60 results about "First order derivative" patented technology

The invention discloses a system and method for measuring the opening and closing state of an electromagnetic valve, and relates to the technical field of electromagnetic valves.The method comprises the steps that after an electromagnetic valve control signal is triggered, dynamic inductance L at each moment t is obtained through real-time backstepping by means of a voltage and current sampling module integrated in a driving loop and an inductance analysis module in a local microcontroller MCU; gaussian filtering processing and derivative calculation are carried out on the dynamic inductance L in the edge calculation module, first-order derivative and second-order derivative characteristics are extracted, and an inductance mutation factor index Cimp is obtained through calculation. According to the method, clamping stagnation, rebound and discontinuous abnormal states occurring in the opening and closing process of the electromagnetic valve are comprehensively reflected, a sudden change threshold value Cthr is set and compared, and a set of dynamic opening and closing behavior diagnosis mechanism with high resolution and high adaptability is constructed. According to the method, high-frequency dynamic response extraction and abnormal trend quantification can be completed within 100 ms after the control signal is triggered, and the method has higher early warning capability and non-intrusive compatibility.

The invention relates to the technical field of multi-agent systems, and discloses a multi-agent and multi-mode alignment interaction method and system for a review scene, and the method comprises the steps: mapping real-time multi-mode data into a local belief vector through a heterogeneous agent cluster, and calculating the spatial divergence to determine a global cognitive entropy; interaction time sequence gating logic based on entropy flow differential is established, and active alignment is triggered when the global cognitive entropy is larger than a convergence threshold value and a first-order derivative is smaller than a damping threshold value; according to the method, through entropy flow differential control and an active semantic disturbance closed loop, decision oscillation of the multi-agent system in the non-cooperative environment is eliminated, and the reliability of the multi-agent system in the non-cooperative environment is improved. Mathematical convergence of the belief state in an adversarial disguise scene is realized, and the system identification precision in a complex interactive game is improved.

The invention discloses an acid-base reagent constant-current supply system and a test method, and relates to the technical field of acid-base reagent constant-current test.The method comprises the steps that before titration is started, initialization setting is conducted on a multi-channel pumping system, and a pressure sensor and a flow meter are started to collect real-time supply state data of all channels; based on the collected pressure measurement value and flow data, a dynamic PI D feedback control algorithm is adopted to adjust pump output so as to maintain constant flow speed output of the acid-base reagent under different load conditions; on the basis of stable supply of an acid-base reagent, continuously collecting a pH value change signal in the titration process by using a pH sensor, identifying a first derivative and a second derivative of a titration reaction based on a time sequence analysis method, and judging a titration inflection point moment when the second derivative exceeds a preset threshold value; and based on the identified first-order derivative and the identified second-order derivative, calling a fuzzy rule base to judge the grade of the titration rate which needs to be adopted at present, and realizing nonlinear self-adaptive adjustment of the titration rate.

The invention discloses a trajectory segmentation method and system based on key point recognition, and relates to the field of trajectory analysis and pattern recognition, and the method comprises the steps: S1, obtaining multi-source trajectory data, and generating time sequence trajectory information; s2, calculating the acceleration corresponding to the track point according to the track information, further calculating the corresponding curvature, carrying out curvature related information statistics through the curvature of the track, and calculating an optimized curvature first-order derivative corresponding to the track point through the curvature information and the statistical information of the curvature; s3, marking acceleration key points, optimizing curvature first-order derivative key points and circling area key points; and S4, integrating information of the acceleration key point, the optimized curvature first-order derivative key point and the circling area key point, and generating a track segmentation result. According to the method, the key points in the trajectory can be accurately recognized, particularly, high performance can be kept in complex trajectories and high-noise data, and the trajectory analysis efficiency and reliability are effectively improved.

This disclosure relates to ethylene interpolymer products comprising a Melt Flow-Intrinsic Viscosity Index value, MFIVI, of from ≥0.05 to ≤0.80; a first derivative of a melt flow distribution function, formula (I) at a loading of 4000 g, of from ≥−1.85 to ≤−1.51; a sum of unsaturation, SUMU, from ≥0.047 to ≤0.100 unsaturations per 100 carbon atoms; and a residual QC catalytic metal of from ≥0.03 to ≤5 ppm of hafnium. Ethylene interpolymer products comprise at least two ethylene interpolymers. Ethylene interpolymer products are characterized by a melt index (I2) from 0.3 to 500 dg / minute, a density from 0.855 to 0.975 g / cc and from 0 to 25 mole percent of one or more a-olefins. Ethylene interpolymer products have polydispersity, Mw / Mn, from 1.7 to 25; and CDBI50 values from 1% to 98%. These ethylene interpolymer products have utility in flexible as well as rigid applications.

