CN110864775B - Predictive maintenance system for weighing equipment of automatic belt scale - Google Patents
Predictive maintenance system for weighing equipment of automatic belt scale Download PDFInfo
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- CN110864775B CN110864775B CN201911152013.XA CN201911152013A CN110864775B CN 110864775 B CN110864775 B CN 110864775B CN 201911152013 A CN201911152013 A CN 201911152013A CN 110864775 B CN110864775 B CN 110864775B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01G—WEIGHING
- G01G11/00—Apparatus for weighing a continuous stream of material during flow; Conveyor belt weighers
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01G—WEIGHING
- G01G11/00—Apparatus for weighing a continuous stream of material during flow; Conveyor belt weighers
- G01G11/003—Details; specially adapted accessories
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Abstract
The invention belongs to the technical field of predictive maintenance of automatic equipment, and particularly relates to a predictive maintenance system of weighing equipment of an automatic belt scale, which comprises the following components: the system comprises a tension sensor node, a vibration sensor node, a humidity sensor node and a server; the tension sensor node is suitable for detecting the tension of the automatic belt scale weighing equipment and sending the tension to the server; the vibration sensor node is suitable for detecting vibration data of the automatic belt scale weighing equipment and sending the vibration data to the server; the humidity sensor node is suitable for detecting the humidity of the working environment of the automatic belt scale weighing equipment and sending the humidity to the server; the server is suitable for acquiring the accumulated use time of the equipment according to the recorded use and maintenance data of the automatic belt scale weighing equipment; the server is suitable for predicting whether the automatic belt scale weighing equipment needs to be maintained or not according to tension, humidity, vibration data and equipment accumulated service time, and monitoring and accurate early warning of faults of the weighing equipment are achieved.
Description
Technical Field
The invention belongs to the technical field of predictive maintenance of automatic equipment, and particularly relates to a predictive maintenance system for weighing equipment of an automatic belt scale.
Background
An automatic belt scale weighing device is a metering device which takes a belt conveyor as a support and can measure the instantaneous flow and the accumulated flow of bulk solid materials on the belt conveyor under the condition of not interrupting the flow of the materials. The method is characterized in that the weighing process is continuous and automatic, and the weighing operation can be completed without intervention.
At present, the maintenance of automatic belt weigher weighing-appliance is confirmed and is maintained by managers after equipment breaks down, can't in time discover the trouble, and the trade loss that precision error leads to exists the scheduling problem for a long time to when automatic belt weigher weighing-appliance takes place the unable use of serious trouble, can influence the production progress of enterprise, more can threaten the safety of personnel and equipment.
Therefore, there is a need to design a new predictive maintenance system for an automated belt scale weighing apparatus based on the above problems.
Disclosure of Invention
The invention aims to provide a predictive maintenance system for weighing equipment of an automatic belt scale.
In order to solve the above technical problem, the present invention provides a predictive maintenance system for an automatic belt scale weighing device, comprising:
the system comprises a tension sensor node, a vibration sensor node, a humidity sensor node and a server;
the tension sensor node is suitable for detecting the tension of the automatic belt scale weighing equipment and sending the tension to the server;
the vibration sensor node is suitable for detecting vibration data of the automatic belt scale weighing equipment and sending the vibration data to the server;
the humidity sensor node is suitable for detecting the humidity of the working environment of the automatic belt scale weighing equipment and sending the humidity to the server;
the server is suitable for acquiring the accumulated use time of the equipment according to the recorded use and maintenance data of the automatic belt scale weighing equipment;
the server is adapted to predict whether the automated belt scale weighing apparatus needs maintenance based on tension, humidity, vibration data, and accumulated equipment usage time.
Further, the tension sensor node includes: the tension sensor, the differential amplifying circuit, the tension microprocessor and the tension communication unit are arranged on the base;
the tension sensor is suitable for detecting the tension of the weighing equipment of the automatic belt scale;
the tension signal detected by the tension sensor is amplified by the differential amplifying circuit and then input to the tension microprocessor, and the tension microprocessor is suitable for sending the amplified tension signal to a server through the tension communication unit.
