677results about How to "Effective filtering" patented technology

The invention relates to the technical field of computer vision and image processing, in particular to a robust image matching system and method based on multi-scale attention feature fusion, and the system comprises a feature extraction module which extracts a multi-resolution feature map containing image features from a to-be-matched image; the position coding module performs spatial position coding on the image features to improve the spatial perception capability of the model; the multi-scale attention module performs multi-scale enhancement processing on the image features, so that the model is more effectively focused on the significant part of the image; the attention module establishes a dependency relationship between image features; the coarse-level matching layer module generates a coarse-level matching result and screens out a matching pair with relatively high confidence coefficient; and the coarse-to-fine module carries out fine processing on the coarse matching result, so that more accurate feature matching is realized. According to the method, the effectiveness and reliability of the method are verified by testing the image matching performance of the to-be-tested picture under the conditions that the to-be-tested picture contains different illumination changes, extreme visual angle changes, repeated textures and the like.

The invention discloses a self-adaptive multi-hop retrieval knowledge graph construction method for large language model questions and answers. The method comprises the following steps: extracting triples of an input question and a corpus; self-adaptive multi-hop retrieval matching is carried out, and a specific triple related to the question in the corpus is retrieved and recognized; constructing a knowledge graph by using the question in the adaptive multi-hop retrieval matching process and a corpus triple; the answer predictor model comprises node embedding, message passing and selective filtering, and the node embedding is used for encoding questions and a knowledge graph; carrying out message transmission based on the coded problem and the knowledge graph based on a graph convolutional network; selective filtering is used for filtering redundant information of the knowledge graph; according to the method, the problem that the large language model generates illusion can be relieved, the complex reasoning process can be understood, and therefore the question answering and logical reasoning performance of the large language model is improved.

The invention provides a substation safety management and control method and system based on a three-dimensional reconstruction model, and relates to the technical field of safety management and control, and the method comprises the steps: obtaining real-time point cloud data inputted by a laser point cloud sensor and a real-time image collected by a camera; comparing the real-time point cloud data with a background point cloud model, and extracting a changed dynamic region by using a background difference algorithm; the dynamic reconstruction module is used for identifying a first position of a first dynamic target in the dynamic region based on the real-time point cloud data; calculating a second position of a second dynamic target contained in the real-time image; if the first position is successfully matched with the second position and the sparse structure of the real-time point cloud data is successfully matched with dense pixels of the real-time image, determining that the first dynamic target and the second dynamic target are both dynamic flight targets; and determining the position of the dynamic flight target according to the first position and the second position, and marking in the three-dimensional model. The safety management and control precision of the transformer substation can be improved.

The invention discloses an AWG chip automatic test system based on a photodiode array, and the system comprises a light source transmitting module which is used for transmitting laser and finally coupling the laser to an input waveguide of an AWG chip; the six-axis control platform controls the single-mode optical fiber FA to be accurately coupled to the AWG chip by adjusting the position of the single-mode optical fiber FA; the light source detection module comprises a PD array composed of a plurality of photodiodes, and the PD array obtains information of an output waveguide of the AWG chip; data acquired by the upper computer and the data acquisition system are transmitted to the upper computer to be processed and displayed, and by taking a CWDM chip as an example, insertion loss, central wavelength, bandwidth, crosstalk and the like of the chip can be calculated by respectively acquiring optical power of four channels in the chip, so that whether the chip reaches the standard or not is judged. In the process, as the AWG chip is a passive device, input and output waveguides at the two ends of the chip carry out optical transmission in an alignment mode, and if alignment is wrong, large loss is likely to be generated.

