Metal stress data acquisition method, device, computer equipment and storage medium

Abstract

This application relates to a metal stress data acquisition method, apparatus, computer device, and storage medium. The method includes: using an embedded system to drive a constant current source to generate a current signal, which drives an excitation coil to detect metal components; acquiring multi-channel stress detection data using a TMR array, performing front-end amplification and channel switching on the stress detection data, and then inputting the data as a sequence into the embedded system; within the embedded system, processing the sequence using a digital orthogonal lock-in amplifier using a preset sampling frequency and storage space to obtain the amplitude and phase of the stress detection data. This method enables high-performance stress data acquisition.

Description

Technical Field

[0001] The present application relates to the field of high-performance signal acquisition technology, and in particular to a metal stress data acquisition method, device, computer equipment, and storage medium. Background Art

[0002] The principle currently used in metal stress detection is that when metal is subjected to stress, the electrical conductivity will undergo a slight change due to the piezoresistive effect, and the change is close to linear. Therefore, the electrical conductivity of the material is generally measured by measuring the eddy current magnetic field, and then the stress is inferred.

[0003] However, the change in conductivity caused by stress is very small, usually less than 1% over the full range, and temperature changes can also cause conductivity changes. Therefore, requirements are placed on both stress detection accuracy and signal detection accuracy. Summary of the Invention

[0004] Based on this, it is necessary to provide a high-performance metal stress data acquisition method, device, computer equipment and storage medium to address the above technical problems.

[0005] A metal stress data acquisition method, the method comprising:

[0006] The embedded system drives a constant current source to generate a current signal, so that the current signal drives an excitation coil to detect the metal component;

[0007] The stress detection data of multiple channels is collected through the TMR array, and after the stress detection data is amplified and switched through the channels at the front end, it is input into the embedded system as a sequence;

[0008] In the embedded system, the sequence is processed by a digital orthogonal lock-in amplifier using a preset sampling frequency and a preset storage space to obtain the amplitude and phase of the stress detection data.

[0009] In one embodiment, the method further includes: obtaining a frequency f of stress detection data, a sampling time N / f for collecting N cycles of the stress detection data, and a sampling frequency f s ;

[0010] Constructing a relationship: Where M is the number of sampling points in a cycle, and N is an integer to ensure full cycle sampling;

[0011] During frequency sweep testing, the change pattern of stress test data is: f=n 2 f1, n=1, 2, ..., 10; said f1 is determined according to the physical properties of the metal component;

[0012] At the sampling frequency f sWhen fixed, the relationship Convert to Thus, the minimum sampling frequency f that meets the conditions is determined s is the preset sampling frequency.

[0013] In one embodiment, the method further includes: determining the occupied storage space according to the fixed number of sampling points and the size of the data of each sampling point;

[0014] The required storage space is determined according to the occupied storage space and the number of sequences that the digital quadrature lock-in amplifier participates in the operation each time.

[0015] In one embodiment, it also includes: receiving external input commands and parameters through the embedded system, controlling the DDS chip to generate a sinusoidal voltage with adjustable amplitude and frequency, and converting it into a current signal after passing through a filter with adjustable cutoff frequency and program-controlled amplification to drive the excitation coil.

[0016] In one embodiment, the method further includes: collecting 8-channel stress detection data through a TMR array, amplifying the stress detection data at the front end, switching channels through a subtractor and an analog switch, and inputting the data into an embedded system as a sequence.

[0017] In one embodiment, the embedded system further includes: FPGA and ARM;

[0018] The FPGA includes a multi-channel high-speed AD acquisition circuit, a DDS multi-frequency signal generation circuit, and a DDR memory read-write controller;

[0019] ARM includes UART read and write control and digital quadrature lock-in amplifier.

[0020] In one embodiment, the method further includes: writing the calculated frequency point as a configuration parameter of the DDS into the DDR, triggering the FPGA to work, and storing the stress detection data collected by the FPGA into the DDR;

[0021] The stress detection data is read from the DDR and the sequence is processed using a digital quadrature lock-in amplifier.