Further, the vibration sensor node includes: the device comprises a vibration sensor, a programmable gain amplifier circuit, a filter circuit, an AD conversion module circuit, a first vibration microprocessor, a second vibration microprocessor and a vibration communication unit;
the vibration sensor is suitable for detecting vibration data of the automatic belt scale weighing equipment;
the first vibration microprocessor is suitable for controlling the amplification factor of the programmable gain amplifier circuit;
vibration signals detected by the vibration sensor are amplified by the programmable gain amplifier circuit and then input into the filter circuit to be subjected to noise elimination, signals subjected to noise elimination are input into the AD conversion module circuit and then input into the first vibration microprocessor, the signals converted by the AD conversion module circuit are sent to the second vibration microprocessor by the first vibration microprocessor, and the signals are sent to the server by the second vibration microprocessor through the vibration communication unit.
Further, the vibration sensor node further includes: the storage module is electrically connected with the first vibration microprocessor;
the storage module is adapted to store vibration data.
Further, the humidity sensor node includes: the humidity sensor, the conditioning circuit, the humidity microprocessor and the humidity communication unit are arranged on the base;
the humidity sensor is suitable for detecting the humidity of the working environment of the automatic belt scale weighing equipment;
the humidity signal that humidity transducer detected transmits to behind the conditioning circuit humidity microprocessor to humidity microprocessor is suitable for and sends humidity signal to the server through humidity communication unit.
Further, the server is adapted to predict whether the automated belt scale weighing apparatus requires maintenance based on tension, humidity, vibration data and accumulated equipment usage time, i.e.
The server is suitable for acquiring tension change of unit weight according to tension and acquiring vibration strength of set frequency according to vibration data.
Further, the server is adapted to establish respective vectors from the data and historical data, i.e.
The server is adapted to establish a data vector and a coefficient vector;
the data includes: tension change of unit weight, vibration intensity of set frequency, humidity and accumulated use time of equipment;
the data vector is: x ═ x(1),x(2),x(3),x(4))；
Wherein x is(1)Change in tension per unit weight; x is the number of(2)A vibration intensity at a set frequency; x is the number of(3)Is humidity of；x(4)Accumulating the service time for the equipment;
the historical data includes: tension change of historical unit weight, vibration intensity of set frequency, humidity and accumulated use time of equipment;
acquiring a tension change coefficient of unit weight, a vibration intensity coefficient and a humidity coefficient of set frequency and an accumulated use time coefficient of equipment according to historical data;
the coefficient vector is: w ═ w (w)(1),w(2),w(3),w(4))；
Wherein, w(1)Coefficient of tension change per unit weight; w is a(2)A vibration intensity coefficient for a set frequency; w is a(3)Is the coefficient of humidity; w is a(4)The time of use coefficient is accumulated for the device.
Further, the server is adapted to construct a predictive maintenance model from the respective vectors and to obtain a solution of the predictive maintenance model, i.e.
s.t.yi(w·xi+b)≥1-ξi；
ξi≥0 i＝1,2,......,N；
Wherein C is a penalty coefficient; x is the number ofiA data vector of the ith training data; y isiIs xiWhen y is a class markiA value of-1 indicates a weighing apparatus fault, when yiWhen the value is 1, the weighing equipment is normal; n is the number of training data; xi is a relaxation variable; xiiRelaxation variables for the ith training data; b is an offset;
the solution for the predictive maintenance model is then: w*And b*；
α＝(α1,α2,α3,......αN,)T；
Wherein, TpThe time interval of signal sampling when vibration and humidity are sampled; x0The data vector of the automatic belt scale weighing equipment when leaving the factory is obtained; w*Is the solution of the coefficient vector; b*Is a solution to the bias; xcA data vector of the current automatic belt scale weighing equipment is obtained; alpha is a Lagrange multiplier vector set; alpha is alpha*For the set of solutions to the dual problem, αN *The Nth element that is a solution to the dual problem; alpha is alphaNIs the nth element of the lagrange multiplier vector; t is transposition; t iswAnd (4) sampling the vibration data according to a time interval under the condition of a calibration data point given by an expert.
