CN111325307B - Bionic design method for solving physical contradiction - Google Patents
Bionic design method for solving physical contradiction Download PDFInfo
- Publication number
- CN111325307B CN111325307B CN202010080591.3A CN202010080591A CN111325307B CN 111325307 B CN111325307 B CN 111325307B CN 202010080591 A CN202010080591 A CN 202010080591A CN 111325307 B CN111325307 B CN 111325307B
- Authority
- CN
- China
- Prior art keywords
- contradiction
- bionic
- parameters
- technical
- physical
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/004—Artificial life, i.e. computing arrangements simulating life
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- General Health & Medical Sciences (AREA)
- Biomedical Technology (AREA)
- Biophysics (AREA)
- Computational Linguistics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Molecular Biology (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Health & Medical Sciences (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a bionic design method for solving physical contradiction, which comprises the following steps: s1: for the physical contradiction and technical contradiction description form of a given problem, the causal relationship between the physical contradiction and the technical contradiction is expressed through a component parameter model; s2: determining contradictions between operation domains; s3: according to the contradiction between operation domains, searching PRIZM matrix, extracting original understanding, and according to the principle of the invention, obtaining bionic cases from a bionic case library; s4: screening a bionic case; s5: and according to the comparison of the form, behavior and physiological dimension of the biological system and the design parameters, behavior and functional parameters of the technical system, finding out the physical contradiction of resource solution. The method finds out the resources for solving the physical contradiction by analogic analysis of the biological system and the technical system, provides the basis of biological system cases for solving the physical contradiction of the technical system, exerts the advantages of bionic design and expands the method for solving the physical contradiction.
Description
Technical Field
The invention relates to a physical contradiction solving method.
Background
At present, the technology competition is increasingly strong, enterprises need to ensure market competitiveness, and the technical innovation is key. By improving the original products, the generation of new technology is a main way for enterprises to develop technical innovation. In the process, a contradiction problem is encountered, and the contradiction problem is divided into technical contradiction and physical contradiction by TRIZ theory, so that the problems are solved from different levels. However, both solving the technical contradiction and the physical contradiction only provides the designer with the inventive principle and the separation method, and the implementation of the inventive principle and the separation method needs to be completed by a person, and the analog design is the main method for embodying the inventive principle, but the problem of how to obtain the analog source design of the problem is not discussed much.
The BioTRIZ establishes a PRIZM contradiction matrix from the perspective of bionic design, the adopted invention principle is the same as TRIZ, and a bionic case is provided for the invention principle. When the problems are solved, the technical contradiction problem of TRIZ theory can be converted into contradiction between the operation domains of BioTRIZ so as to obtain the invention principle and biological case. Thus, the implementation process of the invention principle can be obtained through the analogy design of biological cases, and the research shows that the invention principle recommended by BioTRIZ is more original and novel to implement. However, there is no support for the corresponding biotiz method for the physical contradiction problem in TRIZ theory. If the PRIZM matrix of the BioTRIZ and the bionic case are related to the TRIZ theoretical physical contradiction solution, the BioTRIZ bionic case is used for analogy to support the physical contradiction solution, the basis of the biological system case is provided for the physical contradiction solution, the advantages of the bionic design are brought into play, and the method for solving the physical contradiction is expanded.
Disclosure of Invention
The invention aims to provide a bionic design method for solving physical contradiction, which is different from the traditional method for carrying out resource analysis and selecting a separation method by relying on human experience. The method finds out the resources for solving the physical contradiction by analogic analysis of the biological system and the technical system, provides the basis of biological system cases for solving the physical contradiction of the technical system, exerts the advantages of bionic design and expands the method for solving the physical contradiction.
