1459 results about "Operational reliability" patented technology

The invention discloses a servo motor dynamic overload detection and protection method based on a heat accumulation model, which relates to the technical field of servo system fault protection application, and comprises the steps of constructing a heat accumulation equivalent model, dynamically detecting an overload state, executing a heat dissipation recovery strategy, implementing a multi-stage protection mechanism, self-adaptive environment compensation and a historical data learning function. Through discretization processing of overload curve data and a nonlinear acceleration calculation strategy, the problems of protection lag and false triggering caused by traditional single-parameter detection are avoided, it is ensured that the motor can respond in time in light load, heavy load and load fluctuation scenes, the burn-out risk of the motor is reduced, and through integration of an environment temperature sensor and a heat dissipation condition evaluation unit, the reliability of the motor is improved. The heat accumulation coefficient and the heat dissipation attenuation parameter are dynamically adjusted, the problem of model deviation caused by environment interference is solved, when heat dissipation deterioration and temperature feedback abnormity are detected, the heat dissipation recovery period is automatically prolonged, calculation logic is corrected, and the continuous operation reliability of the system is improved.

The invention discloses a cold plate-immersion liquid cooling cooperative heat dissipation method based on steam zone coupling modeling, and relates to the technical field of cooperative heat dissipation. Comprising the following steps of S1, collecting collaborative heat dissipation monitoring data of each key position in real time, and performing data preprocessing; s2, the comprehensive risk of the steam area is judged, and a risk cooling adjustment instruction is issued according to the comprehensive risk judgment result; s3, receiving a risk cooling adjustment instruction, carrying out collaborative heat dissipation, evaluating the collaborative heat dissipation capability, adjusting the rotating speed of a circulating pump and the opening degree of a valve, and requesting condensation backflow adjustment; s4, judging the adjusting quantity of condensation reflux, executing reflux adjustment and performing safety monitoring; and S5, continuously monitoring the data of each link, and carrying out anomaly detection on the state of each link to realize anomaly regulation and control. The problems that in an existing single-phase cold plate or two-phase immersion liquid cooling mode, steam accumulation is prone to occurring in a high-heat-flow scene, so that the pressure intensity is increased, the boiling point is increased, and the heat exchange efficiency is reduced, and then the operation reliability of equipment is affected are solved.

The invention relates to an unmanned aerial vehicle self-adaptive wind-resistant flight control method and system based on multi-mode environment perception. The method comprises the steps that a miniature wind speed and direction sensor array obtains real-time wind speed and wind direction information of the surrounding environment of an unmanned aerial vehicle; the inertial measurement unit obtains real-time attitude angle, angular velocity and acceleration information of the unmanned aerial vehicle; the visual flow sensor obtains real-time image data of the surrounding environment of the unmanned aerial vehicle; the data fusion and wind field estimation module receives multi-source data collected by the miniature wind speed and direction sensor array, the inertial measurement unit and the visual flow sensor, carries out fusion processing on the multi-source data based on an extended Kalman filtering algorithm, and predicts to obtain predicted wind field information in a future short time window; the flight control core module adopts an adaptive sliding mode control algorithm to calculate a compensation control quantity for counteracting wind disturbance, and performs real-time control on the unmanned aerial vehicle based on the compensation control quantity; and the wind resistance and the operation reliability of the unmanned aerial vehicle in a complex dynamic environment are improved.

The invention relates to a power distribution network abnormal state intelligent identification method based on unmanned aerial vehicle routing inspection, and the method comprises the following steps: S1, obtaining power distribution network routing inspection related data, including asset main data, historical operation and maintenance data and environment constraints; s2, constructing the digital twinning of the power distribution network based on the power distribution network inspection related data, and obtaining the mapping from the equipment ID to the spatial pose and parameters; s3, generating a risk heat map based on historical defects and environmental risk scoring; s4, constructing an equipment-geography-working condition knowledge graph, and generating inspection targets and priorities according to line sections in combination with mapping from equipment IDs to spatial poses and parameters and a risk heat map to obtain a task package; and S5, performing multi-target route inspection according to the task package, the risk heat map and the mapping from the equipment ID to the spatial pose and the parameter, and intelligently identifying the abnormal state of the power distribution network. The operation reliability of the power distribution network is effectively improved, and the power supply quality is improved.

