961results about "Lamps testing" patented technology

The invention, which relates to the technical field of LED lighting testing, discloses a full-life-cycle accelerated testing system for an intelligent high-power LED lighting device, comprising an environmental parameter detection module, a full-life-cycle testing module, a heat dissipation system module, a service life prediction module and a failure analysis module. The environmental parameter detection module collects multi-field coupling environmental parameters; the full life cycle test module establishes an acceleration factor mathematical model, calculates an acceleration coefficient and determines an acceleration test working condition parameter; the heat dissipation system module selects and adjusts the cooling intensity of the natural convection unit or the flow boiling unit; the life prediction module constructs a life physical-statistical hybrid prediction model and predicts the residual life of the device; the failure analysis module analyzes a heat-electricity-light-stress coupling failure mechanism and generates a performance optimization scheme. According to the invention, the accelerated test and performance optimization of the whole life cycle of the LED lighting device are realized through the cooperative work of multiple modules, and the test efficiency and accuracy are improved.

The invention relates to the technical field of LED modules, and discloses an LED module breakpoint detection and positioning method and device, and the method comprises the steps: carrying out the voltage and current data collection of series and parallel nodes of an LED module, and obtaining an electrical feature matrix and a node topological graph; performing iterative calculation on the electrical characteristic matrix, and processing a voltage difference value and a current variation between adjacent nodes to obtain a breakpoint characteristic vector; inputting the breakpoint feature vector and the node topological graph into a multi-task neural network for multilayer convolution operation to obtain an electrical fault distribution graph; performing feature segmentation and depth feature extraction on the electrical fault distribution map to obtain fault area feature data; and establishing an electric field distribution model for the fault area feature data, calculating an electric field singular point through a least square method, and obtaining breakpoint space coordinate data, thereby improving the accuracy of LED module breakpoint detection, and realizing accurate positioning of the LED module breakpoint.

The invention relates to the technical field of electrical performance testing, and particularly discloses an LED vehicle lamp operation monitoring system and method based on data analysis, and the system can accurately obtain the illumination parameters of the environment where an LED vehicle lamp is located, further scientifically analyzes and determines the reference illumination intensity of the LED vehicle lamp, and on this basis, comprehensively monitors and carefully collects the circuit information of the LED vehicle lamp, thereby improving the reliability of the LED vehicle lamp. Through a data analysis technology, each abnormal lamp bead existing in the LED vehicle lamp is accurately positioned, the abnormal lamp beads are specifically adjusted according to predetermined reference illumination intensity, after adjustment is completed, the running state parameters of the LED vehicle lamp are further monitored, the adjustment adaptation index of the LED vehicle lamp is evaluated accordingly, and the adjustment adaptation index of the LED vehicle lamp is evaluated according to the running state parameters of the LED vehicle lamp. Therefore, whether further performance adjustment needs to be carried out or not is intelligently judged, the adjustment effect is fed back in time, and therefore it is ensured that the made adjustment can fully meet set performance indexes.

The invention discloses a matrix layout illumination state detection method, device and equipment, and the method comprises the steps: collecting and analyzing a power supply bus current waveform and a single lamp feedback signal, and generating a node feature cluster; extracting a power consumption difference value of adjacent lamps, identifying an abnormal observation point and constructing a fault diffusion chain; marking a timestamp for the fault diffusion chain, determining a fault source, and marking current by injecting characteristics to delimit an influence domain; deploying monitoring anchor points at the boundary of the influence domain, collecting the light color parameter variation and predicting the residual life; extracting the oscillation envelope of the starting current peak, evaluating the health degree of the driver and generating a maintenance density field; and a three-dimensional detection field is constructed by fusing multi-dimensional detection data, singular points are searched, and coordinates of a fault lamp are accurately analyzed through fault positioning pulses. According to the invention, three-dimensional monitoring from electrical characteristics and optical performance to driver states is realized, a single lamp fault can be accurately positioned, a life trend can be predicted, fault propagation can be tracked, and technical support is provided for intelligent operation and maintenance of a large-scale illumination system.

