Quality control method and equipment of fish and shrimp feed and storage medium

Abstract

The embodiment of the invention provides a fish and shrimp feed quality control method, equipment and a storage medium, and belongs to the technical field of feed production. The method comprises the steps that processing data of a target feed product in a preset first historical time period are obtained, and the processing data comprise raw material feeding and impurity removing processing data, smashing processing data, oil-water mixing processing data and granulation equipment processing parameters; determining historical impurity index parameters of the target feed product according to the raw material feeding and impurity removal processing data; determining historical raw material quality parameters of the target feed product according to the crushing processing data; determining historical finished product quality parameters of the target feed product according to the oil-water mixing processing data and the processing parameters of the granulation equipment; and outputting early warning prompt information according to the historical impurity index parameters, the historical raw material quality parameters and the historical finished product quality parameters. According to the embodiment of the invention, the management and control strength of feed products can be improved, so that the production cost is controllable.

Description

Technical Field

[0001] This application relates to the technical field of feed production, and particularly to a quality control method, device and storage medium for fish and shrimp feed. Background Art

[0002] During the production process of feed products, multiple key production links that affect the feed finished products will be involved, such as raw material feeding and cleaning, primary crushing, primary mixing, secondary crushing, secondary mixing, and granulation (such as conditioning, puffing, etc.). However, in the prior art, only the two key production links of raw material feeding and processing and the final finished product are often detected, and the quality control of the entire forming process of the feed finished product cannot be carried out. When quality problems occur in the final feed finished product, it is often difficult to find the production and processing links where problems occur, and the quality control of feed products is relatively poor, resulting in uncontrollable production costs. Summary of the Invention

[0003] The main purpose of the embodiments of this application is to propose a quality control method, device and storage medium for fish and shrimp feed, which can improve the control strength of feed products and make production costs controllable.

[0004] To achieve the above object, the first aspect of the embodiments of this application proposes a quality control method for fish and shrimp feed, and the method includes: Obtain the processing data of the target feed product within a preset first historical time period, where the processing data includes raw material feeding and impurity removal processing data, crushing processing data, oil-water mixing processing data, and granulation equipment processing parameters; Determine the historical impurity index parameter of the target feed product according to the raw material feeding and impurity removal processing data; Determine the historical raw material quality parameter of the target feed product according to the crushing processing data; Determine the historical finished product quality parameter of the target feed product according to the oil-water mixing processing data and the granulation equipment processing parameters; Output a warning prompt message according to the historical impurity index parameter, the historical raw material quality parameter, and the historical finished product quality parameter.

[0005] To achieve the above object, the second aspect of the embodiments of this application proposes an electronic device, which includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the quality control method for fish and shrimp feed according to any item of the first aspect above.

[0006] To achieve the above object, a third aspect of the embodiments of the present application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the quality control method for fish and shrimp feed according to any one of the first aspect.

[0007] The quality control method, device and storage medium for fish and shrimp feed proposed in the present application collect raw material feeding and impurity removal processing data, crushing processing data, oil-water mixing processing data and pelletizing equipment processing parameters, and process the raw material feeding and impurity removal processing data, crushing processing data, oil-water mixing processing data and pelletizing equipment processing parameters in the first historical time period respectively to obtain the historical impurity index parameters, historical raw material quality parameters and historical finished product quality parameters of the target feed product, so as to realize the quality control of multiple key production links of the feed finished product. At the same time, by outputting warning prompt information, the quality control of a single production link and the entire production line can be realized. Compared with related technologies, the embodiments of the present application can realize the automatic monitoring of the quality of multiple key production links of the feed finished product, with greater quality monitoring intensity, so as to make the production cost controllable by improving the control intensity of the feed product. Brief Description of the Drawings

[0008] Figure 1 is a flowchart of the quality control method for fish and shrimp feed provided by the present application; Figure 2 is a flowchart of the fish feed production process in an embodiment of the quality control method for fish and shrimp feed provided by the present application; Figure 3 is a flowchart of the shrimp feed production process in an embodiment of the quality control method for fish and shrimp feed provided by the present application; Figure 4 is a structural diagram of the hardware structure corresponding to the quality control method for fish and shrimp feed provided by the present application. Detailed Description of the Embodiments

[0009] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0010] It should be noted that although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order from the module division in the device or the order in the flowchart. Terms such as "first" and "second" in the specification, claims and the above-mentioned drawings are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence.