The invention aims at realizing the following technical scheme:
a bionic design method for solving physical contradiction comprises the following steps:
step S1: for the physical contradiction and technical contradiction description form of a given problem, the causal relationship between the physical contradiction and the technical contradiction is expressed through a component parameter model;
step S2: classifying functional parameters which generate contradictions in a technical system into one of six operation domains of materials, structures, energy, information, time and space respectively, and determining contradictions among the operation domains;
step S3: according to the contradiction between operation domains, searching PRIZM matrix, extracting original understanding, and according to the principle of the invention, obtaining bionic cases from a bionic case library;
step S4: analyzing behaviors and functions generated by the biological system on environmental stimulus in the bionic cases, determining operation domains to which the behaviors and functions belong, matching the operation domains with contradictory operation domains, screening the bionic cases, and selecting the bionic design source if the operation domains are matched with the contradictory operation domains; otherwise, discarding the bionic case;
step S5: and according to the comparison of the form, behavior and physiological dimension of the biological system and the design parameters, behavior and functional parameters of the technical system, finding out the physical contradiction of resource solution.
The invention supports the physical contradiction solving by applying a bionic design method, and in the problem analysis stage, the technical contradiction and the physical contradiction described by the problem are connected through a causal relationship by a component parameter model. In the stage of obtaining principle solution, the technical contradiction is converted into the BioTRIZ contradiction by classifying engineering parameters in the technical contradiction into an operation domain of the BioTRIZ, the principle of the invention is obtained through a PRIZM matrix of the BioTRIZ, and a biological case set is obtained in a biological case library through the principle of the invention, so that a bridge is established between the physical contradiction and the biological case. In the biological case selection stage, the operation domain of the biological system physiological dimension is matched with the operation domain of the technical system functional parameter to select a proper biological case, so that the biological case which can be used as an analogy source is provided for the physical contradiction. In the generation stage of the physical contradiction concrete solution, the design parameters, behaviors and functional parameters of the technical system are respectively matched with the ecology, behaviors and physiological dimensions of the biological system, so that the resources in the biological system which are not in the technical system are found, and the resources are transferred into the technical system, thereby changing the prior technical system through the resources and completing the solution of the physical contradiction.
Compared with the prior art, the invention has the following advantages:
1. the connection between the physical contradiction and the technical contradiction is established through the component parameter model, the connection between the physical contradiction and the BioTRIZ bionic case system is established through the technical contradiction, a biological case is provided for solving the physical contradiction as an analogy source, and the bionic design advantage is exerted in the process of solving the physical contradiction.
2. The contradiction (physical contradiction) of the design parameter value and the contradiction between the operation domains of the BioTRIZ are linked through the component parameter model and the technical contradiction, a design-level expression method is provided for the description of the BioTRIZ problem, and the way of expressing and analyzing the BioTRIZ problem is expanded.
Drawings
FIG. 1 is a flow chart of a bionic design for solving a physical contradiction;
FIG. 2 is a functional model;
FIG. 3 is a component parametric model;
FIG. 4 is an analog diagram of a biological system and a technical system;
FIG. 5 is a threaded coupling;
FIG. 6 is a causal relationship between physical contradiction and technical contradiction;
FIG. 7 is a soft structure plate buckle;
fig. 8 shows an embodiment using a motor drive according to the soft trigger.
Detailed Description
The following description of the present invention is provided with reference to the accompanying drawings, but is not limited to the following description, and any modifications or equivalent substitutions of the present invention should be included in the scope of the present invention without departing from the spirit and scope of the present invention.
The invention provides a bionic design method for solving physical contradiction, as shown in figure 1, which comprises the following steps:
step S1: for the physical contradiction and technical contradiction description form of the problem, the causal relationship between the physical contradiction and the technical contradiction is expressed through a component parameter model. In analyzing the problem of technical system contradiction, it is common that technical contradictions are found first, and then physical contradictions are obtained by analysis by a radical contradiction analysis method (rca+) (Souchkov v. Root Conflict Analysis (rca+): structured Problem and Contradictions Mapping [ C ], 2005.). The causal relationship between the technical contradiction and the physical contradiction is expressed by using the component parameter model, so that the physical contradiction problem is solved by using a bionic design method subsequently.
