Abstract: This application provides a fault determining method of a reciprocating device and a port control method. The method includes: obtaining target signal data acquired by a sensor located on a component at a predetermined location of a reciprocating device; determining, according to a data type of the target signal data, a target processing mode; processing, according to the target processing mode, the target signal data, to obtain a running status eigenvalue reflecting a running status of the component; and determining, according to the running status eigenvalue, a fault result indicating whether the component is faulty. The present disclosure solves a technical problem that it is unlikely to accurately determine a fault of a reciprocating device in the related art.

Abstract: A method and apparatus for determining a mechanical device fault are provided. The method includes: obtaining vibration data corresponding to a target test position of a device and a preset neural network model (S101); inputting the vibration data to the preset neural network model, and obtaining an output result of the preset neural network model (S102); determining a target label included in the output result, where the target label is either of a fault label and a non-fault label (S103); and determining, in a case that the target label is the fault label, that a fault occurs at the target test position; otherwise, determining that the fault does not occur at the target test position (S104). Therefore, the technical problem that a high-accuracy mechanical device fault detection means is lacked in the related art is resolved.

Abstract: The embodiments of the present disclosure provide a fault diagnosis method, a method for building a fault diagnosis model, fault diagnosis equipment, electronic device, and non-transitory computer-readable storage medium. The fault diagnosis method, for diagnosing a fluid device, which includes a suction end and a discharge end, includes: obtaining a data set for diagnosing the fluid device, wherein the data set includes first characteristic data about the suction end, second characteristic data about the discharge end, and input-output difference data, and the input-output difference data represents data difference between the suction end and the discharge end; obtaining a fault diagnosis model; and determining whether the fluid device is in failure based on the fault diagnosis model and the data set.

Abstract: A method for generating a portrait of mechanical equipment includes: obtaining all data information related to mechanical equipment; performing data fusion on the data information related to the mechanical equipment to obtain a multi-source data information set; obtaining target attribute data and target state data of the mechanical equipment based on the multi-source data information set; generating attribute labels of the mechanical equipment based on the obtained target attribute data; inputting current target state data of the mechanical equipment into a trained neural network model to obtain current state labels of the mechanical equipment, where the current state labels include state label values of the mechanical equipment; and generating an equipment portrait of the mechanical equipment through attribute label values of the obtained attribute labels and the state label values of the obtained current state labels.

Abstract: A fabric woven by imitating warp knitting, which includes first warps, second warps, first wefts, and second wefts; the first warps and the first wefts are interlaced to form the face of the fabric, and the second warps and the second wefts are interlaced to form the back of the fabric; and 7 to 15 weft interlacing points are arranged between each two adjacent groups of warp interlacing points on the second warps. The fabric woven by imitating warp knitting in the present invention has not only the appearance style of woven fabrics but also the characteristics of good air permeability and good hand feel of warp-knitted fabrics.

Abstract: A valve fault detection method includes: constructing a valve fault indicator system reflecting characteristics of vibration signals of valve states; establishing an LSTM-AE model by using an LSTM deep model and according to an autoencoder principle, and setting a fault discrimination threshold; inputting training data into the LSTM-AE model based on the valve fault indicator system, to train the LSTM-AE model; and inputting detection data of a to-be-detected valve into the trained LSTM-AE model based on the valve fault indicator system, and comparing an output value obtained by the LSTM-AE model with the set fault discrimination threshold, to judge whether the detected valve is faulty and outputting a first judgment result.

Abstract: The embodiments of the present disclosure provide a fault diagnosis method, a method for building a fault diagnosis model, fault diagnosis equipment, electronic device, and non-transitory computer-readable storage medium. The fault diagnosis method, for diagnosing a fluid device, which includes a suction end and a discharge end, includes: obtaining a data set for diagnosing the fluid device, wherein the data set includes first characteristic data about the suction end, second characteristic data about the discharge end, and input-output difference data, and the input-output difference data represents data difference between the suction end and the discharge end; obtaining a fault diagnosis model; and determining whether the fluid device is in failure based on the fault diagnosis model and the data set.