[0011] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terms used herein are for the purpose of describing embodiments of this application only and are not intended to limit this application.

[0012] The quality control method of the fish and shrimp feed of this application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multi-processor systems, and so on. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This application can also be practiced in a distributed computing environment, where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0013] It can be understood that, with reference to Figure 1 as shown, according to a quality control method of fish and shrimp feed provided by an embodiment of this application, the method includes: Step S100, obtain the processing data of the target feed product within a preset first historical time period, where the processing data includes raw material feeding and impurity removal processing data, crushing processing data, oil-water mixing processing data, and pelletizing equipment processing parameters; Step S200, determine the historical impurity index parameters of the target feed product according to the raw material feeding and impurity removal processing data; Step S300, determine the historical raw material quality parameters of the target feed product according to the crushing processing data; Step S400, determine the historical finished product quality parameters of the target feed product according to the oil-water mixing processing data and the pelletizing equipment processing parameters; Step S500, output a warning prompt message according to the historical impurity index parameters, historical raw material quality parameters, and historical finished product quality parameters.

[0014] Therefore, by collecting the data of raw material feeding and impurity removal processing, crushing processing, oil-water mixing processing, and pelletizing equipment processing parameters, and by separately processing the data of raw material feeding and impurity removal processing, crushing processing, oil-water mixing processing, and pelletizing equipment processing parameters in the first historical time period, the historical impurity index parameters, historical raw material quality parameters, and historical finished product quality parameters of the target feed product are obtained, so as to realize the quality control of multiple key production links of the feed finished product. At the same time, by outputting warning prompt information, the quality control of a single production link and the entire production line can be realized. Compared with related technologies, the embodiments of the present application can realize the automatic monitoring of the quality of multiple key production links of the feed finished product, with greater quality monitoring intensity, so as to make the production cost controllable by improving the control intensity of the feed product.

[0015] The embodiments of the present application do not limit the duration corresponding to the first historical time period, and those skilled in the art can perform data analysis with a month or a quarter as the time period.

[0016] The data of raw material feeding and impurity removal processing are the monitoring data of the impurity removal process for each raw material of the target feed product, which may include, for example, the single continuous feeding amount, the impurity type of the generated impurities, the impurity content, etc. In some other embodiments, the data of raw material feeding and impurity removal processing also include the impurity removal equipment parameters. The embodiments of the present application do not limit this.

[0017] The crushing processing data are the monitoring data of the process of performing one or both of the first crushing and the second crushing on each raw material of the target feed product, and can be selectively set according to the formula and process requirements of the target feed product.

[0018] The oil-water mixing processing data are the monitoring data of the target feed product during the second mixing process.

[0019] The pelletizing equipment processing parameters are the monitoring data of the target feed product during the pelletizing process.

[0020] The historical impurity index parameters characterize the impurity content status of each raw material in the target feed product.

[0021] The historical raw material quality parameters characterize the quality of each raw material in the target feed product itself.

[0022] The historical finished product quality parameters characterize the finished product quality of the target feed product.

[0023] Exemplarily, referring to Figure 2 the production process of the fish feed product shown, including raw material feeding and cleaning -> first crushing, first mixing -> second crushing -> second mixing -> puffing -> drying -> oil spraying -> cooling -> sieving -> finished product packing.

[0024] Among them, Figure 2 the raw material feeding and cleaning in Figure 2 include the removal of impurities such as caked materials and sundries like ropes (which can be removed by means of sieve plates, etc.). In some other embodiments, this step also includes removing iron impurities by a permanent magnet drum. Sensors can be set at the output positions such as the feeding port, the permanent magnet drum, and the sieve plate, so as to determine the single - continuous feeding amount, the type of impurities, and the impurity content, and further obtain the raw material feeding and impurity - removing processing data. The embodiments of the present application can selectively set different devices according to actual needs to realize the pretreatment of raw materials in the raw material feeding and cleaning step.

