Liquid viscosity detection system

Abstract

A liquid viscosity detection system comprises a case, a mechanism transmission module, a viscosity detection module, a power module, a control and data processing module and a sample temperature control module, and the control and data processing module is connected with the mechanism transmission module, the viscosity detection module and the sample temperature control module through signal lines. Control and data interaction of each module are realized; the power supply module supplies power to the control and data processing module, the viscosity detection module, the mechanism transmission module and the sample temperature control module through wires; and the sample temperature control module is used for controlling the sample temperature in the detection process.

Description

[0001] The present invention relates to the field of viscosity detection, and in particular to a liquid viscosity detection system Background Art

[0002] With the continuous progress of industrial production and scientific and technological development, viscosity testing is increasingly used in industries such as chemical, grain and food. High-precision viscosity measurement and precise temperature control are of great significance for product quality control and process optimization. However, the viscosity testing instruments currently on the market generally have problems such as complex mechanical structure, low temperature control accuracy, high manufacturing and maintenance costs, and are difficult to meet the requirements for detection accuracy and reliability in industrial production. Traditional viscosity testing instruments often use complex transmission mechanisms, which not only increases the equipment failure rate, but also greatly increases manufacturing and maintenance costs. At the same time, since temperature has a significant impact on viscosity measurement results, the temperature control systems of existing instruments often have problems such as low accuracy and slow response speed, which affects the accuracy of the measurement results. Summary of the invention

[0003] The purpose of the present invention is to provide a high-precision liquid viscosity detection system that can better solve the above-mentioned problems.

[0004] In order to achieve the purpose of the present invention, the following technical solutions are adopted:

[0005] A liquid viscosity detection system comprises a chassis, a mechanism transmission module, a viscosity detection module, a power module, a control and data processing module and a sample temperature control module, wherein the control and data processing module is respectively connected with the mechanism transmission module, the viscosity detection module and the sample temperature control module through signal lines to realize control and data interaction of each module; the power module provides power supply to the control and data processing module, the viscosity detection module, the mechanism transmission module and the sample temperature control module through wires; and the sample temperature control module is used to control the sample temperature during the detection process.

[0006] The liquid viscosity detection system, wherein: the viscosity detection module is installed on the top of the chassis, and the bottom of the viscosity detection module is connected to the mechanism transmission module installed in the chassis.

[0007] The liquid viscosity detection system, wherein: the mechanism transmission module includes a lifting linear motor, a clamping linear motor and a frame, and the lifting linear motor and the clamping linear motor are fixedly mounted on the frame.

[0008] The liquid viscosity detection system, wherein: the upper part of the lifting linear motor is connected to the viscosity detection module.

[0009] The liquid viscosity detection system, wherein: the sample temperature control module includes a copper heating block, a self-priming water pump, a heating rod, a temperature sensor, a baffle, and a copper block guide rail.

[0010] The liquid viscosity detection system, wherein: the self-priming water pump is fixed on the bottom plate of the frame, the left baffle is fixed on the upper part of the base, the left and right baffles are arranged vertically on the ground at a certain distance and parallel to each other, the upper and lower ends of each baffle are fixedly connected to a copper heating block, the upper two copper heating blocks 61 are arranged opposite to each other, and the lower two copper heating blocks are arranged opposite to each other.

[0011] The liquid viscosity detection system, wherein: the copper heating block has a semicircular notch on each side away from the baffle, and after the two opposite copper heating blocks are matched, the two semicircular notches are combined into a circular opening for accommodating the sample barrel.

[0012] The liquid viscosity detection system, wherein: the push rod end of the clamping motor is arranged directly opposite to the right baffle.

[0013] The liquid viscosity detection system, wherein: a mounting hole is opened at each of the four corners of the upper and lower parts of the left and right baffles, and four copper block guide rails are respectively inserted into the mounting holes at the four corners of the two baffles. The guide rails pass through the left baffle and are inserted into the connecting hole of the machine base and are fixed by bolts.

[0014] The liquid viscosity detection system, wherein: the left and right baffles are also connected to each other through at least one release spring; the right baffle can move left and right along the guide rail.

[0015] The liquid viscosity detection system, wherein: the copper heating block is provided with a hollow inner cavity, the upper end of the water inlet copper tube is connected to the water inlet of the lower part of the copper heating block, the lower end is connected to one end of the water inlet elbow, and the other end of the water inlet elbow is connected to the self-priming water pump through a water pipe; the upper end of the water outlet copper tube is connected to the water outlet of the upper part of the copper heating block, the lower end is connected to one end of the water outlet three-way elbow, and the other end of the water outlet three-way elbow is connected to the self-priming water pump through a water pipe.