In the step, the causal relation between the physical contradiction and the technical contradiction is expressed by a component parameter model, and the method comprises the following specific steps:
step S1-1: according to the technical system function model, analyzing the functional effects corresponding to the opposite value requirements (physical contradictions) of the design parameters in the tool component, expressing the design parameters and the opposite values of the design parameters by using the component parameter model, and expressing the functional effects by using the functional parameters of the component parameter model. The functional model is shown in fig. 2, describing the functional relationship between the tool and the functional object, wherein the improvement parameter or deterioration parameter in the technical contradiction is obtained from the effect of this function. The component parametric model is represented by component name, design parameters, and functional parameters, as shown in FIG. 3, wherein: the component name is the unique identification of the component in the technical system; design parameters are parameters that people can directly change through design behavior; functional parameters are used to express the purpose of the component's presence and cannot be changed directly by design actions, the change of the functional parameters being by design parameters. A component contains a design parameter and a plurality of functional parameters. The relation between the component parameter model and the functional model is that design parameters are parameters which can be changed through design behaviors in a tool component in the functional model, the change of the design parameters in the tool component can influence the functional effect of the tool component, and the functional effect is described by the functional parameters in the component parameter model.
Step S1-2: the function parameters are matched with the improvement parameters and the deterioration parameters in the technical contradiction to form the expression of the causal relationship between the physical contradiction and the technical contradiction.
Step S2: functional parameters which generate contradictions in the technical system are respectively classified into one of six operation domains of materials, structures, energy, information, time and space, and the contradictions among the operation domains are determined.
In the step, the functional parameters are classified into the operation domain, firstly, the matching relation between the functional parameters and engineering parameters in technical contradiction is established, and then, the functional parameters are classified into the operation domain through improvement and deterioration in the technical contradiction.
In this step, engineering parameters of the technical contradiction are divided into corresponding operation domains according to the classification relation (Creative Contributions of the Methods of Inventive Principles of TRIZ and Bio TRIZ to Problem Solving [ J ]. Journal of Mechanical Design, AUGUST 2017, vol (139)) of the engineering parameters and the operation domains, and functional parameters matched with the engineering parameters are naturally divided into the corresponding operation domains.
Step S3: according to the contradiction between operation domains, the PRIZM matrix is checked, the original understanding is extracted, the invention principle is used as the retrieval term, and the bionic case is obtained from the bionic case library.
In this step, PRIZM matrix is shown in Table 1, the inventive principle is to search the biological case library of entry (Jian Yanhui. Biological R is used to combine with bionic TRIZ, new set method research on the color of the same group [ D ]. University of success (Taiwan area), pages 2013:49-78), and Table 2 is part of biological case data.
TABLE 1 PRIZM matrix
TABLE 2 biological case library fragment diagram of the inventive principles
In this step, the selection of the bionic case is defined by taking the operation domain where the technical system functional parameter is located as a limit, and the operation domain where the biological system physiological dimension belongs to be matched with the operation domain where the technical system functional parameter is located to be used as an alternative bionic case, thereby participating in the solution of the physical contradiction.
Step S4: analyzing behaviors generated by a biological system on environmental stimulus and functions generated by the behaviors in the bionic case, determining operation domains to which the behaviors and the functions belong, and selecting the operation domains as a bionic design source if the operation domains are matched with contradictory operation domains; otherwise, the bionic case is abandoned.
Step S5: and according to the comparison of the form, behavior and physiological dimension of the biological system and the design parameters, behavior and functional parameters of the technical system, the physical contradiction of resource solution is found.
In this step, resources are found from the operation domain according to analogy between the morphology, behavior and physiological dimensions of the biological system and design parameters, behavior and functional parameters of the technical system, so as to solve the physical contradiction. The analogy diagram of the biological system and the technical system is shown in fig. 4, and the specific steps are as follows:
step S5-1: analyzing the biological system according to the operation domain of the technical system function parameters, and extracting the physiological functions similar to the technical system function parameters.
