882results about "Thermometers using value differences" patented technology

A method and apparatus for measuring optical turbulence using an unmanned aerial vehicle are provided. The unmanned aerial vehicle may include a central body, at least one motor operatively connected to the central body, a mounting element, a three-dimensional anemometer mounted on the mounting element, a first differential temperature sensor mounted on the mounting element, a second differential temperature sensor mounted to the mounting element, and a base mounted to the central body via a payload mounting interface including a first barometric pressure sensor, a central processing board, memory operatively connected to the central processing board, and a processor configured to generate refractive-index structure coefficient information.

The invention discloses a temperature monitoring method for a photovoltaic grid-connected cabinet, and particularly relates to the technical field of photovoltaic grid-connected cabinets. The method comprises the following steps: arranging multiple types of temperature sensors in a grid-connected cabinet, collecting real-time temperature data, constructing a heat distribution model, comparing a current heat map with a historical steady-state heat field template, and identifying heat field offset and an atypical temperature rise trend; when the system detects that early warning is not triggered by an existing measuring point in a heat abnormal area, redundancy alarm logic is automatically started, temperature abnormal early warning is generated, and the speculated abnormal heat source position is recorded; according to the method, the sensing capability of the thermal anomaly in the blind area of the sensor is effectively improved, and the safety and the intelligent level of the system are enhanced.

The invention provides an indoor environment monitoring method and system integrating temperature and humidity, and is applied to the field of sensing data processing. According to the method, the reading difference of the temperature sensor is collected, whether local deviation exists or not is judged, the arrangement type of the sensor is combined, a low temperature value generated by the wall-leaning sensor due to the cold bridge effect is dynamically compensated, misjudgment of an environment system is avoided, and the human body temperature is introduced as a sensing reference by constructing a temperature difference deviation function. According to the method, comprehensive temperature indexes closer to real experience can be generated, when abnormal fluctuation is detected, the space structure and heat source information are further combined, boundary conditions are constructed, dynamic heat flow and temperature and humidity distribution diagrams are simulated, temperature sensing deviation is effectively and reversely corrected, the precision, stability and energy-saving performance of an environment adjusting system are remarkably improved, and the comfort degree of a human body is improved.

The present disclosure is of an atmospheric characterization system that has a central processing board that has a first and a second communication interface. Further, the atmospheric characterization system further has a first precision temperature sensor that is communicatively coupled to the central processing board via the first communication interface and positioned a distance from a first side of the processing board, wherein the precision temperature measures a first temperature and transfers data indicative of the first temperature to the central processing board. In addition, the atmospheric characterization system has a second precision temperature sensor that is communicatively coupled to the central processing board via the second communication interface and positioned the distance from a second opposing side of the processing board such that the first precision temperature sensor and the second precision temperature sensor are equidistance from the processing board and a distance between the first precision sensor and the second precision sensor is a predetermined distance, r, and the second precision temperature sensor measures a second temperature and transfers data indicative of the second temperature to the central processing board simultaneously with the transferring of the first temperature. Additionally, the atmospheric characterization system has a processor that receives the first temperature and the second temperature and calculates a value indicative of atmospheric turbulence based upon the first temperature and the second temperature, wherein the value indicative of the atmospheric turbulence is used for designing, modifying, calibrating, or correcting an optical system.

The invention relates to the technical field of medical cyclotrons, in particular to a medical cyclotron magnetic field intensity adjusting method based on temperature compensation, and the method comprises the following steps: in the process of adjusting the magnetic field intensity of a main magnet based on temperature information, obtaining a temperature variation threshold: collecting the temperature on the surface of the main magnet in real time; determining a temperature difference coefficient, a temperature anomalous coefficient, a temperature abnormal coefficient and a trend approximate value of each acquisition moment; comprehensively analyzing the temperature values acquired by all the sensors, and determining the temperature difference degree and difference factor of each sensor at each acquisition moment; determining the avoiding adjustment value of each sensor at each acquisition moment; and acquiring a temperature variation threshold value at each acquisition moment. The invention aims to solve the problem that the magnetic field intensity of the cyclotron cannot be adjusted according to the actual environment temperature, so that the beam stability and the beam extraction efficiency in the operation process of the medical cyclotron are improved.

