176 results about "Attenuation function" patented technology

The invention discloses a traffic network toughness diagnosis method under flood disasters based on a space-time diagram neural network, and relates to the crossing field of traffic engineering and artificial intelligence. The method comprises the following steps: collecting traffic topology, flood monitoring and traffic flow data, and carrying out space-time alignment; a flood coupling dynamic space-time diagram is constructed, a water depth-traffic capacity response mechanism is introduced, and real-time mapping from a disaster physical state to a network topology is realized by utilizing an attenuation function meeting physical monotonicity constraint and dynamically updating an edge weight of a diagram structure according to real-time water depth; inputting the dynamic graph into a pre-trained space-time graph neural network model, extracting space-time evolution characteristics and outputting a toughness diagnosis result; model training adopts a toughness label generated based on an anti-fact baseline to carry out supervised learning, and introduces a physical constraint loss function. According to the method, the problems of decoupling of disaster features and graph structures and unavailability of toughness labels in the prior art are solved, and the physical consistency and accuracy of diagnosis are improved.

The invention relates to the technical field of electroencephalogram signal processing, and provides a brain-computer AI glasses electroencephalogram signal multi-dimensional quality dynamic detection method, which comprises the following steps: preprocessing collected electroencephalogram signals; performing task frequency band component analysis on the channel signals subjected to the matrix rank analysis, and calculating a power proportion of a target frequency band; performing maximum gradient analysis on the channel signal, and calculating the maximum gradient value of the channel signal; performing root-mean-square analysis on the channel signal, and calculating a root-mean-square value of the channel signal; performing fluctuation amplitude analysis on the channel signal, and calculating a peak-to-peak value of the channel signal; performing brain hemisphere symmetry analysis on the left and right homologous channel signals, calculating the correlation and mean square error of the channel signals, and setting a dynamic threshold according to the frequency band of the channel signals; obtaining an electrode impedance value, and mapping the electrode impedance value into an impedance score through a preset exponential attenuation function; the final quality score of the channel is obtained, and dynamic detection and real-time score updating of the electroencephalogram signal quality are achieved.

The invention discloses a physical-data dual-drive retaining wall catastrophe robustness evaluation method, and relates to the technical field of structure catastrophe evaluation and computer science crossing. Aiming at the problems that an existing retaining wall catastrophe robustness evaluation method cannot correct physical model errors in real time and is insufficient in accuracy, the invention provides a retaining wall catastrophe process robustness evaluation method driven by fusion of a physical model and a neural network. The method comprises the following steps: 1, carrying out time discretization and parameter vectorization on retaining wall catastrophe monitoring parameters; 2, constructing a performance attenuation function based on the physical model; 3, updating an implicit damage state in combination with a neural network Cell module; 4, correcting an error through a feedforward network to obtain a total performance attenuation function; and 5, finally calculating a robustness index and outputting a corresponding robustness grade, thereby realizing quantitative evaluation of the retaining wall catastrophe robustness. Reliable quantitative support can be provided for retaining wall design optimization, operation monitoring and post-disaster recovery evaluation.

The invention relates to the field of robot navigation, and particularly discloses a spatial perception observation information quality evaluation method and system, a terminal and a medium, and the method comprises the steps: converting the measurement information of each dimension into a normalization probability according to the measurement target of each dimension; according to the concept of entropy in the information theory, the normalized probability of each dimension is converted into a computable entropy value; a downstream task weight coefficient is introduced for the entropy value of each dimension, the multi-dimensional entropy value after the downstream task weight coefficient is introduced is mapped into a physical interpretable confidence coefficient in a [0, 1] interval through an exponential attenuation function, and the confidence coefficient explicitly represents the uncertainty of observation information of each dimension. According to the method, a space perception quality evaluation system with mathematics interpretability, scene adaptation and real-time calculation is formed, multi-source uncertainty is mapped into executable confidence, and multi-dimensional accurate evaluation of intelligent agent space perception observation information is achieved.

