Method and device for detecting the surface roughness of a subperiosteal implant

Abstract

The application provides a subperiosteal implant surface roughness detection method and device, acquires light signals scattered by a to-be-detected subperiosteal implant surface and converts the light signals into time-domain interference signals; based on a first preset algorithm, time-frequency conversion is performed on the time-domain interference signals to obtain frequency-domain interference signals and phase spectrum of the frequency-domain interference signals is calculated to acquire phase information; based on a second preset algorithm, phase unwrapping is performed on the phase information to obtain surface height information; and based on the surface height information, surface roughness of the to-be-detected subperiosteal implant is acquired. The application solves the problem that the prior art contact type surface detection method is difficult to measure surfaces with large curvature, and the local detection method has high uniformity requirements for a to-be-detected large surface, resulting in inaccurate surface roughness detection results. The application realizes overall surface scanning through optical detection and improves the accuracy of surface roughness detection results by combining optical signal data processing.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of laser detection, in particular to a method and device for detecting the surface roughness of a subperiosteal implant. BACKGROUND

[0002] A 3D-printed subperiosteal implant has the feature of fitting the surface of a jawbone, and its external morphology is a continuous curved surface consistent with the surface of alveolar bone according to the morphology of each patient. The roughness of a subperiosteal implant is an important indicator of quality detection. Since the upper and lower surfaces have different roughness requirements, the roughness of a subperiosteal implant needs to be comprehensively detected.

[0003] At present, the prior art uses a contact measurement method to measure the local surface of a sampling piece. Since it is limited by the shape of the workpiece, the contact surface detection method is difficult to measure the surface with a large curvature. The local detection method has a high uniformity requirement for the large surface to be measured, which leads to the problem of inaccurate surface roughness detection results. SUMMARY

[0004] To solve the above problems, the present application provides a method and device for detecting the surface roughness of a subperiosteal implant, which realizes overall surface scanning through optical detection and improves the accuracy of surface roughness detection results by combining optical signal data processing.

[0005] To achieve the above purpose, the present application provides a method for detecting the surface roughness of a subperiosteal implant, comprising:

[0006] Obtaining the light signal scattered by the surface of the subperiosteal implant to be measured and converting it into a time-domain interference signal;

[0007] Based on a first preset algorithm, the time-domain interference signal is subjected to time-frequency conversion to obtain a frequency-domain interference signal, and the phase spectrum of the frequency-domain interference signal is calculated to obtain phase information;

[0008] Based on a second preset algorithm, the phase information is subjected to phase unwrapping to obtain surface height information;

[0009] Based on the surface height information, the surface roughness of the subperiosteal implant to be measured is obtained.

[0010] The embodiment of the present application provides a detection method for the surface roughness of a subperiosteal implant, the light signal scattered by the surface of the subperiosteal implant to be measured is obtained, and the method is not limited by the shape of the sample, the surface curvature of the sample, and the uniformity requirement of the sample surface, then the optical signal is converted into a time-domain interference signal, the time-domain interference signal contains multiple phase changes, which can provide a data basis for further analysis of the surface roughness of the subperiosteal implant to be measured, the time-domain interference signal is converted into a frequency-domain interference signal, the phase information is separated, the noise interference can be reduced by separating the phase information, the accuracy of the calculation of the surface roughness of the subperiosteal implant to be measured is improved, and then the surface height information is obtained by further phase unwrapping of the phase information, the surface roughness of the subperiosteal implant to be measured is obtained, the influence of phase ambiguity on the calculation result of the surface roughness of the subperiosteal implant to be measured is reduced, and the accuracy of the calculation of the surface roughness of the subperiosteal implant to be measured is improved.

[0011] Further, the light signal scattered by the surface of the subperiosteal implant to be measured is obtained and converted into a time-domain interference signal, including:

[0012] The optical path difference and the phase difference of the reflected light beams based on different reflection positions are obtained to obtain the light signal scattered by the surface of the subperiosteal implant to be measured.

[0013] The light signal scattered by the surface of the subperiosteal implant to be measured is photoelectrically converted based on a preset photoelectric sensor to obtain the time-domain interference signal.

[0014] Since the prior art is limited by factors such as the shape of the sample, the accuracy of the calculation of the surface roughness of the subperiosteal implant to be measured is not high, the embodiment of the present application provides a detection method for the surface roughness of a subperiosteal implant, the optical signal obtained by optical detection can accurately obtain the optical path difference and the phase difference of different reflection positions of the surface to be measured, the light signal scattered by the surface of the subperiosteal implant to be measured is obtained, and the method is not limited by the shape of the sample, the surface curvature of the sample, and the uniformity requirement of the sample surface, the overall surface can be measured to provide an accurate data basis for subsequent conversion processing, the optical signal is captured by a photoelectric sensor for photoelectric conversion, the weak light signal scattered by the surface of the subperiosteal implant to be measured is more accurately captured, the signal-to-noise ratio of the time-domain interference signal is improved, the optical signal is analyzed in the time domain, the signal distortion and errors are reduced, an accurate data basis is provided, and the accuracy of the calculation of the surface roughness of the subperiosteal implant to be measured is improved.

