367results about How to "Realize acquisition" patented technology

The invention relates to the technical field of geological disaster intelligent monitoring, in particular to a geological disaster intelligent monitoring system and method based on multiple sensors. The method comprises the following steps: covering a monitoring area through multiple sensors, and collecting and summarizing environment data; separating effective signals and noise by adopting a space-time adaptive decomposition method, completing data denoising by combining a signal-to-noise ratio dynamic threshold and a local weighted regression smoothing trend residual error, then aligning time and dimensions through linear interpolation and standardization, and integrating multi-sensor data based on an adaptive weighted fusion method; the fused data is subjected to generation and review of a to-be-reviewed mark, so that the data integrity is ensured; key features are extracted, a mixed model based on LSTM and a random forest is constructed to evaluate disaster risks, and a risk grade division rule is set; and finally, outputting fusion data and an analysis result, and generating an early warning signal and a decision suggestion for potential geological disasters. According to the invention, accurate monitoring and risk assessment of geological environment changes are realized.

The invention relates to the technical field of machine learning, in particular to a supervised time sequence water level data generation method and system and a storage medium. The method comprises the following steps: acquiring multi-source hydrological monitoring data; performing abnormal value identification and data preprocessing according to the hydrological monitoring data to generate standardized hydrological basic data; constructing a data generation model of the conditional generative adversarial network based on the standardized hydrological basic data; hydrological variable driven condition feature regulation and control are carried out on the data generation model, parameter optimization of the generation network is carried out, and hydrological adaptability enhanced condition input feature data are generated; and injecting the condition input characteristic data into the data generation model to generate initial water level time sequence data. According to the method, the rare extreme hydrological events are oversampled by using a hierarchical importance sampling and self-service method (Bootstrap), so that the performance of the generative model in rare event prediction is remarkably enhanced.

The invention belongs to the field of hollowing detection, and provides an outer wall hollowing detection method and system, and the method comprises the steps: carrying out the multi-mode detection of an outer wall, and obtaining an infrared thermal imaging image and an ultrasonic detection signal; performing image enhancement processing on the infrared thermal imaging image; respectively carrying out feature extraction on the infrared thermal imaging image and the ultrasonic echo image by using a convolutional neural network; extracting and fusing high-dimensional feature vectors, and aligning an infrared thermal imaging image with an ultrasonic echo image through an image registration algorithm and a spatial transformation model; and classifying the fused feature vectors through a multi-layer sensor according to the data aligned in the step, and outputting the specific position, size and severity of the hollowing area. According to the scheme, the outer wall hollowing detection can be efficiently carried out.

The invention relates to the technical field of agricultural management, in particular to a corn cultivation environment monitoring system based on a sensor, which comprises a data acquisition module, a data processing module, a corn growth model module, an environment dynamic monitoring and early warning module, a decision support module and a visualization module, and a geographic information system and a dynamic monitoring model are combined to capture the dynamic change trend of the cultivation area environment factors. A corn growth model of a deep neural network and a long-short-term memory network is adopted to predict the growth state and resource requirements of corn, a decision support module intelligently generates cultivation management suggestions based on a model prediction result, and a visualization module displays environment data, prediction results and management suggestions through a multi-dimensional graph and an interactive interface. According to the method, the accuracy of corn cultivation management and the resource utilization efficiency are improved, and technical support is provided for intelligent agricultural development.

The invention discloses an energy storage power station state evaluation method and system based on real-time demand analysis, and relates to the technical field of power station state evaluation, and the method comprises the steps: obtaining the real-time operation data of an energy storage power station; the real-time operation data comprises voltage data, current data, temperature data and power data; based on the real-time operation data, establishing an energy storage power station real-time evaluation index system under the demand of a power grid system; and based on the energy storage power station real-time evaluation index system, establishing an energy storage power station performance comprehensive evaluation model, and performing energy storage power station state evaluation according to the energy storage power station performance comprehensive evaluation model. According to the method, operation data are acquired from multiple dimensions of a PCS converter, a battery body and a PCC point, a systematic evaluation index system of four requirements of power grid frequency modulation, peak regulation, voltage regulation and power oscillation suppression is combined, and an evaluation method of combining dynamic fuzzy comprehensive evaluation and adaptive weight dynamic adjustment is adopted; and comprehensive and accurate evaluation of the state of the energy storage power station is realized.

