526results about How to "Avoid major accidents" patented technology

The invention discloses an aero-engine intershaft bearing early weak fault diagnosis method, which belongs to the technical field of aero-engine fault detection. The method includes the following steps: the fault signal of the intershaft bearing is collected; an AR model is used to remove a deterministic signal generated by periodic rotation of the engine rotor; the processed fault signal is subjected to inverse MED filtering to enhance the shock component of the fault signal; a CEEMD method is used to decompose the processed fault signal, an effective modal component is screened according toa kurtosis value index and an autocorrelation function, and the intershaft bearing fault signal is subjected to noise reduction and reconstruction; and through a Teager energy operator, the output energy of the noise reduction signal is obtained, the envelope spectrum is calculated, and through analyzing the frequency component with a frequency component in the envelope spectrum, engine intershaftbearing early weak fault diagnosis is realized. The fault signal can be subjected to preprocessing, screening, reconstruction and demodulation, a fault characteristic signal reflecting the bearing fault is acquired, and the early weak fault of the intershaft bearing can be accurately diagnosed.

The invention discloses a tower crane video monitoring system with automatic tracking and zooming functions, and the invention also discloses a tower crane video monitoring method with automatic tracking and zooming functions. The method comprises the following implementing steps of taking a marker on a crane hook as a tracking target image, and detecting the area and the center of mass of an object at real time by the image processing technology to realize the automatic zooming and tracking, image sequence acquisition, target characteristic extraction, target characteristic match and target search location; and aiming at swaying in the running process of the tower crane, combining a color histogram with form features, and then improving the present mean shift tracking algorithm which is based on the distribution of a target color histogram according to the real operating condition of the tower crane, thereby realizing the target tracking under the environment of the tower crane. The invention has automatic camera zooming and tracking functions so that a tower crane operator can watch the lifted objects and the circumferential situation thereof clearly in a control room at real time .

The invention discloses a continuous rigid frame bridge prestress damage identification method based on deflection monitoring. The continuous rigid frame bridge prestress damage identification method comprises the following steps: I, establishing a bridge deflection monitoring system, that is, the bridge deflection monitoring system comprises n deflection monitoring devices and one data acquisition device, and the n deflection monitoring devices are respectively arranged on n deflection monitoring points; II, monitoring deflection of a bridge, namely, respectively monitoring deflection data of n deflection monitoring points on a main beam by using the bridge deflection monitoring system in real time, and synchronously transmitting the monitored deflection monitoring data to data processing equipment; III, identifying prestress damage, namely, establishing a finite element model of the bridge, processing the bridge deflection monitoring data, acquiring deflection data caused by prestress damage, establishing a damage identification rigidity matrix and identifying prestress damage. The continuous rigid frame bridge prestress damage identification method is simple in step, reasonable in design, convenient to realize, good in use effect, capable of easily and conveniently completing the prestress damage identification process of a continuous rigid frame bridge, and relatively high in identification result reliability.

The invention discloses power transformer fault intelligent diagnosis technology, method and device, and relates to power transformer fault intelligent diagnosis technology and method and the intelligent diagnosis device based on the technology and the method. The intelligent diagnosis device comprises a data acquisition and transmission part and a management and display part. The intelligent diagnosis device is characterized in that power transformer fault intelligent diagnosis technology and method comprise a dissolved gas in oil analysis and diagnosis technology, a partial discharge online monitoring and diagnosis technology, an infrared temperature measurement diagnosis technology, a vibration analysis and diagnosis method, a frequency response analysis and diagnosis method, a winding temperature indication diagnosis method and a low voltage impulse response test diagnosis method, and fault intelligent diagnosis is carried out. According to the invention, a multi-parameter state monitoring method is used, and multiple fault intelligent diagnosis technologies and methods are integrated; valuable data which can be used to diagnose a fault and find out the position are given; the cause of the defect is eliminated; the shutdown time and the cost are reduced; and the purposes of power transformer intelligent monitoring and intelligent diagnosis are realized.

The invention aims to provide a mining safety helmet with functions of perceiving vital signs and dangerous environment of miners and early warning. The mining safety helmet is formed by a safety helmet shell, a safety helmet liner, a loudspeaker, a human body temperature sensor, a pressure sensor, a methane detection sensor, a carbon oxide detection sensor, an external temperature sensor, an air ventilating opening, a microprocessor, a wireless transmission module, a rechargeable battery, a horizontal speed detection sensor, a vertical speed detection sensor, a gravity induction sensor, a loudspeaker acoustic transmission opening, a power supply switch, a charging interface and a system updating interface. Temperatures, moving speeds, body gestures, head pressure information and underground environment monitoring data of underground personnel can be collected in real time and uploaded. When an accident happens, services are provided for formulating a rescuing scheme according to the collected vital signs and movement state information of the miners; and before the accident happens, early warning can be carried out according to environment monitoring information; and a working condition of the underground personnel can be evaluated according to the personnel movement and the body gesture information under the normal condition.