The invention relates to the technical field of LED reliability testing, and provides an LED lamp residual life prediction method, device and equipment, and the method comprises the steps: carrying out the real-time collection of the operation state parameters of an LED lamp, obtaining the operation state data, environment data and work load data, inputting the operation state data into a preset degradation model for analysis, and obtaining the residual life of the LED lamp. Obtaining a real-time degradation trend curve and analyzing a degradation trend interval; and carrying out weighted fusion calculation on the degradation trend interval by utilizing the environment data and the working load data to obtain a residual life prediction value of the LED lamp, and generating a residual life prediction report according to the residual life prediction value of the LED lamp. By collecting operation state parameters, environment data and working load data of the LED lamp in real time and generating a residual life prediction report, life changes of the LED lamp in different environments and working conditions are achieved, and the problem that an existing light attenuation detection method neglects factors of environment and load changes, and life prediction is not accurate is solved.

The present invention provides a fault diagnosis and maintenance method and system for a smart street lamp, the method comprising: collecting data on the operating parameters of each component node of the smart street lamp, performing noise reduction processing using wavelet transform, and generating structured data. By combining principal component analysis and sliding time window technology with Mahalanobis distance calculation, feature extraction and spatiotemporal correlation analysis are performed on the structured data to obtain key features and spatiotemporal correlation information between nodes. The above information is input into a spatiotemporal hybrid model to generate fault detection results, and a machine learning algorithm is used to locate the faulty components, predict their performance degradation trends, and generate targeted maintenance strategies. The present invention realizes intelligent management of the entire process from fault detection to maintenance, effectively improving the operating stability and management efficiency of smart street lamps.

The invention relates to the technical field of electronic circuit detection, in particular to a detection method for checking abnormal work of a lamp, which comprises the following steps: acquiring the consistency of a lighting state and voltage, extracting abnormal response, checking power supply connection and checking non-response, monitoring and controlling the relationship between output and current action starting, and analyzing response continuity. And detecting branch voltage difference change and direction, monitoring voltage jump and current response starting point performance, extracting response data, and obtaining a classification result. According to the invention, through cooperative detection of voltage and current response behaviors, in combination with path voltage difference direction change and time sequence characteristics, a load abnormal response section is identified step by step, the abnormal state identification capability is enhanced, an action time sequence cross validation mode is adopted to replace a traditional static judgment process, misjudgment interference is reduced, and manual intervention requirements are reduced; therefore, the detection process is more continuous, the related operation is universal, the method can be suitable for various lamp structures, the troubleshooting precision is improved, and the execution cost is controlled at the same time.

The invention relates to the technical field of LED street lamp control, and discloses an LED street lamp test control system, which comprises a multi-dimensional acquisition module and a test control module. According to the LED street lamp test control system, management data and optical detection data of all LED street lamps and sensing data of the working environment of the LED street lamps are acquired through a multi-dimensional acquisition module and are classified to form a data set, a test control module analyzes the switching delay degree and the dimming smoothness of each LED street lamp, corresponding switching fluctuation rate and smoothing coefficient are generated, and the switching fluctuation rate and the smoothing coefficient are calculated. The LED street lamp with abnormal delay is accurately identified, the light attenuation degree of each LED street lamp is analyzed, the corresponding light attenuation coefficient is generated, the root of the light attenuation problem is accurately judged, the multi-dimensional analysis accuracy is high, the fluctuation threshold value, the smooth threshold value and the light attenuation threshold value of the fixed range are set, whether the LED street lamp has the switching delay problem and the function fault or not is judged, and the LED street lamp is high in accuracy. And the corresponding management suggestions are automatically output according to the environment adaptability to the working environment, so that the fault expansion is avoided, and the intelligent decision-making reliability is high.

The invention discloses an intelligent lighting equipment maintenance management system based on data analysis, and belongs to the technical field of equipment maintenance management, and the system comprises a data obtaining module which obtains associated data related to lighting equipment from a plurality of data sources; the transmission module is used for transmitting the acquired associated data to the central management platform; the central management platform carries out unified preprocessing on the associated data and then carries out analysis according to the associated data so as to judge whether the lighting equipment is abnormal or not, and the central management platform comprises a real-time judgment unit, an early warning analysis unit and a power consumption detection unit; and the maintenance adjustment module executes a corresponding strategy according to a judgment result. The power consumption condition of each lighting device can be judged, when the power consumption is abnormal, the power of the lighting device can be dynamically adjusted according to the intensity of natural light of the environment, and resources can be greatly saved under the condition that normal use of the lighting device is guaranteed.