[0022] A metal stress data acquisition device, comprising:

[0023] A detection module, configured to drive a constant current source through an embedded system to generate a current signal, so that the current signal drives an excitation coil to detect the metal component;

[0024] An acquisition module is used to acquire multi-channel stress detection data through a TMR array, amplify the stress detection data at the front end, switch channels, and input the data into the embedded system as a sequence;

[0025] The processing module is used to process the sequence in the embedded system by using a digital orthogonal lock-in amplifier with a preset sampling frequency and a preset storage space to obtain the amplitude and phase of the stress detection data.

[0026] A computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0027] The embedded system drives a constant current source to generate a current signal, so that the current signal drives an excitation coil to detect the metal component;

[0028] Collecting multi-channel stress detection data through a TMR array, amplifying the stress detection data at the front end and switching the channels, and then inputting the data into an embedded system as a sequence;

[0029] In the embedded system, the sequence is processed by a digital orthogonal lock-in amplifier using a preset sampling frequency and a preset storage space to obtain the amplitude and phase of the stress detection data.

[0030] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0031] The embedded system drives a constant current source to generate a current signal, so that the current signal drives an excitation coil to detect the metal component;

[0032] Collecting multi-channel stress detection data through a TMR array, amplifying the stress detection data at the front end and switching the channels, and then inputting the data into an embedded system as a sequence;

[0033] In the embedded system, the sequence is processed by a digital orthogonal lock-in amplifier using a preset sampling frequency and a preset storage space to obtain the amplitude and phase of the stress detection data.

[0034] The aforementioned metal stress data acquisition method, apparatus, computer equipment, and storage medium address the need for both stress and signal detection accuracy by significantly improving signal detection accuracy, thereby addressing stress detection accuracy issues. Regarding signal detection accuracy, multi-channel stress detection data is first acquired at high speed, preserving as much information as possible. This data is then amplified and switched through the front end to form a data sequence. By setting an appropriate sampling frequency and storage space, the sequence is processed using a digital orthogonal lock-in amplifier to restore the original data information as much as possible. Consequently, when using the aforementioned amplitude and phase for stress inversion, the inversion results are superior due to the large amount of information contained in the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A schematic diagram of a metal stress data acquisition system according to an embodiment of the present invention;

[0036] Figure 2 1 is a flow chart of a metal stress data acquisition method according to an embodiment;

[0037] Figure 3 is a structural block diagram of a metal stress data acquisition device in one embodiment;

[0038] Figure 4 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0040] The metal stress data acquisition method provided in this application can be applied to Figure 1 The metal stress data acquisition system shown in the figure is briefly introduced as follows:

[0041] 1. The embedded system (FPGA+ARM) controls the DDS chip to generate a sinusoidal voltage with adjustable amplitude and frequency (40Hz~1MHz) according to the commands and parameters of the information processing platform. After filtering (low-pass or band-pass filter with adjustable cutoff frequency) and program-controlled amplification, it is converted into a current signal (50~500mA) to drive the excitation coil.

[0042] 2. The 8-channel voltage signals output by the TMR array are respectively sent to the embedded system for processing after low-noise preamplification (noise less than 10nV) and high-speed and high-resolution data acquisition.

[0043] 3. The embedded system uses a digital orthogonal phase-locked amplification algorithm to complete accurate signal detection and obtain measurement data (amplitude and phase of 8-channel sinusoidal voltage signals, with amplitude repetition accuracy better than 0.01%).

[0044] 4. The embedded system transmits the measurement data to the information processing platform (PC) through the USB interface, and completes waveform display, information fusion (multi-frequency information fusion, array information fusion), conductivity inversion and calibration, stress inversion and calibration, and realizes three-dimensional imaging of stress distribution through software programming.

