299 results about "Signal region" patented technology

The invention discloses an unmanned aerial vehicle track maintenance and autonomous positioning method in a communication decline scene, and relates to the technical field of navigation maintenance positioning, and the method comprises the steps: carrying out the signal intensity monitoring and smoothing of signal quality and decline information collected in real time, carrying out the decline trend prediction through a long-short-term memory network, and outputting a signal decline report; in combination with multi-unmanned aerial vehicle sensor data, local sensor data is processed in real time through edge calculation, and shared information is fused through particle filtering; a cooperative positioning algorithm and a distributed positioning algorithm are used to correct the shared information of the multiple unmanned aerial vehicles and output the precision for autonomous positioning; and adjusting the unmanned aerial vehicle to an energy-saving flight mode by using an energy consumption model in combination with the signal recession report and the optimal path. According to the method, the flight path of the unmanned aerial vehicle is optimized by adopting deep reinforcement learning and the game theory, and adaptive flight path adjustment is realized in combination with a model prediction control algorithm, so that the unmanned aerial vehicle can dynamically avoid a low-signal area, and flight stability is ensured.

The invention relates to the technical field of boundary recognition, in particular to a glioma boundary recognition method and system based on image fusion, and the method comprises the following steps: obtaining a multi-modal brain image, constructing a fusion matrix, extracting the gray features of an edge region and an adjacent region, recognizing signal-noise abnormal points, and revising a judgment standard. And adjusting the path direction and reconstructing an edge communication structure, and generating a glioma boundary region map under fusion. According to the method, high-precision alignment among modals is realized through multi-modal image gray scale unification and registration processing, key details are expanded and focused by enhancing edges and regions, the recognition accuracy is improved, gray scale comparison between the edges and outer adjacent regions is introduced, the signal distinguishing capability is enhanced, misjudgment is avoided, judgment conditions are dynamically revised according to the signal-noise difference, and the accuracy of recognition is improved. The method enables the recognition standard to have local adaptability, combines the path change trend to reorder and connect edge points, guarantees the continuity of a boundary structure, integrally improves the accuracy and integrity of fuzzy boundary recognition, and enhances the glioma contour extraction effect.

The invention discloses an ad hoc network communication system without a signal area, particularly relates to the technical field of wireless communication, and is used for solving the problem that a connectivity critical state caused by node density or mobility change in a low-density network is not fully considered in an existing dynamic routing protocol. The network connectivity critical state is pre-judged by acquiring node position coordinates and communication radiuses in real time and combining the average node spacing and the dispersion in the moving direction; screening a high-priority detection node based on an obstacle avoidance cooperative angle variance and a virtual pheromone concentration in a critical state, and adaptively adjusting a detection message sending frequency according to a node moving speed; constructing a path stability evaluation model by fusing the link survival duration, the node residual energy and the signal intensity fluctuation rate, dynamically screening a high-stability path as a main transmission link, and taking the rest lists as standby links; and monitoring the signal fluctuation characteristics of the main link in real time, and quickly switching to the path with the optimal comprehensive stability in the standby link in an abnormal state.

The invention discloses an electromagnetic target recognition method based on interpretable multi-task learning, a storage medium and equipment, and the method comprises the steps: firstly constructing a multi-task learning network facing modulation recognition and individual recognition, inputting an original signal, setting a hyper-parameter, and carrying out the training of the multi-task learning network; constructing a generator for outputting a disturbance signal, segmenting an original signal and generating an original mask, generating a disturbance mask through an inversion element, and further generating the disturbance signal; inputting the disturbance signals into the trained multi-task learning network to obtain probability distribution of classification results under different tasks; taking a prediction probability of a multi-task model to a disturbance signal as a supervision label, training a local linear model on an original mask and a disturbance mask, and taking a model weight Wg as a contribution degree of each subsequence to explanation through optimization; and performing normalization processing on the Wg, mapping the weight back to the original signal length, and visually marking a time-frequency domain signal region which plays a key role in model decision based on a constellation diagram.