The invention belongs to the technical field of physical crossing of machine learning and nuclear reactors, and discloses a method, a product and a system for solving the problem of steady-state neutron diffusion of a heterogeneous reactor, which are particularly suitable for a reactor core model of a multi-region and multi-material complex arrangement. According to the method, derivative order reduction processing is carried out on a steady-state multi-group neutron diffusion equation, a first-order derivative equation set equivalent form containing a flow continuity condition is constructed, and the neutron flux density and the neutron current density are jointly predicted by using a neural network. And the continuity of the neutron flux density and the neutron current density can be automatically realized at interfaces of different material regions. Compared with a traditional method, the method has the advantages that complex sampling operation on a material interface can be avoided, and the modeling process is simplified; and the design of a flow continuous constraint loss function at a material interface is reduced, the prediction precision and the training efficiency are effectively improved, and the method has good universality and robustness.

The application discloses a component fatigue micro-damage early identification method based on a nonlinear static component, and particularly relates to the technical field of material nondestructive testing and structural health monitoring, which comprises the following steps: arranging an excitation probe and a receiving probe on the surface of a component to be measured; selecting an excitation frequency based on a frequency dispersion curve and generating a Hanning window modulated wave; collecting a propagation response signal; extracting a static component amplitude A and a fundamental wave amplitude A through time-frequency processing; calculating a nonlinear static parameter beta=A / A²; further calculating a first derivative S(N) and a second derivative ΔS(N) of beta with respect to a fatigue loading cycle N; and identifying a dislocation dominant stage, a dislocation saturation or rearrangement stage, a micro-crack initiation stage and a macro-crack formation stage according to the first derivative S(N) and the second derivative ΔS(N). The application can be used for early stage identification of the evolution process of component fatigue micro-damage.

The application provides a blood sodium detection correction method and system, based on the first derivative sign change and the second derivative extreme value of original spectrum data, the peak value region and the baseline flat region are divided, the local noise level parameters of each flat region are calculated; the first asymmetric factor and the smoothing factor are set for the peak value region, the second asymmetric factor is set for the flat region, and the second smoothing factor is adjusted according to the local noise level parameters; the asymmetric least square fitting is independently performed on each region, the weight is related to the noise level when the residual error is positive, and the weight is 1 minus the asymmetric factor of the region where the spectrum data point is located when the residual error is not positive; the end of the fitting of the previous region is taken as the initial constraint of the latter region, the sub-baseline is generated, and the spline interpolation is connected to form a continuous total baseline; the original spectrum data is subtracted from the total baseline, and the corrected blood sodium spectrum data is obtained.

The present application relates to a kind of corneal biomechanical property calculation method and device based on spline theory, comprising the following steps: step 1, sampling and analysis are carried out from the dynamic video of corneal stress deformation in historical database, and the profile of cornea is extracted;Step 2, the curve of profile change in the process of corneal deformation is fitted using spline theory, and the curve equation of corneal profile is obtained;Step 3, according to the curve equation of corneal profile in step 2, the zero point of its first derivative and second derivative is solved, to determine the first flattening state moment, the maximum indentation moment and the second flattening moment in the process of corneal deformation, so as to calculate the biomechanical property of cornea.The present application can accurately and objectively evaluate the biomechanical property of cornea.

The invention discloses a method for non-destructively detecting the carbonization depth of a cement-based material. The method comprises the following steps: carrying out water saturation treatment on a sample; placing the carbonized surface of the sample above a single-side low-field nuclear magnetic resonance instrument probe downwards, and starting to carry out nuclear magnetic signal test from a preset initial depth from the carbonized surface; gradually moving the unilateral low-field nuclear magnetic resonance instrument main body downwards according to a preset stepping length through a lifter to obtain nuclear magnetic signal data of different depths in the sample; processing the nuclear magnetic signal data of different depths so as to obtain attenuation data of the relative nuclear magnetic signal along with the test depth; first-order derivative processing is carried out on attenuation data of the relative nuclear magnetic signal along with the test depth, and the position where a first-order derivative changes suddenly is the carbonization depth. Compared with a traditional carbonization depth measurement method, the method does not damage the material, is not limited by the internal alkalinity of the material, is more accurate in test result, and has important application potential in the field of durability evaluation of the cement-based material.