[0025] Among them, Figure 2 The primary crushing in Figure 2 can be used for processing larger - granular raw materials such as soybean meal, peanut bran, rapeseed meal, etc. A hammer - mill can be set in the primary crushing step for crushing, and then sieving to obtain the expected primary crushing result. At this time, by collecting the equipment crushing parameters of the hammer - mill and monitoring the states of the raw materials before and after sieving, the primary crushing processing data can be obtained. In some other embodiments, due to different growth requirements of fish and shrimp, secondary crushing is also required. In some embodiments, after secondary crushing with an ultramicro - mill, sieving is carried out. At this time, by collecting the equipment crushing parameters of the ultramicro - mill and monitoring the states of the raw materials before and after sieving, the secondary crushing processing data of the secondary crushing can be obtained. The primary crushing processing data and the secondary crushing processing data are used as the crushing processing data. Among them, when only one crushing step is involved, the crushing processing parameters only involve the processing data of the corresponding crushing step.

[0026] Among them, Figure 2 In Figure 2 , in the secondary mixing, oil and water are added to the material after secondary crushing. Among them, the secondary mixing can be carried out by a mixer. At this time, by collecting the mixing processing configuration parameters of the mixer, the oil - water ratio, and monitoring the mixed material output after mixing, the oil - water mixing processing data can be obtained.

[0027] Among them, Figure 2 In Figure 2 , the puffing is to add steam to the mixed material after secondary mixing and then carry out puffing operations, such as using a puffing machine to carry out puffing operations to form a finished product with a moisture content of about 24% - 28% in the material. The granulation equipment processing parameters are obtained by collecting the equipment operation parameters from the addition of steam to obtaining a finished product with 24% - 28% moisture content.

[0028] Exemplarily, referring to Figure 3 the production process of the shrimp feed product shown in Figure 3 includes raw material feeding and cleaning -> primary crushing, primary mixing -> secondary crushing -> secondary mixing -> conditioning -> granulation -> cooking and stabilization -> drying -> cooling -> crushing -> sieving -> finished product packing.

[0029] Among them,Figure 3 The process of raw material feeding and cleaning -> primary crushing, primary mixing -> secondary crushing -> secondary mixing in Figure 2 is similar to that in , and will not be elaborated here one by one. Figure 3 In , tempering is achieved by adding steam to temper the dry powder after secondary mixing into a wet powder with a moisture content of 15 - 17% and a temperature above 95 °C. By collecting the equipment operation parameters during the process from the increased water volume to obtaining the wet powder with a moisture content of 15 - 17% and a temperature above 95 °C, the processing parameters of the granulation equipment can be obtained.

[0030] It can be understood that the raw material feeding and impurity removal processing data includes the single - continuous feeding amount of each raw material, the impurity type corresponding to the single - continuous feeding amount, and the impurity content corresponding to each impurity type; based on the raw material feeding and impurity removal processing data, the historical impurity index parameters of the target feed product are determined, including: According to the single - continuous feeding amount and the impurity content, calculate the impurity proportion of each impurity type corresponding to each raw material of the target feed product; Obtain the weight coefficient of each impurity type corresponding to each raw material in the target feed product; According to the impurity proportion and the corresponding weight coefficient, determine the total first - impurity proportion of each raw material; Obtain the second - impurity proportion corresponding to each raw material in multiple consecutive second - historical time periods before the first - historical time period of the target feed product; the second - impurity proportion and the first - impurity proportion have the same source parameters; According to the first - impurity proportion and multiple second - impurity proportions, determine the supply quality trend of each raw material; According to the supply quality trend of each raw material, obtain the historical impurity index parameters.

[0031] It can be understood that the single - continuous feeding amount is the weight of a raw material fed continuously. It can be determined by setting a sensor at the feeding port. Since the required processing duration in different production links is different and the total amount ratio of different raw materials is also different, the single - continuous feeding amount is set to ensure more convenient operation during the ratio - making process.

