Method for detecting roller pressure of fish skinning machine

Abstract

The invention relates to the technical field of roller pressure detection, in particular to a method for detecting roller pressure of a fish peeler. The method comprises the following steps: synchronously acquiring a first pressure signal, fish body dynamic deformation, surface glossiness and an equivalent Young modulus signal during rolling; analyzing based on the deformation signal to obtain a dynamic elastic coefficient and a deformation buffer component; analyzing based on the glossiness signal to obtain a comprehensive lubrication coefficient and a mucus lubrication loss component; analyzing based on the Young modulus signal to obtain a comprehensive hardness impedance coefficient and a hardness loss component; according to the first pressure value and the influence significance of the components, a fusion strategy is selected, and equivalent roller peeling pressure is output; and comparing the pressure with the target pressure, if the pressure does not reach the standard, generating a global optimization factor, optimizing the calculation model of each loss component, and performing fusion again until a standard pressure detection value is output. The problems that traditional pressure detection is distorted and accurate peeling pressure cannot be obtained due to deformation, mucus and uneven hardness of the fish body are solved.

Description

Technical Field

[0001] This invention relates to the field of roller pressure detection technology, and in particular to a method for detecting the roller pressure of a fish skinning machine. Background Technology

[0002] In large-scale industrial fish skinning production lines, real-time and accurate detection of the pressure applied by the skinning rollers is crucial for achieving automation and quality control during skinning. Currently, factories mainly use direct measurement methods, such as installing force sensors on the roller support shaft, or indirect calculations by monitoring the pressure of the drive system and the motor current. These methods simplify the contact between the roller and the fish body to an interaction between rigid bodies, and what is obtained is actually the internal force signal of the mechanical system.

[0003] However, as a biological material with mucus, elasticity, and uneven hardness, fish exhibit biomechanical behavior during high-speed continuous processing, causing traditional detection methods to fail significantly. Elastic deformation of fish tissue buffers pressure, surface mucus alters friction and leads to pressure loss, while differences in flesh hardness affect pressure transmission efficiency. The coupling effect of these three time-varying factors results in a large and unstable deviation between the internal force signal measured at the shaft end and the actual effective pressure acting on the fish skin peeling interface. Traditional open-loop detection methods cannot isolate and quantify these interferences, nor can they adaptively adjust to changes in fish species, individual size, and freshness. This leads to distorted detection results, low process control precision, large fluctuations in product quality, and high loss rates. Furthermore, they heavily rely on manual experience for calibration, making it difficult to meet the demands of large-scale factories for high-stability, low-loss continuous production.

[0004] Chinese Patent Publication No. CN109329365A discloses a shallow skinning machine for fish, which can avoid slippage of the feeding roller and efficiently complete the shallow skinning of fish. This shallow skinning machine includes an inclined feeding belt. A feeding roller and a cutting roller are arranged at the bottom of the feeding belt. The drive shaft of the feeding roller is parallel to the rotation shaft of the cutting roller. Multiple feeding rollers are coaxially arranged along the length of the rotation shaft of the feeding roller. Both ends of the drive shaft of the feeding roller are drive wheels, which are connected to a drive shaft via a drive belt. The drive shaft portions at both ends of the feeding rollers are hinged to the lower end of a movable support. The movable support is an inclined frame-shaped support. The middle part of the movable support is hinged to the drive shaft. The upper end of the movable support is connected to a fixed rod via a return spring. Feeding teeth are provided on the roller surface of the feeding rollers along the length of the shaft, and cutting teeth are provided on the roller surface of the cutting rollers along the length of the shaft.

[0005] Therefore, it can be seen that the aforementioned fish shallow skinning machine has the following problems: 1. During the peeling process, the pressure of the feeding roller on the surface of the fish cannot be detected in real time, resulting in the inability to obtain the actual pressure acting on the surface of the fish, leading to problems such as over-peeling or substandard peeling effect.

[0006] 1. During the skinning process, it is not applicable because the pressure detection of the feeding roller is distorted and the skinning pressure cannot be accurately obtained due to the deformation of the fish body, uneven mucus and hardness. Summary of the Invention

[0007] Therefore, the present invention provides a method for detecting the roller pressure of a fish skinning machine, in order to overcome the problems in the prior art where the traditional pressure detection is distorted and cannot obtain accurate skinning pressure due to fish body deformation, uneven mucus and hardness.

[0008] To achieve the above objectives, the present invention provides a method for detecting the roller pressure of a fish skinning machine, comprising: The system simultaneously acquires the first pressure signal generated when the roller rolls on the surface of the fish, the dynamic deformation signal of the fish surface, the gloss signal of the fish surface, and the equivalent Young's modulus signal. Based on the dynamic deformation signal, the dynamic elastic coefficient is obtained to determine whether the deformation of the fish body affects the roller pressure and to determine the deformation buffer component. The comprehensive lubrication coefficient is obtained based on the surface gloss signal to determine whether the amount of mucus on the fish body affects the roller pressure and to determine the mucus lubrication loss component. Based on the equivalent Young's modulus signal, the comprehensive hardness impedance coefficient is obtained to determine whether the hardness of the fish meat affects the roller pressure and to determine the hardness loss component. Based on the first pressure signal, a first pressure value is obtained, and a fusion strategy is determined according to the factors that are determined to have a significant impact, so as to output an equivalent roller peeling pressure. Based on the target peeling pressure, it is determined whether the output equivalent roller peeling pressure meets the standard, and a global optimization factor is determined to optimize the calculation process of each loss component and obtain the optimized new loss component. Based on the optimized new loss components, a new equivalent peeling pressure is obtained by re-fusion, and it is determined whether the new equivalent peeling pressure is qualified. If it is qualified, the roller pressure is tested.

[0009] Furthermore, the process of determining whether the deformation of the fish body affects the roller pressure includes, Based on the dynamic deformation signal, the deformation establishment time constant and steady-state deformation depth are extracted; The dynamic elastic coefficient is calculated based on the deformation establishment time constant and the steady-state deformation depth. The dynamic elastic coefficient is compared with the standard dynamic elastic coefficient; Based on the fact that the dynamic elastic coefficient is greater than the standard elastic coefficient, it is determined that the current deformation of the fish body has affected the roller pressure.

