Method and device for detecting surface roughness of subperiosteal implant

Abstract

The invention provides a method and a device for detecting the surface roughness of a subperiosteal implant. The method comprises the following steps: acquiring an optical signal scattered by the surface of a to-be-detected subperiosteal implant and converting the optical signal into a time domain interference signal; based on a first preset algorithm, performing time-frequency conversion on the time-domain interference signal to obtain a frequency-domain interference signal, and calculating a phase spectrum of the frequency-domain interference signal to obtain phase information; based on a second preset algorithm, performing phase unwrapping on the phase information to obtain surface height information; and acquiring the surface roughness of the subperiosteal implant to be measured based on the surface height information. The problems that in the prior art, a contact type surface detection method is difficult to measure the surface with the large curvature, and a local detection mode has the high requirement for uniformity of the large surface to be detected, so that the surface roughness detection result is inaccurate are solved. Overall surface scanning is achieved through optical detection, optical signal data processing is combined, and the accuracy of the surface roughness detection result is improved.

Description

Technical Field

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

[0002] 3D printed subperiosteal implants have the characteristic of fitting the surface of the jawbone. Their external morphology is a continuous curved surface consistent with the alveolar bone surface according to the different implant morphologies of each patient. The roughness of the subperiosteal implant is an important indicator of quality inspection. Since the upper and lower surfaces have different roughness requirements, it is necessary to conduct a comprehensive inspection of the roughness of the subperiosteal implant.

[0003] At present, the existing technology uses a contact measurement method to measure the local surface of the sample. Due to the limitation of the workpiece shape, the contact surface detection method is difficult to measure surfaces with large curvatures. The local detection method has high uniformity requirements for the large surface to be measured, resulting in inaccurate surface roughness detection results. Summary of the invention

[0004] In order to solve the above problems, the present invention proposes a method and device for detecting the surface roughness of a subperiosteal implant, which realizes overall surface scanning through optical detection and combines optical signal data processing to improve the accuracy of surface roughness detection results.

[0005] To achieve the above object, an embodiment of the present invention provides a method for detecting the surface roughness of a subperiosteal implant, comprising:

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

[0007] Based on a first preset algorithm, performing time-frequency conversion on the time-domain interference signal to obtain a frequency-domain interference signal, and obtaining phase information by calculating a phase spectrum of the frequency-domain interference signal;

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

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

[0010] An embodiment of the present invention proposes a method for detecting the surface roughness of a subperiosteal implant. The method obtains a light signal scattered by the surface of the subperiosteal implant to be tested, which is not limited by the sample shape, surface curvature and sample surface uniformity requirements. The optical signal is then converted into a time domain interference signal. The time domain interference signal contains multiple phase changes, which can provide a data basis for further analyzing the roughness of the surface of the subperiosteal implant to be tested. The time domain interference signal is then converted into a frequency domain interference signal to separate the phase information. By separating the phase information, the interference of noise can be reduced, and the accuracy of the roughness calculation of the surface of the subperiosteal implant to be tested can be improved. The surface height information is further obtained by phase unwrapping the phase information to obtain the surface roughness of the subperiosteal implant to be tested, thereby reducing the influence of phase ambiguity on the roughness calculation result of the subperiosteal implant surface to be tested, and improving the accuracy of the roughness calculation of the subperiosteal implant surface to be tested.

[0011] Furthermore, the step of acquiring the light signal scattered from the surface of the subperiosteal implant to be tested and converting it into a time domain interference signal includes:

[0012] 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 tested is obtained;

[0013] Based on a preset photoelectric sensor, the light signal scattered from the surface of the subperiosteal implant to be tested is photoelectrically converted to obtain a time domain interference signal.

[0014] Since the prior art is limited by factors such as sample shape, the problem of low accuracy in calculating the roughness of the surface of the subperiosteal implant to be tested arises. An embodiment of the present invention proposes a method for detecting the surface roughness of a subperiosteal implant. The optical signal obtained by optical detection can accurately obtain the optical path difference and phase difference of different reflection positions of the surface to be tested, thereby obtaining the light signal scattered by the surface of the subperiosteal implant to be tested. The light signal is no longer limited by the shape of the sample, the curvature of the sample surface, and the uniformity of the sample surface. The overall surface can be measured, providing an accurate data basis for subsequent electrical conversion processing. The optical signal is then captured by a photoelectric sensor for photoelectric conversion, and the weak light signal scattered by the surface of the subperiosteal implant to be tested is more accurately captured, 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 errors, thereby providing an accurate data basis and improving the accuracy of calculating the roughness of the surface of the subperiosteal implant to be tested.