The invention discloses a second generation small-wave support vector machine assessment method for damage and remaining life of a metal structure. According to the method, an intrinsic mode function is obtained through decomposition of an experience mode, a time-frequency domain statistic characteristic of the intrinsic mode function is extracted, a most sensitive characteristic is chosen according to a distance accessment principle to construct a best characteristic set, a minimum quantization error indicator which has an obvious performance degradation trend along with time changes is constructed by means of self-organization neural network characteristic fusion techniques, a biorthogonal small-wave support vector machine kernel function of second generation small-wave transform is provided, a service life prediction model of the second generation small-wave support vector machine is constructed, the minimum quantization error indicator serves as a prediction characteristic, and quantitative assessment for the damage and the remainig service life of a metal structural component of mechanical equipment under a small subsample is achieved.

The invention discloses a method for recognizing lithological characters while drilling, which mainly solves the problems of unclear horizontal boundary and serious rock debris collection time delay of the conventional cutting logging method. The method is characterized in that: actually drilling different rock samples on the ground, recording vibration signal generated under a condition of the combination of a plurality of groups of typical drilling parameters, acquiring different drilling parameters and a standard frequency spectrum under the condition of the combination of lithological characters by using quick Fourier transform, and storing the different drilling parameters and the standard frequency spectrum in a database; setting an orthogonal three-axis acceleration sensor, a two-axis strain transducer and a gyroscope in the drill collar of a near drill bit; and string the data collected by the three-axis acceleration sensor, the two-axis strain transducer and the gyroscope during the drilling of the drill bit, comparing the spectrum of data with the standard frequency spectrum for analysis, extracting data on vibration type, main frequency, frequency doubling and the like to form lithological feature codes, vibration characteristic codes and drill bit health code, and determining the lithological characters. The method can realize while-drilling recognition and has high recognition effect.

The invention discloses a defect identification method of partial discharge signal, which comprises the following steps: (1) acquiring training samples of partial discharge signals representing several partial discharge insulation defect types, extracting phase-resolved pulse sequence data based on the training samples, and normalizing the phase-resolved pulse sequence data; (2) the sparse self-encoder model being trained by the normalized phase-resolved pulse sequence data, and the dimension-reduced training eigenvectors being obtained based on the trained sparse self-encoder model; 3) training the extreme learning machine model by using the training eigenvector; (4) the PD signal to be identified being input into the trained sparse self-encoder model to extract the test feature vector, and the test feature vector being input into the trained limit learning machine model to obtain the defect types represented by the PD signal to be identified. The invention also discloses a defect identification system of a partial discharge signal.

The invention provides a WAMS (wide area measurement system) and SCADA (supervisory control and data acquisition) integrated data based grid forced oscillation source positioning method. Oscillation sources are positioned rapidly and accurately by comprehensive utilization of data of the WAMS and SCADA. According to a main principle, the method includes: firstly, positioning general directions of the oscillation sources by adopting an energy flow function method based on 500kV grid WAMS data, then adopting different accurate oscillation source positioning methods according to properties of three common oscillation sources, computing tie lines of a local weak tie network by adopting an SCADA data based oscillation extreme point judgment method, and judging whether oscillation exists in the weak tie network or not; adopting WAMS data of generator excitation voltage phase to judge whether oscillation is caused by a generator excited system or not; adopting an extreme point computation method of SCADA data of valve or guide vane opening of a generator set to judge whether grid oscillation is caused by a unit prime mover or not.

The invention relates to the field of electric propulsion systems and simulation evaluation, in particular to a method of comprehensive evaluation for simulation credibility of an electric propulsion system. The method includes: disintegrating the electric propulsion system into subsystems; disintegrating the subsystems of the simulation system under various rules until minimum units are obtained; acquiring indexes and weights of the subsystems relative to upper level of nodes; acquiring credibility of the indexes of the subsystems to obtain the credibility of the subsystems; and acquiring results of comprehensive credibility evaluation for the whole electric propulsion system. The method has the advantages that correctness in output results of the established evaluation system can be enhanced and risks in development and application of the simulation system are lowered; developers are effectively aided in finding defects of design process of the simulation system and correcting the defects timely; development cycle of the simulation system can be shortened effectively, development cost of the simulation system can be lowered effectively, and important accidents in practical application of the simulation system can be prevented effectively.