[0010] Furthermore, the process of determining the deformation buffer component includes, A first pressure value is obtained based on the first pressure signal; The absolute difference is calculated based on the dynamic elastic coefficient and the standard dynamic elastic coefficient. The absolute difference is compared with the standard absolute difference; The first deformation buffer component is determined based on the absolute difference being less than or equal to the standard absolute difference. The second deformation buffer component is determined based on the fact that the absolute difference is greater than the standard absolute difference. The first deformation buffer component is the product of the first loss coefficient, the absolute difference, and the first pressure value; the second deformation buffer component is the product of the second loss coefficient, the absolute difference, the first pressure value, and the scaling factor.

[0011] Furthermore, the process of determining whether the amount of mucus on the fish's body affects the roller pressure includes, Spectral analysis is performed on the surface gloss signal to extract the dominant frequency and signal energy ratio. The comprehensive lubrication coefficient is calculated based on the dominant frequency and the signal energy ratio. The overall lubrication coefficient is compared with the standard lubrication coefficient; Based on the fact that the overall lubrication coefficient is greater than the standard lubrication coefficient, it is determined that the current amount of mucus on the fish body has affected the roller pressure.

[0012] Furthermore, the process of determining the viscous lubrication loss component includes, The absolute lubrication deviation value is calculated based on the comprehensive lubrication coefficient and the standard lubrication coefficient. The absolute lubrication deviation value is compared with the standard absolute lubrication deviation value; Based on the fact that the absolute lubrication deviation value is less than or equal to the standard absolute lubrication deviation value, the first viscous lubrication loss component is determined; Based on the fact that the absolute lubrication deviation value is greater than the standard absolute lubrication deviation value, the second viscous lubrication loss component is determined; Wherein, the first viscous lubrication loss component is the product of the first lubrication loss coefficient, the absolute lubrication deviation value, and the first pressure value; the second viscous lubrication loss component is the product of the second lubrication loss coefficient, the absolute lubrication deviation value, the first pressure value, and the lubrication enhancement factor.

[0013] Furthermore, the process of determining whether the firmness of the fish flesh affects the roller pressure includes, Spatial statistical analysis is performed based on the equivalent Young's modulus signal to obtain the mean and coefficient of variation of Young's modulus; The comprehensive hardness resistance coefficient is calculated based on the mean and the coefficient of variation. The comprehensive hardness resistance coefficient is compared with the standard hardness resistance coefficient; Based on the fact that the overall hardness impedance coefficient is greater than the standard impedance coefficient, it is determined that the current hardness of the fish meat has affected the roller pressure.

[0014] Furthermore, the process of determining the hardness loss component includes, The absolute impedance deviation value is calculated based on the comprehensive hardness impedance coefficient and the standard hardness impedance coefficient. The absolute impedance deviation value is compared with the standard absolute impedance deviation value; The first hardness loss component is determined based on the absolute impedance deviation value being less than or equal to the standard absolute impedance deviation value. The second hardness loss component is determined based on the fact that the absolute impedance deviation value is greater than the standard absolute impedance deviation value. Wherein, the first hardness loss component is the product of the first hardness loss coefficient, the absolute impedance deviation value, and the first pressure value; the second hardness loss component is the product of the second hardness loss coefficient, the absolute impedance deviation value, the first pressure value, and the loss enhancement factor.

[0015] Furthermore, the process of determining the fusion strategy based on factors deemed to have a significant impact, in order to output an equivalent roller peeling pressure, includes: Obtain the number of factors determined to have a significant impact; Based on the fact that only some factors are determined to have a significant impact, the first pressure value is summed with the pressure loss components corresponding to all factors determined to have a significant impact to obtain the equivalent roller peeling pressure. Based on the fact that all factors are determined to have a significant impact, it is determined that the first pressure value, the deformation buffer component, the viscous lubrication loss component, and the hardness loss component are all summed to obtain the equivalent roller peeling pressure. If no factor is determined to have a significant impact, the first pressure value is directly adopted, and the equivalent roller peeling pressure is output.

[0016] Furthermore, the process of determining whether the output equivalent roller peeling pressure meets the standard includes, Obtain the absolute pressure deviation between the equivalent roller peeling pressure and the target peeling pressure; The absolute pressure deviation value is compared with the standard pressure deviation value; Based on the fact that the absolute pressure deviation value is greater than the standard pressure deviation value, it is determined that the output equivalent roller peeling pressure does not meet the standard.

[0017] Furthermore, the process of determining the global optimization factor includes, The ratio between the absolute pressure deviation value and the standard pressure deviation value is calculated. Compare the ratio with the standard ratio; The first global optimization factor is determined based on the ratio being less than or equal to the standard ratio; Based on the fact that the ratio is greater than the standard ratio, a second global optimization factor is determined; Wherein, the first global optimization factor is obtained by first calculating the quotient of the ratio and the standard ratio, then calculating the first product of the first optimization intensity coefficient and the quotient, and finally calculating the value 1 plus the first product; the second global optimization factor is obtained by the square of the quotient of the ratio and the standard ratio, then calculating the second product of the second optimization intensity coefficient and the square, and finally calculating the value 1 plus the second product.

[0018] Compared with existing technologies, the beneficial effects of this invention are as follows: By simultaneously acquiring multi-source signals such as roller pressure, fish body dynamic deformation, surface gloss, and equivalent Young's modulus, this invention decomposes the total pressure into buffer or loss components caused by three independent biological factors: deformation, mucus, and hardness, thus achieving physical stripping and precise quantification of complex interferences. Furthermore, by using a closed-loop global optimization factor based on the final pressure deviation, it drives the adaptive calibration of the calculation models for each component. This effectively overcomes the measurement distortion caused by the variability of fish body characteristics, directly outputs the equivalent contact pressure that is strongly correlated with the quality of the skinning process, and significantly improves the accuracy and reliability of pressure detection. This lays the core foundation for achieving precise, stable, and automated control of the skinning process, ultimately achieving the effects of reducing fish meat loss, ensuring skinning quality, and reducing human intervention.

[0019] Furthermore, this invention achieves a precise description and separation of the pressure buffering effect caused by the elastic deformation of the fish body during skinning by quantitatively analyzing the dynamic deformation process of the fish body and calculating its dynamic elastic coefficient. By distinguishing the deformation effect into two states, namely, no significant effect and significant effect, and establishing linear and nonlinear compensation models for the latter two respectively, it can adaptively and with high fidelity calculate the deformation buffering component lost due to deformation. It overcomes the fundamental defect of traditional methods that treat the fish body as a rigid body, resulting in serious distortion of the shaft end pressure measurement value. It provides a precise and reliable deformation compensation data basis for subsequent fusion calculation to obtain the real equivalent contact pressure, thereby significantly improving the authenticity and control accuracy of pressure sensing in the skinning process.