[0016] The liquid viscosity detection system, wherein: the viscosity detection module includes a viscosity sensor, a blade connector, a stirring paddle, a sample barrel support column, a sample barrel support column adjustment screw, a support plate, a guide rail rack, a viscosity collection sensor support plate, and a sample barrel.

[0017] The liquid viscosity detection system, wherein: the viscosity sensor is fixed on the viscosity collection sensor support plate, the motor shaft of the viscosity sensor is exposed downward outside the opening through the opening on the sensor support plate, the paddle connector is connected to the motor shaft, the stirring paddle is fixedly connected to the paddle connector, the sample barrel opening is upward, the bottom is supported by the sample barrel support column, the bottom of the sample barrel support column is threadedly connected to the upper part of the sample barrel support column adjusting screw rod, and the lower part of the adjusting screw rod is threadedly connected to the support plate.

[0018] The liquid viscosity detection system, wherein: the guide rail frame and the outer frame frame are connected by screws, the upper part of the support plate is fixedly connected to the guide rail, and the lower part of the support plate is fixedly connected to the push rod end of the lifting linear motor; the guide rail extends upward from the upper part of the support plate, passes through the guide through hole of the guide rail frame, and is fixedly connected to the bottom of the sensor support plate.

[0019] A viscosity detection method is performed by the liquid viscosity detection system as described above, the method comprising:

[0020] (a) low-pass filtering is performed on the current signal sequence value of the brushless motor collected by the viscosity collector to generate a new current signal sequence a;

[0021] (b) performing dimension reduction processing on the current signal sequence a according to time to obtain a new current signal sequence b at each second;

[0022] (c) Linearly changing the current signal sequence b to obtain the viscosity value sequence c;

[0023] (d) Perform feature value extraction on the viscosity value sequence c to extract the feature value corresponding to the sample.

[0024] The method, wherein:

[0025] In the step (a), the collected current signal value is low-pass filtered, and the filtering algorithm is:

[0026] 1. Initialization: For the collected current signal sequence I(n), initialize the filter output Y(n), where n represents the time of the signal;

[0027] 2. Filtering operation: For the signal value I(n) at each moment, use the weighted average formula to filter. The specific calculation formula is:

[0028] Y(n)=α·I(n)+(1-α)·Y(n-1)

[0029] Among them, Y(n) is the output signal after filtering, I(n) is the collected current signal sequence value, Y(n-1) is the filtering result at the previous moment, and α is the filtering coefficient.

[0030] The method, wherein:

[0031] In the step (b), the data dimension reduction processing algorithm is used to smooth the new current sequence a after filtering, and the specific steps include:

[0032] Data dimensionality reduction: Perform dimensionality reduction on the new current sequence a data. Assume that at the kth moment, the filtered current signal value is y k , where k represents the sampling time point;

[0033] where y k is the value after dimensionality reduction at the k-th sampling point, and y k+i is the current signal value of adjacent sampling points. m is the number of points for averaging. By calculating the average value of each sampling point and its adjacent m points, the original value of this sampling point is replaced.

[0034]

[0035] For the last m sampling points in the signal sequence, directly use the values after filtering in step a, that is, no smoothing processing is performed;

[0036] Signal curve generation: Connect the signal values after dimensionality reduction together to form a sequence b of current values at each second.

[0037] The method described above, where:

[0038] In the above step (c), input the current signal sequence b at each second after dimensionality reduction into the following linear conversion formula to convert the current value into the corresponding viscosity value:

[0039] y = -54.7832 + 0.6634x

[0040] where y is the converted viscosity sequence and x is the current value sequence obtained in step b.

[0041] The method described above, where:

[0042] In the above step (d), the viscosity at the last moment is the final viscosity;

[0043] In the above step (d), input the converted viscosity value sequence V into the following local extreme value detection method to identify the peak viscosity, peak time, trough viscosity, trough time, and breakdown value;

[0044] The local extreme value detection method includes:

[0045] Traverse each data point in the viscosity data sequence V. Let the index of the current data point be i, and its corresponding viscosity value be V(i);

[0046] Compare the current data point V(i) with its adjacent previous and next data points V(i - 1) and V(i + 1);

[0047] If V(i) > V(i - 1) and V(i) > V(i + 1) are satisfied, then judge that the current data point V(i) is a local maximum value;

[0048] If V(i) < V(i - 1) and V(i) < V(i + 1) are satisfied, then judge that the current data point V(i) is a local minimum value;

[0049] The local maximum represents the peak viscosity, and the corresponding time is the peak time; the local minimum represents the trough viscosity, and the corresponding time is the trough time; the difference between the peak viscosity and the trough viscosity is the falling value; the absolute value of the difference between the final viscosity and the trough viscosity is the regeneration value.