[0015] Furthermore, based on the first preset algorithm, the time-domain interference signal is subjected to time-frequency conversion to obtain a frequency-domain interference signal and the phase information is obtained by calculating the phase spectrum of the frequency-domain interference signal, including:

[0016] Based on a first preset algorithm, Fourier transform is performed on the time domain interference signal to obtain a frequency domain interference signal;

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

[0018] Based on the amplitude spectrum of the frequency domain interference signal, the phase spectrum of the frequency domain interference signal is calculated by an inverse tangent function to obtain phase information.

[0019] An embodiment of the present invention proposes a method for detecting the surface roughness of a subperiosteal implant. The time domain signal is converted into a frequency domain signal by time-frequency conversion, so that the distribution characteristics of the signal in frequency can be more clearly obtained and the phase information can be separated. The noise and interference signals can also be effectively identified through frequency domain analysis, thereby improving the accuracy of the roughness calculation of the subperiosteal implant surface to be tested.

[0020] Furthermore, performing phase unwrapping on the phase information based on a second preset algorithm to obtain surface height information includes:

[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] Obtain the neighborhood pixels of the unwrapping starting point to calculate the phase difference, adjust the phase with a deviation greater than a preset threshold, and obtain a number of phase differences;

[0023] Based on the phase differences, a point with the smallest phase difference adjacent to the current pixel point is selected as the next tracking point, and the phase value is updated;

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

[0025] Further, the phase difference after unwrapping is phase converted based on the updated phase value to obtain surface height information, including:

[0026] Taking the updated phase value as a new unwrapping starting point, traverse the phase spectrum region corresponding to the phase information to be processed until the phase change meets the preset unwrapping condition, and obtain the unwrapped phase difference;

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

[0028] Since phase information may have jumps (phase ambiguity), phase unwrapping processing is required. An embodiment of the present invention proposes a method for detecting the surface roughness of subperiosteal implants. By performing phase unwrapping on the phase information, the ambiguity in the phase information can be eliminated, thereby restoring the true phase distribution. Selecting tracking points by phase difference can reduce phase errors, reduce the impact of noise on the results, and improve data accuracy.

[0029] Furthermore, obtaining the surface roughness of the subperiosteal implant to be tested based on the surface height information includes:

[0030] Based on the surface height information, obtaining the total number of traversed measurement points and the height value of each measurement point;

[0031] The arithmetic mean roughness is calculated by the total number of traversed measuring points and the height value of each measuring point;

[0032] Based on the arithmetic mean roughness, the surface roughness of the subperiosteal implant to be tested is obtained.

[0033] An embodiment of the present invention proposes a method for detecting the surface roughness of a subperiosteal implant. The arithmetic mean roughness directly calculated through the surface height information can accurately reflect the microscopic geometric shape characteristics of the implant surface, such as ups and downs and peak-to-valley distribution, thereby achieving accurate measurement of the surface roughness. In addition, the non-contact measurement method of obtaining surface height information can reduce human errors such as scratches and deformation caused by the contact between the measuring tool and the implant surface, thereby improving the accuracy and reliability of the measurement.

[0034] The embodiment of the present invention further provides a device for detecting the surface roughness of a subperiosteal implant, comprising:

[0035] Support frame, laser transmitter and optical processor;

[0036] The subperiosteal implant to be tested is arranged on the support frame, and the subperiosteal implant to be tested is made to present postures at different angles by adjusting the support frame, so as to obtain the surface of the subperiosteal implant to be tested at different angles;

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

[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 tested 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 to obtain a frequency-domain interference signal and obtain 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 used to acquire the surface roughness of the subperiosteal implant to be tested based on the surface height information.

