88 results about "Condition factor" patented technology

A method of analyzing vibrations of a rolling element bearing installed in a rotating machine includes accessing vibration data corresponding to the bearing to be analyzed, determining a degraded condition factor BD for the bearing, selecting an expected designer-determined mean-time-to-failure MTTF of the bearing operating under a design load in the operating environment of the rotating machine, selecting a forecast time period, calculating a reduced mean-time-to-failure RMTTF of the bearing using the expected designer-determined mean-time-to-failure MTTF and the degraded condition factor BD, calculating a probability of failure of the bearing in the forecast time period using the reduced mean time to failure RMTTF, accessing cost data corresponding to a cost of failure of the bearing in the rotating machine, calculating a financial risk from the calculated probability of failure in the forecast time period and the cost data, and displaying the financial risk for the selected time period.

The invention provides a method of reestablishing wireless communications for a mobile vehicle. After a communication link failure on a first communication link is detected, it is determined whether to reconnect on the first communication link based on at least one communication condition factor, and then an attempt is made to establish a second communication link based on the communication condition factor determination.

A method of determining an orbit of an orbital object includes computing predicted tracking measurement values based on the orbit computed from the initial conditions factoring in any modeled environmental forces and realistic maneuvers; computing the differences between the actual and predicted tracking measurements; determining an improved estimate of the initial conditions that reduces the measurement errors using a minimization or root finding algorithm; after the algorithm has converged, reviewing the hypothetical maneuvers in the force model, taking each value and determining which values came up as near-zero in the minimized solutions and which values came up as those of measurable thrust; determining overall burn duration using the first and last burn times; determining the thrust profile of the orbital object over the observation period using the integrated thrust values; and determining the actual maneuver based on the observation data.

The embodiment of the invention discloses a method and a device for data mining of a road traffic accident based on an association rule, which relate to the field of communication. In order to realize effective analysis and counting correlative with occurring condition factors of the accident and serve the jobs of accident prevention, treatment, decision and the like, the invention provides a technical scheme of: acquiring historical data in a prescribed time range and a prescribed road section range from the historical data of the road traffic accident as association rule mined data; determining the attribute of the traffic accident of the association rule mined data; acquiring a frequent item set according to the association rule mined data, the attribute of the traffic accident and the minimum support; and acquiring an accident association rule according to the frequent item set and the minimum degree of confidence. The method and the device are suitable for real-time dynamic traffic information services.

The invention provides a physical modeling experiment device for a multifunctional high-speed remote landslide dynamic process. The physical modeling experiment device comprises a support base, an upper sliding section, a transition section and a lower sliding section, wherein the upper sliding section, the transition section and the lower sliding section are successively connected with each other; the support base is arranged as a height adjusting mechanism; the top end of the height adjusting mechanism is connected with the lower surface of the inlet end of the upper sliding section; the upper sliding section comprises an upper sliding slot, a baffle and a rotating connector; the baffle is mounted in the upper sliding slot; the transition section is arranged as an arc-shaped slide slot matched with the rotating connector; the transition section is hinged with the rotating connector; the lower sliding section comprises a lower sliding slot and an adjusting module; one slot wall of the lower sliding section is hinged with the transition section while the other slot wall is connected with the transition section through the adjusting module. The device provided by the invention can be used for implementing a physical modeling experiment for the multifunctional high-speed remote landslide dynamic process; the three factors of landslide height, landslide volume and topographic condition are mainly contained; the topographic condition factor includes gradient, base and sliding path direction; the reciprocating test can be performed according to different topographic conditions.

The invention relates to the field of rock fracture prediction, in particular to a shale hydraulic fracture propagation prediction method. The method comprises the steps that 1, the normal direction,tangential stress and effect stress of an inclined fracture under the action of the external stress and water pressure are calculated; 2, a strain energy density function is obtained according to thetype of the fracture; 3, a strain energy density factor is obtained according to the strain energy density function; 4, the propagation direction and propagation angle of the fracture are judged according to a strain energy density criterion; 5, influences of stratification, natural fractures and the like on the propagation direction of hydraulic fractures are obtained through numerical simulation, so that fracture propagation under the effect of shale hydraulic pressure is predicted. The prediction method is based on fracture mechanics, a hydraulic condition factor is introduced, and the influences of different stratification directions on the propagation direction of the shale hydraulic fractures are obtained by researching the relation between the fracture propagation direction and themagnitude of the hydraulic pressure and utilizing an extended finite element method, so that accurate prediction of hydraulic fracture propagation is achieved, and higher prediction accuracy is obtained.