[0050] The method, wherein:

[0051] In the step (d), the converted viscosity value sequence V is used to detect the gelatinization temperature by using the derivative method, and the acceleration of the viscosity value change is analyzed by the second-order derivative method to determine the gelatinization temperature;

[0052] Specific methods include:

[0053] (1) Calculation of first-order derivative:

[0054] First, based on the viscosity value sequence V, the first-order derivative V is calculated using the central difference method: ′ (i):

[0055]

[0056] Among them, V(i+1), V(i-1) are viscosity values, and i is the time point;

[0057] (2) Calculation of second-order derivative:

[0058] Based on the first-order derivative V ′ (i):, again use the central difference method to calculate the second-order derivative V ″ (i):

[0059]

[0060] Among them, V ″ (i) represents the change in the rate of change of the viscosity value at time point i, i.e., acceleration;

[0061] Gelatinization point identification:

[0062] For the obtained second-order derivative sequence, the time point corresponding to the first maximum value greater than 0 is the gelatinization start time, and the copper block temperature returned by the temperature sensor 612 at this time point is the gelatinization temperature;

[0063] (4) Result output:

[0064] The output gelatinization temperature is when the second-order derivative reaches the first maximum value, and the copper block temperature returned by the temperature sensor is the gelatinization temperature. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 This is the overall schematic diagram of the high-precision liquid viscosity detection system;

[0066] Figure 2 This is a schematic diagram of the internal structure of a high-precision liquid viscosity detection system;

[0067] Figure 3 Assembly drawing for heating components;

[0068] Figure 4-1 It is a schematic diagram of the heating copper block structure;

[0069] Figure 4-2 Sectional view of the sensor location

[0070] Figure 5 Schematic diagram of viscosity measurement structure;

[0071] Figure 6 This is the circuit wiring diagram of the viscosity detection device;

[0072] Figure 7 Real-time collection of starch gelatinization viscosity information data; DETAILED DESCRIPTION

[0073] The following is combined with Figure 1-7 , the specific implementation modes of the present invention are described in detail. The implementation modes are exemplary and are only used to explain the present invention, and should not be understood as limiting the present invention. Obviously, the embodiments described in the present invention are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present invention.

[0074] "One embodiment" or "some embodiments" described in this specification means that one or more embodiments of the present invention include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, in this specification, the terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0075] like Figure 1 , 2, the present invention relates to a high-precision liquid viscosity detection system, including a chassis 1, a mechanism transmission module 2, a viscosity detection module 3, a control and data processing module 4 ( Figure 2), power module 5, sample temperature control module 6 and industrial computer 7. The above modules 2-7 are organically integrated in the chassis 1 to form a compact and efficient system. Among them, the control and data processing module 4 is the core of the system, and is connected to the mechanism transmission module 2, the viscosity detection module 3, the power module 5 and the sample temperature control module 6 through signal lines to achieve precise control and data interaction of each module. The power module 5 provides a stable power supply for the control and data processing module 4, the viscosity detection module 3, the mechanism transmission module 2, the sample temperature control module 6 and the industrial computer 7 through wires to ensure the normal operation of each part of the system. The liquid viscosity detection equipment in the prior art often has scattered modules, resulting in a large device size and complex operation. The present invention integrates multiple key modules in the chassis, greatly reducing the size of the device, and improving the portability and ease of operation of the device. The control and data processing module 4 adopts advanced algorithms, which can process the data fed back by the viscosity detection module and the sample temperature control module in real time and accurately, ensuring the high accuracy of the detection results. The sample temperature control module 6 can accurately control the sample temperature through the corresponding temperature compensation algorithm during the detection process. The chassis 1 is also equipped with a USB interface 9, and a host computer can be connected to the interface via a data cable to achieve fast data transmission and remote control, further improving the practicality and convenience of the system.

[0076] The viscosity detection module 3 is installed on the top of the chassis 1 , and the bottom of the viscosity detection module 3 is connected to the mechanism transmission module 2 installed in the chassis 1 .

