A new type of fireproof and flame-retardant glass wool thermal insulation quilt for a greenhouse and a preparation method thereof

Abstract

The present application relates to the technical field of agricultural facility materials, and particularly relates to a novel fireproof and flame-retardant glass wool thermal insulation quilt for a greenhouse and a preparation method thereof, which comprises the following steps: determining the quality of the current batch of raw materials based on the equivalent bulk density and the actual fiber diameter; in response to the quality of the current batch of raw materials, determining the quality state of the current batch of raw materials in combination with the bulk density range and the fiber diameter range in which the equivalent bulk density and the actual fiber diameter are located, and adjusting the initial sewing parameters correspondingly; in response to the quality state of the raw materials, obtaining the upper and lower layer fabric feeding speed difference ratio and the thickness compression rate, determining the fabric feeding synchronization based on the upper and lower layer fabric feeding speed difference ratio, and determining whether the product is excessively compressed and thinned based on the thickness compression rate; in combination with the comparison results of the fabric feeding resistance imbalance prediction index and the compression potential prediction index and the corresponding safety threshold, determining whether the prediction accuracy meets the standard, and adjusting the safety threshold. The present application adjusts the sewing parameters adaptively based on the quality of raw materials and the change of process parameters.

Description

Technical Field

[0001] This invention relates to the field of agricultural facility materials technology, and in particular to a novel fireproof and flame-retardant glass wool insulation blanket for greenhouses and its preparation method. Background Technology

[0002] Greenhouses require nighttime covering with insulating blankets during winter to reduce heat loss. Traditional insulating blankets are often made of materials such as straw mats, foamed plastic, and synthetic fiber cotton. These materials generally have the following problems:

[0003] 1. High flammability: Straw mats and most synthetic fiber materials are extremely flammable. Once they come into contact with open flames (such as chimneys near greenhouses, short circuits in electrical wiring, etc.), they will spread rapidly and cause huge economic losses.

[0004] 2. Decreased thermal insulation performance: Foamed plastics and other materials are prone to aging after long-term use, resulting in a decline in thermal insulation performance; straw mats lose thermal insulation performance sharply after absorbing moisture.

[0005] 3. Environmental and health issues: Some materials release toxic and harmful gases when burned or aged. In addition, the core material of traditional thermal blankets may use formaldehyde-containing adhesives during the production process, which is unfriendly to crops in greenhouses and the environment.

[0006] Therefore, the market urgently needs a greenhouse insulation blanket that combines long-lasting and efficient heat preservation, absolute fire safety, and environmental friendliness.

[0007] Chinese patent application CN120052191A discloses a lightweight greenhouse composite insulation blanket and its preparation method. The lightweight greenhouse composite insulation blanket and its preparation method include two waterproof layers and one insulation layer, with the insulation layer located between the two waterproof layers. The insulation layer comprises the following raw materials in parts by weight: 60-85 parts polyurethane, 5-8 parts modified silica aerogel, 0.5-1.2 parts composite flame retardant, and 15-25 parts foam stabilizer. It has the advantages of ensuring the insulation effect of the blanket while reducing its weight and improving its durability. Therefore, the lightweight greenhouse composite insulation blanket and its preparation method have the following problems:

[0008] It is impossible to adaptively adjust sewing parameters based on changes in raw material quality and process parameters to ensure uniform heat preservation, structural integrity, and stable production quality. Summary of the Invention

[0009] Therefore, this invention provides a novel fireproof and flame-retardant glass wool insulation blanket for greenhouses and its preparation method, in order to overcome the problem in the prior art that it is impossible to adaptively adjust sewing parameters based on changes in raw material quality and process parameters to ensure insulation uniformity, structural integrity and production quality stability.

[0010] The present invention aims to prepare a greenhouse insulation blanket that has an extremely high fire resistance rating from the core material to the surface layer, as well as stable and long-lasting high thermal insulation performance, and is safe and environmentally friendly.

[0011] To achieve the above objectives, the present invention provides a novel fireproof and flame-retardant glass wool insulation blanket for greenhouses and its preparation method, comprising:

[0012] Obtain the equivalent bulk density and actual fiber diameter of the quilt core assembly, and determine the quality of the current batch of raw materials based on the equivalent bulk density and actual fiber diameter;

[0013] In response to the current batch of raw material quality, the quality status of the current batch of raw material is determined by combining the equivalent density and the actual fiber diameter within the density and fiber diameter ranges, and the initial sewing parameters are adjusted accordingly.

[0014] The tension fluctuation range is determined based on the quality state of the raw materials, and tension anomalies are determined by combining the actual tension of several sutures obtained according to the initial detection cycle. In response to the quality state, the sewing speed is adjusted based on the suture speed fluctuation or dynamically.

[0015] Based on the initial pressure distribution of the current sewing unit surface layer assembly and quilt core assembly and the real-time output torque of the feed motor, the feed resistance imbalance prediction index and compression potential prediction index are determined.

[0016] Based on the compression potential prediction index, the risk of excessive thinning is predicted and the cause of excessive thinning is determined by adjusting the presser foot pressure. Based on the fabric feeding resistance imbalance prediction index, the fabric feeding synchronicity is predicted and the type of fabric feeding asynchrony is determined by adjusting the real-time output torque or initial pressure distribution.

[0017] The speed difference ratio between upper and lower layers and the thickness compression ratio are obtained in response to the quality state of the raw materials. The feeding synchronization is determined based on the speed difference ratio between upper and lower layers and the product is determined based on the thickness compression ratio.

[0018] The accuracy of the prediction is determined by comparing the prediction index of fabric feeding resistance imbalance and the prediction index of compression potential with the corresponding safety threshold, and the safety threshold is adjusted accordingly.

[0019] Furthermore, the equivalent density and actual fiber diameter are compared with the acceptable range of the raw material basis;

[0020] If the equivalent bulk density is within the acceptable range and the actual fiber diameter is within the acceptable range, then the current batch of raw materials is deemed acceptable, and the quality status of the previous batch of raw materials is determined based on the acceptable bulk density range.

[0021] If the equivalent bulk density is not within the acceptable range or the actual fiber diameter is not within the acceptable range, the current batch of raw materials is deemed unqualified, and production is suspended or transferred to the defective product process.

[0022] Furthermore, the process of determining the quality status of the previous batch of raw materials includes:

[0023] If the equivalent bulk density is within the lower limit of bulk density and the actual fiber diameter is within the lower limit of fiber diameter, then the current batch of raw materials is judged to be in the first quality state.

[0024] If the equivalent bulk density is within the median range of bulk density and the actual fiber diameter is within the median range of fiber diameter, then the current batch of raw materials is judged to be in the second quality state.

[0025] If the equivalent bulk density is within the upper limit of bulk density and the actual fiber diameter is within the upper limit of fiber diameter, then the current batch of raw materials is judged to be in the third quality state.