[0032] The impurity content corresponds one - to - one with the impurity type. Calculating the historical impurity index parameters based on the single - continuous feeding amount can be used to evaluate the impact of the raw material feeding and cleaning link on the subsequent link processing. If the historical impurity index parameters indicate a low content of available raw materials, it will inevitably lead to a longer waiting time in the subsequent links. At this time, the feeding strategy for the feeding port can be changed based on the historical impurity index parameters, which can improve the processing efficiency.

[0033] The influence of different impurity types characterized by weight coefficients on the quality of the subsequent finished feed products. For example, if the influence of iron is the greatest, the weight coefficient of iron is set to be the largest. Among them, the sum of the weight coefficients of different impurity types is 1.

[0034] In the embodiments of the present application, for different quantities in the second historical stage, having the same source parameters indicates the same supply channel, such as the same merchant and the same supply place, or different merchants and the same supply place. The supply quality trend can be obtained by curve fitting the proportion of the first impurity and the proportion of the second impurity, so as to determine the quality stability of the corresponding supply channel, and further determine whether to change the supply channel based on the supply quality trend.

[0035] In some embodiments, a view interface can be provided to display the historical impurity index parameters. It can be understood that, in some embodiments, the curves corresponding to each supply quality trend are displayed in the same coordinate system, and different merchants are plotted with different colors and different supply places are plotted with different line types for the trends, so as to more intuitively control the quality based on the historical impurity index parameters.

[0036] It can be understood that according to the crushing processing data, the historical raw material quality parameters of the target feed product are determined, including: Determine the available crushing amount, waste amount, equipment crushing parameters, raw material crushing image data, and waste image data of each raw material to be crushed from the crushing processing data; Calculate the available crushing proportion of each raw material to be crushed according to the available crushing amount and the waste amount; Obtain the expected available crushing proportion corresponding to the equipment crushing parameters; Determine the crushing deviation value of each raw material to be crushed according to the available crushing proportion and the expected available crushing proportion; Input the waste image data and the raw material crushing image data into a preset crushing model for crushing category classification respectively to obtain the waste crushing status data and the raw material crushing status data; Obtain the historical raw material quality parameters according to the crushing deviation value, the raw material crushing status data, and the waste crushing status data of each raw material to be crushed.

[0037] The waste amount and the available crushing amount can be determined by a weighing sensor. The available crushing amount / waste amount is equal to the available crushing proportion. The expected available crushing proportion can be determined by looking up a table. The crushing capabilities of different crushing devices are clear. The expected available crushing proportion can be set as a specific range or a specific proportion value. The crushing deviation value characterizes the difference between the actual crushing situation and the lowest expected crushing situation. For example, if the expected available crushing proportion is set to [x, y], then the crushing deviation value is (available crushing proportion - x).

[0038] Refer to Figure 2As shown, the waste image data is the image data of the sieved waste after crushing, and the raw material crushing image data is the image data of the available raw materials after sieving. The embodiments of the present application do not limit how to set the camera for shooting, and those skilled in the art can selectively set it according to the actual production line structure.

[0039] The raw material crushing state data characterizes the particle size of the available raw materials. The waste crushing state data characterizes the oil content, water content, and quality state of the crushed raw materials. The crushing model can be a deep learning model, which can be recognized by collecting crushing image data with different water contents and different qualities, so as to classify the crushing. For example, by setting labels such as defective products, water content exceeding the threshold, water content below the threshold, oil content below the threshold, oil content above the threshold, etc., the state of the sieved waste can be classified and monitored. By setting labels such as uniform particle size diameter distribution and non-uniform particle size diameter distribution, the particle size of the sieved raw materials can be classified and monitored.

[0040] It can be understood that since sieving can only screen out powders with a particle size equal to or smaller than the sieve aperture, but in the process of oil-water mixing or even conditioning, the non-uniform particle size diameter distribution will cause quality deviations in this link. Therefore, by adding waste crushing state data and raw material crushing image data, the strict control of the quality of each production link can be further ensured.

