CN115306718B

CN115306718B - Screw compressor fault detection method, apparatus, device, medium and program product

Info

Publication number: CN115306718B
Application number: CN202210833918.9A
Authority: CN
Inventors: 吴新涛
Original assignee: Jiayang Smart Security Technology Beijing Co ltd
Current assignee: Jiayang Smart Security Technology Beijing Co ltd
Priority date: 2022-07-15
Filing date: 2022-07-15
Publication date: 2023-08-18
Anticipated expiration: 2042-07-15
Also published as: CN115306718A

Abstract

The application discloses a screw compressor fault detection method, a device, equipment, a medium and a program product. The screw compressor fault detection method comprises the following steps: acquiring at least one frame of infrared temperature field image acquired by an infrared imager in the working process of a screw compressor; obtaining temperature information of the screw compressor in a working state based on the at least one frame of infrared temperature field image; comparing the temperature information with temperature threshold information to obtain a first comparison result; wherein the temperature threshold information is a temperature threshold of the screw compressor; the temperature threshold information is determined based on production information of the screw compressor; and determining a fault state of the screw compressor based on the first comparison result. So as to realize the effect of detecting the state of the screw compressor accurately, efficiently and with low cost.

Description

Screw compressor fault detection method, apparatus, device, medium and program product

Technical Field

The application relates to the technical field of computers, in particular to a screw compressor fault detection method, a device, equipment, a medium and a program product.

Background

The screw compressor has simple structure, few vulnerable devices, low exhaust temperature and insensitivity to a large amount of lubricating oil contained in the refrigerant, can work under the condition of larger pressure difference or pressure ratio, has good gas transmission regulation characteristic, and can be widely applied to refrigeration devices such as refrigeration, air conditioning, chemical technology and the like. The method is widely applied to the fields of industrial production and the like, so that the method is rapidly developed.

Along with the rapid development of the screw compressor technology, the detection of the running state of the screw compressor is more and more important, and the current detection of the running state of the screw compressor is usually carried out manually, so that the detection result is inaccurate, manpower is wasted, and the detection efficiency is low.

Disclosure of Invention

The embodiment of the application aims to provide a screw compressor fault detection method, device, equipment, medium and program product, so as to realize the effect of accurately, efficiently and low-cost detecting the state of a screw compressor.

The technical scheme of the application is as follows:

in a first aspect, a method for detecting faults of a screw compressor is provided, the method comprising:

acquiring at least one frame of infrared temperature field image acquired by an infrared imager in the working process of a screw compressor;

Obtaining temperature information of the screw compressor in a working state based on the at least one frame of infrared temperature field image;

comparing the temperature information with temperature threshold information to obtain a first comparison result; wherein the temperature threshold information is a temperature threshold of the screw compressor; the temperature threshold information is determined based on production information of the screw compressor;

and determining a fault state of the screw compressor based on the first comparison result.

In a second aspect, there is provided a screw compressor fault detection device comprising:

the first acquisition module is used for acquiring at least one frame of infrared temperature field image acquired by the infrared imager in the working process of the screw compressor;

the first determining module is used for obtaining temperature information of the screw compressor in a working state based on the at least one frame of infrared temperature field image;

the second determining module is used for comparing the temperature information with temperature threshold information to obtain a first comparison result; wherein the temperature threshold information is a temperature threshold of the screw compressor; the temperature threshold information is determined based on production information of the screw compressor;

and a third determining module, configured to determine a fault state of the screw compressor based on the first comparison result.

In a third aspect, an embodiment of the present application provides an electronic device, where the electronic device includes a processor, a memory, and a program or an instruction stored in the memory and capable of running on the processor, where the program or the instruction, when executed by the processor, implements the steps of the method for detecting a fault in a screw compressor according to any one of the embodiments of the present application.

In a fourth aspect, an embodiment of the present application provides a readable storage medium, where a program or an instruction is stored, where the program or the instruction implements the steps of the method for detecting a screw compressor failure according to any one of the embodiments of the present application when the program or the instruction is executed by a processor.

In a fifth aspect, embodiments of the present application provide a computer program product, the instructions in which, when executed by a processor of an electronic device, enable the electronic device to perform the steps of the screw compressor fault detection method according to any one of the embodiments of the present application.

The technical scheme provided by the embodiment of the application at least has the following beneficial effects:

according to the screw compressor fault detection method provided by the embodiment of the application, based on at least one frame of infrared temperature field image in the working process of the screw compressor, which is acquired by the infrared imaging instrument, the temperature information in the working state of the screw compressor can be obtained, then the temperature information is compared with the temperature threshold information to obtain a first comparison result, and the fault state of the screw compressor is determined based on the first comparison result.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application as claimed.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application and do not constitute a undue limitation on the application.

FIG. 1 is a schematic diagram of a screw compressor fault detection system according to an embodiment of the present application;

FIG. 2 is a schematic flow chart of a method for detecting faults of a screw compressor according to an embodiment of the first aspect of the present application;

FIG. 3 is a schematic diagram of a single-point sampling early warning process according to an embodiment of the first aspect of the present application;

FIG. 4 is a schematic diagram of a two-point sampling early warning process according to an embodiment of the first aspect of the present application;

FIG. 5 is a second flow chart of a method for detecting faults of a screw compressor according to an embodiment of the first aspect of the present application;

FIG. 6 is a flow chart of a pedestrian post-treatment process in accordance with an embodiment of the first aspect of the application;

FIG. 7 is a schematic view of a screw compressor fault detection device according to a second embodiment of the present application;

Fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the third aspect of the present application.

Detailed Description

In order to enable a person skilled in the art to better understand the technical solutions of the present application, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the particular embodiments described herein are meant to be illustrative of the application only and not limiting. It will be apparent to one skilled in the art that the present application may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the application by showing examples of the application.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. The implementations described in the following exemplary examples do not represent all implementations consistent with the application. Rather, they are merely examples of implementations consistent with aspects of the application as set forth in the following claims.

Before introducing the technical scheme of the application, the background technology of the technical scheme of the application is introduced:

a pair of intermeshing helical male and female rotors are mounted in the cylinder of a screw compressor, both rotors having a plurality of concave teeth and rotating in opposite directions relative to each other. The gap between the rotors and between the shell and the rotors is only 5-10 wires, the main rotor (also called male rotor or male rotor) is driven by an engine or a motor (most of which are driven by the motor), and the other rotor (also called female rotor or female rotor) is driven by an oil film formed by oil injection of the main rotor or by a synchronous gear at the end of the main rotor and the end of the female rotor. There is theoretically no metal contact in the drive.