Step S5-2: analyzing biological behaviors depending on physiological functions of a biological system, comparing and analyzing the biological behaviors with behaviors of a technical system, searching for differences of behaviors of the biological behaviors and the technical system, and analyzing reasons for the differences of the behaviors.
Step S5-3: and comparing the ecological dimension of the biological system with the technical system structure by combining the behavior difference, and searching for the structural difference. This structural difference is a resource that can be used to resolve the physical contradiction, see R in fig. 4.
Step S5-4: the structural difference is used as a target resource, the resource is searched in a technical system, a subsystem and a super system, and the resource is used for modifying design parameters in a component parameter model, so that the physical contradiction is solved.
Examples:
as shown in FIG. 5, in the threaded coupling, when the space between the nut and the coupled part is narrow, the common wrench cannot realize a large-angle knob due to the large widths of the arms at the two sides of the wrench opening, which affects the assembly and disassembly efficiency. The application of TRIZ describes this problem as contradictory, the working component being the spanner and the working object being the nut. In order to enable the spanner opening to enter a narrow space, the knob angle is increased, the working efficiency is improved, and the width of a side arm of the spanner opening is required to be small; however, in order to ensure the jaw strength, the jaw side arms are wider. Thus, the physical contradiction describes both a large and small jaw side arm width. The corresponding technical contradiction is described as: the improvement parameter is productivity and the deterioration parameter is force. The causal relationship between the physical contradiction and the technical contradiction is established by applying the component parameter model, see fig. 6, the functional parameters are corresponding to the operation domain of biotiz, the domain corresponding to the improved parameters is time, and the domain corresponding to the deteriorated parameters is energy. According to the principle of obtaining the TRIZ contradiction matrix by checking the improvement parameter and the deterioration parameter: 10 (pre-action), 15 (dynamic method), 28 (mechanical substitution method), 36 (phase change method). According to the principle of domain checking PRIZM: 3 (local mass method), 9 (pre-reaction method), 15 (dynamic method), 20 (continuous usage), 22 (harm to benefit), 25 (self-service method).
Considering that the invention focuses on utilizing the causal relationship between technical contradiction and physical contradiction, the reference biological case is obtained. Therefore, the intersection of the principle provided by TRIZ and BioTRIZ is considered important in selecting the principle of the invention. In selecting the principle, the principle provided by TRIZ is used as a main reference. Thus, the principle 15 is selected, and other principles may also yield an effective solution.
According to principle 15 (dynamic method), a biological case library is searched. For the dynamic method in the case library, the biological cases are given as follows: a dynamic structure of liquid water; the microtubule structure of the animal is formed by a tubular structure, and can be bent, elongated and shortened; the number of biometric groups is a dynamic balance, such as the relationship of hunters to hunters.
From the above cases, it was found that microtubule structures of organisms, including some soft structural organisms, have such a biological morphology that it is possible to adapt to narrow spaces by bending, elongation, and shortening, etc. This is consistent with the environment described by our problem.
In order to solve the problem of the embodiment, a soft structure plate buckle is designed, as shown in fig. 7, a spanner opening is formed by a flexible belt, and the inner side surface of the flexible belt is in contact friction with the outer side surface of a nut when in operation, and the friction force drives the nut to rotate. Fig. 8 shows an embodiment of the invention using a motor drive.