The invention provides a method for realizing reversible conversion between a lower boundary variable and an unbounded variable in water transportation and a related product. The method comprises the following steps of: valuing the lower bounded variable; converting the lower bounded variable into an unbounded variable; mathematical transformation of bounded variables and unbounded variables is proved to be reversible; proving that the first-order derivative at the forward transformation segmentation point is continuous; and proving that the first-order derivative at the inverse transformation segmentation point is continuous. The method has the beneficial effect that the bounded variable of the water transportation lower boundary is successfully converted into the unbounded variable. The conversion can meet the requirements of a part of mathematical assimilation methods and mathematical models for unbounded variables in the water transportation information processing and water transportation variable simulation and prediction processes. According to the method, the basic hypothesis of the peripheral nested algorithm is not damaged, the continuity of the algorithm is ensured, and the introduction of new errors is prevented. From the theoretical level, the assimilation precision of the peripheral nested data and the correction precision of the model correction model are higher, and the algorithm is more stable.

Technologies for nondestructively detecting corrosion of an object include a measurement device such as a vector network analyzer (VNA) and a computing device coupled to the measurement device. An object such as a metallic cable is coupled to the measurement device, multiple S-parameter values for the object are measured over a predetermined frequency range. The range may be between 40 MHz to 1 GHz. The S-parameter values may include forward gain / loss (S21) and input impedance (S11). The computing device counts a number of peaks in the S-parameter values and determines an indication of corrosion for the object based on the number of peaks. The indication of corrosion is proportional to the number of peaks. Counting the peaks may include smoothing the S-parameter values, determining a first order derivative, transforming the derivative to a frequency domain signal, and counting peaks in the frequency domain signal. Other embodiments are described and claimed.

The invention relates to the technical field of spraying of surfaces of vacuum cups, and discloses a spraying method for the surfaces of vacuum cups. The method comprises the following steps: establishing a space coordinate system, collecting a structured light three-dimensional point cloud, mapping the point cloud to a two-dimensional parameter domain, calculating a first-order derivative and a normal vector, further calculating a second-order derivative and a basic form coefficient, extracting a Gaussian curvature and an average absolute curvature, generating a spray point spacing function according to the curvature, generating spray points in the parameter domain, and mapping the spray points into three-dimensional coordinates. And finally, path planning and spraying instruction output are carried out. According to the method, through high-precision non-contact modeling and differential geometric analysis, the geometric change of the curved surface is accurately recognized, self-adaptive adjustment of the spraying point density is guided, the spraying efficiency and uniformity are improved through path optimization, the bottlenecks of a traditional manual or mechanical path setting method in the aspects of spraying uniformity and consistency are broken through, and the method is suitable for large-scale popularization and application. And the device is particularly suitable for intelligent and high-precision spraying operation of personalized products and complex structure surfaces.

The present application relates to the method for controlling the opening of the vertical roll mill based on short stroke control, and belongs to the technical field of vertical roll rolling. The method comprises the following steps: obtaining the segmented rolling information of the rolled part in the target workpiece; constructing the quintic polynomial head-tail contour curve according to the rolling information of each segment; obtaining the quartic speed model by taking the first order derivative of time of the quintic polynomial head-tail contour curve, and extracting a plurality of feature points; constructing the deviation degree regression prediction model between the plurality of feature points of the quartic speed model and the preset vertical roll reduction, the preset horizontal roll reduction and the rolling information of each segment; and controlling the opening of the vertical roll mill in the vertical roll rolling according to the deviation degree regression prediction model. The present application improves the opening control precision of the vertical roll mill.

The application relates to the technical field of semiconductor process waste gas treatment, and discloses a pipeline blockage early warning method and system. The method comprises the following steps: obtaining a real-time change curve of real-time pressure and a time sequence according to the obtained time sequence and the real-time pressure of a pipeline; obtaining a fitting function corresponding to the real-time change curve according to the real-time change curve; obtaining a first-order derivative and a second-order derivative of the fitting function according to the fitting function; determining whether the second-order derivative in the time sequence is equal to a first threshold value; if yes, judging a blockage condition of the pipeline at a target moment according to the fitting function; and if not, judging the blockage condition of the pipeline at the target moment according to the first-order derivative and the second-order derivative. The pipeline blockage early warning method can solve the defect that the prior art cannot predict the pipeline blockage condition.