The invention discloses an intelligent auxiliary fracture monitoring system for orthopedic nursing, which comprises the following steps that: the system acquires mechanical parameters, movement track data and biological signals of a fracture patient through a multi-mode sensor, and intelligently analyzes the data by using a deep learning algorithm; generating a fracture state diagnosis result and recovery trend prediction data; the low-power-consumption wireless communication module realizes real-time transmission of diagnosis data and supports remote system parameter adjustment; the personalized nursing scheme generation module generates a rehabilitation plan, a load adjustment strategy and an auxiliary device configuration scheme through an optimization algorithm based on the patient biomechanical model and the diagnosis result; and the adaptive feedback adjustment module dynamically adjusts a data acquisition strategy and processing parameters to ensure the real-time response capability of the system to the state of the patient. The system is suitable for the technical field of intelligent auxiliary monitoring, and can realize real-time monitoring, intelligent diagnosis and personalized rehabilitation guidance of fracture patients.

The invention discloses a drug traceability code acquisition method, system and device based on image recognition, and a medium. The method comprises the steps of obtaining a drug package image; preprocessing the medicine packaging image, and performing edge detection, region segmentation, image correction and barcode analysis on the preprocessed medicine packaging image to obtain medicine traceability code information; obtaining prescription data, and checking the drug traceability code information according to the prescription data; and when the drug traceability code information is checked to be correct, carrying out associative storage on the drug traceability code information and the prescription data. According to the invention, drug traceability code information can be rapidly and accurately identified, and environments such as complex backgrounds, illumination changes, traceability code deformation and the like can be adapted; meanwhile, multiple drug traceability codes can be collected, the purpose of batch collection is achieved, supervision of a drug dispensing end is achieved, medication safety of patients is ensured, drug management can be perfected, and subsequent drug traceability is facilitated.

The invention discloses a method for collecting orchard ecological environment information, and the method comprises the steps: collecting soil parameters, space environment parameters, insect pest parameters and fruit parameters of an orchard in real time through deploying a plurality of collection devices, and carrying out the collection to form an orchard ecological basic data set; a backstepping model is constructed to indirectly calculate key ecological parameters including soil nutrients, fruit quality and insect pest diffusion trend, and an optimization result is corrected through experimental verification and the model; comparing a backstepping result with an orchard target value to analyze a deviation source, and establishing a macroscopic cause chain through data matching and a visual tool; according to the deviation analysis and the cause chain result, determining an executable regulation and control measure matched with the regulation and control direction; and monitoring the effect after the implementation of the regulation and control measures, verifying the regulation and control effect by comparing the data before and after the implementation of the regulation and control measures, and applying feedback data to iterative optimization of the backstepping model. The method is scientific and efficient and can be used for improving orchard production benefits and ecological environment quality.

The invention discloses an enterprise supply chain side evaluation method and system based on big data, and provides an innovative solution for the problems of low data processing efficiency, weak analysis and prediction ability, insufficient causal relationship analysis, decision support lag and the like in supply chain management. The method comprises the steps of integrating and processing real-time data, deeply analyzing the data by using an advanced analysis and prediction module in combination with a mathematical model and a machine learning algorithm, deeply understanding a causal relationship in a supply chain through a causal relationship analysis and optimization module, and finally accelerating a decision process through a visualization and decision support module. According to the system, through modular design and an advanced algorithm, the supply chain management efficiency and scientificity are remarkably improved, and comprehensive evaluation and optimization of the supply chain are achieved. The invention aims to solve the problem of improving the efficiency, accuracy and scientificity of enterprise supply chain management under the background of big data so as to adapt to rapidly changing market demands and a complex supply chain network.