[0026] Furthermore, the process of adjusting the initial suturing parameters includes:

[0027] The current batch of raw materials is in its first quality state, with weak fiber bonding. Adjust the initial setting of the suture tension or switch the suture pattern type.

[0028] The current batch of raw materials is in the third quality state, which poses a risk of reduced thermal insulation performance and increases the initial stitching density of subsequent stitching processes.

[0029] Furthermore, a reasonable range of tension fluctuation is preset based on the initial set value of the sewing tension corresponding to each quality state of the raw material;

[0030] If the proportion of sutures whose actual tension is outside the reasonable range of tension fluctuation is greater than the critical proportion, then the suture tension is judged to be continuously abnormal.

[0031] When the actual tension of the suture is greater than the upper limit of the tension fluctuation range, the tension of the suture is judged to be too high; when the actual tension of the suture is less than the lower limit of the tension fluctuation range, the tension of the suture is judged to be too low.

[0032] Furthermore, the tension of the suture thread is too low when the raw material is in its first quality state;

[0033] If the sewing speed is stable near the set sewing speed value, it is determined that the surface fabric is slipping or the fabric feeding mechanism is abnormal, resulting in loose stitches.

[0034] If the sewing speed fluctuates when the raw material is in its first quality state, it is determined that the tension mechanism of the sewing thread itself is faulty.

[0035] If the tension of the sewing thread is too high, and the raw material is in the third quality state, it is determined that the material is too dense, resulting in excessive resistance and excessive tension. The sewing speed is then dynamically adjusted.

[0036] Among them, the actual sewing speed within the initial detection period corresponding to the continuous abnormal sewing tension is obtained, and the average sewing speed, maximum sewing speed and minimum sewing speed of several actual sewing speeds are determined.

[0037] If the actual deviation between the average sewing speed and the set sewing speed is less than or equal to the deviation threshold, and the fluctuation range of the actual sewing speed is less than or equal to the fluctuation threshold, then it is determined that the sewing speed is stable near the set sewing speed.

[0038] If the actual deviation between the average sewing speed and the set sewing speed is greater than the deviation threshold, or if the fluctuation range of the actual sewing speed is greater than the fluctuation threshold, then the sewing speed is judged to be fluctuating.

[0039] Furthermore, the thermal insulation quilt is divided into several sewing units according to the initial sewing length;

[0040] The current batch of raw materials is in the first quality state. The interlayer pre-pressure, the initial stacking thickness of the material, and the real-time output torque of the upper and lower feeding motors are obtained to determine the feeding resistance imbalance prediction index and the compression potential prediction index.

[0041] If the prediction index of fabric feeding resistance imbalance is less than or equal to the fabric feeding safety threshold, the predicted fabric feeding synchronization is good.

[0042] If the predicted index of fabric feeding resistance imbalance is greater than the fabric feeding safety threshold, it is predicted that there is a risk of fabric feeding asynchrony. The type of fabric feeding asynchrony is determined based on the predicted index of fabric feeding resistance imbalance.

[0043] If the predicted compression potential index is less than or equal to the compression safety threshold, the predicted thickness compression is within the safe range.

[0044] If the compression potential prediction index is greater than the compression safety threshold, there is a risk of excessive thinning in the predicted thickness compression. The cause of excessive thinning is determined based on the compression potential prediction index.

[0045] Furthermore, when the torque imbalance ratio is greater than the pressure unevenness, the feeding asynchrony type is determined to be drive-type asynchrony, and the real-time output torque of the feeding motor with the higher torque is adjusted.

[0046] When the pressure unevenness is greater than the torque imbalance ratio, the feeding asynchrony type is determined to be conditional slip asynchrony, and the initial pressures that are higher than the average initial pressure in the initial pressure distribution are reduced.

[0047] The initial stacking ratio is greater than the pressure overshoot ratio. The predicted reason for excessive thinning is that the material is too loosely stacked, so the preset presser foot pressure is increased.

[0048] If the pressure overshoot ratio is greater than the initial stacking ratio, the reason for the excessive thinning is predicted to be that the preset presser foot pressure is too strong. Therefore, the preset presser foot pressure should be reduced.

[0049] Furthermore, given that the current batch of raw materials is in its first quality state, the actual rotational displacement of the feeding device for the product thickness and surface layer components is obtained, and the difference ratio of the feeding speeds of the upper and lower layers and the thickness compression rate are determined.

[0050] If the ratio of the speed difference between the upper and lower layers of fabric feeding is less than or equal to the proportional threshold, the fabric feeding synchronization is considered good; if the ratio of the speed difference between the upper and lower layers of fabric feeding is greater than the proportional threshold, the fabric feeding is considered asynchronous; if the thickness compression rate is less than the compression rate threshold, the product is considered excessively thinned.

[0051] When the fabric feeding is out of sync, if the predicted index of the fabric feeding resistance imbalance of the completed current sewing unit is greater than the fabric feeding safety threshold, it is determined that the prediction accuracy is not up to standard, and the fabric feeding safety threshold is reduced according to the ratio of the fabric feeding speed difference ratio to the proportional threshold.

[0052] When the product is excessively thinned, if the predicted compression potential of the current sewing unit exceeds the compression safety threshold, the compression safety threshold is reduced based on the ratio of the thickness compression rate to the compression rate threshold.

[0053] A new type of fireproof and flame-retardant glass wool insulation blanket for greenhouses includes:

[0054] The surface layer assembly consists of an upper layer and a lower layer, which are stitched together to secure and wrap the quilt core assembly. The selection of the upper and lower layers is based on different functional requirements for enhancing heat insulation or enhancing weather resistance.

[0055] The comforter core assembly consists of several layers of comforter core. The core material of the comforter core is non-adhesive glass wool felt. Its fiber diameter and density are selected from a range that is configured to synergistically achieve a thermal conductivity of less than 0.040 W / (m·K) and a loose structure. The fiber diameter range of the comforter core assembly is 5-9 μm, and the density range is 10-28 kg / m³.

[0056] The surface layer assembly and the core assembly are compositely connected by a flame-retardant connection method.

[0057] Compared with the prior art, the beneficial effects of the present invention are that the present invention provides a greenhouse insulation blanket with extremely high fire resistance from core material to surface layer, as well as stable and long-lasting high thermal insulation performance, and is safe and environmentally friendly; the insulation cotton in the embodiment with a density range and fiber diameter range can ensure excellent thermal insulation performance (low thermal conductivity) and sufficient fluffiness and strength; at the same time, glass wool is an inorganic silicate material with a melting point higher than 1000℃ and belongs to Class A non-combustible material. The "glue-free" molding process completely avoids the combustion risks associated with traditional glass wool due to the use of organic adhesives, achieving absolute fire resistance from the core material itself. Glue-free glass wool has numerous tiny air pores that effectively block air convection and heat conduction, resulting in extremely low thermal conductivity, stable and long-lasting insulation performance. It is also non-hygroscopic, maintaining dryness and insulation even in high humidity environments. Glue-free glass wool does not use harmful adhesives such as formaldehyde during production, producing no odor or volatile substances during use, and causing no pollution to crops or the environment within the greenhouse. The glass wool material exhibits good stability, is resistant to aging, mold, and insect infestation, and has a service life far exceeding that of traditional materials. The insulation blanket in this invention meets the GB8624A standard (non-combustible material) for fire performance, with a thermal conductivity below 0.040 W / (m·K), demonstrating significant insulation effects. Furthermore, it is entirely non-toxic and odorless, making it perfectly suited for modern greenhouses with high safety and environmental requirements.

