1891 results about "Tooth surface" patented technology

The invention provides a wind generating set fault monitoring method and system based on voiceprint recognition, and the method comprises the steps: collecting gear box voiceprint signal data in real time, recording signal fluctuation caused by gear surface wear, and obtaining an original signal data set containing a frequency spectrum high-frequency component enhancement feature; a time-frequency analysis method is adopted for the original signal data set, non-linear interference of vibration signals is recognized, multi-scale decomposition is carried out, initial wear frequency spectrum narrow-band characteristics and medium-term harmonic components are separated out, and a frequency spectrum component set is obtained; extracting characteristic parameters related to modulation depth abnormal fluctuation from the frequency spectrum component set, identifying a gear pair meshing frequency change rule, and determining a distribution mode of a tooth surface contact noise proportion; and if the feature matching result shows that the deviation between the spectrum high-frequency component diffusion distortion feature and the reference feature library exceeds a threshold value, adding the tooth surface fatigue crack noise feature into the feature library to obtain a target feature library.

The invention discloses a gear three-dimensional structure construction method, system and device and a medium, and the method comprises the steps: obtaining at least two groups of regional point cloud data of a to-be-detected gear and gear rotation angles corresponding to the regional point cloud data; the regional point cloud data is obtained by scanning through a laser scanner based on a multi-axis rotary clamping mechanism adjusting gear rotation angles, and the gear rotation angles corresponding to any two groups of regional point cloud data are different; calculating a rotation center axis of the gear to be measured according to the point cloud data of all areas; registering every two adjacent groups of regional point cloud data based on the rotation center axis and the gear rotation angle corresponding to the regional point cloud data to obtain registered regional point cloud data; and constructing a pose map structure of the to-be-detected gear based on the registered regional point cloud data to obtain a three-dimensional structure of the to-be-detected gear, so that a helical tooth surface with a complex curved surface can be comprehensively scanned, and non-contact, efficient and high-precision detection of the gear is realized.

The invention relates to the technical field of numerical control machining monitoring, in particular to a tooth deviation high-precision monitoring system in a tooth cutting machining process, which comprises an online measurement module, a dynamic compensation module, a deviation calculation module and a result output module which are in signal connection with a numerical control system of a tooth cutting machine tool, the online measurement module, the dynamic compensation module, the deviation calculation module and the result output module are integrated on the processing element; the processing element is used for obtaining workpiece design parameters and constructing a theoretical workpiece model, the online measurement module is used for collecting tooth surface point cloud data in real time in the machining process, the dynamic compensation module is used for correcting vibration errors and temperature errors of the point cloud data, and the deviation calculation module is used for quantifying tooth surface deviation values. And the result output module is used for generating an early warning signal and a dynamic correction instruction and executing system self-calibration. The device and a numerical control system form a closed loop of machining, monitoring, correction and remachining, and finally high-precision real-time monitoring and dynamic correction of tooth deviation are achieved.

The invention provides a tooth surface defect detection method and system for a precision gear. The method comprises the following steps: acquiring an original image sequence covering the whole circumferential direction of a tooth surface of the precision gear; preprocessing the original image sequence to generate a defect candidate region set; inputting a gear image with a fixed size in each region in the defect candidate region set into a deep neural network, and determining a preliminary detection result of the tooth surface of the precision gear; performing joint constraint regression between the predicted coordinates of the defect bounding box in the preliminary detection result and the coordinates of the corresponding true value box, and generating a regression correction bounding box set corresponding to the preliminary detection result; and judging the defect type of the tooth surface of the precision gear according to the spatial position information of the regression correction bounding box set and the corresponding category label. By establishing the index relationship between the image sequence and the gear rotation angle, image acquisition and accurate tooth position matching are realized, and the defect detection precision is effectively improved through cooperation of the deep neural network and the regression correction mechanism.