Further, the server is adapted to predict whether the automated belt scale weighing apparatus requires maintenance based on a solution of the predictive maintenance model, i.e.
The server is adapted to obtain a maintenance urgency index, i.e.
Wherein p is a maintenance shear forcing index and p is greater than 0;
when p is larger, the automatic belt scale weighing equipment needs maintenance more;
the server is adapted to obtain an early warning threshold;
wherein S is an early warning threshold; gamma is an early warning threshold coefficient;
the server is suitable for predicting whether the automatic belt scale weighing equipment needs to be maintained or not according to the early warning threshold value;
when W is*xc+b*If the number is less than S, the server judges that the automatic belt scale weighing equipment needs maintenance and sends out early warning;
when the early warning of automatic belt weigher weighing equipment, if automatic belt weigher weighing equipment continues to operate, then the maximum working time of automatic belt weigher weighing equipment day is:
wherein, TnThe daily maximum working time of the automatic belt scale weighing equipment is recommended for delivery.
Further, the automated belt scale weighing apparatus predictive maintenance system further comprises: a gateway;
the gateway is suitable for receiving tension, humidity and vibration data sent by each node and then sending the data to the server through the gateway, namely
The tension communication unit is adapted to send tension to the gateway;
the vibration communication unit is suitable for sending vibration data to the gateway;
the humidity communication unit is adapted to send the humidity to the gateway.
The invention has the beneficial effects that the invention adopts the tension sensor node, the vibration sensor node, the humidity sensor node and the server; the tension sensor node is suitable for detecting the tension of the automatic belt scale weighing equipment and sending the tension to the server; the vibration sensor node is suitable for detecting vibration data of the automatic belt scale weighing equipment and sending the vibration data to the server; the humidity sensor node is suitable for detecting the humidity of the working environment of the automatic belt scale weighing equipment and sending the humidity to the server; the server is suitable for acquiring the accumulated use time of the equipment according to the recorded use and maintenance data of the automatic belt scale weighing equipment; the server is suitable for predicting whether the automatic belt scale weighing equipment needs to be maintained or not according to tension, humidity, vibration data and equipment accumulated service time, and monitoring and accurate early warning of faults of the weighing equipment are achieved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a functional block diagram of an automated belt scale weighing apparatus predictive maintenance system in accordance with the present invention;
FIG. 2 is a functional block diagram of a server to which the present invention relates;
FIG. 3 is a schematic block diagram of a tension sensor node of the present invention;
FIG. 4 is a circuit diagram of a differential amplifier in a tension sensor node according to the present invention;
FIG. 5 is a functional block diagram of a vibration sensor node in accordance with the present invention;
FIG. 6 is a circuit diagram of a filter in a node of a vibration sensor in accordance with the present invention;
FIG. 7 is a circuit diagram of an AD conversion module in a node of a vibration sensor according to the present invention;
FIG. 8 is a functional block diagram of a humidity sensor node in accordance with the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
FIG. 1 is a functional block diagram of a predictive maintenance system for an automated belt scale weighing apparatus in accordance with the present invention.
As shown in fig. 1, this embodiment 1 provides a system for automated predictive maintenance of a belt scale weighing device, comprising: the system comprises a tension sensor node, a vibration sensor node, a humidity sensor node and a server; the tension sensor node is suitable for detecting the tension of the automatic belt scale weighing equipment and sending the tension to the server; the vibration sensor node is suitable for detecting vibration data of the automatic belt scale weighing equipment and sending the vibration data to the server; the humidity sensor node is suitable for detecting the humidity of the working environment of the automatic belt scale weighing equipment and sending the humidity to the server; the server is suitable for acquiring the accumulated use time of the equipment according to the recorded use and maintenance data of the automatic belt scale weighing equipment (the working state of the automatic belt scale weighing equipment is obtained by weighing and comparing objects with known standard weight, and the fault is caused when the error range exceeds the set error range; the accumulated use time of the equipment is the accumulated use time from last maintenance to the current automatic belt scale weighing equipment; the two types of data can be but are not limited to be manually input into the server by workers); the server is suitable for predicting whether the automatic belt scale weighing equipment needs maintenance or not according to the tension, the humidity, the vibration data and the accumulated use time of the equipment; the problem of present automatic belt weigher weighing equipment trouble difficult monitoring, unable early warning is solved, accurate predictive maintenance has been realized carrying out automatic belt weigher weighing equipment, gives early warning in advance, has avoided considering to confirm the trouble.