The invention discloses a well mining unmanned driving fault data processing method and system, and relates to unmanned driving. The method comprises the following steps: obtaining multi-source heterogeneous data; performing space-time fusion processing on the multi-source heterogeneous data to obtain a fused data set; inputting the fused data set into a pre-trained LSTM-Attention prediction model, and outputting a fault probability prediction value of the unmanned vehicle; calculating a fault risk score according to the fault probability prediction value in combination with the fault influence level; according to the fault risk score, triggering a preset fault processing mechanism of a corresponding level; aiming at the problem that the influence of water mist spraying on equipment operation is not considered in traditional well industrial and mining unmanned driving fault prediction, the method introduces UWB positioning-based vehicle and spraying point distance calculation, adopts a Gaussian distance attenuation function to quantify a spraying influence weight, constructs a temperature compensation factor alpha fused with a spatial distance and a time accumulation effect, and performs fault prediction on equipment operation according to the temperature compensation factor alpha. And the compensation factor is used for dynamically correcting the temperature of the motor and the like, so that the interference of underground dust falling spraying on the temperature monitoring of the equipment is effectively eliminated.

The invention relates to the technical field of computer vision and robot positioning, and discloses a dynamic 3DGS-SLAM method and system based on Gaussian pyramid and adaptive densification. The method comprises the following steps: generating a semantic mask through real-time dynamic target detection so as to distinguish a static background from a dynamic object; constructing a 3D Gaussian map model of the scene; rendering images in parallel on a full-resolution view and a down-sampling resolution view by adopting a motion perception Gaussian pyramid rendering method, and fusing rendering results by utilizing a dynamic mask so as to eliminate motion edge artifacts; a self-adaptive densification strategy based on a monotonic attenuation function is adopted, the initialization radius of the Gaussian ellipsoid is dynamically adjusted based on the training progress, and high-density initialization and progressive redundancy pruning are executed to optimize the geometric fidelity; and finally, performing coarse-to-fine camera pose optimization, and outputting a precise pose and a high-fidelity static map. According to the method, the problems of tracking drift and rendering artifacts under dynamic interference are effectively solved, and the positioning precision and the rendering quality are improved.

The invention discloses an aging model and aging state prediction method and system of a retired power battery. An aging characteristic parameter sequence of a battery cluster is obtained; the aging characteristic parameter sequence is divided into multiple sections; in each section of the aging characteristic parameter sequence, different types of attenuation functions are adopted for fitting, and the membership probability of each type of attenuation function to each section and the weighted sum of each type of attenuation function serve as a fusion fitting function of each section; splicing the fusion fitting functions of all the sections to obtain an aging model of the retired power battery; clustering the fusion fitting function of each segment to obtain a typical fusion function of each cluster in each segment; establishing an aging state prediction model, wherein the aging state prediction model comprises an input layer based on a Transform network, a physical constraint layer based on an attention mechanism, a composite loss calculation layer and a feedback layer; an aging characteristic parameter fusion sequence output by the aging state prediction model is an aging state prediction result of the target battery cluster; and precise modeling and dynamic prediction of the aging state of the battery are realized based on finite parameters.

The invention discloses a gradient heating control system and method for a disposable medical endoscope. The control method comprises the following steps that temperature values Ti are collected in real time through three temperature sensor sets distributed on the front section, the middle section and the rear section of an endoscope body; the temperature gradient delta Tj of each section is calculated, and the calculation result is compared with a set threshold value theta; when any temperature gradient delta Tj exceeds a threshold value theta, a gradient compensation algorithm is started, and heating power output Pout is calculated; and according to a compensation calculation result, the power output of each heating sheet is dynamically adjusted, so that the temperature gradient delta Ti is within a set value. The temperature sensor group is arranged on the endoscope body, the power output of the heating sheet is dynamically adjusted by adopting a self-adaptive gradient compensation algorithm, and the gradient compensation coefficient alpha is adjusted by introducing an exponential attenuation function, so that accurate temperature control, adaptation to different operation modes, reduction of temperature fluctuation and improvement of equipment reliability are realized.

