303results about How to "Achieve quantification" patented technology

The invention belongs to the field of medical signal processing, and provides a detection method of vascular elasticity and blood pressure based on a single probe photoplethysmography pulse wave. According to the technical scheme, through the adoption of the detection method, quantization of the vascular elasticity and estimation of the blood pressure are achieved on the condition that a photoplethysmography pulse wave is collected merely through a single probe. The detection method comprises the first step of collecting the pulse wave and the blood pressure based on a pulse wave collecting system and a cuff sphygmomanometer; the second step of extracting features related to the vascular elasticity and the blood pressure; the third step of building a blood pressure predicting linear regression equation through the adoption of a stepwise regression method according to a relevant feature quantity; the fourth step of training a BP neural network according to the relevant feature quantity, and measuring the elasticity of an artery blood vessel and a blood pressure value through the trained neural network. The detection method of the vascular elasticity and blood pressure based on the single probe photoplethysmography pulse wave has the advantages that the algorithm performance is good, the quantization of the elasticity of the artery blood vessel wall of the human body can be achieved through the photoplethysmography pulse wave collected by the single probe, and the blood pressure value can be accurately predicted.

The invention discloses a testing method and device for driverless automobiles. The method in one embodiment comprises steps of: selecting testing scenario parameter combinations for testing the performance of the driverless automobile from preset testing scenario parameter combinations; determining, on the basis of preset values and preset weighted value corresponding to various types of testing scenario parameters in the testing scenario parameter combinations, the complexity parameter of a testing scenario corresponding to each testing scenario parameter combination; aggregating the complexity parameters with values corresponding to the same preset value section; generating indicative information indicating whether the driverless automobile passes the testing scenario corresponding to the complexity parameter on the basis of a testing result whether the driverless automobile passes the testing scenario corresponding to the complexity parameter. The testing method and device quantify the complexities of the testing scenarios and may further determine various testing scenarios corresponding to the same difficulty so as to increase the testing accuracy of the driverless automobiles.

The invention discloses a method and a technique for analyzing and judging the whole carbon emission metering of the city based on city planning. According to the method and the technique, city planning low-carbon emission fields are divided into six aspects, namely traffic, water, buildings, industries, wastes and carbon sink, and the total carbon emission of the whole city is obtained by carbon emission accounting of the specific aspects. According to the method, the energy resource carbon emissions of land are metered and planned by analyzing land usage and gross land characteristics in the city planning, or the traffic carbon emission can be predicted according to traffic road network density and flow and further the total carbon emission of the city at different planning stages is predicted; finally, organic joint of the carbon emission and international and national carbon emission standards is realized while the carbon emission conforms to a city planning system so as to promote low-carbon economic development and low-carbon cause.

The invention provides an artificial-intelligence-based talent big data quantization precise matching method and an apparatus. The method includes the following steps: acquiring a resume provided by a job applicant, and extracting scoring vectors of plural types of information in the resume; extracting a predetermined number of resumes and scoring vectors thereof as training samples; using the machine deep learning algorithm to conduct training on the training samples so as to obtain a talent data scoring model; using the talent data scoring model to conduct scoring on the bulk of resumes so as to obtain a resume database with scoring values; the resume database with the scoring values providing resumes that match the scoring values in accordance with talent requirements input externally. The technical solution of the invention realizes quantization of the bulk resume information, so that the technical solution is easy to provide a resume with corresponding scoring value in accordance with talent requirements, is more efficient, and meets demands of network recruitment platform and employee entities.

Disclosed is a micro-nano fluidic biochip for assaying a biological sample comprising a first substrate, a second substrate and a third substrate which are sequentially stacked from bottom to top, wherein an upper channel assembly disposed on the second substrate is coupled with the lower channel assembly provided on the first substrate, to form a microfluidic channel, and the microfluidic channel has nano interstices formed at both sides thereof, the nano interstices having a height less than that of the center of the channel.

The invention discloses a method for calculating similarity of short texts by using a deep convolution neural network, and aims to calculate the similarity of short texts by using each word in the short texts and obtain a relatively accurate value of the similarity. According to the technical scheme, the method comprises the following steps: 1) expressing a plurality of short texts as a plurality of matrixes, and sequentially replacing each word in texts by using corresponding word vectors so as to obtain an ordered vector sequence as one matrix; 2) generating a similar matrix of two matrixes representing target short texts, and arranging cosine similarity of word vectors so as to obtain a similarity matrix; 3) paving rows and columns of similar matrixes into same dimensions; and 4) reducing the dimensions of the similar matrixes into one value as the similarity, performing training dimension reduction on the similar matrixes for all similar matrixes of same dimensions by using the deep convolution neural network, and calculating a similarity degree through multi-layer sensation, thereby obtaining the value of the similarity.