[0043] The embodiment of the present invention proposes a detection device for the surface roughness of a subperiosteal implant. The optical processor can accurately capture the microscopic undulation phase information of the surface of the subperiosteal implant to be tested. On this basis, the laser beam emitted by the laser is irradiated on the surface of the subperiosteal implant to be tested of the support frame, and the surface of the subperiosteal implant to be tested at different angles is obtained by adjusting the support frame. Then, the light signal scattered by the surface of the subperiosteal implant to be tested is obtained by a time domain signal acquisition module, which is not limited by the sample shape, surface curvature and sample surface uniformity requirements. Then, the optical signal is converted into a time domain interference signal. The time domain interference signal contains a variety of phase changes and can be used for Further analysis is performed on the roughness of the surface of the subperiosteal implant to be tested to provide a data basis, and then the time domain interference signal is converted into a frequency domain interference signal through the time-frequency conversion module to separate the phase information. By separating the phase information, the interference of noise can be reduced, and the accuracy of the roughness calculation of the surface of the subperiosteal implant to be tested is improved. The phase information is further unwrapped by the phase unwrapping module to obtain the surface height information, and then the surface roughness of the subperiosteal implant to be tested is obtained through the roughness acquisition module, thereby reducing the influence of phase ambiguity on the roughness calculation result of the subperiosteal implant surface to be tested, and improving the accuracy of the roughness calculation of the subperiosteal implant surface to be tested.

[0044] Furthermore, the support frame comprises: a rotatable sample stage and a support rod;

[0045] The rotatable sample stage is provided with a jaw model, the subperiosteal implant to be tested is fitted and installed on the jaw model, and a concave hole is provided at the bottom of the rotatable sample stage;

[0046] One end of the support rod is configured as a sphere;

[0047] The sphere at one end of the support rod is interference-fitted with the concave hole provided 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 generate different angles of the subperiosteal implant surface to be tested.

[0048] An embodiment of the present invention proposes a device for detecting the surface roughness of a subperiosteal implant. The support rod and the rotatable sample stage adopt an interference fit to ensure a tight connection between the sample stage and the support rod, thereby avoiding measurement errors caused by looseness or gaps. Through a non-contact measurement method, the device has stronger adaptability and is not limited by the shape of the sample, the curvature of the sample surface, and the uniformity requirements of the sample surface, thereby ensuring the accuracy and reliability of the detection results.

[0049] Furthermore, the rotatable sample stage is arranged as a hemisphere, and the jaw model is arranged on the spherical surface.

[0050] An embodiment of the present invention proposes a device for detecting the surface roughness of a subperiosteal implant, in which a rotatable sample table is arranged as a hemisphere. This design enables the subperiosteal implant to be tested to be fitted onto a jaw model, simulating a real oral environment. The shape of the hemisphere facilitates observation and detection of the implant at different angles, thereby more comprehensively evaluating its surface roughness.

[0051] Furthermore, the device for detecting the surface roughness of a subperiosteal implant further comprises: a first plano-convex lens and a second plano-convex lens;

[0052] The laser emits high-coherence light and is incident from the first plano-convex lens for beam collimation, and is converged by the second plano-convex lens for beam convergence, and is irradiated onto the subperiosteal implant.

[0053] An embodiment of the present invention proposes a device for detecting the surface roughness of a subperiosteal implant. By collimating and focusing the laser beam, laser common-path interference is achieved to improve the accuracy of measuring surface roughness and the clarity of interference fringes. By focusing the light beam, the laser energy can be concentrated into a small area, thereby improving the measurement resolution and ensuring accurate capture of tiny surface fluctuations. At the same time, the focused light beam enhances the sensitivity of the interference signal, reduces scattering and noise, and helps to obtain accurate roughness data. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 A schematic flow chart of the steps of a method for detecting the surface roughness of a subperiosteal implant provided in one embodiment of the present invention;

[0055] Figure 2 A schematic diagram of the application structure of a device for detecting the surface roughness of a subperiosteal implant provided by a certain embodiment of the present invention;

[0056] Figure 3 A schematic diagram of the module structure of a device for detecting the surface roughness of a subperiosteal implant provided by an embodiment of the present invention;

[0057] Figure 4 A schematic diagram of the application structure of a rotatable sample stage of a device for detecting the surface roughness of a subperiosteal implant provided by a certain embodiment of the present invention;

[0058] Figure 5 A schematic diagram of the support rod application structure of a device for detecting the surface roughness of a subperiosteal implant provided in one embodiment of the present invention. DETAILED DESCRIPTION

[0059] 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.

[0060] Example 1

[0061] See also Figure 1 , Figure 1 The following is a schematic flow chart of the steps of a method for detecting the surface roughness of a subperiosteal implant provided in an embodiment of the present invention. It is worth mentioning that in this embodiment, the following Figure 2 The application structure diagram of a subperiosteal implant surface roughness detection device is explained below and will not be repeated.