[0020] Furthermore, this invention achieves an objective and quantitative assessment of the mucus lubrication state during fish skinning by performing frequency domain analysis on the gloss signal of the fish surface, extracting the dominant frequency and signal energy ratio, and synthesizing a comprehensive lubrication coefficient. It transforms the difficult-to-measure physical properties of mucus into a precisely calculable lubrication coefficient, and intelligently determines whether it significantly affects roller pressure by comparing it with standard values. Furthermore, it calculates the mucus lubrication loss component according to the degree of influence, introducing nonlinear enhancement compensation for severe influences. This solves the traditional problem of unstable friction coefficient at the roller-fish skin interface due to variable mucus coverage, leading to unpredictable pressure transmission efficiency. It provides a reliable basis for accurately compensating for pressure loss caused by lubrication changes, thereby significantly enhancing the adaptability and robustness of the pressure detection system to complex biological interface conditions.

[0021] Furthermore, this invention achieves a comprehensive quantitative assessment of the hardness and uniformity of fish flesh by performing spatial statistical analysis on the equivalent Young's modulus signal, and normalizes it into a comprehensive hardness impedance coefficient. By classifying the impact of hardness and establishing corresponding loss component calculation models, the invention accurately quantifies the changes in pressure transmission efficiency caused by uneven fish hardness, such as the difference between the belly and back of the fish, and the differences between different individuals. This solves the defect of traditional pressure detection methods that ignore the key biomechanical factor of material hardness, and provides a scientific basis for accurately compensating for pressure loss caused by changes in hardness. This ensures that the final output equivalent pressure can truly reflect the effective force of the roller on complex biological tissue, and significantly improves the adaptability of peeling pressure control to differences in fish material and the stability of the overall process.

[0022] Furthermore, this invention constructs a complete intelligent detection system that integrates multi-source information fusion with self-verification and closed-loop optimization. By dynamically selecting fusion strategies based on real-time biometrics and introducing a self-verification mechanism based on the final pressure deviation, the system ensures the reliability of the output pressure value. When the detection result is substandard, the system initiates a graded optimization algorithm based on the severity of the deviation and drives the collaborative calibration of all component calculation models, rapidly converging to the optimal solution through a finite number of iterations. This enables the pressure detection process to possess self-diagnosis, self-correction, and continuous optimization capabilities, solving the pain points of unreliable results, fixed parameters, and reliance on manual adjustment in traditional methods. Ultimately, it outputs a highly accurate, stable roller pressure value that is strongly correlated with the quality of the peeling process. Attached Figure Description

[0023] Figure 1 This is a schematic block diagram illustrating the steps of a method for detecting the roller pressure of a fish skinning machine according to an embodiment of the present invention; Figure 2This is a logic block diagram of how the deformation buffer component is determined based on the absolute difference between the dynamic elastic coefficient and the standard elastic coefficient in an embodiment of the present invention. Figure 3 This is a logic block diagram illustrating how the viscous lubrication loss component is determined based on the absolute lubrication deviation between the comprehensive lubrication coefficient and the standard lubrication coefficient, according to an embodiment of the present invention. Figure 4 This is a logic block diagram illustrating how the hardness compensation component is determined based on the absolute impedance deviation between the comprehensive hardness impedance coefficient and the standard hardness impedance coefficient, according to an embodiment of the present invention. Detailed Implementation

[0024] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0025] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0026] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0027] Please see Figure 1 The diagram shown is a schematic flowchart of the steps of a method for detecting the roller pressure of a fish skinning machine according to an embodiment of the present invention.

[0028] The present invention provides a method for detecting the roller pressure of a fish skinning machine, comprising: Step S1: Simultaneously acquire the first pressure signal generated when the roller rolls on the surface of the fish, the dynamic deformation signal of the fish surface caused by the roller pressure, the surface gloss signal characterizing the degree of mucus coverage on the fish surface, and the equivalent Young's modulus signal characterizing the hardness of the fish flesh. Step S2: Extract the deformation establishment time constant and steady-state deformation depth based on the dynamic deformation signal, and calculate the dynamic elastic coefficient. Determine whether the current deformation of the fish body affects the roller pressure based on the dynamic elastic coefficient. If it is determined that the current deformation of the fish body will affect the roller pressure, determine the deformation buffer component based on the absolute difference between the dynamic elastic coefficient and the standard elastic coefficient. Step S3: Perform spectrum analysis based on the surface gloss signal, extract the dominant frequency and signal energy ratio, and calculate the comprehensive lubrication coefficient. Determine whether the current amount of mucus on the fish body affects the roller pressure based on the comprehensive lubrication coefficient. Under the condition that the current amount of mucus on the fish body will affect the roller pressure, determine the mucus lubrication loss component based on the absolute lubrication deviation value between the comprehensive lubrication coefficient and the standard lubrication coefficient. Step S4: Based on the equivalent Young's modulus signal, perform spatial statistical analysis to obtain the mean and coefficient of variation of Young's modulus, and calculate the comprehensive hardness resistance coefficient. Determine whether the current hardness of the fish meat affects the roller pressure based on the comprehensive hardness resistance coefficient. Under the condition that the current hardness of the fish meat will affect the roller pressure, determine the hardness loss component based on the absolute impedance deviation between the comprehensive hardness resistance coefficient and the standard hardness resistance coefficient. Step S5: Based on the first pressure signal, filter and denoise the signal to obtain the first pressure value. If only some factors are determined to have a significant impact, a selective fusion strategy is adopted. If all factors are determined to have a significant impact, a full fusion strategy is adopted. If no factors are determined to have a significant impact, the first pressure value is directly adopted, and the equivalent roller peeling pressure is output. Step S6: Under the condition of determining the equivalent roller peeling pressure, calculate the absolute pressure deviation value between the equivalent roller peeling pressure and the target peeling pressure, and determine whether the output equivalent roller peeling pressure meets the standard based on the absolute pressure deviation value. Step S7: If the output equivalent roller peeling pressure is found to be substandard, a global optimization factor is determined based on the ratio of the absolute pressure deviation value to the standard pressure deviation value. This factor optimizes the calculation process of the deformation buffer component, the viscous lubrication loss component, and the hardness compensation component. The deformation buffer component, the viscous lubrication loss component, and the hardness compensation component are recalculated and re-fused to obtain a new equivalent peeling pressure. The roller pressure is then tested under the condition that the new equivalent peeling pressure is qualified.