The invention relates to the technical field of lighting electrical testing, in particular to a lamp testing system and method, and the system comprises an electrical parameter collection module, a harmonic analysis module, an optical collection module, a light fluctuation analysis module and an abnormality judgment module. Wherein the electrical parameter acquisition module is used for acquiring a real-time voltage waveform of an input end of a lamp; the harmonic analysis module is used for extracting a fundamental wave and each harmonic component and calculating a harmonic distortion rate; the optical acquisition module is used for synchronously acquiring light signal time sequence data of the light emitting surface of the lamp; the light fluctuation analysis module calculates the light fluctuation frequency of the light source; and the abnormity judgment module is used for generating an electrical-optical relevance index and comparing the electrical-optical relevance index with a preset threshold value so as to output a stroboscopic qualification judgment result of the lamp. According to the method, the accuracy of lamp stroboscopic detection and the causal identification capability are effectively improved by constructing the electrical-optical correlation index and realizing synchronous judgment.

The invention provides a vehicle lamp test case intelligent generation method and system based on a knowledge graph, and relates to the technical field of vehicle lamp test. Comprising the steps of analyzing a test demand according to a customer product demand document, generating a test case according to a vehicle lamp test knowledge graph, filtering invalid test cases and performing case verification, feeding back a test report and updating the vehicle lamp test knowledge graph. According to the method, the test requirements and the index parameters are extracted through the natural language processing technology, intelligent generation of the test cases is achieved in combination with the knowledge graph, invalid cases are filtered through the reinforcement learning agent, the effectiveness and the test efficiency of the test cases are improved, and industrial standards and regulation requirements are met.

The invention discloses an LED lamp bead production detection system based on machine vision, which relates to the technical field of machine vision production detection and comprises a vision acquisition module, a production detection module and an execution learning module. In the prior art, the detection precision is insufficient, and the influence of illumination change and environment interference is large; the adaptability is poor, and the system cannot adapt to LED lamp beads of different specifications; surface defect detection is difficult due to the influence of illumination change on image quality; manual intervention is much and low in efficiency, and manual defect screening is low in efficiency and is easily interfered by human factors; the production process is not optimized enough, problems occurring in production cannot be fed back and adjusted in time, and quality and efficiency are affected; according to the invention, ASIC image processing, machine learning, path planning, a light supplementing technology and automatic elimination operation are integrated, so that the detection precision, adaptability, automation level and production optimization capability of the system are improved; the comprehensiveness and accuracy of detection are ensured in multiple dimensions, and the qualified rate of products is effectively improved.

The invention discloses a toe-in station vehicle brake lamp fault detection method and system. The system comprises an image collector, a photoelectric sensor, a toe-in station controller, a server and a client, wherein the image collector is used for collecting a vehicle image of a toe-in station; the photoelectric sensor is used for outputting an occupying signal; the toe-in station controller comprises a timing unit, and the timing unit is used for recording vehicle occupation time; when the server responds to the situation that the occupation time is larger than zero, an image collector is controlled to collect a vehicle image, and a brake lamp state recognition model of the server recognizes the state of a vehicle brake lamp based on the vehicle image obtained within the occupation time; the server stores vehicle brake lamp state information based on the recognized vehicle brake lamp state, and when the vehicle brake lamp state is a non-lighting state and the occupation time is ended, the vehicle brake state information is sent to a user corresponding to the client code; and the client is used for receiving and displaying the vehicle brake lamp state information.

The invention discloses an intelligent aging test fault diagnosis method, system and equipment for a lamp. The intelligent aging test fault diagnosis method for the lamp comprises the following steps: acquiring information of a tested lamp to be subjected to an aging test; setting external conditions according to the use environment of the tested lamp to be subjected to aging test; the data monitoring module obtains input power supply parameters; collecting power supply data; the data communication module executes data communication; judging whether abnormal data exists in the data or not; summarizing the power supply data in the aging test time period; performing waveform drawing on all the power supply data in the aging test time period, and performing statistical analysis; judging whether the parameters of the tested lamp are abnormal or not; if the judgment result is normal, outputting a normal data analysis result, and executing data archiving; if the judgment result is abnormal, diagnosis of the corresponding fault type is executed; and outputting a fault type analysis result.

A trailer test module of a vehicle is electrically connected between a trailer tow electrical connector of the vehicle and a wiring harness of the vehicle that carries electrical signals for a trailer such that when the electrical connector of the trailer is attached to the trailer tow electrical connector, the trailer tow electrical connector is between the trailer test module and the electrical connector of the trailer. The trailer test module includes circuitry that replicates an electrical load of the trailer.