The invention discloses a single-excitation dual-output multi-parameter measurement eddy current sensor, which is characterized in that after the eddy current sensor is arranged on the surface of a tested piece, a sine excitation signal with certain frequency and power is introduced into an excitation coil, and a magnetic field generated by the excitation coil generates eddy current on the surface of the tested piece; in the actual detection process, the lift-off value of the eddy current sensor and the surface of the tested piece is changed due to mechanical vibration or random working conditions, impedance in the excitation coil is changed, and then the current value of a loop where the excitation coil and the capacitor are located is changed. The impedance change caused by lift-off can be represented by acquiring the voltage values at the two ends of the capacitor; the differential receiving coil receives a combined magnetic field of a primary magnetic field and an eddy current field under the combined action of the primary magnetic field and the eddy current field, and has a lift-off suppression effect to a certain extent, and the balance of the receiving coil is broken only when a defect is encountered, so that the defect is detected and represented by measuring a voltage signal of the receiving coil.

The invention discloses a cardiovascular disease intelligent diagnosis and treatment auxiliary system which comprises a hospital server terminal, a cardiovascular disease intelligent diagnosis and treatment cloud platform, a doctor mobile terminal, a medical care mobile terminal and a patient mobile terminal. The hospital server terminal is used for compiling a clinical patient medical record created and uploaded by a doctor and data uploaded by medical care for clinical examination of a patient, and creating a medical record model of the patient, and the hospital server terminal uploads the created medical record model to the cardiovascular disease intelligent diagnosis and treatment cloud platform for cardiovascular case big data collection; according to the intelligent diagnosis and treatment auxiliary system for the cardiovascular disease, in the intelligent diagnosis and treatment process, a medical record model of a patient can be analyzed, healing duration data of cardiovascular diseases of the same type in a patient healing and disease death record storage unit are retrieved and called, and the healing duration of the patient is calculated and predicted through big data; and the disease death duration data of the same type of cardiovascular diseases in the patient healing disease death record storage unit are retrieved and called, and the survival rate of the patient is calculated and predicted through big data.

The invention discloses a combined purification monitoring method and a combined purification monitoring system for food-grade carbon dioxide, and relates to the technical field of purification monitoring, and the combined purification monitoring method comprises the following steps: carrying out purification analysis on a purification process, carrying out sequential decomposition on purification steps, and establishing step association of the purification steps; configuring an integrated monitoring platform, and configuring a monitoring sensor on each purification step; step monitoring of the purification process is executed, and a real-time feedback data stream is established and returned to the integrated monitoring platform; carrying out independent verification analysis on the returned data based on an independent verification network, and establishing a purification early warning result; performing combined purification fitting analysis on the step purification early warning result and the step association, and establishing a pre-analysis result; and completing joint purification monitoring according to a pre-analysis result and a step purification early warning result. The technical problems of insufficient real-time monitoring and weak early warning capability in the prior art are solved, and the technical effects of dynamic monitoring and abnormal early warning of the food-grade carbon dioxide purification process are realized.

The invention provides a robot environment sensing data processing method, system and device and a medium. According to the method, environment sensing data are obtained through all sensors in an environment sensing sensor cluster, then the collected environment sensing data are integrated into an environment sensing data set and sent to a processor, and the processor generates a robot operation data matrix according to the received environment sensing data set; according to the robot operation data matrix, the processor determines an environment sensing result according to the robot operation data matrix, multi-sensor data collection and spatial position correction are achieved, the problem of multi-source heterogeneous data fusion is solved, and after the robot operation data matrix is generated, the environment sensing result is obtained. And environment features can be efficiently extracted, an environment sensing result can be determined, the sensing precision and real-time performance of the robot on a complex environment are remarkably improved, and a reliable data basis is provided for subsequent navigation, obstacle avoidance and other tasks.