[0058] This invention achieves high consistency and high reliability in the production of fire-retardant glass wool insulation blankets for greenhouses by establishing a closed-loop control logic from raw material identification to finished product verification. The method first dynamically presets process parameters based on the physical properties of the raw materials, such as bulk density and fiber diameter. During sewing, tension and speed are monitored in real time and adaptively compensated. Then, feedforward prediction and intervention are performed on the risks of interlayer slippage and excessive thinning using feed resistance and compression potential indicators. Results are verified by measuring the synchronization of feed and product thickness, and this negative feedback optimizes the thresholds and parameters of the prediction model, forming a smart manufacturing closed loop with self-learning and continuous optimization capabilities. This method fundamentally solves industry problems such as slippage and uneven compaction in the sewing of multi-layer composite materials, significantly improving the insulation uniformity, structural integrity, and production quality stability of the insulation blankets.

[0059] Furthermore, when the raw material is in its first quality state, its overall structural strength is insufficient and it is prone to delamination. Increasing the tension of the seams improves the adhesion of the surface layer and enhances the "reinforcement" effect. When the raw material is in its third quality state, increasing the initial stitch density of subsequent stitching processes compensates for insufficient fluffiness by increasing compression and fixing points, thereby improving the insulation performance in actual use. This invention intelligently identifies the density and fiber diameter of the adhesive-free glass wool felt, accurately classifying it into three quality states, and dynamically optimizing core process parameters such as stitch tension, pattern, and density accordingly. It achieves precise matching from raw material characteristics to process execution, effectively overcoming industry problems such as the easy slippage and delamination of fluffy materials and the impaired insulation performance of dense materials. Through intelligent control combining preset and feedback, it ensures that the insulation core material and the surface layer are tightly and evenly bonded, significantly improving the product's insulation consistency, structural strength, and wind and water resistance performance. At the same time, it makes the finished product of moderate weight, easy to roll up mechanically, and significantly extends its service life. The entire production process minimizes quality fluctuations and optimizes performance, making it suitable for stable industrial production.

[0060] Furthermore, the determined quality states include the first quality state of loose, fine-fibered non-adhesive glass wool felt and the third quality state of dense, coarse-fibered non-adhesive glass wool felt. This invention achieves intelligent identification and precise compensation for sewing abnormalities by monitoring thread tension and sewing speed in real time during the sewing process and setting differentiated tension fluctuation thresholds and diagnostic logic based on the raw material quality state, such as loose or dense. When loose material exhibits excessively low tension, the system can quickly distinguish between surface slippage and equipment malfunction. When dense material causes excessively high tension, the sewing speed is automatically adjusted to mitigate resistance. This effectively eliminates defects such as insulation layer delamination and uneven compaction caused by loose or overly tight stitches, ensuring the uniformity and integrity of the sewn structure. This significantly improves the product's insulation consistency, structural strength, and durability, achieving high-quality, high-stability intelligent production.

[0061] Furthermore, for the first quality state material (fluffy, fine fiber), the core risk during sewing is not excessive resistance, but rather product defects caused by "relative slippage between the upper and lower layers and the fluffy core material." For the third quality state material, dense, coarse-fibered, non-adhesive glass wool felt, it affects the sewing tension and is prone to excessive resistance due to excessive material density when the sewing tension is abnormal. This invention, by real-time monitoring of the sewing unit, obtains the interlayer pressure distribution and the initial stacking thickness of the material, determines the prediction index of feed resistance imbalance and compression potential, and can provide early warning of the risks of asynchronous feed and excessive thinning. Through quantitative analysis, it can accurately distinguish different causes such as drive-type asynchronous and conditional slippage, fluffy material and excessive pressure, and thus achieve targeted parameter adjustment to adjust motor torque and optimize presser foot pressure distribution. From the process level, it actively eliminates the core process risks that cause interlayer slippage and uneven thickness of the insulation blanket, ensuring a tight and uniform product structure and significantly improving the insulation consistency, overall strength and service life of the insulation blanket.

[0062] Furthermore, this invention establishes a negative feedback closed loop for verifying the prediction accuracy of the actual product quality by measuring the difference ratio of fabric feeding speed and the product thickness compression rate after actual sewing. The measured fabric feeding asynchrony and excessive thinning defects are compared with the predicted index threshold. When the prediction matches the measured result but the defect still occurs, the corresponding safety threshold is automatically reduced proportionally, making subsequent predictions more sensitive and accurate. This method enables the entire preparation process to have self-learning and continuous optimization capabilities, dynamically correcting process model parameters. It fundamentally solves the prediction deviation caused by material fluctuations or environmental changes, ensuring the long-term stability of the production process and the ultimate reliability of product quality, thus achieving adaptive evolution in intelligent manufacturing. Attached Figure Description

[0063] Figure 1 This is a schematic diagram of the structure of the fireproof and flame-retardant glass wool insulation blanket in an embodiment of the present invention;

[0064] Figure 2 This is a schematic flowchart of the method for preparing fireproof and flame-retardant glass wool insulation blanket in an embodiment of the present invention;

[0065] Figure 3 This is a schematic diagram of the process for determining the quality status of the previous batch of raw materials in an embodiment of the present invention;

[0066] Figure 4 This is a schematic diagram of the process for determining whether the prediction accuracy meets the standard and adjusting the safety threshold in an embodiment of the present invention.

[0067] In the diagram: 1-Top layer, 2-Quilt core, 3-Bottom layer, 4-Flame-retardant stitching. Detailed Implementation

[0068] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0069] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0070] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0071] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0072] Please see Figures 1-4 As shown, Figure 1 This is a schematic diagram of the structure of the fireproof and flame-retardant glass wool insulation blanket in an embodiment of the present invention; Figure 2 This is a schematic flowchart of the method for preparing fireproof and flame-retardant glass wool insulation blanket in an embodiment of the present invention; Figure 3 This is a schematic diagram of the process for determining the quality status of the previous batch of raw materials in an embodiment of the present invention; Figure 4 This is a schematic diagram of the process for determining whether the prediction accuracy meets the standard and adjusting the safety threshold in an embodiment of the present invention.

[0073] This invention relates to a novel fireproof and flame-retardant glass wool insulation blanket for greenhouses, comprising:

[0074] The surface layer assembly consists of an upper layer 1 and a lower layer 3. The upper and lower layers are stitched together to secure the composite wrapping quilt core assembly. The selection of the upper and lower layers is based on different functional requirements for enhancing heat insulation or enhancing weather resistance.