The invention discloses a robot motion control method and system based on voice interaction, and relates to the technical field of robot motion control, and the method comprises the steps: extracting each segment of independent audio signal and keywords conforming to a preset voice library from mixed multi-channel audio based on a blind source separation technology; and selecting the keyword with the highest confidence coefficient as an execution command word, obtaining a standard track of an action corresponding to the execution command word, generating an executable simulation track of the execution command word in combination with real-time environment information, and controlling the robot to execute motion according to the simulation track after judging that the simulation track is safe and feasible. According to the method, the multi-channel mixed audio is separated into the independent signals, the execution command word is determined after the voice sources of different users are distinguished, the motion trail generated by simulating the conditions of the corresponding preset action and the enforceable environment is utilized, and the multi-dimensional characteristics of the motion trail and the standard trail of the preset action are compared and analyzed; and evaluating the feasibility of the motion trail corresponding to the execution command in the environment.

The invention belongs to the technical field of intelligent traffic, and provides a distributed optical fiber road sensor on-site manufacturing and road risk monitoring and early warning method. Comprising the steps of optical fiber unit manufacturing, concave shallow slot cutting, sensor construction, data acquisition, road surface state data conversion, scattered light time domain signal interval division, frequency domain conversion and filtering processing, multi-mode feature extraction and road surface condition recognition. According to the invention, the concave shallow slot is cut at the edge of the road, and the flat ribbon-shaped optical fiber unit is fixed in the shallow slot by using polyurea, so that the multifunctional distributed optical fiber road sensor which is integrated with the road surface, high in sensitivity, small in size, simple to install, convenient and rapid to maintain and repair and low in cost is constructed; through a zero crossing point and a noise threshold value, normal time domain signal interval judgment is optimized, and the effect of subsequent filtering processing is improved; a road surface condition identification data model is constructed through a multi-modal fusion technology, and the identification precision of multiple road surface abnormal conditions and the positioning precision of abnormal events are improved.

The invention relates to a non-contact pulse signal extraction method and system based on a face video, and the method comprises the steps: preprocessing face video stream data, constructing a pulse signal extraction model, inputting the preprocessed face video stream data into the pulse signal extraction model for training, and obtaining a trained pulse signal extraction model; performing non-contact pulse signal extraction by using the trained pulse signal extraction model; according to the invention, a wavelet difference fusion module is provided, so that the signal extraction stability and precision of the model in a complex dynamic scene are effectively improved; sensing local and global spatial dependence through a self-adaptive multi-scale expansion convolution module, and strengthening the response of a key physiological signal region; a linear Mama module is designed to achieve low computing resource overhead, meanwhile, a stable and extensible time sequence feature expression framework is constructed, high modeling capacity is kept, and meanwhile good generalization performance and actual deployment advantages are achieved.

The invention relates to an ultrasonic fluid metering precision improving method and related equipment, and the method comprises the steps: exciting a first ultrasonic transducer through an excitation wave sequence, enabling a second ultrasonic transducer to work, obtaining a received digital signal corresponding to the excitation wave sequence, and calculating the signal-to-noise ratio of the received digital signal; wherein the excitation wave sequence is a combination of a main wave and a self-damping wave, and the signal-to-noise ratio is a ratio of a peak-to-peak value of a receiving signal area to a peak-to-peak value of a noise area; judging whether the signal-to-noise ratio is greater than a signal-to-noise ratio threshold value or not, if not, adjusting the occupation time of the high and low levels of the self-damping waves, and executing the excitation work again according to the adjusted excitation wave sequence until the actual signal-to-noise ratio is greater than the signal-to-noise ratio threshold value; and determining the corresponding excitation wave sequence when the actual signal-to-noise ratio is greater than the signal-to-noise ratio threshold as a target excitation wave sequence, and exciting the ultrasonic transducer to work according to the target excitation wave sequence so as to execute metering operation. According to the method, the measurement precision is remarkably improved while the hardware cost is not increased.

The invention provides an indoor fingerprint positioning method based on area fitting, which relates to the field of fingerprint positioning, and comprises the following steps: dividing a plurality of triangular areas, and carrying out signal intensity fitting on each triangular area by adopting a signal area fitting method to obtain a plurality of signal intensities in one-to-one correspondence with virtual reference points; calculating to obtain an obstacle area through an obstacle identification algorithm, calculating to obtain an AP fingerprint map with a passable area according to the obstacle area, and establishing a retrieval fingerprint database corresponding to the AP fingerprint map; selecting a passable area with the minimum distance in the retrieval fingerprint database, and matching a reference point in the AP fingerprint map to realize positioning; by adopting the method, the signal intensity fitting of the whole indoor area can be carried out only by measuring the sparse reference points. A double-layer fingerprint database is constructed, positioning errors can be remarkably reduced, the number of fingerprint database data is greatly reduced, and therefore the online matching duration is shortened.