The invention relates to the technical field of fault diagnosis, in particular to a big data-based bus duct fault diagnosis system, which comprises a data synchronization module, an anomaly identification module, an amplitude judgment module, a traceability positioning module and a risk classification module. According to the invention, automatic synchronization of multi-node data is realized through a time correlation mode, layered discrimination is carried out on an abnormal working condition state by means of continuous comparison of data streams, dynamic identification of node parameter fluctuation is realized through interval adjustment and trend aggregation, and abnormal signals are positioned and traced in a link topology. The node operation risk is comprehensively researched and judged in combination with historical and real-time parameters, linkage analysis and active classification of multi-dimensional information are formed, efficient connection of links such as monitoring, recognition, tracing and classification is promoted, operation and maintenance decision and data full-process response are supported, node difference judgment and risk prompt in a complex scene are facilitated, and the method is suitable for popularization and application. And intelligent operation and maintenance of power supply system data driving are improved.

The invention relates to a detection and analysis method and system for an energy storage system, and aims to improve the state monitoring precision, the fault early warning capability and the response intelligence level of the system. The method comprises the following steps: firstly, synchronously acquiring and transmitting multi-source data in real time through a sensor network deployed in a battery module, a power conversion unit and a cooling system; and then, key dynamic features are extracted from the multi-source data, and dynamic feature state information of the energy storage system is comprehensively formed. And inputting the state information into a pre-trained deep learning model, and outputting a health state score and a fault probability of the system. Based on the evaluation result and the fault traceability information, the system triggers a multi-level early warning mechanism and executes an active response strategy, and after response execution, the system re-evaluates the health state in a closed loop mode and verifies the response effect; and if the improvement does not reach the expectation, making a decision to start an artificial diagnosis protocol. According to the invention, a complete process from dynamic perception, intelligent diagnosis and accurate response to closed-loop verification is realized, and the safety and reliability of operation of the energy storage system are improved.

The invention relates to the technical field of fault detection, in particular to an intelligent photovoltaic junction box testing method and system, and the method specifically comprises the steps: constructing a voltage and current dissimilarity index based on the data changes of the current and voltage of an intelligent photovoltaic junction box at adjacent moments, and constructing an electrical parameter abnormal coefficient through combining the correlation between the voltage and the environment temperature; based on the correlation between the internal temperature of the photovoltaic junction box and the time sequence of other parameters, the fault confidence coefficient of the photovoltaic junction box is constructed in combination with the electrical parameter abnormal coefficient; according to the method and the device, the anomaly detection of the photovoltaic junction box is carried out based on the fault confidence coefficient, the influence of environmental factors on related data of the photovoltaic junction box is reduced, the problem that when temperature threshold detection is carried out in an existing photovoltaic junction box detection technology, threshold setting is unreasonable, and false detection is easily caused is solved, the detection precision of the photovoltaic junction box is improved, and false detection is avoided.

The invention discloses a solar street lamp illumination intensity self-adaptive adjusting method, and particularly relates to the technical field of solar street lamps. Calculating a discharge depth nonlinear index according to the nonlinear characteristics of a discharge rate decrease coefficient, an internal resistance increment coefficient and a temperature distribution difference coefficient, timely capturing the nonlinear characteristics of the voltage fluctuation of the battery along with the increase of the discharge depth, and evaluating the electric quantity condition of the storage battery and the nonlinear discharge fluctuation degree of the battery. Meanwhile, according to a light source attenuation coefficient, a metal corrosion coefficient and an insulating layer damage coefficient, a hidden danger evaluation index of the solar street lamp is calculated, the potential fault risk after the street lamp is used for a long time is recognized in time, the brightness is properly adjusted according to the hidden danger degree, and safe and stable operation of a street lamp system is ensured; and correcting the brightness curve according to the discharge depth nonlinear index and the solar street lamp hidden danger evaluation index, so that the system can adapt to the complex characteristics of battery discharge and the street lamp aging effect.