[0077] like Figure 2 As shown, the mechanism transmission module 2 in the present invention includes a lifting linear motor 22, a clamping linear motor 21 and a frame on which they are located. The lifting linear motor 22 and the clamping linear motor 21 are fixedly mounted on the frame. Among them, the upper part of the lifting linear motor 22 is connected to the viscosity detection module 3. This design enables the viscosity detection module 3 to move up and down, thereby flexibly performing detection operations on samples at different positions. The clamping linear motor 21 is responsible for clamping and releasing the sample temperature control module 6.

[0078] In terms of structural design, the lifting linear motor 22 is firmly mounted on the frame bottom plate in the chassis 1 by bolts to ensure its stability during operation. The clamping linear motor 21 is firmly mounted on the base by bolts, and the base is fixedly mounted on the frame bottom plate. This connection method ensures the accuracy and reliability of the clamping operation. Compared with traditional liquid viscosity detection equipment, the mechanism transmission module of the present invention adopts a simple and efficient transmission route design. By reasonably arranging the lifting linear motor 22 and the clamping linear motor 21, complex and error-prone transmission mechanisms are avoided, and the transmission efficiency and accuracy are improved. The module realizes fully automated mechanism action. Whether it is the up and down movement of the viscosity detection module 3 or the clamping and loosening operation of the sample temperature control module 6, no manual intervention is required, which greatly improves the degree of automation of the detection process, reduces human operation errors, and improves detection efficiency. Through the above design, the mechanism transmission module plays a vital role in the high-precision liquid viscosity detection system, ensuring the efficient and accurate operation of the entire system.

[0079] like Figure 3 As shown in , 4 , the sample temperature control module 6 of the present invention includes a copper heating block 61, a self-priming water pump 62, a heating rod 611, a temperature sensor 612, a baffle 63, a copper block guide rail 64, a release spring 65, a water outlet copper pipe 66 and a water inlet copper pipe 67, a water outlet three-way elbow 68, and a water inlet elbow 69.

[0080] The self-priming water pump 62 is fixed on the bottom plate of the frame, the left baffle 63 is fixed on the upper part of the machine base, and the left and right baffles 63 are arranged vertically on the ground at a certain distance and parallel to each other. The upper and lower ends of each baffle 63 are fixedly connected to a copper heating block 61, and the fixing method can be that the copper heating block and the baffle 63 are directly connected with bolts. The upper two copper heating blocks 61 are arranged oppositely, and the lower two copper heating blocks 61 are arranged oppositely. The copper heating block 61 has a semicircular notch on the side away from the baffle 63. After the two opposite copper heating blocks 61 are matched, the two semicircular notches are assembled into a circular opening for accommodating the sample barrel 39. The push rod end of the clamping motor 21 is arranged opposite to the right baffle 63, and the push rod end is provided with a buffer material to avoid rigid contact with the right baffle 63. The temperature sensor 612 is arranged on the copper heating block 61 to detect the temperature of the copper heating block 61.

[0081] like Figure 4-1 and Figure 4-2 As shown, the heating rod 611, the temperature sensor 612 and the copper heating block 61 are gap-fitted and installed in the installation hole opened on the copper heating block 61. The gap between the hole wall is coated with thermal conductive silicone to bond the two together.

[0082] The left and right baffles 63 have a mounting hole at each of the four corners of the upper and lower parts. Four copper guide rails 64 are inserted into the mounting holes at the four corners of the two baffles, respectively. One end of the guide rail 64 passes through the left baffle and is inserted into the machine base connection hole and is fixed to the frame base by bolts. The other end of the guide rail 64 passes through the mounting hole of the right baffle and is exposed. The left and right baffles 63 are also connected to each other by at least one release spring 65. The right baffle 63 can move left and right along the guide rail 64.

[0083] When the clamping motor 21 is not clamped, the right baffle 63 is in a loosened state under the action of the release spring 65, so that there is a 4-5mm gap between the left and right copper blocks and the right copper block does not directly contact the clamping motor 21. When the clamping motor 21 is clamped, the push rod of the clamping motor 21 is fully extended and contacts the right copper block. After the right copper block moves to the left, the left and right copper blocks fit tightly against each other, and the two semicircular notches are combined into a circular opening. The sample barrel 34 is placed in the circular opening and clamped by the left and right copper blocks for better heat transfer.