The invention discloses an intelligent distinguishing system and method for surface defects of a non-welding bottle type container, and particularly relates to the technical field of magnetic powder detection. Electromagnetic interference in an industrial field is simulated by arranging different types of electromagnetic interference sources, and reference measurement and comprehensive analysis are performed on surface magnetic field distribution of a non-welding bottle type container and defect signal intensity change of magnetic powder detection equipment under a step-by-step interference condition, so that the anti-interference capability of the equipment is evaluated. The accuracy of a detection result is divided into different grades, repeated detection and abnormal degree evaluation are performed on an area with an incomplete accuracy result, and if the abnormal degree is high, the area is marked as a pseudo signal area and fed back to a machine learning model to gradually update the model discrimination capability, so that the problem of false defect misjudgment under electromagnetic interference is effectively reduced, and the accuracy of the detection result is improved. And the accuracy and reliability of the detection system in a complex interference environment are improved.

The invention discloses a cold-chain pork quality dynamic evaluation method and system based on multi-source data fusion, and relates to the technical field of data processing and intelligent evaluation, and the method comprises the following steps: collecting multi-source signal information of a whole cold-chain transportation process, sorting according to a unified time sequence, continuously arranging all signals on a time axis, and carrying out data processing on all the signals; a complete dynamic record is formed; and extracting each time interval and signal amplitude change track from the formed dynamic record, analyzing a signal section with repeated wave crests in a short time, and generating a preliminary data manuscript for reflection interference judgment. According to the invention, through time sequence arrangement and dynamic association of multi-source signals, a wave crest track analysis mechanism is constructed, real-time identification and correction of reflection interference are realized, and continuity and accuracy of a gas concentration curve are ensured; and by generating a reflection source position list and adjusting numerical value distribution of repeated fragments, false fluctuation is eliminated, and the stability and reliability of cold-chain pork quality evaluation are improved.

The present invention discloses an image processing-based ultrasonic measurement method for hepatic steatosis. The method comprises preprocessing a set of RF signals from the abdominal region, including the liver, acquired by ultrasound imaging and converting the signals into a grayscale image; processing the grayscale image to obtain a first segmentation template for the liver region; removing interference signal regions from the first segmentation template to obtain a second segmentation template for the liver region; labeling the grayscale image with the second segmentation template to obtain a region of interest; and calculating an attenuation coefficient within the region of interest to characterize the degree of hepatic steatosis. This method allows the attenuation coefficient to be calculated only for sampling points within the liver and non-lesion areas, achieving more accurate hepatic steatosis measurement.

The invention relates to the technical field of intelligent door locks, in particular to an indoor and outdoor unlocking signal distinguishing method and system based on an angle sensor.The method comprises the steps that position data, angle data, trend angle data and distance data of a target object are collected, and space coordinates of the target object are generated by combining the data; according to a preset coordinate range of an authorized unlocking area and an unlocking forbidding area, judging an area type to which the space coordinate of the target object belongs; if the space coordinate of the target object is located in the authorized unlocking area and meets a preset unlocking condition, executing an unlocking operation; if the space coordinate of the target object is located in the unlocking prohibition area or does not meet the preset unlocking condition, locking operation is executed. According to the invention, multi-dimensional information such as measurement data of the angle sensor and the UWB module is comprehensively utilized, indoor and outdoor unlocking signals are accurately distinguished, the problem that indoor and outdoor signals are easy to misjudge in a special-shaped house type is effectively solved, and the unlocking accuracy is greatly improved.

The present disclosure relates to a method and system for calibrating a loudspeaker system in an environment (1). The loudspeaker system comprises an audio device (10) with a first and second loudspeaker arranged with a predetermined horizontal separation. The method comprises the steps of emitting (S2a, S2b) a first and second calibration audio signal from the first and second loudspeaker (11) of the audio device (10), wherein the second calibration audio signal is distinguishable from the first calibration audio signal. The method further comprises receiving (S3a, S3b), with a first external microphone (20) the first and second calibration audio signal, determining (S4) the position of the first external microphone (20) relative to the audio device (10) and calibrating (S8) the loudspeaker system based on the determined position of the first external microphone (20).

