154 results about "Continuous signal" patented technology

The invention provides a scroll compressor cross ring dynamic strain wireless measuring device, which relates to the technical field of compressor state monitoring and comprises a high-temperature-resistant strain gauge, a wire fixing system and a wireless sensor. Wherein the high-temperature-resistant strain gauges are respectively attached to stress sensitive areas of a static key, a ring beam and a movable key of the cross ring every time; the wire fixing system comprises a three-stage fixing structure formed by an adhesive, an internal wire, an external wire and an internal binding post; the three stages of fixing structures are a strain gauge end fixing structure, a lead transition section fixing structure and a binding post end fixing structure in sequence; the high-temperature-resistant strain gauge is connected with the wireless sensor through an internal wire, a binding post and an external wire, and continuous signal collection is achieved. By implementing operation according to the technical route, the impact load borne by the cross ring at the moment of starting and stopping of the compressor can be collected in a high-quality mode, data collection in a closed cavity is achieved, and an experimental basis is provided for subsequent strength design of the cross ring.

The invention discloses a root mean square value RMS detection method and system, and belongs to the technical field of measurement and control. Wherein a to-be-detected voltage signal is preprocessed by the filter amplification circuit, a square wave signal synchronous with a sine wave zero crossing point is generated through the zero crossing comparison circuit, a signal period boundary is identified, and an integral number of complete and continuous signal periods are extracted in real time through the period detection module; the cycle information identified by the cycle detection module is transmitted to the data storage and processing module, meanwhile, the sampling signal of the high-speed ADC module is transmitted to the data storage and processing module, and sine wave data sampled by the high-speed ADC module is subjected to point-by-point square operation; the square values in a complete period are accumulated and summed, and an original sampling sequence is not stored; fIR digital filtering is carried out on the RMS values of continuous C periods through a digital filtering module; and the dynamic response performance of the system under different frequency bands is remarkably enhanced while the measurement precision is improved.

The invention discloses a partial discharge capacity-severity joint estimation method, a product and equipment, and belongs to the technical field of power equipment monitoring. The method comprises the following steps: S1, constructing a physical fusion framework of multi-modal data: constructing a partial discharge signal propagation graph structure, and converting multi-source heterogeneous data into a unified physical graph; s2, establishing a physical prior model of partial discharge propagation based on graph Laplacian frequency domain features; s3, constructing a correction network to compensate the deviation of the physical model; s4, carrying out capacity-severity joint estimation and uncertainty quantification: carrying out joint modeling on the continuous discharge capacity and the discrete severity level, approximating a real posteriori through a variational posteriori, and outputting point estimation and confidence information; and S5, risk assessment and adaptive optimization: performing risk level assessment based on a result of S4, and performing adaptive adjustment and optimization when a false alarm occurs. The method has continuous signal quantization and discrete grade discrimination capabilities, and is especially suitable for non-contact discharge detection scenes under complex medium conditions.

The invention provides a self-adaptive interference suppression method and system for a multi-band signal. The method comprises the following steps: acquiring a multi-band original signal set comprising a plurality of band continuous signal units; then, an adaptive interference modeling model is called to carry out interference mode characterization processing, and an interference signal characterization result is generated; dynamically configuring an interference suppression parameter set in one-to-one correspondence with each frequency band signal interference mode based on an interference signal characterization result; performing adaptive interference suppression processing on the multi-band original signal set by using the interference suppression parameter set to obtain a preliminary suppression signal set; and finally, feeding back the initial suppression signal set to the adaptive interference modeling model for iterative optimization processing to generate a final interference suppression signal set. According to the invention, accurate analysis and adaptive suppression of multi-band signal interference are realized, the stability and reliability of signal transmission are improved, and the complexity and cost of the system are reduced.

The invention relates to the technical field of artificial intelligence and intelligent medical treatment, and discloses a health care information service system based on deep learning and a knowledge graph, and the system uses implicit physiological semantic prototype nodes to establish a mapping access point of a continuous signal and a discrete graph, and generates a dynamic causal graph based on real-time physiological features. The causal deduction module predicts an intervention result on the dynamic map, and the signal reconstruction verification module performs reverse physical signal reconstruction on a map reasoning path and calculates an effectiveness score based on biophysical constraints. And the decision output module fuses the potential result predicted value and the validity score to generate an intervention suggestion. According to the method, deep fusion of time sequence data and symbol knowledge is realized, and physiological safety and interpretability of dynamic health maintenance decision are ensured through a bidirectional verification mechanism of a logic space and a physical signal space.