[0041] It can be understood that according to the oil-water mixing processing data and the processing parameters of the granulation equipment, the historical finished product quality parameters of the target feed product are determined, including: According to the mixing processing data, determine the oil addition ratio, water addition ratio, mixture image data, and mixing equipment processing configuration parameters of the target feed product; Input the mixture image data into a preset mixing recognition model for image recognition to obtain the actual mixing state data; According to the oil addition ratio, water addition ratio, and mixing equipment processing configuration parameters, determine the expected mixing state data; Compare the actual mixing state data with the expected mixing state data to obtain the state data comparison result; According to the processing parameters of the granulation equipment and the expected processing parameters of the granulation equipment, obtain the granulation deviation index; According to the state data comparison result and the granulation deviation index, obtain the historical finished product quality parameters.

[0042] The mixture image data is the image data of the mixture output after mixing by the mixing device. The mixing recognition model is used to provide color maps of different particle distributions. The actual mixing state data indicates the mixing states of different raw materials. The expected mixing state data indicates the expected mixing state. Whether there is an abnormality caused by the deterioration of the performance of the mixing device itself can be determined through the actual mixing state data and the expected mixing state data.

[0043] The expected mixing state data can be obtained through a simulation model. The comparison result of the state data characterizes the difference between the actual mixing state and the expected mixing state.

[0044] The processing parameters of the granulation device characterize the processing parameters adopted when the expected temperature and humidity conditions are reached, such as duration or temperature, etc.

[0045] As Figure 2 shown, the expected temperature and humidity conditions are that the moisture content is between 24% and 28% and the temperature is between 120 degrees and 150 degrees. Whether the expected temperature and humidity conditions are reached is judged by continuously monitoring the data of the duration and the provided temperature. When the expected temperature and humidity conditions are reached, the temperature and duration collected during this process are used as the processing parameters of the granulation device.

[0046] The granulation deviation index characterizes the degree of deviation from the expected processing parameters of the granulation device. It can be calculated by summarizing after single comparison of individual parameters, or by comparing multiple parameters of the processing parameters of the granulation device after coefficient weighting. In this regard, the embodiments of the present application do not limit how to calculate the granulation deviation index, and those skilled in the art can selectively set it according to actual needs.

[0047] It can be understood that according to the historical impurity index parameters, historical raw material quality parameters and historical finished product quality parameters, the equipment parameters or raw material supply parameters of the equipment on the production line where the target feed product is located are adjusted, including: Generating equipment adjustment parameter prompt information according to the historical finished product quality parameters and historical raw material quality parameters; Generating raw material supply parameter prompt information according to the historical impurity index parameters and historical raw material quality parameters.

[0048] It can be understood that generating equipment adjustment parameter prompt information according to the historical finished product quality parameters and historical raw material quality parameters includes: In the case where the granulation deviation index characterizes that the processing parameters of the granulation device match the preset first granulation duration range, generating a first equipment adjustment prompt information corresponding to the equipment crushing parameters in the historical raw material quality parameters according to the raw material crushing state data; When the granulation deviation index characterizes that the processing parameters of the granulation equipment match the preset second granulation duration range, according to the comparison result of the state data, a second equipment adjustment prompt message corresponding to the processing configuration parameters of the mixing equipment is generated. The second granulation duration range and the first granulation duration range are set with different durations.

[0049] The size and water content of the particle size will affect the processing parameters of the treatment equipment during granulation. For example, the granulation process includes Figure 2 The puffing shown. The particle size will affect the puffing duration, and the water content of the particles will also affect the puffing duration. Moreover, different particle sizes and different water contents have different effects on the change of the puffing duration. Therefore, it can be preliminarily determined what causes it based on the granulation duration. The second granulation duration range and the first granulation duration range can be obtained through simulation experiments. When the granulation deviation index satisfies the third granulation duration range, it indicates that the granulation equipment is normal. When neither satisfies the above granulation duration range, it indicates that the granulation equipment is abnormal.