The invention discloses a data processing method and system for a dental three-dimensional model, and relates to the technical field of dental three-dimensional modeling, and the method comprises the steps: obtaining initial data of oral cavity scanning, recognizing a tooth type in the initial data, and determining a corresponding tooth surface reflection parameter according to the tooth type; generating scanning parameter combinations for different tooth positions according to the tooth surface reflection parameters and the tooth anatomical structure; tooth point cloud data are collected, and a tooth enamel reflective area and a shadow shielding area are identified; performing light reflection removal processing on the enamel light reflection area, performing data completion on the shadow shielding area, and generating corrected tooth point cloud data; and performing registration fusion on the corrected tooth point cloud data to generate a dental three-dimensional model containing a complete dentition. According to the method, the problem of data missing caused by enamel light reflection and adjacent tooth shielding is solved through a differential scanning strategy and regional data processing aiming at specific optical characteristics of teeth, and automatic construction of a high-quality dental three-dimensional model is realized.

The invention provides an intelligent toothbrush based on AI visual identification and an oral health assessment method, and relates to the technical field of artificial intelligence and computer vision. The intelligent toothbrush based on AI visual identification and the oral health assessment method comprise the following steps: S1, based on a built-in multispectral camera of the intelligent toothbrush, dynamically adjusting illumination parameters of different oral regions by adopting a visible light and near-infrared bimodal synchronous acquisition algorithm and through a self-adaptive exposure compensation technology, high-resolution images and transmission data of tooth surfaces and gingival lines are obtained, and a multi-mode oral cavity image data set is generated. Illumination parameters are dynamically adjusted through a multispectral camera to obtain high-resolution bimodal data, the focus detection precision is improved in combination with cross-modal feature fusion, the problem that traditional single-modal imaging is insufficient in early-stage dental caries recognition is solved, and the accuracy of early-stage dental caries recognition is improved based on laser radar point cloud complementation and a three-dimensional surface reconstruction technology. And mapping the two-dimensional focus label into a dynamic three-dimensional plaque distribution model.

The invention relates to the technical field of computers, discloses a tooth three-dimensional precision correction method and system based on multi-source oral data fusion, and aims to solve the problems of low registration precision, serious geometric distortion and lack of function oriented optimization of multi-modal oral data in the prior art. The method comprises the following steps: synchronously obtaining intraoral scanning, CBCT and face three-dimensional point cloud data; carrying out format conversion, denoising and grid simplification preprocessing; tooth surface morphology, root canal anatomy and soft tissue contour features are extracted and coded into uniform feature tensors; and multi-modal data space alignment is realized through staged rigid and non-rigid registration. By means of the scheme, the multi-source data fusion precision and the tooth form restoration accuracy are remarkably improved, full-process automatic efficient processing is achieved, and the clinical real-time performance and high-precision diagnosis and treatment requirements are met.

The invention discloses a tooth profile grinding wheel thermal drift modeling and wear life prediction method and system. The method comprises the four stages of thermal drift path network construction, drift differentiation feature extraction, irregular fragmentation recombination and dynamic judgment feedback. A tooth surface multi-region temperature response sequence is collected, a thermal drift path network is established, and a drift differentiation feature set is generated by using a multi-period path evolution relationship so as to distinguish short-period thermal disturbance and trend drift interference; and irregular recombination and energy constraint optimization are carried out on the path based on the thermal response structure boundary to form a response structure unit with thermal-force coupling association. The system further achieves judgment sequence self-learning according to an energy feedback and weight updating mechanism, and therefore the abrasion state and remaining life prediction result of the tooth profile grinding wheel is output. According to the method, dynamic correction of grinding thermal response behaviors and intelligent life evaluation are achieved.

The invention discloses an intelligent eye control bonding system and method for an orthodontic appliance, and relates to the technical field of intelligent oral medical equipment. Comprising a pupil eye-control image positioning module, a bracket initial coordinate is generated through doctor pupil trajectory tracking and doctor head dynamic compensation, a patient three-dimensional oral cavity model is combined for mapping, a three-dimensional visual interface is constructed by integrating oral scanning instrument and cone beam CT data, and the three-dimensional visual interface is projected to an entity tooth surface through a laser positioning projection device. And the dynamic tracking module corrects the posture of the bracket in real time through rigid compensation and elastic compensation based on inertial sensing data. The path planning and control module adopts an improved RRT *-Connect algorithm, and an elastic map and an impedance-admittance hybrid control strategy are fused to optimize a motion path. And the mechanical arm execution module adopts a modular six-axis framework, integrates a triple-combination driving system and a double-cavity end effector, and completes submillimeter-level bonding operation in an oral cavity limited space. The positioning precision and the bonding efficiency of the bracket are improved.