The invention relates to the technical field of bolt connection, in particular to a method for predicting the working condition of a bolt connection structure based on representation of pretightening force relaxation. The invention provides a double-exponential attenuation function, parameter identification of different functions is carried out, the double-exponential function which is simple in structure and good in characterization is obtained, the fitting precision of the double-exponential attenuation function reaches 99.3%, and the bolt pretightening force relaxation rule can be accurately characterized. According to the method, a pre-tightening force relaxation rule function is introduced into an Iwan model to represent the Iwan model under the relaxation condition meeting the actual condition, the relation between various parameters and pre-tightening is analyzed, a mathematical expression is constructed by adopting a least square method, the pre-tightening relaxation rule in a period is equivalent to the pre-tightening relaxation rule of tangential displacement and loading time, and the pre-tightening force relaxation rule is obtained. And constructing an Iwan model density function under a relaxation condition based on various variable parameters. According to the method, nonlinear behaviors such as energy dissipation and rigidity degradation can be predicted, and particularly, a relatively accurate method is provided for predicting various indexes under the working condition of bolt pretightening force relaxation.

The invention relates to the technical field of 3D scanning, and discloses a real-time alignment highlight curved surface metallographic 3D scanning method and system, and the method comprises the steps: extracting normal vector features from a multi-view point cloud, calculating an approximate geodesic distance, and constructing a normal vector geodesic distance correlation graph; constructing a constraint propagation intensity matrix through a geodesic distance inverse ratio and a normal vector included angle exponential attenuation function, and enabling the constraint propagation intensity matrix to act on a multi-view point cloud registration residual error to generate a closed-loop error energy field; constructing a graph cut network node at the gradient extreme value of the energy field, and executing a minimum cut algorithm under geodesic constraint by taking the integral value of the energy field as the side capacity to complete global point cloud fine registration; according to the method, the local geometry and the global topology are combined through the normal vector geodesic association diagram, the problem that the registration accumulative error breaks out at the closed loop position due to the fact that the highlight curved surface metallographic surface lacks texture features is solved, and real-time accurate alignment of the highlight curved surface metallographic workpiece multi-view point cloud on an automatic detection production line is achieved.

The invention discloses an image fusion enhancement method for a multi-signal-source liquid crystal splicing screen, and relates to the technical field of large-screen display control, and the method comprises the steps: building a virtual coordinate system taking a physical gap as a reference at an input end, carrying out the decoding, time synchronization and unified mapping of a multi-source heterogeneous signal, converting the multi-source heterogeneous signal into a unified color space, and carrying out the image fusion enhancement of the multi-signal-source liquid crystal splicing screen. The display consistency of different signal sources is ensured; then, a compensation model based on a brightness attenuation function is introduced into the splicing boundary area, edge pixel brightness is subjected to self-adaptive correction, and brightness unevenness caused by physical gaps is relieved; calculating the content complexity based on the row-level gradient magnitude in the fusion screen area, dynamically constructing a content-sensitive fusion weight, and carrying out weighted fusion on the images on the two sides to generate a transition image frame; and through joint output of the transition image frame and the original side image frame, visual seamless connection of the splicing gap area is realized. Therefore, the integral continuity and visual experience of tiled display are effectively improved while the image detail fidelity is ensured.

The invention relates to a laser radar point-to-line weighted matching method based on edge point quality evaluation, and belongs to the technical field of measurement. The method solves the problems that in traditional point-to-line matching, due to the fact that the quality of edge points is not evaluated, the pose estimation precision is low, and the robustness of an unstructured scene is poor. According to the technical scheme, a preprocessing module screens candidate edge points through projection point cloud, target segmentation and roughness calculation; the position judgment module classifies the candidate points as middle, left or right edge points according to the category consistency of the adjacent points; the direction consistency judgment module calculates a direction standard deviation and screens effective edge points; and the dynamic weighting module allocates weights according to an exponential attenuation function, and optimizes the pose through weighting residual errors. The method has the advantages that the pose estimation precision is remarkably improved, the weak structure environment adaptability is enhanced, the calculation efficiency is optimized, and redundant iteration is avoided.