Fig. 2 is a schematic block diagram of a server according to the present invention.
As shown in fig. 2, in the present embodiment, the server includes a memory, a processor and a communication module. The memory, the processor and the communication module are electrically connected with each other directly or indirectly to realize the data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines.
Wherein the memory is used for storing programs or data. The Memory may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like.
The processor is used to read/write data or programs stored in the memory and perform corresponding functions.
The communication module is used for establishing communication connection between the server and other communication terminals through the network and is used for receiving and transmitting data through the network.
It should be understood that the architecture shown in fig. 2 is merely a schematic diagram of a server, which may also include more or fewer components than shown in fig. 2, or have a different configuration than shown in fig. 2. The components shown in fig. 2 may be implemented in hardware, software, or a combination thereof.
FIG. 3 is a schematic block diagram of a tension sensor node of the present invention;
fig. 4 is a circuit diagram of a differential amplifier in a tension sensor node according to the present invention.
As shown in fig. 3, in the present embodiment, the tension sensor node includes: the tension sensor, the differential amplifying circuit, the tension microprocessor and the tension communication unit are arranged on the base; the tension sensor is suitable for detecting the tension of the weighing equipment of the automatic belt scale; the tension signal detected by the tension sensor is amplified by the differential amplification circuit and then input to the tension microprocessor, and the tension microprocessor is suitable for sending the amplified tension signal to a server through the tension communication unit; as shown in fig. 4, the differential amplification circuit is composed of three operational amplifiers, J7 and J8 are respectively connected with two signal output ends of the tension sensor, the PF0 end inputs the amplified signal into the tension microprocessor, and the amplification factor can be changed by adjusting the potentiometer R16; the tension microprocessor may employ, but is not limited to, cc 2530; the three operational amplifiers of the differential amplification circuit can adopt three operational amplifiers in an OP 496; the tension sensor may be, but is not limited to, a tension measuring sensor R253; the tension communication unit may be, but is not limited to, employing a Zigbee module; the server is adapted to obtain tension changes per unit weight from the tension.
FIG. 5 is a functional block diagram of a vibration sensor node in accordance with the present invention;
FIG. 6 is a circuit diagram of a filter in a node of a vibration sensor in accordance with the present invention;
fig. 7 is a circuit diagram of an AD conversion module in a node of a vibration sensor according to the present invention.