The invention discloses a method for improving vibration monitoring accuracy based on distributed optical fiber Sagnac interference, and the method specifically comprises the steps: obtaining a vibration signal through a distributed optical fiber Sagnac interferometer, and carrying out the signal filtering and phase difference calculation; calculating the wave number or period and amplitude change characteristics of the vibration signal in unit time, if the vibration signal is a narrow-band vibration signal, discarding the vibration signal, otherwise, extracting the frequency spectrum characteristics of the vibration signal by using fast Fourier transform (FFT), if the vibration signal is a narrow-band vibration signal, discarding the vibration signal, and if the vibration signal is a wide-band vibration signal, obtaining the dominant frequency distribution and bandwidth of the signal; intelligent classification is further carried out on the vibration signals based on an R-CNN deep learning model, if the vibration signals are narrow-band vibration signals, the vibration signals are discarded, and otherwise, a wide-band vibration signal area is obtained; calculating the position of a seismic source in the broadband vibration signal area by adopting a trap spectrum method, and triggering an alarm system; if the broadband vibration signal is not obtained in the above step, the vibration signal is an invalid signal, and positioning is not carried out.

The invention discloses an rPPG physiological signal reconstruction recognition system based on generative adversarial optimization, and relates to the technical field of data processing. The system comprises a signal preprocessing module used for extracting an initial rPPG signal from an input video sequence; and the signal reconstruction module comprises a generator and is used for receiving the initial rPPG signal and outputting a reconstructed rPPG signal. According to the method, by introducing a multi-dimensional discriminator set and physiological prior loss collaborative optimization mechanism, the precision and robustness of rPPG signal reconstruction are remarkably improved. The system can restrain signal quality from multiple angles of time domain, frequency domain and time-frequency domain, and restrain irrational fluctuation in combination with physiological laws, thereby effectively overcoming motion artifacts and illumination interference. Meanwhile, the dynamic region-of-interest selection module adaptively focuses an optimal signal region through a learnable attention mechanism, the input quality is improved from the source, and finally high-reliability estimation of the physiological parameters such as the heart rate and the respiration rate in a complex scene is achieved.

The invention relates to the technical field of steel pipe concrete structure detection, in particular to a method for detecting fatigue damage of a steel pipe concrete correction structure for waste incineration power generation. The ultrasonic detection signals under different primary frequencies are subjected to comparative analysis of signal intervals with different amplitude changes, and the ultrasonic detection signals under different frequencies are subjected to targeted filtering optimization processing based on analysis results, so that the accuracy of damage information judgment under different frequencies is comprehensively evaluated. Accurately screening ultrasonic detection signals in the detection process of the correction structure according to an evaluation result, and obtaining a fatigue damage detection result of the correction structure based on a screening result; the accuracy of fatigue damage information judgment of the correction structure is improved, and the detection performance of the concrete filled steel tube correction structure at different positions is improved.

The invention discloses a wide-spectrum rapid scanning and intelligent identification method, system and device, and the method comprises the steps: firstly, carrying out the rapid frequency sweeping through employing a low-sampling-rate and low-quantization-precision receiver, generating a low-resolution time-frequency graph, and recovering the super-resolution of the low-resolution time-frequency graph into a high-resolution spectrum through a pre-trained deep learning model; then, the enhanced time-frequency image is segmented into time-frequency blocks, global features are extracted through a Transform encoder, and detection and screening of multiple candidate signal areas are achieved; and finally, carrying out directional sampling on the candidate region, respectively extracting time domain and frequency domain features, mapping the time domain and frequency domain features to a unified space for fusion, and completing signal category judgment based on the combined features and a judgment network. According to the wide-frequency-spectrum rapid scanning and intelligent identification method, system and device, through a layered architecture of broadband rapid scanning-frequency spectrum quality recovery-multi-region detection-directional sampling and time-frequency fusion identification, the reliability of unmanned aerial vehicle signal detection and identification in a complex electromagnetic environment is improved while the hardware cost is reduced.