The invention relates to the technical field of equipment maintenance, in particular to a distribution box remote diagnosis and maintenance system which comprises a voltage deviation detection module, a node hot stacking identification module, a channel stability classification module, a contact aging trend evaluation module and a period adjustment trigger module. According to the method, peak value change of effective voltage in each channel period in the distribution box is collected and compared with a preset criterion so as to accurately identify an abnormal discharge unit and accurately position a potential risk channel, and the change rate of equivalent series capacitance, contact conductance and contact resistance of a node is continuously sampled in a non-power-on state so as to accurately identify the potential risk channel. According to the method, multi-parameter same-trend change characteristics are determined, the contact aging process is accurately evaluated by integrating the parameter trend, the node trend and the maintenance plan period remaining time are subjected to cross comparison, the maintenance task advance opportunity is automatically judged, the maintenance plan is actively adjusted, the node fault missing detection risk is effectively reduced, and the maintenance timeliness and accuracy are remarkably improved.

A power tool including a motor, an impulse assembly configured to be driven by the motor, a temperature sensor, and a controller. The temperature sensor is configured to output a signal related to a temperature of the power tool. The temperature of the power tool is correlated to a temperature of a fluid within the impulse assembly. The controller is connected to the temperature sensor. The controller is configured to determine the temperature of the power tool based the signal from the temperature sensor, and control, in response to the temperature of the power tool being greater than a temperature threshold, the power tool based on the temperature of the power tool.

The invention relates to the technical field of power electronic device diagnosis, and discloses a reverse conducting IGBT intelligent power module fault automatic diagnosis method and system. The method comprises the following steps: acquiring multi-source monitoring data including a grid voltage waveform, a collector current waveform and a shell temperature change curve when the power module operates; then establishing a dynamic feature extraction model, performing time domain and frequency domain conjoint analysis on the multi-source monitoring data, and generating a feature parameter set; then constructing a fault feature space, and mapping the feature parameter set to a high-dimensional space to form a feature vector distribution diagram; carrying out regional division on the feature vector distribution map by adopting a self-adaptive clustering algorithm, and identifying an abnormal feature aggregation region; and finally, comparing the abnormal feature gathering area with a preset fault feature library through a mode matching engine, and outputting a fault type identification result. According to the method, multi-source data can be integrated to realize dynamic feature extraction and adaptive fault identification, and the real-time performance and accuracy of fault diagnosis are improved.

The invention relates to the technical field of power modules, and discloses a power module detection method and system based on temperature measurement, and the method comprises the steps: obtaining the temperature data of an air inlet outside a power module, in a heat dissipation channel, other units outside the heat dissipation channel, and beside the air inlet, and calculating an air inlet temperature value, a channel temperature value, a unit temperature value, and an inlet temperature value; and calculating a curve matching value of the two thermal difference temperature value change curves according to the thermal difference temperature values, the first thermal difference temperature value and the second thermal difference temperature value, comparing the curve matching value with a preset reference matching value, and if the curve matching value is smaller than the preset reference matching value, performing early warning prompt. The temperature conditions of different positions of the power module are comprehensively considered, the detection deviation is reduced, the accuracy of temperature state detection is improved, the temperature abnormal change trend is captured, potential faults are found in advance, and reliable guarantee is provided for stable operation of the power module.

The invention discloses a fire positioning method based on heat source gradient identification, and belongs to the technical field of fire positioning, and the method specifically comprises the steps: obtaining a two-dimensional temperature distribution image of a fire scene; drawing an isotherm, and marking a potential fire source area based on a preset temperature threshold value; calculating the area of each potential fire source region, screening out an undetermined region from the potential fire source regions, calculating the temperature change rate of a central isotherm of the undetermined region in unit time, and screening out a candidate region from the undetermined region; marking a plurality of points on the peripheral isotherm of the candidate area at equal intervals, generating a temperature gradient path in the reverse direction of the temperature gradient based on each point, calculating the temperature gradient of each path, obtaining the candidate area with the temperature gradient mean value larger than a threshold value, and marking the candidate area as an initial fire source area; continuously drawing vertical lines into the central isotherm from a tangent line of the intersection point on the central isotherm, and marking the intersection point of the vertical lines as an initial fire source center point; according to the invention, rapid positioning of the initial fire source center in the fire scene is realized.