The length and diameter of the rotor determine the compressor displacement (flow) and discharge pressure, the longer the rotor, the higher the pressure; the larger the rotor diameter, the greater the flow.

The spiral rotor groove is filled with air when passing through the air suction port, when the rotor rotates, the rotor groove is closed by the shell wall to form a compression chamber, and after the rotor groove is closed, lubricating oil is sprayed into the compression chamber to play roles of sealing, cooling and lubricating. When the rotor rotates to compress lubricant+gas (abbreviated as oil-gas mixture), the volume of the compression chamber is reduced, and the oil-gas mixture is compressed to the exhaust port. When the compression chamber passes through the discharge port, the oil-gas mixture is discharged from the compressor, completing a suction-compression-discharge process.

Each rotor of the screw machine is supported by antifriction bearings which are secured by end caps near the ends of the shaft. The intake end is supported by roller bearings and the exhaust end is supported by a pair of bearings, typically exhaust end, that position the rotor, i.e., thrust bearings, against axial thrust, bear radial loads, and provide the necessary minimum clearance for axial operation.

The working cycle can be divided into three processes of suction, compression and discharge. As the rotor rotates, each pair of intermeshing teeth successively completes the same duty cycle.

In order to solve the problems that the labor cost is high, the detection efficiency is low and the detection is not accurate enough when the existing fault state of the screw compressor is detected, the embodiment of the application provides a fault detection method, device, equipment, medium and program product for the screw compressor.

The method for detecting the faults of the screw compressor provided by the embodiment of the application is described in detail through specific embodiments and application scenes thereof by combining the accompanying drawings.

Fig. 1 is a screw compressor fault detection system 100 for implementing a screw compressor fault detection method according to an embodiment of the present application, the system including a screw compressor 101, an infrared imager 106, a network video recorder 107, a communication medium 102, and a server 108.

In some embodiments of the present application, the workflow of the screw compressor fault detection system 100 may be: depending on the specific size of the object to be inspected (which may be a screw compressor, for example), in combination with the following infrared imager selection proposal, a suitable infrared imager 106 is selected, and further depending on the size of the screw compressor and the parameters of the infrared imager, the mounting position of the screw compressor to the infrared imager, the horizontal range R (e.g. 104 in fig. 1), and the vertical height H (e.g. 105 in fig. 1) are calculated. The infrared thermal imager can collect infrared temperature field information (specifically, infrared temperature field video can be used, because the infrared imager can continuously monitor the screw compressor all the time), the infrared temperature field information is transmitted to the network camera 107 through the communication medium 102, the network camera 107 stores the infrared temperature field information, meanwhile, the infrared temperature field information can be transmitted to the server 108 through the communication medium 102, the server 108 is utilized to analyze and alarm the infrared temperature field information, and meanwhile, the functions of editing, review, downloading and the like of the video are realized by utilizing the display of the server 108.

It should be noted that the communication medium 102 may be any type of network or networks known in the art or developed in the future, such as a simple communication cable, an internet backbone, ethernet, wireless fidelity (Wireless Fidelity, WIFI), worldwide interoperability for microwave access (Worldwide Interoperability for Microwave Access, WIMAX), wireless communication, broadband over power lines, coaxial cable, etc.

It should be noted that, in fig. 1, the distance R and the height H are optimally selected as far as the calculation result allows due to the limitation of the wall or the overhead beam to which the field infrared imager 106 is attached during the actual arrangement.

In some embodiments of the present application, the screw compressor fault detection system 100 provided in the embodiments of the present application may be applied to screw compressor units of oil and gas fields, and may also be applied to other dynamic devices of oil and gas fields, such as various centrifugal pumps, reciprocating compressors, and the like, and may also be applied to other industrial dynamic devices.

In some embodiments of the present application, different capabilities and functions of the infrared imager, such as pixels, temperature ranges, lenses, etc., may be used with different field needs, with the following options suggested for some typical applications:

A. For electrical equipment

The high temperature range is generally up to 200 ℃.

The low temperature range is typically required to reach-20 c, considering that some devices may be operating outdoors.

For a typical electrical device or component, the pixels of the infrared imager are 160×120, and a standard lens is selected.

For long-distance and small-target measurement (such as wire clamps of a power transmission line, etc.), 320×240 pixels or 640×480 pixels and higher pixels are recommended, and a tele lens is selected.

For close-range, large target measurements (e.g., 1 meter within 1 heat map showing the temperature distribution throughout the power distribution cabinet), it is recommended to fit a wide-angle lens.

For targets with smaller temperature differences (such as alternating-current high-voltage electric equipment and the like), an infrared imager with higher thermal sensitivity is recommended.

If the field needs to have long-time continuous detection requirements, an external power supply is selected.

B. For mechanical, electromechanical devices

An infrared imager with a high temperature of 250 ℃, 350 ℃ and 600 ℃ is selected according to the actual temperature.

For a typical mechanical and electromechanical device, the pixels of the infrared imager are 160×120, and a standard lens is selected.

For partial long-distance and small target measurement (such as high-altitude pipeline detection, etc.), the selection of a tele lens is suggested.

For partial close-range, large target measurements (e.g., distance display of the overall temperature distribution of the furnace), it is recommended to fit a wide-angle lens.

For detecting a part of equipment needing sealing (such as measuring the internal temperature of a closed heating furnace), it is recommended to add an infrared window assembly.

C. Aiming at research and development and quality management equipment

An infrared imager with a temperature of 250 ℃, 350 ℃, 600 ℃, 1200 ℃ and 2000 ℃ is selected according to the actual temperature.

For general purposes (e.g., chips, circuit boards, various devices, etc.), it is recommended to select pixels of the infrared imager as 320×240 or 640×480 pixels and higher, and to use a standard lens.

For partial distance measurement, it is recommended to select a tele lens.

For small target measurements (e.g., microchip temperature distribution within 1mm x 1 mm), it is recommended to fit a macro lens.

For objects that are partially within the sealed enclosure (e.g., to detect the device temperature inside the heater), it is recommended to add an infrared window assembly.

For continuous measurement on site, it is recommended to use infrared imager with external power supply or video output function, and part of site can use thermal imager with continuous shooting function.

