18results about How to "Avoid individual differences" patented technology

The invention belongs to the technical field of textiles and garments, relates to a texture rating technology, is used for solving the problem that an accurate texture prediction model cannot be established only by depending on factor analysis in the prior art, and particularly relates to a fabric texture evaluation analysis system and method and a storage medium. The evaluation analysis platform is in communication connection with an attribute test module, a perception analysis module, a factor analysis extraction module, a model training module and a texture rating module; the attribute testing module is used for carrying out comprehensive physical attribute testing on the sample fabric and obtaining corresponding attribute parameters; the factor analysis and extraction module is used for extracting common factors according to physical attributes; according to the method, the multi-dimensional objective attribute data is simplified into a small number of common factors by adopting a factor analysis method, and the common factors can effectively reflect the main characteristics of the texture of the fabric by utilizing a regression equation, so that individual differences and evaluation deviations caused by purely relying on subjective scoring are avoided.

The invention discloses a wind turbine generator component life probability prediction method and system, and a wind power plant energy control method and system. The prediction method comprises the steps of constructing a state space model of a degradation process of a wind turbine generator component; acquiring real-time state information of the component; inputting the real-time state information into the state space model, evaluating the degradation state of the component by adopting a sequential data assimilation algorithm, and outputting posterior probability distribution of the degradation state; and based on the posterior probability distribution, forward simulating a future degradation path of the component by adopting Monte Carlo simulation until the future degradation path exceeds a preset failure threshold, and obtaining residual life probability distribution of the component. According to the method, the personalized residual life of each unit can be accurately evaluated, and an innovative wind power plant energy management control strategy is created on the basis, so that the absolute maximization of the full-life-cycle economic benefit of the wind power plant in a complex market environment is realized.

The invention relates to a method for detecting the color of a cell culture solution, and belongs to the technical field of cell detection. The method comprises the following steps: acquiring a color detection value a * actual detection of a to-be-detected cell culture fluid; judging whether the color detection value a * actual detection is smaller than a preset value a * preset of a cell culture fluid or not, and if yes, supplementing or replacing a cell culture medium; otherwise, putting back the culture box to continue culturing for one day, detecting the color detection value of the cell culture solution again on the second day, and supplementing or replacing the cell culture medium until the judgment condition is met. According to the method, the cell growth is not influenced, the color change time of the cell culture fluid can be correctly judged, the cell culture fluid is supplemented or replaced for the cells in time, the detection efficiency is improved, and the labor cost is reduced.

The invention relates to the technical field of casting equipment, and particularly discloses a camshaft casting continuous production device and method.The device comprises an electric induction furnace and a slag salvaging mechanism, and the electric induction furnace comprises a furnace body and a support arranged on the furnace body and close to a furnace opening; the slag salvaging mechanism comprises an outer sleeve rotationally connected with the support, a spiral conveyor coaxially arranged in the outer sleeve, and at least one intermittent slag collecting assembly, wherein one end of the outer sleeve extends into the furnace body from the furnace opening. A slag inlet and a slag outlet are formed in the outer sleeve in the axial direction at intervals, the intermittent slag collecting assembly is constructed to continuously collect dross in molten iron in the furnace body and extrude the dross into the outer sleeve from the slag inlet, and the spiral material conveying machine is constructed to continuously convey the dross from the slag inlet to the slag outlet and discharge the dross, so that the time difference between manual slag salvaging and connection of previous and later procedures is effectively solved; the continuity of casting production is guaranteed, and the production efficiency is improved to adapt to the large-scale production requirement; and meanwhile, the consistency of the deslagging degree is ensured through automatic deslagging operation, and the stability of the quality of the camshaft blank is improved.

The present invention provides a method and system, device and medium for pushing evaluation index values, the pushing method comprising the following steps: obtaining the evaluation index value corresponding to the first user; collecting the historical vital sign parameters of the second user with respect to the first user; pushing the evaluation index value to the second user based on the historical vital sign parameters; wherein the historical vital sign parameters include the vital sign parameters collected from the second user within a first preset time period after the second user receives the historical evaluation index value of the first user. The present invention realizes accurate and differentiated pushing of the evaluation index value corresponding to the first user to the second user through intelligent analysis of the historical vital sign parameters of the second user with respect to the first user, and can build a smart digital education ecosystem in the application scenario of student education, realize close connection and interaction between families, schools and students, and break through the limitation of lack of differentiated evaluation in the traditional digital education model.