The invention provides a data co-processing method and system for a linear servo actuator. The method comprises the following steps: firstly, acquiring a multi-level temperature data set of a key heat source area in the linear servo actuator; performing dynamic coupling analysis processing on the multi-level temperature data set based on a thermal field prediction model to generate a temperature change trend prediction result; a dynamic heat dissipation strategy grade is matched according to the temperature change trend prediction result and real-time load current data, a heat dissipation execution control instruction is generated, and temperature feedback data in the heat dissipation process is monitored in real time; and based on a comparison result of the temperature feedback data and a preset temperature threshold, triggering a thermal failure protection mechanism to adjust the execution priority of the composite heat dissipation operation. According to the invention, power output can be reduced, external active heat dissipation control is triggered, equipment shutdown and other related instructions which are in effective contact with an abnormal working state can be triggered, so that the risk of equipment damage caused by abnormal operation of the actuator is effectively reduced, and the reliability and stability of the system are improved.

The invention discloses a temperature sensing and radio frequency identification circuit integrated temperature measurement method and system, which are applied to the technical field of temperature sensor data processing, and the method comprises the steps: obtaining the response time when each temperature sensing node collects the temperature according to a corresponding first preset sampling frequency, and the signal transmission delay time of a corresponding radio frequency identification chip; correcting response time by using a compensation matrix constructed according to the signal transmission delay time sequence to obtain an adjusted response time sequence, and respectively determining a sampling configuration scheme and reference task bearing capacity corresponding to the temperature sensing node according to the adjusted response time sequence and equipment parameters; and carrying out temperature acquisition, and carrying out interpolation reconstruction and optimization on the acquired temperature value to obtain optimized temperature data. According to the method, the response speed of the distributed temperature sensing system is adjusted, and the sampling strategy is adjusted in combination with the dynamic change of the distribution characteristics of the temperature field, so that the temperature monitoring precision is improved.

Cable termination anomaly detection method (200), comprising: placing at least a temperature sensor (2) near a cable termination (1) having a cooling / insulating fluid (7) so as to measure temperatures of a plurality of measuring points (S1-SE); measuring (201) by said temperature sensor (2) and at different measuring times a plurality of groups of temperature values (TGt1-TGtM). The method further comprises: acquiring the plurality of groups of temperature values (TGt1-TGtM) and constructing (203) an axial temperature distribution (ATD(zn)) expressing a one-to-one correspondence between estimated temperature values obtained from the plurality of groups of temperature values (TGt1-TGtM) and height values along a longitudinal axis (A1) of the cable termination.

The invention relates to the technical field of data processing, in particular to a bridge construction structure health state real-time monitoring system, which acquires temperature data including temperatures at a plurality of moments at different positions of a bridge construction structure in real time in the pouring process of the bridge construction structure, and calculates the health state of the bridge construction structure according to the temperature data at the different positions. And determining the temperature change correlation between different positions at each moment, and determining the heat transfer influence degrees of the different positions at each moment according to the temperature change correlation, so as to determine the target temperature anomaly degrees of the different positions at each moment according to the temperature data of the different positions, the temperature change correlation and the heat transfer influence degrees. According to the temperature anomaly degree and the preset anomaly threshold, the health states of the different positions are determined, and the temperature change correlation and the heat transfer influence degree between the different positions are considered, so that the target temperature anomaly degree of the different positions is more accurate, and the monitoring accuracy of the health states is improved.

A short circuit identification method is provided for a sampling element of a battery management system. A temperature sensor is disposed in a battery management system to monitor a temperature of a discharge transistor, and the method includes: obtaining the temperature of the discharge transistor by using the temperature sensor, and calculating a temperature difference of the discharge transistor in a preset duration; comparing a discharge current obtained by using a sampling element with a preset current threshold; and determining that the sampling element is short-circuited. In embodiments of the present application, the temperature sensor is used to monitor the temperature change rate of the discharge transistor in the BMS system, it can be detected that only one sampling element has a short-circuit fault with reference to the discharge current obtained by the sampling element, and corresponding protection measures are taken, so that the BMS system runs safely and stably.

The present disclosure relates to a system (100) for acoustically detecting a temperature change, the system (100) comprising: at least one conversion element (10) for converting a temperature change into a characteristic sound; an acoustic sensor (40) configured to be mechanically connected to the structure (50) at a distance from the at least one conversion element (10); and a processor (42, 62) coupled to the acoustic sensor (40), in which the at least one conversion element (10) comprises an actuation portion (20) having at least one material having thermal expansion properties such that a change in temperature causes a movement of the actuation portion (20) that causes the conversion element (10) to generate a characteristic sound and conduct the characteristic sound into the structure (50), the acoustic sensor (40) is configured to record a characteristic sound generated by the conversion element (10) as a structural sound propagating through the structure (50), and the processor (42, 62) is configured to detect a temperature change based on the characteristic sound recorded by the acoustic sensor (40).