Claims (6)
1. A bionic design method applied to solving physical contradiction existing in a wrench opening is characterized by comprising the following steps:
step S1: for the physical contradiction and technical contradiction description form of a given problem, the causal relationship between the physical contradiction and the technical contradiction is expressed through a component parameter model;
step S2: classifying functional parameters which generate contradictions in a technical system into one of six operation domains of materials, structures, energy, information, time and space respectively, and determining contradictions among the operation domains;
step S3: according to the contradiction between operation domains, searching PRIZM matrix, extracting original understanding, and according to the principle of the invention, obtaining bionic cases from a bionic case library;
step S4: analyzing behaviors generated by a biological system on environmental stimulus and functions generated by the behaviors in the bionic case, determining operation domains to which the behaviors and the functions belong, and selecting the operation domains as a bionic design source if the operation domains are matched with contradictory operation domains; otherwise, discarding the bionic case;
step S5: according to comparison of the form, behavior and physiological dimension of the biological system and design parameters, behavior and functional parameters of the technical system, the physical contradiction of resource solution is found;
the bionic design method is applied to solving the physical contradiction existing in the wrench jaw, and then a soft structure jaw driven by a motor is designed;
the given problem is: when the space between the nut and the connected part is narrow, the width of arms at two sides of a spanner opening of the common spanner is large, so that a large-angle knob cannot be realized, and the loading and unloading efficiency is affected; in order to improve the working efficiency, the width of the side arm of the spanner opening is small; in order to ensure the strength of the spanner opening, the width of the side arm of the spanner opening is large;
the physical contradiction of the given problem is described as both a large and small jaw side arm width;
the technical contradiction corresponding to the physical contradiction is described as: the improvement parameter is productivity and the deterioration parameter is force; establishing a causal relationship between the physical contradiction and the technical contradiction by using a component parameter model;
the functional parameters are corresponding to the operation domain of BioTRIZ, the domain corresponding to the improvement parameters is obtained to be time, and the domain corresponding to the deterioration parameters is energy;
according to the principle provided by the TRIZ contradiction matrix of the improvement parameter and the deterioration parameter, according to the principle provided by the PRIZM of the corresponding domain check, according to the intersection of the principle provided by TRIZ and PRIZM, obtaining the principle solution as a dynamic method principle; searching a bionic case library according to the dynamic method principle, and screening out a bionic case;
the bionic case is a microtubule structure of an organism or a soft structure of a soft structure organism, the microtubule structure or the soft structure adapts to a narrow space by bending, extending and shortening to be consistent with the environment described by the given problem, and the microtubule structure or the soft structure is selected as a bionic design source;
according to the bionic case, a jaw formed by a flexible belt is designed, and when the bionic case works, the inner side surface of the flexible belt contacts with the outer side surface of the nut to rub, and the friction force drives the nut to rotate.
2. The method according to claim 1, wherein in the step S1, the causal relationship between the physical contradiction and the technical contradiction is expressed by a component parameter model, and the specific steps are as follows:
step S1-1: according to the technical system function model, analyzing the functional effects corresponding to the opposite value requirements of the design parameters in the tool component, expressing the design parameters and the opposite value of the design parameters by using the component parameter model, and expressing the functional effects by using the functional parameters of the component parameter model;
step S1-2: the function parameters are matched with the improvement parameters and the deterioration parameters in the technical contradiction to form the expression of the causal relationship between the physical contradiction and the technical contradiction.
3. The method of biomimetic design according to claim 2, wherein the component parameter model is represented by a component name, design parameters and functional parameters.
4. The method according to claim 1, wherein in the step S2, the functional parameters are classified into the operation domain, and the step is implemented by first establishing a matching relationship between the functional parameters and engineering parameters in the technical contradiction, and then classifying the engineering parameters in the operation domain by improving and deteriorating the technical contradiction.
5. The method of claim 1, wherein in step S3, the selection of the bionic case is defined by an operation domain where the technical system function parameter is located, and the operation domain where the biological system physiological dimension is matched with the operation domain where the technical system function parameter is located is used as an alternative bionic case to participate in solving the physical contradiction.