The invention relates to the field of LED driving controllers, in particular to a control method of a waterproof touch type LED driving controller, which automatically identifies environmental conditions and user preferences through an AI algorithm, dynamically adjusts sensor parameters, realizes self-adaptive configuration, intelligently distinguishes real touch control and false triggering through charge detection, capacitive sensing and weak magnetic field change, and improves the control accuracy of the waterproof touch type LED driving controller. A user operation intention such as light touch, long press and sliding is deeply analyzed in combination with machine learning, after a control strategy is dynamically generated, LED brightness and color temperature are automatically adjusted and a command is executed according to the user intention and environmental parameters, the control strategy is optimized through a reinforcement learning algorithm, meanwhile, a health monitoring function is integrated, a user operation mode and environmental data are analyzed, and the user experience is improved. The health state of the equipment is intelligently judged, potential faults are warned in advance, and stable operation of the equipment and user experience are ensured.

The invention relates to the technical field of pipe network monitoring, in particular to a water supply pipe network pipe burst alarm positioning system based on real-time pressure monitoring data, and the system comprises a pressure data collection module which collects pressure data from a plurality of pressure monitoring points of a water supply pipe network; the pressure drop threshold calculation module is used for determining an alarm pressure drop threshold of each pressure monitoring point based on historical pressure data; the voltage drop alarm module is used for calculating a current time window voltage drop value and comparing the current time window voltage drop value with a voltage drop threshold value; the association alarm module is used for clustering alarm information of adjacent pressure monitoring points and combining a plurality of alarm points which are close in space into a single alarm event; the alarm positioning module is used for matching a pipe explosion node corresponding to the current alarm information by utilizing a mode recognition algorithm and quickly positioning the pipe explosion node; according to the method, the system calculates the aggregation characteristics, the description capability and the credibility of the alarm event are enhanced, and the identification and positioning efficiency of the system on the pipe explosion event in the complex pipe network environment is improved.

The embodiment of the invention belongs to the technical field of artificial intelligence, and relates to a product recommendation method and device, computer equipment and a storage medium, and the method comprises the steps: constructing a user portrait corresponding to a requesting user according to dialogue text data; performing semantic analysis operation on the dialogue text data according to a large language model to obtain a real intention of a user and a product demand index; constructing a dynamic knowledge graph according to the user portrait, the real intention of the user and the product demand index; generating a product comparison set according to the dynamic knowledge graph; and performing a comparison operation on the to-be-selected products in the product comparison set according to an iterative comparison process to obtain a target recommended product. According to the method, through deep user portrait and multi-dimensional similarity calculation, dynamic comparison set generation and progressive accurate comparison, irrelevant information is effectively filtered, the cognitive burden of the user is reduced, and the accuracy of personalized recommendation is effectively improved.

The invention relates to the technical field of underwater image enhancement processing, in particular to a pyramid network-based underwater image dynamic enhancement method and application, and the method comprises the steps: decomposing an input underwater image into layered image groups; using a deterministic color mapping network to convert the low-frequency layer input image into a low-frequency layer output image; using a double convolution attention module to obtain enhanced input features; using a packet expansion feedforward network to obtain a pixel-by-pixel mask; performing operation on the enhanced input features and step-by-step pixel masks to obtain high-frequency components; and reconstructing the low-frequency layer output image and the high-frequency component by using a Laplacian pyramid network to obtain an enhanced output underwater image. In conclusion, the underwater image can be dynamically enhanced, the adaptability is high, the method is suitable for various water bodies, color distortion can be effectively corrected, noise introduction is restrained, more image details can be reserved, and the underwater image has better visibility and higher recognition degree.

The invention relates to the field of methylation sequencing, in particular to a screening method of methylation sequencing fragments. The method comprises: 1) using a healthy sample, establishing a signal baseline by constructing an n-order Markov chain model, the healthy sample containing a methylation sequencing result, and a sequencing fragment of the healthy sample originating from an rDNA region; and 2) filtering a to-be-detected sample by using the established signal baseline, the to-be-detected sample containing a methylation sequencing result, and a sequencing fragment of the to-be-detected sample being derived from an rDNA region. According to the method disclosed by the invention, background noise from normal tissues is effectively filtered, and methylation signals (especially rDNA methylation signals) related to diseases are effectively screened out.