[0029] Specifically, this invention simultaneously acquires multi-source signals such as roller pressure, fish body dynamic deformation, surface gloss, and equivalent Young's modulus, decomposing the total pressure into buffer or loss components caused by three independent biological factors: deformation, mucus, and hardness. This achieves physical stripping and precise quantification of complex interferences. Furthermore, through a closed-loop global optimization factor based on the final pressure deviation, it drives the adaptive calibration of the calculation models for each component. This effectively overcomes measurement distortion caused by the variability of fish body characteristics, directly outputting the equivalent contact pressure that is strongly correlated with the quality of the skinning process. This significantly improves the accuracy and reliability of pressure detection, laying a core foundation for achieving precise, stable, and automated control of the skinning process. Ultimately, it achieves the effects of reducing fish meat loss, ensuring skinning quality, and reducing human intervention.

[0030] In this embodiment of the invention, the first pressure signal is acquired by a high-precision strain gauge force sensor. The specific process is as follows: the strain gauge force sensor is installed at a critical force-bearing position on the roller support shaft or the direct pressure application mechanism, with its measurement axis aligned with the roller pressure direction; the sensor senses the micro-strain generated by the force on the support structure, amplifies, filters, and performs temperature compensation, and outputs an analog voltage signal proportional to the pressure; the analog voltage signal is then converted into a digital signal by an analog-to-digital converter, which is the first pressure signal; after installation, the high-precision strain gauge force sensor needs to be calibrated at multiple points using standard weights to establish a linear correspondence between the voltage value and the actual pressure.

[0031] In this embodiment of the invention, the specific process for acquiring the dynamic deformation signal is as follows: A laser triangulation displacement sensor is fixedly installed on one side in front of the direction of the roller's movement; firstly, a focused laser spot is projected onto the surface of the fish body that is about to be crushed by the roller through the laser triangulation displacement sensor, and a position-sensitive detector is used to receive the diffuse reflection light reflected back from the surface of the fish body; when the roller's pressure causes the surface of the fish body to undergo concave deformation, the position of the reflected light spot on the detector will move; the processor inside the sensor calculates the absolute distance change value of the fish body surface relative to the initial reference plane in real time based on the light spot displacement and the principle of triangulation distance measurement; the measurement is performed at a sampling frequency higher than the roller's rotation speed, and the sequence of absolute distance change values ​​obtained over time constitutes a dynamic deformation signal reflecting the elastic response of the fish body.

[0032] The sampling frequency setting must ensure that the dynamic process of fish body deformation establishment and recovery caused by roller pressure can be fully captured. A feasible solution is provided: for common fish skinning machine rollers with a linear velocity range of 0.1m / s to 0.5m / s, the sampling frequency can be set to 100Hz to 1000Hz; preferably 500Hz. The high-frequency sequence of absolute distance change values ​​over time constitutes the dynamic deformation signal reflecting the elastic response of the fish body.

[0033] In this embodiment of the invention, the specific acquisition process of the surface gloss signal is as follows: First, a multi-band optical sensing unit is used, which integrates a light source of a specific wavelength, such as a near-infrared light-emitting diode, and a photodetector; the sensing unit is installed at a specific angle on the side of the roller, such as 45°, so that the light emitted by its light source is obliquely illuminating the surface of the fish, and the detector receives the scattered light in the positive reflection direction or at a specific angle; the mucus on the surface of the fish will significantly change its light reflection characteristics. The higher the degree of mucus coverage, the stronger the specular reflection component and the weaker the diffuse reflection component; after measuring the total intensity signal of the reflected light, it is transmitted to the signal processor; the processor performs high-speed sampling of the light intensity signal and performs time-domain and frequency-domain analysis to extract the ratio of DC component to AC component in the signal, as well as the energy distribution characteristics of a specific frequency band; the normalized optical characteristic parameters are weighted and summed to form a dimensionless value characterizing the surface specular reflection intensity, which is the surface gloss signal that quantifies the degree of mucus coverage.

[0034] In this embodiment of the invention, the specific acquisition process of the equivalent Young's modulus signal is as follows: a pair of ultrasonic transceiver probes are used for measurement using the penetration method; the two probes are slightly contacted on the upper and lower sides of the area to be measured on the fish body, one of which acts as the transmitting probe, emitting a low-frequency ultrasonic pulse wave into the fish tissue; the other acts as the receiving probe, detecting the ultrasonic signal after penetrating the fish tissue; the measurement system records the propagation time of the ultrasonic wave from transmission to reception and the amplitude attenuation of the received waveform; since the propagation speed of sound waves in the tissue is proportional to the square root of the Young's modulus of the tissue, and the amplitude attenuation is related to the viscoelasticity and internal structure of the tissue; the processor built into the system substitutes the measured propagation time and attenuation data into the pre-calibrated "acoustic parameter-mechanical parameter" mapping relationship model using standard imitation meat material, and calculates the estimated value of the equivalent Young's modulus of the local tissue of the fish body in real time; by performing rapid scanning measurement in front of the roller contact area, a set of spatial distribution data can be obtained, and the spatial distribution data is statistically analyzed, for example, the arithmetic mean is calculated, and the obtained average value is the equivalent Young's modulus signal.

[0035] Specifically, based on the dynamic deformation signal, the deformation establishment time constant and steady-state deformation depth are extracted, and the dynamic elastic coefficient is calculated. Based on the comparison between the dynamic elastic coefficient and the standard elastic coefficient, it is determined whether the current deformation of the fish body affects the roller pressure. If the dynamic elastic coefficient is less than or equal to the standard elastic coefficient, it is determined that the current deformation of the fish body has no effect on the roller pressure. If the dynamic elastic coefficient is greater than the standard elastic coefficient, it is determined that the current deformation of the fish body has affected the roller pressure.

[0036] In this embodiment of the invention, the specific calculation process of the dynamic elastic coefficient is as follows: First, the collected dynamic deformation signal is analyzed to identify the complete process curve from the moment the roller begins to contact the fish body until the deformation reaches stability; wherein, the steady-state deformation depth is the average value of the deformation after the complete process curve enters the steady stage; the deformation establishment time constant is obtained by fitting the rising segment of the complete process curve to a first-order exponential response model, and its physical meaning is the time required for the deformation to reach approximately 63% of the steady-state depth; finally, the dynamic elastic coefficient is calculated according to the following formula.