[0045] 5. In order to obtain the three-dimensional residual stress distribution of the metal component, it is necessary to use the sensor array to perform frequency sweep detection on the stress at different depths inside (f = n 2f1, n=1,2,...,10, f1∈40~10kHz),

[0046] The single-point stress measurement time is less than 10 seconds.

[0047] In one embodiment, Figure 2 As shown, a metal stress data acquisition method is provided, which is applied to Figure 1 The metal stress data acquisition system in the example is used to illustrate the following steps:

[0048] Step 202: The embedded system drives a constant current source to generate a current signal, so that the current signal drives an excitation coil to detect the metal component.

[0049] Step 204 : collecting multi-channel stress detection data through the TMR array, performing front-end amplification and channel switching on the stress detection data, and then inputting the data into the embedded system as a sequence.

[0050] Step 206 : In the embedded system, a digital quadrature lock-in amplifier is used to process the sequence using a preset sampling frequency and a preset storage space to obtain the amplitude and phase of the stress detection data.

[0051] The aforementioned metal stress data acquisition method, while addressing the need for both stress and signal detection accuracy, significantly improves signal detection accuracy to compensate for stress detection accuracy issues. Regarding signal detection accuracy, multi-channel stress detection data is first acquired at high speed, preserving as much information as possible. This data is then amplified and switched through the front end to form a data sequence. This sequence is then processed using a digital orthogonal lock-in amplifier by setting an appropriate sampling frequency and storage space, thereby restoring the original data information as much as possible. Consequently, when using the aforementioned amplitude and phase for stress inversion, the inversion results are superior due to the large amount of information contained in the data.

[0052] In one embodiment, the step of selecting the sampling frequency includes: obtaining the frequency f of the stress detection data, sampling time N / f of collecting N cycles of the stress detection data, and sampling frequency f s ; Construct the relationship: Among them, M is the number of periodic sampling points, and N is an integer to ensure full-cycle sampling. During frequency sweep detection, the change pattern of stress detection data is: f = n 2 f1, n = 1, 2, ..., 10; said f1 is determined according to the physical properties of the metal component; at the sampling frequency f s When fixed, the relationship Convert to Thus, the minimum sampling frequency f that meets the conditions is determined sIn this embodiment, by setting the full cycle, it is possible to ensure that the data of the acquisition points are not lost, thereby ensuring the accuracy of the digital orthogonal lock-in amplifier processing.

[0053] In one embodiment, the occupied storage space is determined based on the fixed number of sampling points and the size of the data at each sampling point; the required storage space is determined based on the occupied storage space and the number of sequences involved in the operation of the digital orthogonal lock-in amplifier each time.

[0054] Specifically:

[0055] (1) When the metal material being tested is aluminum alloy (typical conductivity is about 25MS / m, relative magnetic permeability is 1), the frequency corresponding to a penetration depth of 2.2mm is about 2kHz.

[0056] Table 1 Aluminum alloy sweep frequency detection data comparison table

[0057] n <![CDATA[f=n 2 f1(kHz)]]> Number of cycles N Number of sampling points M Sampling time (ms) 1 2 10 31752 5 2 8 40 31752 5 3 18 90 31752 5 4 32 160 31752 5 5 50 250 31752 5 6 72 360 31752 5 7 98 490 31752 5 8 128 640 31752 5 9 162 810 31752 5 10 200 1000 31752 5

[0058] (2) When the metal material being tested is titanium alloy (typical conductivity is about 5MS / m, relative magnetic permeability is 1), the frequency corresponding to the penetration depth of 2.2mm is about 10kHz.

[0059] Table 2 Titanium alloy sweep frequency detection data comparison table

[0060]

[0061]

[0062] (3) When the metal material being tested is a nickel-based alloy (typical conductivity is about 10MS / m, relative magnetic permeability is about 120), the frequency corresponding to a penetration depth of 2.2mm is about 40Hz.