The invention discloses a thermal infrared three-dimensional modeling method and system based on linear Gaussian primitives, and the method comprises the steps: obtaining an infrared image of power transformation equipment, so as to construct a multi-view image set of the power transformation equipment; generating a sparse point cloud from the multi-view image set to construct an initial Gaussian primitive, and converting the initial Gaussian primitive into a linear Gaussian primitive through a linear attenuation function; constructing a thermal infrared physical model, and inputting the image set and the primitives into the physical model to obtain a thermal infrared synthetic image; constructing a composite loss function to calculate an error value of the infrared image and the composite image, calculating a gradient of the composite image, and carrying out back propagation iteration on the error value and the gradient to update parameters of the physical model; according to the method, the thermal infrared physical model is constructed, the atmospheric transmission effect and the thermal diffusion process are modeled, and the thermal loss is compensated by combining a residual addition mechanism, so that the problem of thermal radiation confusion caused by depth information attenuation is solved, and high-precision three-dimensional rendering under the dynamic illumination condition is realized.

The invention discloses a substation emergency lighting self-service power supply system, and relates to the technical field of emergency lighting power supply, and the system comprises the following steps: installing a sensor and a communication module, and setting basic parameters; collecting data, dynamically calculating illumination requirements, and compensating visual delay of human eyes; reading battery parameters, and quantifying the aging degree and the residual available capacity of the battery; calculating the power supply priority of each node by combining the emergency exit position based on the adjacent node state; the LED driving current is dynamically adjusted according to the priority, and gradient switching is adopted when the brightness changes in a large range; the low-electric-quantity node automatically initiates help seeking, and the surrounding nodes reduce own brightness in proportion; operation data are uploaded regularly, algorithm parameters are optimized, and a positioning signal is activated to guide maintenance when the battery is seriously lack of electricity. According to the invention, through the double-variable dynamic model coupling the ambient light attenuation compensation factor and the battery health degree attenuation function, the error accumulation of a single electric quantity criterion is eliminated, so that the power supply duration prediction better fits the real working condition.

The invention discloses an AGV full-life-cycle intelligent operation and maintenance method based on a twin map and reinforcement learning, and belongs to the technical field of equipment operation and maintenance management, and the method comprises the steps: employing an edge-level dynamic attenuation function and a node-level economic weight operator for aggregation, and obtaining a health vector containing a whole vehicle risk score and a part first-level risk identifier; the method comprises the following steps: training a reinforcement learning agent according to a three-section reward function comprising production line instant income, health improvement income and future risk deduction, and determining an operation and maintenance strategy weight file by adopting a profit-oriented gradient update mode optimization strategy with risk suppression factors; and carrying out equipment operation and maintenance management on the AGV in workshop operation according to the strategy weight file. According to the method, dynamic risk propagation and economic quantitative evaluation are adaptively fused under the real-time working condition of a workshop, and a comprehensive optimal decision of maintenance opportunity and production line income is realized under the condition of non-stop observation through a reinforcement learning strategy closed-loop driving AGV fleet preventive maintenance and scheduling method.

The invention relates to a control strategy correction method and device based on the health state of energy storage converter equipment. The current value and the current efficiency of health influence parameters of an energy storage converter are monitored and collected in real time; according to the current value and the rated value of the health influence parameter, obtaining the standard exceeding proportion of each parameter relative to the rated value; obtaining efficiency loss according to the rated efficiency of the energy storage converter under the current working condition and the corresponding current efficiency; respectively taking the exceeding proportion and the efficiency loss as independent variables, and combining an attenuation function, a penalty function and a corresponding weight to obtain a current health state evaluation value of the energy storage converter equipment; and correcting a control strategy of the energy storage converter equipment based on the health state level of the energy storage converter equipment. According to the method, self-adaptive control strategy correction of the energy storage converter based on the equipment health state is realized, and the equipment operation reliability and economic benefits are remarkably improved.

