197 results about "Load cycle" patented technology

There is provided a system for monitoring payload for a load-lifting vehicle. The vehicle has a lifting arm and a hydraulic actuator operatively connected to the lifting arm. The system has a means for correlating actuator pressure within the actuator at a set position of the lifting arm with weight for generating a calculated weight of a payload. The system has a means for generating a payload pattern relating actuator pressure to time as the lifting arm moves the payload through a load cycle. The system has a means for comparing the payload pattern with a set pattern relating pressure to time corresponding to said calculated weight of the payload and storing the calculated weight of the payload into memory if the deviation between the patterns is equal to or less than a certain amount.

Software and methods for extending preexisting objects to support persistence. One use of the present invention is to extend component object model (COM) objects to support persistence in a simple, predefined system. COM objects may be saved to persistence storage and loaded from persistence storage using user-provided save and load methods. When objects are constructed, the objects are added to a Persistent Object Registry. Objects preferably utilize smart pointers, rather than simple pointers, in order to enable restoration of the pointer values after a save and load cycle. The smart pointers include an object ID along with the address. The object ID, together with the information stored in the Persistent Object Registry, may be used to restore a pointer value after loading. Objects may be saved by streaming the objects out and loaded by streaming the objects back into memory from a file.

A composite material II type crack growth rate measuring method capable of acquiring a crack growth S-N curve comprises five steps: 1, a single end-notched flexure (ENF) composite material sample is selected and formed through molding fiber cloth and resin; 2, the sample is tested through a three-point bending manner; 3, a triaxial movable high power digital measurement system is adopted to observe and measure the crack growth length, and the test load, the cycle index and the corresponding crack growth length are recorded; 4, the constant interface shear stress of a neutral surface of the composite material is worked out according to the engineering beam theory, and a three-parameter power function is adopted to fit the crack growth interface shear stress and the corresponding cycle index so as to obtain the crack growth S-N curve; 5, a dual-growth exponent function is utilized to fit the test load cycle index and the a-N curve of a corresponding crack growth length, and the crack growth rate is obtained after derivation; a Paris model and an energy release rate formula are adopted, and a crack growth rate curve is obtained through least-squares approximation.

The invention relates to a starting method for a fuel cell stack in an environment below zero. The starting method comprises the following steps of placing the fuel cell stack in a low-temperature environment to be started, carrying out low-current loading and no-load cycle discharging until the temperature of each single cell in the stack reaches above 0 DEG C, loading to a high load, starting a cooling agent circulation pump, and completing the starting of the fuel cell stack. The starting method has the advantages that an auxiliary heating device is not used, heat generated by polarization of the stack during the internal reaction process is fully utilized for automatic heating, and self-starting working of the fuel cell stack in a low-temperature state is completed.

The invention belongs of the field of Iaas (infrastructure as a service) cloud computation, and relates to a hybrid genetic algorithm based dynamic cloud-computing virtual machine scheduling method. The method includes the steps: monitoring load information of physical machines and virtual machines in the cloud computing environment, analyzing a load cycle and changes of each host, and determining a cycle of load changing; computing a virtual machine placement combination appearing in cloud computation through a hybrid genetic algorithm with multiple fitness degrees. According to three optimization objectives, an optimized virtual machine placement strategy is computed to serve as a final result; the algorithm is executed periodically, the virtual machines are reasonably placed through dynamic migration of the virtual machines, resource utilization rate is increased, and resources are saved. By the method, the problem that resource utilization rate in a current cloud computing center can be solved, and the requirement on automatic management of the current cloud computing center is met.

A load monitoring system (5) is used to monitor the loading of a vehicle (1) by a load handling system (2) which is movable through a loading cycle to load a payload module (3) onto the vehicle (1) from the ground (4). The load monitoring system (5) comprises sensors (53) for sensing positional information and loading force information of the load handling system (2) at multiple positions during the loading cycle. A data processor (54) uses this information to calculate the mass of the payload module (3) and the position of the centre of gravity (31) of the payload module (3).

Methods and apparatus for structural health monitoring are described. In one example, a method for use in designing a structural health monitoring (SHM) system for use in monitoring a host structure is described. The method includes one or more of a process for designing SHM systems for any given piece of structural hardware, a process for evaluating a given SHM system, a method to quantify the performance of a given SHM system in comparison to current inspection processes, a finite element modeling approach to determining excitation frequencies to detect damage and for selecting the best time window to use for sensed excitation signals, a Bayesian Network based data fusion technique that fuses in environmental information (load cycles induced on the structure) with a damage index (DI) to produce crack detection and estimation of crack length, and a damage location and sensor selection technique.