Abstract: A woven warp-knit-like fabric, includes a first warp yarn, a second warp yarn, a third warp yarn, and a weft yarn; the first warp yarn is interwoven with the weft yarn to form a surface layer of a fabric, the second warp yarn is interwoven with the weft yarn to form a middle layer of the fabric, and the third yarn is interwoven with the weft yarn to form an inner layer of the fabric; at least three weft weave points are provided between two adjacent groups of warp weave points on the third warp yarn; the first warp yarn is a non-elastic yarn, the third warp yarn is an elastic yarn or a non-elastic yarn, and elastic properties of the second warp yarn are greater than those of the first warp yarn and the third warp yarn.

Abstract: The present invention discloses a fabric woven by imitating warp knitting, which includes first warps, second warps, first wefts, and second wefts; the first warps and the first wefts are interlaced to form the face of the fabric, and the second warps and the second wefts are interlaced to form the back of the fabric; and 7 to 15 weft interlacing points are arranged between each two adjacent groups of warp interlacing points on the second warps. The fabric woven by imitating warp knitting in the present invention has not only the appearance style of woven fabrics but also the characteristics of good air permeability and good hand feel of warp-knitted fabrics.

Abstract: The present invention relates to a composite yarn, a preparation method thereof and an elastic fabric, wherein the composite yarn comprises a core yarn and an outer wrapping yarn, wherein the core yarn further comprising at least one piece of elastic filament, and wherein the outer wrapping yarn is made of short fiber, wherein the outer wrapping yarn is spirally wrapped on the core yarn, wherein drafting ratio of the core yarn is 1-1.5 times.

Abstract: Disclosed is skeleton yarn, comprising core-ply stretch yarn positioned at the center, middle-ply fine fiber or fine yarn spun made of fiber coating the surface of the core-ply stretch yarn, and outer-ply coarse fiber or coarse yarn spun made of fiber coating the surface of the middle-ply fine fiber or fine yarn spun made of fiber, wherein the middle-ply fine fiber or fine yarn spun made of fiber is high twist fiber, and the outer-ply coarse fiber or coarse yarn spun made of fiber is loose twist fiber. A novel retro denim fabric made from the skeleton yarn can be subjected to a normal post-finishing shrinking process, and the problems of unstable garment model and the like caused by unstable washing shrinkage can be avoided.

Abstract: The present invention discloses a warp-knitted fabric of filament and short staple composite yarn and a preparation method thereof. The warp-knitted fabric of filament and short staple composite yarn is prepared by the corresponding preparation method for the warp-knitted fabric of filament and short staple composite yarn. The preparation method for the warp-knitted fabric of filament and short staple composite yarn has excellent weavability, and can effectively prepare the warp-knitted fabric which is high in size stability, is soft, has high elasticity, is wrinkle-resistant and has an excellent hand feeling and comfort. Moreover, in the preparation method, soluble fiber filaments can be added to prepare a warp-knitted fabric or a 3D interval warp-knitted fabric which is partially or entirely formed by 100% short staple yarns; and low-melting-point filaments can also be added to prepare a warp-knitted fabric which can be randomly cut and has no edge curling variation.

Abstract: The invention discloses a direct preparation process for jeans wear, which comprises the following steps: a, settling cotton yarns through a fascicular warping machine; b, feeding the cotton yarns into a dyeing machine to carry out indigo dyeing; c, feeding the cotton yarns into a leaser to divide the cotton yarns; d, feeding the divided cotton yarns into an axle cone maker to obtain yarn cones; and e, placing the prepared yarn cones into an automatic knitting machine, to obtain a jeans wear. By adopting the above processing steps, the automatic knitting machine is used for directly knitting the cotton yarns prepared as the yarn cones into a jeans wear without the processes of tailoring and sewing denim fabrics in the process of preparing the jeans wear, i.e. the production process of the jeans wear can be shortened effectively, and the material loss can be effectively reduced.