The invention relates to a membrane stack (9) for an air humidifier (1) of a fuel cell for humidifying a dry supply air stream (2) of the fuel cell by means of a moist exhaust air stream (3) of the fuel cell, - wherein the membrane stack (9) is configured in a cuboid shape, has a stacking direction (S) and four stacking sides (10) perpendicular to the stacking direction (S), - wherein the membrane stack (9) has a vertical direction (Z) parallel to the stacking direction (S), a longitudinal direction (X) perpendicular to the vertical direction (Z) and a transverse direction (Y) perpendicular to the vertical direction (Z) and perpendicular to the longitudinal direction (X), - wherein the four stack sides (10) form an air supply inlet (ZE) and an air supply outlet (ZA) facing away from each other in the longitudinal direction (X), and an exhaust air inlet (AE) and an exhaust air outlet (AA) facing away from each other in the transverse direction (Y), - wherein the membrane stack (9) comprises several membranes (11) which are permeable to moisture and impermeable to air and which follow one another in the stacking direction (S) such that the membranes (11) within the membrane stack (9) each separate a supply air path (ZP) connecting the supply air inlet (ZE) to the supply air outlet (ZA) from an exhaust air path (AP) connecting the exhaust air inlet (AE) to the exhaust air outlet (AA). Improved functional reliability can be achieved by having the membrane stack (9) have several spacers (12) which are arranged in the stacking direction (S) between two immediately successive membranes (11) in one of the exhaust air paths (AP).

The invention discloses a power distribution network topology optimization method and system, and relates to the technical field of power distribution network topology optimization, and the system comprises a dynamic health degree obtaining module, an operation risk cost module, a topology optimization module and a maintenance scheme generation module. The dynamic health degree index and the operation risk cost of the key electrical equipment are incorporated into the topological optimization objective function, and the weight is dynamically adjusted according to the health state of the equipment, so that the problem that in the prior art, the actual health state of the equipment is ignored, so that the degradation of the equipment is possibly accelerated by the optimization scheme is effectively solved; therefore, the real-time health condition evaluation information of the key equipment can be effectively integrated, the short-term operation economic index and the long-term operation reliability of the equipment are dynamically balanced in the optimization process, the unexpected fault risk of the equipment is reduced, and the overall reliability and safety of operation of the power distribution network are improved.

The invention discloses a dynamic closed-loop management method for bridge-shaped contact performance, and relates to the technical field of power system protection. The method comprises the following steps: S1, a dynamic sensing process: acquiring multi-source dynamic parameters of a bridge-shaped contact in a non-intrusive mode; s2, a quantitative evaluation process: fusing the multi-source dynamic parameters and the static parameters, and calculating a health index or a health level of the contact through a preset model; s3, adaptively optimizing the process, dynamically adjusting the closing energy or protection parameters of the circuit breaker according to the health state, and compensating the performance change of the contact; and S4, a predictive maintenance process: performing trend extrapolation based on the historical data of the health index, predicting the residual life and generating a maintenance suggestion. The processes are sequentially connected and cyclically iterated to form dynamic closed-loop management, so that the problems of one-sided parameter sensing, inaccurate evaluation, fixed parameters and maintenance lag in the prior art are solved, the operation reliability of the bridge-shaped contact is improved, the service life of equipment is prolonged, and the operation and maintenance cost is reduced.

The invention discloses a hydraulic engineering motor set fault early warning system, and relates to the technical field of hydraulic engineering equipment monitoring, and the hydraulic engineering motor set fault early warning system comprises the following steps: S1, collecting and integrating mechanical state data, including vibration, temperature and oil pollution monitoring; s2, electrical parameter monitoring and complementary analysis are carried out, and mechanical data are associated to identify faults such as short circuit; s3, hydraulic monitoring and cooperative early warning are carried out, pressure flow abnormity is detected, and mechanical and electrical data are linked; s4, multi-source data fusion and fault classification are carried out, and dynamic weight distribution is carried out to improve the diagnosis accuracy; s5, dynamic threshold optimization and cloud decision making are carried out, and the threshold is adjusted according to working conditions to reduce the false alarm rate; s6, closed-loop maintenance and intelligent pushing are carried out, faults are positioned, maintenance suggestions are pushed, and closed-loop verification is carried out; the method has the beneficial effects that accurate fault classification, cross-dimension collaborative early warning and closed-loop maintenance decision making are realized, and the operation reliability and the maintenance efficiency of the unit are remarkably improved.