As shown in fig. 5, in the present embodiment, the vibration sensor node includes: the system comprises a constant current source, a vibration sensor (which can be but is not limited to an ICP pressure acceleration sensor), a programmable gain amplifier circuit, a filter circuit (which can be but is not limited to a MAX274 active filter), an AD conversion module circuit (vibration signal data acquisition needs to select AD with a relatively high sampling rate to meet the requirement of normally acquiring mechanical vibration signals, and meanwhile, the AD conversion module circuit must have high resolution to solve the precision problem of data, so that the AD conversion module circuit can be but is not limited to ADS8344 with high performance and low power consumption produced by TI company), a first vibration microprocessor (which can be but is not limited to an ARM processor STM32 with a Cortex-M core), a second vibration microprocessor (which can be but is not limited to a chip 25cc 30 with high performance and low power consumption produced by TI company) and a vibration communication unit (which can be but; the acquisition of mechanical vibration signals is realized, the acquired signals are transmitted to a server through a communication unit for analysis and processing, and finally the server performs FFT processing to obtain the vibration intensity of set frequency; after the vibration signal is amplified by the programmable gain amplifier circuit, data is easy to generate aliasing distortion, so a filter circuit capable of properly eliminating noise in the data is added behind the programmable gain amplifier circuit to prevent the data from generating distortion when being transmitted to the AD conversion module circuit; the vibration sensor is suitable for detecting vibration data of the automatic belt scale weighing equipment; the first vibration microprocessor is suitable for controlling the amplification factor of the programmable gain amplifier circuit; the vibration signal detected by the vibration sensor is amplified by the programmable gain amplifier circuit and then is input into the filter circuit to eliminate noise, the signal for eliminating noise is input into the AD conversion module circuit and then is input into the first vibration microprocessor, and the first vibration microprocessor sends the signal converted by the AD conversion module circuit to the second vibration microprocessor which sends the signal to the server through the vibration communication unit; as shown in fig. 5, the constant current source is connected to the ICP pressure acceleration sensor, the ICP pressure acceleration sensor detects that the vibration signal is amplified by the programmable gain amplifier circuit (the programmable gain amplifier circuit is connected to the first microprocessor, and is connected to the first microprocessor for regulation and control), and then is input to the filter circuit for noise elimination, the signal for noise elimination is input to the AD conversion module circuit and then is input to the first vibration microprocessor, and the first vibration microprocessor sends the signal converted by the AD conversion module circuit to the second vibration microprocessor, and the second vibration microprocessor sends the signal to the server through the vibration communication unit; as shown in fig. 6 and 7, the signal output by the programmable gain amplifier circuit is input through the No. 2 port of the MAX274 active filter and output through the No. 24 port to the No. 2 port of the ADS 8344.
In this embodiment, the vibration sensor node further includes: a storage module (which may be but is not limited to an SD card) electrically connected to the first vibration microprocessor; the storage module is suitable for storing vibration data, namely, the first vibration microprocessor stores signals converted by the AD conversion module circuit through the storage module.
FIG. 8 is a functional block diagram of a humidity sensor node in accordance with the present invention.
In this embodiment, the humidity sensor node includes: a humidity sensor (which may be but is not limited to employing an HM1500 sensor), a conditioning circuit, a humidity microprocessor (which may be but is not limited to employing a cc2530), and a humidity communication unit (which may be but is not limited to employing a Zigbee module); the humidity sensor is suitable for detecting the humidity of the working environment of the automatic belt scale weighing equipment; the humidity signal detected by the humidity sensor is transmitted to the humidity microprocessor after passing through the conditioning circuit, and the humidity microprocessor is suitable for sending the humidity signal to the server through the humidity communication unit; as shown in fig. 8, the humidity of the working environment of the automatic belt scale weighing device is converted into a weak analog voltage signal by the humidity sensor, processed by the conditioning circuit, then received by the ADC of the humidity microprocessor for digital processing, and finally sent to the server by the humidity communication unit.
In this embodiment, the server is adapted to predict whether the automated belt scale weighing apparatus requires maintenance based on tension, humidity, vibration data, and accumulated usage time of the apparatus, i.e., the server is adapted to obtain tension variation per unit weight based on tension and to obtain vibration intensity at a set frequency based on vibration data.
In this embodiment, the server is adapted to establish corresponding vectors according to the data and the historical data, i.e. the server is adapted to establish data vectors and coefficient vectors;
the data includes: tension change of unit weight, vibration intensity of set frequency, humidity and accumulated use time of equipment;
the data vector is: x ═ x(1),x(2),x(3),x(4))；
Wherein x is(1)Change in tension per unit weight; x is the number of(2)A vibration intensity at a set frequency; x is the number of(3)Is humidity; x is the number of(4)Accumulating the service time for the equipment;
the historical data includes: tension change of historical unit weight, vibration intensity of set frequency, humidity and accumulated use time of equipment; acquiring a tension change coefficient of unit weight, a vibration intensity coefficient of set frequency, a humidity coefficient and an equipment accumulated use time coefficient according to historical data (under the condition of corresponding historical data of tension change of unit weight, vibration intensity of set frequency, humidity and equipment accumulated use time, regression coefficients of the relation between the tension change of unit weight, the vibration intensity of set frequency, humidity, equipment accumulated use time and the working state of the automatic belt scale weighing equipment can be obtained, and the regression coefficients are the tension change coefficient of unit weight, the vibration intensity coefficient of set frequency, the humidity coefficient and the equipment accumulated use time coefficient);
the coefficient vector is: w ═ w (w)(1),w(2),w(3),w(4))；
Wherein, w(1)Coefficient of tension change per unit weight; w is a(2)A vibration intensity coefficient for a set frequency; w is a(3)Is the coefficient of humidity; w is a(4)The time of use coefficient is accumulated for the device.