[0062] like Figure 1 As shown, the embodiment of the present invention provides a method for detecting the surface roughness of a subperiosteal implant, including steps 101 to 104, each of which is specifically as follows:

[0063] Step 101, obtaining a light signal scattered from the surface of the subperiosteal implant to be tested and converting it into a time domain interference signal;

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

[0065] At present, the existing technology is limited by factors such as sample shape, resulting in a problem that the calculation accuracy of the roughness of the surface of the subperiosteal implant to be tested is not high. An embodiment of the present invention proposes a method for detecting the surface roughness 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 tested, and then extract the light signal scattered by the implant on the subperiosteal surface, breaking through the limitations of sample shape, surface curvature and surface uniformity, and realizing comprehensive measurement of the entire surface, providing reliable and accurate data support for subsequent electrical signal processing. In a specific embodiment, a laser transmitter 201 emits a laser to irradiate the surface of the subperiosteal implant 204 to be tested, and the scattered light signal is captured by a scattered light receiving device 202, wherein the scattered light receiving device 202 can use an electrical detector (such as CCD and CMOS), and the scattered light receiving device 202 can also convert the light signal into an electrical signal to obtain a time domain interference signal, and transmit it to the data acquisition system 203. By capturing optical signals through photoelectric sensors for photoelectric conversion, the weak light signals scattered by the surface of the subperiosteal implant to be tested can be captured more accurately, 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 errors, thereby providing an accurate data basis and improving the accuracy of the roughness calculation of the subperiosteal implant surface to be tested.

[0066] Step 102: Based on a first preset algorithm, perform time-frequency conversion on the time-domain interference signal to obtain a frequency-domain interference signal, and obtain phase information by calculating a phase spectrum of the frequency-domain interference signal;

[0067] As an example of this embodiment, based on the first preset algorithm, the time domain interference signal is Fourier transformed to obtain a frequency domain interference signal; the absolute value of the frequency domain interference signal is calculated 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 by the inverse tangent function to obtain the phase information.

[0068] The embodiment of the present invention proposes a method for detecting the surface roughness of a subperiosteal implant. By performing a time-frequency conversion process, a signal originally in the time domain is transformed into the frequency domain. This step enables the distribution characteristics of the signal in the frequency dimension to be more clearly displayed, and the phase information is separated. A specific implementation method uses the Fourier transform method (FFT) to transform the time domain interference signal into the frequency domain to separate the phase information. The specific steps are as follows:

[0069] S1.1 obtain time domain interference signal;

[0070] The time domain interference signal captured and photoelectrically processed by the scattered light receiving device 202 is obtained. The time domain interference signal is usually a time series signal, expressed as I(t), where I is the signal intensity and t is time.

[0071] S1.2 performing Fourier transform 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 through Fourier transform (equivalent to the first preset algorithm). 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 amplitude spectrum and 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] From this we can get the amplitude spectrum:

[0079]

[0080] Phase spectrum:

[0081]

[0082] Then, the phase information is separated from the phase spectrum through the inverse tangent function. Specifically:

[0083]

[0084] Where Im and Re represent the imaginary and real parts of the frequency domain signal respectively.

[0085] Therefore, by analyzing in the frequency domain, noise and interference signals can be effectively identified and eliminated, thereby significantly improving the accuracy of the calculation of the surface roughness of the subperiosteal implant to be tested.

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

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

[0088] In view of the possible mutation phenomenon (i.e., phase ambiguity) in the phase information, phase unwrapping processing is required. The embodiment of the present invention proposes a method for detecting the surface roughness of a subperiosteal implant. By unwrapping the phase information, the ambiguity of the phase information is eliminated, and the true phase distribution state is restored. A specific implementation method is to use path tracking unwrapping (equivalent to the second preset algorithm) in this embodiment. The specific steps are as follows:

[0089] S2.1 Initialize the disentanglement starting point;

[0090] Obtain the phase spectrum region to be processed, select a starting point in the phase spectrum region to be processed as the unwrapping starting point, and the starting point may be a point in the upper left corner or other positions; record the phase value of the selected starting point;

[0091] S2.2 performs path tracking;

[0092] Taking the starting point as the current point, select the neighboring pixels of the current point and calculate their phase values. The neighboring pixels can be selected such as: up, down, left, right and diagonal points, and calculate the phase difference between the current point and the neighboring pixels. The specific formula is as follows:

[0093]

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

[0095] If the calculated phase difference If it exceeds ±π, it means that there is a jump in the phase information and the phase needs to be adjusted. The specific adjustment method can be: correct the jump by adding or subtracting 2π to keep the phase value within the range of [-π,π].