A method for determining a viscosity characteristic value of a melt in an injection mold. The injection mold has: at least one cavity into which a melt is injected and which fills the cavity; a pressure sensor unit disposed on the cavity and measuring a mold internal pressure of the melt in the cavity and generating sensor data for the measured mold internal pressure; and at least one evaluation unit for evaluating the sensor data; the evaluation is characterized in that a starting time point is determined, at which the sign of the first derivative function of the sensor data changes from zero (= 0) to positive (gt; 0); determining a filling time point at which the sign of the second derivative function of the sensor data changes from zero (= 0) to positive (gt; 0); a pressure rise is formed between the mold internal pressure at the filling time point and the mold internal pressure at the starting time point; and obtaining a viscosity characteristic value according to the pressure rise and the time difference between the filling time point and the starting time point. The invention also relates to an associated device.

The present application relates to the technical field of biomedical image processing, and discloses a multi-scene video intelligent clipping method and system, comprising the following steps: obtaining time-synchronized original microscopic video stream and structured experimental operation log; for each operation event, constructing an event neighborhood reference window in the original microscopic video stream and performing spatial registration to generate a locally video segment after spatial correction; generating a spatial attention weight mask according to the operation space coordinate vector, calculating a structure disturbance response value sequence of each frame of the local video segment in combination with a structural similarity index, and obtaining a phase significance score sequence through smoothing filtering; generating an original candidate segment based on the discrete first-order derivative of the phase significance score sequence and baseline period statistical characteristics; according to the preset priority weight of the operation action type label corresponding to the candidate segment, performing cutting and transition processing on the time overlapping segment, and outputting an abstract video file; and generating a metadata index file associated with the abstract video file.

The present invention provides a method for analyzing the stability of heterogeneous systems based on a simplified nonlinear dynamics model, comprising the following steps: establishing a simplified model topology based on the heterogeneous system and obtaining a phase angle difference, where the phase angle difference is the difference between the phase angle of a first node and the phase angle of a second node; obtaining a simplified nonlinear dynamics model based on the heterogeneous system and the phase angle difference based on the simplified model topology; solving the nonlinear dynamics model using an averaging method to obtain an analytical solution, where the analytical solution is an expression of the square of the system amplitude; differentiating the analytical solution with respect to time to obtain a third first-order derivative; obtaining a stability criterion when the third first-order derivative is zero; and determining the stability of the heterogeneous system based on the stability criterion. The method for analyzing the stability of heterogeneous systems based on a simplified nonlinear dynamics model provided by the present invention is simple and efficient, has a low model order, retains the nonlinear characteristics of the system, performs an analytical solution based on a generalized averaging method, proposes a system stability criterion, and facilitates stability analysis.

This invention provides a single-spectrum classification spectral analysis method based on an interpretable deep model, comprising: randomly generating several negative samples; summing the standard spectrum of the target object with the generated negative samples to form several positive samples; performing first-order derivative operations on each of the positive and negative samples to obtain differentiated samples; inputting the differentiated samples into a deep forest model for model training to obtain a trained deep forest model; visualizing the trained deep forest model to obtain a visualized deep forest model; and using the visualized deep forest model to identify whether the target object exists in an unknown substance. The method provided by this invention exhibits excellent recognition performance in substance identification, not only accurately distinguishing between target objects and unknown non-target objects, but also capturing weak target object signals in mixtures or complex matrices, achieving highly sensitive and selective substance identification.

This disclosure relates to ethylene interpolymer products comprising a Melt Flow-Intrinsic Viscosity Index value, MFIVI, from ≥0.05 to ≤0.80; a first derivative of a melt flow distribution function, formula (I) at a loading of 4000 g, from >−1.51 to ≤−1.15; a sum of unsaturation, SUMU, from ≥0.005 to <0.047 unsaturations per 100 carbon atoms; and a residual catalytic metal from ≥0.03 to ≤5 ppm of hafnium. Ethylene interpolymer products comprise at least two ethylene interpolymers. Ethylene interpolymer products are characterized by a melt index (I2) from 0.3 to 500 dg / minute, a density from 0.855 to 0.975 g / cc and from 0 to 25 mole percent of one or more a-olefins. Ethylene interpolymer products have polydispersity, Mw / Mn, from 1.7 to 25; and CDBI50 values from 1% to 98%. These ethylene interpolymer products have utility in flexible as well as rigid applications.d⁢Log⁡(1 / In)d⁢Log⁡(loading)(I)