A failure detection method for battery racks (100, 400) is disclosed and includes: continuously computing a voltage difference data in a computation frequency; computing a standard deviation by using the voltage difference data retrieved from each battery rack (100, 400) up to present; obtaining a first voltage trend and a second voltage trend according to the voltage difference data in a first period and the voltage difference data in a second period when the standard deviation is greater than a preliminary-filtered threshold; computing an intersection of the first voltage trend and the second voltage trend to obtain a voltage trend status; computing a voltage slope according to the voltage difference data of the second period; and generating an alarm message when the voltage trend status is abnormal and the voltage slope is greater than a slope threshold, where the alarm message indicates the position of a battery cell (120, 420) occurring overvoltage status.

The invention relates to the field of temperature measurement, in particular to a temperature change monitoring system and method in a metal raw material melting process, and the temperature change trend is captured by collecting temperature data in a melting furnace in real time and combining a temperature change rate calculation formula. A DBSCAN clustering algorithm is adopted to carry out segmentation processing on temperature data to obtain different temperature change stages, curve fitting is carried out through a least square method, and error factors at all moments are calculated. And finally correcting temperature data based on the error factor to ensure that the measured value is closer to the actual temperature so as to judge whether the smelting furnace reaches the target temperature and avoid the influence of temperature error on the melting effect. The high-precision sensor, the clustering algorithm and error correction are adopted, the temperature change trend is dynamically captured, precise monitoring of the temperature in the metal melting process is achieved, and the melting uniformity and the product quality are ensured.

The invention relates to the technical field of cable monitoring, and discloses a cable joint temperature monitoring method and a cable joint, and the method comprises the steps: obtaining the real-time insulating layer temperature data of the cable joint based on a miniature temperature sensor, and obtaining the real-time environment data of the cable joint based on an auxiliary sensor; comparing the real-time insulating layer temperature data with a real-time environment temperature value, and determining the thermal radiation direction of the cable joint; determining a temperature difference value between the real-time insulating layer temperature data and the real-time environment temperature value, and determining a predicted temperature value of the conductor crimping layer according to the temperature difference value based on the heat radiation direction; determining a predicted temperature change rate of the conductor crimping layer according to the predicted temperature value; the real-time load current of the cable connector is obtained, and the real-time temperature change rate is determined; and determining a difference ratio between the predicted temperature change rate and the real-time temperature change rate, and judging whether the temperature monitoring of the cable joint is abnormal or not. According to the invention, accurate temperature prediction and reliable abnormity judgment of the cable joint are realized.

The invention discloses a temperature monitoring method for a rotating part of a grain conveyor and related equipment, and relates to the field of temperature monitoring. By adopting the technical scheme, the temperature monitoring system acquires the bearing temperature data under the no-load working condition and the full-load working condition, and draws the bearing temperature change thermal distribution diagram based on the bearing temperature rise data, so that the temperature distribution characteristics of the bearing can be comprehensively mastered. An angle sensor and a temperature sensor array are arranged at the position with the maximum temperature gradient, a temperature monitoring system can obtain the corresponding relation between the temperature and the angle in the bearing rotating process in real time, and bearing rotating temperature characteristic parameters such as the angle temperature difference value, the temperature fluctuation amplitude and the temperature change rate are calculated based on the corresponding relation. The temperature monitoring system compares the bearing rotation temperature characteristic parameter with a preset temperature early warning threshold value, and the abnormal operation type of the bearing can be accurately recognized.

The invention relates to the field of fault detection, and discloses a display screen power supply fault detection method and system, which is used for solving the problem that early warning is mistakenly touched due to environment temperature change during display screen power supply fault detection, and comprises the following steps: acquiring power supply temperature data, power supply current data and power supply voltage data in real time; evaluating to obtain a temperature stability coefficient, a current stability coefficient and a voltage stability coefficient, performing first fault judgment, evaluating to obtain a power supply fault index if the first fault judgment judges that the current power supply does not have a fault, performing second fault judgment, and acquiring an environment temperature in real time if the second fault judgment judges that the current power supply has a fault; the fault threshold value is dynamically adjusted in real time according to the environment temperature, the fault adjustment threshold value is obtained, third-time fault judgment is carried out, if it is judged that the current power supply breaks down, related workers are prompted that the power supply breaks down, and the accuracy of fault detection is effectively improved.