The invention provides an intelligent household control model training method, a control method and a device, and relates to the intelligent household technical field; the intelligent household control model training method comprises the following steps: recording condition factor data triggered by the intelligent household equipment in multi-time and corresponding triggering results; quantifying each condition factor data piece so as to form a first input vector; quantifying the triggering result corresponding to each condition factor data piece so as to form a first target vector; training samples according to each the first input vector and the first target vector matched with each the first input vector, thus obtaining a training model. By using the intelligent household control model training method, the control method and the device, common users need not to define linkage rule conditions and control portions, thus automatically defining the intelligent household equipment linkage rules, satisfying user real demands, and improving user experiences.

A method of analyzing vibrations of a rolling element bearing installed in a rotating machine includes accessing vibration data corresponding to the bearing to be analyzed, determining a degraded condition factor BD for the bearing, selecting an expected designer-determined mean-time-to-failure MTTF of the bearing operating under a design load in the operating environment of the rotating machine, selecting a forecast time period, calculating a reduced mean-time-to-failure RMTTF of the bearing using the expected designer-determined mean-time-to-failure MTTF and the degraded condition factor BD, calculating a probability of failure of the bearing in the forecast time period using the reduced mean-time-to-failure RMTTF, accessing cost data corresponding to a cost of failure of the bearing in the rotating machine, calculating a financial risk from the calculated probability of failure in the forecast time period and the cost data, and displaying the financial risk for the selected time period.

The invention discloses a data analysis method for genetic disease gene testing, a system thereof and a storage medium. The method comprises the steps of inputting sample information and sequencing information of a testee; performing bioinformatics analysis on the sequencing data and obtaining an annotation result and a statistics result; performing quality control auditing on a quality index in astatistics result; performing interpretation personnel and flow distribution on a result which passes quality control auditing; determining a variation condition factor pool and performing variationevidence scoring, wherein the variation evidence scoring is used for assisted analysis for a genetic disease variation factor of the testee. The method and the system thereof perform bioinformatics analysis and quality control auditing based on the sequencing data, and performs interpretation personnel and flow distribution based on clinical phenotype information. Furthermore through variation evidence scoring, semi-automatic interpolation is realized and working efficiency is improved. Furthermore, a one-generation verifying primer database can be introduced, thereby greatly saving a primer designing process and reducing resource consumption. The data analysis method, the system thereof and the storage medium can be widely used for genetic disease gene sequencing data analysis and interpretation.

The invention discloses an unmanned ship path programming system and a method capable of taking sea condition factors into consideration. The unmanned ship path programming system comprises an unmanned surface vehicle, a path programming module, a control module, a GPS / IMU module, an environment perceiving module, and a sea condition monitoring module; the path programming module and the control module are arranged in the unmanned surface vehicle, and are used for programming of a series path points based on environment information and calculated ocean wave grade, and controlling the unmannedsurface vehicle to travel along the path points; the environment perceiving module is composed of an electric sea chart and a laser sensor, wherein the electric sea chart is arranged in the unmanned surface vehicle, and is used for providing static state barrier information, and the laser sensor is arranged on the front part of the deck of the unmanned surface vehicle through a support, and is used for providing barrier information; the GPS / IMU sensor is arranged on the top of the unmanned surface vehicle, and is used for providing other modules with the pose information of the unmanned surface vehicle; a navigation radar is adopted by the sea condition monitoring module, and the sea condition monitoring module is used for calculating ocean wave grade. The unmanned ship path programming system and the method capable of taking sea condition factors into consideration are reliable and reasonable, and are capable of improving the rationality of unmanned surface vehicle path programming.