The application discloses a complex conduit first-order continuous center line reconstruction method based on scanning point cloud data and belongs to the field of engine geometric parameter digitization detection. After obtaining scanning point cloud data of an outer surface of a conduit, straight pipe data and curved pipe data of the complex conduit are segmented. For the segmented straight pipe and curved pipe data, random sampling cylinder fitting and circle fitting operation based on intersection of a vector point and a main plane are respectively performed to obtain trend lines of the straight pipe and the curved pipe. For the trend lines of the straight pipe and the curved pipe, center points of different pipe sections based on equally-spaced vertical section planes are solved, and linear fitting is respectively performed on the center points of the different pipe sections to obtain a plurality of discontinuous center line sections of the complex conduit. A cubic spline curve is adopted to perform first-order derivative interpolation fitting between adjacent straight line sections and circular arc section center lines to obtain a complex conduit first-order derivative continuous center line. The reconstructed center line is used as a reference for calibration of a pipe special-purpose measuring device measuring capacity.

The invention relates to a watermelon seed vigor grade classification method based on terahertz transmission and reflection imaging data fusion. The method comprises the following steps: firstly, performing artificial accelerated aging treatment on watermelon seeds under high-temperature and high-humidity conditions to obtain samples with different activity grades; then, a terahertz time-domain spectral imaging system is used for collecting transmission and reflection signals respectively, the transmission signals are subjected to color threshold segmentation to extract an embryo region, and the reflection signals are subjected to Canny edge detection and contour screening to extract a surface region; and after the obtained signal is subjected to smooth filtering and deconvolution processing, first-order derivative difference enhancement is further introduced, and a fusion spectrum is constructed by adopting a weighted fusion strategy. The fusion spectrum is subjected to weight distribution through a frequency attention mechanism and then input to a feature perception convolutional neural network, the network comprises two layers of one-dimensional convolution and nonlinear activation functions and is provided with high, medium and low activity branch classification paths, and finally a classification result of seed activity levels is output.

The present invention is a method for selecting a blood specimen that may have a coagulation abnormality, comprising: acquiring Ys(X) for a blood specimen under examination, wherein the blood specimen under examination is a blood specimen for which prolongation of APTT cannot be determined with certainty, and Ys(X) is a ratio (%) of Rs(i) to Rmax_s at a measurement point or time at which Vs(i) reaches X% of Vmax_s. Rs(i) is a coagulation reaction curve of the specimen, Vs(i) is a first derivative curve of Rs(i), Rmax_s is the maximum value of Rs(i), Vmax_s is the maximum value of Vs(i), VmaxT_s is a measurement point or time at which Vs(i) reaches Vmax_s, i is a measurement point or time, and X is a variable and X > 0. If the measurement point or time at which Vs(i) reaches X% of Vmax_s is after VmaxT_s, Ys(X) is defined as Ys(200 - X).

The invention discloses an intelligent harmful gas concentration identification and detection method, and particularly relates to the field of gas concentration identification and detection.The method comprises the steps that a multi-channel gas response unit is arranged in a target area, and the gas response unit at least comprises an electrochemical channel, a spectrum channel and an ionization channel; collecting gas response values at the same moment to form a three-dimensional response tensor; meanwhile, corresponding environment tensors are collected; performing local sliding window transformation on the gas response value of each channel, calculating a first-order derivative, a second-order derivative, a response intensity variable amplitude and a recovery rate in a window, and constructing a local feature vector group; by constructing a concentration recognition closed-loop process composed of multichannel response feature extraction, concentration decoding modeling, adaptive calibration and disturbance confidence regulation, the recognition accuracy, adaptive capability and anti-interference stability of the system in a complex mixed gas environment are improved.

