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FOXBORO 0303458A脈沖輸入通道模塊

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FOXBORO 0303458A脈沖輸入通道模塊

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主營(yíng)DCS控制系統(tǒng)備件,PLC系統(tǒng)備件及機(jī)器人系統(tǒng)備件,
優(yōu)勢(shì)品牌:Allen Bradley、BentlyNevada、ABB、Emerson Ovation、Honeywell DCS、Rockwell ICS Triplex、FOXBORO、Schneider PLC、GE Fanuc、Motorola、HIMA、TRICONEX、Prosoft等各種進(jìn)口工業(yè)零部件

FOXBORO 0303458A脈沖輸入通道模塊 FOXBORO 0303458A脈沖輸入通道模塊 FOXBORO 0303458A脈沖輸入通道模塊
FOXBORO 0303458A脈沖輸入通道模塊
控制方法:鑄坯的正常切割長(zhǎng)度是由工藝決定并由過程計(jì)算機(jī)下達(dá)給火焰切割機(jī)的
PLC
并由其執(zhí)行。當(dāng)處于澆注末期時(shí),過程計(jì)算機(jī)可根據(jù)此時(shí)鑄流中的鑄坯長(zhǎng)度即時(shí)給出流的關(guān)斷提示。當(dāng)中包鋼水澆鑄完畢關(guān)閉塞棒或異鋼種連澆時(shí),過程計(jì)算機(jī)可根據(jù)此時(shí)鑄流中的鑄坯剩余長(zhǎng)度、目標(biāo)定尺長(zhǎng)度、大定尺長(zhǎng)度、小定尺長(zhǎng)度即時(shí)的計(jì)算出切割時(shí)的佳切割尺寸組合,以保證鑄坯的大的利用,盡可能地提高鋼水的收得率。
2.4.3質(zhì)量判定數(shù)學(xué)模型  質(zhì)量判定模型根據(jù)鑄流跟蹤中各分段所記錄的異常生產(chǎn)信息以及異常信息對(duì)板坯的影響程度對(duì)板坯質(zhì)量進(jìn)行分析、判定,評(píng)估出板坯的質(zhì)量等級(jí)。控制方法:首先根據(jù)在澆鑄過程中可能出現(xiàn)的各種事件對(duì)鑄坯組織性能造成的影響的程度將各個(gè)事件定量的劃為一個(gè)質(zhì)量等級(jí)數(shù)。在鑄坯形成的過程中,計(jì)算機(jī)將鑄坯劃分成若干一定長(zhǎng)度的“段”,結(jié)合鑄流跟蹤模型并對(duì)段進(jìn)行跟蹤,在每一段經(jīng)過實(shí)時(shí)過程參數(shù)監(jiān)控點(diǎn)時(shí)可以將參數(shù)與臨界值不斷地進(jìn)行比較并將異常事件參量作為鑄坯質(zhì)量的評(píng)估參數(shù)貯存起來。每段中可記錄四個(gè)嚴(yán)重事件,但用于判定的只取其優(yōu)先級(jí)別高的等級(jí)數(shù)。當(dāng)板坯切割完成后,將板坯對(duì)應(yīng)的段中的質(zhì)量信息(等級(jí)數(shù))提取出來,根據(jù)各段中有害事件的等級(jí)和在所有段中所占比例大小來確定該鑄坯質(zhì)量的優(yōu)劣和綜合質(zhì)量等級(jí)并進(jìn)行打印記錄,終判定為廢坯、保留坯(需進(jìn)一步評(píng)估或處理)、良坯。      影響鑄坯質(zhì)量的因素很多,例如:鋼水成份超標(biāo)、中包過熱度超標(biāo)、水口破損、冷卻水閥門故障引起冷卻異常、振動(dòng)系統(tǒng)異常等。      2.4.4拉速優(yōu)化模型      過程控制系統(tǒng)根據(jù)當(dāng)前鋼種成份(主要是碳含量)、寬度、厚度、中間包鋼水溫度、鋼水剩余量、下包預(yù)計(jì)到達(dá)時(shí)間和結(jié)晶器冷卻、二次冷卻等信息自動(dòng)計(jì)算出合適的當(dāng)前建議穩(wěn)定拉速和建議大拉速并顯示給操作工,以調(diào)整生產(chǎn)節(jié)奏或防止漏鋼或適當(dāng)加大速度提高生產(chǎn)效率。2.4.5液壓振動(dòng)模型 過程控制系統(tǒng)根據(jù)當(dāng)前澆鑄的鋼種選擇適合的振動(dòng)模式和工藝參數(shù),主要分為正弦(振頻、振幅)和非正弦(振頻、振幅和偏斜角)兩種形式,振頻和振幅可以預(yù)先設(shè)定,也可以隨拉速變化,或者由目標(biāo)速度負(fù)滑動(dòng)率、速度、振幅來決定振動(dòng)頻率。一般振動(dòng)振幅小于6mm,振動(dòng)頻率不超過380次/分,振動(dòng)起步頻率大于60次/分可以保證系統(tǒng)的穩(wěn)定并避免對(duì)振動(dòng)機(jī)械設(shè)備的磨損。