The invention discloses a real-time signal processing early warning method, and relates to the technical field of adaptive signal processing, and the early warning method specifically comprises the following steps: installing a vibration sensor at a bearing pedestal and a housing of a motor, and ensuring that the x direction of the sensor is aligned with the operation direction of equipment; then the driver is calibrated to ensure the accuracy of subsequent data acquisition; the method comprises the following steps: setting acquisition interval time in data acquisition as 5-10S, and performing normalization preprocessing on data acquired by a vibration sensor, and has the advantages that time domain and frequency domain analysis is performed on a vibration signal, a time domain signal is converted into a frequency domain signal by using fast Fourier transform (FFT), and the amplitude of each frequency point is calculated, so that the accuracy of the data acquisition is improved, and the accuracy of the data acquisition is improved. The fusion processing mode can provide deeper understanding of motor vibration characteristics, effectively reveals energy distribution of signals on different frequency components, and is helpful for identifying potential faults or abnormal conditions.

The invention relates to the field of activated carbon adsorption boxes, and particularly provides a dust and waste gas treatment device for chemical production. The device comprises a device body, a pretreatment box is arranged on one side of the device body, a dust filtering mechanism is arranged on the inner side of the pretreatment box, the dust filtering mechanism and the dust filtering mechanism on the inner side of the pretreatment box are key components, a first baffle, a second baffle and a third baffle are arranged in a staggered mode, and an S-shaped flow channel is formed; meanwhile, the detachable filter frame and the filter material are arranged in the flow channel and act together to effectively filter dust in the waste gas, and the primary treatment process greatly reduces the treatment burden of the follow-up activated carbon box, so that the treatment efficiency is improved. The treatment effect of the activated carbon box on waste gas containing a certain amount of dust is improved, efficient operation of the whole dust and waste gas treatment device is ensured, and the treatment adaptability to the waste gas is improved.

The new energy charging pile temperature control device comprises a charging pile body, a temperature control opening is formed in the bottom of the side end face of the charging pile body, a temperature control assembly is clamped in the temperature control opening, and an air cooling assembly is connected to the position, corresponding to the temperature control assembly, in the charging pile body. The temperature control assembly is used for driving air to enter the charging pile body through the temperature control assembly for forced air cooling; according to the charging pile, the air cooling fan drives air to penetrate through the temperature control assembly to enter the charging pile body for forced air cooling in the rapid rotation process, the air filter plate can effectively filter dust in the air in the process that the air penetrates through the air filter plate, and in the process, liquid water in the temperature control frame absorbs heat in the air, so that the heat in the air is dissipated; due to the fact that hot air has the characteristic of flowing upwards, the cooled air enters the charging pile body and then flows from bottom to top for forced air cooling, and therefore dissipation of heat of power equipment arranged in the charging pile body is accelerated, and the heat carried in the air is taken away through liquid water single circulation.

The invention provides a ground fault identification method, device and equipment based on zero-sequence voltage periodic differential energy and a storage medium, and the method comprises the steps: collecting and processing a zero-sequence voltage signal of a bus in a power distribution network system, and obtaining a zero-sequence voltage data sequence; according to the zero-sequence voltage data sequence, calculating zero-sequence voltage periodic differential energy of the bus to obtain a zero-sequence voltage periodic differential energy sequence; determining a zero-sequence voltage period differential energy threshold according to a preset condition, and comparing the zero-sequence voltage period differential energy threshold with the zero-sequence voltage period differential energy sequence to obtain a comparison result; and generating a grounding fault identification result of the power distribution network system according to the comparison result and the zero-sequence voltage signal. Through periodic differential energy detection of the zero sequence voltage, voltage waveform change caused by a grounding fault is captured, an energy threshold value is set, and an instantaneous disturbance signal is effectively filtered. Periodic difference calculation is not sensitive to noise interference and data loss, and the stability and reliability of detection are guaranteed.