[0015] Further, the time-domain interference signal is converted into a frequency-domain interference signal based on a first preset algorithm, and the phase information is obtained by calculating the phase spectrum of the frequency-domain interference signal, including:

[0016] The time-domain interference signal is Fourier transformed based on a first preset algorithm to obtain a frequency-domain interference signal.

[0017] calculating an absolute value of the frequency domain interference signal to obtain an amplitude spectrum of the frequency domain interference signal;

[0018] calculating a phase spectrum of the frequency domain interference signal based on the amplitude spectrum of the frequency domain interference signal by an inverse tangent function to obtain phase information.

[0019] The embodiment of the present application provides a detection method for the surface roughness of a subperiosteal implant, converts a time domain signal into a frequency domain signal through time-frequency conversion, can more clearly obtain the distribution characteristics of the signal in the frequency domain, separates the phase information, can effectively identify noise and interference signals through frequency domain analysis, and improves the accuracy of the calculation of the surface roughness of the subperiosteal implant to be detected.

[0020] Further, the phase information is unwrapped based on the second preset algorithm to obtain surface height information, including:

[0021] Based on the second preset algorithm, a phase spectrum region corresponding to the phase information to be processed is obtained, and an unwrapping starting point is set.

[0022] Phase difference calculation is performed on the neighborhood pixels of the unwrapping starting point, phase adjustment is performed on the phase whose deviation is greater than a preset threshold, and a plurality of phase differences are obtained.

[0023] Based on the plurality of phase differences, a point with the smallest adjacent phase difference is selected as a next tracking point, and a phase value is updated.

[0024] Based on the updated phase value, phase conversion is performed on the unwrapped phase difference to obtain surface height information.

[0025] Further, the phase conversion is performed on the unwrapped phase difference based on the updated phase value to obtain surface height information, including:

[0026] The updated phase value is taken as a new unwrapping starting point, the phase spectrum region corresponding to the phase information to be processed is traversed until the phase change meets a preset unwrapping condition, and an unwrapped phase difference is obtained.

[0027] The unwrapped phase difference is converted into surface height information through a phase conversion formula.

[0028] Since the phase information may jump (phase ambiguity), phase unwrapping processing is required, and the embodiment of the present application provides a detection method for the surface roughness of a subperiosteal implant, which can eliminate the ambiguity in the phase information, thereby restoring the real phase distribution, can reduce the phase error through phase difference tracking point selection, can reduce the influence of noise on the result, and can improve the data precision.

[0029] Further, the surface roughness of the subperiosteal implant to be measured is obtained based on the surface height information, and the surface roughness of the subperiosteal implant to be measured is obtained based on the arithmetic average roughness.

[0030] The total number of traversed measurement points and the height value of each measurement point are obtained based on the surface height information.

[0031] The arithmetic average roughness is calculated based on the total number of traversed measurement points and the height value of each measurement point.

[0032] The surface roughness of the subperiosteal implant to be measured is obtained based on the arithmetic average roughness.

[0033] The embodiment of the present application provides a detection method for the surface roughness of a subperiosteal implant, and the arithmetic average roughness directly calculated based on the surface height information can accurately reflect the microscopic geometric shape characteristics of the implant surface, such as the ups and downs and the peak and valley distribution, so as to realize accurate measurement of the surface roughness. In addition, the non-contact measurement method for obtaining the surface height information can reduce the artificial errors such as scratches and deformation caused by the contact between the measurement tool and the implant surface, and improve the accuracy and reliability of the measurement.

[0034] The embodiment of the present application also provides a detection device for the surface roughness of a subperiosteal implant, which comprises:

[0035] A support frame, a laser emitter and an optical processor.

[0036] The subperiosteal implant to be measured is arranged on the support frame, and the support frame is adjusted to make the subperiosteal implant to be measured present different angle postures, so as to obtain the surface of the subperiosteal implant to be measured at different angles.

[0037] The laser emitter emits a laser beam, and the laser beam is irradiated on the surface of the subperiosteal implant to be measured to generate a light signal scattered by the surface of the subperiosteal implant to be measured.

[0038] The optical processor comprises a time domain signal acquisition module, a time-frequency conversion module, a phase unwrapping module and a roughness acquisition module.

[0039] The time domain signal acquisition module is used to acquire the light signal scattered by the surface of the subperiosteal implant to be measured and convert it into a time domain interference signal.

[0040] The time-frequency conversion module is used to perform time-frequency conversion on the time domain interference signal based on a first preset algorithm, obtain a frequency domain interference signal, and acquire phase information by calculating the phase spectrum of the frequency domain interference signal.

[0041] The phase unwrapping module is used to perform phase unwrapping on the phase information based on a second preset algorithm to obtain surface height information.

