performed on building exterior wall samples of the same material and structure without hollowing, and the sound signal features at different positions are extracted and statistically averaged to form feature library data.

9. The method for using the device for detecting hollowing of building exterior walls based on acoustic signals as claimed in claim 4, characterized in that: In S4, in the data storage step, the local storage device uses a solid state hard disk, and the data storage format is an encrypted binary format to ensure the security and integrity of the data.

10. The method for using the device for detecting hollowing of building exterior walls based on acoustic signals as claimed in claim 4, characterized in that: In S4, in the report generation step, the relevant suggestions are automatically generated based on the area, depth and location information of the hollowing, combined with the building structure safety standards, including whether immediate repair is needed and suggestions on repair processes and materials.

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