The invention discloses an unattended intelligent control method and system for a heat exchange station, and relates to the technical field of heat energy automatic control, and the method comprises the steps: collecting multi-source environment parameter data, constructing an environment parameter sequence set, constructing a heat load prediction model, and outputting a predicted heat load value through extracting a change relation between local temperature trend characteristics and a time sequence. Carrying out residual comparison on an actual thermal load value and the predicted thermal load value, constructing a residual fluctuation measurement sequence, carrying out multi-dimensional state judgment in combination with a preset threshold range, outputting an operation state identifier, carrying out linkage adjustment on a water pump frequency parameter and a water mixing valve opening parameter, calling an optimization control strategy set, and carrying out optimization control on the water pump frequency parameter and the water mixing valve opening parameter. And generating an updated water pump adjusting instruction and an updated valve adjusting instruction. The operation reliability and the energy utilization efficiency of the heat exchange station are improved, unattended intelligent control is achieved, and the technical problems that in a traditional control method, prediction precision is low, abnormal recognition is not accurate, and control parameter coordination is poor are solved.

The invention discloses a scraper conveyor middle trough production line operation state monitoring method based on digital twinning, and belongs to the technical field of industrial intelligent manufacturing. The method comprises the following steps: constructing digital twin bodies in one-to-one correspondence with physical production line elements; establishing a real-time data driving channel between the digital twin and the physical elements; based on the channel, driving the digital twin to synchronously map the real-time operation parameters, and generating a virtual operation state of the production line; based on the virtual operation state, performing time sequence deduction on the processing flow in the digital twin according to the processing technology logic and the equipment performance parameters to obtain a production line pre-estimation state of a future time point; and comparing the parameters in the pre-estimated state with a preset threshold range to generate prediction information. According to the invention, real-time data driving and bidirectional interaction of the physical production line and the virtual model are realized, the problems of data isolation and feedback lag of a traditional monitoring mode are overcome, the prediction capability is provided, and the operation reliability and intelligent management of the production line are effectively improved.

The invention provides an inclined variable-angle aircraft interstage separation ground test device. The inclined variable-angle aircraft interstage separation ground test device comprises an aircraft separation device, an angle adjusting device, a temperature control and acquisition device, a vibration control and impact acquisition device, an ignition control device and a device base. The angle adjusting device comprises a device side plate, an arc groove, an angle ruler, a separation mechanism mounting plate, a supporting hinge, a supporting rod, an adjusting sliding rail, an adjusting base, a locking device, a device base gradienter, a rotating bearing and an auxiliary fixing block. The temperature control device comprises a quartz lamp array heating cage, an outer wall temperature control thermocouple and an inner wall temperature acquisition thermocouple, and can simulate a pneumatic heating environment at a separation moment, so that the thermal deformation matching capability of the separation mechanism in a high-temperature environment and the operation reliability of the separation mechanism are obtained. The vibration control and impact acquisition device is composed of a vibration table, a vibration control sensor and an impact sensor.

The invention discloses an equipment health state monitoring method and system based on the Internet of Things. According to the method, data in a multi-source sensor is obtained and preprocessed, a real-time operation data set of equipment is obtained, and a health quantification deviation value and a health state trend are determined through the real-time operation data set. And when the health state is abnormal, recording a starting point coordinate of an abnormal event, marking an abnormal event triggering timestamp, and analyzing the dependency relationship between the equipment by utilizing graph network modeling. Furthermore, the potential risk probability is analyzed through the long-short-term memory network, real-time monitoring, fault propagation prediction and risk assessment of the equipment health state are achieved, and the operation reliability and the maintenance efficiency of the industrial equipment are improved.