[0042] The roughness acquisition module is configured to acquire the surface roughness of the subperiosteal implant to be measured based on the surface height information.

[0043] The embodiment of the present application provides a detection device for the surface roughness of a subperiosteal implant, and the optical processor can accurately capture the phase information of the microfluctuation of the surface of the subperiosteal implant to be measured. On this basis, the laser beam emitted by the laser is irradiated on the surface of the subperiosteal implant to be measured on the support frame. The surface of the subperiosteal implant to be measured at different angles is obtained by adjusting the support frame. The light signal scattered by the surface of the subperiosteal implant to be measured is obtained by the time-domain signal acquisition module, and the present application is not limited to the shape of the sample, the surface curvature of the sample and the uniformity requirement of the sample surface. Then, the optical signal is converted into a time-domain interference signal, the time-domain interference signal contains a plurality of phase changes, and data basis can be provided for further analysis of the surface roughness of the subperiosteal implant to be measured. The time-domain interference signal is converted into a frequency-domain interference signal by the time-frequency conversion module, the phase information is separated, the noise interference can be reduced by separating the phase information, the accuracy of the calculation of the surface roughness of the subperiosteal implant to be measured is improved, and the surface height information is obtained by further phase unwrapping of the phase information by the phase unwrapping module. Then, the surface roughness of the subperiosteal implant to be measured is obtained by the roughness acquisition module, the influence of phase ambiguity on the calculation result of the surface roughness of the subperiosteal implant to be measured is reduced, and the accuracy of the calculation of the surface roughness of the subperiosteal implant to be measured is improved.

[0044] Further, the support frame comprises a rotatable sample table and a support rod.

[0045] The rotatable sample table is provided with a jawbone model, and the subperiosteal implant to be measured is installed on the jawbone model.

[0046] One end of the support rod is provided with a ball.

[0047] The ball at one end of the support rod is in interference fit with the recess hole arranged at the bottom of the rotatable sample table, and the support rod can be rotated to a plurality of angles after being connected with the rotatable sample table, so as to generate the surface of the subperiosteal implant to be measured at different angles.

[0048] The embodiment of the present application provides a detection device for the surface roughness of a subperiosteal implant, and the optical processor can accurately capture the phase information of the microfluctuation of the surface of the subperiosteal implant to be measured. On this basis, the laser beam emitted by the laser is irradiated on the surface of the subperiosteal implant to be measured on the support frame. The surface of the subperiosteal implant to be measured at different angles is obtained by adjusting the support frame. The light signal scattered by the surface of the subperiosteal implant to be measured is obtained by the time-domain signal acquisition module, and the present application is not limited to the shape of the sample, the surface curvature of the sample and the uniformity requirement of the sample surface. Then, the optical signal is converted into a time-domain interference signal, the time-domain interference signal contains a plurality of phase changes, and data basis can be provided for further analysis of the surface roughness of the subperiosteal implant to be measured. The time-domain interference signal is converted into a frequency-domain interference signal by the time-frequency conversion module, the phase information is separated, the noise interference can be reduced by separating the phase information, the accuracy of the calculation of the surface roughness of the subperiosteal implant to be measured is improved, and the surface height information is obtained by further phase unwrapping of the phase information by the phase unwrapping module. Then, the surface roughness of the subperiosteal implant to be measured is obtained by the roughness acquisition module, the influence of phase ambiguity on the calculation result of the surface roughness of the subperiosteal implant to be measured is reduced, and the accuracy of the calculation of the surface roughness of the subperiosteal implant to be measured is improved.

[0049] Further, the rotatable sample table is provided as a hemispherical body, and the jawbone model is arranged on the spherical surface.

[0050] The embodiment of the present application provides a subperiosteal implant surface roughness detection device, a rotatable sample table is arranged as a hemisphere, so that the subperiosteal implant to be detected can be attached to a jawbone model, a real oral environment is simulated, and the hemisphere shape is helpful to observation and detection of the implant at different angles, so that the surface roughness of the implant can be more comprehensively evaluated.

[0051] Further, the subperiosteal implant surface roughness detection device further comprises a first plano-convex lens and a second plano-convex lens.

[0052] The laser emits high-coherence light, performs beam collimation through the first plano-convex lens, performs beam convergence through the second plano-convex lens, and irradiates the subperiosteal implant.

[0053] The embodiment of the present application provides a subperiosteal implant surface roughness detection device, which realizes laser common-path interference by collimating and focusing a laser beam, improves the accuracy of measuring surface roughness and the definition of interference fringes, and can concentrate laser energy on a small area by focusing the beam, improve the resolution of measurement, ensure the accurate capture of surface micro undulations, and enhance the sensitivity of interference signals by focusing the beam, reduce scattering and noise, and help to obtain accurate roughness data. BRIEF DESCRIPTION OF DRAWINGS

[0054] Figure 1 A step flowchart diagram of a subperiosteal implant surface roughness detection method provided by an embodiment of the present application is provided.