In some embodiments of the application, when the infrared imager is mounted at the object to be detected (e.g., screw compressor), the mounting position of the infrared imager has the following reference parameters:

Parameter one: the detection distance of the infrared imager=the measured target size ++ifov, so the smaller the spatial resolution (IFOV), the farther can be measured.

For example: the cable clamp size of the transmission line is generally 50mm, and if a FlukeTi25 thermal imager is used, the IFOV is 2.5mRad, and the farthest detection distance is 50/2.5=20m.

And (2) parameters II: minimum detection target size=ifov×minimum focus distance, so the smaller the IFOV, the smaller the minimum focus distance, the smaller the target can be detected.

In some embodiments of the present application, the object to be monitored may be a screw compressor of a gas production plant of a certain oil and gas field, and the selected imager may be a FlukeTi25 thermal imager; spatial resolution (IFOV): 2.6mRad; a pixel: 320×240; minimum focusing distance: 0.5m; minimum detection size: 1, a step of; spatial resolution (IFOV): 2.5mRad; a pixel: 160×120; minimum focusing distance: 0.15m.3mm; minimum detection size: 0.38mm.

In some embodiments of the present application, the following issues are noted when installing an infrared imager:

before installation, the installed equipment (i.e. the infrared imager) should be electrified and checked, i.e. the infrared imager is electrified and checked one by one, coarse adjustment is carried out, the installation can be carried out when the infrared imager works normally, and the installation aperture and the position of the inspection camera (the infrared imager), the bracket and the holder are checked, and the camera lens cover should not be opened in the process of moving and erecting the camera. The intelligent infrared imager is installed in a place which is not easily damaged by the outside and is shielded by no obstacle near a monitored target (screw compressor), and the installation position does not influence the work of field equipment and the normal activities of personnel. The camera lens is aimed at a monitoring target from the direction of a light source, so that backlight installation is avoided, otherwise, image blurring is easily caused, or halation is easily generated; when backlight installation is necessary, the contrast of the monitored area should be minimized.

The infrared imaging device is not required to be arranged near an air outlet of the air conditioner or in a place filled with smoke and dust, otherwise, the infrared imaging device is easy to cause the lens to condense water vapor due to temperature change, so that the lens is polluted. The infrared imager is not aligned for a long time with respect to the point source exposed to the light source, such as a spotlight. When the infrared imaging instrument is installed, the cable exposed out of the shield needs to be wrapped by a hose, and the cable plug is not needed to bear the dead weight of the cable. The equipment is firmly and firmly installed. The power supply, the video wire and the control wire should be fixed, and a margin is reserved, so that the rotation of the infrared imager is not affected. The cable should be marked significantly permanently for ease of maintenance and management.

According to the screw compressor fault detection system provided by the embodiment of the application, the infrared imager is arranged, the infrared thermal image signal of the key part of the screw compressor is monitored in real time based on the infrared imager, and the distribution condition of the temperature field of the monitoring equipment and the temperature change of the key part are mastered; and the server is utilized to perform data analysis on the acquired temperature data, automatically generate an electronic report, and automatically early warn, so that the purpose of fault analysis and monitoring of the screw compressor is achieved. The system absorbs the advantages of automatic identification and automatic early warning of infrared monitoring, and considers the temperature of the surface and key parts of the screw compressor on the basis of original vibration monitoring. Potential faults can be detected and diagnosed in the range which can be controlled in the factory as early as possible, and the potential faults can be reasonably and timely maintained, so that safety accidents are avoided.

Fig. 2 is a schematic flow chart of a method for detecting a screw compressor fault according to an embodiment of the present application, where an execution subject of the method for detecting a screw compressor fault may be the server 108 in fig. 1.

As shown in fig. 2, the method for detecting a fault of a screw compressor according to the embodiment of the present application may include steps 210 to 240.

Step 210, acquiring at least one frame of infrared temperature field image acquired by an infrared imager in the working process of the screw compressor.

The infrared temperature field image may be an image which is used to characterize the temperature conditions during operation of the screw compressor. The image may be based on video capture during operation of the screw compressor acquired by the infrared imager.

And 220, obtaining temperature information of the screw compressor in the working state based on at least one frame of infrared temperature field image.

In some embodiments of the present application, at least one frame of infrared temperature field image may be detected based on a temperature detection algorithm, thereby obtaining temperature information in an operating state of the screw compressor.

It should be noted that, the above-mentioned obtaining the temperature information in the working state of the screw compressor by using the temperature detection algorithm is only an example of the present application, and those skilled in the art should understand that other ways may be used to obtain the temperature information in the working state of the screw compressor based on at least one frame of the infrared temperature field image, and any way that may be used to obtain the temperature information in the working state of the screw compressor based on at least one frame of the infrared temperature field image is all the protection of the present application.

And 230, comparing the temperature information with the temperature threshold information to obtain a first comparison result.

The temperature threshold information may be a temperature threshold of the screw compressor, and specifically may be a maximum temperature and a minimum temperature of the screw compressor.

The first comparison result may be a result obtained by comparing the temperature information with the temperature threshold information.

In some embodiments of the application, the temperature threshold information may be determined based on production information of the screw compressor, i.e. the temperature threshold information may be determined based on instructions at the time of production of the screw compressor.

Step 240, determining a fault condition of the screw compressor based on the first comparison result.

In some embodiments of the present application, the temperature information may be compared with the temperature threshold information to obtain a first comparison result, and according to the comparison result, it may be determined whether the screw compressor is malfunctioning.

In some embodiments of the application, under the condition that the screw compressor is determined to have faults, alarm information can be generated to prompt staff of the faults of the screw compressor, so that user experience is improved.

In some embodiments of the application, under the condition that the screw compressor is determined to have faults, a temperature report at the part corresponding to the target heating position can be generated for the operator to check, so that the user experience is improved.

According to the embodiment of the application, the temperature change and the temperature gradient characteristics of the screw compressor during operation are fully analyzed, and the real-time monitoring, fault early warning and load monitoring of the operating state of the screw compressor are realized by combining the infrared specificity and the image intelligent analysis of the screw compressor.