Device and method for measuring a junction temperature of a power semiconductor (3) using the resistance Rgint (32) of said semiconductor (3) comprising at least: a current injector circuit (5) injecting current pulses Iinj in the gate path of said power semiconductor (3) through the emitter of said power semiconductor, said current injector circuit (5) being driven by a digital injection control circuit (4, 6) to synchronize said current pulses within a stabilized part of ON states of the power semiconductor driver (1) PWM signal driving said power semiconductor (3), a peak detector circuit (7) to record emitter voltage peaks Ve at the terminals of the current injector circuit and generate a continuous signal Vpks dependent of the junction temperature Tj through integration of said voltage peaks, a signal conditioning circuit (8) to adapt the continuous signal Vpks dependent of the junction temperature into a range of 3V to 5V of a measurement system (9).

The invention discloses a continuous signal transmission-based communication and sensing integrated staggered transceiving joint design method, which is used for suppressing interference caused by a continuous transmission system and innovatively constructing a signal block structure with alternating communication single function and communication and sensing integrated double functions. The method is based on an interlaced signal structure, on one hand, constructive interference is used for improving communication performance; and on the other hand, the integral main and side lobe ratio and in-block and inter-block interference are optimized to ensure the radar sensing performance. According to the method, a joint optimization model designed for a perception receiving filter and an ISAC transmitted waveform is constructed, the model is solved through an alternative optimization framework and an SCA algorithm, and collaborative optimization of communication performance and perception performance is achieved. The method can effectively solve the problems that radar echoes are seriously interfered by adjacent symbol blocks and the communication performance is limited in a communication and inductance integrated scene of continuous signal transmission, and is suitable for a communication and inductance integrated system to improve the target detection precision and the communication reliability in a continuous signal emission system.

The invention discloses an aging gait detection method and system based on a millimeter wave radar, and the method comprises the following steps: S10: employing the millimeter wave radar to collect the data of the activities of a human body going up and down stairs; s20, performing Fourier transform on the activity data after sampling to obtain signal frequency spectrum and target distance information; wherein the continuous Chirp signals of which the intervals are fixed values are stored as row vectors, and receiving frequency responses of targets at different distances can be obtained by performing 1D-FFT on each row; performing fast Fourier transform on a plurality of Chirp signals of the same distance unit to obtain target speed information, namely a time-Doppler graph; and S30, constructing a YOLOv11 model, constructing a data set by the time-Doppler maps, carrying out classification training by using the YOLOv11 model, carrying out batch classification prediction on the new time-Doppler maps, and finally outputting the prediction accuracy.

An integrated circuit (IC) employs error codes based on fields of data for protecting data transferred from a first circuit to a second circuit on the IC. Each bit of a generated error code is based on one or more fields of the data rather than on consecutive signal bits of a bus. Upon receiving the data in a second circuit, the error code is employed to determine whether the data has been transferred without an error. In case of an error, a response circuit generates an error signal having an error type corresponding to the data fields in which errors are detected. In some examples, the transferred data comprises a transaction request and the error signal indicates whether 10 the transaction request has failed, the transaction request may be retried, or the transaction request may be completed despite the error.

The application discloses a kind of Φ-OTDR system coherence fading inhibition method and device based on spatial resolution internal redundant data, specifically: first, simulate random one-dimensional continuous signal and noise waveform, and carry out channel replication expansion, add different random noise to the waveform of each channel, obtain multi-channel signal and noise data set;Then set the structure, parameter, activation function, loss function and optimizer of time sequence neural network model, data set is sent into model and is trained;Then judge whether the model error meets the requirements, if it does not meet the requirements, adjust the structure, parameter, activation function, loss function and optimizer of model, retrain the model;If it meets the requirements, the actual data detected by Φ-OTDR system is processed and packed, and is sent into the trained model for prediction, to obtain the signal characteristics distributed along the whole optical fiber.The application has low complexity, reduces the influence of coherence fading noise on Φ-OTDR system, and improves the transmission ability of the system.