The invention relates to a method for evaluating the mental health status of electrical network enterprise staff. The method includes the steps that physiological index monitoring data of the tested staff is acquired; personal factor data of the tested staff is acquired; interview data of the tested staff is acquired; mental health source evaluation is conducted through mental health source data, and the mental health source evaluation result is obtained; the physiological index monitoring data of the tested staff is acquired while the personal objective condition factor and personal subjective factor evaluation result, the mental health tendency evaluation result and the mental health type evaluation result are acquired; physiological evaluation is conducted through the physiological index monitoring data, and the physiological evaluation result is obtained. All the factors influencing the mental health status of the electrical network enterprise staff are scientifically detected out, the weights of all the influence factors are determined, and finally the comprehensive evaluation method is formed.

The invention, which belongs to the technical field of industrial control, especially relates to a multivariable-grey-neural-network-based prediction system for a residual life of industrial equipment. The system comprises a residual life precision platform for predicting the residual life of industrial equipment in real time; and when the residual life of the industrial equipment is predicted each time, industrial equipment residual life processing is executed. The processing for the industrial equipment residual life is executed by six steps. The system has the following beneficial effects: problems that the prediction precision level and the prediction capability of the modeling method can not be guaranteed and the influence on the equipment or system operation by field working condition factors are not taken into consideration can be solved; the original sequence trend becomes obvious; key performance parameters can be predicted; the precision level, the prediction capability, and the applicability of the model are enhanced; and an RBF neural network error correction model is obtained.

The invention relates to an automatic micro-moistening and irrigating system capable of totally controlling water, fertilizer, air and temperature. Water, fertilizer, air and temperature of soil are four main environmental condition factors for restraining the growth and the development of crops, wherein the change of any one single factor can cause great influence on the growth and the development of the crops, and after the change reaches a certain critical value, crops can be caused to grow slowly, stop growing and even die. The automatic micro-moistening and irrigating system comprises a water supply tank (1), wherein the water supply tank is connected with a water pipe (2), the water pipe is provided with a valve (3), a heater (4) and a fertilizer feeding pot (5) in sequence; the water pipe is connected with a group of micro-moistening pipes (6); and a computer is connected with a water, fertilizer, air and temperature control system through a sensor. The automatic micro-moistening and irrigating system is used for production of facility agriculture and precision agriculture.

The invention relates to a method for modeling the terrain property of a Wargame map by a grid matrix. The method comprises the following steps: firstly, determining an orthohexagonal grid form, i.e., a hexagonal grid, of the Wargame map, and selecting geographical environment factors which participate in modeling the terrain property; then, according to the dimension of the matrix grid and an externally tangent rectangle which surrounds each geographical condition factor, establishing an initial grid matrix on the basis of the geographical environment factors; then, determining an amount of grid points which simultaneously press and cover the geographical environment factors and the hexagonal grid in the grid matrix, and combining with the area of the hexagonal grid to calculate a pressing and covering area ratio of each geographical condition factor to the hexagonal grid; and finally, according to a terrain property judgment rule, determining the terrain property of the hexagonal grid. Through the method, the complexity of modeling the terrain property of the Wargame map is effectively lowered, and the efficiency of modeling the terrain property of the Wargame map is improved on the premise that modeling precision is guaranteed.

A process for quantitative and qualitative analysis for identifying compounds in a sample mixture involves the identification of a set of reference spectra selected according to a measured condition of the sample, which collectively define a composite spectrum which best matches a spectrum produced from the sample. The compounds associated with respective reference spectra of the identified set are the compounds that are determined to be likely to be present in the sample. Quantities of the compounds may be determined from the intensities of certain representative peaks associated with the compounds, relative to the intensity of a peak associated with a reference compound which is unaffected by the measured condition of the sample. A measured condition may be pH of the sample, for example, and an accurate measurement of pH can be obtained from the test spectrum. Thus, given a test spectrum of a sample and given a set of reference spectra, the process can identify and quantify compounds present in the sample. A process for producing reference spectra as a function of condition factor is also disclosed and a process for automatically pre-processing a spectrum from an NMR system is disclosed.