The invention discloses a fish excrement and particulate matter filtering device for a fish tank, and relates to the technical field of fish tank accessories, the fish excrement and particulate matter filtering device comprises an upper cover, a filtering main body box, a drawer outer box, a filtering drawer and a confluence bottom support; the device is small and exquisite in overall design, small in occupied space and suitable for fish tanks of different sizes, the space around the fish tanks is saved through the design, the device is more attractive and elegant, meanwhile, due to the characteristic of modular assembly, a user can flexibly adjust the device according to the actual size and requirements of the fish tanks, and the practicability is high. The water outlet grooves of the three groups of inclined nozzles in the device obliquely spray water to cooperatively drive the filter screen to rotate, so that effective filtering is realized, fish manure and particle impurities are cleaned through physical scouring and rotary centrifugation, the filter screen is effectively prevented from being blocked, the filtering effect is remarkably improved, and meanwhile, the water outlet grooves of the three groups of inclined nozzles are effectively prevented from being blocked. The design of the rotary filter screen and the inclined nozzle also reduces the energy consumption, and conforms to the modern environment-friendly and energy-saving concept.

The invention discloses a fan rotating part anomaly detection method based on artificial intelligence. The fan rotating part anomaly detection method comprises the steps that S1, a fan rotating part sound signal set is constructed; s2, generating a fan rotating part sound signal feature vector set; s3, training to obtain a deep neural network model for detecting the abnormal state of the fan rotating part; s4, a hierarchical reinforcement learning algorithm is utilized to analyze and classify the feature vector set of the fan rotating part, and a high-level strategy judges whether to activate a low-level strategy according to the operating environment and the load condition of the fan and the overall change trend of the sound signal set; according to the low-layer strategy, whether an abnormal state exists or not is further judged according to the fan rotating component feature vector set; s5, denoising and filtering parameters of the sound signal set are adjusted in real time; and S6, when the low-level strategy identifies an abnormal state through analysis of the feature vector set, the system automatically triggers an alarm mechanism. According to the method, the fan anomaly detection cost is reduced, and the detection precision and the intelligent level are improved.

The invention discloses a compact magnetic deflection system for neutral beam injection. The compact magnetic deflection system comprises an iron yoke assembly, two magnet assemblies with the same structure and a magnet protection assembly, the iron yoke assembly is of a rectangular frame structure and forms a complete magnetic loop, the two magnet assemblies are oppositely arranged in the iron yoke assembly, and a channel is reserved between the two magnet assemblies. The magnet protection assembly surrounds the two magnet assemblies; the magnet assembly comprises a magnet exciting coil box, an iron core and an electrified coil, two space grooves are formed in the excitation coil box in a rectangular-ambulatory-plane mode, the iron core is located in the space groove in the inner layer, the electrified coil is located in the space groove in the outer layer, and the head end and the tail end of the electrified coil extend out of the side edge of the excitation coil box in the same direction; charged ions flexibly deflect out of an original beam line channel by changing the current of the electrified coil or the number of turns of the coil. According to the invention, mixed charged ion beams can be effectively filtered out, and purified neutral beam injection is realized.

The invention discloses a brain disease diagnosis model based on a multilevel causal intervention network, and relates to the field of brain function network analysis and medical auxiliary research. The method specifically comprises the following steps: a brain network pre-construction stage: performing data preprocessing, extracting an fMRI time sequence, and constructing input features required by a model by using tangent Pearson embedding; feature extraction of a brain network is realized by using a three-layer Transform network of a self-attention mechanism; fusing multiple layers of attention by using an HCI module and correspondingly dividing brain network features into causal and non-causal parts; applying DCI to apply a first-order causal constraint to the model to reduce interference of non-causal factors, introducing ICAC into a causal part, and applying a second-order causal constraint to the model to further optimize the model; and realizing classification of brain diseases by using an orthogonal clustering (OCR) readout function. According to the method, non-causal interference factors can be effectively filtered, and high-order function connection information is extracted, so that the accuracy and robustness of brain disease analysis are improved.

The invention relates to the technical field of tail gas treatment, in particular to a cremation machine tail gas treatment device and method. The device comprises a cooling assembly, a low-temperature plasma assembly, a high-voltage electrostatic filtering assembly and an adsorption catalysis assembly which are communicated in sequence. Through multi-stage purification, the rich dust removal effect can be achieved, consumables only need to be replaced in the adsorption catalysis section, the adsorption catalysis section is located at the final position of the treatment link, only a small amount of residual pollutants can be treated, and the replacement period can be greatly prolonged. The method does not involve chemical agents, and does not cause chemical pollution to equipment and the surrounding environment.