The invention relates to the technical field of data analysis and control, in particular to a hydraulic climbing frame safety control method based on digital monitoring, which comprises the following steps: acquiring monitoring data in real time through a sensor group arranged on a hydraulic climbing frame, preprocessing and analog-to-digital conversion are carried out on the monitoring data, then the data are formed and sent to a remote monitoring center through a wireless transmission technology, and the preprocessed monitoring data are input into a pre-stored structure safety evaluation model and a hydraulic system performance evaluation model so as to be analyzed in real time; analyzing the hydraulic climbing frame, judging a safety characterization state of the hydraulic climbing frame according to an analysis result, determining a safety risk type based on an abnormal state of the hydraulic climbing frame, sending early warning information through a user interaction platform when a risk is judged to exist, and executing a corresponding safety control instruction; automatic real-time monitoring, intelligent early warning and active control of the safety state of the hydraulic climbing frame are achieved, and construction safety and operation reliability are remarkably improved.

The invention relates to the technical field of artificial intelligence and equipment control, and discloses an AI-driven commercial refrigerator dynamic energy-saving and load prediction system, which comprises the following steps: circularly multiplexing the working and shutdown of a compressor into an active detection process for the thermodynamic state of a refrigerator, and calculating the temperature of the refrigerator according to the temperature time sequence data generated in the process; according to the method, multi-scale dynamic characteristics capable of representing the total heat load and the heat exchange efficiency at the same time are extracted, a machine learning model is input for working condition classification, and then self-adaptive adjustment of a control strategy is achieved. The insight from the passive response to the single temperature to the core hidden variable of the dynamic thermal load is realized, so that the control system can identify the real working condition and make the optimal energy-saving decision, and the energy efficiency and the operation reliability of the equipment in the complex dynamic environment are improved.

The invention relates to the technical field of transformer coil detection, and discloses a detection device for a transformer coil, which comprises a base frame, the driving mechanism is installed on the base frame and used for providing linear motion in the X direction, the Y direction and the Z direction; according to the scheme, by means of the detection mode that spiral scanning motion is combined with self-adaptive contact and laser ranging, the fatal defects that manual detection is low in efficiency, high in subjectivity and prone to making mistakes and missing detection are overcome, complete three-dimensional shape data of the surface of the coil can be rapidly and accurately obtained, and the detection accuracy is improved. According to the method, local fine defects which are difficult to discover manually can be detected, the reliability and the consistency of detection results are improved, objective and quantitative data support is provided for evaluating the winding quality, the mechanical strength and the long-term operation reliability of a transformer coil, and the manufacturing quality of a transformer and the operation safety of a power grid are guaranteed.

The invention relates to the technical field of motors, and discloses a high-temperature-resistant direct-current coreless gear motor and a test system, and the system comprises a temperature monitoring module, a current regulation and control module, a heat dissipation optimization module, a load response module, a cloud analysis module and a virtual verification module. By arranging the temperature monitoring module, multi-dimensional temperature data during operation of the motor can be acquired in real time, and a temperature distribution diagram can be generated, so that the system can comprehensively sense the internal thermal state of the motor and accurately identify local overheating risk points, thereby improving the operation reliability and safety of the motor under a high-temperature working condition; through cooperative operation and closed-loop control of the current regulation and control module, the heat dissipation optimization module and the load response module, according to real-time temperature and load changes, driving current parameters and heat dissipation resource distribution can be dynamically adjusted, and the heat dissipation efficiency is improved. And the output performance and the torque stability of the motor under high-temperature and high-load conditions are ensured.

The invention provides a cable branch box operation state evaluation method and system, and relates to the technical field of data processing, and the method comprises the steps: 1, collecting the electrical parameters and physical state parameters of a cable terminal, a connecting line lug and an insulating sleeve in a cable branch box, and carrying out the preprocessing of the electrical parameters and the physical state parameters, obtaining a standardized state data sequence; and step 2, classifying the standardized state data sequence according to three parts, namely a cable terminal, a connecting wire lug and an insulating sleeve to form three independent state data subsets, and establishing an analysis framework containing M rows and N columns of analysis units for each state data subset. According to the invention, the operation states of the cable terminal head, the connecting wire lug and the insulating sleeve core component in the cable branch box can be accurately evaluated, and the fault risk can be graded and early warned, so that the differentiated operation and maintenance instruction is generated, and the operation and maintenance efficiency and the equipment operation reliability are effectively improved.