[0063] Table 3 Comparison table of nickel-based alloy frequency sweep test data

[0064] n <![CDATA[f=n 2 f1(Hz)]]> Number of cycles N Number of sampling points M Sampling time (ms) 1 40 1 158760 25 2 160 4 158760 25 3 360 9 158760 25 4 640 16 158760 25 5 1000 25 158760 25 6 1440 36 158760 25 7 1960 49 158760 25 8 2560 64 158760 25 9 3240 81 158760 25 10 4000 100 158760 25

[0065] Specifically, for all metal materials, the number of sampling points can be fixed at 158,760. Each data point is 2 bytes, which requires approximately 310kB of storage space. Since the digital lock-in amplification algorithm involves three sequences, and considering the cache, the storage capacity of the embedded system should be no less than 1MB.

[0066] In one embodiment, a constant current source is driven by an embedded system to generate a current signal, including: receiving external input commands and parameters through the embedded system, controlling a DDS chip to generate a sinusoidal voltage with adjustable amplitude and frequency, and converting it into a current signal after passing through a filter with adjustable cutoff frequency and program-controlled amplification to drive an excitation coil.

[0067] In one embodiment, multi-channel stress detection data is collected through a TMR array, and the stress detection data is amplified at the front end and the channels are switched, and then the data is input into an embedded system as a sequence, including: collecting 8-channel stress detection data through a TMR array, amplifying the stress detection data at the front end, switching the channels through a subtractor and an analog switch, and then inputting the data into the embedded system as a sequence.

[0068] In one embodiment, the embedded system includes: FPGA and ARM; the FPGA includes a multi-channel high-speed AD acquisition circuit, a DDS multi-frequency signal generation circuit and a DDR memory read-write controller; the ARM includes a UART read-write control and a digital orthogonal lock-in amplifier.

[0069] In one embodiment, the frequency point is calculated as the configuration parameter of DDS and written into DDR, and the FPGA is triggered to work, and the stress detection data collected by the FPGA is stored in the DDR; the stress detection data is read from the DDR, and the sequence is processed using a digital orthogonal lock-in amplifier.

[0070] In summary, the present invention uses a planar array magnetic sensor as a sensing element. By providing an excitation signal to the array magnetic sensor, the sensor output signal is amplified and filtered. The signal, acquired by a high-speed, high-precision AD system, is then amplified by a digital orthogonal phase-locked amplifier to obtain amplitude and phase information. Finally, a host computer processes and inverts the signal characteristics, thereby achieving three-dimensional stress distribution imaging. The detection system can detect residual stress distribution within four typical metal materials, with a detection range of -700 to 700 MPa, a stress uncertainty better than 30 MPa, a detection depth of 0 to 2.2 mm, a positional resolution of residual stress distribution better than 5 mm × 5 mm × 0.2 mm, and a single-point stress detection time of less than 10 seconds.

[0071] In terms of specific hardware design, the embedded system can use the ZYNQ core board, which integrates dual-core ARM and FPGA and has rich peripheral resources and IO resources.

[0072] On this basis, the selection of key components is explained.

[0073] 1. DDS selection

[0074] The AD9834 DDS is a 75MHz, low-power DDS device capable of generating high-performance sine and triangle wave outputs. It also integrates an on-chip comparator that supports square wave generation for clock generation. When powered by a 3V supply, its power consumption is only 20mW.

[0075] The AD9834 provides both phase and frequency modulation capabilities. The frequency register is 28 bits, and at a 75MHz clock rate, a resolution of 0.28Hz can be achieved. Similarly, at a 1MHz clock rate, the AD9834 can achieve a resolution of 0.004Hz.

[0076] 2. ADC selection

[0077] The ADC model is ADS1605. ADS1605 is a single-channel differential input, 5MSPS sampling rate high-speed ADC, 2.45Mhz bandwidth, built-in digital filter, and high signal-to-noise ratio.

[0078] 3. Reference source

[0079] The reference source selected is Linear Technology's LT6657-1, which combines robust operating characteristics with extremely low drift and noise. Leveraging advanced curvature compensation, this bandgap reference achieves 1.5ppm / °C drift, predictable temperature characteristics, and 0.1% initial voltage accuracy. It also offers 0.5ppmP-P noise and very low temperature cycling hysteresis.