The utility model discloses an emulsion system anti-scaling device, and particularly relates to the technical field of emulsion. The emulsion system anti-scaling device comprises a filter box, a partition plate is fixedly connected to the right end of an inner cavity of the filter box, a filter screen is fixedly installed at the middle end of the left side of the partition plate, and a blow-down valve is fixedly installed at the right end of the bottom of the filter box; a rotating shaft is movably connected to the middle end of the left side of an inner cavity of the filter box through a bearing, a spiral guide groove is formed in the left end of the rotating shaft, and a fixing sleeve is movably connected to the right end of the rotating shaft. Through the arrangement of the filter screen, dirt in emulsified liquid flowing through the interior of the filter box can be effectively filtered, the cleanliness of the recycled emulsified liquid is effectively improved, and through the arrangement of the hydraulic cylinder, the material pushing plate, the guide rod, the spiral guide groove, the rotating shaft, the fixing sleeve, the blow-down valve and the scraping plate, the cleanliness of the emulsified liquid is effectively improved. The effect of cleaning the surface of the filter screen is achieved, the filter screen is effectively prevented from being blocked, and it is guaranteed that filtering work can be stably carried out for a long time.

The invention relates to an intelligent inflation algorithm applied to an upper arm type upper-air sphygmomanometer, which comprises the following steps of: 1, after the sphygmomanometer enters a measurement state, acquiring and processing a pressure value signal by a central processing unit; 2, eliminating the interference of the pulse wave signal on the inflation slope through a filtering algorithm; 3, after the central processing unit obtains data from the pressure sensor, the increasing slope of the pressure value in the cuff is calculated at fixed time intervals; 4, after the slope is obtained through calculation, the slope is compared with a set target slope, and the inflation rate of the inflator pump is adjusted according to the slope difference degree. The low-pass filter is strong in denoising capability, can effectively filter high-frequency noise and a part with rapid data change, enables signals to be clear and reliable, and can reduce the influence and ensure the stability of inflation slope calculation due to the fact that pulse waves are coupled with noise signals generated by an inflation pump in the inflation process.

The invention discloses a CVE-ATTamp (Cascade Vector Enhanced ATTamp) for a network security scene. The invention discloses a CK association fusion RAG construction method, and relates to the technical field of network security. The method comprises the following steps: (1) carrying out structured analysis and vectorization on CVE vulnerability information data, extracting features and fusing CVSS scores to carry out semantic embedding; (2) ATTamp; semantic modeling of a CK threat matrix is carried out, and a threat semantic space containing tactical level information is constructed; (3) heterogeneous knowledge association and graph construction: calculating cross-domain semantic similarity and establishing logic mapping between vulnerabilities and tactics in combination with expert rules to form a heterogeneous knowledge graph; and (4) attack logic-oriented RAG retrieval and generation: retrieving a key attack path sub-graph based on a hybrid scoring mechanism, and driving a large model to generate a security analysis report with logic depth. According to the method, attack logic is stored through mapping, so that the problems that the traditional RAG lacks inference ability and security data fragmentation are solved, and the accuracy and tactical value of automatic threat analysis are remarkably improved.

The invention provides a power system anomaly detection method and system, and the method comprises the steps: carrying out the prediction of a photovoltaic panel assembly based on real-time environment parameters collected in real time and a constructed power prediction model, and obtaining theoretical power generation power data; comparing the obtained real-time power generation power data of the photovoltaic panel assembly with the theoretical power generation power data to obtain a comparison result, and determining an abnormal photovoltaic panel assembly; and performing analysis based on the image data of the abnormal photovoltaic panel assembly acquired in real time to obtain an abnormal result. According to the method, by comparing the real-time power generation power and the theoretical power generation power of the photovoltaic panel assembly, the photovoltaic panel assembly with the abnormal power generation efficiency can be rapidly identified, potential problems can be directly, effectively and timely found, energy waste and potential safety hazards caused by reduction of the power generation efficiency are avoided, and the power generation efficiency of the photovoltaic panel assembly is improved. By acquiring and analyzing the image data of the photovoltaic panel assembly in real time, the actual condition of the photovoltaic panel can be known more visually, and the accuracy of anomaly detection is improved.

