325 results about "Fault indicator" patented technology

The invention relates to the field of heat exchanger anomaly detection and fault diagnosis, and discloses a heat exchanger anomaly detection and quantitative diagnosis method, system, medium and equipment under multiple unstable working conditions, and the method comprises the steps: collecting data of key parts of a heat exchanger, and preprocessing the data, the data including online monitoring data and offline data; according to the preprocessed data, fluctuation working condition sensitive indexes are constructed, the fluctuation working condition sensitive indexes comprise leakage fault indexes and scaling fault indexes, and follow-up characteristic analysis indexes of the online monitoring data are obtained through the fluctuation working condition sensitive indexes so as to construct an unsteady-state multi-working-condition anomaly detection model; leakage fault quantitative diagnosis and scaling fault quantitative diagnosis are carried out according to the abnormal detection model under the unsteady-state multiple working conditions. Abnormality detection of the heat exchanger under multiple unstable working conditions can be achieved, and the accuracy of abnormality detection is improved.

The invention discloses a distribution network recording fault accurate positioning method based on big data analysis, and relates to the technical field of power distribution network fault positioning, and the method comprises the steps: deploying a fault indicator; setting a trigger threshold value, and triggering high-precision transient recording to generate recording data when the current or the electric field suddenly changes; carrying out time alignment on the recording data and synchronously acquired current intensity, electric field intensity, cable temperature and environment data, extracting transient characteristics and environment characteristics after wavelet transform denoising, and combining the transient characteristics with the environment characteristics to generate a comprehensive characteristic matrix; binding the comprehensive characteristic matrix and the line topology information, and uploading the information to a monitoring center through encryption communication; formulating a dynamic threshold association rule, and judging a fault type; the monitoring center matches the current transient waveform with a historical database and calculates a fault signal propagation time difference; and calculating a fault distance by combining line topology information, and fusing the fault signal propagation time difference and the fault distance to obtain a fault coordinate.

The invention relates to an FTU (feeder terminal unit) broken line fault monitoring method, which comprises the following steps of: performing electrical data acquisition on an FTU line through a preset electrical mutual inductor to obtain electrical data; wherein the electrical data comprises voltage data and current data; performing phase angle calculation on the voltage data and the current data to obtain a phase angle difference value; if the phase angle difference value is not in the standard range, calling a database to obtain the attribute of the FTU line; through a preset distributed parameter model, based on the attribute of the line, the phase angle and the electrical data, carrying out broken line positioning on the line to obtain a broken line area; performing dynamic feature identification on the electrical parameters corresponding to the broken line area to obtain fault dynamic features, and performing fault type analysis on the broken line area based on the fault dynamic features to obtain a fault type monitoring report; the technical problems that a traditional fault monitoring method depends on manual inspection and a simple fault indicator, and it is difficult to meet the positioning precision and judge the fault type are solved.

The present invention belongs to the technical field of signal processing, and particularly relates to a multi-source data fusion fault diagnosis method and system based on the DS evidence theory. The method of the present invention comprises: first, collecting multi-source information of a mechanical device, wherein the multi-source information includes vibration data, image data and sound data; respectively calculating corresponding feature indicators; then, using a PCA algorithm to perform dimensionality reduction processing on the indicators; using a Bayesian fault diagnosis model to perform fault diagnosis, so as to obtain a diagnosis result from each sensor; and then, using the DS evidence theory to perform fault fusion diagnosis. The present invention can comprehensively consider the characteristics of various types of data, extract more effective fault indicators, achieve more comprehensive fault identification, and fuse diagnosis results from a plurality of sensors, thereby ensuring the accuracy of final diagnosis. The present invention is suitable for fault diagnosis of various complex mechanical systems.

The invention relates to a digital twin simulation and optimization method for a large-scale stamping production line, and the method comprises a rapid lightweight modeling technology, a multifunctional fault indicator feedback technology, a three-dimensional dynamic real-time driving simulation technology, and a big data analysis intelligent optimization decision technology. According to the method, virtual-real fusion and a three-dimensional dynamic technology are combined, a three-dimensional visual user interface oriented to the whole manufacturing process is developed based on Unity, the whole stamping production line is simulated in real time, potential problems are predicted and solved through real-time monitoring of the stamping production line, various problems influencing the production efficiency in the production process are optimized, and the manual management and control difficulty is reduced.

The invention discloses a power grid fault intelligent diagnosis method, system and device based on big data and a medium, and relates to the technical field of data processing, and the method comprises the steps: obtaining power grid electrical parameters, setting a first monitoring time period and a second monitoring time period, and obtaining a first monitoring parameter value sequence and a second monitoring parameter value sequence; obtaining a first increment value and a first attenuation value, obtaining a second increment value and a second attenuation value, obtaining a predicted increment value corresponding to the electrical parameters of the power grid based on the prediction model, the first increment value and the second increment value, and obtaining a predicted attenuation value corresponding to the electrical parameters of the power grid based on the prediction model, the first attenuation value and the second attenuation value; obtaining an upper fluctuation threshold value and a lower fluctuation threshold value corresponding to the electrical parameters of the power grid, and obtaining a fault index according to the upper fluctuation threshold value, the lower fluctuation threshold value, the prediction attenuation value and the prediction increment value; and obtaining a power grid fault diagnosis result according to the fault index. The method has the advantages of accurate fault diagnosis, self-adaptive threshold and full-period management.

The invention provides an evaluation method and device for set membership fault detection and application, and belongs to the technical field of fault diagnosability. The performance of the fault detection system is evaluated according to a minimum detectable fault index of the fault detection system, and the minimum detectable fault index is a fault amplitude when a feasible set with a fault residual error and a feasible set without a fault residual error of the system to be detected are just separated. Combining the used observer equation to obtain a residual system equation of a fault-free state and a fault state of the system to be detected; measuring a noise range by using geometry characterization, and obtaining residual feasible set characterization of a fault-free state and a fault state of the to-be-detected system in combination with set membership operation; and determining the minimum detectable fault index of the to-be-detected system. According to the method, observer design optimization, control system design and correction system model parameters can be guided, so that the control system is more stable.

The invention relates to the technical field of fault positioning, in particular to a power distribution network line fault positioning method and system based on a fault indicator, and the method comprises the following steps: obtaining node current data, calculating a jump rate, screening an early warning node, recognizing an intersection section, determining a fault position, and generating a recognition result. According to the invention, through collecting periodic current data of each node fault indicator, combining node numbers and topological structure mapping, systematically establishing a current sequence table and calculating a current increment difference value in unit time, and through grade division and periodic stability identification of a jump rate, key nodes with early warning characteristics can be accurately screened. The method comprises the following steps of: acquiring a path intersection area, positioning a fault centralized distribution section by virtue of jump intensity trend change analysis of the path intersection area, and determining a fault initial position and a grade identifier in combination with a comparison relationship between a sampling time point and trigger delay between nodes, so that accurate identification and quick response of a multi-path fault are realized under a complex topological structure of a power distribution network.

Disclosed herein are systems and methods for self-isolation of power-management integrated circuits (PMICs) of memory modules under and in response to fault conditions. In an embodiment, a PMIC is operably engaged with a memory module that is operably engaged with a platform. The memory module includes a non-volatile-memory block having a power supply controlled by the PMIC. The PMIC has a critical-fault signal pin that can be asserted to shut down the platform. The PMIC determines whether at least one critical fault occurred during a prior cycle, and also determines whether a critical fault occurs during a bootup sequence during a current cycle. Based on determining that a prior-cycle critical fault occurred and that a critical fault occurs during the bootup sequence, the PMIC sets a critical-fault indicator corresponding to the current critical fault; powers down the power supply; and does not assert the critical-fault signal pin.

An MMC-based open-circuit fault diagnosis method and system for a medium-voltage direct-current converter. The method comprises: acquiring on / off states and voltage and current signal data of a sub-module in a modular multilevel converter when the sub-module is in a normal operating state and a fault state; establishing different types of fault determination logic on the basis of the on / off states and the voltage and current signal data of the sub-module when same is in the normal operating state and the fault state, and establishing a fault indicator on the basis of different types of fault determination logic; establishing a sub-module capacitor current observation equation on the basis of the structure of the sub-module in the modular multilevel converter, and determining the relationship between an actual value and a predicted value of a capacitor current and a first threshold value; and on the basis of a determination result regarding the relationship between the actual value and the predicted value of the capacitor current and the first threshold value, displaying an open-circuit fault diagnosis result in combination with the fault indicator. In the method and the system, a capacitor current path and on / off state information are used to perform fault diagnosis quickly and accurately when a fault occurs, thereby providing a solution for actual engineering application.

The invention discloses a distribution line fault positioning method and system based on a Beidou system, and relates to the technical field of line fault analysis, and the method comprises the steps: collecting key node data, defining a node state according to the state data of a distributed power supply, a fault indicator and an intelligent electric meter, constructing a data matrix, and calculating a principal component matrix of the state data; constructing a fault mode recognition model for the principal component matrixes of different state data, and performing model fusion; and calculating the state probability of the node at the next moment based on the historical fault data. According to the method, the model is constructed through the principal component matrix based on the three view angles of the distributed power supply, the fault indicator and the intelligent electric meter, the multi-dimensional characteristics of the fault can be reflected more comprehensively, and the overall fault state of the current power system can be represented more accurately through the comprehensive fault mode vector generated through view angle fusion. Deviation and blind areas possibly existing in a single-view-angle model are reduced, and therefore the fault positioning precision is improved.

The invention relates to the technical field of electric power, and particularly discloses a power distribution branch box monitoring system and method based on a fault indicator, which can compensate for short-time limitation of real-time data by performing compensation and correction through historical load data and operation instruction information, so that a dynamic topological structure diagram at a first moment is more fit with an actual power grid operation state, and the power distribution branch box monitoring accuracy is improved. It is guaranteed that the topological structure of the dynamic topological structure diagram is dynamically updated along with changes of a power grid, the corrected dynamic topological structure diagram can accurately reflect the real connection relation and the electrical distance of the branch box, the quantization result of the branch correlation degree matrix is made to be more suitable for the correlation degree of the actual power grid, and therefore the reliability of the branch correlation degree matrix is improved through dynamic construction logic of the dynamic topological structure diagram. The method can adapt to the dynamic change process of the topological graph of the power distribution network, achieves the effect of dynamically monitoring the fault of the power distribution branch box, and achieves the purpose of reducing the false alarm rate.

The invention discloses a transformer operation state comprehensive intelligent monitoring system, which comprises an information acquisition unit, a preprocessing unit, a core analysis unit, an optimization design unit and an early warning prompt unit, and is characterized in that operation data and environment data of a transformer are acquired through the information acquisition unit, and are preliminarily analyzed through the preprocessing unit; a transformer monitoring model is constructed through the core analysis unit, an influence function between environment data and operation data is constructed by monitoring the working environment of the transformer, the sensitivity of the transformer to environment change is improved, the accuracy of the transformer monitoring model is analyzed through the optimization design unit, fault indexes are processed in a targeted mode, and the fault detection accuracy is improved. The method improves the accuracy of fault recovery and risk response, deeply analyzes and evaluates the predicted risk degree of the transformer through the early warning prompt unit, and generates an early warning prompt signal to achieve the early warning processing of the fault, so as to deal with the sudden influence of the abnormal climate environment change on the transformer.

A memory built-in self-test (BIST) controller, corresponding to a partition BIST controller, is configured to control memory testing in one or more corresponding static random access memories (RAMs) and has a first corresponding register configured to store a failure indicator for each of the one or more corresponding RAMs and a second corresponding register configured to store an uncorrectable failure indicator for each of the one or more corresponding RAMs. The partition BIST controller is configured to generate, based on the first and second registers of the MBIST controller, a first in-field test status indicator which indicates whether a failure occurred during memory testing of any RAM corresponding to the partition BIST controller and a second in-field test status indicator which indicates whether an uncorrectable failure occurred during the memory testing of any RAM corresponding to the partition BIST controller.

The invention discloses a power line troubleshooting practical training device which comprises an operation panel and a power supply module. The operation panel is used for arranging wires according to a preset circuit diagram and is detachably provided with a plurality of analog switches, a plurality of fault indicators, a display operation screen, a plurality of fault points, a plurality of data acquisition terminal units and a core control module; the power supply module is used for supplying power to the operation panel; the analog switch simulates switching on and switching off in a manual or automatic mode so as to achieve the effect of power supply switching. The fault point can simulate a fault condition; the fault indicator is connected with a specified fault point; the core control module is connected with the fault indicator and the data acquisition terminal unit, and is used for selecting the fault type and fault point setting of the current simulation line according to the signal of the display operation screen, and simulating the common fault type. According to the invention, a real-time simulation technology is adopted, so that trainees can carry out troubleshooting and processing in an approximately real environment, and thus the fault handling capability is improved.

The utility model discloses an electrical grounding device for a high-rise building, and relates to the technical field of electrical grounding equipment, the upper part of a box body is in threaded connection with a wire placing pipe, two sides of the inner wall of the box body are respectively provided with two groups of butt joint supports through bolts, a junction box is arranged at the center of the two groups of butt joint supports, and the junction box is connected with the wire placing pipe. A grounding switch is placed below the junction box, a bolt clamping structure is arranged between the grounding switch and the box body, and a heat dissipation window is arranged on the right side of the box body. A grounding wire enters a wire body through a wire placing pipe above a box body, and the grounding wire is placed by a junction box installed through a connecting plate in the box body, so that the grounding wire is connected with a fault indicator, a grounding protector and a potential balance box; the grounding wire in the junction box is detected, so that faults can be conveniently detected.

The invention relates to a multi-source heterogeneous data linkage power distribution data transmission safety supervision method, which comprises the following steps that: a safety supervision gateway receives heterogeneous data streams from an intelligent electric meter, a power distribution terminal, a fault indicator and a distributed energy monitoring unit, and analyzes original data of a protocol by using a multi-protocol analysis engine; the method comprises the following steps: analyzing data, extracting standardized data load and metadata, classifying according to equipment types, content criticality and business domains on the basis of analyzed data and a preset strategy library, dynamically marking security levels of the data, continuously monitoring data sending frequency, flow, connection duration and instruction sequence rationality of each terminal in a transmission process, and transmitting the data to the terminal. And carrying out dynamic trust evaluation and updating a trust value, forwarding encrypted or signed data to a power distribution master station or a data center through an optimal path, carrying out deep detection in the whole process, and recording a full-quantity security log which comprises a source IP, a target IP, a data size, a timestamp and an event type.

The invention discloses a power distribution network master station fault positioning method and system based on multi-dimensional information fusion, and relates to the technical field of intelligent power grids, and the method comprises the steps: obtaining FTU electrical quantity data, circuit breaker monitoring terminal switching value data and fault indicator state signal data; constructing a power distribution network structure matrix D in a normal operation state, and generating a fault information matrix G based on the state signal data; performing normalization processing on the electrical quantity and switching value data, and converting the electrical quantity and switching value data into a time axis image; inputting the image sequence into a convolutional neural network for deep learning, extracting fault features and outputting an inter-node fault initial probability matrix Q; and fusing Q, D, G and three types of original data, performing multi-dimensional information fusion by adopting a D-S evidence theory, generating a final fault probability matrix S, and outputting a fault section and type with the highest probability. According to the method, CNN feature extraction is guided by a topological matrix D / G, and the misjudgment rate of fault positioning is reduced through D-S fusion of electrical features, topological association and equipment state weights.

The invention discloses a multi-feature combined double three-phase permanent magnet synchronous motor turn-to-turn short circuit fault diagnosis method, which belongs to the technical field of motor fault diagnosis and comprises the following steps of: establishing a turn-to-turn short circuit fault mathematical model of a double three-phase permanent magnet synchronous motor under a rotating coordinate system; extracting a plurality of fault features according to the obtained mathematical model, jointly reconstructing a fault index, and introducing a rotating speed into the fault index to obtain a new fault index; and comparing the new fault index with a set threshold value, and judging whether the motor has a fault or not. According to the method, the turn-to-turn short circuit fault mathematical model of the dual three-phase permanent magnet synchronous motor under the rotating coordinate system is set, and a plurality of fault features are adopted to construct the fault indexes, so that the problems of high error / missed diagnosis rate, difficulty in early fault recognition and the like in fault diagnosis under a single feature are solved, and the influence of the rotating speed on the fault diagnosis is reduced.

The invention discloses a fault indicator optimal configuration method based on a graph neural network and a related device, and belongs to the technical field of fault indicator optimal configuration, and the method comprises the steps: collecting topological data and historical operation data of a power distribution network; constructing a graph neural network model based on the topological data of the power distribution network; the graph neural network model comprises an input layer, a graph convolution layer, a graph pooling layer, a full connection layer and an output layer which are connected in sequence; constructing an objective function, wherein the objective function comprises coverage, a cost function and a fault indicator installation condition; using historical operation data of the power distribution network as a training set to train a graph neural network model; optimizing parameters of the graph neural network model by minimizing the objective function to obtain a trained graph neural network model; and obtaining a fault indicator configuration strategy based on the trained graph neural network model. The optimal deployment position of the fault indicator is automatically selected through an intelligent optimization algorithm, so that the coverage efficiency and reliability of the fault indicator are improved.

The invention discloses a power distribution network fault risk sensing method, which comprises the following steps: S1, data acquisition and monitoring: collecting operation data of a power grid in real time through a sensor, an intelligent electric meter, a fault indicator and a remote terminal unit which are installed in the power distribution network; s2, data preprocessing: cleaning the collected original data, removing abnormal values, processing missing data, and unifying data formats; s3, real-time analysis and monitoring: analyzing the real-time data flow by using a big data analysis technology, monitoring the operation state of the power grid, and identifying an abnormal condition; s4, fault early warning model establishment: based on the historical fault data and the current operation data, establishing a fault early warning model for predicting the possibility of fault occurrence and the possible fault type; and S5, risk assessment. According to the invention, potential faults can be sensed in advance, and key information is provided for preventive maintenance and emergency response, so that the stability and reliability of the power distribution network are improved.

The invention relates to an active lubricating system and method with fault diagnosis, a radiator, a first composition plate and a second composition plate are respectively arranged on the peripheral side of a lubricating oil tank, and a rough filter is mounted at the bottom of the lubricating oil tank; a main oil pump and a backup oil pump on the first combination plate are respectively connected with a first electromagnetic directional valve and a first valve block pipeline, and a rough filter is connected with the first electromagnetic directional valve pipeline; the main fine filter and the backup fine filter on the second combination plate are respectively connected with a second electromagnetic directional valve and a second valve block pipeline, the first valve block and the second electromagnetic directional valve are respectively connected with a radiator pipeline, and the second valve block is connected with a gearbox pipeline; the system collects and analyzes signals of all parts and sensors in real time through the controller, quickly determines the fault occurrence position, and displays the system state and fault information by controlling the fault indicating lamp and the buzzer, so that maintenance personnel can conveniently and timely know the working state of the system and take corresponding measures, and the maintenance efficiency is improved. The controller can be automatically switched to the backup assembly when monitoring that the oil pump and the fine filter in the system break down.

A building management system including one or more storage devices storing instructions thereon that, when executed by one or more processors, cause the one or more processors to ingest asset information; cause a graphical model of the building to include a fault indicator based on the asset information, the fault indicator corresponding to a fault occurring on a first physical asset corresponding to a first virtual asset; cause a display device of a user device to display the graphical model within a user interface; receive a selection of the fault indicator from a user via the user interface; and in response to receiving the selection, cause the user interface to navigate to a fault-driven view of the graphical model depicting the first virtual asset and one or more second virtual assets corresponding to one or more second physical assets affected by the fault occurring on the first physical asset.

The invention discloses a permanent magnet synchronous motor turn-to-turn short circuit fault diagnosis method based on current residual error dual normalization, and the method comprises the following steps: calculating a dq-axis reference voltage and a dq-axis current according to collected three-phase voltage, three-phase current and electrical angle information; calculating an estimated value of dq-axis current according to a linear expansion observer; obtaining a dq-axis current residual error according to the actual value and the estimated value of the dq-axis current; calculating a negative-sequence direct-current component of a dq-axis current residual error by utilizing negative-sequence rotation coordinate transformation; performing amplitude normalization processing on the negative-sequence direct-current component of the dq-axis current residual error to obtain an amplitude-normalized negative-sequence direct-current component; performing data credibility check on the signal with the normalized amplitude, and latching the data when a trigger condition is met; performing frequency normalization processing on the dq-axis current residual error to obtain a negative sequence direct current component with double normalization of amplitude and frequency; calculating the quadratic sum of the normalized dq-axis negative sequence direct-current component so as to construct fault features; and comparing the fault feature with a fault threshold, and defining a fault indicator to map the state of the permanent magnet synchronous motor. According to the invention, the diagnosis of the turn-to-turn short circuit fault under the servo working condition can be realized without additional detection equipment.

The invention discloses a state display device of a hard disk and a control device, method, equipment and medium thereof, and relates to the technical field of servers. A processor can adjust output signals of a first output pin and a second output pin of the processor according to obtained in-place state information, fault state information and positioning information of the hard disk; therefore, corresponding indicating lamps are controlled to execute different display strategies so as to distinguish different states of the hard disk and position the hard disk. The processor and the signal conversion module cooperate with each other, and a plurality of display strategies can be realized by simultaneously controlling a fault indicating lamp and a positioning indicating lamp through a second output pin. According to the technical scheme, the processor can prompt various working states of the hard disk under the condition that only two pins are used, so that the use of the pins of the processor is effectively saved, the resource utilization efficiency is improved, and the expansibility and manageability of the server are remarkably improved.

The invention discloses a high-voltage diverter and a sampling device, and belongs to the technical field of diverters, the high-voltage diverter comprises a main body mechanism, and the main body mechanism is internally provided with a disconnection mechanism used for automatic disconnection when a fault occurs and two terminal mechanisms used for wiring; through the linkage design of the built-in temperature sensing piece and the disconnecting mechanism, automatic and accurate fault protection is achieved, when the internal temperature of equipment abnormally rises due to faults and exceeds a safety threshold value, the temperature sensing piece is heated to deform and triggers the disconnecting mechanism, energy stored by the extension spring is used for rapidly driving the on-off connecting piece to act, a main circuit is reliably disconnected, and the safety of the equipment is improved. Meanwhile, the action can be linked with the top protruding block to be self-locked and protrude out of the surface of the protection shell, an intuitive and striking mechanical fault indicator is formed, accident expansion is effectively prevented, definite fault point positioning can be provided for operation and maintenance personnel, the troubleshooting time is shortened, and the safety and maintainability of the system are improved.

The invention relates to a circuit for realizing multi-path power supply output under-voltage fault indication, and belongs to the field of power supply converters. The invention provides a circuit for realizing multi-path power supply output undervoltage fault indication. The circuit comprises voltage-regulator tubes D2 and D3, resistors R2, R3, R4, R5 and R6, photoelectric couplers U1 and U3, MOS (Metal Oxide Semiconductor) tubes U2 and U4, an indication lamp D1 and a 3.3 V power supply V3. According to the circuit, under-voltage fault monitoring can be carried out on the output voltage of multiple paths of power supplies, the circuit is not limited to whether the outputs of the paths are in common ground or not, the under-voltage threshold value of the output voltage can be set by adjusting the voltage stabilizing value of the voltage stabilizing tube, and when any path is under-voltage, the fault indicating lamp can be triggered to work. Every time one path of output voltage detection is added, a primary optocoupler is connected in series in a detection main loop.

The present invention discloses a method, system, storage medium, and feeder terminal for locating a single-phase grounding fault section. The method includes: upon detecting that the zero-sequence voltage amplitude of a distribution line exceeds a preset voltage threshold, initiating zero-sequence voltage and zero-sequence current recording to obtain a first zero-sequence voltage waveform and a first zero-sequence current waveform; broadcasting a recording instruction and a recording start time to a surrounding area, so that transient recording-type fault indicators in the surrounding area, linked to the feeder terminal, upon receiving the recording instruction, transmit three-phase current recording waveforms for a first preset time period after the recording start time to the feeder terminal; and, when the duration after initiating the recording exceeds a preset time limit, determining the single-phase grounding fault section based on the first zero-sequence voltage waveform, the first zero-sequence current waveform, and all received three-phase current recording waveforms. This method can avoid environmental interference, reduce the communication burden of the distribution master station, and improve fault location accuracy.

The fault indicator shell comprises a main shell body, a gland cover and a connecting piece screw cap shell between the main shell body and the gland cover, an annular groove is formed in the opening end of the main shell body, a sealing ring is placed in the annular groove, and a sealing pressing ring with a wedge-shaped section end is arranged at the opening end of the gland cover and used for pressing the sealing ring. The gland cover is pressed and fixed on the main shell by the screw cap shell, and is in threaded connection with the main shell; by means of a threaded connection mechanism between the screw cap shell and the main shell, pressure is applied to the gland cover, so that the gland cover is stably pressed and fixed on the main shell, it is further ensured that the sealing pressing ring can tightly press the sealing ring, and the high-standard sealing effect is achieved. Besides, the design ingeniously utilizes the characteristic of threaded connection, so that a user can easily complete the tightening operation of the shell only by hand force without depending on any additional auxiliary tool, the mounting and dismounting process of the shell is greatly simplified, and the operation convenience of the user is improved.

Devices, systems and methods for using system-level malfunction indicators to monitor the operation and resiliency of the autonomous driving system components are described. One example of a method for diagnosing a fault in a component of an autonomous vehicle includes receiving, from an electrical sub-component of the component, an electrical signal, receiving, from an electronic sub-component of the component, a message, and determining, based on the electrical signal and the message, an operational status of the component.