[0037] In the formula, For steady-state deformation depth, This refers to the average steady-state deformation depth obtained by performing multiple measurements on standard fish samples under a calibration process. Establish a time constant for deformation. A time constant was established to measure the average deformation of a standard fish sample obtained through multiple measurements under a calibration process.

[0038] In this embodiment of the invention, the standard dynamic elastic coefficient ranges from 0.6 to 0.8, preferably 0.7. The preferred range and preferred value can be determined according to the actual situation, and are not specifically limited here.

[0039] Please see Figure 2 As shown, it is a logic block diagram of an embodiment of the present invention for determining the deformation buffer component based on the absolute difference between the dynamic elastic coefficient and the standard elastic coefficient.

[0040] Specifically, given that the current deformation of the fish body will affect the roller pressure, the deformation buffer component is determined based on the comparison between the absolute difference of the dynamic elastic coefficient and the standard elastic coefficient and the standard absolute difference. If the absolute difference is less than or equal to the standard absolute difference, then the first deformation buffer component is determined; If the absolute difference is greater than the standard absolute difference, then the second deformation buffer component is determined.

[0041] In this embodiment of the invention, the absolute difference is the difference between the dynamic elastic coefficient and the standard dynamic elastic coefficient.

[0042] In this embodiment of the invention, the standard absolute difference ranges from 0.05 to 0.15, preferably 0.1. The preferred range and preferred value can be determined according to the actual situation, and are not specifically limited here.

[0043] In this embodiment of the invention, the first deformation buffer component is calculated according to the following formula:

[0044] In the formula, K1 is the first deformation buffer component; K2 is the first loss coefficient, which is obtained through calibration experiments on working conditions affected by slight deformation. Its physical meaning is the pressure compensation amount corresponding to the unit absolute difference. The actual value taken under the condition that the absolute difference is less than or equal to the standard absolute difference; The first pressure value is obtained by filtering and denoising the first pressure signal.

[0045] In this embodiment of the invention, the second deformation buffer component is calculated according to the following formula:

[0046] In the formula, K1 is the second deformation buffer component; K2 is the second loss coefficient, which is obtained through calibration experiments on the working condition affected by severe deformation, and is usually greater than K1. This refers to the actual value taken under the condition that the absolute difference is greater than the standard absolute difference; is the first pressure value; n is the scaling factor, a constant greater than 1, which is the ratio of the actual absolute difference to the standard absolute difference under the condition that the absolute difference is greater than the standard absolute difference.

[0047] Specifically, this invention achieves a precise description and separation of the pressure buffering effect caused by the elastic deformation of the fish body during skinning by quantitatively analyzing the dynamic deformation process of the fish body and calculating its dynamic elastic coefficient. By distinguishing the deformation effect into two states, namely, no significant effect and significant effect, and establishing linear and nonlinear compensation models for the latter two respectively, it can adaptively and with high fidelity calculate the deformation buffering component lost due to deformation. It overcomes the fundamental defect of traditional methods that treat the fish body as a rigid body, resulting in serious distortion of the shaft end pressure measurement value. It provides an accurate and reliable deformation compensation data basis for subsequent fusion calculation to obtain the real equivalent contact pressure, thereby significantly improving the authenticity and control accuracy of pressure sensing in the skinning process.

[0048] Specifically, based on the surface gloss signal, spectral analysis is performed to extract the dominant frequency and signal energy ratio, and a comprehensive lubrication coefficient is calculated. The comparison between the comprehensive lubrication coefficient and the standard lubrication coefficient determines whether the current amount of mucus on the fish body affects the roller pressure. If the overall lubrication coefficient is less than or equal to the standard lubrication coefficient, it is determined that the current amount of mucus on the fish body does not affect the roller pressure. If the overall lubrication coefficient is greater than the standard lubrication coefficient, it is determined that the current amount of mucus on the fish body has affected the roller pressure.

[0049] In this embodiment of the invention, the specific calculation process of the comprehensive lubrication coefficient is as follows: First, the surface gloss signal is subjected to a fast Fourier transform to convert it from the time domain to the frequency domain; in the frequency domain spectrum, the frequency point with the highest energy is determined as the dominant frequency, which reflects the main rhythm of light intensity changes caused by flow or fluctuation on the viscous surface; the signal energy ratio is the ratio of the energy of the frequency domain signal in a narrow band near the dominant frequency to the total energy of the entire frequency band. The higher the ratio, the stronger the signal periodicity; finally, the dominant frequency after normalization is weighted and summed with the signal energy ratio to obtain the comprehensive lubrication coefficient.

[0050] The weighting coefficient of the dominant frequency ranges from 0.5 to 0.7, preferably 0.6, and the weighting coefficient of the signal energy ratio ranges from 0.3 to 0.5, preferably 0.4.

[0051] In this embodiment of the invention, the standard lubrication coefficient ranges from 0.4 to 0.6, preferably 0.5. The preferred range and preferred value can be determined according to the actual situation, and are not specifically limited here.

[0052] Please see Figure 3 As shown, it is a logic block diagram of the present invention for determining the viscous lubrication loss component based on the absolute lubrication deviation value between the comprehensive lubrication coefficient and the standard lubrication coefficient.

[0053] Specifically, given that the current amount of mucus on the fish body affects the roller pressure, the mucus lubrication loss component is determined based on the comparison between the absolute lubrication deviation of the comprehensive lubrication coefficient and the standard lubrication coefficient and the standard absolute lubrication deviation. If the absolute lubrication deviation value is less than or equal to the standard absolute lubrication deviation value, then the first viscous lubrication loss component is determined; If the absolute lubrication deviation value is greater than the standard absolute lubrication deviation value, then the second viscous lubrication loss component is determined.

[0054] In this embodiment of the invention, the absolute lubrication deviation value is the difference between the comprehensive lubrication coefficient and the standard lubrication coefficient.

[0055] In this embodiment of the invention, the standard absolute lubrication deviation value ranges from 0.1 to 0.2, preferably 0.15. The preferred range and preferred value can be determined according to the actual situation, and are not specifically limited here.

[0056] In this embodiment of the invention, the first viscous lubrication loss component is calculated according to the following formula:

[0057] In the formula, This is the first component of viscous lubrication loss. The first lubrication loss coefficient is obtained through calibration experiments on working conditions where the absolute lubrication deviation value is less than or equal to the standard absolute lubrication deviation value. Its physical meaning is the proportion of pressure loss caused by a unit lubrication deviation. The actual value taken under the condition that the absolute lubrication deviation value is less than or equal to the standard absolute lubrication deviation value; This is the first pressure value.