[0084] The copper heating block 61 is provided with a hollow inner cavity, the water outlet copper tube 66 is inserted into the hollow inner cavity and glued to the copper heating block 61 through thermal conductive silicone, the upper end of the water inlet copper tube 66 is flush with the upper part of the copper heating block 61, and the lower end extends beyond the copper heating block and is connected to the upper half of the water outlet tee. The water inlet copper tube 67 is inserted into the water outlet copper tube 66 from bottom to top, and its top inserted into the water outlet copper tube 66 is lower than the top of the water outlet copper tube 66 (water enters from the water inlet copper tube 67 and is pressed close to the top of the copper block. Since the water inlet copper tube is shorter than the water outlet copper tube, water flows out from the gap between the two to take away heat). The outer diameter of the water inlet copper tube 67 is slightly smaller than the water outlet copper tube 66, which is convenient for inserting the water outlet copper tube 66. The lower end of the water outlet copper tube 66 is connected to the first port of the tee 68. After the lower part of the water inlet copper tube 67 is inserted from the first port of the tee 68, it is exposed from the second port opposite to the first port. The exposed end is provided with a reducing section, which is the same size as the outer diameter of the water outlet copper tube 66, and the end of the reducing section is connected to the first port of the elbow 69.

[0085] The second port of the elbow 69 is connected to the self-priming water pump 63 through a water pipe, and the third port of the tee 68 is connected to a drain pipe.

[0086] During cooling, water is pumped through the water inlet elbow 69 to the water pipe 67 by the self-priming water pump 62. After reaching the top, water flows out through the gap between the inner wall of the outlet pipe and the outer wall of the inlet pipe through the water outlet tee 68 and is discharged through the drain pipe.

[0087] The above structure does not require a guide rail to be inserted between the two copper blocks, which reduces the processing difficulty and cost of the copper blocks, and can achieve self-priming cooling through the self-priming water pump 62.

[0088] like Figure 5As shown, the viscosity detection module 3 includes a viscosity sensor 31, a blade connector 32, a stirring paddle 33, a sample barrel support column 34, a sample barrel support column adjustment screw 35, a support plate 36, a guide rail frame 37, a viscosity collection sensor support plate 38, and a sample barrel 39.

[0089] The brushed motor 31 (also called viscosity sensor) is fixed on the viscosity collection sensor support plate 38, and the motor shaft is exposed downward outside the opening on the sensor support plate 38. The paddle connector 32 is connected to the motor shaft of the brushed motor 31 through an interference fit through a flange, and the stirring paddle 33 is connected to the paddle connector 32 through a buckle to achieve circumferential fixation. The stirring paddle 33 is used to transmit the sample resistance to the brushed motor. The sample barrel 39 opens upward, and the bottom contacts the upper end of the sample barrel support column 34 and is supported by the sample barrel support column 34. The bottom of the sample barrel support column 34 is threadedly connected to the upper part of the sample barrel support column adjusting screw 35, and the lower part of the adjusting screw 35 is threadedly connected to the support plate 36. By rotating the screw 35, the sample barrel support column 34 can be moved up and down to adjust its position.

[0090] The guide rail frame 37 is connected to the frame by screws, the upper part of the support plate 36 is fixedly connected to the two stainless steel guide rails by screws, and the lower part of the support plate 36 is fixedly connected to the push rod end of the lifting linear motor 22 by screws; the stainless steel guide rail extends upward from the upper part of the support plate 36, passes through the guide through hole of the guide rail frame 37, and is fixedly connected to the bottom of the sensor support plate 38.

[0091] By moving the push rod of the linear motor 22 up and down, the support plate 36 can be moved up and down along the stainless steel rail, thereby driving the sensor support plate 38 to move up and down. During the viscosity measurement process, the lifting linear motor 22 retracts the push rod, so that the sample barrel 39 enters the circular opening formed by the copper heating block 61, and the sample barrel 39 is clamped to achieve viscosity measurement. After the measurement is completed, the sample barrel 39 is released, the lifting linear motor 22 extends the push rod, and the sample barrel rises to the outside of the sample temperature control module and can be taken out.

[0092] like Figure 2 and Figure 6 As shown, the control and data processing module 4 is composed of a viscosity collector 41 , a temperature and transmission controller 42 , a transmission controller 43 , a bidirectional thyristor 44 and a bracket 45 .

[0093] The viscosity collector 41 is connected to the brush motor 31 through a signal line, and is connected to the industrial computer 7 by means of a USB data line. The temperature and transmission controller 42 is connected to the transmission controller 43 by a signal line, and then controls the up and down movement, clamping and loosening operations of the sample barrel. The temperature and transmission controller 42 is connected to the bidirectional thyristor 44 and the temperature sensor through wires, wherein the bidirectional thyristor 44 is connected to the heating rod 611 to control the heating power, and the temperature sensor 612 is responsible for feedback of the temperature information in the copper block. The temperature and transmission controller 42 is connected to the industrial computer 7 through a USB line to achieve temperature control. The viscosity collector 41, the temperature and transmission controller 42 and the industrial computer are all powered by the power module 5. Compared with other types of viscometers, this device adopts a modular structure, which is convenient for maintenance and updating, has significant advantages in accuracy and control, and is low in cost.