The invention discloses a lamp fault detection method and a vehicle machine system, an electric vehicle comprises the vehicle machine system and a plurality of lamp power supply circuits, the vehicle machine system comprises a display screen, a detection module and a processing module, and the lamp power supply circuits are correspondingly connected with lamps. The lamp fault detection method comprises the steps that the processing module executes a lamp detection process; the detection module detects the working state of the lamp through a circuit and / or an environment image; the display screen displays the working state of the lamp according to a preset rule. According to the invention, the fault vehicle lamp can be positioned and identified, the fault of the vehicle-mounted lamp can be accurately detected, clients and maintenance personnel can accurately position problems through displayed error codes, troubleshooting and maintenance are facilitated, and the driving safety of vehicle owners is effectively improved.

The invention discloses an urban intelligent lighting wireless monitoring method and system, and relates to the technical field of intelligent lighting. The method comprises the following steps: acquiring data of lighting equipment and a multi-dimensional sensor, setting the lighting equipment as nodes, setting a dynamic coupling coefficient between the nodes as an edge weight, and constructing a lighting topology model; performing quantum state feature mapping on the multi-dimensional sensor data, constructing a topological manifold tensor, calculating a topological invariant through manifold decomposition, and generating an abnormal alarm when the topological invariant is greater than a set threshold value; and when an abnormal alarm is detected, obtaining all adjacent lighting devices of an abnormal node, constructing a target function, solving to obtain power and lighting brightness of the adjacent lighting devices, and performing adjustment. Through combination of quantum state feature mapping, topological flow decomposition and dynamic coupling coefficients, multi-dimensional sensor data are precisely processed, high-precision monitoring, energy management optimization and dynamic dimming are realized, and meanwhile, stable operation of the system is ensured through global optimization and an intelligent repair mechanism.

The invention relates to the technical field of LED lamp testing, and discloses an LED lamp testing method and device, testing equipment, a testing system and a storage medium, and the method comprises the steps: generating a corresponding adjustment parameter based on a preset adjustment instruction, and transmitting the adjustment parameter to a to-be-tested device, the to-be-tested equipment is used for adjusting the LED lamp and the camera according to the adjusting parameters; sending a shooting instruction to the to-be-tested equipment, so that the to-be-tested equipment irradiates the standard color card with light emitted by the adjusted LED lamp, and shooting the standard color card through the adjusted camera to obtain a target image; and obtaining a test result corresponding to the LED lamp according to the target image. According to the invention, through synchronous adjustment and collection of cooperative output of illumination and imaging under a controllable condition, integrated performance evaluation of the LED lamp on the to-be-tested device is realized, and a single LED lamp does not need to be disassembled to be tested, so that the test process is simplified.

The invention relates to a method (10) for assessing a remaining lifetime of an LED gear (20). The method (10) comprises the steps of: supplying (11) a constant current load from an electrolytic capacitor (21) of the LED gear (20); measuring (12) an electrical characteristic of the electrolytic capacitor (21) over time when the constant current load is supplied by the electrolytic capacitor (21); calculating (13) a capacitance of the electrolytic capacitor (21) based on the measured electrical characteristic; and determining (15) a remaining lifetime estimate and / or a reaching of an end of lifetime of the LED gear (20) based on the calculated capacitance.

The invention discloses a rapid aging test device and evaluation method for an LED advertising lamp box, and relates to the field of aging test devices.The rapid aging test device comprises an end base and a supporting table, a lower test area is fixedly arranged on the upper side of the end base, a middle test area is installed on the upper side of the lower test area, and an upper test area is installed on the upper side of the middle test area; a top frame is fixedly mounted at the top of the upper test area, a supporting frame is connected to the bottom of the end seat, a base is fixedly connected to the bottom of the supporting frame, universal wheel mounting hole positions are formed in the bottom of the base, and the base is placed in the aging test room. According to the rapid aging test device for the LED advertising lamp box, the three-dimensional space of a test room is fully utilized through the layered and partitioned design, the containing capacity of a unit area is greatly improved, space waste caused by plane placement is avoided, LED lamp boxes of multiple batches and multiple models can be tested at the same time, and the test efficiency is improved.