The invention discloses an online sliding pressure optimization method for a turbine of a thermal power plant. The online sliding pressure optimization method for the turbine of the thermal power plant includes that changing a steam distribution mode of a valve, and confirming a reasonable high-pressure control valve overlapping degree; testing the best valve sites when two valves of the high-pressure control valve are opened and three valves of the high-pressure control valve are opened so as to confirm the best valve sites; comparing the economical efficiency between the best valve site when two valves are opened and the best valve site when three valves are opened; calculating a back pressure correction pressure difference, a main steam temperature correction pressure difference, a reheat temperature correction pressure difference, a high-pressure cylinder efficiency correction pressure difference and a reheat attemperation water correction pressure difference, using each correction pressure difference to calculate a sliding pressure optimization pressure difference, calculating to obtain the sliding pressure optimization pressure (the best pressure) according to the sliding pressure optimization pressure difference, a design value of the sliding pressure and limited conditions, and using a loss differential system to display the best pressure in real time to realize the best precise control for the valve position so as to realize the sliding pressure optimization and all-season sliding pressure quantization and visualization.

The invention discloses a network threat intelligence credibility identification method. The method disclosed by the invention comprises the following steps: 1) constructing an association diagram model of network threat intelligence, wherein a node on the diagram is a network threat indicator; 2) each network threat indicator has an initial reputation value, calculating the initial reputation value of each network threat indicator to serve as a part of a final threat reputation value of the indicator; 3) calculating a weight for each edge in the association diagram model; 4) designing a threat propagation algorithm via the idea of a diagram propagation algorithm, so that the threat reputation value is propagated step by step among the nodes and neighboring nodes, and then combining the threat reputation value with the initial reputation value of each network threat indicator to calculate a final reputation value; and 5) determining the network threat intelligence credibility accordingto the final reputation value of the network threat indicator. By adoption of the network threat intelligence credibility identification method disclosed by the invention, the quality of network threat intelligence can be better evaluated.

The invention relates to the field of satellite communication, in particular to a satellite network dynamic routing method based on inter-satellite link attributes. The method comprises the following steps: collecting a static snapshot sequence diagram of a satellite network, and constructing a satellite network spatio-temporal evolution diagram; enabling a controller node to collect state information of a satellite node in real time, and respectively calculating a link SNR, link survival time and a dynamic utility value of a satellite cache; giving a weight to the dynamic utility value of each inter-satellite link attribute by adopting a self-adaptive maximum deviation algorithm based on multi-attribute decision making, and constructing a weighted satellite network spatio-temporal evolution diagram; obtaining an end-to-end reachable path of the satellite based on the weighted satellite network spatio-temporal evolution diagram, and establishing an optimization model of link utility; and enabling the controller node to select a transmission path by using the optimization model, and determining a reliable satellite end-to-end transmission path. According to the method, the system routing path can be optimized according to the link state information, so that the network throughput is improved, the packet loss rate is reduced, and the dynamic adaptability is relatively high.

The invention provides an acupuncture and acupoint effect quantifying analysis system. In the acupuncture and acupoint effect quantifying analysis system, an expert acupuncture detection unit is formed by an acupuncture parameter measuring instrument, an acupuncture acupoint effect detection unit consists of a temperature sensor, a blood flow sensor and an electromyogrphic sensor, and an acupuncture quantifying mechanical hand forms a closed-loop control structure by an embedded controller, a servo driver, a mechanical acupuncture hand and a feedback detection unit. An expert acupuncture-acupoint effect database is established on the basis of traditional Chinese medicinal acupuncture experts, a control program of the acupuncture quantifying mechanical hand is written on the basis of the database, and through control of the mechanical acupuncture hand and detection on an acupuncture acupoint effect, acupuncture quantification and acupoint effect quantification are achieved. The invention has the beneficial effects as follows: the acupuncture and acupoint effect quantifying analysis system achieves combination of quantitative acupuncture simulation and acupuncture acupoint effect detection, and a novel experimental instrument is provided for researching the compatibility of traditional Chinese medicinal acupuncture acupoints, the specificity of acupuncture and quantification thereof, the specificity of the acupoint effect and quantification thereof and other aspects.