[0055] Figure 2 An application structure diagram of a subperiosteal implant surface roughness detection device provided by an embodiment of the present application is provided.

[0056] Figure 3 A module structure diagram of a subperiosteal implant surface roughness detection device provided by an embodiment of the present application is provided.

[0057] Figure 4 An application structure diagram of a rotatable sample table of a subperiosteal implant surface roughness detection device provided by an embodiment of the present application is provided.

[0058] Figure 5 An application structure diagram of a support rod of a subperiosteal implant surface roughness detection device provided by an embodiment of the present application is provided. DETAILED DESCRIPTION

[0059] With reference to the accompanying drawings, the technical solutions in the embodiments of the present application will be clearly and completely described in the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all the other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0060] Embodiment 1

[0061] Referring to Figure 1 , Figure 1 A step flowchart of a detection method of a subperiosteal implant surface roughness provided by an embodiment of the present application is shown. It is worth mentioning that the present embodiment will be explained in combination with an application structure diagram of a detection device of a subperiosteal implant surface roughness as shown in Figure 2 The present application will not be described in detail hereinafter.

[0062] As shown in Figure 1 , an embodiment of the present application provides a detection method of a subperiosteal implant surface roughness, which comprises steps 101 to 104, and each step is specifically as follows:

[0063] Step 101: obtaining a light signal scattered by a surface of a subperiosteal implant to be measured and converting the light signal into a time-domain interference signal;

[0064] As an example of the present embodiment, based on the optical path difference and phase difference of the reflected light beams at different reflection positions, the light signal scattered by the surface of the subperiosteal implant to be measured is obtained; based on a preset photoelectric sensor, the light signal scattered by the surface of the subperiosteal implant to be measured is photoelectrically converted to obtain the time-domain interference signal.

[0065] The prior art has the problem of low accuracy of calculating the roughness of the surface of the subperiosteal implant to be measured due to the influence of factors such as sample shape. The embodiment of the present application provides a method for detecting the roughness of the surface of a subperiosteal implant. The optical signal obtained by optical detection technology can accurately capture the optical path difference and phase difference of different reflection points on the surface to be measured, and then extract the light signal scattered by the implant on the surface of the subperiosteal implant. The method breaks through the limitations of sample shape, surface curvature and surface uniformity, realizes comprehensive measurement of the entire surface, and provides reliable and accurate data support for subsequent electrical signal processing. In a specific implementation, the laser emitter 201 emits laser light to irradiate the surface of the subperiosteal implant 204 to be measured. The scattered light signal is captured by the scattered light receiving device 202. The scattered light receiving device 202 can use an electrical detector such as a CCD and a CMOS. The scattered light receiving device 202 can also convert the optical signal into an electrical signal to obtain a time-domain interference signal and transmit it to the data acquisition system 203. The photoelectric sensor captures the optical signal for photoelectric conversion, more accurately captures the weak light signal scattered by the surface of the subperiosteal implant to be measured, thereby improving the signal-to-noise ratio of the time-domain interference signal. The optical signal is then analyzed in the time domain to reduce signal distortion and error, thereby providing accurate data basis and improving the accuracy of calculating the roughness of the surface of the subperiosteal implant to be measured.

[0066] In step 102, the time-frequency conversion is performed on the time-domain interference signal based on a first preset algorithm to obtain a frequency-domain interference signal and phase information by calculating a phase spectrum of the frequency-domain interference signal.

[0067] As an example of the embodiment, the Fourier transform is performed on the time-domain interference signal based on the first preset algorithm to obtain the frequency-domain interference signal. The absolute value of the frequency-domain interference signal is calculated to obtain an amplitude spectrum of the frequency-domain interference signal. The phase spectrum of the frequency-domain interference signal is calculated by an inverse tangent function based on the amplitude spectrum of the frequency-domain interference signal to obtain the phase information.

[0068] The embodiment of the present application provides a method for detecting the roughness of the surface of a subperiosteal implant. The time-domain signal is converted to the frequency domain by performing a time-frequency conversion process. This step makes the distribution characteristics of the signal in the frequency dimension more clearly exhibited, and the phase information is separated. In a specific implementation, the Fourier transform method (FFT) is used to convert the time-domain interference signal to the frequency domain to separate the phase information. The specific steps are as follows:

[0069] S1.1 Obtain the time-domain interference signal.

[0070] The acquisition scattered light receiving device 202 captures and photoelectrically processes a time-domain interference signal, which is usually a time series signal, denoted as I(t), where I is the signal intensity and t is the time.