The invention discloses an intelligent inspection method and device for power equipment based on two-way communication, and the method comprises the steps: carrying out the coding of the to-be-inspected power equipment, collecting the operation and maintenance data flow of the power equipment, and obtaining an equipment identification code database through data association mapping and packaging; based on an electromagnetic receiving system, an electromagnetic transmitting system and an optical ranging system, performing dual ranging verification to obtain distance information of the target power equipment; information decoding is carried out on the received electromagnetic carrier waves, a target equipment identification code is obtained, distance information of associated target power equipment is positioned, and the target power equipment and a target operation maintenance data stream are determined; and executing the preset inspection task through the unmanned aerial vehicle equipment, and determining the inspection information of the target power equipment. The technical problem that an existing unmanned aerial vehicle inspection technology is prone to being interfered by complex terrains, and inspection marking errors are caused is solved, and the inspection accuracy and inspection efficiency of the power equipment are improved.

The invention relates to the technical field of mechanical part testing, in particular to a crane jib mechanical part vibration testing device which comprises a vibration platform fixedly arranged at the bottom, the top of the vibration platform is used for installing a cantilever crane, a fixing table is arranged on the left side of the vibration platform, and a fixing steel frame is arranged on the top of the fixing table. The device comprises a fixed steel frame, an overhanging displacement mechanism is installed on the fixed steel frame, the left end of the overhanging displacement mechanism is connected with external matched telescopic equipment, a lifting position control device is installed at the right end of the overhanging displacement mechanism, and position control testing devices are installed on the front side and the rear side of the lifting position control device respectively. The device can be installed in a workshop to test the vibration state of the cantilever crane under different vibration simulation working conditions and obtain the vibration frequency and amplitude, effectively monitors whether different vibration point positions of the current cantilever crane exceed a safety threshold value or not, timely uploads the conditions and then gives an alarm.

The invention provides a strapdown inertial navigation system-level calibration method based on a temperature-control double-shaft position turntable, and overcomes the defects of high workload, easiness in making mistakes, high cost, waste of equipment and manpower and the like in the conventional calibration method. The invention provides temperature and position calibration based on a temperature control double-shaft position rotary table, the transposition limitation of the double-shaft rotary table is overcome, a rotating position and a rotating scheme are designed in a targeted manner, and meanwhile, automatic position calibration of a gyroscope and an accelerometer of a product is realized through automatic transposition of the rotary table. The method can control the temperature of the rotary table incubator, automatically identify the corresponding temperature point of the product, capture the error parameter of the product at the corresponding temperature point, and automatically solve the compensation values of the zero positions of the gyroscope and the accelerometer along with the initial temperature change.

The invention relates to the technical field of man-machine interaction, and discloses a wearable multi-channel physiological parameter acquisition system which comprises wearable physiological parameter acquisition equipment and preprocessing software. The technical problems that most of existing physiological state collecting devices are used in a laboratory environment, the use preparation time is long, wearing is inconvenient, and the working requirement in the actual high-speed cabin environment cannot be met are solved, collecting of physiological data of a driver in the high-speed flight or ground driving environment is achieved, and the working efficiency is improved. And data input is provided for evaluating the fatigue state and the cognitive state of the driver in real time.

The invention belongs to the technical field of oil and gas well drilling, and particularly relates to an experimental device and method for simulating the overflow and leakage co-storage well killing process of a fractured-vuggy stratum. The device comprises a simulation wellbore system, a simulation drilling fluid circulation system, a simulation fracture-vug type stratum structure system, a simulation gas injection system, a data acquisition system and a data processing system. The wellbore simulation system is used for simulating a drill stem and a wellbore in an experiment; the simulated drilling fluid circulating system is connected with the upper part of the shaft system and is used for simulating injection and return of drilling fluid; the simulated fracture-vug type stratum structure system is connected with the lower part of the shaft system and is used for simulating cracks and karst caves in an experiment; the simulated gas injection system is used for injecting gas into the fracture-cavity type stratum structure system; and the data acquisition system and the data processing system are used for acquiring and processing experimental data in the experimental device. The experimental device and method provided by the invention aim at solving the problem that in the prior art, the overflow and leakage coexistence well killing process of a fracture-vug type stratum cannot be comprehensively simulated.

