10results about How to "Extend detection time" patented technology

The utility model relates to the technical field of automobile wire harness detection, in particular to an automobile wire harness conduction detection jig, which comprises a bottom plate and a clamping mechanism, a detection mechanism is arranged on the rear side of the bottom plate, the clamping mechanism is positioned on the front side of the bottom plate, and the clamping mechanism comprises a wire arranging assembly and a fixing assembly. The wire harness detection device has the beneficial effects that a large batch of wire harnesses are separated and separated one by one through the wire arranging assembly, the positions of the wire harnesses are adjusted, the wire harnesses are orderly placed on the surface, and then the two ends of the arranged wire harnesses are pressed and fixed through the fixing assembly, so that stable clamping is realized, the conditions of shaking and the like during detection are prevented, and the detection efficiency is improved. And therefore, the effect of quickly installing and clamping the wire harness is improved, the time for clamping and detecting the wire harness is shortened, and the convenience of installing the wire harness is improved.

The invention provides an intracranial pressure sensor data processing system and algorithm based on an improved wavelet neural network. The system comprises a parameter initialization module; a pre-training module; the parameter generation module is used for generating different parameter sets through improved Tent mapping; a model adjustment module; a training module; an output module; an embedded system module; the data input module takes pressure data acquired by the intracranial pressure sensor as training data and inputs the training data into the embedded system, so that a wavelet neural network structure of the data input module can reach a prediction target and is kept in the system; and the on-line measurement module is used for carrying out on-line measurement in the operation or after the operation, collecting intracranial pressure data in real time and inputting the intracranial pressure data into the system so as to obtain accurate intracranial pressure data. The influence of temperature drift on the sensor is reduced by using the improved wavelet neural network algorithm, so that the sensor has good performance when processing nonlinear and non-stationary signals, and the intracranial pressure monitoring data can reflect the actual intracranial pressure of a patient more accurately.

The invention discloses an integrated circuit testing machine with a material stacking prevention function and a testing system, and the integrated circuit testing machine comprises a testing head and a host. The integrated circuit testing machine is used for cooperating with the classifier. And the test head is used for placing the tested object on the classifier and taking back the tested object by the classifier. The host is used for executing a test program on the tested object through the test head and providing a first instruction to enable the classifier to operate in a replacement stage. In the replacement stage, the classifier firstly executes the retrieval program and then executes the placement program so as to be replaced with another tested object. Wherein the host is used for executing the residual test program through the test head in the replacement stage, and generating a second instruction for stopping the operation of the classifier when the tested object is left on the test head. Therefore, the problem of material stacking caused by the abnormality of the classifier can be solved without increasing the test time.

The invention relates to the technical field of brake oil can detection, in particular to a continuous brake oil can pressure testing device which comprises a bottom support and an electric control conveying belt, and electric control adjusting discs are movably assembled on the two sides of the bottom support. According to the continuous brake oil can pressure testing device, the brake oil can is conveyed through the electric control conveying belt, then the brake oil can is clamped and separated from the two sides through the electric control clamping units on the electric control adjusting disc, and the whole detection process is continuous and efficient; through clamping of the two sides, the stability of the brake oil can in the detection process can be improved, a liquid inlet and a liquid outlet of the brake oil can can be closed and sealed, and the stability and accuracy of internal pressure detection are guaranteed. An electric control screening mechanism is arranged at the upper end of the bottom support and located between the electric control adjusting discs, movement interference on the brake oil cans can be avoided, the brake oil cans with different detection results can be screened and separated, and the detection efficiency is improved.

The present invention discloses a method for realizing frequency hopping unmanned aerial vehicle signal recognition based on wireless spectrum analysis. The method collects unmanned aerial vehicle image transmission data and frequency hopping remote control data. 50 sets of data are collected from each unmanned aerial vehicle as original data. The collected one-dimensional unmanned aerial vehicle time domain signal is converted into a two-dimensional time-frequency signal by short-time Fourier transform. The data is calibrated. A model framework is constructed. The features of the unmanned aerial vehicle signal are extracted by means of a multi-layer convolutional network of a VGG model. The features are extracted by reasonably designing the convolution kernel and the number of network layers. After training a stable model, the output result of the model is converted into the possible position information of each signal element of the frequency hopping unmanned aerial vehicle signal on the time axis prediction on the time-frequency diagram. The accurate signal element positions obtained by signal matching are detected one by one to ensure the independence of the signal elements. The data verified by the signal are sorted, the statistically redundant and repeatedly detected elements are removed, and the data are classified.