The invention relates to super-thick EH36 steel for an offshore wind power pipe pile. The super-thick EH36 steel for the offshore wind power pipe pile comprises the following chemical components in percentage by mass: .015 to 0.18 percent of C, 0.15 to 0.30 percent of Si, 1.40 to 1.60 percent of Mn, less than or equal to 0.0070 percent of P, less than or equal to 0.0030 percent of S, 0.050 to 0.070 percent of Nb, 0.015 to 0.030 percent of V, 0.08 to 0.020 percent of Ti, 0.030 to 0.050 percent of Al, 0.15 to 0.40 percent of Ni, 0.10 to 0.20 percent of Cr, and the balance of Fe. A production process flow comprises the following steps: performing converter operation, performing LF refining, performing vacuum degasifying, performing Ca treatment, performing continuous casting, dehydrogenizing, rolling, performing air cooling, performing high-temperature hot straightening, and normalizing. According to the production process flow, the super-thick EH36 steel of 90 to 120 mm for the offshore wind power pipe pile, which is high in unit weight, high in strength, high in impact toughness, small in thickness tolerance and high in straightness and does not have a surface defect is obtained.

The invention discloses an auxiliary cargo boom for a crane. The crane comprises a lower vehicle part, an upper vehicle part which is positioned on the upper part of the lower vehicle part and is connected with the lower vehicle part, a main cargo boom connected with the upper vehicle part and the auxiliary cargo boom connected with the main cargo boom through a connector, as well as a front luffing bracket and a rear luffing bracket, wherein fixed ends of the front and rear luffing brackets are pivoted with the connector; a front pulling plate assembly is connected between the movable end of the front luffing bracket and the top of the auxiliary cargo boom, and the movable end of the front luffing bracket is connected with the rear luffing bracket through a luffing pulling plate; the lower vehicle part is provided with a luffing winch assembly; and a luffing pulley block is connected between the movable end of the luffing bracket and the luffing winch assembly through a stay cord. The luffing winch assembly tightens or releases the stay cord, force generated by winching acts on the rear luffing bracket through the stay cord, and acts on the auxiliary cargo boom through the luffing pulling plate, the front luffing bracket and the front luffing pulling plate in turn so as to realize continuous change of the included angle between the main cargo boom and the auxiliary cargo boom.

The invention discloses a high-pressure controllable slide-valve type mechanical combined sealing system. The system comprises a controllable slide valve stationary seal assembly and a rotating mechanical seal assembly; the controllable slide valve stationary seal assemble comprises a slide valve gland (13), a slide valve (11) and a tapered shaft sleeve (12) sheathed on a shaft shoulder, the tapered shaft sleeve (12) is positioned inside the slide valve gland (13), the slide valve (11) which is partially positioned in a flange (16) is hermetically connected with the tapered shaft sleeve (12) in a sliding way, and the flange (16) is provided with a pressure source channel I (161) and a pressure source channel II (162) which are respectively used for controlling the slide valve (11) to slide leftwards or slide rightwards; the rotating mechanical seal assembly comprises a rotating seat (9) which is fixedly connected with a shaft sleeve (10), a rotating ring (17) and a stationary ring (7) which are closely jointed on a seal face and the like. The sealing system can help greatly reduce and avoid leakage of dangerous fluid and serious accidents.

The invention relates to a photoelectric rockfall, landslide and collapse monitoring method in which a photoelectric switch or a laser device is used as a monitoring sensor, and a monitoring and alarming device which is capable of monitoring geological disasters, such as rockfall, landslide, collapse and the like, on both sides of a railway or a road at any time anywhere and automatically alarming a disaster and a rock invasion accident immediately. The monitoring device consists of a plurality of monitoring links and a monitoring alarm device; each of the monitoring links consists of an emitting column, a receiving column and an adjusting column arranged between the emitting column and the receiving column; the emitting column consists of a vertical rod 2 fixed on a base 1 and a photoelectric emitter 3 arranged on the vertical rod 2; the adjusting column consists of a vertical rod 6 fixed on a base 7, a penetrating board 5 fixed on the vertical rod 6 and an adjusting board 4 capable of moving, an adjusting board 8 and a fastening bolt 13; the receiving column consists of a vertical rod 10 fixed on a base 11 and a photoelectric receiver 9 arranged on the vertical rod 10; and the monitoring alarm device 12 is connected with the photoelectric receivers through cables.