同時(shí),模型自動(dòng)計(jì)算出振動(dòng)的工藝參數(shù):振動(dòng)正滑動(dòng)時(shí)間、負(fù)滑動(dòng)時(shí)間、負(fù)滑動(dòng)速度比、負(fù)滑動(dòng)率供操作人員和工藝人員實(shí)時(shí)監(jiān)控工藝效果,即時(shí)調(diào)整參數(shù)以達(dá)到好的脫模和減少振痕的目的。2.3.6動(dòng)態(tài)輕壓下模型 過程控制系統(tǒng)根據(jù)澆鑄過程中的鋼種、板坯厚度寬度、結(jié)晶器水水量、二冷水水量、氣量以及拉速、中間包鋼水溫度、生產(chǎn)環(huán)境參數(shù)等利用熱傳導(dǎo)理論推導(dǎo)計(jì)算出鑄坯在各輥?zhàn)幼鴺?biāo)處的坯殼厚度和坯殼表面溫度,從而找出板坯液芯凝固末端。根據(jù)不同鋼種收縮率不同,再經(jīng)過動(dòng)態(tài)輕壓下模型計(jì)算出在坯子凝固末端前某一范圍內(nèi)的輥縫壓下量設(shè)定值并傳給遠(yuǎn)程調(diào)輥縫系統(tǒng)執(zhí)行,一般輕壓下位置在鑄坯固相率60%~80%區(qū)間,單位輕壓下量不大于1.5mm/m。經(jīng)過輕壓下可以明顯改善板坯凝固末端內(nèi)部組織的偏析缺陷。      2.5生產(chǎn)報(bào)表      報(bào)表系統(tǒng)根據(jù)保存在數(shù)據(jù)庫(kù)的歷史生產(chǎn)信息,按客戶要求通過人機(jī)交互界面系統(tǒng)生成、打印報(bào)表。主要生產(chǎn)報(bào)表為以下4種: 1)澆次報(bào)表:匯總一個(gè)澆次中爐次數(shù)量、鋼水用量、板坯信息、介質(zhì)消耗量 等,為工廠的成本核算及產(chǎn)量核算提供依據(jù)。   2)爐次報(bào)表:一爐鋼水澆鑄過程收集的數(shù)據(jù):爐次鋼水重量、生產(chǎn)時(shí)間、鋼種成份、板坯情況等。1.2軟件結(jié)構(gòu)      軟件結(jié)構(gòu)采用服務(wù)器/客戶機(jī)結(jié)構(gòu),整個(gè)系統(tǒng)以數(shù)據(jù)庫(kù)為中心,應(yīng)用服務(wù)器中的通訊軟件從基礎(chǔ)自動(dòng)化系統(tǒng)采集現(xiàn)場(chǎng)實(shí)時(shí)數(shù)據(jù)并保存到數(shù)據(jù)庫(kù)服務(wù)器的ORACLE數(shù)據(jù)庫(kù)中,計(jì)算模型從數(shù)據(jù)庫(kù)提取數(shù)據(jù)經(jīng)過計(jì)算后將結(jié)果放回?cái)?shù)據(jù)庫(kù)中供客戶機(jī)監(jiān)控顯示或由通訊程序下載到基礎(chǔ)自動(dòng)化系統(tǒng)指導(dǎo)生產(chǎn)。      數(shù)據(jù)庫(kù)服務(wù)器裝有WINDOWS2003SERVER操作系統(tǒng),應(yīng)用軟件為ORACLE10g數(shù)據(jù)庫(kù)軟件,用于對(duì)所有實(shí)時(shí)數(shù)據(jù)和歷史數(shù)據(jù)的存儲(chǔ)、維護(hù)管理。 Control method: the normal cutting length of the casting blank is determined by the process and sent to the flame cutting machine by the process computer PLC And executed by it. When it is at the end of pouring, the process computer can give the prompt of cutting off the flow immediately according to the slab length in the current casting flow. When the stopper or continuous casting of different steel grades is closed after the pouring of molten steel in the tundish, the process computer can immediately calculate the optimal cutting size combination for cutting according to the remaining length of the billet, the target fixed length, the maximum fixed length, and the minimum fixed length in the casting stream, so as to ensure the maximum utilization of the billet and improve the yield of molten steel as much as possible.