[0096] S2.3 performs path update;

[0097] According to the phase difference and phase change, select the neighboring point with the smallest phase difference with the current point as the next tracking point, record the new phase value of the tracking point, and adjust the phase as needed;

[0098] S2.4 loops through the area to be processed;

[0099] Repeat steps S2.2 and S2.3 until the entire phase spectrum region to be processed 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 the preset unwrapping condition), the unwrapping process is completed and the unwrapping ends; then the unwrapped phase is smoothed, and the phase and height formula (equivalent to the phase conversion formula) is used to convert the unwrapped phase into surface height information. The specific formula is as follows:

[0102]

[0103] In the formula, is the phase difference (in radians), λ is the laser wavelength (in meters), and Δh is the height change of the surface (in meters).

[0104] At this point, by selecting tracking points and using phase differences for calculations, the phase error can be effectively reduced, and the interference of noise on the final result can be weakened, thereby improving the accuracy of the data.

[0105] Step 104: based on the surface height information, obtain the surface roughness of the subperiosteal implant to be tested.

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

[0107] The arithmetic mean roughness directly calculated from the surface height information can accurately reflect the microscopic geometric shape characteristics of the implant surface, such as ups and downs and peak-to-valley distribution, so as to achieve accurate measurement of the surface roughness. A specific implementation method is to obtain the total number of measurement points and the height value of each measurement point, and calculate the roughness parameter. The specific formula is as follows:

[0108]

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

[0110] Therefore, the calculated arithmetic mean 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 that obtains surface height information can reduce human errors such as scratches and deformation caused by the contact between the measuring tool and the implant surface, thereby improving the accuracy and reliability of the measurement.

[0111] An embodiment of the present invention proposes a method for detecting the surface roughness of a subperiosteal implant. The method obtains a light signal scattered by the surface of the subperiosteal implant to be tested, which is not limited by the sample shape, surface curvature and sample surface uniformity requirements. The optical signal is then converted into a time domain interference signal. The time domain interference signal contains multiple phase changes, which can provide a data basis for further analyzing the roughness of the surface of the subperiosteal implant to be tested. The time domain interference signal is then converted into a frequency domain interference signal to separate the phase information. By separating the phase information, the interference of noise can be reduced, and the accuracy of the roughness calculation of the surface of the subperiosteal implant to be tested can be improved. The surface height information is further obtained by phase unwrapping the phase information to obtain the surface roughness of the subperiosteal implant to be tested, thereby reducing the influence of phase ambiguity on the roughness calculation result of the subperiosteal implant surface to be tested, and improving the accuracy of the roughness calculation of the subperiosteal implant surface to be tested.

[0112] Example 2

[0113] See also Figure 3 , Figure 3 A schematic diagram of the module structure of a device for detecting the surface roughness of a subperiosteal implant provided in an embodiment of the present invention. Figure 2 The application structure diagram of a subperiosteal implant surface roughness detection device is explained below and will not be repeated.

[0114] like Figure 3 As shown, the embodiment of the present invention provides a device for detecting the surface roughness of a subperiosteal implant, comprising: a support frame 301, a laser transmitter 201 and an optical processor 302;

[0115] The subperiosteal implant 204 to be tested is arranged on the support frame 301, and the subperiosteal implant 204 to be tested is made to present postures at different angles by adjusting the support frame 301, so as to obtain the surface of the subperiosteal implant to be tested at different angles;

[0116] The laser emitter 201 emits a laser beam, and the laser beam is irradiated on the surface of the subperiosteal implant to be tested to generate a light signal scattered by the surface of the subperiosteal implant to be tested;

[0117] The optical processor 302 includes: 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 used to acquire the light signal scattered by the surface of the subperiosteal implant to be tested and convert it into a time domain interference signal;

[0119] The time-frequency conversion module 304 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 obtain phase information by calculating the phase spectrum of the frequency-domain interference signal;