The embodiment of the invention provides a digital human control method, system and device for a private interaction terminal, and the method comprises the steps: obtaining a continuous signal value collected by a sensor, and generating a time sequence feature vector corresponding to the continuous signal value; determining an emotion tag corresponding to the time sequence feature vector, and an action tag and a voice performance parameter associated with the emotion tag, the emotion tag representing the current user emotion, the action tag representing the type of the action currently executed by the digital person, and the voice performance parameter representing the voice intonation currently sent by the digital person; and driving the digital person to execute the corresponding facial expression, body action and voice intonation based on the emotion label, the action label and the voice expression parameter. The method has the capability of recognizing complex behavior states, so that changes of expressions and actions of the digital human are more natural.

The invention discloses a motor rotor angle determination method, system and device and a medium, and relates to the technical field of motor detection.The method comprises the steps that angle collection is conducted on a rotor of an electric power steering motor in real time through a magnetic encoder, and a real-time detection angle is obtained; acquiring a historical amplitude, a historical angle tracking error and a historical zero offset value output by the zero offset compensation adaptive wave trap after previous angle acquisition, and a historical angle output by the phase-locked loop; performing adaptive processing based on the real-time detection angle, the historical amplitude, the historical angle tracking error, the historical angle and the historical zero offset value by using a zero offset compensation adaptive wave trap to obtain a real-time reference signal; and inputting the real-time reference signal into a phase-locked loop for angle tracking error compensation to obtain a real-time target angle of the rotor. According to the invention, continuous signal processing can be directly carried out through the zero offset compensation adaptive wave trap and the phase-locked loop, and the calculation amount and noise influence are reduced, so that the result accuracy can be improved.

The present application relates to the technical field of fan blades, and particularly to a fan blade fault diagnosis method and system based on voiceprint and vibration fusion analysis, which forms a joint observation unit by synchronously and consistently checking blade voiceprint segments and vibration segments in the same time window, and gives a diagnosis qualification based on the stability of joint energy in the window within the joint observation unit; the cooperative relationship between the voiceprint and the vibration is described by using a cooperative relationship measure with an energy regularization term, and a fusion relationship violation damage judgment is formed by combining local time evolution deviation, so as to convert continuous signals into discrete blade fault events. Then, the fault events are aggregated into event clusters according to time adjacency, and the cluster level severity is calculated, the severity is mapped to pre-configured diagnosis classification and disposal rules, an explicit blade fault diagnosis conclusion is output, and disposal actions such as alarm, work order or risk prompt are triggered, so that the diagnosis result is directly implemented in the fan monitoring and operation system.

The invention relates to the technical field of power system automation, and particularly discloses a power network fault early warning method based on a large model, and the method comprises the steps: directly mapping the data of a high-frequency power sensor into a time sequence soft prompt vector which can be understood by the large model through a lightweight encoder and a linear projection technology; deep alignment of continuous signals and discrete semantics is realized, and information loss and efficiency bottleneck caused by numerical textualization are avoided. And then, directionally retrieving an operation and maintenance knowledge base by using the soft prompt vector, introducing a cross-modal affinity matrix to construct a semantic gating mechanism, dynamically screening and enhancing retrieved key knowledge fragments according to real-time waveform characteristics, and automatically inhibiting redundant text noise irrelevant to the current working condition. And finally, deep attention interaction and reasoning are performed on a composite sequence formed by an instruction, enhanced knowledge and soft prompt through a large model, a control signal containing fault classification and disposal suggestions is output, and real-time accurate early warning considering high-frequency signal sensitivity and expert knowledge logicality is realized.

This invention discloses an electronic image sharpening method based on image processing, comprising: mapping the image to an initial continuous signal function continuously distributed in coordinates; constructing a liquid time constant prediction branch and generating liquid response parameters based on local gradient and contrast features; reconstructing the discrete state transition matrix into a dynamic evolution kernel, constructing a liquid state space model architecture and performing bidirectional scanning to obtain a latent space state feature sequence; calculating an edge gain adjustment factor and coupling it to the input weight matrix to generate an evolutionary feature tensor; performing spatiotemporal smoothing correction in conjunction with sensor motion parameters; and outputting the electronic image through spatial dimension recovery and implicit function resampling. This invention achieves enhanced edge details while suppressing background noise, eliminating displacement deviations and artifacts, and significantly improving the sharpness and structural fidelity of electronic images.