6. The method for designing a bionic structure according to claim 1, wherein the specific steps of the step S5 are as follows:
step S5-1: analyzing the biological system according to the operation domain of the technical system function parameters, and extracting physiological functions similar to the technical system function parameters;
step S5-2: analyzing biological behaviors depending on physiological functions of a biological system, comparing and analyzing the biological behaviors with behaviors of a technical system, searching for differences of the behaviors, and analyzing reasons for generating the differences of the behaviors;
step S5-3: comparing the ecological dimension of the biological system with the technical system structure by combining the behavior difference, and searching for the structure difference;
step S5-4: the structural difference is used as a target resource, the resource is searched in a technical system, a subsystem and a super system, and the resource is used for modifying design parameters in a component parameter model, so that the physical contradiction is solved.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010080591.3A CN111325307B (en) | 2020-02-05 | 2020-02-05 | Bionic design method for solving physical contradiction |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010080591.3A CN111325307B (en) | 2020-02-05 | 2020-02-05 | Bionic design method for solving physical contradiction |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111325307A CN111325307A (en) | 2020-06-23 |
| CN111325307B true CN111325307B (en) | 2023-07-21 |
Family
ID=71172140
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010080591.3A Active CN111325307B (en) | 2020-02-05 | 2020-02-05 | Bionic design method for solving physical contradiction |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111325307B (en) |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5465320A (en) * | 1991-07-04 | 1995-11-07 | Hitachi, Ltd. | Method of automated learning, an apparatus therefor, and a system incorporating such an apparatus |
| WO2004100065A2 (en) * | 2003-05-07 | 2004-11-18 | Lifelike Biomatic, Inc. | System and method for simulation of the evolution of complex living organisms |
| JP2010231578A (en) * | 2009-03-27 | 2010-10-14 | Honda Motor Co Ltd | Program and method for supporting selection of characteristic parameter |
| CN106055742A (en) * | 2016-05-19 | 2016-10-26 | 同济大学 | Method for product self-adaption design modification based on design entropy |
| CN106407512A (en) * | 2016-08-30 | 2017-02-15 | 上海交通大学 | Product ecological system conflict resolution method based on conflict matrix |
| CN106557615A (en) * | 2016-10-27 | 2017-04-05 | 燕山大学 | A kind of bionical object select method theoretical based on TRIZ |
| CN106997341A (en) * | 2017-03-22 | 2017-08-01 | 山东大学 | A kind of innovation scheme matching process, device, server and system |
| CN108920751A (en) * | 2018-05-24 | 2018-11-30 | 西安交通大学 | The Converse solved method of winding deformation of power transformer state based on topological optimization |
| CN108921276A (en) * | 2018-06-21 | 2018-11-30 | 燕山大学 | A kind of the equipment lightweight bionic method and system of force flow guiding |
| CN109033748A (en) * | 2018-08-14 | 2018-12-18 | 齐齐哈尔大学 | A kind of miRNA identification of function method based on multiple groups |
-
2020
- 2020-02-05 CN CN202010080591.3A patent/CN111325307B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5465320A (en) * | 1991-07-04 | 1995-11-07 | Hitachi, Ltd. | Method of automated learning, an apparatus therefor, and a system incorporating such an apparatus |
| WO2004100065A2 (en) * | 2003-05-07 | 2004-11-18 | Lifelike Biomatic, Inc. | System and method for simulation of the evolution of complex living organisms |
| JP2010231578A (en) * | 2009-03-27 | 2010-10-14 | Honda Motor Co Ltd | Program and method for supporting selection of characteristic parameter |
| CN106055742A (en) * | 2016-05-19 | 2016-10-26 | 同济大学 | Method for product self-adaption design modification based on design entropy |
| CN106407512A (en) * | 2016-08-30 | 2017-02-15 | 上海交通大学 | Product ecological system conflict resolution method based on conflict matrix |