The invention discloses a railway work protection system and method based on an intelligent bracelet. The system comprises the intelligent bracelet worn by a constructor, a handheld terminal worn by a construction responsible person, a 3G transmission network, Internet and a background server, wherein the intelligent bracelet and the handheld terminal are in communication connection with the background server by the 3G transmission network and Internet in sequence. The constructor sends a serial number to the background server by the intelligent bracelet; the background server is used for searching the information of the constructor according to the serial number and sending the information to the handheld terminal of the construction responsible person; the background server is used for transmitting early warning information to the handheld terminal and the intelligent bracelet of the construction responsible person and the constructor in sequence through Internet and the 3G transmission network; the constructor is reminded of evacuating from dangerous construction road sections through sound signals, vibration signals and electrical stimulation signals. By the aid of the railway work protection system and method, the reliability and safety of the railway work protection system can be effectively improved.

The invention relates to buildings, and particularly belongs to technical application of magnetic suspension in the filed of vibration prevention of an engineering structure. The invention adopts the technical proposal that: a plurality of substructures are arranged in the engineering structure, the bottom layers of the substructure are provided with an electromagnet, the lower part of the electromagnet is provided with a corresponding structural electromagnet, the electromagnet and the structural electromagnet after being powered have the same electromagnetic polarity, and the electromagnet and the structural electromagnet are connected with an electromagnetic control device with an earthquake signal receiving device. The technical application has the advantages that: because the engineering structure applied with the magnetic suspension technology fully isolates the earthquake influence, the problems of various assumptions calculated by earthquake action, mutual influence of the earthquake and the structure, and the like disappear; and the structure is not influenced by the strength, properties and the like of the earthquake.

The invention relates to a portable switchgear partial discharge patrol detection system, which comprises a signal acquisition unit and a data processing unit. The signal acquisition unit comprises a plurality of partial discharge state signal acquisition instruments, and has the capability of signal acquisition, single-machine patrol detection and providing a simple on-site decision basis. The data processing unit comprises function modules of data extraction, data analysis and classification and separation and the like according to fault types. The portable switchgear partial discharge patrol detection system is characterized in that, through internet-of-thing technology, embedded technology and data mining technology, the system provides an overall plan for equipment state detection for operation and maintenance staffs; through bluetooth technology, signal acquisition units based on different partial discharge detection technologies and the data processing unit are networked for data transmission; and the data processing unit collects data of each acquisition unit and transmits the data to a regional server through WIFI. The system provides a more macroscopic and comprehensive decision basis, helps operation personnel to find equipment in an abnormal operating condition in time and prevents occurrence of major accidents.

The invention discloses an oil pollution monitoring and cleaning and filtering device of an embedded hydraulic power system, which comprises a main oil way A of the hydraulic system, a second electronic-magnetic or electronic-liquid steering valve which is arranged between the inlet and the outlet of the main oil way A of the hydraulic system. The device is characterized in that a branch oil way B is parallelly arranged on the inlet and the outlet of main oil way A of the hydraulic system, a branch oil way B is provided with a first electronic-magnetic or electric-liquid steering valve, a filter or a one-way valve and the filter is parallelly connected with a pressure gradient oil pollution monitoring and display device. The filtering device aims at not influencing the normal operation of the system when the attachment as the hydraulic equipment is embedded into the design of the hydraulic power system, monitoring results can better show the practical operation of oil.

The invention discloses an intelligent power plant electrical equipment fault diagnosis method based on width learning and temporal and spatial characteristics of infrared images. The method is characterized by analyzing temporal and spatial characteristics of the infrared images, combining image texture information and temperature temporal variation information, and completing electrical equipment fault diagnosis by using width learning. The method is capable of extracting target power equipment needed to be analyzed in each infrared image in extremely short time and giving corresponding temperature information, solving the defect that the infrared images can only be analyzed by using specially-equipped random software, deeply exploring temporal and spatial attributes of the infrared images, analyzing the infrared images at multiple dimensions and improving effectiveness and accuracy of the infrared diagnosis technique.