[0075] The quilt core assembly consists of several layers of quilt core 2, the fiber diameter and bulk density of which are selected from the range configured to synergistically achieve a thermal conductivity of less than 0.040 W / (m·K) and a loose structure. The fiber diameter range of the quilt core assembly is 5-9 μm, and the bulk density range is 10-28 kg / m³.

[0076] The surface layer assembly and the core assembly are compositely connected by a flame-retardant connection method.

[0077] In practice, the upper and lower layers are made of flame-retardant composite materials, preferably:

[0078] Implementation Plan 1: Flame-retardant Oxford cloth or PVC-coated cloth;

[0079] Implementation Plan 2: A composite material of aluminum foil composite film and non-woven fabric. The aluminum foil layer not only reflects infrared radiation and enhances the heat preservation effect, but it is also a non-combustible material itself.

[0080] The core material of the quilt is non-adhesive glass wool felt, and the fiber diameter of the non-adhesive glass wool quilt core ranges from 5-9μm, and the bulk density ranges from 10-28kg / m³.

[0081] In this embodiment, the quilt core is composed of adhesive-free glass wool felt with a bulk density of 16 kg / m³ and an average fiber diameter of 6 μm;

[0082] This embodiment uses high-strength, aging-resistant flame-retardant PVC-coated Oxford cloth. Flame-retardant stitches 4 are formed by stitching along the edges and center of the insulation blanket using flame-retardant polyester thread (or aramid thread), which tightly fixes the three-layer structure into a whole.

[0083] The resulting thermal insulation blanket meets the GB8624A standard (non-combustible material) for combustion performance, with a thermal conductivity of less than 0.040 W / (m·K) and a significant thermal insulation effect.

[0084] Specifically, this invention provides a greenhouse insulation blanket that has an extremely high fire resistance rating from the core material to the surface layer, while also having stable and long-lasting high thermal insulation performance, and is safe and environmentally friendly; the insulation cotton in the embodiment has a range of density and fiber diameter that can ensure excellent thermal insulation performance (low thermal conductivity) and sufficient fluffiness and strength; at the same time, glass wool is an inorganic silicate material with a melting point higher than 1000℃ and belongs to Class A non-combustible materials. The "glue-free" molding process completely avoids the combustion risks associated with traditional glass wool due to the use of organic adhesives, achieving absolute fire resistance from the core material itself. Glue-free glass wool has numerous tiny air pores that effectively block air convection and heat conduction, resulting in extremely low thermal conductivity, stable and long-lasting insulation performance. It is also non-hygroscopic, maintaining dryness and insulation even in high humidity environments. Glue-free glass wool does not use harmful adhesives such as formaldehyde during production, producing no odor or volatile substances during use, and causing no pollution to crops or the environment within the greenhouse. The glass wool material exhibits good stability, is resistant to aging, mold, and insect infestation, and has a service life far exceeding that of traditional materials. The insulation blanket in this invention meets the GB8624A standard (non-combustible material) for fire performance, with a thermal conductivity below 0.040 W / (m·K), demonstrating significant insulation effects. Furthermore, it is entirely non-toxic and odorless, making it perfectly suited for modern greenhouses with high safety and environmental requirements.

[0085] In this embodiment, the fiber diameter and bulk density of the quilt core are synergistically optimized through fineness control and density control;

[0086] Specifically, the fiber diameter (fineness control) is controlled at 5-9μm in order to obtain finer fibers, thereby forming more and more complex micropores in a unit volume, greatly increasing the tortuosity of the heat conduction path and achieving an extremely low thermal conductivity.

[0087] The bulk density is controlled at 10-28 kg / m³ to ensure sufficient loft (which helps trap still air and improve insulation) while maintaining a certain structural strength and resilience, and to prevent excessive compaction during use that could lead to a decline in insulation performance.

[0088] The optimal synergistic range between fiber diameter and density was determined under the specific constraint of "no glue". This range can simultaneously meet the multiple requirements of thermal insulation quilts for "lightweight", "high heat insulation", "certain structural strength" and "easy to sew and process", and solve the process problems that may occur when glue-free glass wool is used as quilt core, such as "too loose" or "too rigid".

[0089] The method for preparing a novel fireproof and flame-retardant glass wool insulation blanket for greenhouses according to embodiments of the present invention includes:

[0090] Step S1: Obtain the equivalent bulk density and actual fiber diameter of the quilt core assembly, and determine the quality of the current batch of raw materials based on the equivalent bulk density and actual fiber diameter;

[0091] Step S2: In response to the current batch of raw material quality, the quality status of the current batch of raw material is determined by combining the equivalent density and the actual fiber diameter within the density range and fiber diameter range, and the initial sewing parameters are adjusted accordingly.

[0092] Step S3: Determine the tension fluctuation range based on the quality state of the raw material, and determine the tension abnormality by combining the actual tension of several sutures obtained according to the initial detection cycle. In response to the quality state, adjust the sewing speed based on the suture speed fluctuation or dynamically adjust the sewing speed.

[0093] Step S4: Based on the initial pressure distribution of the current sewing unit surface layer assembly and quilt core assembly and the real-time output torque of the feed motor, determine the feed resistance imbalance prediction index and the compression potential prediction index.

[0094] Step S5: Based on the compression potential prediction index, predict the risk of excessive thinning and determine the cause of excessive thinning, adjust the presser foot pressure; based on the fabric feeding resistance imbalance prediction index, predict the fabric feeding synchronicity and determine the type of fabric feeding asynchrony, adjust the real-time output torque or initial pressure distribution.

[0095] Step S6: In response to the quality state of the raw material, obtain the difference ratio of the upper and lower layer feeding speeds and the thickness compression ratio, determine the feeding synchronization based on the difference ratio of the upper and lower layer feeding speeds, and determine whether the product is overly compressed based on the thickness compression ratio.

[0096] Step S7: Combine the comparison results of the fabric feeding resistance imbalance prediction index and the compression potential prediction index with the corresponding safety threshold to determine whether the prediction accuracy meets the standard, and adjust the safety threshold.

[0097] Specifically, this invention achieves high consistency and high reliability in the production of fire-retardant glass wool insulation blankets for greenhouses by establishing a closed-loop control logic from raw material identification to finished product verification. The method first dynamically presets process parameters based on the physical properties of the raw materials, such as bulk density and fiber diameter. During sewing, tension and speed are monitored in real time and adaptively compensated. Then, feedforward prediction and intervention are performed on the risks of interlayer slippage and excessive thinning using fabric feeding resistance and compression potential indicators. Results are verified by measuring fabric feeding synchronization and product thickness, and this negative feedback optimizes the thresholds and parameters of the prediction model, forming a smart manufacturing closed loop with self-learning and continuous optimization capabilities. This method fundamentally solves industry problems such as slippage and uneven compaction in the sewing of multi-layer composite materials, significantly improving the insulation uniformity, structural integrity, and production quality stability of the insulation blankets.