The invention discloses an artificial intelligence-based periodontal state evaluation method, which comprises the following steps of: acquiring multi-modal tooth data which comprises a tooth surface image and a local blood vessel network image of an oral cavity; preprocessing the multi-modal tooth data, and performing cross-modal registration by using a registration module to obtain a registered tooth surface image and a registered blood vessel network image; extracting multi-dimensional features of the registered blood vessel network image through a first feature extraction module, wherein the multi-dimensional features comprise spatial morphological features, topological connectivity features and hemodynamic features of blood vessels; extracting macroscopic morphological features and lesion local features of the registered tooth surface image through a second feature extraction module; performing cross-modal fusion on the multi-dimensional features, the macroscopic morphological features, the local lesion features and the clinical data to obtain fusion features; and outputting a periodontal state evaluation result based on the fusion features, thereby facilitating improvement of periodontal state evaluation accuracy and periodontal disease early warning capability.

The present invention discloses an orthodontic appliance and a manufacturing method thereof. The orthodontic appliance includes: a fixing member and an orthodontic wire; the fixing member is used to be fixed on the tooth surface, and the orthodontic wire has a plurality of curved structures for releasing orthodontic force. The orthodontic wire is an elastic member with elasticity, and the orthodontic wire and the fixing member are detachably buckled and connected. This appliance can accurately control the amount of tooth movement, precisely quantify the acting force applied to the local and overall teeth; greatly save the time of patients and doctors, significantly reduce the medical cost, and greatly improve the convenience of orthodontics; this manufacturing method has a short production time, high production efficiency, greatly saves the manufacturing process steps, and reduces the medical cost.

The invention discloses a face gear worm grinding machine error compensation method based on sensitivity analysis and a multi-source error mapping model, which comprises the following steps of: 1, constructing a multi-source error-tooth surface error mapping model based on a vector decomposition and truncation function method, the truncation function method is used for quantitatively describing propagation mechanisms of geometric errors and thermal errors in a machining chain and influences of the propagation mechanisms on tooth surface deviation, and high-order error terms are eliminated to improve calculation efficiency; 2, responding to the output of the mapping model, applying an improved Morris sensitivity analysis method, distributing a weighting coefficient higher than a geometric error component for a thermal error component, and calculating a weighting sensitivity coefficient so as to identify a key error component which has the greatest influence on the tooth surface precision; and 3, based on the key error component, a motion axis compensation value is generated through an error compensation model, and the compensation value is input into a machine tool control system to adjust the relative position of the worm grinding wheel and the workpiece, so that the tooth surface error is reduced.

The invention relates to a method and device for measuring pitch deviation based on a line laser sensor, and the method comprises the following steps: S1, calibrating the position of the line laser sensor, and obtaining the coordinate value of a coordinate system of the line laser sensor in a measurement coordinate system; s2, installing a tested gear; s3, adjusting the relative position of the line laser sensor and the measured gear; selecting a measured position in the tooth surface area of the gear teeth of the measured gear, adjusting the position of the line laser sensor, and recording the sum of the offset of the adjusted line laser sensor relative to the center of the measured gear along the x axis and the y axis in the effective measurement range of the line laser sensor at the measured position; s4, performing zero returning operation on the angle sensor of the rotating shaft of the tested gear; and S5, controlling the detected gear to rotate along the center line of the detected gear. According to the method and the device, the pitch deviation can be measured in a non-contact mode, excessive calibration and leveling are not needed before detection, and the measurement efficiency and the measurement precision are both improved.