The present invention discloses a bolt detection system and an implementation method thereof. The system comprises a training learning module and a detection module. The method comprises the steps of:collecting bolt knocking sound by employing a bolt detection system, performing feature extraction of the collected bolt knocking sound, and performing training learning of the extracted features according to the machine learning algorithm; and collecting knocking sound of a bolt to be detected by employing the bolt detection system, and performing defect detection of the collected knocking soundof the bolt to be detected according to a result of training learning. The whole work process does not need human intervention so as to reduce the labor cost and improve the detection reliability; and moreover, the bolt detection system and the implementation method thereof can perform feature extraction and training learning of a lot of knocking sound of bolts to achieve quantification of bolt defect indexes, comprehensively identify the defects of the bolts so as to further improve the detection reliability. The bolt detection system and the implementation method thereof are widely appliedto the field of connection piece detection.

A novel gene 65B13 expressed specifically and transiently in dopaminergic neuron precursor cells immediately after cell cycle exit was obtained by the present invention. The cellular expression of 65B13 can be used as an index to select cells that are suitable in terms of their safety, survival rate, and network formation ability, for transplant therapy of neurodegenerative diseases such as Parkinson's disease.

The invention discloses a neural-network-based appropriation budgeting method for a scientific research project, and aims to the problem that scientific research appropriation budgeting accuracy and practicability cannot be combined. The method comprises the following steps of: analyzing components of appropriation of the scientific research project and key factors influencing budgeting, wherein the key factors comprise a research cycle, the number of researchers, a key technical coefficient, a project result coefficient and the innovativeness and complexity of the project; and establishing a quantified expression of the influencing factors, and establishing a nonlinear expression between a quantification result and an appropriation budgeting result of the project through a neural network by taking the quantification result as input and taking the appropriation budgeting result of the project as output. An application result shows that the method is reliable and high in evaluation accuracy.

The present invention provides a composite structure successive approximation analog-digital converter and a quantitative method thereof, belonging to the technical field of analog digital conversion.The composite structure successive approximation analog-digital converter comprises a digital analog conversion module, a comparison module and a successive approximation logic module, the digital analog conversion module comprises a capacitance weight digital analog conversion unit and a serial capacitive digital analog conversion unit, and the successive approximation logic module comprises a capacitance weight successive approximation logic unit and a serial successive approximation logic unit which are respectively used to control the capacitance weight digital analog conversion unit andthe serial capacitive digital analog conversion unit. The composite structure successive approximation analog-digital converter and a quantitative method thereof employ the capacitance weight digitalanalog conversion unit to perform sampling and employ a two-step mode for conversion to achieve quantization of analog input, the comparison module is configured to compare the voltage signals outputby the digital analog conversion module with reference signals, and the obtained comparison result is converted to output codes of a composite structure successive approximation analog-digital converter through the successive approximation logic module. The composite structure successive approximation analog-digital converter and the quantitative method thereof are high in area efficiency, low inpower consumption and fast in conversion speed.

The invention relates to a small-scale municipal sludge and household waste synergetic incineration treatment method. The small-scale municipal sludge and household waste synergetic incineration treatment method comprises a municipal sludge incineration system, a household waste synergetic treatment system, a waste heat recycling device and a smoke purifying system. The municipal sludge incineration system comprises a sludge feeding device, a sludge drying machine and a sludge incineration device which are sequentially connected in series. The household waste synergetic treatment system comprises a waste feeding device and a waste pyrolysis gasification furnace which are connected in series. The gas outlet end of the waste pyrolysis gasification furnace communicates to the sludge incineration device, and generated pyrolysis gasification gas is introduced into an assistant combustion device through a draught fan. The waste heat recycling device is a waste heat boiler, the waste heat boiler is used for generating steam by heating boiler feed water, the steam communicates with a turbine generator set, the turbine generator set utilizes the steam generated by the waste heat boiler through absorbing heat to generate electricity, the electricity is used for auxiliary power supply supplementation of the municipal sludge incineration system and the household waste treatment system. First-grade exhausted steam of the turbine generator set is conveyed into the sludge drying machine to be used as a heat source for drying the sludge. The smoke generated after sludge incineration is processed by the smoke purifying system and is discharged after reaching standards.