[0120] The phase unwrapping module 305 is used 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 used to acquire the surface roughness of the subperiosteal implant to be tested 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 adopt an interference fit technology to effectively prevent measurement errors that may be caused by looseness or gaps. As an example of this embodiment, see Figure 4 and Figure 5 , Figure 4 A schematic diagram of the application structure of a rotatable sample stage of a device for detecting the surface roughness of a subperiosteal implant provided by a certain embodiment of the present invention; Figure 5 A schematic diagram of the support rod application structure of a device for detecting the surface roughness of a subperiosteal implant provided in a certain embodiment of the present invention. The support frame 301 includes: a rotatable sample stage 205 and a support rod 206; a jaw model is arranged on the rotatable sample stage 205, and the subperiosteal implant 204 to be tested is fitted and installed on the jaw model, and a concave hole is arranged at the bottom of the rotatable sample stage 205; one end of the support rod 206 is arranged as a sphere; the support rod 206 is provided with a base; the sphere at one end of the support rod 206 is interference-fitted with the concave hole arranged at the bottom of the rotatable sample stage 205, and the support rod 206 can be rotated to a variety of angles after being connected to the rotatable sample stage 205 to produce the subperiosteal implant surface to be tested at different angles. The device adopts a non-contact measurement method, has stronger adaptability, is not limited by the sample shape, surface curvature and surface uniformity, thereby ensuring the accuracy and reliability of the detection results.

[0123] In order to further improve the accuracy of roughness measurement calculation, the shape of the rotatable sample stage 205 can be changed to simulate a more realistic oral structure. As an example of this embodiment, the rotatable sample stage 205 is set as a hemisphere, and the jawbone model is set on a spherical surface. In this embodiment, the hemisphere can make the subperiosteal implant to be tested fit perfectly on the jawbone model, accurately simulating the real oral environment. The structure of the hemisphere also facilitates observation and detection of the implant from various angles, thereby achieving a comprehensive and detailed evaluation of the implant surface roughness.

[0124] It is worth mentioning that when the laser is emitted, the angle of the rotatable sample stage needs to be adjusted so that the incident light is perpendicular to the surface to be measured, so as to ensure the accuracy of the surface roughness measurement by the laser common-path interference method and the clarity of the interference fringes. In order to achieve laser common-path interference, a plano-convex lens is generally provided for beam collimation and focusing. As an example of this embodiment, a first plano-convex lens 307 and a second plano-convex lens 308 are provided; the laser emits high-coherence light and is incident from the first plano-convex lens 307 for beam collimation, and the beam is converged through the second plano-convex lens 308 and irradiated on the surface of the subperiosteal implant. By focusing the beam, the laser energy can be concentrated into a small area, the resolution of the measurement is improved, and the accurate capture of the small fluctuations of the surface is ensured. At the same time, the focused beam enhances the sensitivity of the interference signal, reduces scattering and noise, and helps to obtain accurate roughness data.

[0125] The embodiment of the present invention proposes a detection device for the surface roughness of a subperiosteal implant. The optical processor can accurately capture the microscopic undulation phase information of the surface of the subperiosteal implant to be tested. On this basis, the laser beam emitted by the laser is irradiated on the surface of the subperiosteal implant to be tested of the support frame, and the surface of the subperiosteal implant to be tested at different angles is obtained by adjusting the support frame. Then, the light signal scattered by the surface of the subperiosteal implant to be tested is obtained by a time domain signal acquisition module, which is not limited by the sample shape, surface curvature and sample surface uniformity requirements. Then, the optical signal is converted into a time domain interference signal. The time domain interference signal contains a variety of phase changes and can be used for Further analysis is performed on the roughness of the surface of the subperiosteal implant to be tested to provide a data basis, and then the time domain interference signal is converted into a frequency domain interference signal through the time-frequency conversion module to separate the phase information. By separating the phase information, the interference of noise can be reduced, and the accuracy of the roughness calculation of the surface of the subperiosteal implant to be tested is improved. The phase information is further unwrapped by the phase unwrapping module to obtain the surface height information, and then the surface roughness of the subperiosteal implant to be tested is obtained through the roughness acquisition module, thereby reducing the influence of phase ambiguity on the roughness calculation result of the subperiosteal implant surface to be tested, and improving the accuracy of the roughness calculation of the subperiosteal implant surface to be tested.

[0126] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

[0127] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" means that the specific features, structures, materials or characteristics described in conjunction 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 may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

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

Claims

1. A method for detecting the surface roughness of a subperiosteal implant, characterized in that: include: Obtaining the light signal scattered from the surface of the subperiosteal implant to be tested and converting it into a time domain interference signal; Based on a first preset algorithm, performing time-frequency conversion on the time-domain interference signal to obtain a frequency-domain interference signal, and obtaining phase information by calculating a phase spectrum of the frequency-domain interference signal; Based on a second preset algorithm, phase unwrapping is performed on the phase information to obtain surface height information; Based on the surface height information, the surface roughness of the subperiosteal implant to be tested is obtained.