[0058] In this embodiment of the invention, the second viscous lubrication loss component is calculated according to the following formula:

[0059] In the formula, This is the second component of viscous lubrication loss. This is the second lubrication loss coefficient, which is usually greater than... ; The actual value taken under the condition that the absolute lubrication deviation value is greater than the standard absolute lubrication deviation value; is the first pressure value; m is the lubrication enhancement factor, a constant greater than 1, which is the ratio of the actual absolute lubrication deviation value to the standard absolute lubrication deviation value under the condition that the absolute lubrication deviation value is greater than the standard absolute lubrication deviation value.

[0060] Specifically, this invention achieves an objective and quantitative assessment of the mucus lubrication state during fish skinning by performing frequency domain analysis on the gloss signal of the fish surface, extracting the dominant frequency and signal energy ratio, and synthesizing a comprehensive lubrication coefficient. It transforms the difficult-to-measure physical properties of mucus into a precisely calculable lubrication coefficient, and intelligently determines whether it significantly affects roller pressure by comparing it with standard values. Furthermore, it calculates the mucus lubrication loss component according to the degree of influence, introducing nonlinear enhancement compensation for severe influences. This solves the traditional problem of unstable friction coefficient at the roller-fish skin interface due to variable mucus coverage, leading to unpredictable pressure transmission efficiency. It provides a reliable basis for accurately compensating for pressure loss caused by lubrication changes, thereby significantly enhancing the adaptability and robustness of the pressure detection system to complex biological interface conditions.

[0061] Specifically, spatial statistical analysis is performed based on the equivalent Young's modulus signal to obtain the mean and coefficient of variation of the Young's modulus, and the comprehensive hardness resistance coefficient is calculated. Based on the comparison between the comprehensive hardness resistance coefficient and the standard resistance coefficient, it is determined whether the current fish body hardness affects the roller pressure. If the overall hardness resistance coefficient is less than or equal to the standard resistance coefficient, it is determined that the current hardness of the fish meat does not affect the roller pressure. If the overall hardness resistance coefficient is greater than the standard resistance coefficient, it is determined that the current hardness of the fish meat has affected the roller pressure.

[0062] In this embodiment of the invention, the specific method for obtaining the comprehensive hardness resistance coefficient is as follows: First, statistical analysis is performed on multiple measurement points of the equivalent Young's modulus signal in the area of ​​the fish body that the roller is about to contact; simultaneously, the arithmetic mean and coefficient of variation of the Young's modulus of all measurement points are calculated, i.e., the ratio of the standard deviation to the mean; then, the comprehensive hardness resistance coefficient is calculated according to the following formula.

[0063] In the formula, The overall hardness resistance coefficient; It is the arithmetic mean; To reference Young's modulus, it was obtained by statistically averaging the Young's modulus measured on standard fish samples under calibrated conditions; This is the variation weighting coefficient, used to adjust the contribution of hardness non-uniformity to the overall impedance. Its typical value range is 0.1-0.5, preferably 0.25. is the coefficient of variation.

[0064] In this embodiment of the invention, the standard impedance coefficient ranges from 0.9 to 1.5, preferably 1.2. The preferred range and preferred value can be determined according to the actual situation, and are not specifically limited here.

[0065] Please see Figure 4 As shown, it is a logic block diagram of the present invention for determining the hardness compensation component based on the absolute impedance deviation between the comprehensive hardness impedance coefficient and the standard hardness impedance coefficient.

[0066] Specifically, given that the firmness of the fish's flesh affects the roller pressure, a hardness compensation component is determined based on the comparison between the absolute impedance deviation of the comprehensive hardness impedance coefficient and the standard hardness impedance coefficient and the standard absolute impedance deviation. If the absolute impedance deviation value is less than or equal to the standard absolute impedance deviation value, then the first hardness loss component is determined. If the absolute impedance deviation value is greater than the standard absolute impedance deviation value, then the second hardness loss component is determined.

[0067] In this embodiment of the invention, the absolute impedance deviation value is the difference between the comprehensive hardness impedance coefficient and the standard hardness impedance coefficient.

[0068] In this embodiment of the invention, the standard absolute impedance deviation value ranges from 0.15 to 0.35, preferably 0.2. The preferred range and preferred value can be determined according to the actual situation, and are not specifically limited here.

[0069] In this embodiment of the invention, the first hardness loss component is calculated according to the following formula:

[0070] In the formula, This represents the first hardness loss component; The first hardness loss coefficient is obtained by calibration experiments on working conditions where the absolute impedance deviation value is less than or equal to the standard absolute impedance deviation value. Its physical meaning is the proportion of pressure loss caused by unit impedance deviation. The actual value taken under the condition that the absolute impedance deviation value is less than or equal to the standard absolute impedance deviation value; This is the first pressure value.

[0071] In this embodiment of the invention, the second hardness loss component is calculated according to the following formula:

[0072] In the formula, This represents the second hardness loss component; This is the second hardness loss coefficient, which is typically greater than... ; This is the actual value taken under the condition that the absolute impedance deviation value is greater than the standard absolute impedance deviation value; This is the first pressure value; The loss enhancement factor is the ratio of the actual absolute impedance deviation to the standard absolute impedance deviation under the condition that the absolute impedance deviation is greater than the standard absolute impedance deviation, and is a constant greater than 1.

[0073] Specifically, this invention achieves a comprehensive quantitative assessment of the hardness and uniformity of fish flesh by performing spatial statistical analysis on the equivalent Young's modulus signal, and normalizes it into a comprehensive hardness impedance coefficient. By classifying the impact of hardness and establishing corresponding loss component calculation models, it accurately quantifies the changes in pressure transmission efficiency caused by uneven fish hardness, such as the difference between the belly and back of the fish, and the differences between different individuals. This solves the defect of traditional pressure detection methods that ignore the key biomechanical factor of material hardness, and provides a scientific basis for accurately compensating for pressure loss caused by changes in hardness. This ensures that the final output equivalent pressure can truly reflect the effective force of the roller on complex biological tissue, and significantly improves the adaptability of peeling pressure control to differences in fish material and the stability of the overall process.

[0074] Specifically, based on the first pressure value and according to the number of significantly influential factors, a fusion strategy for determining the output equivalent roller peeling pressure is established, wherein... If only some factors are determined to have a significant impact, a selective fusion strategy is adopted. If all factors are determined to have a significant impact, then a complete fusion strategy will be adopted. If no factor is determined to have a significant impact, the first pressure value is directly adopted, and the equivalent roller peeling pressure is output.