The invention provides a method for realizing reversible conversion between a water transport upper boundary variable and an unbounded variable and a related product. The method comprises the following steps: valuing an upper bounded variable; converting the upper bounded variable into an unbounded variable; mathematical transformation of bounded variables and unbounded variables is proved to be reversible; proving that the first-order derivative at the forward transformation segmentation point is continuous; and proving that the first-order derivative at the inverse transformation segmentation point is continuous. The method and the device provided by the invention have the beneficial effects that the conversion from the bounded variable of the water transport upper boundary to the unbounded variable is successfully realized. The conversion can meet the requirements of a part of mathematical assimilation methods and mathematical models for unbounded variables in the water transportation information processing and water transportation variable simulation and prediction processes. According to the method, the basic assumptions of the peripheral nested algorithms are not destroyed, the continuity of the algorithms is ensured, and the introduction of new errors is prevented. From the theoretical level, the assimilation precision of the peripheral nested data and the correction precision of the model correction model are higher, and the algorithm is more stable.

The invention discloses a theoretical model for spiral self-feeding shape correction of a pipe, which comprises the following steps of: establishing a theoretical formula of total kinetic energy T of the pipe on the basis of a thin-wall hypothesis under the conditions that a rotating shaft of the pipe is assumed to coincide with a bent plane and axial rolling of the pipe is ignored; establishing a simplified theoretical formula of potential energy V of the pipe on the basis of a reciprocating bending unified curvature theorem and a bidirectional effect under the condition of neglecting plastic dissipation of the pipe; modeling is conducted on the movement track of the pipe on the basis of the Lagrange equation so as to obtain a movement track equation set, and the movement track equation set comprises a coupling relational expression among the circumferential bending angle of the pipe, the spiral azimuth angle of the pipe and the axial self-feeding displacement s; wherein the Lagrange equation is as follows: Qq is the generalized force applied to the pipe, L is the Lagrange quantity, and q is the generalized coordinate system and is a first derivative of q.

The invention relates to the technical field of medical examination, and discloses an automatic station adjusting method and system for ophthalmologic examination, and the method comprises the steps: collecting a load input signal of a contact interface between a station supporting part and an examined part; separating a load fluctuation component with a frequency between 1 Hz and 5 Hz; determining a load phase lag value based on a first-order derivative of the fluctuation component, correcting phase deviation, and analyzing an elastic restoring force parameter; according to the invention, a load displacement transient cooperative compensation mechanism is established, the delay of a visual image feedback link is eliminated, the response period is enabled to be lower than 10ms, the physiological tremor phase is aligned, the mechanical hysteresis of soft tissue of the detected part is headed, and the dynamic compensation of the soft tissue of the detected part is realized. And the dynamic distance between the interference signal sampling plane and the fundus tissue is maintained.

The present invention discloses a model predictive control system and method for a medicine calcining machine based on the entropy weight method. The method includes constructing a nonlinear model based on the quality data, temperature data, and real-time power of the electrothermal machine during the medicine processing process, constructing a system state space equation, linearizing it, and designing a state observer to observe the value of the first derivative of the real-time temperature of the medicine; discretizing the system state space equation to construct a discretized system; for the discretized system, using the rolling optimization method to predict the system state for a future period of time; designing a quadratic control law, and using the entropy weight method to obtain the weight coefficients of the system state and the weight coefficients of the input variables in the quadratic control law; substituting the predicted system state for a future period of time, setting constraint conditions, solving the system input variable sequence, and taking the first input variable in the solved sequence as the power of the electrothermal machine at the next moment and applying it to the medicine calcining machine.

The present invention relates to a chemically strengthened glass having a thickness t (mm), in which a first-order derivative CSx′ of a stress value CSx (MPa) is −4.7 or larger in a range of CSx≥0 in a profile of the stress value CSx (MPa), in which the stress value CSx (MPa) is a function of depth x (μm) from a glass surface, and in which the stress value CSx (MPa) is measured by a scattered light photoelastic stress meter, and a manufacturing method thereof.

This application discloses a method, apparatus, device, and storage medium for determining the critical load of a thin film. This application determines the total input energy load curve through a thin film scratch test. Based on the instantaneous normal load and total input energy in the initial stage of the scratch test, a baseline energy load curve for the entire stage is determined. Then, the failure energy load curve is determined using the energy balance method. This application performs first-order differentiation on the failure energy load curve and finds the peak value of the first-order derivative curve to determine the critical load of the thin film. This method eliminates the subjectivity of manual observation and the ambiguity of friction curves, greatly improving the repeatability of the results. Furthermore, this method eliminates the need to calculate cracking energy and peeling energy separately, avoiding the physical difficulties of directly calculating cracking energy and peeling energy. The peak value of the first-order derivative of the failure energy load curve more accurately corresponds to peeling in adhesion failure, thus the critical load can be accurately determined based on the peeling point.