The invention discloses a control method and device of a wind driven generator, a terminal and a storage medium, particularly relates to the technical field of operation control of the wind driven generator, and is used for solving the problem that a supporting structure bears violent asymmetric loads due to dynamic response differences of wind and wave load directions in a marine environment in an existing control method. Wind direction and wave direction data are synchronously obtained in real time, the wind direction change rate is calculated, supporting structure vibration signals are analyzed to recognize wave excitation dominant frequency components, and when it is detected that wave excitation energy suddenly changes and the wind direction change rate exceeds the limit, the wind wave direction difference is analyzed; meanwhile, a wave spectrum energy concentration frequency band is determined by analyzing the tower top movement track, the load asymmetry risk level is evaluated by combining the direction difference and the wave energy concentration frequency band, finally, the yaw speed and the variable pitch speed are adjusted in a self-adaptive mode according to the risk level, and accurate recognition and early warning of the wind wave load direction mismatching working condition are achieved. And the operation reliability of the wind driven generator in extreme weather is improved.

The invention relates to the technical field of generator set intelligent control, and discloses a generator set intelligent control method and system, and the method comprises the steps: obtaining the sensor data and vibration signals of a generator set; obtaining a corrected frequency characteristic value according to sensor data screening, denoising and frequency characteristic correction; generating and iteratively updating a control decision instruction sequence according to the real-time change of the vibration signal and the corrected frequency characteristic value to obtain a system stability index; and combining system stability index feedback adjustment to obtain a control decision reliability index. The method can solve the problem of noise interference under a dynamic working condition, realizes fault early warning, parameter optimization and system stability, and improves energy efficiency and operation reliability.

The invention relates to the technical field of multi-stage centrifugal pumps, and discloses an axial balance assembly which comprises a balance shaft sleeve, a pump shaft and a high-pressure throttling ring connected to a water inlet and outlet section, the balance shaft sleeve is connected to the pump shaft and arranged on the periphery of the pump shaft in a sleeving mode, and the high-pressure throttling ring is arranged on the periphery of the balance shaft sleeve in a sleeving mode. The high-pressure throttling ring and the periphery of the balance shaft sleeve are limited to form a flow blocking cavity, the flow blocking cavity is provided with a high-pressure flow blocking inlet and a high-pressure flow blocking outlet, the high-pressure flow blocking inlet and the high-pressure flow blocking outlet are oppositely arranged at the two ends of the flow blocking cavity in the axial direction of the balance shaft sleeve, and the high-pressure throttling ring is provided with a high-pressure ring end face. The balance shaft sleeve is provided with a high-pressure shaft end face, and the high-pressure choke flow inlet is located between the high-pressure ring end face and the high-pressure shaft end face. According to the axial balance assembly, generation of residual axial force from the high-pressure section to the low-pressure section is reduced, the service life of the water pump is prolonged, and the operation reliability of the water pump is improved.

The invention discloses an oil return control method and system of a cascade heat pump system, and the control method comprises the following steps: 1, detecting a first state parameter of an intermediate heat exchanger so as to adjust a compressor and a throttling device at a low-temperature side and a high-temperature side, and when a second state parameter at the low-temperature side meets a condition, adjusting the compressor and the throttling device at the high-temperature side; the operation frequency of the compressor on the low-temperature side / high-temperature side is adjusted again, and return oil flushing is conducted on the intermediate heat exchanger; the second method comprises the following steps: respectively calculating the accumulated carbonization time of the corresponding lubricating oil in the low-temperature side or the high-temperature side, and judging whether the lubricating oil is replaced or not based on the accumulated carbonization time; and the third method comprises the steps that the accumulated low-frequency operation duration of the compressor on the low-temperature side or the high-temperature side in the low-frequency state is detected, and when the triggering condition is met, the operation frequency of the compressor is increased. Based on the control method, the operation reliability and the energy efficiency performance of the cascade heat pump system are improved, and the service life of equipment is prolonged.