[0094] The working process of the viscosity detection system includes the preheating stage, the sensor calibration stage, the sample collection stage, and the data storage and processing stage. In the preheating stage, the heating rod is powered on to heat and transfer the heat to the copper block to heat the liquid sample in the sample barrel, and the temperature sensor feeds back the temperature information. In the sensor calibration stage, the viscosity sensor rotates to obtain data, and returns the information to the controller after processing the data. In the sample collection stage, the rotation speed of the brushed motor and the temperature of the temperature control module are controlled according to the custom program, and the current response signal value of the motor is obtained by changing the temperature over time at a constant speed. In the data storage and processing stage, the collected viscosity information is stored and processed by operating the computer to finally obtain the test results.

[0095] Wherein: processing the collected current response signal value includes the following steps:

[0096] (a) Preprocessing the current signal sequence value of the brushless motor collected by the viscosity collector, performing low-pass filtering on the original data, and generating a new current signal sequence a;

[0097] (b) performing dimension reduction processing on the current signal sequence a according to time to obtain a new current signal sequence b at each second;

[0098] (c) Linearly changing the current signal sequence b to obtain the viscosity value sequence c;

[0099] (d) Perform feature value extraction on the viscosity value sequence c to extract the feature value corresponding to this sample.

[0100] in:

[0101] In the step (a), the collected current signal value is low-pass filtered to reduce the influence of signal noise generated by non-target factors on the detection signal.

[0102] The specific filtering algorithm is:

[0103] 1. Initialization: For the collected current signal sequence I(n), initialize the filter output Y(n), where n represents the time of the signal.

[0104] 2. Filtering operation: Use the weighted average formula to filter the signal value I(n) at each moment. The specific calculation formula is:

[0105] Y(n)=α·I(n)+(1-α)·Y(n-1)

[0106] Among them, Y(n) is the output signal after filtering, I(n) is the collected current signal sequence value, Y(n-1) is the filtering result at the previous moment, and α is the filtering coefficient, which ranges from 0 to 1. Usually, a suitable value is selected according to the response speed of the system. A smaller value can better suppress high-frequency noise.

[0107] By performing the low-pass filtering process on the original data, a new current signal sequence a is generated.

[0108] In the step (b), the data dimension reduction processing algorithm is used to smooth the new current sequence a after filtering, and the specific steps of the algorithm are as follows:

[0109] 1. Data dimensionality reduction: Perform dimensionality reduction on the new current sequence a data. Assume that at the kth moment, the filtered current signal value is y k , where k represents the sampling time point.

[0110] Among them, y k is the dimension-reduced value of the k-th sampling point, y k+i is the current signal value of adjacent sampling points, m is the number of points for averaging, for example, m can be 30, 60, 90, 120. By calculating the average value of each sampling point and its adjacent m points, the original value of the sampling point is replaced to achieve data dimensionality reduction and smoothing.

[0111]

[0112] Process the last m points: For the last m sampling points in the signal sequence, directly use the values ​​filtered in step a, that is, no smoothing is performed.

[0113] Signal curve generation: Through the above method, a new set of dimension-reduced data is obtained. The signal values ​​after dimension reduction are connected together to form a current value sequence b at each second.

[0114] In the step (c), the current signal sequence b at each second after dimension reduction is input into the following linear conversion formula to convert the current value into the corresponding viscosity value:

[0115] y = -54.7832 + 0.6634x

[0116] Among them, y is the converted viscosity sequence, and x is the current value sequence obtained in step b.

[0117] This linear relationship is obtained through experiments. The specific method is as follows: First, measure the current signal values of different standard viscosity liquids under different conditions and take their average values. Then, using the relationship between these average current signal values and the known standard viscosity values, the parameters -54.7832 and 0.6634 of the regression curve are obtained by using the linear regression analysis method.

[0118] Through the above steps, a discrete data sequence V of viscosity changing with time is obtained, where y and V are equal.

[0119] When the detected liquid is a starch solution, there are parameters such as gelatinization temperature, peak viscosity, peak time, trough viscosity, trough time, final viscosity, breakdown value, and retrogradation value during the gelatinization process of starch. In step d, these parameters can be calculated.