The invention discloses a crack propagation rate measurement method. The method comprises the steps of applying alternating load to a test piece with a single-side penetrated crack by a testing machine; measuring load-displacement curves at an interval of certain loading cycles and fitting a linear segment to obtain the non-dimensional flexibility value of the test piece; acquiring the length of the crack according to the relation of the non-dimensional flexibility value of the single-side penetrated crack and the length of the crack under a clamped boundary condition; recording the number of the current loading cycles to obtain a crack length-load cycle number curve, and determining the crack propagation rate; and calculating the corresponding stress intensity factor, acquiring discrete data and fitting to obtain the parameters of the crack propagation rate. The method has the advantages that the method is suitable for measuring the crack propagation rate under positive and negative stress ratios and can be used for measuring the crack length automatically; and the measurement system has wide application range and is particularly suitable for measuring the crack propagation rate of novel materials such as a metal laminated board, a metal/composite material laminated board, a ceramic matrix composite material, a welding material.

A system includes a control unit having a processor and a communication interface. The communication interface is configured to communicate with one or more charging stations that are electrically coupled to receive electrical power from a power distribution grid and that are configured to selectively charge one or more energy storage devices connected to the charging stations. The processor is configured to generate first control signals for communication by the communication interface to the one or more charging stations to control transfer of reactive and/or active power from the charging stations to the power distribution grid. The control signals are generated based at least in part on a load cycle profile of one or more electric machines electrically coupled to the power distribution grid.

The invention discloses an asynchronous motor fault monitoring and diagnosing method based on deep learning. The asynchronous motor fault monitoring and diagnosing method comprises the following stepsthat electric power load time series of an asynchronous motor in known working condition types are acquired, the time span is Num1 electric power load cycles, and electric power load data at each sample time includes data of three dimensions of voltage, current and power; the voltage data, the current data and the power data are separately used as the gray value of pixel points of three layers inRGB images, and the time series of the electric power load cycles are transformed into the RGB image in a segmented mode, and each electric power load time series correspondingly obtains a set of feature image time series; and a deep neural network is trained by the feature image time series of the asynchronous motor and the corresponding working condition types, and a fault diagnosis model is obtained and then used for classifying the working conditions of the asynchronous motor to be tested. The fault diagnostic accuracy of the asynchronous motor fault monitoring and diagnosing method is high, and the threshold of employees is reduced while saving the time of system development.

An active-passive rehabilitation device is disclosed providing natural and relatively unconstrained motion of the treated joint, which promotes drainage and mitigates edema in the extrema. This active-passive rehabilitation device enables the application of adjunctive therapeutic modalities such as cryotherapy units and pneumatic sequential compression devices. Electronic controls allow the active-passive rehabilitation device to be programmed to provide resistive load for Active Range of Motion or Active Resistive Range of Motion (AROM or ARROM) for prescribed therapeutic cycles. Speed, range of motion and therapeutic torque limitations are some of the parameters that may be user controlled and/or programmable. Historical data can be stored in the device and can be downloaded electronically in real-time or at discrete intervals, allowing caretakers to monitor progress and even modify load cycles via electronic communication means. The unit has a lifting provision, can be folded to accommodate storage, and has integrated stabilization and bed attachment devices.

The invention discloses a cloud computing system load predicting method capable of automatically adjusting parameters, which comprises the following steps: at the moment t, computing the actual load O(t) of a system at the moment t through system call; executing short-term prediction; computing alpha (t) and E(t) by utilizing the O(t) value and historical data; executing long-term prediction; computing alpha T(t) and ET(t) by utilizing the O(t) and the historical data; combining the short-term prediction and the long-term prediction; when t is less than T, outputting the O(t) and switching to the next step; otherwise, taking the maximum value or average value of E(t-1) and ET(t-T) as the output at the moment t; and updating the historical data, waiting the moment t+1 and switching to the first step. In the invention, the alpha (t) and the alpha T(t) are computed in real time through error functions, thereby enhancing the prediction accuracy of classic EWMA (Exponentially Weighted Moving Average); the requirement that a prediction value is slightly larger than an actual value can be met by expanding the alpha (t) and the alpha T(t) to an interval (-1, 1); and the responsiveness of the prediction to the load periodicity of a cloud computing platform is enhanced by introducing a long-term prediction module.