The invention discloses a Bluetooth device rapid pairing method and system based on multiple scenes. The method comprises the steps that scene features, device historical pairing, demand features, an efficiency set and signal intensity data are acquired; performing time sequence sampling on the signal intensity, calculating a stable distance value in combination with the correction model, and weighting historical data by using a time decay function to generate a historical weight score; scene correlation scores are obtained through scene model matching, demand features are mapped into demand vectors, an efficiency set is subjected to standardization processing, and function matching scores are calculated through cosine similarity. And performing weighted summation and normalization processing by integrating the stable distance, the historical weight, the scene correlation and the function matching to obtain an equipment priority score. And finally, carrying out intelligent grouping and conflict resolution on the equipment library based on the scores, generating a dynamic pairing strategy and executing connection. According to the method, rapid pairing of the Bluetooth equipment can be realized.

The invention discloses a house safety level prediction method and system based on a Bayesian network, and relates to the technical field of house safety evaluation. The method comprises the following steps: acquiring structural characteristic parameters, environmental influence factors and historical state information of a target house; performing three-level quantization processing on the structural characteristic parameters to obtain a structural evaluation matrix, and constructing a dynamic attenuation function based on the environmental impact factors to calculate a dynamic attenuation weight; generating a historical state index based on the historical state information through a multi-dimensional feature fusion technology; based on the structure evaluation matrix, the dynamic attenuation weight and the historical state index, calculating the structure redundancy as a hidden variable; constructing a three-layer Bayesian network; and probability propagation calculation is carried out through a Bayesian network inference engine, and the house safety level of the target house is determined according to the probability distribution of the output layer. By implementing the technical scheme provided by the invention, the actual safety level of the house can be accurately evaluated and predicted.

A computer having a system for mitigating mechanical rattle arising due to a mechanical coupling of an audio output transducer to a part of the computer device, the system comprising: a processing subsystem configured to receive an input audio signal and to output a drive signal for driving the audio output transducer to produce a transducer output, wherein the processing subsystem is configured to selectively apply an attenuation function to the input audio signal to attenuate a signal component of the input audio signal at a frequency that causes mechanical rattle in the computer; and an analyser subsystem configured to receive the input audio signal and to output a control signal to the processing subsystem to control application of the attenuation function to the input audio signal by the processing subsystem based on a spectral content of the received input audio signal; wherein the attenuation function is based on characteristic acoustic behaviour of the computer.

The utility model relates to the technical field of steam vapor-liquid separation devices, and provides a steam vapor-liquid separation device with a silencing function under a negative pressure condition, which comprises a tank body device, a silencing device, a spraying device, a negative pressure device and a drainage device, the silencing device is arranged on the tank body device, one part of the silencing device is located in the tank body device, the spraying device is arranged on the negative pressure device, one part of the spraying device is located in the negative pressure device, and the drainage device is located outside the tank body device and communicated with the tank body device. According to the steam-liquid separation device with the noise reduction function under the negative pressure condition, steam is conveyed into the tank body device through the noise reduction device, the steam in the tank body device is cooled through the spraying device, the steam in the tank body device is rapidly discharged through the negative pressure device, the steam in the tank body device is sealed through the water drainage device, and the steam in the tank body device is discharged through the water drainage device. Therefore, noise is reduced, and steam leakage is isolated.

The invention discloses a construction settlement dynamic monitoring method based on data analysis, and relates to the technical field of construction engineering monitoring and data-driven modeling, and the method comprises the steps: combining a causal diagram modeling method with a multi-source data analysis mechanism, achieving the structural modeling and dynamic correlation recognition of multi-level observation variables in a construction settlement region, and achieving the dynamic monitoring of the construction settlement. According to the method, a causal structure is updated in real time under multi-source heterogeneous data flow through a fast conditional independence test algorithm in combination with a modular skeleton diagram updating mechanism, logic consistency of a monitoring model is kept, and a multi-objective function optimization algorithm is combined with DAG constraint and a direction confidence coefficient matrix, so that a multi-source heterogeneous data flow is optimized. According to the method, automatic judgment and global optimal causal direction reasoning of conflict causal relationships are achieved, a priori knowledge attenuation function is combined with a data-driven confidence fusion model, time sequence dynamic evaluation of causal edge reliability is achieved, and self-evolution of a knowledge system is achieved.