The application discloses an automatic fault identification method for infrared images of screw compressors, which comprises the steps of firstly selecting a screw compressor to be detected and acquiring a temperature image of equipment; then obtaining the temperature of the heating point and the normal phase temperature of the equipment by processing the temperature image; and finally, calculating the relative temperature by combining the environmental reference temperature to judge the running condition and fault information of the equipment. The application adopts the infrared image processing technology to monitor the running condition and fault information of the screw compressor, utilizes the infrared temperature image processing technology to find the abnormal heating point of the temperature, calculates the heating temperature, the normal temperature, the ambient temperature and the relative temperature of the abnormal point, automatically judges the running condition and the fault information of the screw compressor equipment by a relative temperature difference judging method, and realizes the on-line rapid detection of the running condition of the screw compressor.

In some embodiments of the application, each frame of the infrared temperature field image may have at least one heat generating site of the screw compressor therein; each heat generating site may correspond to a component of a screw compressor (e.g., may be, but is not limited to, a compressor inlet/outlet, bearings, seals, couplings, motors, etc.); the temperature threshold information may include first temperature threshold information and second temperature threshold information.

Wherein the first temperature threshold information may be a minimum temperature allowed by the screw compressor.

The second temperature threshold information may be a maximum temperature allowed by the screw compressor.

In some embodiments of the application, the heat generating site is generally referred to as a screw compressor key temperature field indicating site, and may be, for example, a site at a compressor inlet and outlet, a bearing, a sealing device, a coupling, a motor, etc.

In some embodiments of the present application, in order to accurately determine the fault status of the screw compressor, determining whether the screw compressor has a fault may include the following two methods:

(1) Preset point position threshold algorithm

The preset point position threshold algorithm is to select a preset heating point, and determine whether the screw compressor fails or not by using temperature information of the selected preset heating point.

For a preset point position threshold algorithm, the following two calculation modes can be adopted:

A. site calculation

Step 220 may specifically include:

acquiring temperature information of parts corresponding to each heating site in the working state based on at least one frame of infrared temperature field image;

step 230 may specifically include:

comparing the temperature information corresponding to the target heating site with the temperature threshold information to obtain a first comparison result;

step 240 may specifically include:

and determining a screw compressor fault under the condition that the temperature information of the parts corresponding to the target heating sites is smaller than or equal to the first temperature threshold information and/or the temperature information of the parts corresponding to the target heating sites is larger than or equal to the second temperature threshold information.

Wherein the target heat generating site may be at least one of the at least one heat generating site.

In some embodiments of the present application, temperature information of the component corresponding to each heating site in the working state may be obtained based on at least one frame of infrared temperature field image, and then the temperature information corresponding to the target heating site is compared with temperature threshold information, and when it is determined that the temperature information of the component corresponding to the target heating site is less than or equal to the first temperature threshold information, and/or the temperature information of the component corresponding to the target heating site is greater than or equal to the second temperature threshold information, a screw compressor fault is determined.

In one example, referring to fig. 3, if the first temperature threshold information is a and the second temperature threshold information is b, temperature information I at the heating site a is obtained, and if it is determined that I is less than or equal to a and/or I is greater than or equal to b, then a screw compressor fault is determined, an early warning is sent, and then a temperature report at a part corresponding to the heating site is generated.

In the embodiment of the application, based on at least one frame of infrared temperature field image, the temperature information of the parts corresponding to each heating site in the working state is obtained, the temperature information corresponding to the target heating site is compared with the temperature threshold information to obtain a first comparison result, and the screw compressor fault is determined under the condition that the temperature information of the parts corresponding to the target heating site is determined to be smaller than or equal to the first temperature threshold information and/or the temperature information of the parts corresponding to the target heating site is determined to be greater than or equal to the second temperature threshold information, so that whether the screw compressor is faulty or not can be accurately determined, and the fault detection accuracy of the screw compressor is improved.

B. Absolute value calculation

In some embodiments of the application, the target heat generating site may comprise a first target heat generating site and a second target heat generating site.

Wherein the first target heat generating site may be one of the at least one heat generating site, and the second target heat generating site may be another heat generating site of the at least one heat generating site other than the first target heat generating site.

Step 230 may specifically include:

determining an absolute value of a difference value between temperature information corresponding to the first target heating site and temperature information corresponding to the second target heating site;

comparing the absolute value with temperature threshold information to obtain a first comparison result;

step 240 may specifically include:

in the event that the absolute value is determined to be less than or equal to the first temperature threshold information and/or the absolute value is determined to be greater than or equal to the second temperature threshold information, a screw compressor fault is determined.

In some embodiments of the present application, after obtaining temperature information of the first target heating site and the second target heating site in the operating state of the component corresponding to the first target heating site based on at least one frame of the infrared temperature field image, an absolute value of a difference value between the temperature information corresponding to the first target heating site and the temperature information corresponding to the second target heating site may be calculated, and if the absolute value is less than or equal to the first temperature threshold information and/or if the absolute value is greater than or equal to the second temperature threshold information, a screw compressor fault may be determined.

In one example, referring to fig. 4, if the first temperature threshold information is a and the second temperature threshold information is B, temperature information I at a heat generating site a (first target heat generating site) and temperature information II at a heat generating site B (second target heat generating site) are obtained, an absolute value of I-II is calculated, and if the absolute value is less than or equal to a and/or the absolute value is greater than or equal to B, a screw compressor fault is determined, an early warning is issued, and then a temperature report at corresponding parts at the heat generating site a and the heat generating site B is generated.

In the embodiment of the application, the absolute value of the difference value between the temperature information corresponding to the first target heating site and the temperature information corresponding to the second target heating site is determined, the absolute value is compared with the temperature threshold information to obtain the first comparison result, and the screw compressor fault is determined under the condition that the absolute value is smaller than or equal to the first temperature threshold information and/or the absolute value is larger than or equal to the second temperature threshold information, so that whether the screw compressor is faulty or not can be accurately determined, and the fault detection accuracy of the screw compressor is improved.

(2) Regional big data algorithm

In practical engineering applications, a single point location estimate is inaccurate. In addition, as the service life of the machine increases, the threshold at the time of shipment (i.e., temperature threshold information) may not be appropriate relative to the present day, and thus the product threshold information (i.e., temperature threshold information) is not trusted blindly. Based on the two problems, the regional big data algorithm is improved. The area big data algorithm takes a preset heating site as a center, a certain distance is a radius, and compared with the prior single preselected heating site or a plurality of preselected heating sites, the area big data algorithm detects the state of key devices of the screw compressor, and can well represent the key devices. The infrared temperature field map is therefore used to monitor the screw compressor status and the average temperature of this area is used to gauge this device. And aiming at the second problem (the threshold is not credible), the regional big data algorithm adopts the comparison thought, compares the currently acquired infrared temperature field image with the historical monitoring results stored in the database, and particularly performs data comparison with the previous alarm situation, if the temperature curve changes of the currently acquired infrared temperature field image and the historical monitoring results are close to each other and the temperature of the currently acquired infrared temperature field image is basically consistent, the user can consider that the user needs to alarm, otherwise, the user does not need to alarm.