The invention relates to the technical field of fault diagnosis, in particular to an intelligent street lamp fault diagnosis and maintenance system, which comprises a signal collaborative acquisition module, a frequency domain conversion module, a fault identification module, a coupling verification module and a maintenance scheduling module. According to the invention, through a multi-source data synchronous acquisition and time sequence alignment technology, the influence of external environment interference on monitoring data is eliminated, and the stability and accuracy of photoelectric signals are ensured. Stable signal features are extracted through frequency domain conversion and feature screening, accurate fault recognition is achieved based on frequency components and similarity calculation, multi-dimensional verification is conducted in combination with instantaneous power comparison and communication delay detection, the accuracy and reliability of fault judgment are improved, therefore, misjudgment and missed judgment are avoided, maintenance scheduling is optimized, and the fault diagnosis efficiency is improved. The fault response efficiency and the overall stability of the street lamp system are improved, maintenance lag and resource waste caused by inaccurate fault diagnosis are effectively reduced, and the operation reliability and the maintenance response speed of the street lamp are improved.

The invention provides a traffic signal lamp data quality detection method, a traffic signal lamp data quality correction method and related equipment, and the method comprises the steps: receiving traffic signal lamp data reported by traffic signal lamp equipment in real time based on a distributed stream processing architecture, carrying out the structural processing, and extracting equipment identification, timestamp, signal state, phase information and other fields; in a distributed stream processing architecture, anomaly detection tasks of multiple dimensions of data timeliness, signal logic consistency and equipment online state are executed in parallel, data quality marks including anomaly types and corresponding anomaly parameter values are generated, and traffic signal lamp data with quality labels are formed. And for the detected abnormal data, executing corresponding data correction strategies according to different abnormal types, and issuing the corrected traffic signal lamp data to a downstream service module for use. According to the invention, high-concurrency and low-delay data processing is realized in a scene of dense deployment of multi-source traffic signal lamp equipment, and the real-time performance and accuracy of the traffic signal lamp data are improved.

The invention discloses a pump lamp tube fault accurate diagnosis system based on multi-parameter data analysis, and relates to the technical field of industrial automation monitoring, and the system comprises a multi-parameter acquisition and unique fault judgment algorithm, a multi-parameter acquisition module is connected with a high-precision current transformer, an infrared temperature sensor, a miniature pressure sensor, a photoelectric sensor and the like, and the multi-parameter acquisition module is connected with the unique fault judgment algorithm; parameters such as current, voltage, lamp tube surface temperature, internal gas pressure and luminous intensity during operation of a pumping lamp tube are accurately acquired, denoising and filtering parameters and a normalization method based on lamp tube rated parameter values are set by the preprocessing unit, and a fault diagnosis model is constructed by the data analysis module by selecting multiple learning algorithms. The collected and preprocessed parameter vector is X, a weight vector W and a bias item b are obtained through model training, a comprehensive score S is calculated, a fault judgment threshold T is set through a large amount of sample data training, and if S is larger than or equal to T, it is judged that a lamp tube has a fault, and a fault type mark is output; if Slt; and T, judging normal operation of the lamp tube.

The invention discloses an intelligent monitoring system for predicting the service life of a high-power LED lamp bead, and relates to the technical field of intelligent monitoring, and the system comprises a data collection module for collecting the real-time current density distribution data of the high-power LED lamp bead in a working state, and a calculation module for calculating the real-time current density distribution data of the high-power LED lamp bead in a working state. The calculation module is used for calculating the hot spot position and the hot spot temperature of the lamp bead based on the current density distribution data, the analysis module is used for analyzing the influence degree of the hot spot position and the hot spot temperature on the brightness attenuation of the lamp bead, and the driving regulation and control module is used for adjusting the driving current of the lamp bead according to the influence degree, optimizing the brightness and prolonging the service life of the lamp bead; according to the intelligent monitoring system for predicting the service life of the high-power LED lamp bead, the problem of brightness attenuation caused by inconsistent current density in a long-time high-power working state in the prior art is solved.

The present teachings relate to a method for identifying reusable components of a vehicle lamp assembly, the method including: i) performing an electric circuit functionality test on each component of a plurality of components of the vehicle lamp assembly; ii) performing an illumination test on each light source within the vehicle lamp assembly; iii) identifying which of the components of the plurality of components pass and / or fail the electric circuit functionality test; and iv) identifying which light sources pass and / or fail the illumination test.