The invention pertains to system and method for profiling, modeling and monitoring temperature and heat flow in a meat piece or food item in a cooking by placing the item on a flat surface of a cooking device in a sufficiently visible way for monitoring with an optical head, collecting data with suitable sensors and mirrors, such as IR sensor, visible range sensor, high resolution Lidar sensor, laser or LED device with different color options that has a collimated beam, scanning with a scanning mechanism, measuring temperature of bottom and upper surfaces of the item, modeling the item with a 3D as horizontally oriented equithermal slices and perpendicularly non-equithermal relative each other, and calculating temperature of these slices, particularly Tcore of a central slice.

The present application relates to the technical field of ship engineering, and discloses a method and system for intelligent monitoring of cargo hold working data. The method first uses a camera to obtain a cargo hold image, extracts specific features through an edge detection algorithm, divides the sub-regions to count the number of pixels, and calculates the distribution uniformity to determine the type of cargo distribution. If it is a uniformly distributed target, the first infrared camera device and the temperature sensor are used to obtain data, and the uniform temperature is weighted and calculated. If it exceeds the first threshold, the corresponding cooling fan speed is adjusted; if it is a non-uniformly distributed target, the data is obtained in the same way to calculate the non-uniform temperature, and the corresponding cooling fan speed is adjusted if it exceeds the second threshold. Finally, the weighted comprehensive difference of the uniform temperature, non-uniform temperature and the corresponding threshold difference is calculated within a set period. When it is higher than the set threshold, the first and second thresholds of the next period are adjusted in the opposite direction. The above method can realize precise and intelligent control of cargo hold temperature to ensure cargo safety.

The invention discloses an automatic spraying control method and system for a fuel tank, and the method comprises the steps: obtaining the temperature monitoring data of the fuel tank, and carrying out the prediction, and obtaining the temperature prediction data; evaluating the high-temperature degree of the fuel tank based on the temperature prediction data to obtain a high-temperature degree evaluation value, and setting an initial control condition of the automatic spraying device according to the high-temperature degree evaluation value; determining temperature change characteristics of the fuel tank within a period of time after spraying, and determining a temperature change coefficient of the fuel tank based on the temperature change characteristics; and determining a control correction coefficient of the automatic spraying device based on the temperature change coefficient, and correcting an initial control condition of the automatic spraying device according to the control correction coefficient. By analyzing the temperature response characteristics in the spraying process and dynamically optimizing the control parameters, a complete monitoring-prediction-control-feedback closed loop is formed, the control precision is remarkably improved, timely and effective intervention is ensured when risks occur, energy and resources are saved, and unnecessary resource waste and equipment abrasion are avoided.

A water heating system includes a first heating chamber arranged in parallel with a second heating chamber; a first temperature sensor positioned to sense a first temperature in the first heating chamber; a second temperature sensor positioned to sense a second temperature in the second heating chamber; and a controller configured to: determine a first temperature value based on a first sensor signal from the first temperature sensor, determine a second temperature value based on a second sensor signal from the second temperature sensor, compute a differential between the first temperature value and the second temperature value, determine that scale buildup is indicated in response to the differential exceeding a first threshold, and initiate a corrective action in response to determining that scale buildup is indicated.

The present invention relates to the field of heat treatment control technology, and in particular to a quenching and tempering device and method for forgings. The method installs thermocouple sensors at different detection depths in the forging, obtains temperature data of the heating process; analyzes the numerical changes of the temperature data to determine the temperature change index; determines the abnormal interference degree of the central depth of the two detection depths according to the fluctuation of the temperature change index at two adjacent detection depths; determines the abnormal interference attenuation coefficient according to the depth difference and abnormal interference degree difference of the two adjacent central depths; and then determines the interference index of the detection depth; determines the degree of temperature uniformity requirement according to the interference index and temperature data, and adjusts the heating speed of the forging at the current moment according to the degree of temperature uniformity requirement. The present invention can analyze the temperature changes at different detection depths, eliminate the influence of abnormal interference, facilitate the uniform heating effect of the forging, and improve the quality of quenching and tempering of the forging.