Specific step 220 may include:

determining first average temperature information in a preset range of a preset site based on at least one frame of infrared temperature field image;

step 230 may specifically include:

the first average temperature information and the temperature threshold information are subjected to difference to obtain a difference value;

step 240 may specifically include:

and under the condition that the difference value is larger than a preset threshold value, determining that the screw compressor is in fault.

The preset site may be any one of at least one heating site.

The preset range may be a preset range, for example, may be a range with a radius of 0.5 meters centered on the preset locus.

The first average temperature information may be average temperature information within a preset range of a preset site.

In the embodiment of the application, the first average temperature information in the preset range of the preset position is determined based on at least one frame of infrared temperature field image, the difference is obtained by differentiating the first average temperature information and the temperature threshold information, and the screw compressor fault is determined under the condition that the difference is determined to be larger than the preset threshold, so that whether the screw compressor is faulty or not can be accurately determined, and the fault detection accuracy of the screw compressor is improved.

In some embodiments of the present application, there is a slight problem in determining the temperature of the screw compressor by using the infrared imager, for example, if a pedestrian breaks into the scene and just generates a shielding phenomenon for the screw compressor, then there is a significant difference between the infrared temperature field image and the infrared temperature field image when no pedestrian shields, in which case the working state of the screw compressor cannot be reasonably estimated. It should be noted that the infrared imager provides not only an infrared temperature field image, but also a visible light image. Based on this, detection of pedestrians can be performed using visible light images to distinguish two different situations. The specific implementation mode is as follows:

in some embodiments of the present application, in order to avoid the influence of pedestrians on the detection result, after step 210, the above-mentioned screw compressor fault detection method may further include:

acquiring at least one frame of visible light image in the working process of a screw compressor acquired by an infrared imager;

detecting at least one frame of visible light image to obtain a detection result of the at least one frame of visible light image;

step 220 may specifically include:

And obtaining temperature information of the screw compressor in the working state based on the infrared temperature field image corresponding to the visible light image without pedestrians.

The visible light image can be a common shooting image, and each frame of visible light image has a corresponding frame of infrared temperature field image, namely the visible light image and the infrared temperature field image are in one-to-one correspondence.

The detection result may be used to indicate whether or not there is a pedestrian in at least one frame of the visible light image.

In some embodiments of the present application, referring to fig. 5, after the visible light image is acquired, pedestrian detection may be performed on the visible light image, and if no pedestrian is detected, the above steps 220-240 are performed based on the infrared temperature field image corresponding to the visible light image. If a pedestrian is detected, subsequent post-processing of the pedestrian and image analysis and comparison are performed (specific embodiments are described in further detail below).

In the embodiment of the application, at least one frame of visible light image is detected by acquiring at least one frame of visible light image in the working process of the screw compressor acquired by the infrared imager, so that the detection result of the at least one frame of visible light image is obtained, and the temperature information of the screw compressor in the working state is obtained based on the infrared temperature field image corresponding to the visible light image without pedestrians, so that the pedestrian detection can be performed based on the visible light image corresponding to the infrared Wen Changtu, and whether pedestrians intrude into the screw compressor or not can be accurately determined, and the fault detection of the screw compressor is prevented from being influenced.

In some embodiments of the present application, in order to improve accuracy and efficiency of fault detection of the screw compressor, the detecting at least one frame of visible light image to obtain a detection result of the at least one frame of visible light image may specifically include:

inputting at least one frame of visible light image into a pre-trained pedestrian detection model to obtain a first detection result of the at least one frame of visible light image;

and/or;

inputting at least one frame of visible light image into a pre-trained pedestrian segmentation detection model to obtain a second detection result of the at least one frame of visible light image;

the pedestrian detection model may be a pre-trained neural network model based on deep learning, and the model may be used for detecting whether a pedestrian exists in the visible light image.

The first detection result may be a detection result obtained based on a pedestrian detection model. The first detection result may specifically include: and the indication information is used for indicating whether the at least one frame of visible light image has pedestrians. Specifically, a box is used to frame pedestrians in the visible light image.

The second detection result may be a detection result obtained based on a pedestrian segmentation detection model. The second detection result may specifically include: the indication information for indicating whether the visible light image has pedestrians and the contour information of the pedestrians can be specifically identified.

In some embodiments of the present application, the pedestrian segmentation detection model may be a neural network model constructed based on the Yolov5 algorithm, where Yolov5 is used as a representative algorithm of the single-stage target detection algorithm, and detection accuracy is not inferior to that of the double-stage detection algorithm while maintaining extremely fast reasoning speed. The concept of the Yolov5 algorithm is that pictures are sent into a backbone network, feature graphs with different scales are obtained after feature pyramids are obtained, and then classification and regression tasks are carried out simultaneously through a detection head. The label matching strategies are to gridde the picture, and the unit cell at the center of the boundary box is responsible for the prediction of the corresponding real label. YOLOV5, by designing its own backbone network structure, uses the form of convolutional neural network FPN and path aggregation network PAN in the neck network part, and uses powerful mosaic data enhancement and Mixup data enhancement, resulting in higher accuracy on the data set. Based on the data set produced, the algorithm uses Yolov5 for full training and learning, and finally can detect whether the picture contains pedestrians (specifically, whether pedestrians are informed or not, and then the pedestrians are framed by using a mark frame).

In some embodiments of the present application, referring to fig. 6, if the detection result requirement is not very accurate (i.e., no accurate acquisition of pedestrian position information, i.e., no acquisition of a fine profile of a pedestrian), the pedestrian detection model described above may be employed. If the detection result is required to be fine, a pedestrian segmentation detection model (specifically, a model constructed by using a Cascade Mask R-CNN algorithm is adopted, and the embodiment of the application is not limited to the Cascade Mask R-CNN algorithm, and any other mode capable of obtaining the pedestrian contour belongs to the protection of the application), and based on the model, accurate contour information of the pedestrian can be obtained, so that the accuracy of pedestrian detection is improved.