The invention discloses a steel wire rope mesh tensioning device and a method. The steel wire rope mesh tensioning device comprises aluminum alloy joints, a fixing end, a tension sensor, a steel wire rope mesh, a tensioning end and a tensioning device. The tensioning device comprises a torque wrench, a draw bar and a locking nut, and the tension sensor and the torque wrench are respectively provided with corresponding display screens. The method comprises following steps: fixing one end of the steel wire rope mesh at the fixing end via one aluminum alloy joint at first, connecting the other end of the steel wire rope mesh with the tensioning end via the other aluminum alloy joint, and screwing down the locking nut so as to fix the steel wire rope mesh. The locking nut continues being screwed down by the torque wrench, corresponding torque values are displayed on the display screen of the torque wrench, simultaneously, by the aid of tensioning at the tensioning end, tension values of the steel wire rope mesh are displayed on the display screen of the tension sensor, quantization of force in a total tensioning process is realized, a reinforcing mode is improved, and standard quality is improved sufficiently.

The invention provides a starting test system for simulating ditch bed deposits under disturbance of upstream debris flow. The starting test system comprises a source tank, an artificial rainfall simulating device, an upstream debris flow migration simulating device, a cross plate head shear rheometer, a multi-physical-parameter monitoring system and a measurement and control system. The artificial rainfall simulating device is arranged above the source tank, the upstream debris flow migration simulating device is arranged on the upper portion of the source tank, the cross plate head shear rheometer is connected into the source tank, the multi-physical-parameter monitoring system is arranged in the source tank, and the measurement and control system is connected with the artificial rainfall simulating device, the upstream debris flow migration simulating device, the cross plate head shear rheometer and the multi-physical-parameter monitoring system. The starting test system for simulating the ditch bed deposits under the disturbance of the upstream debris flow has the advantages that starting effects and mechanisms of the ditch bed deposits under the disturbance of the upstream debris flow can be accurately simulated, and accordingly on-way erosion phenomena in debris flow disaster formation procedures can be revealed.

The invention belongs to the technical field of neural networks and relates to a method for realizing state quantization network in cross array neural morphology hardware. The method of the inventionincludes: after quantifying the parameters of an artificial neural network (weight, threshold, leakage constant, set voltage, refractory period and synaptic delay), the quantized parameters are mappedto the cross-array neural morphology hardware, and then the input data after preprocessing are sent to the cross-array neural morphology hardware to realize the state quantization network. Through state quantization, the requirements of cross-array neural morphology hardware for memory cell size, memory level, reliability and so on are effectively reduced.

The invention provides an intelligent control type cookware. The intelligent control type cookware comprises a pot body (1) and a pot handle (2), and is characterized in that the pot body (1) is in a three-layered structure which sequentially comprises an inner layer (101), a temperature measuring sensor layer (102) and an outer layer (103); and the pot handle (2) comprises a handle body (201), a signal processing unit (202) and a display timing unit (203). According to the intelligent control type cookware disclosed by the invention, a pot body temperature and cooling time can be displayed and can be controlled in a cooking process; the intelligent degree of cooking is improved; and the cooking quality is realized.

The invention discloses a sensitive equipment voltage sag tolerance characteristic testing and data processing method. The method comprises the following steps: setting duration time of the sag in variable-step by section, adding the density of testing points at a transition part of a tolerance curve so as to guarantee that the obtained tolerance curve is more precise, and guarantee that the testing frequency is within a reasonable range; testing under various influence elements to obtain a large amount of tolerance curves, and performing enveloping processing, and performing line broken processing on the enveloped line; dividing a non-rectangular uncertain region of the equipment into two regions, describing the rectangular region therein according to uniform distribution by taking the determination probability values of the upper enveloping line and the lower enveloping line and the region boundary line as the reference values, and quantizing the influence degree on the equipment bythe voltage sag event by adopting a line section specific method between related points for the non-rectangular region. The method disclosed by the invention can provide a reasonable testing method and a simple data processing method for the users of power grids, governance vendors, and sensitive equipment, thereby realizing the quantitative description of the non-rectangular uncertain region of the equipment.