This utility model relates to the field of durability testing technology, specifically a solid-state drive (SSD) insertion / removal durability testing fixture. It includes a test base, a feeding mechanism, a gripping mechanism, and an insertion / removal mechanism. The feeding mechanism is mounted on the surface of the test base and includes a conveyor frame, a conveyor belt, and a conveyor motor. It can quickly and accurately align the gripping claw with the SSD under test, and the gripping force can be naturally adjusted according to the spring compression. This avoids damage to the SSD casing caused by rigid gripping while ensuring effective clamping of the SSD. The pawl, under the elastic force of the second spring, continuously engages with the ratchet tooth groove, forming a one-way locking structure. This completely restricts gear reversal, thereby locking the position of the pressure plate and ensuring that the gripping claw maintains a stable clamping force. Even if the electric telescopic rod experiences slight extension or contraction, or if the equipment vibrates during operation, it will not loosen, providing absolutely stable gripping assurance for subsequent lifting, conveying, and other processes.

The invention discloses an injection molding defect correction rule learning method and a terminal, and relates to the field of injection molding process optimization, and the injection molding defect correction rule learning method comprises the following steps: collecting multiple groups of mold testing data of a mold testing process; subtracting the data corresponding to each former mode from the last mode data of each trial mode process to construct a training data set; screening the training data set according to a preset support degree threshold to obtain a frequent data set; screening the frequent data set according to a preset confidence threshold to obtain a rule set; and screening the rule set to obtain a defect correction rule. According to the technical scheme, the data sets of multiple mold adjustment processes can be collected, learning of injection molding defect correction knowledge is automatically completed, manual intervention is not carried out, individual difference, deviation and locality of manual knowledge summarization are avoided, and good data compatibility can be achieved.

The utility model relates to the field of auxiliary frock provides a kind of anti-roll bar link assembly device. Anti-roll bar link assembly device includes base;First clamping component, setting in base, first clamping component includes the clamping groove of being set in pair, clamping groove is used to place the node mandrel of anti-roll bar link, first clamping piece is arranged in clamping groove for the node mandrel clamped in clamping groove;Second clamping component, setting in base, second clamping component includes clamping rod, clamping rod is used to the bearing of the rod end of anti-roll bar link clamped between clamping rod and base. The anti-roll bar link assembly device can firmly fix node mandrel, avoid the positioning deviation caused by the thickness change of mandrel;Can eliminate the wobble clearance of rod end bearing;Reduce the data deviation after assembly;Adjustable first clamping piece can be adapted to node mandrel of different thickness without replacing parts, save the changeover adjustment time of traditional frock.

The present application relates to a kind of five-axis linkage tool grinder rotating shaft dynamic characteristic test system, specifically to the field of intelligent detection, the scheme is through to the multi-source heterogeneous time series data, generate information-rich structured multidimensional feature tensor sequence by synchronization, segmentation and advanced feature extraction;Using the pre-training and fine-tuning of deep convolutional autoencoder, establish personalized encoder and health benchmark statistical distribution model for each device, overcome individual differences;By calculating Mahalanobis distance and normalized reconstruction error and fusion, output continuous quantitative real-time health index, realize the accurate characterization of performance degradation process;Finally, based on health index sequence, the probability prediction of remaining useful life and the identification of dominant degradation mode are output simultaneously by multi-task prediction model, so that maintenance decision is changed from post-alarm to state-based accurate prediction, effectively avoiding unplanned shutdown and over-maintenance.

The invention discloses an automatic control method for continuous winding of a CICC type high-temperature superconducting coil for a star simulator, relates to the field of intelligent manufacturing, and solves the technical problems of low forming precision and poor environmental adaptability in the continuous winding forming process of irregular-shaped coils. According to the method, target data, cable materials and coil finished product shapes are identified; a parameter identification model is established, and control parameters during coil firing forming are obtained based on the parameter identification model; establishing a digital twinborn model of the firing furnace, and performing environment calibration on the control parameters based on the digital twinborn model to obtain standard control parameters; controlling the firing machine to operate based on the standard control parameters; according to the invention, the performance of the finished coil and the reliability of equipment operation can be improved, so that low efficiency, unstable precision and individual difference influence caused by traditional manual parameter setting depending on experience are avoided.

The invention discloses a skid deformation monitoring method and device. The method comprises the following steps: acquiring training image data, and establishing a data set according to the training image data; training the basic convolutional neural network model by using the training data set to obtain an application convolutional neural network model, and testing the application convolutional neural network model by using the test data set to obtain a prediction area of the test data set; comparing the intersection-to-union ratio with a standard intersection-to-union ratio, and comparing the center distance with a standard center distance according to a comparison condition; the method comprises the following steps: acquiring real-time production data in a production field, inputting the real-time production data into a final application convolutional neural network model to obtain a model prediction region, calculating a region center point according to the model prediction region, calculating distances among four vertexes to obtain four-point distances, and calculating a mean square error according to the four-point distances and a standard distance. And comparing the mean square deviation with a standard mean square deviation. According to the invention, the problem of inaccurate monitoring of the skid deformation degree in the prior art is solved.