In the embodiment of the application, a first detection result of at least one frame of visible light image is obtained by inputting the at least one frame of visible light image into a pre-trained pedestrian detection model; and/or; at least one frame of visible light image is input into the pre-trained pedestrian segmentation detection model to obtain a second detection result of the at least one frame of visible light image, so that the corresponding detection model can be selected according to the user requirement, the detection result of the visible light image is obtained, and the user experience is improved.

In some embodiments of the present application, in order to further accurately detect a fault of the screw compressor, after the detecting at least one frame of visible light image, a detection result of the at least one frame of visible light image is obtained, the above-mentioned method for detecting a fault of the screw compressor may further include:

removing pedestrians in the infrared temperature field image corresponding to the visible light image with pedestrians to obtain a target infrared temperature field image;

determining second average temperature information of the target area based on the target infrared temperature field image;

comparing the second average temperature information with the historical average temperature information to obtain a second comparison result;

based on the second comparison result, a fault condition of the screw compressor is determined.

The target infrared temperature field image may be an infrared temperature field image obtained by removing pedestrians from the infrared temperature field image.

The target region may be other regions of the target infrared temperature field image than the region where the pedestrian is located.

The historical average temperature information can be temperature information obtained by storing infrared temperature field images without pedestrians in a fault state of the screw compressor and temperature information obtained by storing infrared temperature field images without pedestrians in a non-fault state of the screw compressor; i.e. the historical average temperature information may be temperature information obtained from infrared temperature field images of pedestrians not in the fault state and the non-fault state of the screw compressor of the history record. The second average temperature information may be average temperature information of a target region in the target infrared temperature field image.

The second comparison result may be a comparison result of the second average temperature information and the historical average temperature information.

In the embodiment of the application, when the pedestrian is determined to be in the visible light image, the pedestrian in the infrared temperature field image corresponding to the visible light image with the pedestrian can be removed to obtain the target infrared temperature field image (namely, the pedestrian post-processing process), then the second average temperature information of the target area in the target infrared temperature field image is determined, the second average temperature information is compared with the historical average temperature information to obtain a second comparison result (image analysis and comparison process), and the fault state of the screw compressor can be accurately determined based on the second comparison result, so that the fault detection accuracy of the screw compressor is improved.

In the embodiment of the application, the temperature of the screw compressor is monitored on line by utilizing an infrared image recognition technology, and the load monitoring and the fault early warning are realized according to the temperature change characteristics. The infrared temperature field image is combined with the visible light image, so that comprehensive monitoring and analysis are realized.

In the embodiment of the application, from the viewpoint of arranging infrared imaging monitoring, the infrared monitoring technology can be also adopted to monitor a plurality of compressors in the same factory in real time. The infrared monitoring technology can directly indicate the focus of equipment failure, the temperature measurement is continuous and comprehensive, and the result is visual. The intelligent identification of the temperature gradient image can predict equipment faults through the comparison of dynamic temperature differences and normal states. An infrared monitoring system is arranged for a plurality of compressors, so that contrasting differential infrared monitoring is realized. The infrared diagnosis system of the screw compressor with universality is developed through comparison of a plurality of equipment in the same factory. In the embodiment of the application, the infrared monitoring fault technology does not use precedent on the screw compressor, and compared with other fault on-line monitoring schemes, the application is more flexible to implement and has no interference to equipment.

In the embodiment of the application, the identification of personnel is more comprehensive, most of products on the market at present are identification of facial feature information of personnel, and the application combines special personnel in petrochemical industry on the basis of the identification of personnel, extracts tens of thousands of personnel feature information, such as special personnel feature information of wearing protective clothing, safety helmets, respirators and the like. More accurate personnel interference discharge.

In the embodiment of the application, the equipment temperature field data is utilized to generate the equipment key position temperature report, the data can be checked in real time, the data storage time can be defined according to the setting, the traceability of the historical data is ensured, and the fault starting track can be inquired.

The application designs a brand new algorithm early warning logic aiming at the problem that pedestrian intrusion frequently occurs in practical engineering practice, and pedestrians shield key parts of the screw compressor to cause the change of the alarm logic of the screw compressor, so that the application firstly judges whether pedestrians exist in the scene by using visible light images, and if the pedestrians exist, two schemes for locating the contours of the pedestrians are provided, firstly, the previous detection results (namely the detection results obtained by a pedestrian detection model) are utilized, no additional training and labeling are carried out, and secondly, the segmentation algorithm (namely the pedestrian segmentation detection model) is utilized to obtain the final results. After the corrected infrared image of the pedestrian (the infrared temperature field image after the pedestrian is removed) is obtained, the working state of the screw compressor is monitored through a picture comparison algorithm. And if no pedestrians exist, monitoring the working state of the screw compressor by using a pre-selected point position threshold method and a regional big data method. The application has strong practical significance on the whole, and basically achieves the aim at the beginning.

It should be noted that, in the screw compressor fault detection method provided by the embodiment of the present application, the execution body may be a screw compressor fault detection device, or a control module in the screw compressor fault detection device for executing the screw compressor fault detection method.

Based on the same application conception as the screw compressor fault detection method, the application also provides a screw compressor fault detection device. The screw compressor fault detection device provided by the embodiment of the application is described in detail below with reference to fig. 7.

Fig. 7 is a schematic structural view showing a screw compressor failure detection apparatus according to an exemplary embodiment.

As shown in fig. 7, the screw compressor failure detection apparatus 700 may include:

the first acquisition module 710 is configured to acquire at least one frame of infrared temperature field image acquired by the infrared imager during the working process of the screw compressor;

a first determining module 720, configured to obtain temperature information in the working state of the screw compressor based on the at least one frame of infrared temperature field image;

a second determining module 730, configured to compare the temperature information with temperature threshold information, to obtain a first comparison result; wherein the temperature threshold information is a temperature threshold of the screw compressor; the temperature threshold information is determined based on production information of the screw compressor;

A third determination module 740 is configured to determine a fault state of the screw compressor based on the first comparison result.

In the embodiment of the application, at least one frame of infrared temperature field image in the working process of the screw compressor acquired by the infrared imager is acquired based on the first acquisition module, the temperature information in the working state of the screw compressor can be obtained based on the first determination module according to the at least one frame of infrared temperature field image, then the temperature information is compared with the temperature threshold information based on the second determination module to obtain a first comparison result, and the fault state of the screw compressor is determined based on the third determination module according to the first comparison result.