The invention discloses a surface-emitting laser and a surface-emitting laser preparation method, which are applied to the field of lasers, and the surface-emitting laser comprises a signal area, an amplification area and a surface-emitting area, each of the signal region, the amplification region and the surface emission region comprises a substrate, an epitaxial layer grown and prepared on the surface of the substrate, and a post-process layer prepared and formed on the surface of the epitaxial layer and the surface of the substrate; the epitaxial layer in the surface emission region comprises a passive second-order grating layer; and the volume of the active region in the epitaxial layer in the signal region is smaller than that of the active region in the epitaxial layer in the amplification region. According to the surface emitting laser, the signal area, the amplification area and the surface emitting area in the surface emitting laser are separately prepared, function separation of the signal area, the amplification area and the surface emitting area is achieved, the surface emitting area internally provided with the passive second-order grating layer is matched, and the surface emitting laser capable of improving the output power and the modulation rate at the same time is achieved.

The invention discloses an underground power optical cable multi-scene vibration area positioning method based on a PLGS-YOLO model, relates to the technical field of deep learning models and power optical cable monitoring, and solves the problem that a model adopted for vibration area positioning in an existing underground power optical cable cannot meet application requirements due to interference of background noise or non-target area signals. The method is used for judging the laying scene of the vibration event and positioning the corresponding signal area. YOLOv11n is optimized, SPPFDMSCA and PLMSAM are utilized, and feature extraction efficiency is enhanced through a multi-scale attention mechanism; the GSConv combines the advantages of the traditional convolution and the depth separable convolution, so that the calculation complexity is reduced, and meanwhile, the multi-channel characteristics are reserved; the VoVGSCSP optimizes feature fusion, improves the detection precision and the model efficiency, and remarkably reduces the calculation complexity.

The invention discloses a communication anti-interference method assisted by a plurality of closed intelligent reflecting surfaces on a receiving side, and the method comprises the steps: constructing a closed space selection structure formed by a plurality of RIS panels in a surrounding manner, placing a receiving antenna in the closed space selection structure, and enabling each RIS unit to independently regulate and control the transmission or reflection state of incident electromagnetic waves; according to the relative position of a receiving antenna and an external signal source, the space outside the structure is divided into different signal areas, and each signal area is covered by an RIS panel; and according to the signal area where the signal source is located, adjusting the working mode of the RIS unit of each signal area: adjusting the RIS unit of the signal area where the signal source is located to a transmission mode, and adjusting the RIS units of other signal areas to a reflection mode. According to the invention, the reachable transmission rate and the anti-interference capability of a communication system are improved, the problem of signal interference in a complex environment is solved, and efficient and reliable communication in a complex interference environment is realized.

To provide a mounting technique capable of enhancing a radar detection distance.SOLUTION: The radar antenna device is for installation on a side of a vehicle. The radar antenna device comprises two antenna circuit boards, wherein each antenna circuit board comprises a first side comprising a signal transmitting unit and a signal receiving unit. The signal transmitting unit includes a first signal zone, and the first signal zone is located within an angle range between 0 degree and 50 degrees from a normal of a center of the first surface. The radar antenna device also comprises a base for mounting the two antenna circuit boards. One end of each antenna circuit board is coupled to one end of the base such that a first direction parallel to the base and extending from a center of the first surface is located in the first signal zone and forms an angle between 52.5 degrees and 65 degrees.SELECTED DRAWING: Figure 3

The present invention discloses a method for controlling a variable speed limit for mixed traffic in a near-signal area based on a macro model, comprising the following steps: dividing the road sections in the near-signal area by function and length; periodically feeding back the traffic flow information of each road section to vehicles within the control area; constructing a variable speed limit model for mixed traffic in the near-signal area based on the macro model; determining the objective function and constraints according to the control objective, and designing a method for controlling a variable speed limit for mixed traffic based on the macro model; and controlling the vehicles in each controlled road section within a set time interval to execute a speed adjustment process according to the calculated optimal speed. The present invention provides a variable speed limit control method for effectively controlling mixed vehicle groups in the near-signal area under new mixed traffic conditions, providing a new approach to alleviating the adverse effects of periodic regulation of traffic lights and lane changes of vehicles in the near-signal area.