The invention discloses an SNP molecular marker related to the condition factor of Takifugu fasciatus and applications thereof. The gene sequence of SNP molecular marker source Takifugu fasciatus serotonin receptor 4 (HTR4) is as shown in SEQ ID NO:1, an SNP site exists at the 100th position of the sequence, and the base is C or G. The SNP locus disclosed by the invention is obviously related to the condition factor of the Takifugu fasciatus, and can be effectively used for molecular marker-assisted breeding of the Takifugu fasciatus, so that the breeding time of improved fish varieties can besaved. The method is accurate in operation, simple and practical.

The invention provides an electricity reminding method, device and apparatus and a computer readable storage medium. The method comprises the following steps of: if the current battery electricity ofa terminal achieves a preset electricity threshold value, obtaining the current position of the terminal; judging whether the current position has a condition for charging the terminal or not; and ifthe current position has the condition of charging the terminal, sending charging reminding on the terminal. According to the method, the problem that the low-electricity reminding is blind in the prior art is solved; and condition factors of the current positions of terminals are comprehensively considered, so that the intelligence and personality of terminal electricity reminding are improved and the effectiveness and pertinence of reminding information are improved.

The invention discloses an imprecise condition estimation method for an outage probability of power equipment. The method comprises the steps of taking related running condition factors, which influence a running state of the power equipment, as sub-nodes, taking the running state of the power equipment as a father node, and constructing a reliability network of equipment outage probability estimation; calculating prior probabilities of the power equipment in different running states and a condition reliability set corresponding to the sub-nodes according to related running condition history data of the power equipment; and implementing probabilistic reasoning based on the prior probabilities and the condition reliability set corresponding to the sub-nodes in the reliability network according to equipment running conditions given in a target time segment of estimation, and finally obtaining an imprecise condition estimation result of the outage probability of the power equipment under the running conditions given in the target time segment of estimation. According to the method disclosed by the invention, an important basic parameter estimation means can be provided for assessing the running reliability of a power system lack of historical statistic data; and the method has wide application potential.

The invention provides a thin-skin walnut indoor micro-branch engrafting method, belonging to the walnut vegetative propagation technique. The micro-branch engrafting method uses the health tissue culture seedlings of good thin-skin walnut breed (strain) and the health tissue culture seedlings are cut into vaneless stem segments in length of 2.0cm-4.0cm as scions and the scions are engrafted on rootstocks in stem diameter of about 3mm-7mm, and the engrafting cuts are banded using plastic strips and the engrafted seedlings are planted in the nutrient bags and the nutrient bags are capped to keep humidity and the nutrient bags with engrafted seedlings are cultured in a greenhouse of 22-28 DEG C. When the branches to be engrafted grow into 3.0cm-5.0cm, the seedlings are trained and the engrafted seedlings are transplanted into big field after 30 days. The engrafting survival rate can be more than 70%. The engrafting method is free from the limitation of the season condition factor with features of high propagation coefficient, quick seedlings establishment speed, utilization of factory seedlings raising. The engrafting method is suitable for improving the breeds and enlarging the scale of the walnut industry and developing the forestry and fruit industry.

The invention relates to a hybrid power vehicle shifting control optimization method in a braking process; the optimization method comprises an upshift control method and a downshift control method; the downshift control method comprises the following steps: building a vehicle dynamics model, and building downshift rule target functions, wherein the downshift rules comprise an economical downshift rule, a safety type downshift rule and a dynamical type downshift rule; DOE sampling, and optimizing each sampling point so as to obtain an optimal downshift speed vs and a target function value corresponding to the optimal downshift speed; comparing the target function value corresponding to the optimal downshift speed with the target function value corresponding to a non-downshift status, thus obtaining a shifting condition factor R, and determining whether to shift or not according to the shifting condition factor R; forming a shifting rule determined by a vehicle acceleration as, a motor torque Tm and the optimal downshift speed vs. The novel method allows the hybrid power vehicle to have more reasonable shifting strategies in the braking process, thus improving vehicle fuel oil efficiency, and reducing gas emission.