The invention discloses a coal storage and transportation intelligent management method and system, relates to the technical field of intelligent management systems, and aims to solve the problems of lack of environment monitoring, scheduling decision lag, extensive safety response and serious data island in the prior art. The method comprises the following steps: collecting the physical state, environmental parameters and operation behavior data of a coal storage yard in real time through a distributed sensor network; constructing a three-dimensional dynamic digital twinborn model and inputting the model into a time sequence neural network to predict the risk of spontaneous combustion, collapse or dust explosion in the future; and generating a dynamic scheduling instruction in combination with the task priority and the equipment state, and triggering a multi-level security response mechanism. The system comprises a sensor network module, a data fusion modeling module, a risk prediction module, a scheduling optimization module, and a closed-loop control and safety response module. According to the scheme, safety early warning preposition, scheduling decision intelligent optimization and resource energy efficiency collaborative improvement in the storage and transportation process are achieved, and the response capability and operation reliability of the coal supply chain are remarkably enhanced.

The invention provides a biomass power generation furnace front feeding cantilever spiral, and relates to the technical field of biomass power generation equipment, the biomass power generation furnace front feeding cantilever spiral comprises a driving part and a feeding part, the driving part comprises a gear motor, a driving shaft, a driving gear, a linkage gear, a driven gear, a rotary lifting disc, a driving piece, a positioning support, a driving part shell and a visual sensing assembly; the feeding part comprises a spiral shaft, a feeding part shell and a rotary anti-blocking assembly. The anti-blocking device has the advantages that shearing force is formed through coaxial and reverse rotation of the rotary anti-blocking assembly and the spiral shaft, the breaking efficiency of soft straw blocking materials is improved, the blocking rate is greatly reduced, the gear meshing precision is precisely controlled by combining a visual camera and a laser displacement sensor, tooth collision is avoided, the equipment operation reliability is remarkably improved, and the practicability is high. And two operation modes are supported to adapt to different materials, and the applicability is high.

The invention relates to the field of homogenizer intelligence, and discloses a homogenizer intelligent pressure increasing and reducing control system based on servo synchronous transmission, which comprises the following steps: extracting the operation inertia difference of each plunger mechanism under a multi-pump parallel structure, generating a synchronous offset vector map, and calculating the pressure increasing and reducing of the homogenizer based on the synchronous offset vector map. Calling a slip registration algorithm and an inertia field decoupling network, extracting reconstructed plunger stroke and pressure response mapping data, constructing a three-dimensional flow-path-stress tensor model, judging whether fluctuation-wear coupling sensitive points exist or not, activating a frequency conversion regulation and control strategy set of a servo driving layer based on a disturbance window and the coupling sensitive points, and carrying out the control of the servo driving layer. And judging whether structural thermal drift feedback unbalance exists or not, dynamically adjusting servo redundancy and a buffer response strategy in combination with a preset life curve and an abnormal response backtracking channel, and outputting a synchronous regulation and control instruction set. The method has the advantage of improving the long-term operation reliability of the homogenizer.

The invention belongs to the field of flexible direct-current transmission power module tests, and discloses a multi-dimensional electromagnetic compatibility test system and method for a flexible direct-current transmission power module, and the method is characterized in that a dynamic power grid simulation unit simulates the electrical stress of the power module under a complex working condition by reproducing power grid limit faults such as direct-current short circuit and alternating-current harmonic waves; the broadband interference injection unit is used for superposing multi-band electromagnetic interference to simulate a composite interference scene according to the noise characteristics of the IGBT / IGCT switching process; the multi-physical field monitoring unit synchronously acquires key parameters such as electromagnetic field intensity, signal transmission, temperature rise and vibration, and analyzes module response under the action of multiple stress coupling in real time. According to the system, cooperative loading of power grid faults and noise is realized, limitation of a single interference source and a simple scene in a traditional test is broken through based on multi-physics field data fusion analysis, and the comprehensive evaluation precision of the anti-interference capability, the operation reliability and the safety of the power module in an extreme electromagnetic environment is improved.

The invention discloses a spiking neural network driven robot dynamic adaptive control system, which relates to the technical field of robot control, and comprises seven modules: an environment sensing module which integrates various sensors and collects and transmits environment, attitude and interaction information; the signal preprocessing module processes data through composite filtering and feature extraction; the spiking neural network modeling module constructs a three-layer structure and performs training based on a fusion learning rule; the dynamic decision output module converts the pulse signal into a control instruction and adjusts gain; the actuating mechanism driving module drives the actuator to act; the state feedback monitoring module monitors and feeds back motion parameters and system states; and the adaptive optimization module optimizes the network and module parameters based on feedback data, and dynamically matches the environment. The control precision and the response speed of the robot in a complex environment are improved, the adaptive capacity is enhanced, the operation reliability and safety are guaranteed through multi-module cooperation, and the application scene is expanded.