[0050] It can be understood that too much or too little oil addition ratio and too much or too little water addition ratio will cause at least one of the color, adhesion, and expansion degree of the mixed powder to be different. Therefore, it can be determined whether the actual oil ratio or the actual water ratio is abnormal by comparing the color, adhesion, and expansion degree based on the actual mixing state data and the expected mixing state data; and the actual oil ratio depends on the oil in the raw material and the added grease; the actual water ratio depends on the water in the raw material and the added water. When both the actual water ratio and the actual oil ratio are normal, it indicates that the equipment is abnormal. Therefore, a second equipment adjustment prompt message can be generated based on the comparison result of the state data. The embodiments of the present application do not limit how to compare.

[0051] It can be understood that according to the historical impurity index parameters and historical raw material quality parameters, a raw material supply parameter prompt message is generated, including: When the comparison result of the state data characterizes that the water addition ratio or the oil addition ratio does not meet the preset addition conditions, according to the waste crushing state data in each historical raw material quality parameter and the comparison result of the state data, a first raw material supply parameter prompt message is generated; According to the crushing deviation value in the historical raw material quality parameter, a second raw material supply parameter prompt message is generated; According to the historical impurity index parameters, a third raw material supply parameter prompt message is generated.

[0052] The comparison result of the state data can identify the actual water ratio and the actual oil ratio. Therefore, it can be determined whether the water content and oil content in the raw material meet the requirements. Different water contents and oil contents will cause different remaining raw material forms during crushing. Therefore, through the joint judgment of the two, it can be further ensured whether the raw material is abnormal.

[0053] The comminution deviation value represents the availability rate of raw materials. The larger the comminution deviation value, the less the available part. Therefore, it is possible to consider replacing the raw materials to ensure the quality of the raw materials and thus improve the quality of feed products.

[0054] It can be understood that when multiple comminutions are involved, historical raw material quality parameters corresponding to each link will be generated. By comparing each historical raw material quality parameter individually, a second raw material supply parameter prompt message is generated to prompt the link and reason affecting the quality of the finished product.

[0055] It can be understood that according to the oil addition ratio, water addition ratio, and mixing equipment processing configuration parameters, the expected mixing state data is determined, including: Obtain the running duration of the mixing equipment corresponding to the mixing equipment processing configuration parameters; According to the running duration, determine the performance deterioration factor of the mixing equipment; According to the performance deterioration factor and the mixing equipment processing configuration parameters, obtain the actual processing parameters; Input the actual processing parameters, oil addition ratio, and water addition ratio into a preset mixing state prediction model to obtain the expected mixing state data.

[0056] After the mixing equipment runs for a long time, its performance will change. Therefore, obtaining the performance deterioration factor based on the running duration can further ensure the accuracy of the working parameters of the actual equipment operation. At this time, based on the expected mixing state data and the actual mixing state data, it can be further accurately checked whether the mixing equipment causes quality deviation.

[0057] The performance deterioration factor can be obtained from the product manual or simulation. For example, if the mixing equipment processing configuration parameters include the driving speed, the speed reached by the actual mixing equipment after configuring the expected speed can be determined through the performance deterioration factor to obtain the actual processing parameters.

[0058] The embodiment of the present application also provides an electronic device. The electronic device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the above-mentioned quality control method for fish and shrimp feed is implemented. The electronic device can be any intelligent terminal including a tablet computer, in-vehicle computer, etc.

[0059] Please refer to Figure 4 , Figure 4 which schematically shows the hardware structure of an electronic device in another embodiment. The electronic device includes: The processor 401 can be implemented in the form of a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, etc., and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application; The memory 402 can be NAND flash. The relevant program codes are stored in the memory 402 and are called by the processor 401 to execute the quality control method of the fish and shrimp feed in the embodiments of the present application; The input / output interface 403 is used to implement information input and output; The communication interface 404 is used to implement communication interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.); The bus 405 transmits information between various components of the device (such as the processor 401, the memory 402, the input / output interface 403, and the communication interface 404); Among them, the processor 401, the memory 402, the input / output interface 403, and the communication interface 404 are communicatively connected to each other inside the device through the bus 405.