The invention provides a molecular identifier related to laying duck egg laying and egg quality traits and application thereof. The molecular identifier is located in part of coding area sequence of alaying duck LRRTM1 gene, the nucleotide sequence of the molecular identifier is as shown in SEQ ID NO:1, the length of the sequence is 1427 bp, and there exists T / C biallelic mutation at the 1259 bp of the sequence; the single nueleotide polymorphism (SNP) of the sequence can be taken as the related molecular identifier of the egg laying duck egg laying and egg quality related trait correlation analysis. The invention further discloses a screening method of the molecular identifier and the application of the molecular identifier in the laying duck egg laying and egg quality related traitcorrelation analysis. The application of the molecular identifier in laying duck egg laying and egg quality trait auxiliary selection has the advantages that a detection method is rapid and accurateand not influenced by the condition factors of the culturing environment.

The invention relates to a fuzzy comprehensive evaluation method of a geological strength index, and the method is characterized in that a rock joint group number, a joint interval and a rock completeness coefficient are used for describing rock structural characteristics, a large proportional scale waveform coefficient, a small proportional scale smooth coefficient and a joint erosion coefficient are used for describing conditions of a structural plane, and a fuzzy comprehensive evaluation set is established according to the fuzziness, hierarchy and difference of the evaluation index influencing the geological strength index value; a membership function of rock material characteristics is constructed, and the weight of the evaluation factor is determined on the basis of the layering analysis method; and finally a rock structural characteristic and structural plane condition factor evaluation matrix is established according to the geological exploration result and the test data, and the value of the geological strength index is determined according to the maximal subordinate principle. The comprehensive evaluation method is strong in pertinence, high in accuracy, capable of reasonably combining the geological investigation result, the test result, statistical data and expert opinions, capable of reducing the subjectivity in decision-making of a researcher and easy to realize.

PCT No. PCT / DK97 / 00341 Sec. 371 Date Dec. 29, 1997 Sec. 102(e) Date Dec. 29, 1997 PCT Filed Aug. 22, 1997 PCT Pub. No. WO98 / 10079 PCT Pub. Date Mar. 12, 1998Expression vectors capable of being replicated in lactic acid bacterial cells comprising a promoter region comprising (a) a promoter sequence element the function of which is regulatable by an environmental or growth condition factor and (b) at least one further nucleotide sequence element, the position, orientation, presence and / or sequence of which element has a regulatory effect on the expression of a gene operably linked to the promoter region in which vectors the position, orientation, presence and / or sequence of at least one of said elements (a) or (b) is modified relative to the position, orientation, presence and / or sequence of the corresponding non-modified element whereby the expression of the gene is altered, and a lactic acid bacterium which is transformed with such a vector as defined above are provided. The recombinant cells containing such a regulatable or inducible gene expression system are useful as food or feed starter cultures or as strains for the production of gene products such as pharmaceutically or immunologically active compounds including oligo- or polypeptides derived from a Mycobacterium species including M. tuberculosis.

The invention discloses an Eleotris acanthopoma fry breeding method and an Eleotris acanthopoma fry breeding pond body system. The method comprises the following steps of: selecting Eleotris acanthopoma parents, pairing the parents according to the ratio of females to males, breeding doughtily, preventing and controlling diseases, reproducing and breeding fries. The Eleotris acanthopoma fry breeding pond body system comprises a water purification pond, a spawning pond, a fry breeding pond and an Eleotris acanthopoma fry temporary culture device which is arranged in the fry breeding pond. By creating natural conditions and all kinds of condition factors during the reproduction of Eleotris acanthopoma to breed before the reproduction, the rate of fry emergence of sperms and follicle of Eleotris acanthopoma is improved and the survival rate of fertilized eggs is further improved. Moreover, by taking disinfection measures in all environments, the morbidity of the fries is reduced. The arranged simple Eleotris acanthopoma fry temporary culture device can be used for the hatching of the fertilized eggs and the culture of the fries at the same time. The space occupied for culture and the cost are reduced. The Eleotris acanthopoma fry breeding method and the Eleotris acanthopoma fry breeding pond body system are suitable for low-cost culture.