The invention discloses a dynamic collision prevention method for an unmanned surface vehicle based on a sparse iteration potential field algorithm. The method comprises the steps of firstly buildinga safe distance model and a potential function (a function of distances with a start and an end), then finding spare points by using a binary search thought and a sparse constraint method, and thus planning the shortest safe path at any angle from a grid map. Then aiming at the kinetic characteristic of the unmanned surface vehicle and the characteristic that the convention on the international regulations for preventing collisions needs to be conformed to during an unmanned surface vehicle planning process, maritime rules and kinematical constraints are considered while the unmanned surface vehicle avoids collision, so that the optimal path with quantized safe distance can be planed in real time for the unmanned surface vehicle. The dynamic collision prevention method provided by the invention can be applied to the field of unmanned surface vehicle path planning, and can quickly and dynamically prevent collisions in real time.

The invention discloses an offshore platform moving equipment importance evaluation method and an offshore platform moving equipment importance evaluation system. The method comprises the following steps: S1, the importance evaluation indexes of equipment are established; S2, the scoring standard of each importance evaluation index is established; S3, multiple evaluators determine the initial weight value of each importance evaluation index and the optimal order relation of the importance evaluation indexes respectively using an AHP method, and thus, multiple initial weight values of each importance evaluation index and multiple optimal order relations of the importance evaluation indexes are obtained; S4, calculation is performed on the multiple initial weight values of each importance evaluation index and the multiple optimal order relations of the importance evaluation indexes by use of a fuzzy Borda sequence value method to get the Borda value of each importance evaluation index; S5, the group weight value of each importance evaluation index and the optimal order relation of the importance evaluation indexes are generated according to the Borda value of each importance evaluation index; and S6, the importance of the equipment is calculated according to the group weight value of each importance evaluation index and the optimal order relation of the importance evaluation indexes. The invention puts forward an equipment combination group evaluation method based on an AHP method, a fuzzy Borda sequence value method and a Monte Carlo simulation method. Quantification of the importance of offshore platform moving equipment is realized.

The invention provides a map path acquiring method and device. The map path acquiring method comprises the following steps: acquiring a plurality of paths between a current position and a target position, and acquiring a path from the plurality of paths as a reference path; acquiring a plurality of recommended nodes on the reference path, and if the distance between two adjacent recommended nodes exceeds a preset division distance, inserting a node between the two adjacent recommended nodes; for each node of the node-inserted reference path, acquiring the first matching degree of the other paths in the plurality of paths relative to the reference path in a geo-fencing manner; and sequencing the other paths according to the first matching degree to obtain a first candidate path set of the other paths relative to the reference path. The embodiment of the invention can realize effective assessment of the plurality of paths, so as to provide the most suitable path and buddies for outgoing crowds.

The invention relates to a rotor fault diagnosis method giving comprehensive consideration to current and voltage information of a motor and calculating a fault index for evaluating fault severity of a rotor according to the current and voltage information. The index can achieve diagnosis and quantification of a broken bar fault of the motor rotor. The method gives the comprehensive consideration to voltage and current signals, eliminates influence of a control strategy and a control parameter of the motor on a diagnostic result since the influence of the control strategy and the control parameter finally affects voltage of the motor, while the voltage is considered in the method; load and torque changes have smaller influence on the fault diagnosis index; at the same time, the method does not increase hardware expenditure of a system; a fault diagnosis program of the method can be embedded into a controller of an inverter; and the method can achieve on-line rotor fault diagnosis and has greater practical significance.

The invention discloses a greedy sparse decomposition-based ECPT defect rapid detection method, and by use of the formation of temperature concentrated areas and spatial distribution sparse characteristics of both ends of a crack and a gap, a thermograph video space is processed by innovated statistical signal processing algorithm, namely greedy sparse decomposition for automatic and direct separation of defect thermal model components without analysis of other specific thermal model blind source region for realization of ECPT defect automatic rapid detection and quantification. By combining ECPT nondestructive testing physical principle, a single channel blind source separation model is constructed, by combination of sparse analysis theory, the greedy sparse decomposition-based ECPT defect rapid detection method can be used for conductor material defect automatic rapid detection, the greedy sparse decomposition-based ECPT defect rapid detection method can directly handle an ECPT thermograph video without artificial selection of thermograph or pixel features, and the loss of large amount of data is avoided. At the same time, no additional signal processing method is added and defects can be automatically, accurately and rapidly detected.