[0071] S1.2 Fourier transform is performed on the time-domain interference signal (equivalent to the first preset algorithm);

[0072] The time-domain interference signal is converted from the time domain to the frequency domain by Fourier transform (equivalent to the first preset algorithm), and the specific calculation formula is as follows:

[0073]

[0074] In the formula, is the frequency-domain interference signal, f is the frequency, and j is the imaginary unit;

[0075] S1.3 Extract the amplitude spectrum and the phase spectrum;

[0076] In the frequency domain, the frequency-domain interference signal and its amplitude information and phase information can be expressed as:

[0077]

[0078] Therefore, the amplitude spectrum is:

[0079]

[0080] The phase spectrum is:

[0081]

[0082] Then, the phase information is separated from the phase spectrum by an inverse tangent function, and specifically:

[0083]

[0084] In the formula, Im and Re represent the imaginary part and the real part of the frequency-domain signal, respectively.

[0085] By analyzing in the frequency domain, noise and interference signals can be effectively distinguished and removed, thereby significantly improving the accuracy of calculating the surface roughness of the subperiosteal implant to be measured.

[0086] Step 103, based on the second preset algorithm, phase unwrapping is performed on the phase information to obtain surface height information;

[0087] As an example of the embodiment, based on a second preset algorithm, a phase spectrum region corresponding to the to-be-processed phase information is acquired, and a unwrapping starting point is set; phase difference calculation is performed on pixels in a neighborhood of the unwrapping starting point, phase adjustment is performed on a phase with a deviation greater than a preset threshold, and a plurality of phase differences are obtained; based on the plurality of phase differences, a point with a smallest phase difference adjacent to a current pixel point is selected as a next tracking point, and a phase value is updated; based on the updated phase value, phase conversion is performed on the unwrapped phase difference, and surface height information is obtained. Specifically, the updated phase value is taken as a new unwrapping starting point, the phase spectrum region corresponding to the to-be-processed phase information is traversed until a phase change meets a preset unwrapping condition, and an unwrapped phase difference is obtained; the unwrapped phase difference is converted into surface height information through a phase conversion formula.

[0088] In view of the possible abrupt change (i.e., phase ambiguity) in the phase information, phase unwrapping processing is required, and the embodiment of the present application proposes a detection method for the surface roughness of a subperiosteal implant, which eliminates the ambiguity of the phase information by performing unwrapping processing on the phase information, and then restores the real phase distribution state. In a specific implementation manner, path tracking unwrapping (equivalent to the second preset algorithm) is used in the embodiment, and the specific steps are as follows:

[0089] S2.1 initialization of an unwrapping starting point;

[0090] A phase spectrum region to be processed is acquired, a starting point is selected as an unwrapping starting point in the phase spectrum region to be processed, the starting point can be selected as a point at the top left corner or other positions, and a phase value of the selected starting point is recorded.

[0091] S2.2 path tracking is performed;

[0092] The starting point is taken as a current point, the neighborhood pixels of the current point are selected and the phase values thereof are calculated, the neighborhood pixels can be selected as points in the up, down, left, right and diagonal directions, the phase difference between the current point and the neighborhood pixels is calculated, and the specific formula is as follows:

[0093]

[0094] In the formula, is a phase value of a neighborhood pixel, is a phase value of a current point;

[0095] If the calculated phase difference exceeds ±π, it indicates that the phase information has a jump, and the phase needs to be adjusted. The specific adjustment method can be: 2π is added or subtracted to correct the jump, so that the phase value is kept within the range of [-π, π].

[0096] S2.3 path updating is performed;

[0097] According to the phase difference and the change of the phase, a neighborhood point with the minimum phase difference from the current point is selected as the next tracking point, the new phase value of the tracking point is recorded, and the phase is adjusted as needed;

[0098] S2.4 Looping through the to-be-processed region;

[0099] Steps S2.2 and S2.3 are repeated until the entire to-be-processed phase spectrum region is traversed.

[0100] S2.5 Convergence detection and post-processing;

[0101] When the convergence condition of the unwrapping process is met, for example, the phase change is less than a certain threshold (equivalent to a preset unwrapping condition), it means that the unwrapping process is completed, and the unwrapping is ended. Then, the unwrapped phase is smoothed, and the unwrapped phase is converted into surface height information using the phase and height formula (equivalent to the phase conversion formula). The specific formula is as follows:

[0102]

[0103] In the formula, is the phase difference (unit: radian), λ is the wavelength of the laser (unit: meter), and Δh is the height change of the surface (unit: meter).

[0104] At this point, by selecting the tracking point and using the phase difference for calculation, the phase error can be effectively reduced, the noise interference on the final result can be weakened, and the accuracy of the data is improved.

[0105] Step 104, based on the surface height information, the surface roughness of the subperiosteal implant to be measured is obtained.

[0106] As an example of this embodiment, based on the surface height information, the total number of traversed measurement points and the height values of each measurement point are obtained; the arithmetic average roughness is calculated through the total number of traversed measurement points and the height values of each measurement point; and based on the arithmetic average roughness, the surface roughness of the subperiosteal implant to be measured is obtained.