The invention discloses a parameter optimization control system and method based on visual inspection equipment of a ZB45 packaging machine, and the whole control system employs an industrial control computer, builds a local area network cloud server, collects the related detection data and operation parameters of each visual inspection device, carries out the deep learning and twinborn detection of the collected data, and achieves the optimal control of the parameters of the visual inspection equipment. Aiming at the defects of information isolated island, time consumption in adjustment and optimization, poor precision and the like existing in a traditional visual detection solution, intelligent development is carried out, and a unified monitoring platform and a parameter adjustment and optimization intelligent analysis system of each visual detector are established. After the method is implemented, the parameter tuning duration of each visual inspection device can be reduced, and the effective operation rate of the device is improved; according to the method, the defect detection precision is improved, missed detection and false detection of defective cigarettes are reduced, the functions of state monitoring, parameter optimization, self-tuning adjustment, remote control and the like of each detection device are realized, and a foundation is laid for intelligent construction in the field of cigarette detection devices.

The invention relates to the field of farmland geographical contour measurement, in particular to a high-precision farmland geographical information acquisition device which comprises a mounting plate and a distance measuring wheel arranged on the mounting plate, a mounting frame is connected to the mounting plate, and a scanner used for acquiring and processing farmland geographical contour information is mounted through the mounting frame; according to the invention, the distance measuring wheel, the mounting plate, the mounting rack and the scanner are driven to move, the scanner is started to collect, store and record the geographical contour information of the farmland on the moving path while moving, and then the number of rotation turns of the distance measuring wheel is counted by the counter in the moving process. The contour length of the farmland on the moving path of the distance measuring wheel can be obtained through the numbers on the counter and the fixed perimeter of the distance measuring wheel, and the effect of diversified collection of farmland geographic contour information is achieved, so that more detailed and accurate geographic information is provided for workers, and subsequent land planning and management are facilitated.

The utility model discloses an intelligent temperature, humidity and pressure sensor, which is characterized by comprising a shell structure, a connector, a protective cover, an analog board, a main board, a probe board, a pressure sensitive element and an upper cover structure, the analog board, the main board and the pressure sensitive element are accommodated in the shell structure, and the probe board extends out of one end of the shell structure, is in contact with the environment and is used for measuring environment temperature and humidity information; the main board is used for data acquisition and communication control, and the analog board is used for power conversion and analog current driving; the hollow part of the upper cover structure accommodates the connector, and the connector is protected on the opposite side through the protective cover; the pressure sensitive element is used for measuring environment pressure information; the pressure sensitive element and the probe plate output digital signals. Three laser welding connecting parts are arranged at the joint of the shell structure, between the upper cover structure and the shell structure and between the connector and the upper cover structure; and the interior of the shell structure is completely isolated from the external environment through a potting method.

The invention discloses a financial reconciliation system reconciliation risk identification control method and system, a medium and equipment. The method comprises the following steps: a payer acquisition step: acquiring a transaction bill of a payment channel; a transaction party acquisition step: acquiring a transaction bill of a business party; an account checking platform acquisition step: acquiring an account checking result generated by the financial account checking platform; a risk identification control step: checking the transaction bill of the payment channel, the transaction bill of the business party and an account checking result generated by the account checking platform, modifying error data, and sending a processing result to an abnormal data processing module; an abnormal data processing step: receiving an error data modification structure, and manually modifying the unmodified data; and an abnormal data display step: analyzing, counting and displaying the reconciliation data subjected to error data processing. According to the method, the collection and automatic reconciliation of the transaction bill can be realized, and the abnormal data generated after reconciliation can be cleaned and corrected.