The invention relates to a power station boiler diagnosis expert system and a fault diagnosis method thereof and aims to solve the problems that currently the operation fault causes of a thermal powerplant are not visual, the number of the parameters and state variables monitored by the system of the thermal power plant can reach hundreds and thousands, and fault position finding from the thousands of measuring parameters, state variables and alarm information is quite difficult. The power station boiler diagnosis expert system comprises a DCS data collecting system module which is mounted ona boiler unit and used for collecting boiler parameters and is characterized in that the DCS data collecting system module is connected with a real-time database system module, the real-time databasesystem module is connected with an overlimit alarm module, the overlimit alarm module is connected with a fault diagnosis module, and the fault diagnosis module is connected with a diagnosis knowledge database module, a fault symptom database module, a knowledge database updating module, a fault predicting diagnosis module and a user interface module. The power station boiler diagnosis expert system is applicable to power station boiler diagnosis.

The invention relates to a subway power supply system dynamic risk analysis and evaluation method based on fuzzy reasoning, and the method at least comprises the steps: S1, determining a DC feed-out cable and a return cable of a target DC substation according to a power supply section of a track position where a target train is located; S2, establishing a risk transmission chain of direct-currentcable breakdown of the subway power supply system, and determining the key characteristic quantity of a direct-current feed-out cable in the risk transmission chain; S3, taking the obtained key characteristic quantity value of the direct current feed-out cable as a value vector, and carrying out fuzzy set calculation through a fuzzy reasoning method to obtain a membership function diagram corresponding to the value vector; and S4, reasoning according to the membership function diagram of each numerical vector to obtain a possibility observation diagram of direct-current cable breakdown. The method can reasonably evaluate the risk level of the system and block the propagation evolution of a risk propagation chain, thereby avoiding major accidents as much as possible.

The invention discloses a measuring method and device for a buried oil-gas pipeline and a cathodic protection device. The GIC measuring method comprises the following steps: a current sensor is additionally mounted in an insulated-flange hook-line cable of the buried oil-gas pipeline so as to measure electric currents in the buried oil-gas pipeline; a current and voltage sensor is mounted in the cathodic protection device so as to measure electric currents and voltages in the cathodic protection device; a parameter identification method for on-line study is used to update the soil resistance parameters of the buried oil-gas pipeline, and calculate the GIC dynamic current of the buried oil-gas pipeline and the GIC dynamic current of the cathodic protection device in real time. Through the adoption of the measuring method disclosed by the invention, the problems in the indirect measurement of GIC and the dynamic current of the cathodic protection device are effectively solved; the GIC of the buried oil-gas pipeline at a cathodic protection station, and the GIC of the cathodic protection device at the cathodic protection station can be accurately monitored; the influence of a geomagnetic storm on the buried oil-gas pipeline can be correctly evaluated, and defensive measures can be taken in time to avoid major accidents.

The invention relates to a video-sensing patrol alarm device and patrol alarm method for a fire-fighting robot. With the method and apparatus, defects in the prior art can be overcome. According to the technical scheme, a positioning tag sensing receiver is electrically connected with a robot control center; a video acquisition positioning component and a sensing information acquisition module are in communication connection with a remote control server side; the remote control server side is in communication connection with the robot control center by a signal instruction receiving module; and the robot control center is electrically connected with an execution mechanism by a drive control center module. A motion positioning feedback module is arranged on the execution mechanism and is in communication connection with the remote control server side. Besides, a device mounting part is fixed at an upper surface of a front side of a vehicle body; and the sensing information acquisition module is fixed inside the device mounting part. The video acquisition positioning component includes an infrared thermal imaging system fixed at the upper surface of the device mounting part and a video probe fixed on a mechanical arm.

The invention provides a locomotive vehicle running gear bearing holder fault pre-alarm method.According to the method, a composite sensor and a detection instrument are installed on a locomotive vehicle running gear bearing seat for online data acquisition and preprocessing, time domain impact SVi data, time domain vibration Vi data and temperature data Ti are generated, the time domain impact characteristic value SVmax and the time domain vibration characteristic value VRMS are calculated, fast Fourier transform is conducted, a corresponding shock frequency spectrum and a vibration frequency spectrum are obtained, an impact fault characteristic mark Ib and a vibration fault characteristic mark Vb are obtained through processing, a temperature pre-alarm mark Tb is obtained through calculation with temperature data, trend analysis is conducted on the Ib, the Vb and the Tb sequence data, and an alarm or pre-alarm is given according to the trend analysis result.The locomotive vehicle running gear bearing holder fault pre-alarm method is high in diagnosis accuracy, easy to master, high in operability and wide in application range; scientific operation or maintenance guidance opinion is provided, planned maintenance is converted to state maintenance, safety of the locomotive vehicle is greatly improved, maintenance cost is saved, and operation economic benefits are raised.