[0120] In step (d), the viscosity at the last moment is the final viscosity.

[0121] In step (d), the converted viscosity value sequence V is input into the following local extremum detection method to identify peak viscosity, peak time, trough viscosity, trough time, and breakdown value.

[0122] The specific local extremum detection method includes:

[0123] Traverse each data point in the viscosity data sequence V. Let the index of the current data point be i, and its corresponding viscosity value be V(i);

[0124] Compare the current data point V(i) with its adjacent previous and next data points V(i - 1) and V(i + 1);

[0125] If V(i) > V(i - 1) and V(i) > V(i + 1) are satisfied, then it is determined that the current data point V(i) is a local maximum;

[0126] If V(i) < V(i - 1) and V(i) < V(i + 1) are satisfied, then it is determined that the current data point V(i) is a local minimum.

[0127] Record the indices and their corresponding viscosity values of the detected local maxima and local minima respectively, and generate an extremum data list. Through the above method, the local extremum points in the viscosity data can be effectively extracted.

[0128] The local maximum represents the peak viscosity, and the corresponding time is the peak time; the local minimum represents the trough viscosity, and the corresponding time is the trough time; the difference between the peak viscosity and the trough viscosity is the falling value; the absolute value of the difference between the final viscosity and the trough viscosity is the regeneration value.

[0129] In the step (d), the converted viscosity value sequence V is used to detect the gelatinization temperature by using the derivative method, and the acceleration of the viscosity value change is analyzed by the second-order derivative method to determine the gelatinization temperature.

[0130] The specific method is as follows:

[0131] (1) Calculation of first-order derivative:

[0132] First, based on the viscosity value sequence V, the first-order derivative V is calculated using the central difference method: ′ (i):

[0133]

[0134] Among them, V(i+1), V(i-1) are viscosity values, and i is the time point.

[0135] (2) Calculation of second-order derivative:

[0136] Based on the first-order derivative V ′ (i):, again use the central difference method to calculate the second-order derivative V ″ (i):

[0137]

[0138] Among them, V ″ (i) represents the change in the rate of change of the viscosity value at time point i, that is, the acceleration.

[0139] Gelatinization point identification:

[0140] For the obtained second-order derivative sequence, the time point corresponding to the first maximum value greater than 0 is the gelatinization start time, and the copper block temperature returned by the temperature sensor 612 at this time point is the gelatinization temperature.

[0141] (4) Result output:

[0142] When the output gelatinization temperature reaches the first maximum value of the second-order derivative, the copper block temperature returned by the temperature sensor 612 is the gelatinization temperature.

[0143] The system, wherein: different temperature control methods are used at different times, as follows:

[0144] (t0) For the preheating stage, heating and water cooling are used together. Heating is regulated by PID, and cooling is controlled by switch quantity. The difference between the target temperature and the temperature of the heated copper block is set as input to determine which method to use.

[0145] (t1) During the operation, in the temperature maintenance stage, PID is used for temperature control. The difference between the target temperature and the actual temperature is used as input and input into the PID controller to output the relevant voltage.

[0146] (t2) During the operation, in the temperature linear rise stage, the quadratic integral PID is used for temperature control. The difference between the target temperature and the actual temperature is used as input to enter the quadratic integral PID to output the relevant voltage, thereby achieving precise temperature control.

[0147] (t3) During the operation, the temperature drops linearly. The switch quantity is used for temperature control, and the target temperature is compared with the actual temperature. When the target temperature is greater than the actual temperature at a certain moment, the water pump is turned off. When the target temperature is less than the actual temperature at a certain moment, the water pump is turned on to continue cooling.

[0148] The system, wherein: during the time (t0), the temperature should be set to be consistent with the initial temperature during viscosity measurement when operating the instrument to ensure the accuracy of the data. In order to achieve precise adjustment of the viscosity value, a proportional-integral-differential (PID) control algorithm is used to perform real-time feedback adjustment on the system. The specific implementation steps of the PID algorithm are as follows:

[0149] (1) Error calculation

[0150] Assume the target viscosity is V ref , the current viscosity value detected in real time is V cur , then the system error e(t) is expressed as:

[0151] e(t)=V ref -V cur

[0152] (2)PID controller output:

[0153] The PID controller calculates the control quantity u(t) based on the error value e(t). The PID control formula is as follows:

[0154]

[0155] in:

[0156] Kp is the proportional coefficient, which is used to quickly respond to error changes;

[0157] Ki is the integral coefficient, which eliminates the steady-state error of the system;

[0158] Kd is the differential coefficient, which suppresses the rapid change of error and enhances the stability of the system.