[0080] 4. Constant current chip

[0081] The constant current chip model is LT1206, with a minimum drive current of 250mA, a bandwidth of 60Mhz, an input impedance of 10MΩ, and a wide voltage supply range of ±5V to ±15V.

[0082] 5. Programmable amplifier

[0083] The programmable amplifier model is LTC6911-1, which can switch different amplification factors of 0, -1, -2, -5, -10, -20, and -50 through programming. It has low noise and rail-to-rail operation.

[0084] It should be understood that although Figure 2 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. In addition, Figure 2 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0085] In one embodiment, Figure 3As shown, a metal stress data acquisition device is provided, including: a detection module 302, an acquisition module 304 and a processing module 306, wherein:

[0086] A detection module 302 is configured to drive a constant current source through an embedded system to generate a current signal, so that the current signal drives an excitation coil to detect the metal component;

[0087] An acquisition module 304 is configured to acquire multi-channel stress detection data through a TMR array, amplify the stress detection data at the front end, switch channels, and then input the data into an embedded system as a sequence;

[0088] The processing module 306 is used to process the sequence in the embedded system using a digital orthogonal lock-in amplifier with a preset sampling frequency and a preset storage space to obtain the amplitude and phase of the stress detection data.

[0089] In one embodiment, the acquisition module 304 is further configured to acquire the frequency f of the stress detection data, the sampling time N / f for acquiring N cycles of the stress detection data, and the sampling frequency f s ;

[0090] Constructing a relationship: Where M is the number of sampling points in a cycle, and N is an integer to ensure full cycle sampling;

[0091] During frequency sweep testing, the change pattern of stress test data is: f=n 2 f1, n=1, 2, ..., 10; said f1 is determined according to the physical properties of the metal component;

[0092] At the sampling frequency f s When fixed, the relationship Convert to Thus, the minimum sampling frequency f that meets the conditions is determined s is the preset sampling frequency.

[0093] In one embodiment, the acquisition module 304 is also used to determine the occupied storage space based on a fixed number of sampling points and the size of the data at each sampling point; and determine the required storage space based on the occupied storage space and the number of sequences involved in the operation of the digital orthogonal lock-in amplifier each time.

[0094] In one embodiment, the detection module 302 receives external input commands and parameters through an embedded system, controls the DDS chip to generate a sinusoidal voltage with adjustable amplitude and frequency, and converts it into a current signal after passing through a filter with adjustable cutoff frequency and program-controlled amplification to drive the excitation coil.

[0095] In one embodiment, the acquisition module 304 is further configured to acquire 8-channel stress detection data through a TMR array, amplify the stress detection data at the front end, switch channels through a subtractor and an analog switch, and input the data into the embedded system as a sequence.

[0096] In one embodiment, the embedded system includes: FPGA and ARM; FPGA includes a multi-channel high-speed AD acquisition circuit, a DDS multi-frequency signal generation circuit and a DDR memory read-write controller; ARM includes UART read-write control and a digital orthogonal lock-in amplifier.

[0097] In one embodiment, the frequency point is calculated as the configuration parameter of DDS and written into DDR, and the FPGA is triggered to work, and the stress detection data collected by the FPGA is stored in the DDR; the stress detection data is read from the DDR, and the sequence is processed using a digital orthogonal lock-in amplifier.

[0098] The specific definitions of the metal stress data acquisition device can be found in the definitions of the metal stress data acquisition method above and will not be further elaborated here. Each module in the aforementioned metal stress data acquisition device can be implemented in whole or in part via software, hardware, or a combination thereof. Each of these modules can be embedded in or independent of a processor within a computer device in hardware form, or stored in a computer device memory in software form, allowing the processor to call and execute the corresponding operations of each module.

[0099] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network 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 network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a metal stress data acquisition method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad provided on the computer device housing, or an external keyboard, touchpad or mouse.