The invention discloses a modeling method of an ash content accumulation model of a diesel particulate filter. The modeling method comprises the steps that step 1, the status of an engine is checked;step 2, the diesel particulate filter is weighed initially; step 3, ash content is subjected to loading cycle; step 4, a regeneration mode is entered; step 5, a reference point is tested, the accumulation cycle of the ash content is completed, the next accumulation cycle of the ash content is carried out; step 6, the number times of the accumulation cycle of the ash content is confirmed; step 7, the diesel particulate filter is weighed, engine oil is replaced, and data are recorded; step 8, the running time of the engine is confirmed; and step 9, modeling is carried out for analyzing the corresponding numerical relationship between ash content accumulation and fuel consumption. According to the modeling method of the ash content accumulation model of the diesel particulate filter, the relationship between the ash content accumulation rate and fuel oil consumption and engine oil consumption can be established accurately, and the control accuracy and effectiveness of an ECU for the regeneration process of the diesel particulate filter can be ensured.

The invention discloses a cloud data central virtual machine scheduling method based on an OpenFlow frame and mainly solves the problem that transfer scheme optimization object under an existing cloud computing data center environment is single. The method includes the steps of firstly, collecting related information of a cloud data central server and a virtual machine through an OpenFlow controller, and analyzing virtual machine load cycles and change conditions; secondly, calculating a new virtual machine position according to an ant colony algorithm based on pheromone diffusion; thirdly, collecting routing information and the new virtual machine information by the OpenFlow controller; fourthly, using a Dijkstra algorithm to calculate an appropriate transfer path to complete virtual machine scheduling according to the routing information and the new virtual machine position. By the method which can be used for scheduling the virtual machine by using the improved ant colony algorithm under the OpenFlow frame, the overall energy consumption of a cloud data center can be lowered, and load balancing can be achieved.

A shot shell such as would be utilized in a shotgun or the like, wherein the cartridge forming the shell has a collapsible extension removably or permanently engaging the shot end of the cartridge, with the cartridge configured to provide a un-compressed length of, for example, 2.50 inches (the minimum length of shell for conventional automatic or semi-automatic, magazine fed shotguns. The collapsible extension is configured to be compressed when placed in a spring-fed magazine, so as to provide increased magazine capacity when compared to standard length shells, while expanding when removed by from the magazine during a loading cycle, so as to facilitate reliable placement of the shell into the breach from the magazine. The collapsible extension in the loaded cartridge of the present invention is configured to be ejected from the barrel upon firing of the cartridge. The present system thereby provides a means to increase the capacity of conventional automatic or semi-automatic (i.e., pump actuated) shotguns, while reducing the likelihood of jamming or malfunction due to utilizing shells which are shorter than the firearm was designed to process.

This is a multi-phase pulse width modulator for loading current balance. It includes an error magnify unit supplying error voltage; a sawtooth wave surge unit supplying sawtooth wave surge voltage; a multi-phase pulse width modulating unit outputing a modulating signal by receiving the error voltage and the sawtooch wave voltage; a comparing voltage unit supplying delta control voltage; a pulse delay unit outputting an adjusted control voltage by adjusting loading cycle of the multi-phase pulse width modulating signal from receiving the delta control voltage; a switch driving unit outputting a driving voltage from receiving the control voltage; and a switch unit outputting loading balance voltage from receiving the switch driving voltage.

The invention discloses a method for establishing probability models of fatigue failure probability and fatigue life probability of a cement-based material in consideration of a stress level. Based on the quasi-static loading strength and the fatigue life at different stress levels of cement-based materials, the fatigue life probability model of the cement-based materials can be obtained easily and quickly. On the one hand, the model can predict the fatigue failure probability of the cement-based materials and structures using the cement-based materials by the number of fatigue load cycles. On the other hand, the fatigue life of the cement-based materials and structures can be calculated by setting the fatigue failure probabilities, which provides a new way and a new method for the fatigue performance design and service condition detection and evaluation of the structure under fatigue load.

A launcher apparatus for soft foam toy darts, the apparatus having a lock that operates momentarily during a cock and load cycle of the launcher apparatus to prevent an improper cocking operation. The launcher apparatus includes a barrel, a slide, a firing assembly and the lock. The launcher apparatus also includes three protrusions or surfaces for operative engagement with the lock to partially depress the lock, to fully depress the lock, and to disengage the lock to reset the launcher apparatus for the next cock and load cycle. During operation, one protrusion surface depresses the lock partially and momentarily, a second protrusion or surface fully depresses the lock to enable the lock to be maintained in the depressed state, and a third protrusion or surface causes the lock to be released.