In some embodiments of the application, each of the infrared temperature field images has at least one heat generating site of the screw compressor therein; each heating site corresponds to a component of the screw compressor; the temperature threshold information includes first temperature threshold information and second temperature threshold information.

In some embodiments of the present application, to accurately determine the fault condition of the screw compressor, the first determination module 720 may specifically be configured to: based on the at least one frame of infrared temperature field image, obtaining temperature information of the parts corresponding to each heating site in the working state;

the second determining module 730 may specifically be configured to: comparing the temperature information corresponding to the target heating site with the temperature threshold information to obtain a first comparison result; wherein the target heat generating site is at least one heat generating site of the at least one heat generating site;

the third determination module 740 may specifically be configured to: and determining the screw compressor fault under the condition that the temperature information of the parts corresponding to the target heating position is smaller than or equal to the first temperature threshold information and/or the temperature information of the parts corresponding to the target heating position is larger than or equal to the second temperature threshold information.

In some embodiments of the application, the target heat generating sites comprise a first target heat generating site and a second target heat generating site; to further improve the accuracy of fault detection of the screw compressor, the second determination module 730 may specifically be configured to: determining an absolute value of a difference value between the temperature information corresponding to the first target heating site and the temperature information corresponding to the second target heating site; comparing the absolute value with temperature threshold information to obtain a first comparison result;

The third determination module 740 may specifically be configured to: determining that the screw compressor is faulty in the case that the absolute value is determined to be less than or equal to the first temperature threshold information and/or that the absolute value is greater than or equal to the second temperature threshold information.

In some embodiments of the present application, to further improve the accuracy of fault detection of the screw compressor, the first determining module 720 may specifically be configured to: determining first average temperature information in a preset range of a preset site based on the at least one frame of infrared temperature field image; wherein the preset site is any one of the at least one heating site;

the second determining module 730 may specifically be configured to: the first average temperature information and the temperature threshold information are subjected to difference to obtain a difference value;

the third determination module 740 may specifically be configured to: and determining that the screw compressor is faulty under the condition that the difference value is larger than a preset threshold value.

In some embodiments of the present application, in order to avoid the influence of pedestrians on the detection result, the above-mentioned fault detection device for a screw compressor may further include:

the second acquisition module is used for acquiring at least one frame of visible light image in the working process of the screw compressor acquired by the infrared imager; each frame of visible light image is provided with a corresponding frame of infrared temperature field image;

A fourth determining module, configured to detect the at least one frame of visible light image, to obtain a detection result of the at least one frame of visible light image; the detection result is used for indicating whether the at least one frame of visible light image has pedestrians;

the first determining module 720 may specifically be configured to: and obtaining temperature information of the screw compressor in the working state based on the infrared temperature field image corresponding to the visible light image without pedestrians.

In some embodiments of the present application, to improve the accuracy and efficiency of fault detection of the screw compressor, the fourth determination module may specifically be configured to:

inputting the at least one frame of visible light image into a pre-trained pedestrian detection model to obtain a first detection result of the at least one frame of visible light image; wherein, the first detection result includes: indication information for indicating whether the at least one frame of visible light image has pedestrians;

and/or;

inputting the at least one frame of visible light image into a pre-trained pedestrian segmentation detection model to obtain a second detection result of the at least one frame of visible light image; wherein the second detection result includes: the display device comprises display information for displaying at least one frame of visible light image, indication information for indicating whether a pedestrian exists in the at least one frame of visible light image, and contour information of the pedestrian.

In some embodiments of the present application, in order to further accurately detect a fault of the screw compressor, the above-mentioned fault detection device for the screw compressor may further include:

a fifth determining module, configured to reject pedestrians in an infrared temperature field image corresponding to the visible light image with pedestrians, so as to obtain a target infrared temperature field image;

a sixth determining module, configured to determine second average temperature information of the target area based on the target infrared temperature field image; the target area is other areas except the area where the pedestrian is located in the target infrared temperature field image;

a seventh determining module, configured to compare the second average temperature information with historical average temperature information to obtain a second comparison result; the historical average temperature information is the temperature information obtained by the stored infrared temperature field image without pedestrians in the fault state of the screw compressor and the temperature information obtained by the infrared temperature field image without pedestrians in the non-fault state of the screw compressor;

and an eighth determining module, configured to determine a fault state of the screw compressor based on the second comparison result.

The screw compressor fault detection device provided by the embodiment of the application can be used for executing the screw compressor fault detection method provided by the embodiments of the methods, and the implementation principle and the technical effects are similar, so that the description is omitted herein for brevity.

Based on the same inventive concept, the embodiment of the application also provides electronic equipment.

Fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 8, the electronic device may include a processor 801 and a memory 802 storing computer programs or instructions.

In particular, the processor 801 may include a Central Processing Unit (CPU), or an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or may be configured as one or more integrated circuits that implement embodiments of the present application.

Memory 802 may include mass storage for data or instructions. By way of example, and not limitation, memory 802 may include a Hard Disk Drive (HDD), floppy Disk Drive, flash memory, optical Disk, magneto-optical Disk, magnetic tape, or universal serial bus (Universal Serial Bus, USB) Drive, or a combination of two or more of the above. Memory 802 may include removable or non-removable (or fixed) media, where appropriate. Memory 802 may be internal or external to the integrated gateway disaster recovery device, where appropriate. In a particular embodiment, the memory 802 is a non-volatile solid-state memory. The Memory may include read-only Memory (Read Only Memory image, ROM), random-Access Memory (RAM), magnetic disk storage media devices, optical storage media devices, flash Memory devices, electrical, optical, or other physical/tangible Memory storage devices. Thus, in general, the memory comprises one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software comprising computer-executable instructions and when the software is executed (e.g., by one or more processors) it is operable to perform the operations described in the screw compressor fault detection methods provided by the embodiments described above.

The processor 801 implements any one of the screw compressor fault detection methods of the above embodiments by reading and executing computer program instructions stored in the memory 802.

In one example, the electronic device may also include a communication interface 803 and a bus 810. As shown in fig. 8, the processor 801, the memory 802, and the communication interface 803 are connected to each other via a bus 810 and perform communication with each other.

Communication interface 803 is primarily used to implement communication between modules, devices, units, and/or devices in embodiments of the invention.