[0098] An ideal thermal blanket should have advantages such as low thermal conductivity, good insulation, moderate weight, easy to roll up, good wind and water resistance, and long service life.

[0099] Before sewing, an online detection device is used to perform non-contact rapid detection on the current batch of glue-free glass wool felt to obtain its actual density and fiber diameter distribution.

[0100] Specifically, the real-time surface density (kg / m²) of the glue-free glass wool felt is obtained, and the equivalent bulk density (kg / m³) is calculated by combining the width with a microwave thickness gauge.

[0101] The average value and distribution range of the fiber diameter of the glue-free glass wool felt were obtained by laser diffraction, and the average value of the fiber diameter was taken as the actual fiber diameter.

[0102] The equivalent bulk density and actual fiber diameter are compared with the basic acceptable range of raw materials. If the equivalent bulk density is within the acceptable range and the actual fiber diameter is within the acceptable range, the current batch of raw materials is judged to be qualified. The quality status of the previous batch of raw materials is determined based on the acceptable range of bulk density.

[0103] If the equivalent bulk density is not within the qualified range or the actual fiber diameter is not within the qualified range, the current batch of raw materials is judged to be unqualified, and production is suspended or transferred to the defective product process.

[0104] The acceptable range for the bulk density is 10-28 kg / m³, and the acceptable range for the fiber diameter is 5-9 μm.

[0105] If the equivalent bulk density is within the lower limit range and the actual fiber diameter is within the lower limit range when the current batch of raw materials is qualified, then the current batch of raw materials is judged to be in the first quality state.

[0106] If the equivalent bulk density is within the median range of bulk density and the actual fiber diameter is within the median range of fiber diameter, then the current batch of raw materials is judged to be in the second quality state.

[0107] If the equivalent bulk density is within the upper limit of bulk density and the actual fiber diameter is within the upper limit of fiber diameter, then the current batch of raw materials is judged to be in the third quality state.

[0108] Specifically, the current batch of raw materials is in the first quality state. The non-adhesive glass wool felt material is fluffy, with fine fibers and a lot of still air inside, and its thermal insulation performance (λ) is predicted to be excellent. However, it has few fiber interlacing points, and its body strength (σ) is predicted to be weak.

[0109] The current batch of raw materials is in the second quality state. The thermal insulation performance and body strength of the non-adhesive glass wool felt are in balance. It is sewn according to the initial sewing parameters.

[0110] The current batch of raw materials is in the third quality state. The material of the non-adhesive glass wool felt is dense or the fibers are coarse. The predicted strength (σ) is high, but the dense structure may lead to a slight risk of decreased thermal insulation performance (λ).

[0111] The current batch of raw materials is in its first quality state, with weak fiber bonding. Adjust the initial setting of the suture tension or switch the suture pattern type.

[0112] Specifically, based on the ratio of equivalent density to the actual fiber diameter to the median of the corresponding median range, the initial setting value of the suture tension is increased by the tension controller of the quilting machine, or the "||" type suture is switched to a "well" type suture or a diamond suture.

[0113] The current batch of raw materials is in the third quality state, which poses a risk of reduced thermal insulation performance. To address this, the initial stitch density of subsequent sewing processes will be increased, and the insufficient loft will be compensated for by increasing compression and fixing points, thereby improving the thermal insulation performance in actual use.

[0114] In this embodiment, the top layer, bottom layer and quilt core are sewn together using a quilting machine. The quilting machine receives control commands and adjusts the set initial sewing parameters to complete the sewing. The initial sewing parameters include the initial set value of the sewing tension and the initial sewing density.

[0115] The initial suture tension setting can be selected from 30-120 cN, and the initial suture density stitch length can be selected from 3-12 mm.

[0116] The lower limit of the bulk density is 10-16 kg / m³, the median bulk density is 16-22 kg / m³, the upper limit of the bulk density is 22-28 kg / m³, the lower limit of the fiber is 5-6.3 μm, the median fiber density is 6.3-7.6 μm, and the upper limit of the fiber density is 7.6-9 μm.

[0117] It is understandable that other qualified raw materials whose combination of equivalent bulk density and actual fiber diameter does not fall into the aforementioned quality state are judged as the second quality state.

[0118] Specifically, when the raw material is in its first quality state, its overall structural strength is insufficient and it is prone to delamination. Increasing the tension of the stitching improves the adhesion of the surface layer and enhances the "reinforcement" effect. When the raw material is in its third quality state, increasing the initial stitching density of subsequent stitching processes compensates for insufficient fluffiness by increasing compression and fixing points, thereby improving the insulation performance in actual use. This invention intelligently identifies the density and fiber diameter of the adhesive-free glass wool felt, accurately classifying it into three quality states, and dynamically optimizing core process parameters such as stitching tension, pattern, and density accordingly. It achieves precise matching from raw material characteristics to process execution, effectively overcoming industry problems such as the easy slippage and delamination of fluffy materials and the impaired insulation performance of dense materials. Through intelligent control combining preset and feedback, it ensures that the insulation core material and the surface layer are tightly and evenly bonded, significantly improving the product's insulation consistency, structural strength, and wind and water resistance performance. At the same time, it makes the finished product of moderate weight, easy to roll up mechanically, and significantly extends its service life. The entire production process minimizes quality fluctuations and optimizes performance, making it suitable for stable industrial production.

[0119] During the quilting process, high-precision sensors such as dynamic tension sensors are used to monitor and obtain the actual tension of several sutures in real time according to the initial detection cycle.

[0120] The reasonable range of tension fluctuation is preset based on the initial set value of the sewing tension corresponding to each quality state of the raw materials.

[0121] In practice, the lower limit of the tension fluctuation range in the first quality state is 0.85 × the initial setting value of the suture tension, and the upper limit of the tension fluctuation range is 1.15 × the initial setting value of the suture tension; the lower limit of the tension fluctuation range in the third quality state is 0.80 × the initial setting value of the suture tension, and the upper limit of the tension fluctuation range is 1.25 × the initial setting value of the suture tension.

[0122] If the proportion of sutures whose actual tension is outside the reasonable range of tension fluctuation is greater than the critical proportion, then the suture tension is judged to be continuously abnormal.

[0123] Specifically, if the actual tension of any suture exceeds the upper limit of the tension fluctuation range, the tension of the suture is judged to be too high.

[0124] When the actual tension of any suture is less than the lower limit of the tension fluctuation range, the tension of the suture is judged to be too low.

[0125] If the tension of the sewing thread is too low, and the sewing speed is stable near the sewing speed setting value when the raw material is in the first quality state, it is judged that the surface fabric is slipping or the feeding mechanism is abnormal, resulting in loose stitches.

[0126] If the sewing speed fluctuates when the raw material is in its first quality state, it is determined that the tension mechanism of the sewing thread itself is faulty.