The invention discloses a design method of a complex shape modifying and finishing wheel and a honing wheel for internal meshing powerful gear honing, and relates to the technical field of machine manufacturing. The method comprises the following steps: establishing a trimming wheel tooth surface numerical model, and judging whether the modification amount of the trimming wheel tooth surface numerical model meets the modification requirement or not; if yes, establishing a space coordinate conversion relation and a conjugate meshing equation of the dressing wheel and the honing wheel, and establishing a honing wheel tooth surface numerical model in combination with the dressing wheel tooth surface numerical model; according to the space coordinate conversion relation between the workpiece gear and the honing wheel and the honing wheel tooth surface numerical model, a complex modification workpiece gear tooth surface numerical model is established, and whether the modification amount of the complex modification workpiece gear tooth surface numerical model meets the modification requirement or not is judged; and if yes, a dressing wheel three-dimensional solid model and a honing wheel three-dimensional solid model are established according to the dressing wheel tooth surface numerical model and the honing wheel tooth surface numerical model respectively. According to the method, precise design and verification of the complex shape modifying and finishing wheel and the honing wheel for powerful gear honing can be achieved.

The invention belongs to the field of data processing, particularly relates to a wind turbine generator gear box tooth surface strength optimization method considering multi-working-condition load distribution, and aims to solve the problem that the optimization effect is affected due to the fact that strength optimization checking is carried out only for a single working condition in the prior art. The method comprises the following steps: acquiring working condition data of the gearbox under various preset working conditions; load spectrum decoupling processing is conducted on the working condition data, a dynamic load distribution matrix synchronous with the tooth surface meshing period is determined, stress field conversion is conducted on the dynamic load distribution matrix, and a tooth root bending stress field and a tooth surface contact stress field are obtained; inputting the tooth root bending stress field and the tooth surface contact stress field into a pre-constructed double-constraint optimization model to obtain a tooth surface strengthening parameter tensor output by the model; and inputting the tooth surface strengthening parameter tensor into a preset process mapping system. Based on the method provided by the invention, the multi-working-condition operation data of the gearbox are synchronously obtained for optimization calculation, and the limitation of traditional single load analysis is broken through.

The invention relates to the technical field of power grid stability analysis, in particular to a mechanical vibration micro-grid electromechanical coupling system stability analysis method, which comprises the following steps of: detecting a tooth surface contact radius, a relative speed and a Young modulus to generate a contact stiffness initial value, correcting nonlinear stiffness by interval difference, and calculating the stability of a micro-grid electromechanical coupling system. The method comprises the following steps: calculating a coupling response vector by combining rotor displacement and bearing clearance, inputting a Lyapunov exponent method to solve an exponent vector, constructing a model length ratio to detect derivative characteristics, extracting a multidimensional state vector in a positive value period and the coupling response vector to generate a compensation action, and constructing an FPGA simulation path injection disturbance execution error feedback back-transmission fuzzy control algorithm. According to the method, a contact stiffness dynamic correction and nonlinear difference method is introduced, six-degree-of-freedom displacement and bearing clearance parameters are combined, an electromechanical coupling model is established, a stability boundary is recognized through Lyapunov regression, a critical state is detected through derivative features, and multi-dimensional state vector fuzzy control compensation is fused. And the response and the immunity are optimized by combining FPGA simulation and a disturbance mechanism.

The invention provides an abrasive flow polishing device and method for gear tooth surface homogenization. According to the method, tooth-shaped drainage pieces with the same shape as the gear are installed at the two ends of the upper portion and the lower portion of the gear, drainage section design is introduced, an abrasive flow medium path runner model is constructed, main parameters influencing an experiment are sampled and grouped through a Latin hypercube sampling method, abrasive flow polishing simulation is conducted in a grouped mode, and a Gaussian regression process is utilized to obtain an abrasive flow polishing simulation result. Selecting the minimum root-mean-square error of each group of PiVi data, determining the group of experimental parameters, obtaining a group of abrasive flow machining process parameters of optimal inlet pressure, back pressure and drainage section length, and finally guiding the experiment; according to the method, the influence of the inlet effect is relieved, the abrasive flow medium path runner model is constructed, a set of optimal abrasive flow machining process parameter combination is obtained, and the method is suitable for spur gears and bevel gears and high in universality.