The embodiment of the invention provides an electromechanical equipment fault prediction method and system based on a BAS system, and the method comprises the steps: firstly constructing an equipment state reference library based on a historical operation log of the BAS system, and then obtaining an equipment multi-source monitoring data set through a real-time monitoring network of the BAS system, and covering part sensor data, system control instruction data and environment feedback data. And then performing state alignment verification processing on the multi-source monitoring data set and the equipment state reference library to generate a state alignment verification result indicating a matching degree. And performing fault feature level derivation processing based on the result, and generating an equipment fault precursor feature chain containing an abnormal transmission path. And finally, an equipment fault dynamic risk assessment report is generated according to the evolution trend of the fault precursor feature chain and is synchronized to an operation and maintenance decision module of the BAS system, so that the probability of equipment fault occurrence is effectively reduced, the operation reliability and stability of electromechanical equipment are improved, and economic loss and safety risks caused by equipment faults are reduced.

The invention relates to the technical field of industrial equipment fault detection, and discloses a generator iron core lamination equipment fault detection method and system, and the method comprises the steps: obtaining an original vibration signal, and obtaining a first vibration data set through synchronous calibration and feature extraction; a second vibration data set is obtained through time-frequency analysis, decomposition and denoising; constructing a model to enhance the periodic weak impact signal, and obtaining an enhanced signal feature set; performing matching quantification with a preset reference frequency template library, and determining a potential fault signal distribution range; and when the threshold value is exceeded, a fault feature data set is obtained through depth feature extraction, a hyperplane decision model is constructed based on the fault feature data set, and a feature local evolution trend is analyzed to output an early warning result. The method can accurately capture early fault signals, reduces the missing detection and false detection rate, and improves the operation reliability of equipment.

The invention discloses a gradient functional coating hob abrasion monitoring system for hard rock tunneling. The gradient functional coating hob abrasion monitoring system adopts a three-layer gradient functional coating structure including a surface high-hardness abrasion-resistant layer, a middle tough buffer layer and a bottom strong combination transition layer. The method comprises the following steps of: forming continuous gradient grain size, porosity and hardness-toughness gradient distribution by atomic-scale diffusion, innovatively integrating an embedded sensing network, implanting a resistor array, an acoustic emission unit and a thermal resistance type sensor in a coating, and constructing a wear state evaluation model by combining a multi-modal data fusion algorithm. Dynamic adjustment and active protection of the rotating speed and the propelling pressure of the cutterhead are achieved through a three-stage progressive control strategy. Performance limitation and an off-line monitoring mode of a traditional coating are broken through, gradient function cooperation and intelligent sensing control are integrated, the service life of hard rock tunneling equipment under the complex working condition is remarkably prolonged, and the operation reliability of the hard rock tunneling equipment under the complex working condition is remarkably improved.

The invention relates to a pole-mounted circuit breaker monitoring method and system, electronic equipment and a medium. The method comprises the following steps: acquiring a voltage recovery waveform characteristic and a mechanical vibration characteristic during operation of a vacuum arc-extinguishing chamber, and performing timestamp alignment; calculating a contact gap conductive channel risk value based on the aligned waveform characteristics; generating breaking capacity attenuation trend characteristics by combining the historical breaking current peak value, the breaking times and the risk value; calculating the remaining service life according to the trend characteristics, and synchronously obtaining a fault probability value according to the conductive channel risk value; and finally, according to the residual service life and the fault probability value, determining a maintenance early warning level and outputting a maintenance early warning signal. Therefore, according to the method, the risk of the conductive channel is evaluated through fusion of the operation waveform and the mechanical signal, and the breaking capacity attenuation trend is extrapolated along the historical breaking data, so that online evaluation and advanced early warning of the health state of the pole-mounted circuit breaker are realized, and the operation reliability and the operation and maintenance efficiency of the key node of the power distribution network are improved.