| CN106557615A (en) * | 2016-10-27 | 2017-04-05 | 燕山大学 | A kind of bionical object select method theoretical based on TRIZ |
| CN106997341A (en) * | 2017-03-22 | 2017-08-01 | 山东大学 | A kind of innovation scheme matching process, device, server and system |
| CN108920751A (en) * | 2018-05-24 | 2018-11-30 | 西安交通大学 | The Converse solved method of winding deformation of power transformer state based on topological optimization |
| CN108921276A (en) * | 2018-06-21 | 2018-11-30 | 燕山大学 | A kind of the equipment lightweight bionic method and system of force flow guiding |
| CN109033748A (en) * | 2018-08-14 | 2018-12-18 | 齐齐哈尔大学 | A kind of miRNA identification of function method based on multiple groups |
Non-Patent Citations (5)
| Title |
|---|
| Research and application: conceptual integrated model based on TRIZ and bionics for product innovation;Liu Xiaomin;International Journal on Interactive Design and Manufacturing;全文 * |
| TRIZ理论及其在机械产品创新设计中的应用;刘尚明;刘东亮;刘恒义;;现代制造技术与装备(第03期);全文 * |
| 基于ENV模型的机械系统矛盾消解方法研究;胡骥;王中双;刘尚;;齐齐哈尔大学学报(自然科学版)(第06期);全文 * |
| 基于SVM的TRIZ矛盾矩阵的仿真研究;王皓晨;中国优秀硕士学位论文全文数据库(第01期);全文 * |
| 基于权利要求分析的专利规避方法研究;刘尚;何春江;李岩;;齐齐哈尔大学学报(自然科学版)(第04期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111325307A (en) | 2020-06-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109726812A (en) | Feature ordering neural network and method generate the method for simplifying feature set model | |
| Markovic et al. | Multi‐scale modeling of heterogeneous structures with inelastic constitutive behaviour: Part I–physical and mathematical aspects | |
| Singh et al. | Hetconv: Beyond homogeneous convolution kernels for deep cnns | |
| Galambos et al. | Tensor product model transformation-based control design for force reflecting tele-grasping under time delay | |
| CN111325307B (en) | Bionic design method for solving physical contradiction | |
| Wasilewski et al. | Measuring the perceived iq of multimodal large language models using standardized iq tests | |
| Chowdhury et al. | Protein-protein interaction network prediction using stochastic learning automata induced differential evolution | |
| Koo et al. | Interpreting deep neural networks beyond attribution methods: quantifying global importance of genomic features | |
| Chu et al. | Deep unfolded convolutional dictionary learning for motif discovery | |
| Bhatnagar et al. | Research Methodology as SDLC Process in Image Processing | |
| Zamil et al. | Prediction of protein-protein interaction from amino acid sequence using ensemble classifier | |
| Della Santina et al. | Soft Robotic Modeling and Control: Bringing Together Articulated Soft Robots and Soft-Bodied Robots | |
| Majdandzic et al. | Statistical correction of input gradients for black box models trained with categorical input features | |
| Ding et al. | An exact transformation of convolutional kernels enables accurate identification of sequence motifs | |
| Islam et al. | Pattern identification on protein sequences of neurodegenerative diseases using association rule mining | |
| Moriwaki et al. | Achieving general-purpose AI that can learn and make decisions for itself | |
| CN109767814A (en) | A kind of amino acid global characteristics vector representation method based on GloVe model | |
| Sibai et al. | Hardware acceleration of the STRIKE string kernel algorithm for estimating protein to protein interactions | |
| Estrada Pabón et al. | The Role of Configurational Entropy in Miniprotein Stability | |
| Lupión¹ et al. | 1 Department of Informatics, University of Almería, ceiA3 Excellence Agri-food Campus, Almería, Spain 2 | |
| Martinec et al. | Modelling proportions and sequences of operations in team design activities | |
| Manzano et al. | Toward smart composites: Small-scale, untethered prediction and control for soft sensor/actuator systems | |
| Mirzoyan et al. | The construction of local convex hull on the task of pattern recognition | |
| DeSalle et al. | The Basics of Phylogenetics | |
| Shi et al. | Shape-shifting microgel automata controlled by DNA sequence instructions |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |