356results about How to "Improve fault detection efficiency" patented technology

The invention discloses a plurality of united observer based fault diagnosis and fault-tolerant control device and a method and belongs to the field of aerospace. The plurality of united observer based fault diagnosis and fault-tolerant control device comprises following modules of a fault injection module, a fault diagnosis module, a real time monitoring module and a hardware control module. According to the method, the problem that traditional observer based fault diagnosis methods are limited by conditions is mainly solved, the operation is simple, the implementability is high, and the method can be used for diagnosing faults of actuating mechanisms of a four rotor wing helicopter and verifying feasibility of state monitoring.

The invention discloses a fault detection system based on edge calculation. The fault detection system comprises a cloud server, an edge processing device, and an acquisition device. The cloud serveris used for training a neural network in advance and downloading the trained neural network to the edge processing device. After acquiring the state data of a grid device in a grid system, the acquisition device transmits the state data to the edge processing device. The edge processing device uses the neural network to analyze the state data, and the cloud server determines whether the grid device generates a fault according to an analysis result. It can be seen that the system, by downloading the neural network to the edge processing device, and can analyze the state data first by using theedge processing device during fault detection, thereby reducing the computing pressure of the cloud server and improving the fault detection efficiency.

The invention discloses a method, equipment and a system for diagnosing a failure of a passive optical network (PON). The method comprises the steps of: pre-obtaining identification information of each ONU (Optical Network Unit) in the PON, optical fiber link physical distance and the corresponding peak information of the ONU when the PON is normal; establishing a correspondence table of the identification information and the corresponding peak information of each ONU according to the obtained identification information and the physical distance parameter information of each ONU and the optical fiber link physical distance and the corresponding peak information of the ONU; obtaining corresponding peak information of optical fiber links of all current ONUs in the PON according to the preset failure diagnosis measure; matching the corresponding peak information of the current optical fiber link with the pre-stored leak information, and if corresponding peak position and / or amplitude changes, obtaining the identification information of the ONU corresponding to the changed peak according to the correspondence table; and if not, executing the equipment failure diagnosis. By applying the invention, the failure position can be immediately found and positioned, the failure maintenance time is shortened and the failure detection efficiency is improved.

The embodiment of the invention provides a failure detection method and device for nodes in a cluster system. The method comprises the following steps that: a first node judges whether a first heartbeat message sent by a second node is received in preset time or not, wherein the first node is a neighbor node of the second node, and the first heartbeat message is a heartbeat message which is sent to each neighbor node of the second node in parallel by the second node; under the condition that the first node does not receive the heartbeat message sent by the second node, the first node sends a request message to other neighbor nodes other than the first node in all the neighbor nodes of the second node; the first node receives response messages carrying reception states sent by the other neighbor nodes; and under the condition that the first node determines that other neighbor nodes do not receive the heartbeat message according to the reception states, the first node determines that the second node fails. Through adoption of the failure detection method and device for the nodes in the cluster system, the node failure detection efficiency can be increased.

The invention discloses an LED display system which comprises a detection and control device and an LED display screen, wherein the detection and control device comprises a detection module and a control module; the detection module is provided with a detection submodule, a state feedback submodule and a storage submodule; the control module is provided with a data encoding submodule, a data-check error-correction submodule and a control submodule; the data encoding submodule receives video signals, encodes data and generates display data; the detection submodule is used for detecting the display device and generating detection data; the storage submodule is used for receiving and storing the detection data; the state feedback submodule is used for generating state display data and transmitting the state display data to an external display terminal; the data-check error-correction submodule is used for correcting the display data according to the detection data and transmitting the display data to the control submodule; and the control submodule is used for controlling the display device according to the display data.

The invention discloses a fault detection method based on holohedral polytope filter, and belongs to the field of the fault diagnosis. The method comprises the following steps: establishing a system model of a wireless sensor network system according to a state vector of the wireless sensor network system; determining observation vector according to the system model, iteratively determining the holohedral polytope at the k moment; predicting the estimated holohedral polytope at the k+1 moment according to the holohedral polytope at the k moment; acquiring the observation vector at the k+1 moment, computing a consistency state set of the wireless sensor network at the k+1 moment according to the observation vector at the k+1 moment; detecting whether the consistency state set at the k+1 moment is intersected with the estimated holohedral polytope at the k+1 moment; if detecting that the consistency state set at the k+1 moment is free from intersection with the estimated holohedral polytope at the k+1 moment, determining that the wireless sensor network system at the k+1 moment is in fault. The problem that the wireless sensor network is low in instantaneity while detecting the faultis solved; the practicability of the detection method is increased, and the fault detection efficiency and accuracy rate are improved.

The invention discloses a fault detecting method and device of a power grid video monitoring device. The fault detecting method includes the steps that the fault detecting device obtains a current image shot by the power grid video monitoring device, compares the current image with a prestored historical image shot by the power grid video monitoring device, judges whether faults exist in the current image or not according to the comparison result of the current image and the historical image, and generates first warning information for warning if faults exist in the current image. By means of the fault detecting method and device, the problem that in the prior art, due to the fact that manual browsing is needed, the fault detection efficiency is low is solved, and the fault detection efficiency is improved.

The invention relates to a trans-regional synchronization fault monitoring method, device and system in an electric safety region, computer equipment, and a readable storage medium. The method comprises the following steps: acquiring monitoring data of an operation system in a trans-regional synchronization process, performing state analysis on the operation system according to an acquisition result of the monitoring data to obtain a state analysis result; and generating a fault monitoring result according to the state analysis result. By acquiring the monitoring data of various operation systems in the trans-regional synchronization process and performing the state analysis and fault diagnosis on the operation system based on the acquisition result of the monitoring data, the fault produced in the trans-regional synchronization process can be timely discovered and the fault reason can be determined, the fault detection efficiency is improved, and the operation and maintenance staff can fast repair the produced fault according to the fault monitoring result, thereby guaranteeing the normal operation of the trans-regional data synchronization data of an electric system, and furtherimproving the operation and maintenance efficiency and the working efficiency of an electric automatic system.

An embodiment of the invention discloses a fault detection method and a fault detection device for rotating mechanical equipment, which are used for realizing precise detection of a fault of the rotating mechanical equipment. The fault detection method comprises the steps of: pre-constructing an expert decision-making system used for fault determination and a fault classification model use for fault classification based on historical data; extracting a vibration signal feature value after acquiring an original vibration signal of the rotating mechanical equipment; inputting the vibration signal feature value and acquired equipment data of the rotating mechanical equipment into the expert decision-making system to obtain a fault determination result about whether the rotating mechanical equipment has a fault; further, when the fault exists, inputting the vibration signal feature value and the acquired equipment data of the rotating mechanical equipment into the fault classification model to obtain a fault classification result. The fault detection method and the fault detection device can realize the intelligent fault diagnosis and classification of the rotating mechanical equipmentby utilizing an artificial intelligence algorithm, and improve the efficiency and effectiveness of fault detection.

The invention discloses an analysis system for electrical equipment faults. The analysis system comprises an acquisition module, a receiving unit, an equipment analysis module, a judgment module, an equipment monitoring module, an alarm unit and intelligent equipment; and the acquisition module is used for acquiring electrical equipment information and transmitting a signal to the receiving unit,and the receiving unit receives the electrical equipment information, and performs marking treatment. The specific marking treatment process comprises the following steps: 1, acquiring the electricalequipment information. Related data acquired by the equipment monitoring module and the equipment analysis module are analyzed through the judgment module, related data are calculated, whether the equipment is worn or fails is judged, the remaining time of normal operation of the equipment is determined according to the related data, and a corresponding alarm signal is sent out, so the reliabilityof equipment failure monitoring is improved, equipment damage is avoided, economic losses are reduced, the safety of the device is improved, and the failure detection efficiency is improved.

The invention discloses a method for selecting a wire after single-phase grounding of an underground system. By adopting the method, after single-phase grounding happens in the ungrounded system, a fault wire can be selected according to the change of zero sequence current after a neutral point of a capacitor bank is instantly grounded. The method comprises the following steps: A, additionally installing a control switch and a medium resistor between the neutral point of a capacitor and the ground, and keeping the control switch on the point position during normal operation; B, judging whether single-phase grounding happens in a circuit or not according to the voltage change of a bus bar, and judging that single-phase grounding failure happens when the criterion is that a zero sequence voltage is more than a certain value, a certain phase voltage in three-phase voltages is reduced, and voltages of other two phases rise; C, immediately closing the control switch and putting in a resistor after single-phase grounding is judged to ensure that the grounding mode of the system is turned into grounding through the resistor and the active component of the zero sequence current of the single-phase grounded circuit is greatly increased; and D, tripping the circuit switch to clear the failure after the single-phase grounded circuit is determined.

The invention discloses an optical fiber fault detection device, which comprises an optical time domain reflectometer (OTDR) and an optical switch, wherein the optical switch is connected between an OTDR and a passive optical network, used for enabling the OTDR to be connected with optical distribution node networks (ODNs) whose number is N in the passive optical network and communicated with the OTDR and the ODNs needing detecting, and N is an integer not smaller than 1. Each ODN in the passive optical network comprises an optical fiber fault detection interface for being connected with the optical switch, and the OTDR is used for performing optical fiber fault detection to the ODNs needing detecting. Correspondingly, the invention further comprises an optical fiber fault detection method. The optical fiber fault detection method is easy to implement, convenient to operate and insusceptible to limitation of testing conditions, avoids interrupting tasks being performed by the passive optical network, can be applied to various passive optical networks, improves optical fiber fault detection efficiency and reduces detection cost.

The invention belongs to the technical field of battery management systems and relates to a Bayesian network-based fault detection method. The invention mainly aims to solve the problem of the low fault detection efficiency of an existing battery management system. The Bayesian network-based fault detection method includes the following steps that: a Bayesian network topological structure having conventional fault representation and fault-cause corresponding relations is established; the Bayesian network topological structure is trained, and a conditional probability is obtained; Bayesian network topological structure parameter learning is performed, and the prior probabilities of fault representations are obtained; after a certain fault representation occurs on a battery management system, the Bayesian network topological structure calculates the posterior probabilities of corresponding fault causes according to the prior probability of the corresponding fault representation and the conditional probability; and a fault cause corresponding to the maximum posterior probability is adopted as a fault detection result. With the Bayesian network-based fault detection method of the invention adopted, frequent testing by technicians is not required; the process of fault detection is simplified; and the efficiency of the fault detection of the battery management system is improved. TheBayesian network-based fault detection method is suitable for the battery management system.

The invention discloses a method, apparatus and system of detecting a link fault, and belongs to the field of the Internet technology. The method of detecting a link fault includes the steps: in the state that first equipment is used as a link detection receiving end, according to a preset detection cycle, detecting a link detection message transmitted from second equipment which is taken as a link detection transmitting end in a multicast mode; and when detecting that the quantity of packet loss of the link detection message reaches a first preset threshold, determining that a link fault exists between the first equipment and the second equipment. The method, apparatus and system of detecting a link fault can improve the efficiency of improving link fault detection.

The invention discloses a failure isolation method and a failure isolation system for a video server and an Internet protocol (IP) network in an Internet protocol television (IPTV) network. The method comprises the following steps of: performing passive video media stream data capturing at a certain intermediate point of the IPTV network by using acquisition equipment; processing video media stream data layer by layer according to an IPTV protocol stack, and calculating a lost media packet number Nt and a media packet loss rate Rt of a moving picture experts group transport stream (MPEG-TS) layer, and a lost packet number Nr and a packet loss rate Rr of a real-time transport protocol (RTP) layer respectively; and performing association analysis on the packet loss parameters of the MPEG-TS layer and the RTP layer to judge whether an IPTV service quality problem caused by media stream packet loss is caused by a failure of the video server or the IP network. By the method and the system, the source of the network failure can be effectively determined, and failure detection efficiency can be improved.

The invention discloses a fault detection circuit of a relay and a relay with the same. The fault detection circuit comprises a contact voltage drop detection device and a signal output circuit. The contact voltage drop detection device detects voltage drops of two ends of a contact of the relay. When it is judged that two ends of the contact of the relay are in a fault state, the signal output circuit outputs fault signals to prompt that it is judged that the relay breaks down or fails. The contact voltage drop detection device comprises a comparison circuit and an optical coupler. The optical coupler detects to obtain contact voltage drop signals of two ends of the contact of the relay. When detecting that two ends of the contact of the relay have voltage drops, it shows that the contact of the relay is in a disconnected state. The output end of the optical coupler inputs a contact voltage drop signal to the comparison circuit. After the contact voltage drop detection device acquires the contact voltage drop signal, the contact voltage drop detection device outputs the acquired fault judgment signal through detection to a signal output circuit to judge and prompt that the relay is in a fault or failure state. Thus, the position where the system fault point is located can be quickly judged, the fault detection efficiency is high and fault loss is low.

The invention discloses an intelligent diagnosing method and a system of an electrical device. The method comprises the steps that: when an output signal of the target electrical device is normal, the target electrical device is judged to be with no faults; and when the output signal of the target electrical device is abnormal, electrical device interface end signals connected with the target electrical device are inquired in turn so that whether there is an input signal is judged. When there is the input signal, a fault type of the target electrical device is judged to be misconnection of a signal line; and when there is no input signal, the fault type of the target electrical device is judged to be a connection fault of the signal line.

The invention provides a high-voltage interlocking loop and a high-voltage interlocking loop detector, and relates to the technical field of high-voltage interlocking loop detection. A diagnosis controller is connected with the high-voltage interlocking loop and used for detecting the high-voltage interlocking loop, obtaining voltage information according to a diagnosis signal and an equivalent resistor and diagnosing fault state information according to the voltage information. The high-voltage interlocking loop is characterized in that the input end of one corresponding high-voltage connector is connected with a first low-value resistor and a first high-value resistor, the output end of the corresponding high-voltage connector is connected with a second low-value resistor, one end of a ground resistor is connected with a third low-value resistor and a second high-value resistor, and the other end of the ground resistor is grounded; the ground resistor, the low-value resistors and the high-value resistors are combined into the equivalent resistor through a loop resistor according to the loop connection state, and external connection with a power supply is achieved through the high-voltage connectors. The state of each high-voltage connector and the fault section of the high-voltage interlocking loop can be judged according to different pieces of voltage information, and the fault detection efficiency can be improved.

The invention provides an automatic detection method for a brake shoe borer loss fault of a railway wagon. Firstly, an area classifier, a positioning classifier and a fault judgment classifier are trained firstly; a brake shoe borer image to be tested is segmented through the area classifier, in the areas obtained after segmentation, a multi-level multiple-cascade-connection detection concept is adopted, a brake shoe borer is positioned through the positioning classifier, whether the brake shoe borer is lost or not is judged through the fault judgment classifier, and fully automatic detection on the brake shoe borer loss fault of the railway wagon is realized. By means of the automatic detection method for the brake shoe borer loss fault of the railway wagon, the fault detection rate reaches 99 percent, the detection speed reaches five frames / second, and the actual application requirement is met.

The invention provides an automobile static current detecting device. The device includes a data collecting unit, a display unit, a current detecting clamp and an MCU, wherein a first input terminal of the data collecting unit is connected with a positive electrode wiring terminal of the current detecting clamp; a second input terminal of the data collecting unit is connected with a negative wiring terminal of the current detecting clamp; the output terminal of the data collecting unit is connected with the input terminal of the MCU; the output terminal of the MCU is connected with the input terminal of the display unit; the current detecting clamp is used for detecting static current in a wire harness; the MCU collects static current through the data collecting unit and performs fitting of a current curve of the static current from a collection starting time point to an ending time point; the MCU outputs the current curve and calculates the average discharge current, accumulated discharge capacity and accumulated discharge time. According to the invention, fault detection efficiency of automobile electric parts can be improved and automobile use safety can be improved.

The invention discloses a chemical process failure detection method based on a failure-dependent principal component space. The method comprises the following steps: constructing a principal component space and a residual space by PCA (Principal Component Analysis) according to history data in a normal state; optimizing the principal component space by a GA (Genetic Algorithm) according to history data in a failure state to obtain a failure-dependent principal component; constructing statistics in each failure-dependent principal component sub-space and the residual space; fusing the statistics of each failure-dependent principal component sub-space and the residual space into comprehensive statistics by a Bayes method; and calculating the comprehensive statistics according to online acquired data during online monitoring, and judging a running state. Through adoption of the chemical process failure detection method, a failure detection space is constructed by history normal data, and the failure detection space is optimized by the GA with history failure data, so that redundancy of failure detection is lowered, and the efficiency and accuracy of the failure detection are increased.

The invention discloses an LED display system which comprises a display device and a detection control device; the detection control device comprises a detection module and a control module; the detection module is provided with a detection sub-module and a state return sub-module; the control module is provided with a data encoding sub-module, a data validation error correction sub-module and a control sub-module; the data encoding sub-module receives a video signal to encode data and generate display data; the detection sub-module is used for detecting the display device and generate detection data; the state return sub-module is used for generating state display data and sending the data to an external display terminal; the data validation error correction sub-module is used for correcting the display data according to the detection data, and sending the display data to the control sub-module; and the control sub-module is used for control the display device according to the display data. The LED display system has the advantages of high fault detection efficiency, high detection precision and good detection effect.

The invention discloses a fire-fighting lighting intelligent monitoring system on the basis of the power line communication and an implementing method thereof. The fire-fighting lighting intelligent monitoring system is characterized by comprising a power carrier concentrator on the basis of the power line communication and at least one power carrier acquisition device on the basis of the power line communication, wherein the power carrier concentrator is connected with a control center; the power carrier acquisition device is networked by a power line communication protocol and establishes communication with the power carrier concentrator; and the power carrier acquisition device is connected with fire-fighting lighting equipment. The fire-fighting lighting intelligent monitoring system on the basis of the power line communication and the implementing method thereof have the benefits that the convenience for installing the system is realized by a power line communication mode; cables are prevented from being relaid in a building so as to avoid damage to the existing structure of the building; due to the application of a cooperative working mode of the power carrier concentrator and the power carrier acquisition device, the ease of using the system is promoted; and the fire-fighting lighting intelligent monitoring system has the function of automatically calculating and indicating an escape route, so that the accident response time is shortened.

The invention relates to a method for detecting aircraft cable fault by use of Wigner data distribution matrix. The method comprises the following steps: an incoming reference signal setting step, including a center frequency selection stage, a frequency bandwidth selection stage and a stage for selecting time width of the incoming reference signal according to the selected center frequency and the frequency bandwidth; a signal transmission step, including transmitting the set incoming reference signal to a to-be-tested cable with a receiving interface; a noise reducing step, including receiving a reflection signal of the to-be-tested cable with the receiving interface, and reducing noise of the received reflection signal of the to-be-tested cable by using a wavelet coefficient shrinkage noise reduction method, to reduce the influence of noise signals on the reflection signal; and a fault information processing step, including calculating the correlation between the incoming reference signal and the reflection signal, and calculating local peak time in the correlation function waveform to accurately determine the fault position of the aircraft cable. According to the invention, this kind of fault information is more obvious by using Wigner data distribution matrix, thereby improving fault detection efficiency of aircraft cables.

The invention discloses a wireless communication device testability design method. The method includes performing functional unit division on a wireless communication device, including a voice and panel unit, a processor unit, a baseband signal processing unit, a radio frequency unit, a power amplifier unit, a filter unit and a backboard unit, wherein the voice and panel unit, the baseband signal processing unit, the radio frequency unit, the power amplifier unit and the filter unit are connected with the processor unit through respective control interfaces and data communication interfaces via the backboard unit, and the voice and panel unit provides a device internal unit program upgrade interface and maintenance interface to the outside. Main faults of each unit are automatically diagnosed when the device is powered on, a test command is input through the maintenance interface when a fault occurs, a test signal passes through each unit inside and realizes loopback gradually, and the faults of each unit are diagnosed automatically. The wireless communication device testability design method has the beneficial effects of utilizing hardware resources of the device itself, increasing test software to realize testability design of the device itself, accurately positioning the faults inside the device, and greatly reducing debugging and testing and maintenance guarantee cost of the device.

The invention discloses a fault detection method and system based on wavelet transform and a neural network, and a medium. The method comprises the steps of: acquiring a first vibration signal of a to-be-detected bearing; determining first frequency domain information of the first vibration signal, and selecting a corresponding wavelet basis function according to the first frequency domain information; performing continuous wavelet transform on the first vibration signal according to a wavelet basis function to obtain a first time-frequency diagram; inputting the first time-frequency diagram into a pre-trained fault diagnosis model, and outputting to obtain a fault type identification result, wherein the fault diagnosis model is obtained through convolutional neural network training. According to the fault detection method of the invention, by selecting the appropriate wavelet basis function, weak fault vibration information can be reserved in continuous wavelet transform, interference of noise is avoided, the precision of the time-frequency diagram is improved, and the accuracy degree of bearing fault detection is further improved; and the fault diagnosis model is trained through the convolutional neural network, the bearing fault detection efficiency is improved, and the method can be widely applied to the technical field of equipment bearing fault detection.

The invention provides an intelligent device fault detection method, device and system. The method includes the following steps that: a serial number is preset for each device, obtained state information of each device contains device information; the actual use state data of each device are obtained according to the state information of each device; the actual use state data of each device are compared with the standard use state data of each device; and once the difference value of the actual use state data of a certain device and the standard use state data of the device exceeds a set threshold value, it is judged that a fault occurs on the device. Each intelligent device is provided with a controller for controlling the operation of the device, and the controller itself can obtain the state information of the device in real time, namely, the controller of the device can be adopted to realize fault detection for the device, and extra sensors are not required to be adopted, and therefore, costs can be decreased, consumption such as additional data processing and processing time can be avoided, and the efficiency of device fault detection can be improved.

The invention discloses an LED special-shaped display system which comprises a display device and a detection control device. The detection control device comprises a data distribution module, a detection module and a control module, wherein the detection module is provided with a detection submodule, a storage submodule and a state feedback submodule, and the control module is provided with a data coding submodule, a data check and error correction submodule and a control submodule; and video signal data are grouped by the data distribution module, the fault of the display device is detected by the detection module, the display device feeds back the state, and then the display of the display device is controlled by the control module. The invention has high fault detection efficiency, high detection accuracy and good detection effect.

The invention discloses a pipeline detection robot. The pipeline detection robot comprises a robot head, a robot middle portion connected with the robot head through a first elastic connecting body and a robot tail connected with the robot middle portion through a second elastic connecting body. A bionic leg for traveling is arranged on each of the left sides and the right sides of the robot head, the robot middle portion and the robot tail. A camera for camera-shooting and multiple ultrasonic sensors for detecting obstacles are arranged on the robot head. A circuit control board for controlling the traveling gait of the robot and receiving detection signals is arranged on the robot middle portion. A winder for take-up and pay-off of cables is arranged at the robot tail. According to the pipeline detection robot, a body of the pipeline detection robot has certain scalability and flexibility, meanwhile has flexible gait planning capability and can adapt to the application needs of cornering, crawling, obstacle avoidance and detection in different pipeline environments; and due to the fact that detection signal transmission is stable and reliable, the pipeline failure detection efficiency of the robot is higher.