A rack greasy dirt cleaning device of a gear rack climbing type ship lift comprises a machine base, the machine base is installed on a rack protective cover, and the rack protective cover is installed on a ship chamber and moves up and down along with the ship chamber; a tooth surface oil scraping mechanism is installed on the machine base, the tooth surface oil scraping mechanism makes contact with the tooth surface of a ship lift rack, and pressing force is adjusted through a torsion adjusting mechanism. An end face oil scraping mechanism is installed below the tooth face oil scraping mechanism, receives oil dirt and adjusts contact and separation between the end face oil scraping mechanism and the tooth top face of the ship lift rack through an end face oil scraping adjusting assembly. The rack greasy dirt cleaning device of the gear rack climbing type ship lift can automatically clean greasy dirt on the rack, manual cleaning is not needed, and the maintenance cost and the workload of the ship lift are greatly reduced.

The invention belongs to the field of gear machining detection, and particularly relates to a cylindrical gear ghost order detection method and detection equipment based on tooth surface waviness analysis. The method comprises the following steps: firstly, acquiring tooth surface deviation data of each tooth in a gear, carrying out resampling, inclination error correction and de-modification on the tooth surface deviation data, and then combining the tooth surface deviation data into full-tooth deviation curves in four directions; and then extracting waviness data and generating a full-tooth waviness curve. After RC is carried out on a full-tooth waviness curve, on one hand, the full-tooth waviness curve is converted into a frequency domain signal for selecting a frequency range, on the other hand, spectral analysis is carried out on a waviness signal through an iterative sine wave fitting algorithm within the specified frequency range, sine wave components are extracted, and a corresponding order spectrum is generated. And finally, when a sine wave component of which the amplitude is greater than or equal to 0.02 mu m and which is in a non-integral multiple harmonic order with the tooth number exists in the order spectrum of the target gear, detecting the gear ghost order. According to the invention, the problem of lack of a high-precision and high-efficiency waviness analysis and gear ghost order detection method in the prior art is solved.

The grinding wheel grinding face gear tool setting method based on on-machine measurement comprises the steps that an initial measurement coordinate system of a face gear is established; a face gear manufacturing error is considered, and a measurement coordinate system of the face gear is optimized through an iteration method; based on errors such as tooth profile, tooth pitch and tooth thickness of the face gear, a face gear tooth surface uniform grinding optimization model is established, the position of the measurement coordinate system is further optimized by adopting a nonlinear optimization method, and a final measurement coordinate system is obtained; and finally, determining the position of the grinding wheel grinding face gear according to the basic model of the grinding wheel grinding face gear. The tool setting precision and efficiency of the grinding wheel and the face gear can be improved, and the uniformity of the tooth surface grinding amount of the face gear can also be improved.

The invention relates to the technical field of gear detection, and discloses a gear fatigue damage monitoring method and system based on a GCM counting method.The method comprises the steps that the input torque of a main speed reducer is obtained by calculating automobile running resistance, and tooth surface contact stress is obtained by combining gear geometric parameters and the Hertz contact theory; dividing stress into m grades, dividing a monitoring period into k time windows, and counting the cycle index of each stress grade to construct a GCM matrix; and correcting the stress into symmetric cyclic stress by adopting a Goodman criterion, calculating fatigue damage of each grade according to the S-N curve of the material, accumulating to obtain a total damage value, judging fatigue failure when the total damage exceeds a threshold value, and otherwise, calculating the residual cycle life. According to the method, accurate evaluation and early warning of the fatigue life of the main reducer gear can be realized, and the reliability and the safety of an automobile transmission system are improved.

The invention discloses a gear tooth surface micro-texture laser machining device and a machining method thereof. The machining device comprises a laser, a movement mechanism used for providing spatial position changes for the laser, a clamping mechanism used for adjusting the posture of a gear and a detection mechanism used for detecting the machining process of the gear micro-texture. The detection mechanism comprises a data acquisition block used for performing data acquisition on a gear tooth surface processing area, and the data acquisition block is fixed on the laser through a supporting plate. During machining, the detection mechanism moves along with the laser, data collection can be conducted on a machining area on line, machining errors can be monitored and fed back in real time, and error compensation can be conducted at any time. The machining device is further provided with a calibration module, and the calibration module is a substrate material made of a gear material. A substrate material can be preprocessed, a substrate material-laser parameter matching model is established, and a basis is provided for subsequent tooth surface texture processing. The invention further discloses a gear tooth surface micro-texture machining method.