The invention provides a measuring method of a dynamic stress field evolution law of a complex heterogeneous structure. A transparent photosensitive resin model of the complex heterogeneous structure is prepared by 3D (three-dimensional) printing technology to serve as a test piece, the test piece is placed in a light path of a circularly polarized light dark field and subjected to continuous stress loading and picture recording, a plurality of continuously changing full-field stress fringe gray images are acquired according to videos generated by picture recording, gray value change sequences of pixel points at positions in the images are acquired, finally, full-field fringe orders under continuous loading conditions are calculated according to the relation between gray values and the fringe orders, and full-field stress values under the continuous loading conditions are further calculated. Therefore, the global dynamic stress field evolution law of the complex heterogeneous structure subjected to high exterior load under fixed light field conditions can be extracted and quantified by the method.

The invention discloses a micro-grid protection method which is applied to the technical field of an electric power system and comprises the following steps: 1) establishing a micro-grid line differential protection model in communication delay; 2) conducting research on the detection technology in communication delay; and 3) establishing an information model based on the IEC61850 micro-grid line differential protection system. According to the first step of establishing a micro-grid line differential protection model in communication delay, a micro-grid line differential protection model is established so that the micro-grid can switch smoothly between the islanding operation mode and the grid connection operation mode. In step 2, the differential protection algorithm is improved by the introduction of a third-order dynamic time warping algorithm into the traditional differential protection algorithm. In step 3, the establishment of communication delay evaluation indexes and the use of a multi-interval optimization method protect the seeking problem of critical dimension in communication network delay. The invention has the communication delay compensation function, and achieves high reliability and strong compatibility.

The embodiment of the invention provides a bullet screen emotion analysis method and device. The method comprises the steps of obtaining a bullet screen text in a preset time period; matching the bullet screen text with a bullet screen emotion dictionary, and performing text vectorization on emotion words obtained by matching to obtain a word vector of each emotion word; summing word vectors of all emotion words in the bullet screen text to obtain a bullet screen text vector, and inputting the bullet screen text vector into a preset emotion analysis model to obtain an emotion type of the bullet text; wherein the preset emotion analysis model is obtained after training according to a bullet screen text sample with an emotion type label; and performing text vectorization on the emotion wordsobtained by matching to obtain a word vector of each sentiment word, thereby realizing quantification of the sentiment words, and inputting the barrage text vector into a preset emotion analysis model to obtain an emotion type of the bullet screen text, so that the emotion type of the bullet screen text can be quickly and accurately obtained.

The invention discloses an energy damage identification method based on quasi-distributed acceleration data. The energy damage identification method comprises the following steps of distributing a plurality of vertical acceleration sensors on a long-span bridge in a quasi-distributed mode to measure vertical acceleration time interval response signals of a long-span bridge structure under outside stimulation; collecting acceleration time interval data signals when the long-span bridge is not damaged to calculate quasi-distributed acceleration energy E0 when the bridge is not damaged; timely collecting the acceleration time interval data signals during an operation period of the long-span bridge to timely calculate quasi-distributed acceleration energy Ed during the operation period of the long-span bridge and calculate an energy difference index and / or an energy curvature difference index of the E0 and the Ed; and using peaks of the energy difference index and / or the energy curvature difference index to locate damage position, and simultaneously quantizing the damage based on change rate peaks of the energy difference index and / or the energy curvature difference index. The energy damage identification method achieves accurate and rapid identification and quantization on damage of the long-span bridge structure.

The invention provides an ultrasonic torsional vibration measuring device. The ultrasonic torsional vibration measuring device includes an ultrasonic power supply, an amplitude-change pole, a computer, a display device, a first bracket, a second bracket and a third bracket; a transducer is arranged on the first bracket, the upper end of the transducer is connected with the lower end of the amplitude-change pole through a double-end bolt, and the upper end of the amplitude-change pole is provided with a standard knife rod; a laser displacement sensor pan-tile is arranged on the second bracket, and a laser displacement sensor is arranged on the laser displacement sensor pan-tile. The invention further discloses a measuring method of the ultrasonic torsional vibration measuring device. By fitting a torsional amplitude function curve, the torsional vibration amplitude of each point on the knife rod can be simply calculated, and quantization of the torsional vibration amplitude of an edge of one, participating in cutting, of a milling cutter, a drill and other cutter tools is achieved. Through the torsional amplitude of an ultrasonic vibration device, the torsional vibration amplitude of a cutting edge or a point of a small-diameter cutter tool can be calculated.