The utility model provides a control module with a damping function, which belongs to the technical field of control modules and comprises a control module, a damping component and a radiating component. A mounting frame is arranged on one side of the control module, a fixing seat is mounted in the mounting frame, a mounting sleeve is mounted on the periphery of the inner wall of the mounting frame, a movable rod is arranged in the mounting sleeve in a penetrating manner, one end of the movable rod is connected with the bottom of the fixing seat, and when the control module is fixed in the fixing seat, the movable rod is fixed on the mounting sleeve. When the control module vibrates, the movable rod moves towards the interior of the mounting sleeve, the limiting rings are mounted on the surfaces of the movable rod and the mounting sleeve, and the movable rod moves, so that the damping springs arranged in the middles of the limiting rings absorb vibration and dissipate the vibration through self stretching, the vibration amplitude is reduced, the control module has the damping function, and the sensitivity of the control module is guaranteed.

The invention relates to a longitudinal relaxation time calculation method, nuclear magnetic resonance imaging equipment and a storage medium, and the method comprises the steps: executing a pulse sequence, and collecting a first multi-echo signal; the pulse sequence comprises a radio frequency pulse and a readout gradient, and the radio frequency pulse comprises a first excitation pulse and a plurality of second excitation pulses in a repetition time of the pulse sequence; the first multi-echo signal is a multi-echo signal acquired after executing a second excitation pulse; performing image reconstruction on the first multi-echo signal to obtain a multi-echo image; calculating target signal intensity according to a signal attenuation function and the information of the multi-echo image; and calculating the longitudinal relaxation time according to the target signal intensities of the plurality of repetition times. According to the invention, after a small number of first excitation pulses are applied, accurate longitudinal relaxation time distribution is obtained, and the problem of low calculation efficiency in the prior art is solved.

The invention discloses an intelligent drilling path planning method and system for a multi-layer thin plate, and relates to the field of intelligent path planning. Firstly, task analysis is conducted on hole sites according to material attributes and drilling parameters, and single-hole generation heat and a temperature attenuation function are calculated through thermophysical model parameterization; and thus, a minimum cooling interval time matrix of the hole site set is obtained. On the basis, the tool moving speed and the drilling time consumption are comprehensively considered, a time sequence diagram fused with the cooling constraint is constructed, and global path searching and optimization are conducted through a space-time A * algorithm. According to the method, a traditional static planning problem which purely pursues the shortest geometric distance is converted into a spatio-temporal dynamic optimization problem which meets a thermal safety threshold value, cooling waiting time and moving travel time are automatically balanced through an algorithm, the problem of material performance degradation caused by local heat accumulation in the prior art is effectively solved, and the service life of the material is prolonged. The drilling quality and efficiency of the multi-layer thin plate are both improved.

An object of the present disclosure is to predict an occurrence probability of a violation with high accuracy.Therefore, content of the present disclosure is a violation prediction apparatus that predicts an occurrence probability of a violation, and is configured to: evaluate conversation data that includes conversation partner information for identifying a partner of a conversation and indicates a conversation content and a conversation situation, thereby obtaining a conversation content evaluation value and a conversation situation evaluation value; evaluate a relationship with the partner of the conversation based on relationship data that indicates a human relationship with a target user and on the conversation partner information, thereby obtaining a relationship evaluation value; calculate a social interaction effect based on the conversation content evaluation value, the conversation situation evaluation value, and the relationship evaluation value; calculate a time attenuation value of the social interaction effect based on a time attenuation function; and calculate an occurrence probability of a violation.