The application discloses an integrated flexible communication system compatible with FDD and TDD, which comprises a radio frequency transmitting unit, a radio frequency receiving unit, a continuous signal processing unit, a special signal processing unit, a burst signal processing unit and a state machine control unit. The application recombines the physical layer, the coding and synchronization sublayer, the MAC sublayer, the frame sublayer, the I / O sublayer and the network layer in the FDD communication system and the TDD communication system according to the function implementation mechanism, breaks the traditional layered architecture, fuses the common modules dispersed in each sublayer according to the large data processing mechanism and the scheduling control processing mechanism, trims the control and signal processing units exclusive to each sublayer, greatly reduces the processing and scheduling overhead in the traditional layered implementation mode, and reduces the hardware implementation complexity of each function mechanism, thereby most supporting the stringent requirement of the deep space exploration task on product miniaturization.

This invention discloses a signal Doppler tolerance and sidelobe optimization method based on a weighted ambiguity function template. The method includes determining a discrete ambiguity function based on a two-dimensional ambiguity function of a continuous signal and a radar transmitted signal; obtaining matched filtering results for signals with different Doppler frequency shifts and determining the main lobe and sidelobe positions based on the Doppler frequency shift results; for the Doppler frequency shift case, establishing a cost function for Doppler tolerance optimization and a weighted cost function for joint optimization of Doppler tolerance and sidelobe based on the main lobe and sidelobe positions, respectively; setting the weight coefficients of the weighted cost function according to signal characteristic requirements to obtain the target cost function; and using simulation parameters for iterative updating to obtain the optimization result. This invention can improve signal Doppler tolerance while reducing signal sidelobes, significantly improving the practicality of random noise signals; and it allows for setting weight coefficients according to signal characteristic requirements to adjust the optimization ratio of signal Doppler tolerance and sidelobe, providing strong flexibility.

The application discloses a satellite navigation receiver signal processing method and system, and belongs to the technical field of satellite navigation. The method comprises the following steps: step 1, initializing the satellite navigation receiver, and establishing a communication link between the satellite navigation receiver and an RTK reference station; step 2, processing received satellite signals by the satellite navigation receiver to obtain satellite ephemeris parameters; then combining the received reference station data to form basic data; step 3, constructing a carrier phase double difference prediction model and a code phase prediction model, combining the basic data, respectively calculating local carrier signal control quantities and local code signal control quantities, and writing the control quantities into a digital control oscillator; and step 4, performing position solving, updating a satellite navigation receiver predicted position by using a new position obtained by solving, and feeding back to step 3 to form a closed loop control of position solving assisted signal tracking. The application can realize high-precision and continuous signal tracking in a complex environment.

The subject matter of this specification can be implemented in, among other things, a system that includes a first light source to produce a pulsed beam and a second light source to produce a continuous beam, a modulator to impart a modulation to the second beam, and an optical interface subsystem to transmit the pulsed beam and the continuous beam to an outside environment and to detect a plurality of signals reflected from the outside environment. The system further includes one or more circuits configured to identify associations of various reflected pulsed signals, used to detect distance to various objects in the environment, with correct reflected continuous signals, used to detect velocities of the objects. The one or more circuits identify the associations based on the modulation of the detected continuous signals.

The invention relates to a multi-user burst detection method and device, and the method comprises the steps: carrying out the digital gain adjustment of a received signal, and obtaining an adjusted signal; determining a burst judgment threshold; performing frequency offset coarse compensation on the local synchronization sequence to obtain a plurality of coarse compensation sequences with the length of N; selecting a plurality of sampling point positions from the sampling point positions between the minimum sampling point position and the maximum sampling point position as starting sampling point positions; taking the position of each initial sampling point as a starting point, intercepting N continuous signal values from the adjusted signal, and obtaining an intercepted signal corresponding to the position of the initial sampling point; combining each coarse compensation sequence and the intercepted signal corresponding to the position of each initial sampling point in pairs to form a plurality of sequence-signal combination pairs; determining a correlation peak sequence of each sequence-signal combination pair; determining a peak value and a frequency offset estimation value of each sequence-signal combination pair; and detecting time domain initial positions and frequency offset estimation values of a plurality of users.