[0060] The embodiments of the present application also provide a computer-readable storage medium. The computer-readable storage medium is a computer-readable storage medium. This storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned quality control method of the fish and shrimp feed is implemented.

[0061] As a non-transitory computer-readable storage medium, the memory can be used to store non-transitory software programs and non-transitory computer-executable programs. In addition, the memory can include high-speed random access memory, and can also include non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory optionally includes a memory remotely set relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an enterprise internal network, a local area network, a mobile communication network, and combinations thereof.

[0062] The embodiments described in the embodiments of the present application are for more clearly illustrating the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art know that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are equally applicable to similar technical problems.

[0063] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than those shown, or combine certain steps, or different steps.

[0064] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, that is, they may be located in one place, or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0065] Those of ordinary skill in the art can understand that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, and their appropriate combinations.

[0066] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0067] It should be understood that in the present application, "at least one (item)" means one or more, and "a plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that there can be three relationships. For example, "A and / or B" can mean: only A exists, only B exists, and both A and B exist at the same time. Among them, A and B can be singular or plural. The character " / " generally means that the associated objects before and after are in an "or" relationship. "At least one (one) of the following" or its similar expression means any combination of these items, including any combination of single item (one) or plural items (ones). For example, at least one (one) of a, b, or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0068] In several embodiments provided by this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the above-mentioned units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of devices or units can be in electrical, mechanical or other forms.

[0069] The units described above as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0070] In addition, in each embodiment of this application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0071] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in each embodiment of this application. The foregoing storage medium includes: various media that can store programs such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

[0072] The preferred embodiments of the embodiments of this application have been described above with reference to the drawings, and thus do not limit the scope of rights of the embodiments of this application. Any modifications, equivalent replacements, and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of this application shall be within the scope of rights of the embodiments of this application.

Claims

1. A method for controlling the quality of fish and shrimp feed, characterized in that: The method comprises: Acquire processing data of the target feed product within a preset first historical time period, wherein the processing data includes raw material feeding and impurity removal processing data, crushing processing data, oil-water mixing processing data, and pelletizing equipment processing parameters; Determine the historical impurity index parameters of the target feed product according to the raw material feeding and impurity removal processing data; Determining historical raw material quality parameters of the target feed product based on the crushing processing data; Determining historical finished product quality parameters of the target feed product based on the oil-water mixing processing data and the pelletizing equipment processing parameters; Output warning prompt information based on the historical impurity index parameters, the historical raw material quality parameters and the historical finished product quality parameters.

2. The quality control method for fish and shrimp feed according to claim 1, characterized in that: The raw material feeding and impurity removal processing data includes a single continuous feeding amount of each raw material, an impurity type corresponding to the single continuous feeding amount, and an impurity content corresponding to each impurity type; determining the historical impurity index parameters of the target feed product based on the raw material feeding and impurity removal processing data includes: Calculating the impurity proportion of each impurity type corresponding to each of the raw materials of the target feed product according to the single continuous feeding amount and the impurity content; Obtaining a weight coefficient of each of the impurity types corresponding to each of the raw materials in the target feed product; Determine the total proportion of the first impurity of each of the raw materials according to the impurity proportion and the corresponding weight coefficient; Obtaining the second impurity proportion corresponding to each of the raw materials of the target feed product in a plurality of consecutive second historical time periods before the first historical time period; the second impurity proportion and the first impurity proportion have the same source parameter; Determining a supply quality trend of each of the raw materials according to the first impurity proportion and a plurality of the second impurity proportions; The historical impurity index parameters are obtained according to the supply quality trend of each of the raw materials.