The utility model discloses a closing clip capable of preventing tissue from being torn, and belongs to the field of medical hemostatic clips. The closing clamp capable of preventing the tissue from being torn comprises a first clamping arm and a second clamping arm, the near ends of the first clamping arm and the second clamping arm are connected through a connecting part, and the far end of the first clamping arm and the far end of the second clamping arm are respectively provided with a locking structure which can be buckled and locked together. The clamping faces of the first clamping arm and the second clamping arm are each divided into an anti-skid tooth face and a clamping smooth face in the width direction, and the anti-skid tooth face and the clamping smooth face of the first clamping arm and the anti-skid tooth face and the clamping smooth face of the second clamping arm are arranged in a one-to-one correspondence mode or in a crossed correspondence mode. According to the utility model, the clamping surfaces of the two clamping arms of the closing clamp are divided into the anti-slip tooth surfaces and the clamping smooth surfaces, so that the clamping pressure of the closing clamp on vascular tissues during closing is reduced, unnecessary damage to the tissues in the process of closing the tissues is effectively avoided, and hemostasis failure caused by tearing of the vascular tissues is prevented.

The invention provides a gear peeling time-varying meshing stiffness prediction method and system based on a back propagation neural network, and the method comprises the steps: considering a tooth surface peeling fault based on a gear tooth bearing contact analysis method, and constructing a helical gear pair time-varying meshing stiffness calculation model; a real irregular tooth surface peeling area is fitted by adopting a least square ellipse fitting method to obtain an ellipse appearance representation, any peeling position is completely described through six key geometric parameters, the geometric parameters of the ellipse appearance are systematically traversed and fitted, and diversified peeling appearance samples are generated. Introducing a tooth profile deviation matrix corresponding to the peeling morphology sample into a tooth surface bearing contact analysis model, and constructing a training data set; and constructing a back propagation neural network model of multiple hidden layers, and performing end-to-end training by using the training data set, so that the back propagation neural network model learns a nonlinear mapping relationship from geometric parameters to a time-varying meshing stiffness curve, thereby predicting the time-varying meshing stiffness under any peeling morphology.

The invention discloses an involute helical gear tooth surface waviness rapid detection method based on wavelet transformation, relates to the technical field of gear measurement and evaluation, and aims to solve the problems of low efficiency, insufficient anti-interference capability and limited extraction precision in existing tooth surface waviness detection. High-density data sampling is carried out on a specified tooth surface of an involute helical gear, a multi-scale characteristic decomposition signal of wavelet transform is utilized, a tooth surface waviness signal is separated from complex morphology characteristic components, and in combination with a threshold optimization algorithm, detail characteristics of waviness are effectively reserved, and meanwhile interference of non-correlation signals is restrained. In addition, efficient data processing and real-time waviness feature extraction are realized by designing a rapid analysis process and an automatic parameter adjustment mechanism. The method is suitable for gear quality detection in a batch production environment, and provides a reliable basis for defect diagnosis and optimization in a gear manufacturing process. Compared with a traditional detection method, the method has remarkable advantages in the aspects of detection precision, stability and speed.

The invention provides a gear contact fatigue life prediction method considering macro-micro geometric parameter influence. The method comprises the following steps: firstly, establishing a tooth surface contact-dynamics analysis model considering macro-micro geometric parameter influence, and calculating tooth surface dynamic load distribution; secondly, establishing a calculation model of the stress on the surface and below the surface of the gear considering the influence of lubrication and surface roughness, and calculating the oil film pressure and the stress on the surface and below the surface of the gear; and finally, establishing a gear contact fatigue life prediction model considering the influence of macro and micro geometric parameters, and calculating the contact fatigue life of the gear. According to the method, the influence of the rigidity change of the gear on the contact fatigue life of the gear is considered, the contact fatigue life of gears with different web structures is predicted, and the deviation between the contact fatigue life obtained through theoretical calculation and the actual contact fatigue life is reduced. Meanwhile, the method considers the influence of the error on the contact fatigue life of the gear, so that the prediction of the contact fatigue life of the gear with the modification and the error is realized.