[0107] The arithmetic average roughness directly calculated from the surface height information can accurately reflect the micro-geometric shape characteristics of the implant surface, such as ups and downs and peak and valley distribution, so as to realize accurate measurement of the surface roughness. In a specific implementation, the total number of measurement points and the height values of each measurement point are obtained, and the roughness parameters are calculated. The specific formula is as follows:

[0108]

[0109] In the formula, Ra is the arithmetic average roughness, h i is the height value of each measurement point, and N is the total number of measurement points.

[0110] Therefore, the calculated arithmetic average roughness Ra can be used as the surface roughness of the subperiosteal implant to be measured. It is worth mentioning that the non-contact measurement method of obtaining surface height information can reduce artificial errors such as scratches and deformations caused by contact between the measuring tool and the implant surface, and improve the accuracy and reliability of the measurement.

[0111] The embodiment of the present application provides a detection method for the surface roughness of a subperiosteal implant. The light signal scattered by the surface of the subperiosteal implant to be measured is obtained, and the method is not limited by the shape of the sample, the surface curvature and the uniformity of the sample surface. Then, the optical signal is converted into a time-domain interference signal, the time-domain interference signal contains a plurality of phase changes, and data basis for further analyzing the roughness of the surface of the subperiosteal implant to be measured is provided. Then, the time-domain interference signal is converted into a frequency-domain interference signal, and the phase information is separated. The separation of the phase information can reduce the interference of noise and improve the accuracy of the calculation of the roughness of the surface of the subperiosteal implant to be measured. Then, the phase information is further phase-unwrapped to obtain the surface height information and the roughness of the surface of the subperiosteal implant to be measured, the influence of phase ambiguity on the calculation result of the roughness of the surface of the subperiosteal implant to be measured is reduced, and the accuracy of the calculation of the roughness of the surface of the subperiosteal implant to be measured is improved.

[0112] Embodiment 2

[0113] Referring to Figure 3 , Figure 3 A module structure schematic diagram of a detection device for the surface roughness of a subperiosteal implant is provided in an embodiment of the present application. In the embodiment of the present application, the application structure schematic diagram of the detection device for the surface roughness of the subperiosteal implant is also explained as shown in Figure 2 The following will not be described in detail.

[0114] As shown in Figure 3 An embodiment of the present application provides a detection device for the surface roughness of a subperiosteal implant, which comprises a support frame 301, a laser emitter 201 and an optical processor 302.

[0115] The subperiosteal implant to be measured 204 is arranged on the support frame 301. The support frame 301 is adjusted to make the subperiosteal implant to be measured 204 assume different angle postures, so as to obtain the surface of the subperiosteal implant to be measured at different angles.

[0116] The laser emitter 201 emits a laser beam, and the laser beam irradiates the surface of the subperiosteal implant to be measured to generate a light signal scattered by the surface of the subperiosteal implant to be measured.

[0117] The optical processor 302 comprises a time-domain signal acquisition module 303, a time-frequency conversion module 304, a phase unwrapping module 305 and a roughness acquisition module 306.

[0118] The time-domain signal acquisition module 303 is configured to acquire the light signal scattered by the surface of the subperiosteal implant to be measured and convert it into a time-domain interference signal.

[0119] The time-frequency conversion module 304 is configured to perform time-frequency conversion on the time-domain interference signal based on a first preset algorithm, obtain a frequency-domain interference signal, and acquire phase information by calculating the phase spectrum of the frequency-domain interference signal.

[0120] The phase unwrapping module 305 is configured to perform phase unwrapping on the phase information based on a second preset algorithm to obtain surface height information.

[0121] The roughness acquisition module 306 is configured to acquire the surface roughness of the subperiosteal implant to be measured based on the surface height information.

[0122] In order to ensure a stable and tight connection between the support rod and the rotatable sample stage, the support rod and the rotatable sample stage are connected by using an interference fit technology, which effectively prevents measurement errors caused by looseness or gaps. As an example of this embodiment, see Figure 4 and Figure 5 , Figure 4 A rotatable sample stage application structure diagram of a subperiosteal implant surface roughness detection device according to an embodiment of the present application is shown in the figure. Figure 5 A support rod application structure diagram of a subperiosteal implant surface roughness detection device according to an embodiment of the present application is shown in the figure. The support frame 301 comprises a rotatable sample stage 205 and a support rod 206. The rotatable sample stage 205 is provided with a jawbone model, and the subperiosteal implant 204 to be measured is installed on the jawbone model. The bottom of the rotatable sample stage 205 is provided with a recess. One end of the support rod 206 is provided with a ball. The support rod 206 is provided with a base. The ball at one end of the support rod 206 is interference-fitted with the recess provided at the bottom of the rotatable sample stage 205. After the support rod 206 is connected to the rotatable sample stage 205, it can be rotated to multiple angles to produce different angles of the surface of the subperiosteal implant to be measured. This device uses a non-contact measurement method, has stronger adaptability, is not limited by the shape, surface curvature and surface uniformity of the sample, and thus ensures the accuracy and reliability of the detection results.