2. A method for detecting the surface roughness of a subperiosteal implant as claimed in claim 1, characterized in that: The method of obtaining the light signal scattered by the surface of the subperiosteal implant to be tested and converting it into a time domain interference signal comprises: 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 tested is obtained; Based on a preset photoelectric sensor, the light signal scattered from the surface of the subperiosteal implant to be tested is photoelectrically converted to obtain a time domain interference signal.

3. A method for detecting the surface roughness of a subperiosteal implant as claimed in claim 1, characterized in that: The method 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 a first preset algorithm, Fourier transform is performed on the time domain interference signal to obtain a frequency domain interference signal; Calculating 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 by an inverse tangent function to obtain phase information.

4. A method for detecting the surface roughness of a subperiosteal implant as claimed in claim 1, characterized in that: The performing phase unwrapping on the phase information based on the second preset algorithm to obtain surface height information includes: 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; Obtain the neighborhood pixels of the unwrapping starting point to calculate the phase difference, adjust the phase with a deviation greater than a preset threshold, and obtain a number of phase differences; Based on the phase differences, a point with the smallest phase difference adjacent to the current pixel point is selected as the next tracking point, and the phase value is updated; Based on the updated phase value, the unwrapped phase difference is phase-converted to obtain the surface height information.

5. A method for detecting the surface roughness of a subperiosteal implant as claimed in claim 4, characterized in that: The step of performing phase conversion on the unwrapped phase difference based on the updated phase value to obtain surface height information includes: Taking the updated phase value as a new unwrapping starting point, traverse the phase spectrum region corresponding to the phase information to be processed until the phase change meets the preset unwrapping condition, and obtain the unwrapped phase difference; The unwrapped phase difference is converted into surface height information through the phase conversion formula.

6. A method for detecting the surface roughness of a subperiosteal implant as claimed in claim 5, characterized in that: The step of obtaining the surface roughness of the subperiosteal implant to be tested based on the surface height information includes: Based on the surface height information, obtaining the total number of traversed measurement points and the height value of each measurement point; The arithmetic mean roughness is calculated by the total number of traversed measuring points and the height value of each measuring point; Based on the arithmetic mean roughness, the surface roughness of the subperiosteal implant to be tested is obtained.

7. A device for detecting the surface roughness of a subperiosteal implant, characterized in that: The method for detecting the surface roughness of a subperiosteal implant according to any one of claims 1 to 6 comprises: Support frame, laser transmitter and optical processor; The subperiosteal implant to be tested is arranged on the support frame, and the subperiosteal implant to be tested is made to present postures at different angles by adjusting the support frame, so as to obtain the surface of the subperiosteal implant to be tested at different angles; The laser transmitter emits a laser beam, and the laser beam is irradiated on the surface of the subperiosteal implant to be tested to generate a light signal scattered by the surface of the subperiosteal implant to be tested; The optical processor comprises: 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 by the surface of the subperiosteal implant to be tested 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 obtain phase information by calculating the phase spectrum of the frequency-domain interference signal; 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; The roughness acquisition module is used to acquire the surface roughness of the subperiosteal implant to be tested based on the surface height information.

8. A device for detecting the surface roughness of a subperiosteal implant as claimed in claim 7, characterized in that: The support frame comprises: a rotatable sample stage and a support rod; The rotatable sample stage is provided with a jaw model, the subperiosteal implant to be tested is fitted and installed on the jaw model, and 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 sphere at one end of the support rod is interference-fitted with the concave hole provided 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 generate different angles of the subperiosteal implant surface to be tested.

9. A device for detecting the surface roughness of a subperiosteal implant as claimed in claim 8, characterized in that: The rotatable sample stage is arranged as a hemisphere, and the jawbone model is arranged on a spherical surface.

10. The device for detecting the surface roughness of a subperiosteal implant according to claim 9, characterized in that: Also includes: a first plano-convex lens and a second plano-convex lens; The laser emits high-coherence light and is incident from the first plano-convex lens for beam collimation, and is converged by the second plano-convex lens for beam convergence, and is irradiated on the surface of the implant under the periosteum.

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