[0075] In this embodiment of the invention, the selective fusion strategy is to sum the first pressure value with the pressure loss components corresponding to all factors that are determined to have a significant impact, and obtain the equivalent roller peeling pressure.

[0076] The pressure loss component includes the deformation buffer component, the viscous lubrication loss component, and the hardness loss component.

[0077] In this embodiment of the invention, the complete fusion strategy is to sum the first pressure value with the deformation buffer component, the viscous lubrication loss component, and the hardness loss component to obtain the equivalent roller peeling pressure.

[0078] Specifically, given the equivalent roller peeling pressure, the absolute pressure deviation between the equivalent roller peeling pressure and the target peeling pressure is calculated. Based on the comparison between the absolute pressure deviation and the standard pressure deviation, it is determined whether the output equivalent roller peeling pressure meets the standard. If the absolute pressure deviation value is less than or equal to the standard pressure deviation value, then the output equivalent roller peeling pressure is determined to meet the standard. If the absolute pressure deviation value is greater than the standard pressure deviation value, then the output equivalent roller peeling pressure is determined to be substandard.

[0079] In this embodiment of the invention, the standard pressure deviation value is taken as 5% to 15% of the target tare pressure, preferably 10%. The preferred range and preferred value can be determined according to the actual situation, and are not specifically limited here.

[0080] Specifically, given that the output equivalent roller peeling pressure is substandard, a global optimization factor is determined based on the comparison between the ratio of the absolute pressure deviation value to the standard pressure deviation value and the standard ratio. If the ratio is less than or equal to the standard ratio, then the first global optimization factor is determined; If the ratio is greater than the standard ratio, then the second global optimization factor is determined.

[0081] In this embodiment of the invention, the standard ratio ranges from 1.0 to 2.0, preferably 1.5. The preferred value and the preferred range can be determined according to the actual situation, and are not specifically limited here.

[0082] In this embodiment of the invention, the first global optimization factor is calculated according to the following formula:

[0083] In the formula, It is the first global optimization factor; The first optimized strength coefficient is a constant, with a value ranging from 0.05 to 0.15, preferably 0.1. This is the actual ratio of the absolute pressure deviation value to the standard pressure deviation value. This is the standard ratio.

[0084] In this embodiment of the invention, the second global optimization factor is calculated according to the following formula:

[0085] In the formula, It is the second global optimization factor; The second optimized strength coefficient is a constant, with a value ranging from 0.1 to 0.3, preferably 0.2. This is the actual ratio of the absolute pressure deviation value to the standard pressure deviation value. This is the standard ratio.

[0086] In this embodiment of the invention, under the condition of determining the global optimization factor, the deformation buffer component, the viscous lubrication loss component, and the hardness loss component are recalculated based on the global optimization factor, and then re-fused to obtain a new equivalent pressure, thereby completing the detection of roller pressure.

[0087] Specifically, for the deformation buffer component: multiply the global optimization factor λ by the first compensation coefficient k1 or the second compensation coefficient k2 to obtain the updated compensation coefficient, i.e., k1'=λ×k1 or k2'=λ×k2.

[0088] For the viscous lubrication loss component: multiply the global optimization factor by the first lubrication loss coefficient C1 or the second lubrication loss coefficient C2 to obtain the updated lubrication loss coefficient, i.e., C1' = λ×C1 or C2' = λ×C2.

[0089] For the hardness loss component: multiply the global optimization factor by the first hardness loss coefficient H1 or the second hardness loss coefficient H2 to obtain the updated hardness loss coefficient, i.e., H1'=λ×H1 or H2'=λ×H2.

[0090] Using the updated compensation coefficient, lubrication loss coefficient, and hardness loss coefficient, the optimized deformation buffer component, viscous lubrication loss component, and hardness loss component are recalculated. The updated equivalent roller peeling pressure is recalculated according to the full fusion strategy or the selective fusion strategy, and step S6 is executed to determine whether it meets the standard. If the new equivalent roller peeling pressure meets the standard, it is output as the final detection result. If the new equivalent roller peeling pressure still does not meet the standard, the current result is used as input, and steps S7 and S8 are repeated for the next optimization iteration until a qualified peeling pressure value is output as the roller pressure value for a single detection, or the preset maximum number of iterations is reached, such as 4 times. If the maximum number of iterations is reached and the standard is still not met, the system outputs the current optimal peeling pressure value as the roller pressure value for a single detection.

[0091] Specifically, this invention constructs a complete intelligent detection system that integrates multi-source information fusion with self-verification and closed-loop optimization. By dynamically selecting fusion strategies based on real-time biometrics and introducing a self-verification mechanism based on the final pressure deviation, the system ensures the reliability of the output pressure value. When the detection result is substandard, the system initiates a graded optimization algorithm based on the severity of the deviation and drives the collaborative calibration of all component calculation models, rapidly converging to the optimal solution through a finite number of iterations. This enables the pressure detection process to possess self-diagnosis, self-correction, and continuous optimization capabilities, solving the pain points of unreliable results, fixed parameters, and reliance on manual adjustment in traditional methods. Ultimately, it outputs a highly accurate, stable roller pressure value that is strongly correlated with the quality of the peeling process.

[0092] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A method for detecting the pressure of rollers in a fish skinning machine, characterized in that, include, The system simultaneously acquires the first pressure signal generated when the roller rolls on the surface of the fish, the dynamic deformation signal of the fish surface, the gloss signal of the fish surface, and the equivalent Young's modulus signal. Based on the dynamic deformation signal, the dynamic elastic coefficient is obtained to determine whether the deformation of the fish body affects the roller pressure and to determine the deformation buffer component. The comprehensive lubrication coefficient is obtained based on the surface gloss signal to determine whether the amount of mucus on the fish body affects the roller pressure and to determine the mucus lubrication loss component. Based on the equivalent Young's modulus signal, the comprehensive hardness impedance coefficient is obtained to determine whether the hardness of the fish meat affects the roller pressure and to determine the hardness loss component. Based on the first pressure signal, a first pressure value is obtained, and a fusion strategy is determined according to the factors that are determined to have a significant impact, so as to output an equivalent roller peeling pressure. Based on the target peeling pressure, it is determined whether the output equivalent roller peeling pressure meets the standard, and a global optimization factor is determined to optimize the calculation process of each loss component and obtain the optimized new loss component. Based on the optimized new loss components, a new equivalent peeling pressure is obtained by re-fusion, and the roller pressure is tested under the condition that the new equivalent peeling pressure is qualified.