[0159] is the cumulative value of the error;

[0160] is the rate of change of error over time.

[0161] (3) Real-time adjustment of control quantity:

[0162] The calculated control quantity u(t) is input to the actuator to adjust the regulating unit (temperature regulating device) in the viscosity control system. The actuator adjusts the process parameters according to u(t) so that the actual temperature gradually approaches the target temperature.

[0163] The system, wherein: during the time (t1), the above PID temperature control method is adopted.

[0164] The system, wherein: during the time (t2), the PID controller and the temperature device form a type I system, in which the integral link is only once, which can effectively track the ramp signal. However, there is a steady-state error, and an integral link is now added to effectively improve the temperature control accuracy. To realize the control function of the type II system, it can be expanded based on the structure of the PID controller, as follows:

[0165] PID expansion controller output:

[0166]

[0167] Others are the same as above PID control.

[0168] The newly added K i2 It is the quadratic integral coefficient, which is used to adjust the intensity of the quadratic integral term.

[0169] In the system, during the time (t3), the program cyclically determines whether the actual temperature is greater than the target temperature during the cooling period, and if so, turns on the self-priming water pump 62, otherwise turns off the self-priming water pump 62. The cyclic determination time is 500ms.

[0170] During the operation of the instrument, the actual temperature of the liquid in the sample barrel is different from the temperature of the heating block displayed by the machine because the temperature sensor is embedded in the copper heating block 61. A correction algorithm can be used to correct this limitation.

[0171] Here’s how:

[0172] The actual liquid temperature lags behind the heating block temperature, and the lag is a function of the rate of temperature change and the apparent viscosity of the starch sample.

[0173] TL=-8.51-0.93(RR)+0.079(PV)+0.0043(RR)(PV)

[0174] -0.0017(RR) 2 -0.00014(PV) 2

[0175] Where: RR is the heating rate, TL is the hysteresis temperature (actual liquid temperature), and PV is the peak viscosity.

[0176] The advantage of this control system is that different temperature algorithms are used in different time periods, which saves time and greatly improves the accuracy of temperature control.

[0177] The present invention can achieve high-precision viscosity measurement, and at the same time, an innovative water cooling system with a water suction pump 62 is designed to ensure accurate control of the sample temperature. This design not only greatly improves the measurement accuracy, but also simplifies the mechanical structure, reduces the manufacturing and maintenance costs, and provides a more reliable and economical solution for viscosity detection in industrial production.

[0178] The above are only preferred embodiments of the present invention, and are not intended to limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not intended to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A liquid viscosity detection system, comprising a chassis, a mechanism transmission module, a viscosity detection module, a power module, a control and data processing module and a sample temperature control module, characterized in that: The control and data processing module is connected to the mechanism transmission module, viscosity detection module, and sample temperature control module through signal lines to realize control and data interaction of each module; the power supply module provides power supply to the control and data processing module, viscosity detection module, mechanism transmission module, and sample temperature control module through wires; the sample temperature control module is used to control the sample temperature during the detection process.

2. The liquid viscosity detection system according to claim 1, characterized in that: The viscosity detection module is installed on the top of the chassis, and the bottom of the viscosity detection module is connected with the mechanism transmission module installed in the chassis.

3. The liquid viscosity detection system according to claim 1, characterized in that: The mechanism transmission module comprises a lifting linear motor, a clamping linear motor and a frame, and the lifting linear motor and the clamping linear motor are fixedly installed on the frame.

4. The liquid viscosity detection system according to claim 3, characterized in that: The upper part of the lifting linear motor is connected with the viscosity detection module.

5. The liquid viscosity detection system according to claim 1, characterized in that: The sample temperature control module includes a copper heating block.

6. The liquid viscosity detection system according to claim 1, characterized in that: The viscosity detection module includes a viscosity sensor.

7. A viscosity detection method, characterized in that The method is performed by the liquid viscosity detection system according to any one of claims 1 to 6, and the method comprises: (a) low-pass filtering is performed on the current signal sequence value of the brushless motor collected by the viscosity collector to generate a new current signal sequence a; (b) performing dimension reduction processing on the current signal sequence a according to time to obtain a new current signal sequence b at each second; (c) Linearly changing the current signal sequence b to obtain the viscosity value sequence c; (d) Perform feature value extraction on the viscosity value sequence c to extract the feature value corresponding to the sample.

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