[0127] During implementation, when the raw material is in the first quality state, the actual sewing speed within the initial detection period corresponding to the continuous abnormality of the sewing tension is obtained, and the average sewing speed, maximum sewing speed and minimum sewing speed of several actual sewing speeds are determined. The initial detection period is a preset unit time.

[0128] If the actual deviation between the average sewing speed and the set sewing speed is less than or equal to the deviation threshold, and the fluctuation range of the actual sewing speed is less than or equal to the fluctuation threshold, then the sewing speed is considered to be stable.

[0129] If the actual deviation between the average sewing speed and the set sewing speed is greater than the deviation threshold, or if the fluctuation range of the actual sewing speed is greater than the fluctuation threshold, then the sewing speed is judged to be fluctuating.

[0130] Specifically, the actual deviation = |average sewing speed - set sewing speed| / set sewing speed × 100%, and the sewing speed fluctuation range = (maximum sewing speed - minimum sewing speed) / average sewing speed × 100%;

[0131] The sewing speed setting is a preset value, the deviation threshold is 2%, and the fluctuation threshold is 4%.

[0132] If the tension of the sewing thread is too high, and the raw material is in the third quality state, it is determined that the material is too dense, resulting in excessive resistance and excessive tension. The sewing speed is then dynamically adjusted.

[0133] Specifically, the adjusted sewing speed = sewing speed setting value + sewing speed change, where the sewing speed change = - proportional coefficient × (actual thread tension - upper limit of tension fluctuation range), and the proportional coefficient = 0.1% of the sewing speed setting value / cN;

[0134] It is understood that the proportional coefficient means that for every unit change in tension, the corresponding sewing speed setting will be adjusted by one-thousandth (0.1%) of a unit.

[0135] Specifically, the determined quality states include the first quality state of loose, fine-fibered non-adhesive glass wool felt and the third quality state of dense, coarse-fibered non-adhesive glass wool felt. This invention achieves intelligent identification and precise compensation for sewing abnormalities by monitoring thread tension and sewing speed in real time during the sewing process and setting differentiated tension fluctuation thresholds and diagnostic logic based on the raw material quality state, such as loose or dense states. When loose material exhibits excessively low tension, the system can quickly distinguish between surface slippage and equipment malfunction. When dense material causes excessively high tension, the system automatically adjusts the sewing speed to mitigate resistance. This effectively eliminates defects such as insulation layer delamination and uneven compaction caused by loose or overly tight stitches, ensuring the uniformity and integrity of the sewn structure. This significantly improves the product's insulation consistency, structural strength, and durability, achieving high-quality, high-stability intelligent production.

[0136] During the production of thermal insulation blankets, multiple layers of insulation material need to be stacked, pressed, wrapped, and sewn together. On a sewing machine, several layers of insulation material and wrapping material are stacked together for processing. This process can easily cause misalignment between the insulation material and the wrapping material, resulting in an uneven and loose thermal insulation blanket. Consequently, the insulation, light transmission, moisture resistance, and other functions of the finished thermal insulation blanket are reduced.

[0137] Further analysis will be conducted based on the fabric feeding situation of the upper and lower fabric feeding mechanisms of the device;

[0138] The current batch of raw materials is in the first quality state. During the sewing process, the thermal insulation blanket is divided into several sewing units according to the initial sewing length. The initial sewing length in practice is 10cm along the sewing direction.

[0139] Obtain the average feed difference ratio, average thickness, and average thread tension of several sewing units.

[0140] By using a distributed micro-pressure sensor array installed on the presser foot, the initial pressure distribution between the upper and lower layers and the fluffy core material is measured when the presser foot initially contacts the material but before full pressure is applied. The pressure distribution non-uniformity and the average initial pressure are calculated based on several initial pressures in the initial pressure distribution. The pressure distribution non-uniformity represents the standard deviation and is recorded as the interlayer pre-pressure.

[0141] The original thickness of the three layers of material naturally stacked at the location to be sewn is measured using a laser rangefinder at the pre-pressing foot and recorded as the initial stack thickness of the material.

[0142] In the final stage of fabric feeding, the real-time output torque of the upper and lower fabric feeding motors is obtained to determine the fabric feeding resistance imbalance prediction index and the compression potential prediction index.

[0143] Specifically, the prediction index for fabric feeding resistance imbalance is: {|Real-time output torque of the upper fabric feeding motor - Real-time output torque of the lower fabric feeding motor| / [(Real-time output torque of the upper fabric feeding motor - Real-time output torque of the lower fabric feeding motor) / 2]} × (Interlayer pre-pressure / Average initial pressure).

[0144] Specifically, the fabric feeding resistance imbalance prediction index integrates "power difference" (torque difference) and "condition difference" (uneven pressure distribution). A large difference in output torque indicates potential asynchrony at the drive level; a large value for pressure distribution unevenness indicates uneven adhesion between material layers and inconsistent friction conditions, which amplifies the slippage risk caused by drive differences. The higher the value of the fabric feeding resistance imbalance prediction index, the higher the predicted risk of impending fabric feeding asynchrony.

[0145] Compression potential prediction index = (initial material stack thickness / ideal material stack thickness) / (preset press foot full pressure / average initial pressure).

[0146] Specifically, (initial stack thickness of material / ideal stack thickness of material) greater than one indicates that the material stack is looser than ideal, and there is physical space for compression; (preset presser foot full pressure / average initial pressure) indicates the multiple of the preset presser foot full pressure relative to the current measured average interlayer pre-pressure; the larger the compression potential prediction index, the higher the risk of the predicted thickness compression rate after stitching being too low, i.e., excessive thinning.

[0147] If the prediction index of fabric feeding resistance imbalance is less than or equal to the fabric feeding safety threshold, the predicted fabric feeding synchronization is good.

[0148] If the predicted index of fabric feeding resistance imbalance is greater than the fabric feeding safety threshold, it is predicted that there is a risk of fabric feeding asynchrony. The type of fabric feeding asynchrony is determined based on the predicted index of fabric feeding resistance imbalance.

[0149] Specifically, when the torque imbalance ratio is greater than the pressure unevenness, the type of fabric feeding asynchrony is determined to be drive-type asynchrony.

[0150] When the pressure unevenness is greater than the torque imbalance ratio, the feeding asynchrony type is determined to be conditional slip asynchrony, and the pressing state needs to be adjusted to homogenize the interlayer pressure.

[0151] Torque imbalance ratio = |Real-time output torque of the upper fabric feeding motor - Real-time output torque of the lower fabric feeding motor| / [(Real-time output torque of the upper fabric feeding motor - Real-time output torque of the lower fabric feeding motor) / 2], Pressure unevenness = (Interlayer pre-pressure / Average initial pressure).

[0152] If the predicted compression potential index is less than or equal to the compression safety threshold, the predicted thickness compression is within the safe range.

[0153] If the compression potential prediction index is greater than the compression safety threshold, there is a risk of excessive thinning in the predicted thickness compression. The cause of excessive thinning is determined based on the compression potential prediction index.