In this embodiment, the server is adapted to construct the predictive maintenance model from the respective vectors and to obtain a solution to the predictive maintenance model, i.e.
The classification hyperplane problem with the maximum geometric spacing can be expressed as a constraint optimization problem;
s.t.yi(w·xi+b)≥1-ξi；
ξi≥0 i＝1,2,......,N；
wherein, C is a penalty coefficient (the penalty coefficient can be 0.6, 0.45, etc., and the best effect is obtained when the penalty coefficient is 0.45); x is the number ofiA data vector of the ith training data; y isiIs xiWhen y is a class markiIs weighed when it is-1Equipment failure when yiWhen the value is 1, the weighing equipment is normal; n is the number of training data; xi is a relaxation variable; xiiRelaxation variables for the ith training data; b is an offset;
the solution for the predictive maintenance model is then: w*And b*；
Converting the original problem into a dual problem, and solving the optimal solution of the dual problem to obtain:
α＝(α1,α2,α3,......αN,)T；
wherein, TpThe time interval of signal sampling when vibration and humidity are sampled; x0The data vector of the automatic belt scale weighing equipment when leaving the factory is obtained; w*Is the solution of the coefficient vector; b*Is a solution to the bias; xcA data vector of the current automatic belt scale weighing equipment is obtained; alpha is a Lagrange multiplier vector set; alpha is alpha*For the set of solutions to the dual problem, αN *The Nth element that is a solution to the dual problem; alpha is alphaNIs the nth element of the lagrange multiplier vector; t is transposition; t iswAnd (4) sampling the vibration data according to a time interval under the condition of a calibration data point given by an expert.
In this embodiment, the server is adapted to predict whether the automated belt scale weighing apparatus requires maintenance based on a solution of the predictive maintenance model, i.e.
The server is adapted to obtain a maintenance urgency index, i.e.
Wherein p is a maintenance forced cutting degree index, p is more than 0, and the normal condition is about 1;
when p is larger, the weighing device is more maintenance-requiring; the smaller p, the healthier the weighing device. The server is adapted to obtain an early warning threshold;
wherein S is an early warning threshold; gamma is an early warning threshold coefficient; when gamma is 0.25, a compromise is effectively made between avoiding false positives and avoiding false negatives;
the server is suitable for predicting whether the automatic belt scale weighing equipment needs to be maintained or not according to the early warning threshold value;
when W is*xc+b*If the S is less than the preset threshold, the server judges that the automatic belt scale weighing equipment needs to be maintained and sends out early warning, so that whether the symmetrical equipment needs to be maintained or not can be predicted more accurately and timely;
when the early warning of automatic belt weigher weighing equipment, if automatic belt weigher weighing equipment continues to operate (if promptly must weigh because weighing task), then automatic belt weigher weighing equipment maximum operating time per day is:
wherein e is a natural constant; t isnIs recommended when leaving factoryThe daily maximum working time of the automatic belt scale weighing equipment; parameters such as the maintenance urgency index, the early warning threshold value, the daily maximum working time and the like can be checked or set by logging in the server. Example 2
On the basis of embodiment 1, in this embodiment 2, the system for predictive maintenance of an automatic belt scale weighing device further includes: a gateway; the gateway is suitable for receiving tension, humidity and vibration data sent by each node and then sending the data to the server through the gateway, namely the tension communication unit is suitable for sending tension to the gateway; the vibration communication unit is suitable for sending vibration data to the gateway; the humidity communication unit is suitable for sending humidity to the gateway; when the communication module of each node adopts a Zigbee module, the gateway can adopt a Zigbee gateway; data transmission can be more convenient through the gateway.