The utility model relates to a safety type building curtain wall installation assembly. The safety type building curtain wall installation assembly comprises a bottom plate, a face plate and a communicating part. Elastic protruding arms are distributed on the bottom plate, first tooth faces are formed on the elastic protruding arms, and the first tooth faces can elastically deform to enable the free ends of the first tooth faces to move. A rigid arm is arranged on the panel, and a second tooth face is formed on the rigid arm. After the first tooth surface is connected with the second tooth surface, the protruding block can extend into the space between the elastic protruding arms, and a gap is formed between the opposite surfaces of the first tooth surface and the second tooth surface. And a bag part is formed on the side surface of the bump. The communicating part comprises a connecting block and at least one one-way valve pipe. An injection hole is formed in the connecting block. The one-way valve pipe comprises a valve pipe body and a connecting pipe. The valve pipe body is inserted into the communicating hole, and the connecting pipe is fixedly matched with the connecting block. Medium can be injected into the bag part from the injection hole through the one-way valve pipe, so that the bag part expands to support the free end of the elastic protruding arm. According to the utility model, the fixing state of the panel can be improved, so that the fixing state is firmer and more reliable, and the panel is easy to disassemble and assemble.

The invention discloses a machine tool rack defect detection method and device, equipment and a medium. The method comprises the following steps: acquiring an end face image of a target rack; the target rack is an arc-shaped rack, a plurality of teeth are distributed on the arc surface of the arc-shaped rack, and the end face image comprises contour information of the end faces of the teeth; identifying whether a first defect feature exists according to the end face image; the first defect feature is a contour feature formed by tooth offset; if yes, outputting first defect information, and if not, obtaining a tooth surface image of the target rack; the tooth surface image is obtained based on an upper view angle of the tooth, and the tooth surface image comprises contour information of a plurality of tooth side surfaces; identifying whether a second defect feature exists or not according to the tooth surface image; the second defect feature is a contour feature formed by defects on the tooth surface; if yes, the second defect information is output, if not, the target rack is marked as a qualified product, and the arc-shaped rack defect detection method and device have the advantage that the arc-shaped rack defect detection precision is improved.

The invention relates to the technical field of angle measurement, in particular to an angle measurement device. The device comprises a gear transmission mechanism, an angle detection mechanism and two anti-backlash mechanisms, the gear transmission mechanism comprises a driving gear and two follow-up gears; the angle detection mechanism comprises two follow-up end angle sensors. According to the angle measuring device provided by the invention, before the driving gear is started, the two anti-backlash mechanisms apply pre-tightening torques in opposite directions to the two follow-up gears respectively, so that the two follow-up gears are in contact with the left side tooth surface and the right side tooth surface of the driving gear respectively, and then the backlash in the tooth side when the driving gear is started in the forward direction and the reverse direction is eliminated; therefore, a bidirectional transmission preparation state without return stroke errors is realized. Therefore, the problems that due to the fact that a certain gear backlash is reserved between meshing gears, power can be transmitted to the output end only after the gear backlash is eliminated, and time delay and angle deviation are generated on signals detected by an angle sensor are solved.

Disclosed is a skiving tool for machining teeth where machining marks are produced at unequal distances. Some cutting edges of a skiving tool at least partially extend at different heights along a tool axis. During machining, cutting edges arranged at different axial heights relative to the workpiece axis successively engage on a tooth flank. The engagement of the cutting edges occurs at different time intervals and at different distances in the width direction of the tooth flank. The effects of the engagement of the cutting edges on the machining process and the excitation of vibrations when the teeth produced are used therefore have a frequency spectrum of greater width and lower amplitude than if the cutting edges were to engage at equal time intervals and equal distances. The more irregular surface structure of the teeth have a positive effect on noise excitation behavior when teeth are engaging with other teeth.