The invention discloses a scene perception information fusion decision-making method for industrial field multi-source heterogeneous data, which comprises an edge layer, a cloud layer and an interaction layer which form a three-level collaborative architecture, and belongs to the technical field of industrial field data processing. The method comprises the specific steps that S1, an edge layer collects industrial field multi-source heterogeneous original data and carries out self-adaptive preprocessing to obtain cleaned multi-source feature data; s2, the edge layer processes the multi-source feature data through a lightweight scene perception model, and outputs a preliminary scene judgment result; s3, the cloud layer constructs and updates a causal relationship graph based on industrial business knowledge and incremental data of the edge layer, processes data uploaded by the edge layer through a causal reasoning fusion model, outputs a decision result and issues the decision result through the interaction layer; and S4, the cloud layer optimizes parameters of the causal reasoning fusion model and the lightweight scene perception model based on a decision execution result fed back by the edge layer, and issues the optimized parameters to the edge layer through the interaction layer to realize dynamic iteration.

The utility model discloses an air-cooled water chiller with an impurity removal mechanism, which comprises an air-cooled mechanism and a condenser arranged in the air-cooled mechanism, a water-cooled mechanism is arranged at the bottom of the air-cooled mechanism, a water pump is arranged on one side in the water-cooled mechanism, the air-cooled mechanism comprises an air-cooled box, and the air-cooled box is provided with an air inlet and an air outlet. Connecting hinges are symmetrically installed on the two sides of the top of the water spraying air cooling box, the tops of the two connecting hinges are rotationally connected with an access cover, a motor cover is fixedly installed at the bottom of the air cooling box, an unfolding motor is fixedly installed on one side of the interior of the motor cover, and the output end of the unfolding motor is fixedly connected with a chain wheel transmission assembly. Lifting threaded rods are symmetrically installed on the top of the chain wheel transmission assembly, rapid cooling of cooling fins is achieved through a cooling fan, meanwhile, the cooling fins can take away heat of a condenser, the cooling effect of the water cooler is achieved, and dust and impurities in air can be effectively filtered out by arranging a dustproof net.

The utility model discloses a Bluetooth wireless communication circuit of a PCR instrument, which comprises a first chip U1 and a second chip U2, the first chip U1 is an MCU chip, a 29th pin of the first chip U1 is connected with one end of a first resistor R1, the other end of the first resistor R1 is connected with a second pin of the second chip U2, a 32th pin of the first chip U1 is connected with one end of a second resistor R2, the other end of the second resistor R2 is connected with the other end of the first resistor R1, and the other end of the second resistor R2 is connected with the other end of the second resistor U2. The other end of the second resistor R2 is connected with a third pin of the second chip U2; the sixth pin of the first chip U1 is a power supply positive electrode input pin, the typical input voltage is 3.3 V, the first chip U1 is connected with a VDD, and the VDD power supply voltage is 3.3 V; a seventh pin of the first chip U1 is a power supply negative electrode input pin and is connected with a power supply reference point GND; according to the scheme, the Bluetooth communication circuit for the PCR instrument is simple in circuit and occupies less hardware resources; the communication mode of an existing instrument is simplified, and the PCR instrument can conduct wireless information exchange with related external equipment such as a mobile phone, a PAD and a notebook computer.