The invention discloses a robot speed reducer service life prediction method and device, equipment and a medium, relates to the technical field of service life prediction, and is used for solving the problem that the existing robot speed reducer service life prediction accuracy is relatively low. The method comprises the following steps: carrying out data acquisition on a full life cycle of a to-be-predicted robot speed reducer to obtain target full-cycle data; wherein the target full-cycle data comprises multiple groups of speed data, multiple groups of angle data and multiple groups of current data of the speed reducer; inputting the target full-cycle data into a trained life prediction model to obtain a life prediction result corresponding to the to-be-predicted robot speed reducer; wherein the trained life prediction model is obtained based on a plurality of preset regression models and a plurality of preset classification models, so that the problem that the precision of a single model is insufficient when the data size is small is effectively solved while the life prediction accuracy of the robot speed reducer is improved.

The invention relates to a portable algae detection device and method based on deep learning. The device comprises a base; the rotating disc is horizontally and rotatably mounted on the base; the first motor is connected with the rotating turntable; the guide rail is vertically mounted on the base; the sliding block is slidably mounted on the guide rail; the second motor is connected with the sliding block; a lens of the electronic camera is provided with a microscope objective lens, and the electronic camera is fixedly installed on the sliding block; and the processor is electrically connected with the first motor, the second motor and the electronic camera. The rotating platform is used for replacing an xy-axis moving platform in the horizontal direction, mechanical errors caused by machining are effectively avoided, and the difficulty of mechanical control and the cost of mechanical maintenance are greatly reduced; the customized simplified optical microscope system replaces the whole set of optical microscope system, the research and development and maintenance cost of the device is reduced, the size and weight of the device are reduced, the device is convenient to carry, and the device is not limited to use in a laboratory any more, but can be widely applied.

The invention relates to the technical field of airport terminal passenger flow model design, in particular to an airport terminal passenger flow-based BIM model generation method and device and a medium, and the method comprises the following steps: 1, classifying airports with annual passenger throughput; step 2, determining regional distribution of plane terminals, and for each region, designing a BIM model of each region according to classification of terminals of annual passenger throughput; 3, numbering the drawn standard BIM models according to the classification of terminal buildings, and storing the standard BIM models in a BIM model library in a classified manner; and 4, calling the BIM model of each region in the BIM model library, and completing the design of the BIM model of the terminal building. According to the method, the annual passenger throughput is used as a core factor, the repeated design process of analysis, decision making and mapping of project terminal process requirements is strided, the design period is further shortened through a standardized and callable design mode, and the design efficiency and the design quality are remarkably improved.

The invention provides a ray operation position feedback device based on a tooth bracket. The ray operation position feedback device comprises a ray therapy machine, a six-dimensional therapy bed, a first camera, a second camera, a head fixing assembly, a tooth positioning bracket and a tooth position marker, the tooth position marker body is mounted on the tooth positioning bracket, and the tooth positioning bracket is used for being fixed on palate teeth of a patient; the first camera and the second camera are used for collecting image information of the tooth position marker and transmitting the image information to the ray therapy machine; and the ray therapy machine determines the position information of the tooth position marker according to the received image information, so that the six-dimensional treatment bed is controlled to move, and the head treatment part of a patient lying on the six-dimensional treatment bed is kept at the ray focus position of the ray therapy machine. By means of the ray operation position feedback device, the problem of micro-deviation of the head of a patient can be effectively solved, and meanwhile the situation that the patient feels extremely uncomfortable and even shocks when screw placement is conducted on the head of the patient can be avoided.

The invention belongs to the field of biological medicines, and particularly relates to a combination, a method and a detection kit for combined detection of Alzheimer's disease biomarkers. The invention provides application of a biomarker group in detection of Alzheimer's disease, at least one of APOE4, GDF-15, UCH-L1 and PF4, phosphorylated Tau protein and total Tau protein, and the detection result is more accurate and reliable.

The invention relates to the technical field of artificial intelligence, in particular to an automatic entity labeling method perpendicular to industry policies and regulations. The method comprises the following steps: analyzing a document format, judging whether the document is a text document, dynamically splitting the document into text blocks based on semantic integrity, vectorizing the text, identifying entities and attributes, vectorizing the entities, clustering based on vector similarity and the like. According to the method, through full-process automation of semantic-driven text partitioning, LLM entity recognition and disambiguation, knowledge network construction and graph fusion, the tedious links of reading-understanding-labeling-rechecking in traditional manual labeling are replaced, the requirements for professional labeling personnel and quality inspection personnel are reduced through the automatic process, and in addition, the automatic labeling efficiency is improved. Through cooperation of a dynamic partitioning strategy (reducing LLM single processing capacity), vector retrieval (quickly positioning similar entities) and map fusion (incremental updating knowledge), the labeling period is greatly shortened.