2. The method for detecting roller pressure in a fish skinning machine according to claim 1, characterized in that, The process of determining whether the deformation of the fish body affects the roller pressure includes, Based on the dynamic deformation signal, the deformation establishment time constant and steady-state deformation depth are extracted; The dynamic elastic coefficient is calculated based on the deformation establishment time constant and the steady-state deformation depth. The dynamic elastic coefficient is compared with the standard dynamic elastic coefficient; Based on the fact that the dynamic elastic coefficient is greater than the standard elastic coefficient, it is determined that the current deformation of the fish body has affected the roller pressure.

3. The method for detecting the roller pressure of a fish skinning machine according to claim 2, characterized in that, The process of determining the deformation buffer component includes: A first pressure value is obtained based on the first pressure signal; The absolute difference is calculated based on the dynamic elastic coefficient and the standard dynamic elastic coefficient. The absolute difference is compared with the standard absolute difference; The first deformation buffer component is determined based on the absolute difference being less than or equal to the standard absolute difference. The second deformation buffer component is determined based on the fact that the absolute difference is greater than the standard absolute difference. The first deformation buffer component is the product of the first loss coefficient, the absolute difference, and the first pressure value; the second deformation buffer component is the product of the second loss coefficient, the absolute difference, the first pressure value, and the scaling factor.

4. The method for detecting the roller pressure of a fish skinning machine according to claim 3, characterized in that, The process of determining whether the amount of mucus on the fish's body affects the roller pressure includes, Spectral analysis is performed on the surface gloss signal to extract the dominant frequency and signal energy ratio. The comprehensive lubrication coefficient is calculated based on the dominant frequency and the signal energy ratio. The overall lubrication coefficient is compared with the standard lubrication coefficient; Based on the fact that the overall lubrication coefficient is greater than the standard lubrication coefficient, it is determined that the current amount of mucus on the fish body has affected the roller pressure.

5. The method for detecting roller pressure in a fish skinning machine according to claim 4, characterized in that, The process of determining the component of viscous lubrication loss includes: The absolute lubrication deviation value is calculated based on the comprehensive lubrication coefficient and the standard lubrication coefficient. The absolute lubrication deviation value is compared with the standard absolute lubrication deviation value; Based on the fact that the absolute lubrication deviation value is less than or equal to the standard absolute lubrication deviation value, the first viscous lubrication loss component is determined; Based on the fact that the absolute lubrication deviation value is greater than the standard absolute lubrication deviation value, the second viscous lubrication loss component is determined; Wherein, the first viscous lubrication loss component is the product of the first lubrication loss coefficient, the absolute lubrication deviation value, and the first pressure value; the second viscous lubrication loss component is the product of the second lubrication loss coefficient, the absolute lubrication deviation value, the first pressure value, and the lubrication enhancement factor.

6. The method for detecting roller pressure in a fish skinning machine according to claim 5, characterized in that, The process of determining whether the firmness of the fish meat affects the roller pressure includes, Spatial statistical analysis is performed based on the equivalent Young's modulus signal to obtain the mean and coefficient of variation of Young's modulus; The comprehensive hardness resistance coefficient is calculated based on the mean and the coefficient of variation. The comprehensive hardness resistance coefficient is compared with the standard hardness resistance coefficient; Based on the fact that the overall hardness impedance coefficient is greater than the standard impedance coefficient, it is determined that the current hardness of the fish meat has affected the roller pressure.

7. The method for detecting roller pressure in a fish skinning machine according to claim 6, characterized in that, The process of determining the hardness loss component includes: The absolute impedance deviation value is calculated based on the comprehensive hardness impedance coefficient and the standard hardness impedance coefficient. The absolute impedance deviation value is compared with the standard absolute impedance deviation value; The first hardness loss component is determined based on the absolute impedance deviation value being less than or equal to the standard absolute impedance deviation value. The second hardness loss component is determined based on the fact that the absolute impedance deviation value is greater than the standard absolute impedance deviation value. Wherein, the first hardness loss component is the product of the first hardness loss coefficient, the absolute impedance deviation value, and the first pressure value; the second hardness loss component is the product of the second hardness loss coefficient, the absolute impedance deviation value, the first pressure value, and the loss enhancement factor.

8. The method for detecting roller pressure in a fish skinning machine according to claim 7, characterized in that, The process of determining the fusion strategy based on factors deemed to have a significant impact, in order to output an equivalent roller peeling pressure, includes the following: Obtain the number of factors determined to have a significant impact; Based on the fact that only some factors are determined to have a significant impact, the first pressure value is summed with the pressure loss components corresponding to all factors determined to have a significant impact to obtain the equivalent roller peeling pressure. Based on the fact that all factors are determined to have a significant impact, it is determined that the first pressure value is summed with the deformation buffer component, the viscous lubrication loss component and the hardness loss component to obtain the equivalent roller peeling pressure. If no factor is determined to have a significant impact, the first pressure value is directly adopted, and the equivalent roller peeling pressure is output.

9. The method for detecting roller pressure in a fish skinning machine according to claim 8, characterized in that, The process of determining whether the output equivalent roller peeling pressure meets the standard includes, Obtain the absolute pressure deviation between the equivalent roller peeling pressure and the target peeling pressure; The absolute pressure deviation value is compared with the standard pressure deviation value; Based on the fact that the absolute pressure deviation value is greater than the standard pressure deviation value, it is determined that the output equivalent roller peeling pressure does not meet the standard.

10. The method for detecting roller pressure in a fish skinning machine according to claim 9, characterized in that, The process of determining the global optimization factor includes: The ratio between the absolute pressure deviation value and the standard pressure deviation value is calculated. Compare the ratio with the standard ratio; The first global optimization factor is determined based on the ratio being less than or equal to the standard ratio; Based on the fact that the ratio is greater than the standard ratio, a second global optimization factor is determined; Wherein, the first global optimization factor is obtained by first calculating the quotient of the ratio and the standard ratio, then calculating the first product of the first optimization intensity coefficient and the quotient, and finally calculating the value 1 plus the first product; the second global optimization factor is obtained by the square of the quotient of the ratio and the standard ratio, then calculating the second product of the second optimization intensity coefficient and the square, and finally calculating the value 1 plus the second product.

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