Bus 810 includes hardware, software, or both, that couple components of an electronic device to each other. By way of example, and not limitation, the buses may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an infiniband interconnect, a Low Pin Count (LPC) bus, a memory bus, a micro channel architecture (MCa) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a video electronics standards association local (VLB) bus, or other suitable bus, or a combination of two or more of the above. Bus 810 may include one or more buses, where appropriate. Although embodiments of the invention have been described and illustrated with respect to a particular bus, the invention contemplates any suitable bus or interconnect.

The electronic device can execute the screw compressor fault detection method in the embodiment of the invention, thereby realizing the screw compressor fault detection method described in fig. 2.

In addition, in combination with the screw compressor fault detection method in the above embodiment, the embodiment of the present invention may be implemented by providing a readable storage medium. The readable storage medium has program instructions stored thereon; the program instructions, when executed by a processor, implement any of the screw compressor fault detection methods of the above embodiments.

In addition, in combination with the screw compressor fault detection method in the above embodiment, the embodiment of the present invention may be implemented by providing a computer program product. Instructions in the computer program product, when executed by a processor of an electronic device, cause the electronic device to perform any of the screw compressor fault detection methods of the above embodiments.

It should be understood that the invention is not limited to the particular arrangements and instrumentality described above and shown in the drawings. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present invention are not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between steps, after appreciating the spirit of the present invention.

The functional blocks shown in the above-described structural block diagrams may be implemented in hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, a plug-in, a function card, or the like. When implemented in software, the elements of the invention are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine readable medium or transmitted over transmission media or communication links by a data signal carried in a carrier wave. A "machine-readable medium" may include any medium that can store or transfer information. Examples of machine-readable media include electronic circuitry, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio Frequency (RF) links, and the like. The code segments may be downloaded via computer networks such as the internet, intranets, etc.

It should also be noted that the exemplary embodiments mentioned in this disclosure describe some methods or systems based on a series of steps or devices. However, the present invention is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, or may be performed in a different order from the order in the embodiments, or several steps may be performed simultaneously.

Aspects of the present application are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such a processor may be, but is not limited to being, a general purpose processor, a special purpose processor, an application specific processor, or a field programmable logic circuit. It will also be understood that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware which performs the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In the foregoing, only the specific embodiments of the present application are described, and it will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the systems, modules and units described above may refer to the corresponding processes in the foregoing method embodiments, which are not repeated herein. It should be understood that the scope of the present application is not limited thereto, and any equivalent modifications or substitutions can be easily made by those skilled in the art within the technical scope of the present application, and they should be included in the scope of the present application.

Claims

1. A method of detecting a screw compressor fault, the method comprising:

determining a fault condition of the screw compressor based on the first comparison result;

after the acquiring at least one frame of infrared temperature field image acquired by the infrared imager during the working process of the screw compressor, the method further comprises:

acquiring at least one frame of visible light image in the working process of a screw compressor acquired by an infrared imager; each frame of visible light image is provided with a corresponding frame of infrared temperature field image;

detecting the at least one frame of visible light image to obtain a detection result of the at least one frame of visible light image; the detection result is used for indicating whether the at least one frame of visible light image has pedestrians;

determining second average temperature information of the target area based on the target infrared temperature field image; the target area is other areas except the area where the pedestrian is located in the target infrared temperature field image;

comparing the second average temperature information with the historical average temperature information to obtain a second comparison result; the historical average temperature information is the temperature information obtained by the stored infrared temperature field image without pedestrians in the fault state of the screw compressor and the temperature information obtained by the infrared temperature field image without pedestrians in the non-fault state of the screw compressor;

determining a fault state of the screw compressor based on the second comparison result;

the obtaining the temperature information of the screw compressor in the working state based on the at least one frame of infrared temperature field image comprises the following steps:

2. The method of claim 1, wherein each of the infrared temperature field images has at least one heat generating site of the screw compressor therein; each heating site corresponds to a component of the screw compressor; the temperature threshold information comprises first temperature threshold information and second temperature threshold information;

based on the at least one frame of infrared temperature field image, obtaining temperature information of the parts corresponding to each heating site in the working state;

the comparing the temperature information with temperature threshold information to obtain a first comparison result comprises:

comparing the temperature information corresponding to the target heating site with the temperature threshold information to obtain a first comparison result; wherein the target heat generating site is at least one heat generating site of the at least one heat generating site;

the determining, based on the first comparison result, a fault condition of the screw compressor includes:

and determining the screw compressor fault under the condition that the temperature information of the parts corresponding to the target heating position is smaller than or equal to the first temperature threshold information and/or the temperature information of the parts corresponding to the target heating position is larger than or equal to the second temperature threshold information.

3. The method of claim 2, wherein the target heat generating site comprises a first target heat generating site and a second target heat generating site;

Comparing the temperature information corresponding to the target heating site with the temperature threshold information to obtain a first comparison result, wherein the first comparison result comprises:

determining an absolute value of a difference value between the temperature information corresponding to the first target heating site and the temperature information corresponding to the second target heating site;

determining that the screw compressor is faulty in the case that the absolute value is determined to be less than or equal to the first temperature threshold information and/or that the absolute value is greater than or equal to the second temperature threshold information.

4. The method of claim 2, wherein said obtaining temperature information for an operating state of the screw compressor based on the at least one frame of infrared temperature field image comprises:

determining first average temperature information in a preset range of a preset site based on the at least one frame of infrared temperature field image; wherein the preset site is any one of the at least one heating site;

and determining that the screw compressor is faulty under the condition that the difference value is larger than a preset threshold value.

5. The method according to claim 1, wherein the detecting the at least one frame of visible light image to obtain a detection result of the at least one frame of visible light image includes:

and/or;

6. A screw compressor fault detection device, the device comprising:

a third determining module, configured to determine a fault state of the screw compressor based on the first comparison result;

the apparatus further comprises:

an eighth determination module configured to determine a fault state of the screw compressor based on the second comparison result;

the first determining module is specifically configured to obtain temperature information of the screw compressor in a working state based on an infrared temperature field image corresponding to a visible light image of no pedestrian.

7. An electronic device, the electronic device comprising: a processor and a memory storing computer program instructions; the processor, when executing the computer program instructions, implements the screw compressor fault detection method of any one of claims 1-5.

8. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon computer program instructions, which when executed by a processor, implement the screw compressor fault detection method according to any of claims 1-5.

9. A computer program product, characterized in that instructions in the computer program product, when executed by a processor of an electronic device, cause the electronic device to perform the screw compressor fault detection method according to any one of claims 1-5.