[0154] Specifically, if the initial stacking ratio is greater than the pressure overshoot ratio, the predicted reason for excessive thinning is that the material is too loosely stacked, thus increasing the preset presser foot pressure;

[0155] If the pressure overshoot ratio is greater than the initial stacking ratio, the predicted cause of excessive thinning is that the preset presser foot pressure is too strong. Therefore, the preset presser foot pressure should be reduced.

[0156] Initial stacking ratio = (initial stacking thickness of material / ideal stacking thickness of material), pressure overshoot ratio = (preset presser foot full pressure / average initial pressure).

[0157] The ideal thickness of the material stack is the average of the initial stack thickness of several sewing units. The compression safety threshold is 1.0-1.5, and the fabric feeding safety threshold is 0.5-1.0. The implementers can determine these values ​​through experimental calibration based on equipment accuracy, material characteristics, and process requirements.

[0158] When the fabric feeding asynchrony type is drive-type asynchrony, adjust the real-time output torque of the fabric feeding motor with the higher torque between the real-time output torque of the upper fabric feeding motor and the real-time output torque of the lower fabric feeding motor.

[0159] When the fabric feeding asynchrony type is conditional slip asynchrony, reduce the initial pressure of some components in the initial pressure distribution that are higher than the average initial pressure.

[0160] Specifically, for materials in the first quality state (fluffy, fine fiber), the core risk during sewing is not excessive resistance, but rather product defects caused by "relative slippage between the upper and lower layers and the fluffy core material." For materials in the third quality state, dense, coarse-fiber, non-adhesive glass wool felt affects the sewing tension, and excessive resistance can easily occur due to the material's density when the sewing tension is abnormal. This invention monitors the sewing unit in real time to obtain the interlayer pressure distribution and the initial stacking thickness of the material, and determines the prediction indicators for feed resistance imbalance and compression potential. This allows for early warning of the risks of asynchronous feed and excessive thinning. Through quantitative analysis, it accurately distinguishes between different causes such as drive-type asynchronous and conditional slippage, and material fluffiness and excessive pressure, thereby enabling targeted parameter adjustments to adjust motor torque and optimize presser foot pressure distribution. From a process perspective, this invention proactively eliminates the core process hazards that lead to interlayer slippage and uneven thickness in the insulation blanket, ensuring a tight and uniform product structure and significantly improving the insulation consistency, overall strength, and service life of the insulation blanket.

[0161] After several sewing units of the current thermal insulation blanket are sewn, the accuracy of the prediction for the second layer is verified based on the actual product situation.

[0162] The current batch of raw materials is in the first quality state. During the sewing process, the actual rotational displacement of the upper layer feed roller and the actual rotational displacement of the lower layer feed roller are obtained. At a fixed distance (e.g., 5cm) behind the needle, a non-contact laser thickness gauge is installed to measure the thickness of the product that has just been sewn.

[0163] Determine the ratio of the upper and lower layer feed speeds and the thickness compression rate. The ratio of the upper and lower layer feed speeds is defined as: |Actual rotational displacement of the upper layer - Actual rotational displacement of the lower layer| / [(Actual rotational displacement of the upper layer + Actual rotational displacement of the lower layer) / 2] × 100%. The ratio of the upper and lower layer feed speeds quantifies the relative slippage rate of the upper and lower layers of fabric.

[0164] Thickness compression ratio = product thickness / target thickness × 100%, where the target thickness is a preset value set according to requirements, reflecting the degree to which the core material is compacted or not fully filled;

[0165] If the ratio of the speed difference between the upper and lower layers of fabric feeding is less than or equal to the proportional threshold, the fabric feeding synchronization is considered good; if the ratio of the speed difference between the upper and lower layers of fabric feeding is greater than the proportional threshold, the fabric feeding is considered asynchronous; if the thickness compression rate is less than the compression rate threshold, the product is considered excessively thinned.

[0166] When the fabric feeding is out of sync, if the predicted index of the fabric feeding resistance imbalance of the completed current sewing unit is greater than the fabric feeding safety threshold, it is determined that the prediction accuracy is not up to standard, and the fabric feeding safety threshold is reduced according to the ratio of the fabric feeding speed difference ratio to the proportional threshold.

[0167] When the product is excessively thinned, if the predicted compression potential of the current sewing unit exceeds the compression safety threshold, the compression safety threshold is reduced based on the ratio of the thickness compression rate to the compression rate threshold.

[0168] The ratio threshold is 1.5%, and the compression ratio threshold is 92%.

[0169] Specifically, this invention establishes a negative feedback closed loop for verifying the prediction accuracy of the actual product quality by measuring the difference ratio of fabric feeding speed and the product thickness compression rate after actual sewing. The measured fabric feeding asynchrony and excessive thinning defects are compared with predicted index thresholds. When the prediction matches the measured results but the defect still occurs, the corresponding safety threshold is automatically reduced proportionally, making subsequent predictions more sensitive and accurate. This method enables the entire manufacturing process to have self-learning and continuous optimization capabilities, dynamically correcting process model parameters. It fundamentally solves the prediction deviation caused by material fluctuations or environmental changes, ensuring the long-term stability of the production process and the ultimate reliability of product quality, thus achieving adaptive evolution in intelligent manufacturing.

[0170] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0171] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for preparing a novel fireproof and flame-retardant glass wool insulation blanket for greenhouses, characterized in that, include: Obtain the equivalent bulk density and actual fiber diameter of the quilt core assembly, and determine the quality of the current batch of raw materials based on the equivalent bulk density and actual fiber diameter; In response to the current batch of raw material quality, the quality status of the current batch of raw material is determined by combining the equivalent density, the actual fiber diameter, and the density range and fiber diameter range, and the initial sewing parameters are adjusted accordingly. Based on the quality status of the raw materials, the range of tension fluctuation is determined. Combined with the actual tension of several sutures obtained according to the initial testing cycle, it is determined whether there is tension abnormality. In response to the quality status, the tension structure fault is determined based on the suture speed fluctuation or the sewing speed is dynamically adjusted. Based on the initial pressure distribution of the current sewing unit surface layer assembly and quilt core assembly and the real-time output torque of the feed motor, the feed resistance imbalance prediction index and compression potential prediction index are determined. Based on the compression potential prediction index, the risk of over-thinning is predicted and the cause of over-thinning is determined to adjust the presser foot pressure. Based on the fabric feeding resistance imbalance prediction index, the fabric feeding synchronicity is predicted and the type of fabric feeding asynchrony is determined to adjust the real-time output torque or initial pressure distribution. The speed difference ratio between upper and lower layers and the thickness compression ratio are obtained in response to the quality state of the raw materials. The feeding synchronization is determined based on the speed difference ratio between upper and lower layers and the product is determined based on the thickness compression ratio. The accuracy of the prediction is determined by comparing the prediction index of fabric feeding resistance imbalance and the prediction index of compression potential with the corresponding safety threshold, so as to adjust the safety threshold.