The invention discloses an intelligent wave recording and traveling wave ranging integrated design method and system, relates to the technical field of power systems, and comprises heterogeneous data fusion processing including hardware isolation and independent acquisition, a clock synchronization mechanism, data caching and alignment, data format standardization, algorithm optimization and fusion, and data verification and correction. Large-capacity and multi-backup mixed storage is achieved, and combination of multiple storage media, data redundancy backup and improvement of data reliability are included; starting based on multivariate information collection, wherein the starting comprises analog quantity starting, switching value starting, GOOSE message starting and station control layer message starting; the comprehensive distance measurement algorithm comprises establishment of an electromagnetic-circuit framework model, construction of a comprehensive distance measurement model, solving of an objective function through an optimization algorithm, correction of a preliminary fault point coordinate estimation value, realization of a power fault accurate positioning system and support of computer equipment and a storage medium. The problem of single recorded data is solved, and the data processing speed and the flexibility of the system are improved.

The invention discloses a pulse detection device and an automatic pulse taking method, and relates to the technical field of medical instruments.The pulse detection device comprises a pulse detection body used for being worn on the hand and further comprises a first fingerstall, a second fingerstall and a third fingerstall which are worn on the index finger, the middle finger and the ring finger of a doctor respectively, and the first fingerstall, the second fingerstall and the third fingerstall are connected; piezoresistive pressure sensors are arranged at finger pulps of the first fingerstall, the second fingerstall and the third fingerstall respectively, the pulse detection body further comprises a signal conditioning circuit arranged at the position of the hand back, the piezoresistive pressure sensors are electrically connected with the signal conditioning circuit, and the signal conditioning circuit is used for detecting a first state when the first state is detected. And the processor is used for converting from the standby mode to the working mode, receiving a signal of the piezoresistive pressure sensor, processing the signal and sending the processed signal to the upper computer, and is also used for converting from the working mode to the standby mode when a second state is detected. The pulse condition data and the floating, middle and sinking pressure can be automatically collected when a doctor takes the pulse, the doctor does not need to control, the complete information such as the pulse diagnosis state, the floating, middle and sinking pressure and the cun-guan-chi pulse condition can be detected, and fusion of manual pulse taking and sensor pulse taking is achieved.

The invention relates to the technical field of measuring electrical variables, and specifically discloses a reliability detection method and system for an intelligent grounding wire based on Lora communication, including evaluating the Lora communication between a host end of an intelligent grounding wire and a slave end, judging whether the Lora communication status between the host end and the slave end of the intelligent grounding wire is reliable, evaluating a grounding terminal of an intelligent grounding wire whose Lora communication status between the host end and the slave end is reliable, judging whether the grounding terminal status of the intelligent grounding wire is reliable, and evaluating the working and hanging detection status of a connection terminal of an intelligent grounding wire whose grounding terminal status is reliable, judging whether the status of the intelligent grounding wire is reliable. The invention solves the problem that a traditional detection method relies on a low-precision sensor and that data analysis and processing technology are insufficient, helps to improve the stability and reliability of the entire system, reduce safety hazards caused by communication failures, promptly discover and locate potential failures, ensure that problems are identified and resolved as early as possible, and maintain the normal operation of a grounding system.

The present invention provides a detection method and device for the placement state of wafers in a wafer box, which is applied to the detection of wafer boxes. The detection method includes: obtaining the standard value of the thickness and the standard value of the angle of the wafer; using a laser and a camera to scan the wafer box to obtain the three-dimensional morphology of the wafer box; according to the three-dimensional morphology, using a thickness calculation algorithm and an angle calculation algorithm to calculate the thickness and angle of each wafer in the wafer box; wherein the thickness calculation algorithm processes the data of the three-dimensional morphology through a point cloud downsampling method and a point cloud clustering method; comparing the thickness and angle of each wafer in the wafer box with the standard value of the thickness and the standard value of the angle to determine whether there are duplicate wafers, oblique wafers, and missing wafers in the wafer box. The present invention solves the technical problem that the traditional Mapping operation needs to use a ranging sensor to scan the inside of the wafer box point by point to determine the wafer position, resulting in a long scanning time and affecting production efficiency.