The invention discloses a network connection vehicle speed optimization control method and system for a continuous signal intersection, and belongs to the technical field of intelligent traffic control, a hierarchical speed control framework is adopted, the network connection vehicle speed optimization control method comprises a global speed planning layer, a local speed tracking layer and a communication layer, and the specific steps are as follows: the global speed planning layer estimates an intersection queuing length based on an LWR model; a continuous passing time window is predicted through forward solving and reverse recursion, and an expected comfortable vehicle speed curve is generated through quintic polynomial trajectory planning; the local speed tracking layer constructs a multi-objective optimization function under a model prediction control framework, integrates a reinforcement learning element controller to adjust a weight coefficient on line, and adopts a sequential quadratic programming algorithm to solve an optimal torque and speed trajectory; according to the invention, the vehicle can continuously pass through a plurality of intersections at a smooth and comfortable speed, so that parking waiting, urgent acceleration and deceleration are effectively reduced, the passing efficiency and the riding comfort are improved, and the energy consumption of the vehicle is reduced.

The application relates to a fast wideband signal detection method, device and equipment based on a time-frequency graph and a medium. The method determines the starting and ending frequencies of a wideband signal by performing Gaussian blurring, time domain averaging, gradient estimation and gradient matching on a time-frequency graph of an electromagnetic signal; verifies and scores the starting and ending frequency positions of each row on the time-frequency graph, and if the score passes, the row contains a wideband signal, otherwise, the row does not contain a wideband signal; determines whether the wideband signal is a continuous signal, and if it is not, calculates the starting and ending times of a wideband signal pulse in the time-frequency graph according to the number of rows containing the wideband signal; and obtains the characteristics of the wideband signal in the time-frequency graph according to the starting and ending frequencies of the wideband signal and the starting and ending times of the wideband signal pulse. The method proposes different feature extraction processes and detection decision mechanisms, guarantees the timeliness of detection, and provides theoretical support for fast wideband signal detection in complex environments.

The application relates to the technical field of circuits, and discloses a neural network optimization circuit, which can simultaneously train multiple target training data and simultaneously optimize errors of the multiple target training data, has high parallelism, fast calculation speed, on-chip learning ability, no non-continuous signals such as switch signals and clock signals in the training process, realizes fast convergence under the guarantee of strict mathematical theory, uses analog circuits, and has low expansion cost. Furthermore, the second differentiator is placed from the disturbance source to the position of the output of the adder, the original convergence direction of the circuit can be maintained, the requirement for disturbance power is reduced, and the stability of the network is improved.

The embodiment of the invention relates to the technical field of laser radars, and discloses a centroid extraction method, a laser radar, a robot and a storage medium, and the centroid extraction method comprises the steps: firstly obtaining an original echo signal curve outputted after the laser radar detects a target object, dividing the original echo signal curve into N continuous signal section curves, for each signal section curve, determining an asymmetric Gaussian convolution kernel matched with the signal section curve, and then performing convolution operation on the asymmetric Gaussian convolution kernel and an original energy value in the signal section curve to obtain a first target energy value corresponding to the signal section curve, and so on until M first target energy values are obtained, and finally, extracting the centroid according to the M first target energy values and the corresponding pixel positions. According to the method, the asymmetric Gaussian convolution kernel is adopted for convolution operation, the local form of the signal is precisely fitted, the asymmetric Gaussian convolution kernel is differentially matched, the accuracy of centroid extraction is improved, and then the ranging accuracy of the laser radar is improved.

The invention relates to the technical field of medical instruments, in particular to a fetal heart rate acceleration recognition method and system. The method comprises the following steps: acquiring a Doppler echo original signal of a fetal heart, comparing the Doppler echo original signal with a preset threshold after simulation conditioning, and outputting an effective signal starting point and an initial data stream; on the basis of the effective signal starting point and the initial data stream, collecting is stopped after preset-length data is accumulated, audio is played after filtering and amplifying processing, if the continuous signal duration exceeds a set threshold value, current data segment retention is stopped, and the processed audio and the current data segment are output; in combination with the effective trigger identifier and the instantaneous fetal heart rate, the steps are executed circularly, interference signals are eliminated, and a real-time fetal heart rate monitoring result and an abnormal prompt are output; by means of accurate screening, real-time processing and dynamic threshold value adaptation of whole-process signals, fetal heart monitoring with high anti-interference capacity and high real-time performance is achieved, the real-time fetal heart rate and an abnormal prompt can be accurately output, and the fetal heart monitoring quality during pregnancy is effectively improved.