3. The quality control method for fish and shrimp feed according to claim 1, characterized in that: Determining the historical raw material quality parameters of the target feed product according to the crushing processing data includes: Determining the available amount of each raw material to be pulverized, the amount of waste material, equipment pulverization parameters, raw material pulverization image data and waste material image data from the pulverization processing data; Calculating the crushing available ratio of each of the raw materials to be crushed according to the crushing available amount and the waste amount; Obtaining the expected crushing available ratio corresponding to the crushing parameters of the equipment; Determining a crushing deviation value of each of the raw materials to be crushed according to the crushing available proportion and the expected crushing available proportion; Inputting the waste material image data and the raw material crushing image data into a preset crushing model for crushing category classification, respectively, to obtain waste material crushing state data and raw material crushing state data; The historical raw material quality parameters are obtained according to the crushing deviation values ​​of the raw materials to be crushed, the raw material crushing state data and the waste material crushing state data.

4. The quality control method for fish and shrimp feed according to claim 1, characterized in that: Determining the historical finished product quality parameters of the target feed product according to the oil-water mixing processing data and the pelletizing equipment processing parameters includes: Determine the fat addition ratio, water addition ratio, mixed material image data and mixing equipment processing configuration parameters of the target feed product according to the mixing processing data; Inputting the mixed material image data into a preset mixed material recognition model for image recognition to obtain actual mixed material state data; Determining expected mixing state data according to the oil addition ratio, the water addition ratio and the mixing equipment processing configuration parameters; Performing a state data comparison on the actual mixed state data and the expected mixed state data to obtain a state data comparison result; Obtaining a granulation deviation index according to the granulation equipment processing parameters and the expected granulation equipment processing parameters; The historical finished product quality parameter is obtained according to the status data comparison result and the granulation deviation index.

5. The method for controlling the quality of fish and shrimp feed according to claim 4, characterized in that: The adjusting, according to the historical impurity index parameters, the historical raw material quality parameters and the historical finished product quality parameters, the equipment parameters of the equipment in the production line where the target feed product is located or the supply parameters of the raw materials includes: Generate equipment adjustment parameter prompt information according to the historical finished product quality parameters and the historical raw material quality parameters; Raw material supply parameter prompt information is generated according to the historical impurity index parameters and the historical raw material quality parameters.

6. The method for controlling the quality of fish and shrimp feed according to claim 5, characterized in that: The generating of equipment adjustment parameter prompt information according to the historical finished product quality parameters and the historical raw material quality parameters includes: When the granulation deviation index indicates that the processing parameters of the granulation equipment meet the preset first granulation time range, generating first equipment adjustment prompt information corresponding to the equipment pulverization parameters in the historical raw material quality parameters according to the raw material pulverization state data; When the granulation deviation index indicates that the processing parameters of the granulation equipment meet the preset second granulation time range, the second equipment adjustment prompt information corresponding to the processing configuration parameters of the mixing equipment is generated according to the status data comparison result; the first granulation time range and the second granulation time range have different set time lengths.

7. The method for controlling the quality of fish and shrimp feed according to claim 5, characterized in that: The generating raw material supply parameter prompt information according to the historical impurity index parameter and the historical raw material quality parameter includes: When the status data comparison result indicates that the water addition ratio or the oil addition ratio does not meet the preset addition condition, first raw material supply parameter prompt information is generated according to the waste crushing status data in each of the historical raw material quality parameters and the status data comparison result; generating second raw material supply parameter prompt information according to the crushing deviation value in the historical raw material quality parameter; According to the historical impurity index parameters, third raw material supply parameter prompt information is generated.

8. The method for controlling the quality of fish and shrimp feed according to claim 4, characterized in that: The step of determining the expected mixing state data according to the grease addition ratio, the water addition ratio and the mixing equipment processing configuration parameters includes: Obtaining the operating time of the mixing device corresponding to the processing configuration parameters of the mixing device; Determining a performance degradation factor of the mixing device according to the operating time; Obtaining actual processing parameters according to the performance degradation factor and the processing configuration parameters of the mixing equipment; The actual processing parameters, the oil addition ratio and the water addition ratio are input into a preset mixing state prediction model to obtain expected mixing state data.

9. An electronic device, characterized in that: The electronic device comprises a memory and a processor, the memory stores a computer program, and the processor implements the quality control method of fish and shrimp feed according to any one of claims 1 to 8 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the quality control method for fish and shrimp feed according to any one of claims 1 to 8 is implemented.

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