The invention provides an aluminum processing deep well casting production line AI video violation snapshot monitoring method, which is characterized in that an intelligent safety production early warning model is constructed based on a computer vision deep learning technology, embedded equipment is used as a data acquisition terminal, and the action of the data acquisition terminal is associated with the operation of a console of an aluminum processing deep well casting production line. When the console starts to execute a dangerous process, the data acquisition terminal is triggered, the data acquisition terminal carries out continuous data acquisition on a monitoring picture of the front-end monitoring equipment and sends the acquired data to the AI monitoring video server at the rear end, and an AI system of the AI monitoring video server carries out data analysis through an intelligent safety production early warning model. AI identification is carried out by an AI analysis module, and alarm response is carried out according to an analysis result; according to the invention, the operation behavior of the casting production field operation personnel can be monitored in real time, the unsafe behavior of the personnel is judged through AI visual analysis, an early warning is given to remind the personnel to correct the unsafe behavior, and the occurrence of safety accidents is avoided.

The invention discloses an electric vehicle charging intelligent management system based on multi-source data analysis, and relates to the technical field of electric vehicle charging, and the electric vehicle charging intelligent management system is characterized in that information is extracted from multi-source data including historical charging data HC, driving behavior data Db, geographic position information GP and seasonal factors TS, and a PCA feature extraction technology is used to extract the multi-source data including historical charging data HC, driving behavior data Db, geographic position information GP and seasonal factors TS; the system can generate more personalized and accurate charging schemes according to actual conditions and preferences of different users. The system can dynamically adjust the charging time, the charging amount and the place according to the specific charging habit, the driving route and the seasonal factor of the user, so that the charging experience is more intelligent, and the charging time T, the charging amount Q and the charging station selection D of the historical charging data HC are subjected to feature extraction through the PCA technology. The system converts high-dimensional data into multi-dimensional features Z and generates a feature matrix HZ, so that the redundancy of the data is reduced, key features are reserved, and the efficiency of data analysis is greatly improved.

The invention discloses a numerical control system macro variable-based on-machine measurement data edge-end interactive calculation method, which comprises a numerical control system and an edge calculation controller, the numerical control system and the edge calculation controller carry out interoperation through a plurality of interactive protocols, and the interoperation comprises on-machine measurement data acquisition, processing and storage. The data interaction protocol of the numerical control system and the edge calculation controller comprises a heartbeat control bit, an input information storage bit, a calculation function flag bit, a circulation flag bit, a machine tool time recording bit, an operation time recording bit, a calculation result display bit and a return value flag bit. The flag bits of the interaction protocol respectively correspond to single numerical control system macro variable address numbers; on-machine measurement data edge-end accurate real-time interaction is achieved based on the numerical control system macro variables, the calculation efficiency is high, the occupied storage space and variable addresses of the numerical control system are small, and certain universality and flexibility are achieved.

The utility model discloses a battery signal acquisition device and an energy storage system, the battery signal acquisition device comprises a plurality of battery packs, the battery signal acquisition device comprises a BIC acquisition board, and the BIC acquisition board is electrically connected with a battery management system and one of the battery packs so as to be used for acquiring a battery signal of one of the battery packs; a battery signal of one battery pack is sent to the battery management system; and at least one FPC circuit board, each FPC circuit board is connected with other battery packs except one battery pack in the battery in a one-to-one correspondence manner, each FPC circuit board is electrically connected with the BIC acquisition board so as to be used for acquiring battery signals of other battery packs, and the BIC acquisition board forwards the battery signals of other battery packs. By adopting the battery signal acquisition device, the acquisition of battery signals of a plurality of battery packs can be realized, the cost of the battery signal acquisition device is lower, the assembly efficiency is higher, and the FPC circuit board is not easy to lose.