[0123] To further improve the accuracy of roughness measurement calculation, the shape of the rotatable sample table 205 can be changed to simulate a more realistic oral cavity structure. As an example of the present embodiment, the rotatable sample table 205 is set as a hemisphere, and the jawbone model is arranged on the spherical surface. In the present embodiment, the setting as a hemisphere can enable the subperiosteal implant to be measured to perfectly fit on the jawbone model, accurately simulate the real oral environment, and facilitate observation and detection of the implant from various angles, thereby achieving comprehensive and detailed evaluation of the surface roughness of the implant.

[0124] It is worth mentioning that when the laser is emitted, the angle of the rotatable sample table needs to be adjusted so that the surface to be measured is perpendicular to the incident light, which can ensure the accuracy of the laser common-path interferometry measurement of the surface roughness and the clarity of the interference fringes. To achieve laser common-path interference, a plano-convex lens is generally arranged for beam collimation and focusing. As an example of the present embodiment, a first plano-convex lens 307 and a second plano-convex lens 308 are arranged. The laser emits highly coherent light and is incident from the first plano-convex lens 307 for beam collimation, and is incident from the second plano-convex lens 308 for beam convergence, and is incident on the surface of the subperiosteal implant. By focusing the beam, the laser energy can be concentrated in a small area, improving the measurement resolution and ensuring accurate capture of the surface micro-undulations. At the same time, focusing the beam enhances the sensitivity of the interference signal, reduces scattering and noise, and helps to obtain accurate roughness data.

[0125] The present embodiment proposes a detection device for the surface roughness of a subperiosteal implant. The optical processor can accurately capture the phase information of the micro-undulations of the surface of the subperiosteal implant to be measured. On this basis, the laser beam emitted by the laser is incident on the surface of the subperiosteal implant to be measured on the support frame. Different angles of the surface of the subperiosteal implant to be measured are obtained by adjusting the support frame. The light signal scattered by the surface of the subperiosteal implant to be measured is obtained by the time-domain signal acquisition module, without being limited by the shape of the sample, the surface curvature, and the uniformity requirement of the sample surface. Then, the optical signal is converted into a time-domain interference signal, which contains multiple phase changes and provides a data basis for further analysis of the roughness of the surface of the subperiosteal implant to be measured. The time-domain interference signal is converted into a frequency-domain interference signal by the time-frequency conversion module, and the phase information is separated. The separation of the phase information can reduce the interference of noise and improve the accuracy of the roughness calculation of the surface of the subperiosteal implant to be measured. The surface height information is obtained by further phase unwrapping of the phase information by the phase unwrapping module, and the roughness of the surface of the subperiosteal implant to be measured is obtained by the roughness acquisition module. The influence of phase ambiguity on the calculation result of the roughness of the surface of the subperiosteal implant to be measured is reduced, and the accuracy of the roughness calculation of the surface of the subperiosteal implant to be measured is improved.

[0126] The above merely describes the preferred embodiments of the present application, and it should be pointed out that those skilled in the art can make several improvements and modifications without departing from the technical principles of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.

[0127] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. Moreover, the specific features, structures, materials or characteristics described can be combined in any suitable manner in any one or more embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the present specification and the features of the different embodiments or examples without contradiction.

[0128] In addition, the terms "first", "second" are only used for description purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the technical features indicated. Therefore, the features defined with "first", "second" can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise specifically limited.

Claims

1. A method for detecting the surface roughness of a subperiosteal implant, characterized in that, include: Acquire the light signal scattered from the surface of the subperiosteal implant under test and convert it into a time-domain interference signal; Based on the first preset algorithm, the time-domain interference signal is converted to a frequency-domain interference signal to obtain a frequency-domain interference signal. The phase information is obtained by calculating the phase spectrum of the frequency-domain interference signal. Based on the second preset algorithm, the phase information is unwrapped to obtain surface height information, including: based on the second preset algorithm, obtaining the phase spectrum region corresponding to the phase information to be processed, and setting the unwrapping starting point; obtaining the phase difference calculation of the neighboring pixels of the unwrapping starting point, adjusting the phase with a deviation greater than a preset threshold to obtain several phase differences; based on the several phase differences, selecting the point with the smallest phase difference adjacent to the current pixel as the next tracking point, and updating the phase value; based on the updated phase value, performing phase transformation on the unwrapped phase difference to obtain surface height information; The step of performing phase transformation on the unwrapped phase difference based on the updated phase value to obtain surface height information includes: using the updated phase value as a new unwrapping starting point, traversing the phase spectrum region corresponding to the phase information to be processed until the phase change meets the preset unwrapping condition to obtain the unwrapped phase difference; and converting the unwrapped phase difference into surface height information through a phase transformation formula. Based on the surface height information, the surface roughness of the subperiosteal implant to be tested is obtained.