2.4.3 Quality judgment mathematical model The quality judgment model analyzes and judges the slab quality according to the abnormal production information recorded in each segment of the casting stream tracking and the influence of the abnormal information on the slab, and evaluates the slab quality grade. Control method: firstly, each event is quantitatively classified into a quality grade according to the degree of influence of various events that may occur during the casting process on the structure and properties of the slab. In the process of slab formation, the computer divides the slab into several "segments" of a certain length, combines the casting flow tracking model and tracks the segments. When each segment passes the real-time process parameter monitoring point, the parameters can be continuously compared with the critical value, and the abnormal event parameters can be stored as the evaluation parameters of slab quality. Four most serious events can be recorded in each segment, but only the highest priority level is used for judgment. After the slab is cut, the quality information (grade number) in the corresponding section of the slab is extracted, and the quality and comprehensive quality grade of the slab are determined according to the grade of harmful events in each section and the proportion in all sections, and printed and recorded. Finally, the slab is determined as scrap, retained slab (to be further evaluated or treated), and good slab. There are many factors affecting the quality of casting billet, such as excessive molten steel composition, excessive tundish superheat, damaged nozzle, abnormal cooling caused by cooling water valve failure, abnormal vibration system, etc. 2.4.4 The process control system of casting speed optimization model automatically calculates the appropriate current recommended stable casting speed and recommended maximum casting speed according to the current steel composition (mainly carbon content), width, thickness, temperature of molten steel in the tundish, residual amount of molten steel, expected arrival time of ladle lowering, mold cooling, secondary cooling and other information, and displays them to the operator, Adjust the production rhythm or prevent breakout or increase the speed appropriately to improve production efficiency. 2.4.5 The hydraulic vibration model process control system selects the appropriate vibration mode and process parameters according to the current casting steel type, which are mainly divided into two forms: sinusoidal (vibration frequency, amplitude) and non sinusoidal (vibration frequency, amplitude and deflection angle). The vibration frequency and amplitude can be preset, or can change with the casting speed, or the vibration frequency can be determined by the negative slip rate, speed and amplitude of the target speed. Generally, the vibration amplitude is less than 6mm, the vibration frequency is not more than 380 times/minute, and the vibration starting frequency is more than 60 times/minute, which can ensure the stability of the system and avoid the wear of vibration machinery and equipment. At the same time, the model automatically calculates the vibration process parameters: vibration positive sliding time, negative sliding time, negative sliding speed ratio, and negative sliding rate for operators and technologists to monitor the process effect in real time, and adjust the parameters in time to achieve the best demoulding and reduce vibration marks. 2.3.6 The dynamic soft reduction model process control system deduces and calculates the shell thickness and shell surface temperature of the slab at each roller coordinate using the heat conduction theory according to the steel grade, slab thickness and width, mold water volume, secondary cooling water volume, air volume, casting speed, tundish steel temperature, production environment parameters, etc. during the casting process, so as to find out the solidification end of the slab liquid core. According to the different shrinkage rates of different steel grades, the set value of roll gap reduction within a certain range before the solidification end of the billet is calculated by the dynamic soft reduction model and transmitted to the remote roll gap adjustment system for execution. Generally, the soft reduction position is within the range of 60%~80% of the solid rate of the billet, and the unit soft reduction is not more than 1.5mm/m. After soft reduction, the segregation defect of the internal structure at the solidification end of the slab can be obviously improved. 2.5 The production report system generates and prints reports through the human-computer interaction interface system according to the historical production information saved in the database and customer requirements. The main production reports are as follows: 1) Casting report: summarize the quantity of heats, molten steel consumption, slab information, medium consumption, etc. in a casting to provide a basis for cost accounting and output accounting of the factory.
2) Heat report: the data collected in the process of one heat of molten steel casting: heat of molten steel weight, production time, steel composition, slab condition, etc. 1.2 Software structure The software structure adopts the server/client structure. The whole system is database centric. The communication software in the application server collects the on-site real-time data from the basic automation system and stores it in the ORACLE database of the database server, The calculation model extracts data from the database and puts the results back into the database after calculation for monitoring and display by the client or downloading the communication program to the basic automation system to guide production. The database server is equipped with WINDOWS2003SERVER operating system, and the application software is ORACLE10g database software, which is used for the storage, maintenance and management of all real-time data and historical data.