[0100] Those skilled in the art will understand that Figure 4The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0101] In one embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps of the method in the above embodiment when executing the computer program.

[0102] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method in the above embodiment are implemented.

[0103] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0104] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0105] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A metal stress data acquisition method, characterized in that: The method comprises: The embedded system drives a constant current source to generate a current signal, so that the current signal drives an excitation coil to detect the metal component; Collecting multi-channel stress detection data through a TMR array, amplifying the stress detection data at the front end and switching the channels, and then inputting the data into an embedded system as a sequence; In the embedded system, the sequence is processed by a digital orthogonal lock-in amplifier using a preset sampling frequency and a preset storage space to obtain the amplitude and phase of the stress detection data; The step of selecting the sampling frequency includes: Frequency of obtaining stress test data , the sampling time for collecting N cycles of the stress detection data and sampling frequency ; Constructing a relationship: ; Where M is the number of sampling points in a cycle, and N is an integer to ensure full cycle sampling; During frequency sweep testing, the change pattern of stress test data is as follows: , ; It is determined based on the physical properties of the metal component; At the sampling frequency When fixed, the relationship Convert to , thereby determining the minimum sampling frequency that meets the conditions is the preset sampling frequency.

2. The method according to claim 1, characterized in that The steps to select a storage space include: Determine the occupied storage space based on the fixed number of sampling points and the size of the data at each sampling point; The required storage space is determined according to the occupied storage space and the number of sequences that the digital quadrature lock-in amplifier participates in the operation each time.

3. The method according to claim 1, characterized in that The embedded system drives the constant current source to generate a current signal, including: The embedded system receives external input commands and parameters, controls the DDS chip to generate a sinusoidal voltage with adjustable amplitude and frequency, and converts it into a current signal after passing through a filter with adjustable cutoff frequency and program-controlled amplification to drive the excitation coil.

4. The method according to claim 1, wherein The method includes collecting multi-channel stress detection data through the TMR array, performing front-end amplification and channel switching on the stress detection data, and inputting the data into the embedded system as a sequence, including: Eight-channel stress detection data are collected through the TMR array. After the stress detection data is amplified at the front end, the channel switching is performed through a subtractor and an analog switch, and the data is input into the embedded system as a sequence.

5. The method according to any one of claims 1 to 4, characterized in that The embedded system includes: FPGA and ARM; The FPGA includes a multi-channel high-speed AD acquisition circuit, a DDS multi-frequency signal generation circuit, and a DDR memory read-write controller; ARM includes UART read and write control and digital quadrature lock-in amplifier.

6. The method according to claim 5, characterized in that The method further comprises: The frequency point is calculated as the configuration parameter of DDS and written into DDR, and the FPGA is triggered to work and the stress detection data collected by FPGA is stored in DDR; The stress detection data is read from the DDR and the sequence is processed using a digital quadrature lock-in amplifier.

7. A metal stress data acquisition device, characterized in that: The device comprises: A detection module, configured to drive a constant current source through an embedded system to generate a current signal, so that the current signal drives an excitation coil to detect the metal component; An acquisition module is used to acquire multi-channel stress detection data through a TMR array, amplify the stress detection data at the front end, switch channels, and input the data into the embedded system as a sequence; a processing module, configured to process the sequence in the embedded system using a digital orthogonal lock-in amplifier with a preset sampling frequency and a preset storage space to obtain the amplitude and phase of the stress detection data; The step of selecting the sampling frequency includes: Frequency of obtaining stress test data , the sampling time for collecting N cycles of the stress detection data and sampling frequency ; Constructing a relationship: ; Where M is the number of sampling points in a cycle, and N is an integer to ensure full cycle sampling; During frequency sweep testing, the change pattern of stress test data is as follows: , ; It is determined based on the physical properties of the metal component; At the sampling frequency When fixed, the relationship Convert to , thereby determining the minimum sampling frequency that meets the conditions is the preset sampling frequency.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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