The present invention discloses a 5G exo-radiation radar signal accumulation method, belonging to the field of exo-radiation radar technology. The method comprises the following steps: S1, signal acquisition and parameter setting; S2, signal segmentation interception; S3, Rényi entropy calculation; S4, signal accumulation interval selection; S5, signal coherent accumulation. To address the problem that the bandwidth of 5G downlink signals strongly depends on the transmission content, a sliding Rényi entropy calculation is performed to select signal intervals in the 5G signal with high transmission content as the coherent accumulation intervals for the exo-radiation radar. This method can effectively improve target resolution and echo signal-to-noise ratio, achieving effective detection of low-lying, slow, and small targets while using less computing resources.

The invention relates to the technical field of wireless communication, in particular to an ad hoc network transmission method suitable for a field environment, which comprises the following steps: S1, heterogeneous network architecture design: network nodes are deployed in a non-signal area and are responsible for data acquisition and Mesh relay transmission; the gateway nodes are deployed at the boundary of a signal area and are responsible for 4G / LoRa protocol conversion and cloud forwarding, and each node has the capability of automatically identifying the signal intensity of the current environment; and S3, an intelligent transmission mechanism is adopted, in the starting stage, after the nodes are powered on, cellular network signals are automatically detected, and according to the signal strength, the roles of the network nodes and the competitive gateway nodes are autonomously determined. An autonomous relay transmission mechanism based on the Mesh network is constructed, the network reliability is improved, autonomous roaming and multi-path transmission of the nodes are achieved, the communication success rate in a severe environment is improved, energy consumption distribution is optimized, and the situation that specific nodes deplete energy too early is avoided through dynamic role distribution.

To improve night scene determination accuracy.SOLUTION: An image processing device of the present invention has a controller. The controller configured to: extract a traffic light region where a traffic light exists, from a camera image captured by an in-vehicle camera; determine a luminous region and a non-luminous region within the traffic light region; and determine the camera image as a night scene when brightness and chroma of the luminous region and the non-luminous region correspond to nighttime brightness and chroma characteristics.SELECTED DRAWING: Figure 4

The invention provides an unmanned aerial vehicle routing inspection and slope monitoring system for a non-signal area. The unmanned aerial vehicle routing inspection and slope monitoring system comprises an unmanned aerial vehicle routing inspection module and a slope monitoring module. The unmanned aerial vehicle inspection module constructs an off-line high-precision map through laser radar scanning and camera acquisition, realizes autonomous positioning in a GPS-free environment in combination with multi-modal data, and generates an optimized route. The slope monitoring module collects topographic data in real time through a distributed sensor, evaluates a slope risk level by using a hybrid machine learning model, and dynamically adjusts an unmanned aerial vehicle inspection strategy according to the risk level. According to the invention, the problem that automatic inspection of a non-signal area is difficult to realize is solved, and real-time monitoring and early warning of slope deformation are realized.

To provide a technique capable of estimating a camera position without having high processing performance.SOLUTION: An optical wireless communication system includes a plurality of light sources, a receiving device including an event camera, and an information processing device. Each of the plurality of light sources transmits an optical wireless communication signal. The receiving device receives the optical wireless communication signal via the event camera. The optical wireless communication signal includes position-related information for identifying a position in an absolute coordinate system of a transmission source of the optical wireless communication signal. The information processing device identifies a signal region of the optical wireless communication signal in an image plane coordinate system of an image plane obtained by the event camera to acquire a light source image position indicating a position at which each of the plurality of light sources is projected in the image plane coordinate system, acquires a light source absolute position indicating a position at which each of the plurality of light sources is located in the absolute coordinate system on the basis of the position-related information included in the optical wireless communication signal, and uses the light source image position and the light source absolute position to estimate a position and a direction of the event camera in the absolute coordinate system.SELECTED DRAWING: Figure 1

The present invention relates to a device (100) for detecting a predetermined gesture of an operator of a vehicle (10) for triggering an opening and / or closing process of a vehicle flap (12) of the vehicle (10). The device (100) comprises: a sensor unit (110), which is designed to emit an electromagnetic signal and to receive again an emitted electromagnetic signal reflected in the surroundings of the vehicle (10); and a cover element (120), which is arranged at a predetermined distance (114) from the sensor unit (110), is at least partially impermeable to the electromagnetic signal of the sensor unit (110) and has at least one opening (122, 123) through which at least part of a detection region (112) extends. The predetermined distance (114) and / or the at least one opening (122, 123) are designed to form a predetermined detection region (112) of the signal region (111), said detection region extending on an opposite side of the cover element (120) in relation to the sensor unit (110).