In summary, the invention uses the tension sensor node, the vibration sensor node, the humidity sensor node and the server; the tension sensor node is suitable for detecting the tension of the automatic belt scale weighing equipment and sending the tension to the server; the vibration sensor node is suitable for detecting vibration data of the automatic belt scale weighing equipment and sending the vibration data to the server; the humidity sensor node is suitable for detecting the humidity of the working environment of the automatic belt scale weighing equipment and sending the humidity to the server; the server is suitable for acquiring the accumulated use time of the equipment according to the recorded use and maintenance data of the automatic belt scale weighing equipment; the server is suitable for predicting whether the automatic belt scale weighing equipment needs to be maintained or not according to tension, humidity, vibration data and equipment accumulated service time, and monitoring and accurate early warning of faults of the weighing equipment are achieved.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In light of the foregoing description of the preferred embodiment of the present invention, many modifications and variations will be apparent to those skilled in the art without departing from the spirit and scope of the invention. The technical scope of the present invention is not limited to the content of the specification, and must be determined according to the scope of the claims.
Claims (3)
1. An automated belt scale weighing apparatus predictive maintenance system, comprising:
the system comprises a tension sensor node, a vibration sensor node, a humidity sensor node and a server;
the tension sensor node is suitable for detecting the tension of the automatic belt scale weighing equipment and sending the tension to the server;
the vibration sensor node is suitable for detecting vibration data of the automatic belt scale weighing equipment and sending the vibration data to the server;
the humidity sensor node is suitable for detecting the humidity of the working environment of the automatic belt scale weighing equipment and sending the humidity to the server;
the server is suitable for acquiring the accumulated use time of the equipment according to the recorded use and maintenance data of the automatic belt scale weighing equipment;
the server is suitable for predicting whether the automatic belt scale weighing equipment needs maintenance or not according to the tension, the humidity, the vibration data and the accumulated use time of the equipment;
the tension sensor node comprises: the tension sensor, the differential amplifying circuit, the tension microprocessor and the tension communication unit are arranged on the base;
the tension sensor is suitable for detecting the tension of the weighing equipment of the automatic belt scale;
the tension signal detected by the tension sensor is amplified by the differential amplification circuit and then input to the tension microprocessor, and the tension microprocessor is suitable for sending the amplified tension signal to a server through the tension communication unit;
the vibration sensor node includes: the device comprises a vibration sensor, a programmable gain amplifier circuit, a filter circuit, an AD conversion module circuit, a first vibration microprocessor, a second vibration microprocessor and a vibration communication unit;
the vibration sensor is suitable for detecting vibration data of the automatic belt scale weighing equipment;
the first vibration microprocessor is suitable for controlling the amplification factor of the programmable gain amplifier circuit;
the vibration signal detected by the vibration sensor is amplified by the programmable gain amplifier circuit and then is input into the filter circuit to eliminate noise, the signal for eliminating noise is input into the AD conversion module circuit and then is input into the first vibration microprocessor, and the first vibration microprocessor sends the signal converted by the AD conversion module circuit to the second vibration microprocessor which sends the signal to the server through the vibration communication unit;
the vibration sensor node further includes: the storage module is electrically connected with the first vibration microprocessor;
the storage module is suitable for storing vibration data;
the humidity sensor node includes: the humidity sensor, the conditioning circuit, the humidity microprocessor and the humidity communication unit are arranged on the base;
the humidity sensor is suitable for detecting the humidity of the working environment of the automatic belt scale weighing equipment;
the humidity signal detected by the humidity sensor is transmitted to the humidity microprocessor after passing through the conditioning circuit, and the humidity microprocessor is suitable for sending the humidity signal to the server through the humidity communication unit;
the server is adapted to predict whether the automated belt scale weighing apparatus needs maintenance based on tension, humidity, vibration data and accumulated equipment usage time, i.e.