The invention provides a sea area influence measurement method and device for a coastal zone land area development level, and belongs to the technical field of information suitable for administrative purposes. The method comprises the following steps: generating a plurality of equidistant sampling lines perpendicular to a coastline along the coastline, wherein each sampling line extends a preset distance towards a land area and a sea area; acquiring an intersection point of each sampling line and the coastline as a sampling intersection point SIP; calculating an index average value of all pixels penetrated by each sampling line based on land social economic index data, and assigning the average value to the corresponding SIP to form a land development level point with vertical representativeness; carrying out nearest distance matching operation on a target pixel in the sea area and each SIP (Session Initiation Protocol); and according to the Euclidean distance between the target pixel and the SIP, performing attenuation processing on the land development level represented by the SIP by adopting a Gaussian attenuation function to obtain a sea area social economic influence score of the target pixel, thereby realizing fine description of transmitting the land development level to the sea area.

The invention relates to the technical field of precise speed reducer manufacturing, and discloses a cycloidal gear tooth surface flexible modification method based on multi-parameter dynamic compensation, which comprises the following steps: establishing an elastic deformation calculation model based on a Hertz contact theory and dynamic load characteristics, and introducing contact rigidity, a dynamic coefficient and a rotating speed index to correct deformation; constructing a thermal deformation compensation model based on a thermal-mechanical coupling theory, and considering a material thermal expansion coefficient, a working temperature rise and a rotating speed influence factor; a modification curve is constructed by adopting a third-order Fourier series, and flexible regulation and control of the tooth surface profile are realized by optimizing a coefficient proportional relation; and a manufacturing error self-adaptive matrix is constructed based on measurement data of the laser interferometer, and the exponential attenuation function is adopted to distribute the compensation amount, so that the accurate regulation and control of the tooth surface microscopic contour are realized. According to the joint reducer, the contact stress can be reduced by 14% or above, the transmission return difference is controlled within 0.52 arcmin, the service life is prolonged to 66000 hours, and the requirements for high precision and high reliability of the joint reducer of the industrial robot are met.

An in-ear hearing protection device is provided. The in-ear hearing protection device includes a microphone (410) configured to receive environmental sound. The in-ear hearing protection device also includes a processor (420) configured to perform an attenuation function on the received environmental sound to provide an attenuated sound. The in-ear hearing protection device also includes a speaker (440) configured to play the attenuated sound. The in-ear hearing protection device also includes a communication module (430) configured to receive second attenuation function details from a second in-ear protection device. The processor is configured to calculate first attenuation function details and compare the first attenuation function details to the second attenuation function details. The attenuation function performed is based on one of the first attenuation function details and the second attenuation function details.

The invention discloses a carbon emission reduction behavior quantitative evaluation method and system. The method comprises the following steps: deconstructing equipment-level and system-level emission reduction behavior units based on an energy topology network; historical data are collected, a climate correction coefficient and an equipment attenuation function are loaded, and a dynamic datum line is generated; real-time monitoring, material balance and activity level data are fused, and the absolute emission reduction of a single body is calculated through cross validation; quantizing the behavior interaction effect by adopting a cooperative coefficient matrix, and outputting the calibrated net emission reduction; and finally generating a three-dimensional evaluation report of a time axis, a space axis and a responsibility axis. According to the method, the problems of behavior association deficiency, dynamic adaptability insufficiency and synergistic effect quantification blank in traditional evaluation are solved, and accurate evaluation of park carbon emission reduction quantification is supported.

The invention provides an aeromagnetic data-based interior high-precision inversion method, and the method comprises the steps: carrying out the preprocessing of the aeromagnetic data of a target region, eliminating the noise and interference, and extracting the region magnetic anomaly information related to a deep interior; constructing a remanence intensity model based on a depth attenuation function, and obtaining the remanence intensity of each grid point of the target area according to the target area and the remanence intensity model; based on the residual magnetism intensity model, establishing a non-linear attenuation model of the residual magnetism intensity along with the depth, and obtaining the magnetic anomaly intensity generated by each depth layer in the target area on the earth surface by using the non-linear attenuation model; and inputting the regional magnetic anomaly information, the residual magnetism probability parameter, the geological constraint and the magnetic anomaly intensity into the interior inversion model to obtain an interior depth prediction value of the target region. According to the method, the influence of residual magnetism on the magnetization direction is considered, and the precision of interior inversion is improved.