The invention relates to the field of strain detection, in particular to a self-adaptive strain detection method and system and a medium. The method comprises the following steps: inputting grid point coordinates, noisy displacement data and a maximum smooth half window; calculating the overall noise level sigma through local linear regression analysis; extracting local strain curvature characteristic quantity through cubic polynomial regression; establishing a noise and curvature balance relation based on the sigma and the curvature characteristic quantity, and calculating an adaptive smooth half window; obtaining the strain estimation value of each grid point through linear polynomial regression, and finally obtaining the strain distribution of the whole field. According to the method, the optimal smooth window can be automatically adjusted without manual intervention, balance is achieved between noise suppression and detail reservation, the problem that a traditional fixed window method is insufficient in precision in a non-uniform deformation area is solved, high-precision full-field strain detection of a noise-containing displacement field is achieved, and the detection precision is improved. The method is suitable for derivative calculation of digital image related systems and various noisy continuous signals.

The application belongs to the technical field of wireless positioning, and discloses a method and device for wireless positioning and multipath signal generation, frequency, amplitude, modulation and delay data are issued in real time by a host computer, linear interpolation is performed on transmission delay data by a digital processing module, and a signal instantaneous value is generated by using a phase increment calculation combined with a lookup table mode, so that the multipath signal dynamically changing in a wireless positioning scene can be accurately simulated, the carrier phase and delay characteristics are taken into account, the problem that a traditional method only pays attention to pseudo code phase change and ignores the carrier phase delay characteristic is solved, and the signal transmission law in a complex motion scene can be more truly restored; interpolation processing and buffer cache output are used, so that continuous and stable signal output can be realized, accumulated errors caused by the fact that a frequency word cannot be divided by an integer are effectively avoided, the simulation accuracy under long-time operation conditions is improved, and the signal generation stability and reliability are ensured; and continuous signals are directly output through digital-to-analog conversion and signal conditioning.

The present application relates to the field of strain detection, and particularly to a self-adaptive strain detection method, system and medium. The method comprises: inputting grid point coordinates, noisy displacement data and a maximum smoothing half window; calculating an overall noise level sigma through local linear regression analysis; extracting a local strain curvature characteristic quantity through cubic polynomial regression; establishing a noise and curvature balance relationship based on sigma and the curvature characteristic quantity, and calculating an adaptive smoothing half window; obtaining strain estimation values of each grid point through linear polynomial regression, and finally obtaining overall strain distribution. The method can automatically adjust the optimal smoothing window without manual intervention, balances between noise suppression and detail preservation, solves the problem of insufficient accuracy of traditional fixed window methods in non-uniform deformation areas, realizes high-precision full-field strain detection of noisy displacement fields, and is suitable for derivative calculation of digital image correlation systems and various noisy continuous signals.

This application discloses a method and apparatus for determining SAS (Self-Rating Anxiety) patients based on PPG signals, relating to the field of biomedical technology. The method includes: acquiring a target continuous PPG signal and blood oxygen saturation data of the patient within a set time period; determining the trough position of the target continuous PPG signal based on a window sliding minimum detection method, and segmenting the target continuous PPG signal into at least two individual PPG signals; determining at least one risk period corresponding to the patient from the set time period based on the blood oxygen saturation data, and the blood oxygen change amplitude corresponding to each risk period; performing multi-peak fitting processing on each individual PPG signal using a Gaussian function to obtain the Gaussian mean change amplitude corresponding to each risk period; and determining the patient's SAS result based on the blood oxygen change amplitude and Gaussian mean change amplitude corresponding to each risk period, along with the judgment criteria. In this application, the Gaussian mean is used instead of heart rate, which effectively ignores the interference of high-frequency signals, making the SAS detection results more reliable.

This utility model provides a geological disaster monitoring and protection network. The monitoring and protection network consists of a mesh sensing unit, a signal processing unit, and an adaptive fixing component. The mesh sensing unit is a grid of continuous signal sensing lines covered with an environmental protection layer. The signal processing unit is electrically connected to both ends of the sensing lines, detects continuity and outputs a level signal. The adaptive fixing component includes anchors and a clamping mechanism. The anchor end is inserted into the geological body, and the mounting end is connected to the base of the clamping mechanism. The clamping mechanism fixes the nodes of the detection network through clamping channels and closures, and the sensing lines remain conductive within the channels. The anchors and clamping mechanism are connected at adjustable angles. The clamping channels are cross-shaped, and the closures are spiral locking caps. Adjacent sensing units are connected in series through plug-in terminals. This monitoring and protection network provides comprehensive monitoring, is stable and reliable, easy to install and maintain, highly adaptable to the environment, and also has a protective function.