The invention discloses a mine fire risk factor weight determining method. The mine fire risk factor weight determining method is characterized in that a weight determining method based on a Skowron difference matrix is provided to get the relationship between a mine fire influence factor and a fire risk. By adopting the method, fuzzy data in expert information U can be processed, and a logical inference capability is achieved; weights influencing mine fire risk factors can be updated according to the accumulated feature of U; condition factor weights and the sequence thereof under U can be obtained directly without giving consideration to the compatibility of the difference matrix, and a mine fire rating system and standard are established; the method can be applied to determination of mine fire factor weights.

The invention discloses a soil bin testing device suitable for the testing of running performances of a wheel, and the device comprises a soil bin system, a single-wheel testing system, a plough loosening flattening system and a control system. The single-wheel testing system is disposed on the soil bin system and makes reciprocating motion in the length direction of the soil bin system. The plough loosening flattening system is disposed at the front part of the single-wheel testing system, and the control system is electrically connected with the soil bin system, the single-wheel testing system and the plough loosening flattening system. The device can achieve the simulation of different bearing conditions of the wheel, can control the speed and slippage rate, meets the requirements of the testing of the running performances of different types of wheels under different soil conditions, achieves the automatic control of a testing process, collects and storage the related running performance parameters in real time, can achieve the research of the impact on the trafficability from a running condition factor, a wheel related factor and a soil factor through an indoor test, and is advantageous in that the test conditions and environment factors can be controlled, the test repeatability is good and the test precision is high.

The invention relates to a rice disease image detection method integrating multiple context deep learning models. Compared with the prior art, the rice disease image detection method can assist in eliminating a defect that rice disease image detection does not consider relevant condition factors of the rice disease image detection. The method of the invention includes the following steps that: training samples are collected and pre-processed; rice image context information is integrated on the basis of deep learning, so that a rice disease image detection model is obtained; the space, location, temperature and humidity information of a rice image to be processed is collected and preprocessed; and the specific position of a disease in the rice image is marked. According to the rice diseaseimage detection method integrating multiple contextual deep learning models of the invention, the features of the disease image itself are considered, and relevant factors such as space, time, temperature and humidity at the time of the collection of the disease image are also considered; a rice disease image global context training model, a rice disease image local context training model and a rice disease attribute constrained context training model are integrated; and therefore, the detection and recognition capacity of the method of the invention for the rice disease image under a field complex application condition can be improved, and the detection rate of the rice disease image can be improved.

The invention discloses a selecting method and system of application programs with a same function in a mobile terminal. The method comprises following steps of determining a function corresponding to an action content initiated by a user, searching the application programs capable of realizing the function so as to obtain an application program set; obtaining the current environment parameter of the mobile terminal and the operation related parameter of each application program; and selecting the application program capable of realizing the function for the user in an optimum stateby using the environment parameter and the operation related parameter. According to the method and the system disclosed by the invention, under the condition of comprehensively considering the environment factor of the mobile terminal and the operation condition factor of the application programs, the optimum application program is intelligently selected and provided to the user from the application programs with the same function; and further the user experience is improved.

The invention discloses a power distribution network power supply reliability prediction method based on big data correlation analysis. The power distribution network power supply reliability prediction method comprises steps that a rough set theory is used to mine condition factors strongly related to reliability of a power distribution network from acquired power distribution network big data, and training learning is carried out by using an established GA-BP neural network to generate a prediction model according to the extracted condition factors and historical statistic data of regional power distribution network reliability indexes. The accurate and fast evaluation of the power distribution network power supply reliability in a target year is realized.

A method of determining an orbit of an orbital object includes computing predicted tracking measurement values based on the orbit computed from the initial conditions factoring in any modeled environmental forces and realistic maneuvers; computing the differences between the actual and predicted tracking measurements; determining an improved estimate of the initial conditions that reduces the measurement errors using a minimization or root finding algorithm; after the algorithm has converged, reviewing the hypothetical maneuvers in the force model, taking each value and determining which values came up as near-zero in the minimized solutions and which values came up as those of measurable thrust; determining overall burn duration using the first and last burn times; determining the thrust profile of the orbital object over the observation period using the integrated thrust values; and determining the actual maneuver based on the observation data.