The application discloses a kind of defect detection systems, including detection device and image processing module, wherein the detection device, including object table, telecentric light source, horizontal light source, coaxial light source, camera, the object table is used to load workpiece, and the workpiece includes through-hole workpiece and non-through-hole workpiece;When the telecentric light source is opened, the camera obtains the projection image of the workpiece.The application is replaced by machine, that is, through automatic non-contact optical detection system, appearance detection and size measurement are detected to flange, and unqualified products are removed.Optical image detection replaces human eye, without visual requirements, with guaranteed definition, and also avoids the problems of personal injury and reduced efficiency caused by long-term labor of artificial;And through machine determination, consistency is strong, avoids randomness, and guarantees the overall quality of flange.

The invention provides UPLC-MS (Ultra Performance Liquid Chromatography-Mass Spectrometry) chemical components of Zhuang medicine embelia parviflora and a fingerprint spectrum analysis method thereof, and belongs to the technical field of medicine analysis. The method comprises the following steps: step 1, setting detection conditions of a quadrupole electrostatic field orbitrap high-resolution mass spectrometry method; 2, setting fingerprint conditions; 3, chemical component identification result analysis; and 4, establishing the UPLC fingerprint chromatography of the embelia parviflora. According to the method, chemical components of embelia parviflora are analyzed by adopting a UPLC-Q-Exactive HRMS (High Resolution Mass Spectrometry-Quantitative Exactive High Resolution Mass Spectrometry) technology, and in consideration of serious interference of ion fragments, a spectrum library matching result can be seriously influenced, and the deduction of a mass spectrum splitting decomposition process can be interfered, so that only 10 components with the matching degree being greater than 85% are screened in an experiment, and the deduction of the mass spectrum splitting decomposition process is carried out.

The present invention provides a traffic light state detection method and system based on a single camera, including: an image acquisition module acquires an original image and sets an area of ​​interest on the original image; an object detection module detects whether there is a traffic light in the area of ​​interest image; a state detection module detects the state of the traffic light in the area of ​​interest image and outputs the result; at the same time, it detects whether the traffic light is in the center of the area of ​​interest image, if so, the area of ​​interest parameters remain unchanged, if not, the parameter fine-tuning module adjusts the area of ​​interest parameters; it determines whether the cumulative number of images of the area of ​​interest in which the traffic light is not detected continuously exceeds a threshold, if not, the area of ​​interest parameters remain unchanged, if so, the area of ​​interest parameters are adjusted. The present invention uses a single high-resolution camera to replace the telephoto and short-focus cameras, reduces equipment costs, simplifies the detection algorithm, and the area of ​​interest sliding window method combining fine-tuning and coarse-tuning avoids the problem of increased model data volume caused by high-resolution images.

The present invention provides a battery diaphragm surface defect detection device and process, including a tensioning device for tensioning the battery diaphragm, a detection light source located on the outside of the battery diaphragm and a detection device located on the inside of the battery diaphragm, the tensioning device includes a plurality of tensioning limit rollers, and the plurality of tensioning limit rollers are arranged in a predetermined position to control the battery diaphragm to move along a V-shaped path; the detection device is set to be multiple, and also includes a drive control device for controlling the directional movement of the plurality of detection devices, the drive control device includes a drive control component that moves in a circular manner, and the plurality of detection devices are installed on the outer surface of the drive control component. The invention can improve the accuracy and efficiency of battery diaphragm surface defect detection.

The utility model relates to AOI optical detection equipment technical field, concretely is a kind of AOI optical detection automation conveying track, it includes: track main body, the top of track main body is equipped with transport platform, the side wall of track main body is equipped with clamping groove, the top of clamping groove is equipped with through slot, through slot penetrates the top of track main body, first spring group is installed in the inside of through slot, the bottom of first spring group is equipped with connecting clamping plate;Beneficial effects are: the utility model proposes a kind of AOI optical detection automation conveying track, using clamping groove and connecting clamping plate mutually cooperate and use, multiple tracks can be positioned and connected, it is convenient to detect multiple samples, increase the efficiency and time of detection.