The high-precision NDIR gas sensor comprises a gas detector, a signal processing circuit, a microprocessor with an analog-to-digital converter (ADC), a light source driving circuit, a power conversion circuit, a communication module and circuit, a screen driving circuit and a display. The signal processing circuit carries out preliminary amplification and analog filtering on output signals of the detector through an instrument amplifier, a band-pass filter and isolation, noise can be effectively removed, and the characteristics of target signals can be enhanced. A microprocessor with an analog-to-digital converter (ADC) collects signals and achieves digital filtering through FFT conversion, the signal quality is further optimized, and finally the detected gas concentration value is displayed on a display screen in real time. The system can realize high-efficiency signal processing on the premise of ensuring real-time performance, has the advantages of simple structure, easy realization, low cost and the like, and is suitable for various signal processing scenes including but not limited to the fields of industrial automation, sensor data processing, medical signal analysis and the like.

The invention relates to a vehicle owner-oriented credit score prediction method, system and device and a storage medium, and the method comprises the steps: obtaining multi-dimensional user score data, and employing an automatic feature extraction algorithm to extract multi-dimensional key features from the multi-dimensional user score data according to the correlation between user behaviors and credit risks; inputting the multi-dimensional key features into a credit score prediction model to obtain a user credit score; and performing user credit risk layering according to the user credit score, capturing a change condition of the user credit score, dynamically adjusting a layering strategy according to the change condition, and generating a personalized financial service strategy for users of different levels. The credit scoring method has the effect of improving the credit scoring accuracy.

The utility model provides a novel debris flow blocking structure, which belongs to the technical field of disaster prevention and control and comprises a retaining wall body, an upper debris flow blocking device is arranged at the top of the retaining wall body and comprises a plurality of net rods, and a protective net is fixedly arranged on the net rods. When a large amount of debris flow moves at a high speed, large-particle-size broken stones and tree trunks wrapped along the way mainly move on the upper portion of the debris flow, and the debris flow upper portion blocking device in the blocking structure can effectively block and protect the debris flow. The phenomenon that debris flow climbs over and is blocked in the high potential energy and high speed state is avoided, the multiple drainage holes in the lower portion can effectively filter silt and water in the debris flow, the further erosion-coercing-amplification effect of the debris flow is reduced, and therefore the debris flow disaster volume is reduced, and the disaster-causing range is narrowed.

The utility model discloses a material metering device for production of riptacaine cream, which comprises an outer shell, a weighing mechanism, a material metering bin, a feed pipe, a feed valve, a discharge pipe, a discharge valve and an extrusion discharge mechanism, a cavity is arranged in the outer shell, and the weighing mechanism is mounted in the cavity of the outer shell; the material measuring bin is arranged on the weighing mechanism, and a feeding port is formed in the position, located in the cavity of the outer shell, above the material measuring bin. The feeding pipe is mounted on the outer shell, and the feeding pipe extends to the position above the material measuring bin; the feeding valve is mounted on the feeding pipe, and the feeding valve is suitable for controlling feeding of the feeding pipe; the discharging pipe is mounted at the bottom of the material measuring bin, and the discharging pipe is communicated with the material measuring bin; and the discharge valve is mounted on the discharge pipe. The riptacaine cream weighing device can meter and weigh riptacaine cream in a clean environment.

The invention relates to the technical field of building roof greening, and discloses a building roof greening and rainwater recycling irrigation system which comprises a microcontroller, a greening module arranged on a building roof, a rainwater recycling module connected with the greening module and an irrigation module. The microcontroller is electrically connected with the greening module, the rainwater recycling module and the irrigation module; the greening module sequentially comprises a water collecting layer, a filtering layer, a protective layer, a pervious concrete layer, a nutrient soil layer and a vegetation layer from bottom to top. The rainwater recycling module comprises a water pumping pipe arranged at the top of the side wall of the water collecting layer and a rainwater recycling box connected with the water pumping pipe; the rainwater recycling box comprises a first filter box, a second filter box, a disinfection box and a clear water box which are sequentially arranged from top to bottom; the irrigation module comprises a first water suction pump connected with the clear water tank, a water outlet pipe connected with the first water suction pump, a water conveying pipe connected with the water outlet pipe, a drip irrigation pipe connected with the water conveying pipe and a water dropper. By means of the system, maximum utilization of rainwater resources and continuous improvement of the ecological environment are achieved.