The invention discloses an LED lamp aging test device, and relates to the technical field of LED lamp testing, the LED lamp aging test device comprises a frame body, the inner side of the frame body is slidably provided with a lifting plate, the side surface of the frame body is fixedly provided with a pair of driving motors, and the driving motors are respectively arranged at two sides of the frame body. The output end of each driving motor is fixedly provided with an adjusting screw rod through a coupler, the side face of the lifting plate is in threaded connection with the side faces of the adjusting screw rods through lug plates, and the clamping assembly is used for vertically fixing the cylindrical bulb to the surface of the lifting plate and comprises a positioning piece arranged at the top of the lifting plate. According to the LED lamp aging test device, different from a traditional mode of manually connecting bulbs to be tested and power supplies one by one, simultaneous connection of a plurality of bulbs and the power supplies is realized by using a mechanical structure, so that the efficiency of bulb aging test is improved; and in the connecting process, the bulb is protected, and the bulb is prevented from being scratched.

The utility model relates to the technical field of filament detection equipment, and discloses a vehicle H7 bulb filament detection mechanism, which comprises a working platform, and a tray is arranged at the top end of the working platform. According to the vehicle H-shaped bulb filament detection mechanism, due to the design of a second air cylinder and a first air claw, a plurality of bulbs can be accurately clamped and conveyed into a moving block, due to the design of a first air cylinder, the bulbs on the moving block can be sequentially aligned with the second air claw, and due to the fact that the second air claw is provided with two grippers, the bulbs can be accurately clamped and conveyed into the moving block. Due to the design of the power-on detection module and the current sensor, power-on detection can be conducted on the bulbs, and when lamp filaments of the bulbs break down, the current sensor stops the device and gives an alarm to attract attention of operators. And due to the design of the camera and the illuminating lamp, the lamp filament can be photographed and detected, so that the bulb can be efficiently and accurately detected.

The invention discloses an automatic detection device for testing lamp beads of an LED lamp strip, and belongs to the technical field of LED lamp strip testing. The device mainly comprises a workbench, one side of the top surface of the workbench is provided with a discharging device used for installing a lamp strip reel, the other side of the top surface of the workbench is provided with a receiving device used for rolling the lamp strip reel, and a lamp bead detection bin used for detecting an LED lamp strip is fixedly installed on the top surface of the workbench and located between the discharging device and the receiving device. The interior of the lamp bead detection bin is divided into a dust removal area and a detection area through a partition plate, the detection area comprises a belt pressing assembly and a detection assembly, and by combining winding and unwinding of an LED lamp belt with lamp bead detection, rapid and continuous detection can be achieved, it is ensured that each lamp bead can emit light reliably and be recognized accurately, and the detection efficiency is improved. The strip pressing assembly and the conductive terminals effectively maintain the flatness of the LED lamp strip and ensure accurate contact of power supply contacts, so that the damage risk of lamp beads is reduced, the production efficiency is improved, the product quality is ensured, and errors caused by manual operation are reduced.

The invention provides a fault monitoring method and system based on LED classroom lamps and a storage medium, and relates to the technical field of fault monitoring, and the method comprises the steps: obtaining an operation data matrix of the LED classroom lamps; extracting a running current sequence from the running data matrix, converting the running current sequence into a running current unbiased domain, and determining the current variation deviation characteristics of the LED classroom lamp in the unstable working state through the running current unbiased domain; obtaining operation light intensity data of the LED classroom lamp under the unsteady-state work, and performing unsteady-state feature extraction on the operation light intensity data to obtain a light intensity fault feature vector of the LED classroom lamp under the unsteady-state work; the fault type information of the LED classroom lamp is determined by using the current variation deviation feature and the light intensity fault feature vector, and a fault report of the LED classroom lamp is sent according to the fault type information, so that the operation current feature and the light intensity feature of the LED classroom lamp under the unsteady-state work can be effectively extracted, and the fault monitoring precision of the LED classroom lamp is improved.

The invention relates to the technical field of lighting equipment, and provides an intelligent fault diagnosis method and system for LED lighting equipment, for each LED street lamp, extracting multi-dimensional data information of the LED street lamp in a first preset time period from a multi-dimensional state matrix, and determining whether the LED street lamp has a potential fault based on the multi-dimensional data information. If the potential fault exists, generating a pre-selected fault set of the LED street lamp based on the multi-dimensional data information; for each pre-selected fault in the pre-selected fault set, performing extension calendar analysis on the pre-selected fault based on extension structure information of the LED street lamp network to obtain fault influence node information corresponding to the pre-selected fault, and based on the state information of each fault influence node in the fault influence node information in a second preset time period, judging whether the pre-selected fault exists, and if so, determining that the pre-selected fault is a target fault corresponding to the LED street lamp. The method improves the accuracy of fault detection.