2. The preparation method of the novel fireproof and flame-retardant glass wool insulation blanket for greenhouses according to claim 1, characterized in that, Compare the equivalent density and actual fiber diameter with the acceptable range of the raw material base; If the equivalent bulk density is within the acceptable range and the actual fiber diameter is within the acceptable range, then the current batch of raw materials is deemed acceptable, and the quality status of the previous batch of raw materials is determined based on the acceptable bulk density range. If the equivalent bulk density is not within the acceptable range, or the actual fiber diameter is not within the acceptable range, then the current batch of raw materials is deemed unqualified.

3. The preparation method of the novel fireproof and flame-retardant glass wool insulation blanket for greenhouses according to claim 2, characterized in that, The process of determining the quality status of the previous batch of raw materials includes, If the equivalent bulk density is within the lower limit of bulk density and the actual fiber diameter is within the lower limit of fiber diameter, then the current batch of raw materials is judged to be in the first quality state. If the equivalent bulk density is within the median range of bulk density and the actual fiber diameter is within the median range of fiber diameter, then the current batch of raw materials is judged to be in the second quality state. If the equivalent bulk density is within the upper limit of bulk density and the actual fiber diameter is within the upper limit of fiber diameter, then the current batch of raw materials is judged to be in the third quality state.

4. The preparation method of the novel fireproof and flame-retardant glass wool insulation blanket for greenhouses according to claim 3, characterized in that, The process of adjusting the initial suture parameters includes, The current batch of raw materials is in the first quality condition. Adjust the initial setting of the suture tension or switch the suture pattern type. The current batch of raw materials is in the third quality state, so the initial stitch density of subsequent stitching processes should be increased.

5. The preparation method of the novel fireproof and flame-retardant glass wool insulation blanket for greenhouses according to claim 4, characterized in that, The reasonable range of tension fluctuation is preset based on the initial set value of the sewing tension corresponding to each quality state of the raw materials. If the proportion of sutures whose actual tension is outside the reasonable range of tension fluctuation is greater than the critical proportion, then the suture tension is judged to be continuously abnormal. If the actual tension of any suture exceeds the upper limit of the tension fluctuation range, the tension of the suture is judged to be too high. If the actual tension of any suture is less than the lower limit of the tension fluctuation range, the tension of the suture is judged to be too low.

6. The preparation method of the novel fireproof and flame-retardant glass wool insulation blanket for greenhouses according to claim 5, characterized in that, The tension of the suture thread is too low, even when the raw material is in its first quality state; If the sewing speed is stable near the set sewing speed value, it is determined that the surface fabric is slipping or the fabric feeding mechanism is abnormal, resulting in loose stitches. If the sewing speed fluctuates when the raw material is in its first quality state, it is determined that the tension mechanism of the sewing thread itself is faulty. If the tension of the sewing thread is too high, and the raw material is in the third quality state, it is determined that the material is too dense, resulting in excessive resistance and excessive tension. The sewing speed is then dynamically adjusted. Among them, based on the average value of several actual sewing speeds within the initial detection period corresponding to the continuous abnormal sewing tension, if the actual deviation between the average sewing speed and the sewing speed setting value is greater than the deviation threshold, or the fluctuation amplitude of the actual sewing speed is greater than the fluctuation threshold, then the sewing speed fluctuation is judged to be.

7. The preparation method of the novel fireproof and flame-retardant glass wool insulation blanket for greenhouses according to claim 6, characterized in that, The thermal blanket is divided into several sewing units according to the initial sewing length; The current batch of raw materials is in the first quality state. The interlayer pre-pressure, the initial stacking thickness of the material, and the real-time output torque of the upper and lower feeding motors are obtained to determine the feeding resistance imbalance prediction index and the compression potential prediction index. If the predicted index of fabric feeding resistance imbalance is greater than the fabric feeding safety threshold, it is predicted that there is a risk of fabric feeding asynchrony. The type of fabric feeding asynchrony is determined based on the predicted index of fabric feeding resistance imbalance. If the compression potential prediction index is greater than the compression safety threshold, there is a risk of excessive thinning in the predicted thickness compression. The cause of excessive thinning is determined based on the compression potential prediction index.

8. The preparation method of the novel fireproof and flame-retardant glass wool insulation blanket for greenhouses according to claim 7, characterized in that, When the torque imbalance ratio is greater than the pressure unevenness, the feeding asynchrony type is determined to be drive-type asynchrony, and the real-time output torque of the feeding motor with the higher torque is adjusted. When the pressure unevenness is greater than the torque imbalance ratio, the feeding asynchrony type is determined to be conditional slip asynchrony, and the initial pressures that are higher than the average initial pressure in the initial pressure distribution are reduced. The initial stacking ratio is greater than the pressure overshoot ratio. The predicted reason for excessive thinning is that the material is too loosely stacked, so the preset presser foot pressure is increased. If the pressure overshoot ratio is greater than the initial stacking ratio, the reason for the excessive thinning is predicted to be that the preset presser foot pressure is too strong. Therefore, the preset presser foot pressure should be reduced.

9. The preparation method of the novel fireproof and flame-retardant glass wool insulation blanket for greenhouses according to claim 8, characterized in that, The current batch of raw materials is in the first quality state. Obtain the actual rotational displacement of the feeding device of the product thickness and surface component, and determine the difference ratio of the feeding speed between the upper and lower layers and the thickness compression rate. If the difference in fabric feeding speed between the upper and lower layers is less than or equal to the proportional threshold, then the fabric feeding synchronization is considered to be good. If the difference in fabric feeding speed between the upper and lower layers is greater than the proportional threshold, it is determined that the fabric feeding is out of sync. If the thickness compression ratio is less than the compression ratio threshold, the product is judged to be excessively thinned. When the fabric feeding is out of sync, if the predicted index of the fabric feeding resistance imbalance of the completed current sewing unit is greater than the fabric feeding safety threshold, it is determined that the prediction accuracy is not up to standard, and the fabric feeding safety threshold is reduced according to the ratio of the fabric feeding speed difference ratio to the proportional threshold. When the product is excessively thinned, if the predicted compression potential of the current sewing unit exceeds the compression safety threshold, the compression safety threshold is reduced based on the ratio of the thickness compression rate to the compression rate threshold.

10. A novel fire-resistant and flame-retardant glass wool insulation blanket for greenhouses, prepared using the method described in any one of claims 1-9, characterized in that, include: The surface layer assembly consists of an upper layer and a lower layer, which are stitched together to secure and wrap the quilt core assembly. The selection of the upper and lower layers is based on different functional requirements for enhancing heat insulation or weather resistance. The comforter core assembly consists of several layers of comforter core. The core material of the comforter core is non-adhesive glass wool felt. The thermal conductivity of non-adhesive glass wool felt is less than 0.040W / (m·K). The fiber diameter of the comforter core assembly ranges from 5 to 9μm, and the bulk density ranges from 10 to 28kg / m³. The surface layer assembly and the core assembly are compositely connected by a flame-retardant connection method.

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