The server is suitable for acquiring tension change of unit weight according to tension and acquiring vibration intensity of set frequency according to vibration data;
the server is adapted to establish corresponding vectors from the data and historical data, i.e.
The server is adapted to establish a data vector and a coefficient vector;
the data includes: tension change of unit weight, vibration intensity of set frequency, humidity and accumulated use time of equipment;
the data vector is: x ═ x(1),x(2),x(3),x(4))；
Wherein x is(1)Change in tension per unit weight; x is the number of(2)A vibration intensity at a set frequency; x is the number of(3)Is humidity; x is the number of(4)Accumulating the service time for the equipment;
the historical data includes: tension change of historical unit weight, vibration intensity of set frequency, humidity and accumulated use time of equipment;
acquiring a tension change coefficient of unit weight, a vibration intensity coefficient and a humidity coefficient of set frequency and an accumulated use time coefficient of equipment according to historical data;
the coefficient vector is: w ═ w (w)(1),w(2),w(3),w(4))；
Wherein, w(1)Coefficient of tension change per unit weight; w is a(2)A vibration intensity coefficient for a set frequency; w is a(3)Is the coefficient of humidity; w is a(4)Accumulating the usage time coefficient for the device;
the server is adapted to construct a predictive maintenance model from the corresponding vectors and to obtain a solution to the predictive maintenance model, i.e.
s.t.yi(w·xi+b)≥1-ξi；
ξi≥0 i＝1,2,......,N；
Wherein C is a penalty coefficient; x is the number ofiA data vector of the ith training data; y isiIs xiWhen y is a class markiIs a-1 hour meterIndicating a failure of the weighing apparatus when yiWhen the value is 1, the weighing equipment is normal; n is the number of training data; xi is a relaxation variable; xiiRelaxation variables for the ith training data; b is an offset;
the solution for the predictive maintenance model is then: w*And b*；
α＝(α1,α2,α3,......αN,)T；
Wherein, TpThe time interval of signal sampling when vibration and humidity are sampled; x0The data vector of the automatic belt scale weighing equipment when leaving the factory is obtained; w*Is the solution of the coefficient vector; b*Is a solution to the bias; xcA data vector of the current automatic belt scale weighing equipment is obtained; alpha is a Lagrange multiplier vector set; alpha is alpha*For the set of solutions to the dual problem, αN *The Nth element that is a solution to the dual problem; alpha is alphaNIs the nth element of the lagrange multiplier vector; t is transposition; t iswAnd (4) sampling the vibration data according to a time interval under the condition of a calibration data point given by an expert.
2. The automated belt scale weighing apparatus predictive maintenance system of claim 1,
the server is adapted to predict whether the automated belt scale weighing apparatus requires maintenance based on a solution of the predictive maintenance model, i.e.
The server is adapted to obtain a maintenance urgency index, i.e.
Wherein p is a maintenance shear forcing index and p is greater than 0;
when p is larger, the automatic belt scale weighing equipment needs maintenance more;
the server is adapted to obtain an early warning threshold;
wherein S is an early warning threshold; gamma is an early warning threshold coefficient;
the server is suitable for predicting whether the automatic belt scale weighing equipment needs to be maintained or not according to the early warning threshold value;
when W is*xc+b*If the number is less than S, the server judges that the automatic belt scale weighing equipment needs maintenance and sends out early warning;
when the early warning of automatic belt weigher weighing equipment, if automatic belt weigher weighing equipment continues to operate, then the maximum working time of automatic belt weigher weighing equipment day is:
wherein, TnThe daily maximum working time of the automatic belt scale weighing equipment is recommended for delivery.
3. The automated belt scale weighing apparatus predictive maintenance system of claim 2,
the automated belt scale weighing apparatus predictive maintenance system further comprises: a gateway;
the gateway is suitable for receiving tension, humidity and vibration data sent by each node and then sending the data to the server through the gateway, namely
The tension communication unit is adapted to send tension to the gateway;
the vibration communication unit is suitable for sending vibration data to the gateway;
the humidity communication unit is adapted to send the humidity to the gateway.
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