2. The method for detecting the surface roughness of a subperiosteal implant as described in claim 1, characterized in that, The process of acquiring the light signal scattered from the surface of the subperiosteal implant under test and converting it into a time-domain interferometric signal includes: Based on the optical path difference and phase difference of the reflected beams at different reflection positions, the light signal scattered from the surface of the subperiosteal implant under test is obtained. Based on a preset photoelectric sensor, the light signal scattered from the surface of the subperiosteal implant under test is converted into a time-domain interference signal.

3. The method for detecting the surface roughness of a subperiosteal implant as described in claim 1, characterized in that, The step of performing time-frequency conversion on the time-domain interference signal based on the first preset algorithm to obtain a frequency-domain interference signal, and obtaining phase information by calculating the phase spectrum of the frequency-domain interference signal, includes: Based on the first preset algorithm, the time-domain interference signal is subjected to Fourier transform to obtain the frequency-domain interference signal; Calculate the absolute value of the frequency domain interference signal to obtain the amplitude spectrum of the frequency domain interference signal; Based on the amplitude spectrum of the frequency domain interference signal, the phase spectrum of the frequency domain interference signal is calculated using the arctangent function to obtain the phase information.

4. The method for detecting the surface roughness of a subperiosteal implant as described in claim 1, characterized in that, The step of obtaining the surface roughness of the subperiosteal implant based on the surface height information includes: Based on the surface height information, the total number of traversed measurement points and the height value of each measurement point are obtained; The arithmetic mean roughness is calculated by using the total number of measurement points traversed and the height value of each measurement point. The surface roughness of the subperiosteal implant under test is obtained based on the arithmetic mean roughness.

5. A device for detecting the surface roughness of a subperiosteal implant, characterized in that, Performing a method for detecting the surface roughness of a subperiosteal implant as described in any one of claims 1 to 4, comprising: Support frame, laser emitter, and optical processor; The subperiosteal implant to be tested is placed on the support frame. By adjusting the support frame, the subperiosteal implant to be tested is made to present different angles, so as to obtain the surface of the subperiosteal implant to be tested at different angles. The laser emitter emits a laser beam, which illuminates the surface of the subperiosteal implant to be tested, thereby generating a light signal scattered from the surface of the subperiosteal implant to be tested. The optical processor includes: a time-domain signal acquisition module, a time-frequency conversion module, a phase unwrapping module, and a roughness acquisition module; The time-domain signal acquisition module is used to acquire the light signal scattered from the surface of the subperiosteal implant under test and convert it into a time-domain interference signal. The time-frequency conversion module is used to perform time-frequency conversion on the time-domain interference signal based on a first preset algorithm to obtain a frequency-domain interference signal, and to obtain phase information by calculating the phase spectrum of the frequency-domain interference signal; The phase unwrapping module is used to unwrap the phase information based on a second preset algorithm to obtain surface height information. This includes: obtaining the phase spectrum region corresponding to the phase information to be processed based on the second preset algorithm, and setting an unwrapping starting point; obtaining the phase difference of neighboring pixels of the unwrapping starting point, adjusting phases with deviations greater than a preset threshold to obtain several phase differences; selecting the point with the smallest phase difference adjacent to the current pixel as the next tracking point based on the several phase differences, and updating the phase value; performing phase transformation on the unwrapped phase difference based on the updated phase value to obtain surface height information. The step of performing phase transformation on the unwrapped phase difference based on the updated phase value to obtain surface height information includes: using the updated phase value as a new unwrapping starting point, traversing the phase spectrum region corresponding to the phase information to be processed until the phase change meets the preset unwrapping condition to obtain the unwrapped phase difference; and converting the unwrapped phase difference into surface height information using a phase transformation formula. The roughness acquisition module is used to acquire the surface roughness of the subperiosteal implant to be tested based on the surface height information.

6. The device for detecting the surface roughness of a subperiosteal implant as described in claim 5, characterized in that, The support frame includes: a rotatable sample stage and a support rod; A jawbone model is set on the rotatable sample stage, and the subperiosteal implant to be tested is fitted onto the jawbone model. A concave hole is provided at the bottom of the rotatable sample stage. One end of the support rod is configured as a sphere; The ball at one end of the support rod is press-fitted with the recessed hole at the bottom of the rotatable sample stage. After the support rod is connected to the rotatable sample stage, it can be rotated to various angles to produce different angles of the subperiosteal implant surface to be tested.

7. The device for detecting the surface roughness of a subperiosteal implant as described in claim 6, characterized in that, The rotatable sample stage is configured as a hemisphere, and the jawbone model is set on the spherical surface.

8. The device for detecting the surface roughness of a subperiosteal implant as described in claim 7, characterized in that, Also includes: First plano-convex lens and second plano-convex lens; The laser emitter emits highly coherent light, which is collimated by the first plano-convex lens, converged by the second plano-convex lens, and then irradiates the surface of the subperiosteal implant.

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